Aug 2026· International Conference Innovation Engineering and Technology· pp. 1-5· 0 citations· 7 references
Abstract
Efficient water management is an important challenge in modern agriculture because of erratic weather patterns and rising water scarcity. This paper presents an Artificial Intelligence (AI)-powered Smart Sprinkler System that integrates Machine Learning with real-time weather data to optimize irrigation decisions.The proposed system uses a Random Forest classifier trained using historical weather attributes such as temperature, humidity, wind speed, pressure, and cloud cover to predict rainfall events. Real-time weather parameters are retrieved from the OpenWeatherMap API and used together with user-defined watering schedules to manage sprinkler activation intelligently.If rainfall is detected or predicted, the system automatically shuts off irrigation, thereby preventing water wastage. A web-based dashboard provides real-time monitoring of weather conditions, sprinkler status, upcoming schedules, and activity logs.Experimental evaluation demonstrates that the proposed approach effectively reduces unnecessary irrigation while maintaining schedule reliability. The system offers a cost-effective, scalable, and intelligent solution for sustainable water resource management in both agricultural and residential irrigation systems.
Efficient irrigation management requires timely responses to soil moisture conditions and anticipated weather changes. This article presents an embedded, weather-based irrigation system that integrates soil moisture monitoring using multiple sensors, edge-based decision-making, automated pump control, and local data ma...
The research shows the potential of the integration of artificial intelligence with low cost embedded platforms to create scalable, water efficient and sustainable smart agriculture solutions.
P. V, Hemapriya· International Journal for Re...· 0 citations
Climate change has increasingly disrupted agricultural productivity in Benin City, Edo State,
Nigeria, manifesting through erratic rainfall patterns, prolonged dry seasons, flooding events,
and rising temperatures. These challenges have significantly affected smallholder farmers who
rely on traditional irrigation me...
I. Okafor· WORLD JOURNAL OF INNOVATION...· 0 citations
Sustainable agricultural water management is increasingly important in arid and semi-arid regions, where limited freshwater resources, climatic variability, and inefficient irrigation practices can constrain long-term food production. This study proposes an intelligent fog–cloud smart irrigation framework that integrat...
Mohammed Balfaqih, Atheer Nagro, Abdulaziz Al-Tuwairqi· European Journal of Sustaina...· 0 citations
Water scarcity and inefficient irrigation remain problems in agriculture. This study developed and tested an IoT-based irrigation system with a mobile application and machine learning prediction for rice paddy water management. Soil moisture, air temperature, and relative humidity sensors were connected to an ESP32 mic...
I. P. A. Arthawan, Anak Agung Adi Wiryya Putra· Journal Mobile Technologies...· 0 citations
Agriculture is one of the major consumers of freshwater, and inefficient irrigation practices can lead to significant water wastage, reduced crop productivity, and increased cultivation costs. Conventional irrigation methods often depend on fixed schedules or manual decisions and may not adequately respond to changing...
M. Rathamani· RCHUB JOURNAL OF COMPUTATION...· 0 citations
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