Smart Battery Management

Jun 6, 2020 | White Papers

June 2020

In this Ekkono SWP (Short White Paper) we discuss how the nature of IoT devices and their environments require adaptive Battery Management Systems (BMS), tailored for the specific device. We mean that incremental Edge Machine Learning is the enabling technology to do so. To be truly smart a BMS system should include all possible sources of information i.e. data from the battery, the user, the device, the environment and any knowledge about future plans and events.

The most reasonable approach for this scenario is to run the machine learning on a microcontroller on the device, but this also entails strict requirements on the software to be feasible. Ekkono’s Edge Machine Learning library is designed from scratch to meet these requirements and to enable incremental learning on the edge. Read this SWP to learn more about using Edge Machine Learning for Smart Battery Management.

Click the image to download the SWP document (pdf).

Ekkono’s SWP are documented results of our #openfika webinars.

The webinars are also recorded and available to watch in our YouTube channel or below:

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