International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 03 | Mar 2025
p-ISSN: 2395-0072
www.irjet.net
Precision Farming in the Digital Age: Leveraging AI and IoT for Sustainable Crop Management Alen Jose1, Arjun A T2, Bilahari Sagar3, Nufais Basheer4, Shijina.B5, Athira R Kurup6 12345Department of Computer Science and Engineering, TOMS College of Engineering Mattakara, India 4Assistant Professor
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Abstract - Agriculture is important for human livelihoods
to communicate and share data on the Internet. These devices, usually equipped with sensors and software, enable the collection and exchange of real-time information, so that they can respond wisely to the environment. In agriculture, IoT allows smart decisions and improves agriculture practices by integrating data-driven equipment. IoT is widely adopted in agriculture in agriculture because of the ability to solve important challenges and increase different agricultural processes. For example, accurate agriculture uses IoT to adapt resources such as water, fertilizers and pesticides, ensuring efficient and durable agriculture. The soil, weather patterns and surveillance of real time of real-time crops allow farmers to make informed decisions, reduce the risk and maximize the return. In addition, IoT – controlled future analysis equipment helps farmers to estimate challenges such as insect transition or unfavorable climatic conditions, and ensures active measures. The demand to increase global food is inspired by population growth, and further outlines the importance of IoT in agriculture. IoT addresses problems such as lack of resources, unexpected weather and soil, which can greatly affect the crops. Addition agriculture often depends on historical knowledge, lack of accuracy and adaptability provided by real-time data. By integrating IoT, farmers can cross these boundaries, improve resource management, reduce cost and adopt permanent practice to effectively meet future agricultural needs.
and finances, but traditional farming faces challenges such as climate, resources and environmental issues. Accuracy Using technology to increase agricultural production provides a revolutionary solution Reduce environmental impact. Benefit from data -driven techniques, It optimizes inputs such as water, fertilizers and pesticides to improve food quality and important in the midst of production efficiency, which increases the demand for global food. this project A user suggests a friendly application that integrates IoT, AI and machine learning To give real -time insight to farmers. Important features include crops and fertilizers Recommendations, soil monitoring and effective irrigation control, Promote permanent agricultural practices. The purpose of the app is to increase productivity, Resource use and environmental protection, simplify agricultural processes. Key Words: Precision Agriculture, IoT in Farming, Machine Learning in Agriculture, Sustainable Farming, Climate-Resilient Agriculture, Soil Health Monitoring, Crop Recommendation System, Global Food Security, Water Use Efficiency
1.INTRODUCTION It presents an innovative approach to meeting the challenges facing traditional agricultural practices. Along with increasing global demand for food and climate change, a lack of resources and environmental decline, the change in the agricultural sector is strictly decisive by the change solutions. The project proposes a state application that integrates artificial intelligence (AI), Internet of Things (IoT) and Machine Learning (ML) technologies to bring revolution in agriculture. The aim of the application is to provide real time, data -drift insights on soil health, weather conditions, crop recommendations and irrigation control, so that they can adapt resource use, increase productivity and use permanent practice. By taking advantage of advanced technologies, the project tries to bridge traditional agriculture and modern accurate agriculture, strengthen farmers to make informed decisions and contribute to more flexible and durable agricultural axes.
1.2 Problem Definition The demanding situations that the agricultural zone faces are serious and severe, ranging from unpredictable weather conditions to inadequate water assets, deterioration of soils, and attacks through pests, aside from the fluctuations in market fees. All those matters affect productiveness and sustainability. Depending on traditional agricultural practices, often generalized recommendations and manual tracking, diverse agricultural needs are inadequate to meet the dynamic requirements. This AI-PRE procedure Agriculture app is designed to apply these challenges through advanced, customized and actionable insight through advanced post analysis, gadget studies and real-time tracking. These satellite images, climate forecast, soil sensors and historical crops trying to bind facts to adapt to any useful use of resources from total performance, expect risk reducing and decorating the exact crop control. Steps for decisions, future abstinence growth, cost efficiency and
1.1 Background Internet of Things (IoT) is a transformative technique that includes a network of interacted equipment that is able
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