Abstract: The Crop Management System (CMS) is an innovative web application designed to revolutionize agricultural practices by integrating advanced technologies. This project encompasses four essential modules: Crop Prediction, Disease Detection, and Government Forum Dashboard. Leveraging the power of Python, the CMS aims to provide a comprehensive solution for modern farming. The Crop Prediction module employs machine learning algorithms to forecast optimal crops based on factors such as soil type, climate, and historical data. This feature empowers farmers to make informed decisions, enhancing crop yield and profitability. The Disease Detection module employs image processing techniques to identify and diagnose diseases affecting crops, allowing for timely intervention and reducing yield loss. The Government Forum Dashboard acts as a central hub for stakeholders to exchange information, policies, and best practices, fostering a collaborative ecosystem. Implemented as a web application, the CMS ensures accessibility across devices, providing a user-friendly interface for farmers and stakeholders. The backend is built using Python, leveraging its versatility and robust libraries for data processing, machine learning, and web development. In conclusion, the Crop Management System addresses critical aspects of modern agriculture, ranging from crop selection to disease management, marketing, and policy advocacy. By harnessing the power of Python and cutting-edge technologies, this project stands as a pivotal tool for advancing agricultural practices, ultimately contributing to sustainable and efficient farming practices.
Keywords: Data Mining, Crop Recommendation system, Resource Optimization, Prediction.
Cite:
Prof. Narode. Priyanka. P., Shelke Kirti R., Salunke Ashlesha V., Nanekar Tejaswini N., Deokar Aditi R.P,"Advancement in Integrated Crop Management System for Sustainable Agriculture", IJARCCE International Journal of Advanced Research in Computer and Communication Engineering, vol. 13, no. 3, 2024, Crossref https://doi.org/10.17148/IJARCCE.2024.133130.
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DOI:
10.17148/IJARCCE.2024.133130
