Ontology-Based Smart Irrigation System: Enhancing Agricultural Water Management
Ontology-Based Smart Irrigation System
DOI:
https://doi.org/10.62019/abbdm.v4i1.131Keywords:
Machine Learning and Deep Learning Models, Classification, Urdu Fake and Real News Tweets, and Fake News IdentificationAbstract
An Ontology-Based Smart Irrigation System is presented in this research with the goal of improving agricultural water management. The main issue discussed is the inefficiency of conventional irrigation techniques, which results in water waste and lower crop yields. The process used entails creating an ontology, which includes defining concepts, establishing relationships, identifying domains, and populating the ontology. In order to facilitate real-time monitoring and decision-making, the irrigation system also incorporates sensors, actuators, and data processing algorithms. The main conclusions show that the ontology-based approach boosts crop output, encourages sustainable farming practices, and enhances water consumption efficiency. The findings of this study imply that ontology-based smart irrigation systems present a viable way to deal with the problems associated with water scarcity, improve agricultural output, and reduce their negative effects on the environment. The research adds to the expanding corpus of information on intelligent irrigation systems and emphasizes the significance of implementing cutting-edge technologies for agriculture's sustainable water management.
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Copyright (c) 2024 tanveer tani, maher u nisa, Muhammad Azam, Aiman zahra, Mian Muhammad Mohsin Sattar
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