Date of Award


Document Type



Santa Clara : Santa Clara University, 2022.


Computer Science and Engineering

First Advisor

Behnam Dezfouli


Many WiFi-based IoT (Internet of Things) devices rely on limited energy resources such as batteries or energy harvesting. Although monitoring and studying the energy consumption of these devices is essential, the use of external, hardware-based energy measurement tools is costly, non-scalable, and introduces many challenges regarding the connectivity of such tools with devices. In this thesis, we propose EMT, a novel tool to collect, analyze, and monitor the power cycles of IoT devices without the need for any external tools. The basic idea is to modify the WiFi Access Point's software to keep track of the power status of devices reported in packets. EMT also includes back-end and front-end components for data storage, analysis, and visualization. We demonstrate the effectiveness and features of EMT via empirical evaluations.

Available for download on Tuesday, July 11, 2023