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Tech Guides - IoT and Hardware

25 Articles
article-image-hot-chips-31-ibm-power10-amds-ai-ambitions-intel-nnp-t-cerebras-largest-chip-with-1-2-trillion-transistors-and-more
Fatema Patrawala
23 Aug 2019
7 min read
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Hot Chips 31: IBM Power10, AMD’s AI ambitions, Intel NNP-T, Cerebras largest chip with 1.2 trillion transistors and more

Fatema Patrawala
23 Aug 2019
7 min read
Hot Chips 31, the premiere event for the biggest semiconductor vendors to highlight their latest architectural developments is held in August every year. The event this year was held at the Memorial Auditorium on the Stanford University Campus in California, from August 18-20, 2019. Since its inception it is co-sponsored by IEEE and ACM SIGARCH. Hot Chips is amazing for the level of depth it provides on the latest technology and the upcoming releases in the IoT, firmware and hardware space. This year the list of presentations for Hot Chips was almost overwhelming with a wide range of technical disclosures on the latest chip logic innovations. Almost all the major chip vendors and IP licensees involved in semiconductor logic designs took part: Intel, AMD, NVIDIA, Arm, Xilinx, IBM, were on the list. But companies like Google, Microsoft, Facebook and Amazon also took part. There are notable absences from the likes of Apple, who despite being on the Committee, last presented at the conference in 1994. Day 1 kicked off with tutorials and sponsor demos. On the cloud side, Amazon AWS covered the evolution of hypervisors and the AWS infrastructure. Microsoft described its acceleration strategy with FPGAs and ASICs, with details on Project Brainwave and Project Zipline. Google covered the architecture of Google Cloud with the TPU v3 chip.  And a 3-part RISC-V tutorial rounded off by afternoon, so the day was spent well with insights into the latest cloud infrastructure and processor architectures. The detailed talks were presented on Day 2 and Day 3, below are some of the important highlights of the event: IBM’s POWER10 Processor expected by 2021 IBM which creates families of processors to address different segments, with different models for tasks like scale-up, scale-out, and now NVLink deployments. The company is adding new custom models that use new acceleration and memory devices, and that was the focus of this year’s talk at Hot Chips. They also announced about POWER10 which is expected to come with these new enhancements in 2021, they additionally announced, core counts of POWER10 and process technology. IBM also spoke about focusing on developing diverse memory and accelerator solutions to differentiate its product stack with heterogeneous systems. IBM aims to reduce the number of PHYs on its chips, so now it has PCIe Gen 4 PHYs while the rest of the SERDES run with the company's own interfaces. This creates a flexible interface that can support many types of accelerators and protocols, like GPUs, ASICs, CAPI, NVLink, and OpenCAPI. AMD wants to become a significant player in Artificial Intelligence AMD does not have an artificial intelligence–focused chip. However, AMD CEO Lisa Su in a keynote address at Hot Chips 31 stated that the company is working toward becoming a more significant player in artificial intelligence. Lisa stated that the company had adopted a CPU/GPU/interconnect strategy to tap artificial intelligence and HPC opportunity. She said that AMD would use all its technology in the Frontier supercomputer. The company plans to fully optimize its EYPC CPU and Radeon Instinct GPU for supercomputing. It would further enhance the system’s performance with its Infinity Fabric and unlock performance with its ROCM (Radeon Open Compute) software tools. Unlike Intel and NVIDIA, AMD does not have a dedicated artificial intelligence chip or application-specific accelerators. Despite this, Su noted, “We’ll absolutely see AMD be a large player in AI.” AMD is considering whether to build a dedicated AI chip or not. This decision will depend on how artificial intelligence evolves. Lisa explained that companies have been improving their CPU (central processing unit) performance by leveraging various elements. These elements are process technology, die size, TDP (thermal design power), power management, microarchitecture, and compilers. Process technology is the biggest contributor, as it boosts performance by 40%. Increasing die size also boosts performance in the double digits, but it is not cost-effective. While AMD used microarchitecture to boost EPYC Rome server CPU IPC (instructions per cycle) by 15% in single-threaded and 23% in multi-threaded workloads. This IPC improvement is above the industry average IPC improvement of around 5%–8%. Intel’s Nervana NNP-T and Lakefield 3D Foveros hybrid processors Intel revealed fine-grained details about its much-anticipated Spring Crest Deep Learning Accelerators at Hot Chips 31. The Nervana Neural Network Processor for Training (NNP-T) comes with 24 processing cores and a new take on data movement that's powered by 32GB of HBM2 memory. The spacious 27 billion transistors are spread across a 688mm2 die. The NNP-T also incorporates leading-edge technology from Intel-rival TSMC. Intel Lakefield 3D Foveros Hybrid Processors Intel in another presentation talked about Lakefield 3D Foveros hybrid processors that are the first to come to market with Intel's new 3D chip-stacking technology. The current design consists of two dies. The lower die houses all of the typical southbridge features, like I/O connections, and is fabbed on the 22FFL process. The upper die is a 10nm CPU that features one large compute core and four smaller Atom-based 'efficiency' cores, similar to an ARM big.LITTLE processor. Intel calls this a "hybrid x86 architecture," and it could denote a fundamental shift in the company's strategy. Finally, the company stacks DRAM atop the 3D processor in a PoP (package-on-Package) implementation. Cerebras largest chip ever with 1.2 trillion transistors California artificial intelligence startup Cerebras Systems introduced its Cerebras Wafer Scale Engine (WSE), the world’s largest-ever chip built for neural network processing. Sean Lie the Co-Founder and Chief Hardware Architect at Cerebras Lie presented the gigantic chip ever at Hot Chips 31. The 16nm WSE is a 46,225 mm2 silicon chip which is slightly larger than a 9.7-inch iPad. It features 1.2 trillion transistors, 400,000 AI optimized cores, 18 Gigabytes of on-chip memory, 9 petabyte/s memory bandwidth, and 100 petabyte/s fabric bandwidth. It is 56.7 times larger than the largest Nvidia graphics processing unit, which accommodates 21.1 billion transistors on a 815 mm2 silicon base. NVIDIA’s multi-chip solution for deep neural networks accelerator NVIDIA which announced about designing a test multi-chip solution for DNN computations at a VLSI conference last year, the company explained chip technology at Hot Chips 31 this year. It is currently a test chip which involves a multi-chip DL inference. It is designed for CNNs and has a RISC-V chip controller. It has 36 small chips, 8 Vector MACs per PE, and each chip has 12 PEs and each package has 6x6 chips. Few other notable talks at Hot Chips 31 Microsoft unveiled its new product Hololens 2.0 silicone. It has a holographic processor and a custom silicone. The application processor runs the app, and the HPU modifies the rendered image and sends to the display. Facebook presented details on Zion, its next generation in-memory unified training platform. Zion which is designed for Facebook sparse workloads, has a unified BFLOAT 16 format with CPU and accelerators. Huawei spoke about its Da Vinci architecture, a single Ascend 310 which can deliver 16 TeraOPS of 8-bit integer performance, support real-time analytics across 16 channels of HD video, and consume less than 8W of power. Xiling Versal AI engine Xilinx, the manufacturer of FPGAs, announced its new Versal AI engine last year as a way of moving FPGAs into the AI domain. This year at Hot Chips they expanded on its technology and more. Ayar Labs, an optical chip making startup, showcased results of its work with DARPA (U.S. Department of Defense's Defense Advanced Research Projects Agency) and Intel on an FPGA chiplet integration platform. The final talk on Day 3 ended with a presentation by Habana, they discussed about an innovative approach to scaling AI Training systems with its GAUDI AI Processor. AMD competes with Intel by launching EPYC Rome, world’s first 7 nm chip for data centers, luring in Twitter and Google Apple advanced talks with Intel to buy its smartphone modem chip business for $1 billion, reports WSJ Alibaba’s chipmaker launches open source RISC-V based ‘XuanTie 910 processor’ for 5G, AI, IoT and self-driving applications
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Vincy Davis
26 Jun 2019
9 min read
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10+ reasons to love Raspberry Pi

Vincy Davis
26 Jun 2019
9 min read
It’s 2019 and unless you’ve been living under a rock, you know what a Raspberry Pi is. A series of credit-card-sized board computers, initially developed to promote computer science in schools, has now released its Raspberry Pi 4 Model B in the market yesterday. Read More: Raspberry Pi 4 is up for sale at $35, with 64-bit ARM core, up to 4GB memory, full-throughput gigabit Ethernet and more! Since its release in 2012, Raspberry Pi has had several iterations and variations. Today it has become a phenomenon, it’s the world's third best-selling, general-purpose computer. It's inside laptops, tablets, and robots. This year its offering students and young people an opportunity to conduct scientific investigations in space, by writing computer programs that run on Raspberry Pi computers aboard the International Space Station. Developers around the world are using different models of this technology to implement varied applications. What do you do with your Raspberry Pi? Following the release of Raspberry Pi 4, an interesting HN thread on applications of the Raspberry Pi exploded with over a thousand comments and over 1.5k votes. The original thread poster asked, “I have Raspberry Pi and I mainly use it for VPN and piHole. I’m curious if you have one, have you found it useful? What do you do with your Raspberry Pi?” Below are some select use cases from the thread. Innovative: Raspberry Pi Zero transformed a braille display into a full-feature Linux laptop A braille user transformed a braille display into a full-feature Linux laptop, using a Raspberry Pi Zero. The user used a braille display which featured a small compartment with micro-USB and converted it into a ARM-based, monitorless, Linux laptop with a keyboard and a braille display. It can be charged/powered via USB so it can also be run from a power bank or a solar charger, thus potentially being able to run for days, rather than just hours, without needing a standard wall-jack. This helped the user to save space, power and weight. Monitor Climate change effects Changes in climate have been affecting each and everyone of us, in some way or the other. Some developers are using Raspberry Pi innovatively to tackle these climatic changes. Monitoring inhouse CO2 levels A developer working with the IBM Watson Group states that he uses several Raspberry Pis to monitor CO2 levels in his house. Each Raspberry Pi has a CO2 sensor, with a Python script to retrieve data from sensor and upload it to a server, which is also a Raspberry Pi. Later, on detecting that his bedroom has high level of CO2, he improved ventilation and reduced the CO2 levels around. Measuring conditions of coral reefs Nemo Pi is a Nemo foundation’s technology, which works as an underground weather station. It uses Raspberry Pi computers to protect coral reefs from climate change by measuring temperature, visibility, pH levels, and the concentration of CO2 and nitrogen oxide at each anchor point. Checking weather updates remotely You can also use the Raspberry Pi for ‘Weather Monitoring’, to check the changes in the weather remotely using a smartphone. The main conditions in the weather monitor are the temperature, humidity, and the air quality. Raspberry Pi 3 model B, can be programmed such that it takes data from Arduino, and depending on the data acquired, the cameras are actuated. The Pi receives data from sensors and uploads it to the cloud so that appropriate action can be taken. Making Home Automation feasible Raspberry Pi has been designed to let you create whatever you can dream of, and of course developers are making full use of it. There are many instances of developers using Raspberry Pi to make their home automation more feasible. Automatic pet door drive A developer have used this technology to install a fire-protection-approved door drive for their pets. It is used along with another Raspberry Pi which analyzes a video stream and detects the pet. If the pet is in the frame for ‘n’ amount of time, a message is sent to the Pi connected to the door drive, which opens up slightly, to let the pet in. Home automation Raspberry Pi 3 model works with the Home Assistant with a Z-Wave USB Dongle, and provides climate, covers, lights, locks, sensors, switches, and thermostats information. There are many takers of the RaZberry card, which is a tiny daughter card that sits on top of the Raspberry PI GPIO connector. It is powered by the Raspberry PI board with 3.3 V and communicates using UART TTL signals. It supports home automation and is not only compatible with all models of Raspberry Pi, but also with all third party software. Watering a plant via a reddit bot! There’s another simple instance where a subreddit has control over the watering of a live plant. The Pi runs a reddit bot that reads the votes, and switch on the pump to water. It also collects data about sunlight, moisture, temp and humidity to help form the decision about watering. Build easy electronic projects Raspberry Pi can be used to learn coding and to build electronics projects, and for many of the things that your desktop PC does, like spreadsheets, word processing, and browsing the internet to learn programming and execute projects. Make a presentation Rob Reilly, an independent consultant states that he uses Raspberry Pi in his Steampunk conference badge while giving tech talks. He plugs it in the HDMI, powers up the badge and runs slides with a nano-keyboard/mousepad and LibreOffice. He says that this works great for him as it displays a promotional video on it's 3.5" touch-screen and runs on a cell phone power pack. Control a 3D printer, a camera or even IoT apps A user of Raspberry Pi states that he makes use of the Raspberry Pi 3 model to use OctoPrint.  It is an open source web interface for 3D printers which allows to control and monitor all aspects of printer and print jobs. A system architect says that he regularly uses Raspberry Pi for digital signage, controlled servos, and as cameras. Currently, he also uses a Pi Zero W model for a demo Azure IoT solutions. Raspberry Pi is also used as a networked LED marquee controller. Read More: Raspberry Pi Zero W: What you need to know and why it’s great FullPageOS is a Raspberry Pi distribution to display one webpage in full screen. It includes Chromium out of the box and the scripts necessary to load it at boot. This repository contains the source script to generate the distribution out of an existing Raspbian distro image. Also a developer, who’s also the Former VP of Engineering at Blekko Inc search engine states that he uses Raspberry Pi for several purposes such as running the waveforms live software from Digilent and hooks to an Analog Discovery on his workbench. He also uses Raspberry Pi for driving a display which showcases a dashboard of various things like Nagios alerts, data trends, etc. Read More: Intelligent mobile projects with TensorFlow: Build a basic Raspberry Pi robot that listens, moves, sees, and speaks [Tutorial] Enjoy Gaming with Raspberry Pi There are many Raspberry Pi-Exclusive Games, available for its users. Minecraft PE is one such game, which comes preinstalled with Raspbian. Most games designed to run natively on the Raspberry Pi are written in Python. Raspberry Pi is being used to stream PlayStation to backups over SMB by networking the onboard Ethernet port of the Pi, to allow access to a Samba Share service running on the Pi. It allows seamless playback of games with heavy Full Motion Video sequences. When an additional support for Xlink Kai is provided to play LAN enabled games over the Pi’s WiFi connection, it enables smooth connection for lag-free multiplayer on original hardware. A user on Hacker News comments that he uses RetroPie, which has a library of many interesting games. Loved not only by developers, but also by the general public These 35$ masterpieces of Raspberry Pi give big power in the hands of someone with little imagination and a spare of electronics. With its fast processing and better network connectivity, even beginners can use Raspberry Pi for practical purposes. A college student, on Hacker News claims that he uses a Raspberry Pi 3b+ model to automate his data entry job by using Python and Selenium, which is a portable framework for testing web applications and provides a playback tool for authoring functional tests. He says that since its automated, it allows him to take long coffee breaks and not worry about it, while travelling. Kevin Smith, the co-founder of Vault states that his office uses a Raspberry Pi and blockchain NFTs to control the coffee machine. An owner of the NFT, once authenticated, can select the coffee type on their phone which then signals the Raspberry Pi to make the particular coffee type, by jumping the contacts that was previously used to be pressed by the machine's buttons. Another interesting use of Raspberry Pi is by a user who used the Raspberry Pi technology to get real-time information from the local transit authority, and the GPS installed buses to help those stranded at the bus station. Raspberry Pi 3 models can also be installed in a Tesla car within the internal network as a bastion box, to run a software which provides interaction with the car’s entertainment system. Read More: Build your first Raspberry Pi project Last year, the Raspberry Pi Foundation launched a new device called the Raspberry Pi TV HAT, which lets you decode and stream live TV. It connects to the Raspberry Pi via a GPIO connector and has a port for a TV antenna connector. Tensorflow 1.9 has also announced that they will officially support Raspberry Pi, thus enabling users to try their hand on live machine learning projects. There’s no doubt that, with all its varied features and low priced computers, developers and the  general public have many opportunities to experiment with Raspberry Pi and get their work done. From students to international projects, Raspberry Pi is being used assuredly in many cases. You can now install Windows 10 on a Raspberry Pi 3 Raspberry Pi opens its first offline store in England Setting up a Raspberry Pi for a robot – Headless by Default [Tutorial]
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Guest Contributor
13 May 2019
6 min read
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How much does it cost to build an IoT app?

Guest Contributor
13 May 2019
6 min read
According to a Gartner study, the estimated approximate amount to be spent on the connected things (IoT related services) for the year 2017 was ($235 billion) and it is predicted to reach a level of 14.2 billion by the end of 2019. The number of connected devices across the globe will also be increased by around 10 billion by the end of the year 2020. Research by IDC (International Data Corporation) shows that market transformation due to IoT escalation has scaled up to approx 1.9 trillion in 2013 and will reach 7.1 trillion by the year 2020. These stats draw a clear picture that the Internet of Things is making businesses agile, fast, user-engaging and most importantly connected with each other. The areas where IoT is predicted to be used are exponentially growing. However, with the expansion comes with a burgeoning question “What is the cost of building an IoT Solution?” Before estimating the costs of developing an IoT app, you should have a clear answer to the following questions: What is the main idea or goal of your IoT app? Who will be the users of your upcoming IoT app? What benefits will you provide to the users through the app? What hardware are you going to use for the app development? What type of features will your IoT app have? What might be the possible challenges and issues of your IoT app? It’s important to answer these questions as more details you provide to your IoT development partner, the better your app result will be. Getting an insight into each IoT app development phase provides the developer with a clear picture of the future app. It also saves a lot of time by eliminating the chances of making unnecessary corrections. So, it’s essential to give significant consideration to the above-mentioned questions. Next, let's move to the various factors that help in estimating the cost of developing an IoT app. The time required to develop an IoT app Development phase eats most of the time when it comes to creating an IoT app for business purposes. The process starts with app information analysis and proceeds to prototype development and visual design creation. The phases include features and functionality research, UI/UX design, interface design, logo, and icon selection. Your IoT app development time also depends on the project size, use of new technologies and tools, uncertain integration requirements, a growing number of visual elements and complex UI and UX feature integration. Every aspect which consumes time leads an app towards cost increment. Thus, you can expect high-cost for your IoT app if you wish to incorporate all the above features in your connected environment. Integrating advanced features in your IoT app Often your app may require advanced feature integration such as Payment Gateway, Geo-location, Data Encryption, Third-party API Integration, All-across device synchronization, Auto-learning feed, CMS Integration, etc. Integrating advanced features like social media and geo-location functionality take much effort and time as compared to other simple features. This ultimately increases the app’s cost. You can hire programmers for integrating these advanced features. Generally, hourly rates of professional designers and programmers depend on the region the developers reside, such as: The cost in Eastern Europe is $30-50/hour The cost in Western Europe is $60-130/hour The cost in North America is $50-150/hour The cost in India is $20-50/hour Choose IoT developers accordingly by knowing the development cost of your region. Remember, the cost is just a rough idea and may vary with the app development requisites. The team required for building an IoT app Like any normal app, IoT app development also requires a team of diligent and skilled developers, who possess ample know-how of the latest technologies and development trends. Hiring experienced developers would unquestionably cost higher and lead your IoT app development process towards price expansion. Your IoT app development team (with cost) may consist of Front-end developer - $29.20 per hour Back-end developer - $29.59 per hour UI Designer - $41.93 per hour QA Engineer - $45 per hour Project Manager - $53.85 per hour Business Analyst - $39 per hour The cost mentioned above for each professional is gathered on an average basis. Calculating the total cost will give you the overall cost of IoT development. Don’t consider the aforementioned cost the final app investment as it may vary according to the project size, requisites, and other parameters. Post app development support and maintenance The development of IoT app doesn’t end at deployment, rather the real phase starts just after it. This is the post-production phase where the development company is supposed to provide after deployment support for the delivered project. If you have hired developers for your IoT app development make sure that they are ready to offer you the best post-deployment support for your app. It can be related to adding new features to the app or resolving the issues found during app performance. Also, make sure that they provide your app with a clear code so that anyone with the same skills can easily interpret and modify it to make future changes. Cost based on the size of project or app Generally, projects are categorized based on three sizes: small, middle and large. As obvious, a small project or less complicated app costs less than a complex one. For example, the development of IoT applications for modern home appliances like a refrigerator or home theatre is much easy and cost-effective. On the contrary, if you wish to develop a self-driven vehicle, it would be an expensive plan to proceed. Similarly, developing IoT application for ECG monitors incurs less cost approx 3000$ – 4000$ whereas the IoT system created for fitness machines requires around 30,000$ – 35,000$. This might not be the final cost of apps and you may also discover some hidden costs later on. Conclusion It is recommended to take the assistance of an IoT app development company, which has talented professionals to establish an in-depth IoT app development cost structure. Remember, the more complex your app is the more cost it will incur. So make a clear plan by understanding the needs of your customers while also thinking about the type of features your IoT app will have. About The Author Tom Hardy is a senior technology developer in Sparx IT Solutions. He always stays updated with the growing technology trends and also makes others apprised through his detailed and informative technology write-ups.
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Guest Contributor
15 Jan 2019
5 min read
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How are Mobile apps transforming the healthcare industry?

Guest Contributor
15 Jan 2019
5 min read
Mobile App Development has taken over and completely re-written the healthcare industry. According to Healthcare Mobility Solutions reports, the Mobile healthcare application market is expected to be worth more than $84 million by the year 2020. These mobile applications are not just limited to use by patients but are also massively used by doctors and nurses. As technology evolves, it simultaneously opens up the possibility of being used in multiple ways. Similar has been the journey of healthcare mobile app development that has originated from the latest trends in technology and has made its way to being an industry in itself. The technological trends that have helped build mobile apps for the healthcare industry are Blockchain You probably know blockchain technology, thanks to all the cryptocurrency rage in recent years. The blockchain is basically a peer-to-peer database that keeps a verified record of all transactions, or any other information that one needs to track and have it accessible to a large community. The healthcare industry can use a technology that allows it to record the medical history of patients, and store it electronically, in an encrypted form, that cannot be altered or hacked into. Blockchain succeeds where a lot of health applications fail, in the secure retention of patient data. The Internet of Things The Internet of Things (IoT) is all about connectivity. It is a way of interconnecting electronic devices, software, applications, etc., to ensure easy access and management across platforms. The loT will assist medical professionals in gaining access to valuable patient information so that doctors can monitor the progress of their patients. This makes treatment of the patient easier, and more closely monitored, as doctors can access the patient’s current profile anywhere and suggest treatment, medicine, and dosages. Augmented Reality From the video gaming industry, Augmented Reality has made its way to the medical sector. AR refers to the creation of an interactive experience of a real-world environment through superimposition of computer-generated perceptual information. AR is increasingly used to develop mobile applications that can be used by doctors and surgeons as a training experience. It stimulates a real-world experience of diagnosis and surgery, and by doing so, enhances the knowledge and its practical application that all doctors must necessarily possess. This form of training is not limited in nature, and can, therefore, simultaneously train a large number of medical practitioners. Big Data Analytics Big Data has the potential to provide comprehensive statistical information, only accessed and processed through sophisticated software. Big Data Analytics becomes extremely useful when it comes to managing the hospital’s resources and records in an efficient manner. Aside from this, it is used in the development of mobile applications that store all patient data, thus again, eliminating the need for excessive paperwork. This allows medical professionals to focus more on attending and treating the patients, rather than managing database. These technological trends have led to the development of a diverse variety of mobile applications to be used for multiple purposes in the healthcare industry. Listed below are the benefits of the mobile apps deploying these technological trends, for the professionals and the patients alike. Telemedicine Mobile applications can potentially play a crucial role in making medical services available to the masses. An example is an on-call physician on telemedicine duty. A mobile application will allow the physician to be available for a patient consult without having to operate via  PC. This will make the doctors more accessible and will bring quality treatment to the patients quickly. Enhanced Patient Engagement There are mobile applications that place all patient data – from past medical history to performance metrics, patient feedback, changes in the treatment patterns and schedules, at the push of a button on the smartphone application for the medical professional to consider and make a decision on the go. Since all data is recorded in real-time, it makes it easy for doctors to change shifts without having to explain to the next doctor the condition of the patient in person. The mobile application has all the data the supervisors or nurses need. Easy Access to Medical Facilities There are a number of mobile applications that allow patients to search for medical professionals in their area, read their reviews and feedback by other patients, and then make an online appointment if they are satisfied with the information that they find. Apart from these, they can also download and store their medical lab reports, and order medicines online at affordable prices. Easy Payment of Bills Like in every other sector, mobile applications in healthcare have made monetary transactions extremely easy. Patients or their family members, no longer need to spend hours waiting in the line to pay the bills. They can instantly pick a payment plan and pay bills immediately or add reminders to be notified when a bill is due. Therefore, it can be safely said that the revolution that the healthcare industry is undergoing and has worked in the favor of all the parties involved – Medical Professionals, Patients, Hospital Management and the Mobile App Developers. Author's Bio Ritesh Patil is the co-founder of Mobisoft Infotech that helps startups and enterprises in mobile technology. He’s an avid blogger and writes on mobile application development. He has developed innovative mobile applications across various fields such as Finance, Insurance, Health, Entertainment, Productivity, Social Causes, Education and many more and has bagged numerous awards for the same. Social Media – Twitter, LinkedIn Healthcare Analytics: Logistic Regression to Reduce Patient Readmissions How IBM Watson is paving the road for Healthcare 3.0 7 Popular Applications of Artificial Intelligence in Healthcare
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Prasad Ramesh
31 Dec 2018
10 min read
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How to choose components to build a basic robot 

Prasad Ramesh
31 Dec 2018
10 min read
This post will show you how to choose a robot chassis kit with wheels and motors, a motor controller, and some power for the robot, talking through the trade-offs and things to avoid. This article is an excerpt from a book written by Danny Staple titled Learn Robotics Programming. In this book, you will learn you'll gain experience of building a next-generation collaboration robot Choosing a robot chassis kit The chassis, like the controller, is a fundamental decision when making a robot. Although these can be self-made using 3D printing or toy hacking, the most simple place to start is with a robot chassis kit. These kits contain sets of parts to start off your robot build. A chassis can be changed, but it would mean rebuilding the robot. The internet has plenty of robot chassis kits around. Too many, so how do you choose one? Size Getting the size for a robot right matters too. Take a look at the following photos: Chassis 1 is 11 cm in and just about fits a controller in it, but is too tiny. This will make it hard to build your robot. Squeezing the controller, power, and all the sensors into this small space would need skill and experience beyond the scope of a first robot build. Chassis 2 is Armbot. This large robot is 33 cm by 30 cm, with an arm reach of another 300 mm. It needs eight AA batteries, big motors, and a big controller. These add to the expense and may cause issues around power handling for a new builder. It has lots of space, but issues around weight and rigidity. Armbot is one of my most expensive robots, excluding the cost of the arm! Chassis 3 in the preceding image will fit the Pi, batteries, and sensor, but without being large and bulky. It is around the right dimensions, being between 15-20 cm long and 10-15 cm wide. Those that have split levels might be great for this, but only one or two levels, as three or four will make a robot top heavy and may cause it to topple. This has enough space and is relatively easy to build. Wheel count Some robot chassis kits have elaborate movement methods, legs, tank tracks, and tri-star wheels, to name a few. While these are fun and I encourage experimenting with them, this is not the place to start at. So, I recommend a thoroughly sensible, if basic, wheels on motors version. There are kits with four-wheel drive and six-wheel drive. These can be quite powerful and will require larger motor controllers. They may also chew through batteries, and you are increasing the likelihood of overloading something. This also makes for trickier wiring, as seen in the following: Two-wheel drive is the simplest to wire in. It usually requires a third wheel for balance. This can be a castor wheel, roller ball, or just a Teflon sled for tiny robots. Two wheels are also the easiest to steer, avoiding some friction issues seen with robots using four or more wheels. Two wheels won't have the pulling power of four or six-wheel drive, but they are simple and will work. They are also less expensive: Wheels and motors A kit for a beginner should come with the wheels and the motors. The wheels should have simple non-pneumatic rubber tires. The most obvious style for inexpensive robots is shown in the following photo. There are many kits with these in them: The kit should also come with two motors, one for each wheel, and include the screws or parts to mount them onto the chassis. I recommend DC Gear motors, as the gearing will keep the speed usable while increasing the mechanical pushing power the robot has. Importantly, the motors should have the wires connected, like the first motor in the following photo: It is tricky to solder or attach these wires to the small tags on motors, and poorly attached ones do have a frustrating habit of coming off. The kits you will want to start with have these wires attached, as can be seen in the following: Another point to note is that where the motors are mounted, the kits should have some encoder wheels, and a slot to read them through. The encoder wheels are also known as odometry, tacho, or tachometer wheels. Simplicity You don't want to use a complex or hard-to-assemble kit for your first robot build. I've repeated this throughout with two-wheel drive, two motors with the wires soldered on and steering clear of large robots, or unusual and interesting locomotion systems, not because they are flawed, but because it's better to start simple. There is a limit to this, a robot kit that is a fully built and enclosed robot leaves little room for learning or experimentation and would actually require toy hacking skills to customize. Cost Related to simplicity is cost. Robot chassis kits can be brought from around $15, up to thousands of dollars. Larger and more complex robots tend to be far more costly. Here, I am aiming to keep to the less costly options or at least show where they are possible. Conclusion So, now you can choose a chassis kit, with two wheels and a castor, two motors with wires soldered on them, slots, and encoder wheels. These are not expensive, and widely available on popular internet shopping sites as "Smart Car Chassis," with terms like "2WD": The kit I'm working with looks like the preceding photo when assembled without the Raspberry Pi. Choosing a motor controller The next important part you'll need is a motor controller. Much like the motors, there are a number of trade-offs and considerations before buying one. Integration level Motor controllers can be as simple as motor power control driven from GPIO pins directly, such as the L298. This is the cheapest solution: a generic L298N motor controller can be connected to some of the IO pins on the Raspberry Pi. These are reasonably robust and have been easily available for a long time. They are flexible, but using parts like this will take up more space and need to be wired point to point, adding complexity to the build: Others are as complex as whole IO controller boards, many of which hide their own controller similar to an Arduino, along with motor control chips. Although the cheapest and most flexible ways are the most basic controllers, those with higher integration will reduce size, keep the pin usage count low (handy when you are connecting a lot to the robot), and may simplify your robot build. They often come integrated with a power supply too. Motor controllers can be bought as fully integrated Raspberry Pi hats, boards designed to fit exactly on top of a Raspberry Pi. These tend to have a high level of integration, as discussed before, but may come at the cost of flexibility, especially if you plan to use other accessories. Pin usage When buying a motor controller in Raspberry Pi hat form, pin usage is important. If we intend to use microphones (PCM/I2S), servo motors, and I2c and SPI devices with this robot, having boards that make use of these pins is less than ideal. Simply being plugged into pins doesn't mean they are all used, so only a subset of the pins is usually actually connected on a hat. To get an idea of how pins in different boards interact on the Raspberry Pi, take a look at https://pinout.xyz , which lets you select Raspberry Pi boards and see the pin configuration for them. Controllers that use the I2C or serial bus are great because they make efficient use of pins and that bus can be shared. At the time of writing, PiConZero, the Stepper Motor Hat, and ZeroBorg all use I2C pins. The Full Function Stepper Motor Hat is able to control DC motors and servo motors, is cheap, and is widely available. It also has the pins available straight through on the top and an I2C connector on the side. It's designed to work with other hats and allow more expansion. Size The choice of this depends on the chassis, specifically the size of the motors you have. In simple terms, the larger your chassis, the larger a controller you will need. The power handling capacity of a motor controller is specified in amps. For a robot like the The Robot Kit I'm Using image, around 1 to 1.5 amps per channel is good. The consequence of too low a rating can be disaster, resulting in a robot that barely moves, while the components cook themselves or violently go bang. Too large a controller has consequences for space, weight, and cost: The level of integration can also contribute to size. A tiny board that stacks on a Pi would take up less space than separate boards. Related to size is if the board keeps the camera port on the Raspberry Pi accessible. Soldering As you choose boards for a robot, you will note that some come as kits themselves, requiring parts to be soldered on. If you are already experienced with this, it may be an option. For experienced builders, this becomes a small cost in time depending on the complexity of the soldering. A small header is going to be a very quick and easy job, and a board that comes as a bag of components with a bare board will be a chunk of an evening. Here, I will recommend components that require the least soldering. Connectors Closely related to soldering are the connectors for the motors and batteries. I tend to prefer the screw type connectors. Other types may require matching motors or crimping skills: Conclusion Our robot is space constrained; for this reason, we will be looking at the Raspberry Pi hat type form factor. We are also looking to keep the number of pins it binds to really low. An I2C-based hat will let us do this. The Full Function Stepper Motor Hat (also known as the Full Function Robot Expansion Board) gets us access to all the Pi pins while being a powerful motor controller: It's available in most countries, has space for the ribbon for the camera, and controls servo motors. I recommend the 4tronix PiConZero hat, or assembling a stack of PiBorg hats. These may be harder to source outside of the UK. The reader will need to adapt the code, and consider a tiny shim to retain access to the GPIO pins if using a different board. In this article, we learned about selecting the parts needed to build a basic robot. We looked at the size, wheel, cost, and connectors for the robot chassis and a controller. To learn more about robotics and build your own robot check out this book Learn Robotics Programming. Real-time motion planning for robots made faster and efficient with RapidPlan processor Boston Dynamics adds military-grade mortor (parkour) skills to its popular humanoid Atlas Robot Sex robots, artificial intelligence, and ethics: How desire shapes and is shaped by algorithms
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Savia Lobo
31 Oct 2018
3 min read
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Automation and Robots - Trick or Treat?

Savia Lobo
31 Oct 2018
3 min read
Advancements in AI are on a path of reinventing the way organizations work. Last year, we wrote about RPA, which made front-end manual jobs redundant. This year, we have actual robots on the field. Last month, iRobot, the intelligent robot making company revealed its latest robot, Roomba i7+, that maps and stores your house and also empties the trash automatically. Last week, Google announced its plans to launch a ‘Cloud Robotics platform’ for developers in 2019, which will encourage efficient robotic automation in highly dynamic environments. Earlier this month, Amazon announced that it is opening a chain of 3,000 cashier-less stores across the US by 2021. And most recently, Walmart also announced that it is going to launch a cashierless store next year. The terms ‘Automation’ and ‘Robotics’ sometimes have a crossover, as Robots can be used to automate physical tasks while many types of automation have nothing to do with physical robots. The emergence of AI robots will reduce the need for a huge human workforce, boost the productivity of organizations and reduce their time to market. For example, customer service and other front-end jobs can function 24*7*365 without an uninterrupted service. Within industrial automation, robots can automate time-consuming physical processes. Collaborative robots will carry out a task in the same way a human would, albeit more efficiently! The positives aside, AI there is a danger of it getting out of control as machines can go rogue without humans in the loop. That is why members of European Parliament (MEPs) passed a resolution recently on banning autonomous weapon systems. They emphasized that weapons like these, without proper human control over selecting and attacking targets are a disaster waiting to happen. At the more mundane end of the social spectrum, the dangers of automation are still very real. Robots are expected to significantly replace a lot of human labor. For instance, as per the World Economic Forum survey, in 5 years, machines will do half of our job tasks of today as 1 in 2 employees would need reskilling/upskilling. Another study by renowned economist Andy Haldane, The Bank of England’s chief economist says 15 million jobs in Britain at stake with Artificial Intelligence robots set to replace humans at workforce. As of now, having AI for organizations is a treat due to the different advantages they provide over humans. Although it will replace jobs, people can upskill their knowledge to continue thriving in the automation augmented future. Four interesting Amazon patents in 2018 that use machine learning, AR, and robotics How Rolls Royce is applying AI and robotics for smart engine maintenance Home Assistant: an open source Python home automation hub to rule all things smart
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Vijin Boricha
06 Jul 2018
6 min read
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Amazon Echo vs Google Home: Next-gen IoT war

Vijin Boricha
06 Jul 2018
6 min read
IoT has been around for a while now and big players like Google, Apple and Amazon have been creating buzz around smart devices over past couple of years. But 2018 is seeing a particular interest in smart speakers. That’s no surprise after Amazon succeeding with Echo it was obvious that other market leaders would love to compete in this area. Speaking about competition, Google recently revealed impressive set of enhancements to their not so old Google Home at Google I/O 2018. Like Amazon Echo, Google Home has entered the arena where users can interact with Home to play music, get personal assistance, and control their smart home. With Google being backed with their omnipresent search engine, Echo’s place of staying on top looks a little dicey. With that being said, let's get into the crux of the discussion keeping in mind three major components: Entertainment Personal assistant Smart home controller Entertainment The ideal purpose of a speaker is to entertain you with music but here your smart speaker can interact with you and play your favourite tracks. So, if you are at a moderate distance from your device all you have to do is wake the Echo with the command “Alexa” and Google Home with “Okay Google”. Don’t close your options here as both devices provide users with alternative commands such as the Echo wakes up with "Echo," "Amazon" or "Computer" and Home with "Hey Google”. Both these devices do a fair job of hearing users as they are always listening and their built-in microphone can listen to users over moderate background disturbance. These devices offer almost similar means of connection where your Echo can be plugged in to your existing home system while Home is capable of controlling any Google Cast-enabled speaker. When it comes to connecting these devices to your TV, Home does the job well by partially controlling a CEC (Consumer Electronics Control) supported television. On the other hand, Echo needs to be integrated with Fire TV in order to control your TV. With this you must have already guessed the winner but this does not end here, Google Home has a upper hand when it comes to connecting to multiple speakers to play a single song. Amazon Echo being more than a year older still misses this feature. Personal assistant Considering the variety of personal services Google offers (Google calendar, GTasks, and Google Maps) you must be expecting a straight win for Home here as well. However, Echo hasn’t stayed behind in this race. Echo uses Alexa as its digital assistant whereas Home uses the Google assistant, the digital assistant that is shipped with other Google products such as Pixel, to respond to voice commands. So, if you ask Google Home Who is Harry Potter?, you will get a definite answer from Home. You can follow that question with Which other movie is he associated with?, Home will again provide you a definite answer as it inferred the ‘he’ you referred to is actor Daniel Radcliffe. Similarly, Echo kept up with its standards when Alexa is asked about the weather. Then, when asked How about Thursday?, the response received is accurate despite the word ‘weather’ not being used in the follow-up question. Surprisingly Google falls short when it comes to updating personal tasks. The Echo can set reminders and stack-up a to-do list which the Google Home still cannot. But it would just be a matter of time to see these features added in Google Home. When it comes to assisting a group of people, Google Home supports upto 6 multiple users and when trained is capable of recognizing family member’s voice as long as they don’t sound similar. So, if one of the family members asks for a traffic or calendar update Home will customize the response depending on which member has asked for an update. Unfortunately, Echo lacks this capability. Google Home is still in its initial stages of enhancing its functionalities but already seems to be superior. Apart from a few, Home shares a lot of capabilities that are on Echo and in addition it supports recognizing family members and responding accordingly, so Google steals the show here as well. Smart Home Controller Another major functionality of a smart speaker is controlling your smart home. Both of these devices have displayed versatile functionalities but the winner in this area is a total surprise. Although Echo has a 2 year head start in this market Google Home hasn’t been that far behind in the race. Google has managed to integrate better with IFTTT (If This Then That) than that of Echo. This integration helps in crafting customizable commands. In a nutshell Home has more command options than Echo. So if a bulb is called “desk lamp” in the Philips app, Alexa will not respond to anything other than “desk lamp”. This comes with an additional support twist where you can group all lights and command Alexa to turn on/off all lights and the job’s done. The downside here is that without this grouping you would have to control your appliances with specific names. Well, with Google Home that’s not the case. You can assign a nickname to your home appliance and it would follow your orders. So while you must group your appliances on Echo, Google Assistant automatically groups a particular category of smart appliances helping you refer to it with your choice of command. Although Google Home has a upper hand in customizing commands, Echo is a much better device in terms of home automation control as it supports a vast variety of home appliances unlike Home. So, this time the winner is Amazon Echo. It is kind of difficult to make a clear choice as each of these have their advantages over disadvantages. If home automation is something that matters the most to you, Amazon Echo would be an apt choice. On the other hand, if personal assistant and music is all that your looking for Google Home fits perfectly. So, what are you waiting for, say the command and get things done for you. Related Links Windows 10 IoT Core: What you need to know How to build an Arduino based ‘follow me’ drone ROS Melodic Morenia released
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Vijin Boricha
29 Jun 2018
5 min read
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5 DIY IoT projects you can build under $50

Vijin Boricha
29 Jun 2018
5 min read
Lately, IoT is beginning to play an integral part in various industries, be it at the consumer-level, or at the enterprise side of it. With a lot of big players like Apple, Microsoft, Amazon, and Google entering this market, IoT adoption has scaled tremendously. It is said to have jumped from a hobbyist level to an industry infrastructure where everything functions on smart devices, that can talk. The bulk release of popular IoT products prove that this market is getting bigger and a lot of individuals have been amazed with home automation products such as Amazon Alexa, Apple Homepod, Google Home and others. These devices are one of the most sought-after things for hobbyist and enthusiasts who are interested to do simple automation with sensors. Following are 5 IoT projects ideas that you can build without a hole in the pocket. To learn how to actually build similar kind of projects, check out our books; Internet of Things with Raspberry Pi 3 Smart Internet of Things Projects Raspberry Pi 3 Home Automation Projects Weather control station This project will not only help you measure the room temperature but will also help you measure the altitude and the pressure in the room. For this project you will need the Adafruit Starter Pack for Windows 10 IoT Core on the latest Raspberry Pi kit. Along with the Raspberry Pi Kit you will also be using other sensors that read temperature, pressure, and altitude. To make your weather station advanced, you can connect the device to your cloud account to store the weather data. Hardware Raspberry Pi 2 or 3 Breadboard Adafruit BMP280 Barometric Pressure & Altitude Sensor Software Windows 10 IoT Core Approximate total cost Less than $60 Facial Recognition Door Self-built home security projects are some of the most popular DIY projects because they can be cheaper and simple compared to bulky professional installations. Here's a project that controls entry access using facial recognition, thanks to Microsoft Project Oxford. This project from Mazudo, based on Raspberry Pi and Windows IoT, is posted on Hackster.io. This is a handy project for DIY enthusiasts who want to build a quick security lock for their homes. Hardware Raspberry Pi 3 Breadboard USB camera Relay switch Speaker Software Windows 10 IoT Core Approximate total cost Less than $50 Your very own Alexa Echo Alexa Echo has always been a handy device, which can take notes, schedule reminders for your appointments, and play podcasts for you. Brilliant, isn’t it?  You can build a fully functional customized Alexa Echo with all the features of Alexa, apart from accessing official music servers like Amazon prime. It will also have an integration with recently included third party apps like todoist and Any.do. This DIY Echo can also be connected to your cell phone devices to manage notifications when the timer goes off, and so on. Only one thing that your DIY will be missing is the ability to function as a bluetooth speaker. Hardware Raspberry Pi 3 Breadboard USB speaker and mic Software Raspbian Approximate total cost Less than $50 Pet Feeder You surely don’t want your pet to starve when you’re away, do you? This customized pet feeder is controlled via the internet; set timings and feed your pet automatically later. These pet feeders are directly connected to WiFi using ESP8266 chip. We can easily add features like controlling the device using cell phone and making dashboards using Freeboard. This project can be later upgraded or rightly reprogrammed to fill your snack bowl at regular intervals as well. Hardware Arduino PIR motion sensor ESP8266 ESP-01 Software Arduino IDE ESP8266Flasher.exe Approximate total cost Less than $40 Video Surveillance Robot Video surveillance is a process of monitoring a scenario, person or an environment as a whole. A video surveillance robot can capture the activities happening in the surrounding where it is deployed and can be controlled using a GUI Interface. For further enhancements, you can even connect your device to the cloud and save the recorded data there. Hardware Raspberry Pi ARM Cortex- A7 CPU L293 motor driver Software Raspbian Approximate total cost Less than $50 These are few economical yet highly useful Internet of Things projects, which can be leveraged to improve your daily activities. Still not convinced?. Think of it this way. Buying the microchip board is a one time investment as it can be reused in separate projects. The sensors and other peripherals aren’t that expensive. You might say, it’s just way easier to buy an IoT device. I would argue that, buying an IoT device is not as satisfying as building one for the same purpose. In the end, there are multiple advantages of building one as you can brag about it to your friends and most importantly include it in your resume to give you that edge over others in an interview. Cognitive IoT: How Artificial Intelligence is remoulding Industrial and Consumer IoT Windows 10 IoT Core: What you need to know 5 reasons to choose AWS IoT Core for your next IoT project  
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Vijin Boricha
17 May 2018
5 min read
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Tips and tricks for troubleshooting and flying drones safely

Vijin Boricha
17 May 2018
5 min read
Your drone may have some problems when you fly it regularly or if you have just started piloting a drone. This can be because of maintenance or accidents. So, we need to troubleshoot and fly our drone safely. In this article, we will look at a few common troubleshooting drone tips. This is an excerpt from Building Smart Drones with ESP8266 and Arduino written by Syed Omar Faruk Towaha.  1. My drone tries to flip or flip when I turn it on This problem may occur for several reasons. Check if you calibrated your ESCs. Are your propellers balanced? Have you configured the radio properly? Are your ArduPilot's sensors working properly? Have you checked all the wire connection? Have you calibrated the drone frame? Have you added the wrong propellers to the wrong motors (for example, clockwise propellers to anticlockwise motors)? I hope you can solve the problem now. 2. My motors spin but the drone does not fly or take off This happens because the motors are not giving enough thrust to take off the drone. From the parameter list of the Mission Planner, change THR_MAX . Make sure it is in between 800 and 1000. If THR_MAX is 800 and still the drone does not take off, change the parameter to above 800 and try flying again. 3. My drone moves in any direction The drone moves in any direction even though the stick of the transmitter is cantered. To solve the problem, you must match the RC channel's 1 and 2 values to the PWM values displayed on the Mission Planner. If they are not the same, this error will happen. To match them, open your Mission Planner, connect it via telemetry, go to the Advanced Parameter List, and change HS1_TRIM and HS2_TRIM. With the roll and pitch stick cantered, the RC1 channel and RC2 channel should be the same as the values you wrote for the HS1_TRIM and HS2_TRIM parameters. If the values are different, then calibrate your radio. The HS1 trim value must match the live stick cantered roll value, and the HS2 trim value must match the pitch stick cantered value. You must not use the radio trim for yaw. Make sure the center of gravity of the copter is dead center. 4. When I pitch or roll, the drone yaws This can happen for several reasons. For the brushless AC motors, you need to swap any two of the three wires connected to the ESC. This will change the motor spinning direction. For the brushless DC motors, you need to check if the propellers are mounted properly because the brushless DC motors do not move in the wrong directions unless the connection is faulty. Also, check that the drone's booms are not twisted. Calibrating the compass and magnetometer will also help if there is no hardware problem. 5. It faces GPS lost communication This happens because of a bad GPS signal. You can do one thing before launching the drone. You need to find a spot where the GPS signal is strong so that it can be set to return to home or return to launch if the radio communication is lost. Before flying the drone, you may disarm the drone for a couple of minutes in a strong GPS signal. 6. It shows radio system failed To solve this issue, we can use the radio amplifier. Using the radio amplifier can increase the signal strength. You can have radio failure when there is a minor block in between the drone and the receiver. 7. My drone's battery life is too short When a drone is not used, we should keep the battery stored at room temperature with low humidity. High temperature and moisture will cause the battery to damage the chemical elements inside the battery cells. This will result in a shorter battery life. For the LiPo battery, I would suggest using a balance charger. 8. Diagnosing drone problems using logs For our ArduPilot, we used telemetry to communicate the drone to our Mission Planner. So, after the flight, we can analyze the telemetry logs. The telemetry logs are known as tlogs. There is Sik radio telemetry, Bluetooth telemetry, XBee, and so on. Before going any further, let's see where we can find the data files and how we can download them: In the home screen, you will find the telemetry logs below the Flight Data panel. From there you can choose the graph type after loading the log. When you load the logs, you will be redirected to a folder where the tlogs are situated. Click any of them to load. You can sort them by time so that you can be sure which data or log you need to analyze. You can also export your tlog data to a KML file for further analysis. You can also see the 3D data of the flight path from the tlog files: Open the Mission Planner's flight data screen. Click on the Telemetry Log tab and click on the button marked Tlog>KML or Graph. A new window will appear. Click on the Create KML + GPX button. A .kmz and .kml file will be created where the .tlog files are saved. In Google Earth, just drag and drop the .kmz file and you will see the 3D flight path. You can see the graphs of the tlog files by clicking Graph Log on the screen after the Togl>KMs or Graph button has been clicked. From there you need to select the flight tlog and a Graph this screen will appear. Check the necessary data from the screen and you will see the graphs. We have learned to diagnose drone issues through logs and have also learned to analyze graphs depending on data and troubleshooting flight problem. Get to know more about radio control calibration problems and before/after flight safety from this book Building Smart Drones with ESP8266 and Arduino. Drones: Everything you ever wanted to know!    
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Savia Lobo
15 May 2018
8 min read
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Cognitive IoT: How Artificial Intelligence is remoulding Industrial and Consumer IoT

Savia Lobo
15 May 2018
8 min read
Internet of Things (IoT) has gained a huge traction due to the ability to gather data from sensors embedded within a variety of IoT devices including Close-circuit cameras, vehicles, smart homes, smart appliances, and many more. Think of IoT as a network of devices which gathers raw and real-time data, analyzes them, and provides desired outputs that benefit the users. But what after the data is analyzed? What is done with the analyzed report? The data has to be acted upon. Here, Artificial Intelligence can do the needful. AI can get hold of all that data crunched by IoT devices and act on it in a successful and organized manner. Industries that already use IoT devices can automate certain mundane workflows such as documentation, machine maintenance notification alert, and so on when powered by AI. Intelligent things with AI-backed IoT The saying, ‘With great power come great responsibilities’, is true for AI powered IoT.AI backed IoT devices can make complex decisions, perform self-learning, and can carry out autonomous decision making. One can group IoT applications broadly into two categories based on who the end user is, i.e. Industrial IoT for enterprises and consumer IoT for individual consumers. Let’s look into some of the major domains that AI has enhanced. 1. Industrial IoT Also known as the IIoT, IoT has impacted industries by bringing in unprecedented opportunities. However, it has also brought in a wave of new risks to businesses. IIoT provides the internet with a new ability to control machines, factories and the industrial infrastructure. Some of the characteristics of IIoT include, Improved Interoperability where the machines and sensors communicate via IoT Availability of Transparent information with the presence of more sensors, which means abundance of information. Autonomous decision making now lies in the hands of the IoT devices, where they can detect emergency situations, for instance when a machine servicing is required and can act on it immediately.    Manufacturing Manufacturing is by far the biggest industry affected by the IoT wave. According to a report, ‘global manufacturers will invest $70 billion on IoT solutions in 2020, which is up from the $29 billion they spent in 2015’.Let’s see how some of the processes in manufacturing get a lift with AI enabled IoT: Detection of machine health using Predictive maintenance : Predictive maintenance involves collection and evaluation of data from machines in order to increase efficiency and optimize the maintenance processes. With predictive maintenance, manufacturers can determine the condition of their equipments and also predict when machines need maintenance. A startup named Konux, based in Munich, Germany, has developed a machine-learning powered monitoring system for train switches. The Konux switch sensor can be retrofitted onto existing train networks, providing real-time monitoring of track conditions and rolling stock. Data is transmitted wirelessly to the Konux Kora platform, which uses predictive algorithms based on machine learning to alert staff to specific problems as well as drive recommendations for maintenance. Supply Chain Optimization : With an IoT-optimized supply chain, manufacturers can get hold of real-time data and analyze issues to act upon them before the onset of any major problem. This in turn reduces inventory and capital requirements. In order to track a product, companies have set up smart shelves, which keep a record of when the product has been removed, the total no. of products, and so on. This smart shelf is connected to their entire network which is linked to their planning and demand sensing engine. Here, the AI powered decision support systems help to translate those demand signals into production and order processes. Read ‘How AI is transforming the manufacturing Industry’ for a more indepth look at AI’s impact on the manufacturing industry. Retail Adoption of IIoT in retail has upped the game for online retailers. Retail stores now comprise of in-store advertising and gesture walls. These walls help customers search merchandize, offers, and buy products with simple gestures. Retailers also have Automated Checkouts, or most simply self-checkout kiosks. This enables customers to avoid long queues and pay for products using a mobile app based payments system which scans the QR code embedded on the products, contactless payments or other means. With IoT enabled sensors, retailers can now extract insights about the most popular areas people pass by and where they stop to see the merchandize. Retailers can then send promotional text messages, discount coupons directly on the customer’s phone while they are in the store’s vicinity. For instance, Apple’s iBeacon enables devices to alert apps and websites about customer location. Retailers have also adopted Inventory Optimizations by using digital shelf and RFID techniques for managing their inventories effectively. Healthcare IoT in healthcare is proving to be a boon for patients by decreasing costs and reducing multiple visits to doctors. With these healthcare solutions, patient monitoring can be done in real-time. Due to this real-time data, diseases can be treated well in advance before they reach a malignant stage. These IoT enabled healthcare solutions provide accurate collection of data, automated workflows which are combined with data driven decisions.This cuts down on waste, reducing system costs and most importantly minimizes errors. Also, creation and management of drugs is a major expenditure in the healthcare industry. With IoT processes and devices, it is possible to manage these costs better. A new generation of “smart pills” is allowing healthcare organizations to ensure that a patient takes his or her medication, while also collecting other vital data. Apart from these major applications of IoT in the Industrial sectors, it has also affected sectors such as telecommunications, energy, and in the Government. Next up, we move on to explaining how AI backed IoT can affect and enhance the consumer domain. 2. Consumer IoT Consumers go for services that provide them with an easy way to do mundane tasks. Let us have a look at some examples where AI has intelligently assisted IoT for consumers benefit. Connected Vehicles Connected vehicles are vehicles that use any of a number of different communication technologies to communicate with the driver, other cars on the road (vehicle-to-vehicle [V2V]): This tech helps wirelessly exchange information about the speed and position of surrounding vehicles. This helps in avoiding crashes, ease traffic congestion, and improve the environment. roadside infrastructure (vehicle-to-infrastructure [V2I]): These technologies capture vehicle-generated traffic data wirelessly and provide information such as warnings from the infrastructure to the vehicle that inform the driver of safety, mobility, or environment-related conditions. the “Cloud” [V2C]: A Vehicle-to-Cloud infrastructure integrates NaaS (Network As A Service) into the automotive ecosystem and allows provisioning of vehicle-based services for automobile user. Connected homes These AI enabled IoT devices and services can automatically respond to preset rules, be remotely accessed and managed by mobile apps or a browser, and send alerts or messages to the user. For instance, Google Home, with a built-in Google Assistant, controls home and helps people with lists, translation, news, music, calendar and much more. Google Home can also answer any questions asked to it. This is because of Google’s huge Knowledge Graph that it is connected to. Similarly, Amazon’s Echo, a voice-controlled speaker and Apple’s homepod also assist in collecting data they get via voice. The AI can also get all devices within the home connected, with the help of Wi-Fi. With the latest IFTTT technology, your Google Home can talk to Nest and adjust the temperature of your home as per your requirement or the external temperature change. Health and lifestyle AI integrated with predictive analytics within the embedded devices such as fitness apps, health trackers, diet planners, and so on, makes them intelligent and personalized. For instance, Fitbit coach app paired with the Fitbit has a huge database. The app uses complex algorithms to extract meaningful information from the user data. This data is further used to recommend highly-tailored workout plans. Also, AthGene, uses ML algorithms to convert genetic information into valuable insights for customizing fitness regimen, diet plans, and lifestyle changes for users. IoT was only about devices monitoring data and giving insights in real-time. But AI added the efficiency factor, and also gave the power to these systems to take decisions. AI with IoT has a bright future; one can expect smart machines managed via Echo or Google Home in the future. Read Next How Google’s DeepMind is creating images with artificial intelligence Customer Relationship management just got better with Artificial Intelligence 5 Ways Artificial Intelligence is Transforming the Gaming Industry
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Savia Lobo
02 May 2018
5 min read
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Should you go with Arduino Uno or Raspberry Pi 3 for your next IoT project?

Savia Lobo
02 May 2018
5 min read
Arduino Uno and Raspberry Pi 3 are the go-to options for IoT projects. They're tiny computers that can make a big impact in how we connect devices to each other, and to the internet. But they can also be a lot of fun too - at their best, they do both. For example, Arduino Uno and Raspberry Pi were used to make a custom underwater camera solution for filming the Netflix documentary, Chasing Coral. They were also behind the Autonomous racing robot. However, how are the two microcomputers different? If you're confused about which one you should start using, here's a look at the key features of both the Arduino Uno and the Raspberry Pi 3.This will give you a clearer view on what fits your project well, or maybe just help you decide what to include on your birthday wishlist. Comparing the Arduino Uno and Raspberry Pi 3 Raspberry Pi 3 has a Broadcom BCM2837 SoC with it can handle multiple tasks at one time. It is a Single Board Computer (SBC), which means it is a fully functional computer with a dedicated processor, memory, and is capable of running an OS - Raspberry Pi 3 runs on Linux. It can run multiple programs as it has its own USB ports, audio outputs, a graphic driver for HDMI output. Arduino Uno is a microcontroller board based on the ATmega328, an 8-bit microcontroller with 32KB of Flash memory and 2KB of RAM, which is not as powerful as SBCs. However, they are a great choice for quick setups. Microcontrollers are a good pick when controlling small devices  such as LEDs, motors, several different types of sensors, but cannot run a full operating system. The Arduino Uno runs one program at a time. One can also install other operating systems such as Android, Windows 10, or Firefox OS. Let's look at the features and how one stands out better than the other: Speed The Raspberry Pi 3 (1.2 GHz) is much faster than Arduino (16 MHz). This means it can complete day-to-day tasks such as web surfing, playing videos, with greater ease From this perspective, Raspberry Pi is the go-to choice for media centered applications. Winner: Raspberry Pi 3 Easy time interface Arduino Uno offers a simplified approach for project building. It has easy time interfacing with presence of analog sensors, motor, and other components. By contrast, the Raspberry Pi 3  has a more complicated route if you want to set up projects. For example, to take sensor readings you'll need to install libraries and connect to a monitor, keyboard and mouse. Winner: Arduino Uno Bluetooth/ Internet connectivity Raspberry Pi 3 connects to Bluetooth devices and the internet directly using Ethernet or by connecting to Wi-Fi. The Arduino Uno can do that only with the help of a Shield that adds internet or Bluetooth connectivity. HATS (Hardware Attached on Top) and Shields can be used on both devices to give them additional functionality. For example. HATs are used on the Raspberry Pi 3, to control an RBG Matrix, add a touchscreen, or even create an arcade system. Shields that can be used on the Arduino Uno include a Relay Shield, a Touchscreen Shield, or a Bluetooth Shield. There are hundreds of Shields and HATs that provide the functionality that you regularly use. Winner: Raspberry Pi 3 Supporting ports The Raspberry Pi 3 has an HDMI port, audio port, 4 USB ports, camera port, and LCD port, which is ideal for media applications. On the other hand, Arduino Uno does not have any of these ports in the board. However, some of these ports can be added on the Arduino Uno with the help of Shields. Arduino Uno has 14 digital input/output pins (of which 6 can be used as PWM outputs), 6 analog inputs, a 16 MHz crystal oscillator, a USB connection, a power jack, an ICSP header, and a reset button. Winner: Raspberry Pi 3 Other features Set-up time Raspberry Pi 3 takes longer to set up. You'll also probably need additional components such as a HDMI cable, a monitor, a cable, and a keyboard and mouse. For the Arduino Uno you simply have to plug it in. The code then runs immediately. Winner: Arduino Uno Affordable Price Arduino Uno is much cheaper. It's around $20 compared to Raspberry Pi 3, which is around $35. It's important to note that this excludes the cost of cables, keyboards, mouse and other additional hardware.As mentioned above, you don't need those extras with the Arduino Uno. Winner: Arduino Uno Both Arduino Uno and Raspberry Pi 3 are great in their individual offerings. Arduino Uno would be an ideal board if you want to get started with electronics, and begin building fun and engaging hands-on projects. It's great for learning the basics of how sensors and actuators work, and an essential tool for one's rapid prototyping needs. On the other hand, Raspberry Pi 3 is great for projects that need an online connection and have multiple operations running  at the same time. Pick as per your need! You can also check some of our exciting books on Arduino Uno and Raspberry Pi. Raspberry Pi 3 Home Automation Projects: Bringing your home to life using Raspberry Pi 3, Arduino, and ESP8266 Build Supercomputers with Raspberry Pi 3 Internet of Things with Arduino Cookbook   How to build a sensor application to measure Ambient Light 5 reasons to choose AWS IoT Core for your next IoT project Build your first Raspberry Pi project
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Savia Lobo
19 Apr 2018
5 min read
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5 reasons to choose AWS IoT Core for your next IoT project

Savia Lobo
19 Apr 2018
5 min read
Many cloud service providers have been marching towards adopting IoT (Internet of Things) services to attract more customers. This league includes top cloud merchants such as AWS, Microsoft Azure, IBM, and much recently, Google. Among these, Amazon Web Services have been the most popular. Its AWS IoT Core service is a fully-managed cloud platform that provides IoT devices with an easy and secure connection to interact with cloud applications and other IoT devices. AWS IoT Core can keep track of billions of IoT devices, with the messages travelling to and from them. It processes and routes those messages to the AWS endpoints and to other devices reliably and securely. This means, with the help of AWS IoT Core, you can keep track of all your devices and have a real-time communication with them. Undoubtedly, there is a lot of competition around cloud platforms to host IoT services. Users are bound to a specific cloud platform for a varied set of reasons such as a yearly subscription, by choice, or other reasons. Here are 5 reasons to choose AWS IoT core for your IoT projects: Build applications on the platform of your choice with AWS IoT Core Device SDK AWS IoT Core Device SDK is the primary mode of connection between your application and the AWS IoT core. It uses the MQTT, HTTP, or webSockets protocols to effectively connect and exchange messages with this service. The languages supported by the AWS IoT device SDK are C, Arduino, and JavaScript. The SDK provides developers with mobile SDKs for Android and iOS, and a bunch of SDKs for Embedded C, Python and many more. It also includes open-source libraries, developer guides with samples, and porting guides. With these features, developers can build novel IoT products and solutions on the hardware platform of their choice. AWS IoT Summit 2018 held recently in Sydney shed light on cloud technologies and how it can help businesses lower costs, improve efficiency and innovate at scale. It had sessions dedicated to IoT. (Intelligence of Things: IoT, AWS DeepLens, and Amazon SageMaker) Handle the underlying infrastructure and protocol support with Device Gateway The device gateway acts as an entry gate for IoT devices to connect to the Amazon Web Services (AWS). It handles multiple protocols, which ensures secure and effective connection of the IoT devices with the IoT Core. The list of protocols include MQTT, WebSockets, and HTTP 1.1. Also, with the device gateway, one does not have to worry about the infrastructure as it automatically manages and scales huge amount of devices at ease. Authentication and Authorization is now easy with AWS methods of authentication AWS IoT Core supports SigV4, an AWS method of authentication, X.509 certificate based authentication, and customer created token based authentication. The user can create, deploy and manage certificates and policies for the devices from the console or using the API. AWS IoT Core also supports connections from users’ mobile apps using Amazon Cognito, which creates a unique ID for app users and can be used to retrieve temporary, limited-privilege AWS credentials. AWS IoT Core also enables temporary AWS credentials after a device has authenticated with an X.509 certificate. This is done so that the device can more easily access other AWS services such as DynamoDB or S3. Determine device’s current state automatically with Device Shadow Device shadow is a JSON document, which stores and retrieves the current state for a device. It provides persistent representations such as the last reported state and the desired future state of one’s device even when the device is offline. With Device Shadow, one can easily build applications to interact with the applications by providing REST APIs. It aids applications to set their desired future state without having to request for device starting state. AWS IoT core differentiates between the desire state and the last reported state. It can further command the device to make up the difference. Route messages both internally and externally using AWS Rules Engine The Rules Engine helps build IoT applications without having to manage any infrastructure. Based on the rules defined, the Rules engine evaluates all the incoming messages within the AWS IoT Core, transforms it, and delivers them to other devices or cloud services. One can author or write rules within the management console using the SQL-like syntax The Rules Engine can also route messages to AWS endpoints such as AWS Lambda, Amazon Kinesis, Amazon S3, Amazon Machine Learning, Amazon DynamoDB, Amazon CloudWatch, and Amazon Elasticsearch Service with built-in Kibana integration. It can also reach external endpoints using AWS Lambda, Amazon Kinesis, and Amazon Simple Notification Service (SNS). There are many other reasons to choose AWS IoT Core for your projects. However, it is purely one’s choice as many might already be using or bound to other cloud services. For those, who haven’t yet started, they may choose AWS for a plethora of other cloud services that they offer, which includes AWS IoT Core too.  
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Raka Mahesa
31 Jan 2018
5 min read
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How IoT is going to change tech teams

Raka Mahesa
31 Jan 2018
5 min read
The Internet of Things is going to transform the way we live in the future. It will change how we commute, how we work, even simple day to day activities. But one thing that’s often overlooked when we talk about the internet of things is how it will impact IT teams. We’ve seen a lot of change in the shape of the modern IT team over the last 10 years thanks to things like DevOps, but IoT is going to shape things further in the near future.  To better understand how the Internet of Things will shape IT teams in the future, we first need to understand the application of the Internet of Things, especially in the sector closest to IT teams, the enterprise sector. IoT in the enterprise sector If you look at consumer media, the most common applications of the Internet of Things are the small-scale ones like smart gadgets and smart home systems. Unfortunately, this class of IoT products hasn't really caught up with mainstream consumers; its audience is limited to hobbyists and people in the tech. However, it's a whole different story with the enterprise sector becuse companies all over the world are starting to realize the benefit of applying IoT in their line of business.  Different industries have different applications of IoT. Usually though, IoT is used to either increase efficiency or reduce cost. For example, a shipping service may apply a monitoring system on their vehicles to track their speed and mileage to find ways to reduce fuel usage. Similarly, an airline company could apply sensors on their fleet of airplanes to monitor engine conditions to maintain it properly. A company may also apply IoT to manage its energy consumption so that it can reduce unneeded expenses. What new skills does IoT demand of tech pros All of these applications of IoT are going to require new skills and maybe even new job roles. So while we’ll see efficiencies thanks to these innovations, to really make an impact its still going to need both personal and organizational investment in skills and knowledge to ensure IoT is really helping to drive positive change. IoT and the second data explosion Let’s start with the most obvious change – the growth of data. Yes, the big data explosion has been happening all around us for the last decade, but IoT is bringing with it a second explosion that will be even bigger. This means everyone is going to have to become more data-savvy. That’s not to say that everyone will need to moonlight as a data scientist, but they will need an awareness of how data is stored and processed, who needs access to it and who needs to act on it. Device management will become more important than ever IoT isn’t just about data. It’s also about devices. With more gadgets and sensors connected to a given network, device management and maintenance will be an essential part of the IT team’s work. To tackle this problem, the team will need to grow bigger to handle more work, or they will need to use a more powerful device management tool that can handle a big amount of connected devices. New security risks presented by IoT An increase in the number of connected devices also presents increased security risks. This means pressure will be on IT departments to  IT team will need to tighten up security. Managing networks is one part of that, but a further challenge will be managing the human side of security – ensuring good practice is followed by staff and taking steps to minimize social engineering threats. IT teams will have to customize IoT solutions to meet their needs IoT doesn’t yet have many standards. That means today’s organizations face opportunities and challenges in how they customize solutions and tools for their own needs. This can be daunting, but for people working in IT teams it’s also really exciting – it gives them more control and ownership of the work they are doing. Third party solutions will no doubt remain, but they won’t be quite so important when it comes to IoT. True, companies like IBM will be working on IoT solutions right now to capture the market; however, because these innovations are in their infancy there’s a limit on traditional technology corporations’ ability to shape and define the IoT landscape in the way they have done with innovations in the past.  And that's just a small bit of how the Internet of Things will affect the IT team. When IoT takes off, it will change our lives in the most unimaginable ways possible, so of course there will be even more changes that will happen with the IT teams in charge of this. But then again, the world of technology is ripe with changes and disruptions, so I'm sure we're all used to changes and will be able to adapt. Raka Mahesa is a game developer at Chocoarts who is interested in digital technology in general. Outside of work, he enjoys working on his own projects, with Corridoom VR being his latest released game. Raka also regularly tweets @legacy99.
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Raka Mahesa
24 Jan 2018
4 min read
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Why Metadata is so important for IoT

Raka Mahesa
24 Jan 2018
4 min read
The Internet of Things is growing all the time. However, as IoT takes over the world, there are more and more aspects of it that needs to be addressed, such as security and standardization. It might not be ideal to live in a wild west where everything is connected but there are no guidelines or rules for how to manage and analyze these networks. A crucial part of all this is metadata – as data grows in size, the way we label, categorize and describe it will become more important than ever. Find our latest and forthcoming IoT eBooks and videos here.  We probably shouldn’t be that surprised – if IoT is all about connecting things that wasn’t previously connected – traffic lights, lamps, car parts – good metadata allows us to make sure those connections remain clear and legible. It helps to ensure that things are working properly. A system without definitions, without words and labels, would, after all, get chaotic pretty quickly. Metadata makes it easier to organize IoT data If metadata is, quite simply, data about data, it’s not hard to see why it might be so important when dealing with the expanse of data that is about to be generated thanks to the internet of things. While IoT will clearly largely run on data – information and messages passing between objects, moving within a given system, metadata is incredibly useful in this new world because it allows us to better understand the systems that we are developing. And what’s more, once we have that level of insight, we can begin to do more to further improve and optimize IoT systems using machine learning and artificial intelligence.  Consider how metadata organizes your media library – it would be a mess without it, practically unusable. When you scale that up, we’ll be able to make much smarter use of IoT. Without it, we might well be lost in a chaotic mess of connections.  Metadata, then, allows us to organize and catalog data.  Metadata solves IoT's interoperability problem Metadata can also help with the biggest problem of IoT: interoperability. Interoperability refers to the ability for one device to communicate and exchange data with another device. And this is really important in the context of the Internet of Things, because having great interoperability means more devices can connect with each other.  How does metadata solve interoperability? Well, by using metadata, a device can quickly identify a new device that tries to connect to it by looking at its model number, device class, and other attributes. Once the new device has been identified, our device can find a suitable communication protocol that's supported by both devices to exchange data. Metadata can also be added on the exchanged data, so both devices can read and process the data correctly, just like adding image format metadata allows any application to display that image. Metadata helps to protect legacy hardware and software There's another aspect that metadata can help with. The Internet of Things is an evolving technology where new products are introduced every day, and bring along with them changes and innovations. But what happens to the old products that have been replaced by new ones? With metadata, we can archive and protect the future accessibility of our devices, making sure that new devices can still communicate with older, legacy devices.  That's why metadata is important for the Internet of Things. There are many benefits that can be gained by having a robust system of metadata in the Internet of Things. And as the Internet of Things grows and is used to manage more crucial aspects of our lives, the need for this system will also grow. Raka Mahesa is a game developer at Chocoarts who is interested in digital technology. Outside of work, he enjoys working on his own projects, with Corridoom VR being his latest relesed gme. Raka also regularly tweets @legacy99.
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Raka Mahesa
20 Sep 2017
5 min read
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Raspberry Pi v Arduino - which one's right for me?

Raka Mahesa
20 Sep 2017
5 min read
Okay, so you’ve decided to be a maker and you’ve created a little electronic project for yourself. Maybe an automatic garage door opener, or maybe a simple media server for your home theatre. As you learn your way further into the DIY world, you realize that you need to decide on the hardware that will be the basis of your project. You’ve checked the Internet for help, and found out the two popular hardware choices for DIY projects: the Raspberry Pi and the Arduino. Since you're just starting out, it seems both hardware choices serve the same functionality. They both are able to run the program needed for your project and they both have a big community that can help you. So, which hardware should you choose? Before we can make that decision, we need to understand which hardware is best. Let's start with the Raspberry Pi. To put it simply, the Raspberry Pi is a computer with a very, very small physical size. Despite its small size, the Raspberry Pi is actually a full-fledged computer capable of running an operating system and executing various programs. By connecting the mini-computer to a screen via an HDMI cable, and to an input device like a keyboard or a mouse, people will be able to use the Raspberry Pi just like any other computer out there. The latest version even has wireless connectivity built right into the device, making it very easy for the hardware to be connected to the Internet. So, what about the Arduino? The Arduino is a microcontroller board--an integrated circuit with a computing chipset capable of running a simple program. If smart devices are run by computer processors, then "dumb devices" are run by microcontrollers. These dumb devices include things like a TV remote, air conditioner, calculator, and other simple devices. Okay, so now we have completed our crash course for both platforms, let's actually compare them, starting from the hardware aspect. Raspberry Pi is a full-blown computer, so it has most of the stuff you'd expect from a computer system. It has a quad-core ARM-based CPU running at 1,200 MHz, 1 GB of RAM, microSD card slot for storage, 4 USB 2.0 ports, and it even has a GPU to drive the display output via an HDMI port. The Raspberry Pi is also equipped with a variety of modules that enables the hardware to easily connect to other devices like camera and touchscreen. Meanwhile, the Arduino is a simple microcontroller board. It has a processor running at 16 MHz, a built-in LED, and a bunch of digital and analog pins to interface with other devices. The hardware also has a USB port that's used to upload a custom program into the board. Just from the hardware specification alone we can see that both are on a totally different level. The Raspberry Pi has a processor running at 1,200 MHz CPU clock, which is roughly similar to a low-end smartphone, whereas the processor in Arduino only runs at 16 MHz CPU clock. This means an Arduino board is only capable of running a simple program, while a Raspberry Pi can handle a much more complex one. So far it seems that Raspberry Pi is a much better choice for DIY projects. But well, we all know that a smartphone is also much more limited and slower than a desktop computer, yet no one is going to say that smartphone is useless. To understand the strength of the Arduino, we need to look at and compare the software running the hardware we're discussing. Since Raspberry Pi is a computer, the device requires an operating system to be able to function. An operating system offers many benefits, like a built-in file system and multitasking system, but it also has disadvantages like needing to be booted up first and programs requiring additional configuration so they can run automatically. On the other hand, an Arduino is running its own firmware that will execute a custom, user-uploaded program as soon as the device is turned on. The software on Arduino is more much limited, but it also means using it is pretty simple and straightforward. This theme of simplicity and complexity also extends to the software development for both platforms. Developing a software for Raspberry Pi is complex, just like developing any computer software. Meanwhile, Arduino provides a development tool that allows you to quickly develop a program in your desktop computer and easily upload it to the Arduino board via USB cable. So with all that said, which hardware platform is the right choice? Well, it depends on your project. If your project is simply about reading sensor data and processing that, then the simplicity of Arduino will help the development of your project immensely. If your project includes a lot of task and processes, like uploading data to the internet, sending you e-mail, reading image data, and other stuff, then the power of Raspberry Pi will help your project successfully do all those tasks. And, if you're just starting out and haven't really decided on your future project though, I'd suggest you to go with Arduino. The simplicity and ease-of-use of an Arduino board makes it a really great learning tool where you can focus on making new stuff instead of making your things work together. About the Author RakaMahesa is a game developer at Chocoarts, who is interested in digital technology in general. Outside of work hours, he likes to work on his own projects, with Corridoom VR being his latest released game. Raka also regularly tweets as @legacy99
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