Various techniques and strategies can be applied to achieve energy efficiency in IoT applications. These include transmission power modelling, sensor power modelling, cluster approach, energy harvesting models, and transmission distance modelling. In recent years, AI-powered mechanisms have been used to manage the power of a vast collection of IoT devices in a meaningful way by assigning specific computational and communication tasks to different devices.

For example, multi-agent systems have been used to model different components of sensing devices (sensing, processing, communication) and mechanisms such as genetic algorithms have been used to optimise system parameters. Software contributes to about 80% of the total energy consumption of an embedded system, and the development of energy-efficient and optimised software will continue to be a priority for IoT ecosystems employing edge devices and AI in the coming years.