Steve is an independent software consultant in Silicon Valley specializing in the Microsoft product stack having retired after a 40+ year career doing semiconductor industry, with side excursions in to medical image management. Over the years he has worked with a wide range of platforms from mainframes to PCs, many of which have gone to the great scrap yard in the sky.
Co-chair Baynet User Group's South Bay Chapter and Baynet Treasurer
The availability of machine learning in the cloud combined with extensive press coverage of “IOT (Internet Of Things) evolution has led to extensive speculation about innovative new applications. A key element in most of these application are sensor elements residing on the cloud edge which are capable of automatically feeding data to cloud resident machine learning applications.
These sensor applications face a number of constrains, which are not normally encountered when developing other computer based applications. Two of the most important constrains are related to power and communications. Cost and complexity issues preclude the use of hardwired connections. In addition the commonly used Wi-Fi and Cellular Radio (Smart Phone) wireless technologies do not provide suitable solutions for most of the application. Since power must be obtained from batteries or solar cell sources low power consumption is also a critical issue.
The presentation will provide a overview of the following topics
Microcontroller vs other computing environments
Microcontroller development tools
Low Power Communication options such as Sigfox, and Lorawan along their pros and cons
Things Network Open Source Project
Connecting to Cloud IOT servers
Follow the overview a walk thought of the development of the code used to implement a low cost IOT metrological sensor will be presented.
Sample of various hardware components used for IOT sensor development will be shown