Solar-Assisted IoT waste monitoring system with photovoltaic energy feasibility assessment

Abstract

Internet of Things (IoT)-based waste monitoring systems are increasingly used to support smart and efficient waste management systems. However, many existing systems still depend on conventional batteries or grid power, which can increase maintenance requirements and limit outdoor deployment. Although solar photovoltaic (PV) energy can support low-power IoT systems, the practical feasibility of PV supply for smart waste-monitoring nodes is often not evaluated quantitatively. This paper presents a solar-assisted IoT waste-monitoring system and assesses the feasibility of photovoltaic energy. The developed prototype integrates a PV module, battery storage, Arduino-based control unit, ultrasonic waste-level sensor, MQ4 gas sensor, flame sensor and real-time monitoring through the Blynk IoT platform. The practical contribution of this work is not the use of individual standard components, but the combined assessment of sensing performance and PV energy feasibility. The evaluation includes PV output performance, tilt-angle effect, preliminary shading/placement observation, system load consumption, estimated battery-only runtime, PV-load energy balance, and preliminary accuracy of waste-level sensing. Experimental results show that, among the selected angles tested, 15° produced the highest average power output during the short-duration prototype test. The battery runtime was estimated using the final 12 V lead-acid battery specification, and preliminary five-point validation showed 97.87% average accuracy under controlled bin-level testing. These findings indicate that the proposed system is better described as a solar-assisted IoT waste-monitoring node, where PV energy can reduce reliance on batteries under favorable sunlight conditions. The current prototype is not yet optimized as a low-power IoT node because the MQ4 gas sensor dominates the load demand. The study provides a practical basis for evaluating PV-supported smart waste monitoring deployment in urban environments.