Intelligent Orchard Monitoring: An IoT-Based Approach for Real-Time Apple Disease Detection Using Environmental Factors

Abstract

This research introduces a novel methodology for apple disease detection based on environmental factors, integrating the capabilities of the Internet of Things (IoT). By deploying advanced sensors in orchards, the aim is to facilitate real-time monitoring and transform these spaces into intelligent ecosystems. The methodology encompasses data collection from environmental variables like temperature, humidity, pressure, and light. Using the Mamdani fuzzy inference system (MFIS), the collected data is then employed to predict potential apple diseases. Initial tests conducted in an apple orchard in Shimla, India, demonstrated the system's effectiveness and efficiency, with minimal delays during various phases of the process. The study also offers a comparative analysis with existing state-of-the-art methodologies in the realm of disease detection.