Self-Sustaining Wireless Sensor Networks: Energy Harvesting Models and Implementation Approaches

Abstract

Energy harvesting (EH) has emerged as a key enabler for self sustaining wireless sensor networks (WSNs),reducing reliance on batteries and enabling long-term deployment in remote environments. This work reviews ambient energy conversion modalities—solar, thermal, vibrational, RF—and key storage strategies(capacitors, batteries, super capacitors). We then implement a multi-source EH prototype integrating photovoltaic and piezoelectric modules coupled with a power-management IC on a standard WSN platform. Our implementation is evaluated in indoor/outdoor and vibrational field tests to assess energy balance, duty-cycle sustainability, and data delivery reliability.We observe that hybrid EH systems using complementary sources significantly improve node uptime: solar + vibration increases uptime by 45%over single-source solar in variable conditions. Through a PID power-management controller, sensor nodesmaintain ≥80% uptime at ≥70% duty cycles under intermittent energy availability. Communication success remains at 95% for data sampling intervals up to 10 min. Analysis highlights design trade-offs: larger storage reduces outage, but adds size/cost; multi-source complexity increases system robustness at the expense of hardware complexity. We conclude that capacitor-super capacitor hybrid storage architectures with adaptive duty cycling enable reliable, self sustaining WSNs for environmental, structural health, and industrial IoT applications.