Lewis Krishnamurti is a fourth year Bachelor of Advanced Computing Student studying at the University of Sydney. He is currently an honours student under the supervision of Prof. Athman Bouguettaya. He is interested in decentralised and peer-to-peer systems. In his spare time, he enjoys going for walks around the city of Sydney.
Designing and developing a crowdsourcing framework for energy harvesting and sharing
Energy-as-a-Service (EaaS) is defined as the wireless transfer of energy among IoT devices. An energy provider is a device that can share energy. An energy consumer is a device that requests energy. Energy may be harvested by the provider through wearables such as smart textiles or smart shoes. As such, a framework is required that can predict the potential harvestable energy of a user. To better determine how much energy can be harvested from an individual user throughout the day, multiple aspects need to be considered such as the individual person’s body characteristics, the capabilities of the harvesting devices they are wearing, and their day-to-day movement patterns. In particular, data such as activity and heartrate gathered from health-related wearables can be used in part to estimate the energy to be harvested from a user. The aim of this project is to produce a framework to estimate the energy harvestable from a user throughout their day-to-day life. This involves first gathering activity data of individuals from a dataset of Fitbit users and using this data with machine learning algorithms to create an energy harvesting model.