Title: Weather prediction based on wireless sensor network and internet of things with analysis using hybrid SSOA with MA

Authors: Priya Shamu; Anila Sathishkumar

Addresses: Department of Information and Communication Engineering, Anna University, Guindy, Chennai, India ' Department of Electronics and Communication Engineering, Sri Ramakrishna Institute of Technology, Coimbatore, Tamilnadu, India

Abstract: Weather forecasting is a rapidly expanding field that forecasts the weather in a specific location at a certain time weather forecasting is regarded as the most essential aspect of study since it involves numerous real-time problems. These are the specifications for weather-detecting wireless sensor networks. In this paper, we suggest combining the mayfly algorithm (MA) with the shuffled shepherd optimisation algorithm (SSOA). A collection of climatic data is used to carry out the experiments. The data is split into heat, wind, and rain based on meteorological factors such as temperature, humidity, and clouds. The weather is expected to verify the suggested qualifying techniques at a high degree of accuracy, based on the results achieved. The result demonstrates that the hybridised SSOA and MA technique is effective and precise in forecasting meteorological conditions. This experiment was conducted out on agricultural land utilising a wireless sensors network and IoT.

Keywords: agriculture fields; wireless sensor network; WSN; climate monitoring; weather prediction; hybrid SSOA.

DOI: 10.1504/IJMC.2025.147614

International Journal of Mobile Communications, 2025 Vol.26 No.1, pp.112 - 132

Received: 08 Oct 2021
Accepted: 18 Dec 2022
Published online: 24 Jul 2025 *

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