DESC: Type I: Repurposing Batteryless SmartPhones as Long-lived and Adaptable Sensors for Sustainable and Scalable Environmental Monitoring

This project aims to repurpose old smartphones as sustainable, battery-free alternatives to conventional Internet of Things (IoT) sensors, creating a long-lived platform for environmental monitoring. With most smartphones replaced every 2–3 years and billions of IoT devices in use globally, the environmental and economic costs of short device lifespans are substantial. This project addresses these concerns by integrating repurposed smartphones into real-world monitoring networks for tree phenotyping and river dynamics. Equipped with biocompatible, energy-harvesting phone cases, these smartphones operate without batteries or manual maintenance. This work promotes the progress of science by extending the utility of existing devices, reducing infrastructure costs, and supporting environmental science through scalable, real-time data collection. The project also supports graduate and undergraduate research and encourages the reuse of computing resources in sustainable applications. The project develops models, algorithms, hardware platforms, and foundational methods for creating an ultra-long-lived, maintenance-free remote sensing platform for environmental applications. It focuses on transforming old smartphones into reusable, battery-free sensors equipped with custom-designed, energy-harvesting phone cases. These systems operate reliably under intermittent power conditions using capacitor-based energy storage rather than conventional batteries. The research includes the development of battery-free computing techniques, energy-aware scheduling strategies, and domain adaptation algorithms to ensure robust performance across a wide range of smartphone models and environmental conditions. The system supports continuous monitoring of tree canopies and river systems, with sensing tasks such as image capture and data logging. Evaluation is conducted through iterative hardware-software co-design and extensive field testing in diverse geographic regions. The resulting platform contributes to ecological monitoring, embedded computing, and the broader understanding of sustainable sensing in resource-constrained environments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.