IoT-Driven Energy Management and Real-Time Monitoring of a Photovoltaic-Powered Solar Dryer Using an ESP32 Platform

Solar drying has emerged as an environmentally sustainable technology for preserving agricultural and medicinal products through the utilization of renewable solar energy. However, conventional solar dryers generally operate without intelligent monitoring and energy-management capabilities, limiting process supervision, system autonomy, and efficient utilization of available energy resources. To address these challenges, this study presents the development and experimental validation of an Internet of Things (IoT)-driven photovoltaic-powered solar dryer based on the ESP32 microcontroller platform. The proposed system integrates a solar air collector, drying chamber, photovoltaic power supply, lithium-ion battery storage unit, battery management circuitry, wireless communication module, and electronically controlled ventilation subsystem. The ESP32 controller performs real-time acquisition of electrical and operational parameters, including battery voltage, charging status, power availability, ambient conditions, and ventilation operation. Acquired data are transmitted through a wireless network to a remote monitoring interface, enabling continuous supervision and energy-management functions. The photovoltaic subsystem provides autonomous electrical power for the monitoring and ventilation units without dependence on external grid electricity. Experimental tests were conducted under outdoor operating conditions to evaluate system performance and operational reliability. The developed monitoring platform achieved stable real-time communication with a data update interval below 5 s and maintained uninterrupted operation throughout the drying cycle. The photovoltaic-battery subsystem ensured continuous energy supply for sensor monitoring and ventilation control, while remote access enabled effective supervision of system status and energy utilization. The integration of IoT technology improved operational transparency, reduced the need for manual intervention, and enhanced the overall autonomy of the solar drying process. The obtained results demonstrate that the proposed ESP32-based IoT architecture provides a reliable and scalable solution for smart solar drying applications. Furthermore, the developed platform establishes a foundation for future integration of artificial intelligence, predictive maintenance, and intelligent energy-management strategies aimed at improving drying efficiency, energy utilization, and sustainability.