Energy efficiency constitutes a critical concern for battery-powered wireless sensors. Improving energy efficiency can significantly prolong the continuous operation period of these sensors. The sensor energy consumption is mainly from two parts, i.e sampling, and communication. Previous efforts aimed at improving sampling energy efficiency have predominantly relied on duty cycles. The duty cycles based methods seek to elongate the sampling interval to decrease energy consumption per unit of time. However, a larger sampling interval comes with the risk of losing important data for the user while a small sampling interval leads to higher energy consumption. Therefore, this research aims to develop a value based adaptive sampling method to reduce wireless sensor energy consumption while minimising the impact on the user’s data requirements.

PhD Student

Luning Li

Supervisor 

Ajith Parlikad