IoT-integrated Intelligent and Quality-aware Solar Drying Systems: A Comprehensive Review of Technologies and Control Strategies

Abstract

Solar drying has recently been recognized as a sustainable and energy-effective technique for minimizing post-harvest losses of agricultural produce, especially in regions with high solar intensity. Traditional open sun drying techniques, although cheap, are very sensitive to environmental changes which affect both the drying process and the resulting product quality. Advanced solar drying systems now include hybrid and mixed-mode systems which use direct and indirect systems to enhance thermal efficiency and drying rates. The Internet of Things (IoT) technologies now enable real-time monitoring and control for optimizing drying processes through their recent development. The review examines solar drying system technological development through the investigation of heat and mass transfer phenomena and different dryer designs and technical evaluations. The study focuses on IoT-based designs which use sensors and microcontrollers and Wi-Fi and GSM and LoRa and Bluetooth communication protocols and cloud computing and actuator-based automation. The paper contrasts conventional control methods like on-off and PID control with intelligent control methods like fuzzy logic control (FLC) and artificial neural networks (ANNs) and machine learning-based predictive models. The research demonstrates that intelligent control methods enable users to handle nonlinear drying kinetics together with solar irradiance fluctuations and drying processes which depend on quality factors. In general, intelligent solar drying systems with IoT can have a substantial potential to enhance drying homogeneity, lessen energy usage, decrease after harvest losses and improve food quality and safety. These innovations help to achieve sustainable agriculture and resilient food systems within the framework of climate variability and food security of the world.