Authors : Dr. Mallika Natarajan; Dr. Benciya Abdul Jaleel

Volume/Issue : Volume 9 - 2024, Issue 5 - May

Google Scholar : https://tinyurl.com/3xcrvj7h

Scribd : https://tinyurl.com/n4aj5ncu

DOI : https://doi.org/10.38124/ijisrt/IJISRT24MAY2340

Note : A published paper may take 4-5 working days from the publication date to appear in PlumX Metrics, Semantic Scholar, and ResearchGate.

Abstract : The agricultural sector in Oman faces challenges in accurately tracking and managing produce quantities in real-time across geographically dispersed locations. This research introduces the CBMIS, an AI-powered Real-time Agricultural Produce Monitoring System. The CBMIS leverages the Internet of Things (IoT) and biometric authentication to capture weight data from farms. This data is then transmitted to a cloud server, providing stakeholders with immediate access to variety-wise stock status. By utilizing AI, the CBMIS can go beyond simple data collection. AI can analyze historical data and market trends to predict future production levels and market demands. This real-time information empowers stakeholders to make informed decisions regarding logistics, sales, and marketing strategies. The CBMIS has the potential to improve inventory management, optimize resource allocation, and enhance overall market efficiency within the Omani agricultural sector.

Keywords : Real Time Data, Cloud Storage, Biometric, Authentication, Fuzzy Weighing Controller.

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