TinyML

Chapter 16. Optimizing Energy Usage

The most important advantage that embedded devices have over desktop or mobile systems is that they consume very little energy. A server CPU might consume tens or hundreds of watts, requiring a cooling system and main power supply to run. Even a phone can consume several watts and require daily charging. Microcontrollers can run at less than a milliwatt, more than a thousand times less than a phone’s CPU, and so run on a coin battery or energy harvesting for weeks, months, or years.

If you’re developing a TinyML product, it’s likely that the most challenging constraint you’ll have to deal with is battery life. Requiring human intervention to change or recharge batteries is often not feasible, so the useful lifetime of your device (how long it will continue working) will be defined by how much energy it uses, and how much it can store. The battery capacity is typically limited by the physical size of your product (for example, a peel-and-stick sensor is unlikely to be able to accommodate anything more than a coin battery), and even if you’re able to use energy harvesting, there are sharp limits on how much power that can supply. This means that the main area you can control to influence the lifetime of your device is how much energy your system uses. In this chapter we talk about how you can investigate what your power usage is and how to improve it.

Developing Intuition

Most desktop engineers have a rough feel for how long different kinds of ...