Hybrid Approach for Weather Prediction in IoT Network

A growing field, weather predictions keep track of the environment in certain locations at particular periods. climate observation is also a weather monitor that will be regarded among the more beneficial for study when real concerns occur. Real-time weather parameters are monitored using a WSN over the IoT environment. This study employs the hybrid approach based on the Optimization shuffled shepherd and Mayfly techniques. It displays a collection of climatic statistics, with the main factors being rainfall, temperature, and humidity. The final results from hybridized OSSA and MA demonstrate the effectiveness of the proposed model under meteorological situations.