EcoSense: A Hardware Approach to On-Demand Sensing in the Internet of Things
Ye Liu, Qi Chen, Guangchi Liu, Hao Liu, Qing Bo Yang · IEEE Communications Magazine · 2016
An Internet of Things system typically contains a large number of low-cost devices that are mainly powered by batteries and designed to operate for a relatively long period of time. Due to the stagnated battery technology, energy efficiency will still be a burning issue for future IoT systems. To achieve better energy efficiency, we propose an innovative sensor architecture called EcoSense. Unlike traditional software-based approaches (e.g., duty cycling or adaptive sampling techniques), EcoSense provides a hardware-based on-demand sensing mechanism that effectively eliminates the energy waste caused by a sensor working in sleep or standby mode. When desired events are not present, an EcoSense sensor is completely turned off to save energy (i.e., drawing zero current). When desired events occur, an on-demand connection module will harvest energy from the events and reactivate the sensor. We implemented light- and RF-driven EcoSense sensors, and evaluated their performance in realworld experiments. Experimental results show that the EcoSense technique is able to immediately detect lights and RF signals, and offers reasonable reaction distances.