Intelligent Orchard monitoring: IoT integrated Fuzzy Logic based real-time apple disease prediction encompassing environmental factors

Abstract

This work presents a novel methodology for apple disease detection based on environmental factors, integrating the capabilities of the Internet of Things (IoT). Advanced sensors are placed in apple orchards to continuously monitor various environmental factors such as temperature, humidity, pressure, and light. The data gathered from these sensors is analyzed using the Mamdani fuzzy inference system (MFIS) to predict possible apple diseases. The use of advanced sensors, cloud storage, and the Mamdani fuzzy inference system proved effective in timely disease detection along with inclusion of environmental factors. According to predicted outcomes, a recommendation system is also presented in the mobile application. Initial experiments in Shimla, India, showed that this system is effective and efficient, with minimal delays in different stages. The study also compares this new approach with current advanced methods in disease detection.

URN:NBN:sciencein.jist.2024.v12.795