Smart Irrigation System

SystemThis project explores the development of an innovative Smart Irrigation System (SIS) aimed at enhancing water efficiency in agriculture. With Lebanon’s agricultural sector facing challenges such as water scarcity and inefficient resource management, the proposed system leverages the Internet of Things (IoT) and machine learning to offer a more sustainable solution. The system integrates soil moisture sensors, temperature and humidity sensors, and weather data APIs to provide real-time irrigation scheduling, aiming to reduce water waste and optimize crop production.

The system’s design incorporates solar-powered components, ensuring energy efficiency and sustainability. Through the use of a Raspberry Pi controller, the system collects and analyzes environmental data, automatically adjusting irrigation cycles based on soil and weather conditions. The backend architecture is supported by machine learning algorithms that predict irrigation needs, allowing the system to adapt to various agricultural settings and crop types. A web-based interface was developed for easy monitoring and control, providing farmers with a user-friendly tool to manage their irrigation systems remotely.

The successful implementation of the prototype demonstrated the potential of IoT solutions in addressing agricultural inefficiencies. In addition to offering cost-effective water management, the system’s adaptability can contribute to environmental sustainability and food security. This paper outlines the design, implementation, and evaluation of the system, discussing its technical features, testing results, and potential applications in Lebanon and similar agricultural regions.

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Project Details

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