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Student Project | Agricultural Studies | India | Volume 13 Issue 1, January 2024 | Rating: 5.4 / 10
IoT Based Smart Irrigation System Using Weather Forecasting
Nitesh Yadav
Abstract: Agriculture sustains a significant portion of the global population, and Punjab, India, renowned for its farming activity, heavily relies on this sector for livelihoods. Groundwater, a vital freshwater resource, is extensively used for irrigation, contributing substantially to agricultural productivity. However, traditional irrigation practices have led to challenges such as water wastage, environmental degradation, and crop damage. This paper introduces a groundbreaking "Smart Irrigation System Using Weather Forecasting" to address these challenges. Leveraging Arduino Uno and NodeMCU with sensors (DHT11, soil moisture, LDR, raindrop), the system enables real - time data acquisition. Two relays, one interfaced with Arduino Uno and the other with NodeMCU, facilitate manual and remote control via the Blynk app. LEDs provide visual feedback on water levels, soil moisture, and rainfall status. The system integrates an innovative Weather app fetching real - time data from OpenWeatherMap. A Statistical Weather feature predicts rainfall probabilities, crucial for regions facing issues like untimely rain after ground irrigation, leading to water wastage and crop damage, as observed in Punjab, India. This project aims to optimize water usage, improve crop yield, and contribute to environmental sustainability. Utilizing statistical weather datasets, a machine learning model predicts optimal watering times, addressing critical challenges in water resource management. The user - friendly design, with remote monitoring and control, makes it a valuable advancement in smart agriculture. The research presents a holistic solution to global water scarcity concerns, offering an innovative approach to sustainable and efficient water management in agriculture.
Keywords: agriculture, smart irrigation, Punjab, India, water management
Edition: Volume 13 Issue 1, January 2024
Pages: 930 - 936