Engineering Sciences

Innovative battery-free wireless piezoresistive sensor for green-IoT applications

Publié le - Internet of Things

Auteurs : Mario Costanza, Abdo-Rahmane Anas Laaraibi, Antonino Pagano, Gurvan Jodin, Florence Razan, Ilenia Tinnirello, Samuel Margueron, Roberto La Rosa

This paper unveils an innovative wireless piezoresistive sensor designed to operate autonomously without batteries, addressing the critical challenge of energy sustainability in Internet of Things (IoT) applications. Traditional sensor systems often rely on batteries, which pose significant limitations in maintenance, environmental impact, and operational lifespan. Our proposed solution integrates an energy-harvesting system that efficiently converts ambient light into electrical energy, enabling continuous operation in various environments. The findings demonstrate that the developed sensor exhibits high sensitivity and accuracy in measuring mechanical strain, with a coefficient of determination (r2) of 0.99 and a root mean square error (RMSE) of 1.17 N, making it suitable for real-time monitoring applications. The integration of Time Domain to Digital Conversion (TDDC) technology significantly reduces power consumption by eliminating the need for conventional analog-to-digital converters, thus enhancing the overall energy efficiency of the wireless sensor network (WSN). The contributions of this work are multifaceted: we present the first demonstration of TDDC for force and resistive measurements in battery-free sensor nodes, propose a mathematical model for resistance to time domain digital conversion, and develop two calibration methods tailored for force and resistance measurements. These innovations advance the field of green wireless sensor technologies and pave the way for scalable and sustainable IoT solutions. The implications of this research extend to various applications, including structural health monitoring, industrial condition monitoring, and environmental sensing, where long-term data collection is essential for proactive maintenance and fault detection.