The project involves designing grid-friendly solar arrays that can autonomously control the rate at which solar power is delivered to the grid.
The project uses machine learning and optimization approaches to analyze energy data at city-scale. Moreover, it involves the development of smart applications that provide energy-efficiency recommendations to buildings.
The project involves developing energy and grid optimization techniques to integrate energy storage with renewable sources in the grid.
In this project, we are designing a smart textile called Tribexor, that robustly senses joint motions by observing the open circuit voltage of an all-textile triboelectric harvesting device.
The project detects the presence of cocaine using wearable on-body sensor. Our project uses wearable ECG sensors since cocaine is known to cause morphological changes in ECG signal.
The project is building an electric bike sharing testbed to study Electric Vehicles (EVs) and the interaction between EVs and the grid. The project also seeks to make electric bikes a viable transport in small towns.
The project develops a solar electric vehicle charging station for electric vehicles and the design of intelligent charging algorithms that maximize the use of renewables.
Anonymous energy data comprising energy usage, solar generation, and local weather is often released in public domain to aid sustainability research. However, such anonymous data may leak information such as the location of the consumer. In this project, we are designing techniques to mitigate localization attacks on such data.