Many of the new applications expected in the Internet of Things revolve around accessing environmental data. Whether that data comes from personal health monitors, back-up cameras for automobile safety, magnetic sensing for positioning, accelerometers and gyroscopes for location and direction sensing, or familiar smoke and carbon monoxide detectors, clearly a variety of sensors will be delivering the data. As sensors become ubiquitous elements in the IoT, connecting to them and managing the first level of data becomes critical. Even a robust network won't be able to handle raw sensor data, so intermediate-level data processing and storage will be needed.
Microcontrollers will likely provide the first level of data processing and storage needed to use sensor data efficiently. Generating rolling averages, identifying outliers, compressing and storing data when bandwidth is at a premium, and managing power levels to extend battery life can be done by using MCUs in close conjunction with edge sensor networks. Combining data from multiple sensor "pods" can add intelligence to the eyes and ears and help "focus" on important events even before the Big Data "brains" step in for a closer examination.
I expect that much of the innovation in the IoT will come from these mid-level applications that intelligently process raw sensor data to make Big Data algorithms more efficient and intelligent. Just like in the stock market, knowing something a few milliseconds before someone else means big returns. This will probably be the same in the information torrent of the IoT.
If you are interested in learning more about how MCUs can be efficiently used to capture data from, manage communications with, and "crunch" data from sensors, you should attend my next Design News Continuing Education Center (CEC) online course, Controlling Sensors Efficiently with MCUs, Sept. 14-18, sponsored by Digi-Key. The course will provide a summary of common sensing functions and the devices to implement them, show how MCUs can be used as the key control element in sensing systems, and illustrate common design techniques with several examples from manufacturer reference designs and development platforms. I hope to see you there (using my MCU-based remote camera interface screen-grabber)!
One of the example development platforms that I will be using in the classes is the Texas Instruments CC2541DK-MINI, available here from Digi-Key. The components of the kit, shown in the figure below, include a USB dongle, keyfob board and case, and a debugger. Example applications include an accelerometer connected to a PC and an iOS (iPod, iPad, iPhone) app that manages keyfob alerts.
MCU manufacturers are making it as easy as possible to innovate in the IoT space by providing ready-to-use development platforms with form factors close enough to an end product to easily generate a proof of concept or spec out the next product. What will your IoT innovation look like?
Warren Miller has more than 30 years of experience in electronics and has held a variety of positions in engineering, applications, strategic marketing, and product planning with large electronics companies like Advanced Micro Devices, Actel, and Avnet, as well as with a variety of smaller startups. He has in-depth experience of programmable devices (PLDs, FPGAs, MCUs, and ASICs) in industrial, networking, and consumer applications and holds several device patents.