Weather Monitoring and Classification Tools Using Fuzzy Logic Method Based on Internet of Things for Agriculture - Avindra , Muhammad Alfazri; Taqwa , Ahmad; Suroso , Suroso (ISB Atma Luhur, 2025)
Agriculture is a crucial sector that faces significant challenges due to climate change, such as altered rainfall patterns, increased temperatures, and extreme weather, which threaten productivity. This research aims to design and develop a weather monitoring and classification tool utilizing the Fuzzy Logic method based on the Internet of Things (IoT). The system integrates sensors for temperature, humidity, air pressure, wind speed, and rainfall, processing the data through Fuzzy Logic to classify weather into sunny, cloudy, light rain, moderate rain, and heavy rain. The results are accessible in real-time via an LCD screen and the Blynk application. Achieving 100% accuracy in monitored conditions, the system operates continuously for 24 hours, powered by solar energy. Unlike traditional systems, this tool provides innovative solutions to weather-related agricultural challenges, enabling farmers to make informed decisions and mitigate losses due to extreme weather. This research contributes to advancing IoT applications in precision agriculture, providing a reliable, sustainable, and scalable solution to weather monitoring.