AI-powered Real-time Agricultural Produce Monitoring System for Improved Inventory Management and Market Efficiency in Oman


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

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.

References :

  1. A Comprehensive Study of Using Internet of Things (IOT) in Monitoring System for Smart Agriculture. Sajadul Hassan Kumhar, Shaik. Mohammad Rafi, Ayan Das Gupta, V. Prakash, Mudasir M Kirmani, Surendra Kumar Shukla Proceedings ArticleDOI  ,28 Apr 2022  
  2. Agricultural Inventory Management System. Hakan, Erden. (2015).   doi: 10.1109/AGRO-GEOINFORMATICS.2015.7248152
  3. Jinbo, Chen., Ye, Huang., Pengxiao, Xia., Yuying, Zhang., Yu, Zhong. (2019). Design and implementation of real‐time traceability monitoring system for agricultural products supply chain under Internet of Things architecture. Concurrency and Computation: Practice and Experience, doi: 10.1002/CPE.4766
  4. Agriculture monitoring system based on internet of things by deep learning feature fusion with classification  K. Sita Kumari a, S.L. Abdul Haleem b, G. Shivaprakash c, M. Saravanan d, B. Arunsundar e, Thandava Krishna Sai Pandraju f Computers and Electrical engineering , Volume 102, September 2022, 108197
  5. Edan Y, Han S, Kondo N. Automation in agriculture. In: Nof S, editor. Springer Handbook of Automation. Berlin, Heidelberg: Springer Berlin Heidelberg; 2009. pp. 1095-1128. DOI: 10.1007/978-3-540-78831-7_63
  6. Samaleswari, Prasad, Nayak., Satyananda, Champati, Rai., Biswajit, Sahoo. (2022). SAW: A real-time surveillance system at an agricultural warehouse using IoT.   doi: 10.1016/b978-0-12-823694-9.00001-3
  7. Anil, A., Kumar. (2022). Keynote Speech: Application of Artificial Intelligence (AI)in Supply Chains.   doi: 10.1109/iccmso58359.2022.00012
  8. Yanhong, Wu. (2022). Intelligent Information Processing System in Supply Chain Management Applications.   doi: 10.1109/AIoTCs58181.2022.00063
  9. Cláudia, Maria, Iannelli-Servín. (2022). Intelligent Information Processing System in Supply Chain Management Applications.   doi: 10.1109/aiotcs58181.2022.00063
  10. Morgan, Eldred., Jim, Thatcher., Abdul, Rehman., Ivan, Gee., Abhijith, Suboyin. (2023). Leveraging AI for Inventory Management and Accurate Forecast – An Industrial Field Study.   doi: 10.2118/214457-ms
  11. Role of AI in the Inventory Management of Agri-Fresh Produce at HOPCOMS. Advances in finance, accounting, and economics book series, doi: 10.4018/978-1-6684-4483-2.ch008 (2022)
  12. (2023). The Efficacy of Artificial Intelligence in making Best Marketing Decisions.   doi: 10.1109/icidca56705.2023.10100132
  13. Abhijit, Chirputkar., Pratik, Ashok. (2023). The Efficacy of Artificial Intelligence in making Best Marketing Decisions.   doi: 10.1109/ICIDCA56705.2023.10100132
  14. Brindusa, Covaci,, Radu, Brejea,, Mihai, Covaci. (2023). Artificial Intelligence and Financial Markets. Computational social sciences, doi: 10.1007/978-3-031-26518-1_1
  15. Pravalika, N., Sapnil, Dutta., N., P., Deshpande., Md, Wasim, Akhtar., Dr., Anusha, Preetham. (2022). Analysis of Market Obligation Using AI: A Survey. International Journal of Engineering Research in Computer Science and Engineering, doi: 10.36647/ijercse/09.10.art009
  16. Sagarika, Mishra., Michael, Thomas, Ewing., Holly, Cooper. (2022). Artificial intelligence focus and firm performance. Journal of the Academy of Marketing Science, doi: 10.1007/s11747-022-00876-5
  17. Shaktija, Singh, Baghel., Poonam, Negi, Rawat., Rajesh, Singh., Shaik, Vaseem, Akram., Shweta, Pandey., AishwaryVikram, Singh, Baghel. (2022). AI, IoT and Cloud Computing Based Smart Agriculture.   doi: 10.1109/IC3I56241.2022.10072567
  18. Kalra, M., & Singh, S. (2015). A Review of Metaheuristic Scheduling Techniques in Cloud Computing. Egyptian Informatics Journal, 16(3), 275-295.
  19. Gangwar, H., Date, H., & Ramaswamy, R. (2015). Understanding Determinants of Cloud Computing Adoption Using an Integrated TAM-TOE Model. Journal of Enterprise Information Management, 28(1), 107-130.
  20. Asghari, S. & Navimipour, N. (2016). Review and Comparison of Meta-Heuristic Algorithms for Service Composition in Cloud Computing. Majlesi Journal of Multimedia Processing, 4(4).

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.

Never miss an update from Papermashup

Get notified about the latest tutorials and downloads.

Subscribe by Email

Get alerts directly into your inbox after each post and stay updated.
Subscribe
OR

Subscribe by RSS

Add our RSS to your feedreader to get regular updates from us.
Subscribe