The demand for microcontrollers will grow substantially over the next five years, according to the findings of a Grand View Research report released last year. These miniature computers discretely control appliances and devices that have to think on their own, such as components in your automobile and devices for home automation. According to the report, this increased demand will be driven by certain sectors: primarily automotive, followed by pressure from industry automation and consumer electronics.
Microcontroller ubiquity will be the result of consumers’ growing expectation that appliances and devices be smarter and more automated. An expectation that manufactures of those items will continue to fuel by taking advantage of a price-dip in microcontrollers, helping to make devices with microcontrollers cheaper, and thus more accessible to consumers.
A dependable, embedded application is an essential part of any microcontroller, but the processes that receive and analyze data collected from the microcontroller will be equally important. Healthcare is an excellent example.
A recent blog post on MedTechWorld’s Medical Device and Diagnostic Industry (MD+DI) website serves as a good reference for understanding how one industry sector is being affected by the plentiful availability of microprocessors and their ability to cater to underserved markets. Near-patient devices, those small and mobile enough to live at home with the patient, will catalyze quicker testing and diagnostics if effective analyzation and predictive models are in place.
As the MD+DI post states, a medical device’s success will not be dictated solely by the quality of the device itself. The differentiator will be the union between the device’s ability to collect data and the backend process to manage, analyze, and present data to the user.
In short, when it comes to programming microcontrollers, the development work won’t end with the embedded application; instead, the lion’s share of the work will begin with analysis of the data from the application.
Developer Marko Švaljek notes in Arduino Succinctly, recently published as part of Syncfusion’s Succinctlyseries, that when initially experimenting with microcontrollers, the first thing he thought to do was collect and analyze data coming from an Arduino board’s temperature and light sensors. This led him to learn more about big data and electronics—topics he actively covers in his blog: msvaljek.blogspot.com.
If you’re just now exploring microcontrollers, or only just now have an inkling to explore, read Arduino Succinctly. It’s a great introduction to physical computing and will have you programming on the board and interacting with the real world within the first chapter.
Other Succinctly series resources on data science and analysis include:
MATLAB Succinctly by Dmitri Nesteruk
R Succinctly by Barton Poulson
If you’re interested in Arduino boards and components, you can find them online at www.arduino.cc (in the US, go to store-usa.arduino.cc). If you’d like to take a look at data and analytics platforms that make managing big data easier, look at the Syncfusion Big Data Platform and Essential Predictive Analytics.