Leveraging IoT and Genetic Algorithm-Based Clustering for Enhanced Environmental Management in Smart Greenhouses: A Novel Approach for Sustainable Agriculture

Abstract

The growing problems of water deficit and the imperative need for organic farming have widened the demands for more efficient use of resources in green houses. In this regard, the presented research offers a novel solution the use of Internet of Things (IoT) technology in combination with a genetic algorithm based-clustering to improve water management and increase crop yields in greenhouses. IoT devices allow controlling important parameters of the environment like temperature, soil moisture, wind speed, etc., that helps to control irrigation accurately. The genetic algorithm-based clustering technique, as proposed in the paper, reduces water usage by dynamically interactively for irrigation which optimizes plant health and crop yield. These findings highlight the feasibility of the referred IoT and genetic algorithms for sustainable greenhouse management particularly on water scarce environments. This paper provides benefit-making knowledge contributes to the development of smart agriculture needed to confront these global issues through improving resource use efficiency and sustainable agriculture production..