Adaptive Smart Cat Feeding System Based on ESP32 Using Fuzzy Logic and IoT Monitoring

Abstract

Smart pet feeders are increasingly utilised to enhance daily pet care; however, most existing systems depend on fixed feeding schedules and lack adaptability to changing conditions. This study details the design and implementation of an Internet of Things (IoT)-based smart cat feeder that incorporates an ESP32 microcontroller, fuzzy logic control, and a web-based interface. The system utilises a fuzzy inference mechanism to adaptively determine feeding portions under uncertain conditions, thereby addressing the limitations of threshold-based feeding strategies. A web interface enables real-time monitoring and manual override functions. Experimental results demonstrate that the system operates reliably and provides a more flexible, adaptive feeding behaviour than conventional automatic feeders. These findings suggest that the proposed approach offers a practical and effective solution for intelligent pet care applications.