ARCHIVES
Original Article
BGrow: An AI-IoT Enabled Collaborative Digital Platform for Smart Agricultural Investment & Monitoring
Dr.TC Manjunath1
Prathiksha M2
Purnachandra B N3
Rohan R Sindhe4
M. Vinod Kumar5
1 Professor & Dean Research, Department of Computer Science and Engineering, Rajarajeswari College of Engineering, Bangalore, Karnataka, India. 2 3 4 5 Department of Computer Science and Engineering, Rajarajeswari College of Engineering, Bangalore, Karnataka, India.
Published Online: September-December 2025
Pages: 328-337
Cite this article
↗ https://www.doi.org/10.59256/indjcst.20250403051
References
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2. P. Alves, A. Valente, and R. Campos, “Digital-twin-based irrigation management system for water saving,” Computers and Electronics in Agriculture, vol. 210, pp. 1–12, 2023.
3. X. Chen, Y. Sun, and Q. Liu, “AI-driven testing and debugging framework for complex intelligent systems,” IEEE Access, vol. 11, pp. 14523–14534, 2023.
4. L. Gao, H. Zhang, and Y. Zhang, “OpenCV-based real-time monitoring and surveillance system,” International Journal of Computer Applications, vol. 182, no. 10, pp. 25–31, 2018.
5. M. S. Alam, A. Rahman, and M. Hossain, “IoT-based robot monitoring system for remote agricultural environments,” International Journal of Advanced Computer Science and Applications, vol. 12, no. 4, pp. 67–74, 2021.
6. K. Akilan, R. S. Babu, and V. Reddy, “Design of IoT-enabled surveillance platform for hazardous environments,” International Journal of Emerging Technologies in Engineering Research, vol. 8, no. 7, pp. 12–18, 2020.
7. Y. Wu and C. Deng, “Wireless distributed sensing for environmental monitoring using ZigBee networks,” Sensors, vol. 19, no. 14, pp. 1–15, 2019.
8. J. Park, S. Kim, and E. Lee, “Development of a cost-efficient autonomous monitoring robot for agricultural applications,” IEEE Transactions on Automation Science and Engineering, vol. 17, no. 4, pp. 1634–1646, 2020.
9. F. Silva, C. Santos, and M. Souza, “GPS and imaging-based real-time environmental monitoring for smart-forest ecosystem management,” Sustainable Computing: Informatics and Systems, vol. 23, pp. 91–101, 2019.
10. A. Al-Mamun, H. Zahir, and R. Khan, “Wireless IoT monitoring framework for industrial and agricultural systems,” International Journal of Distributed Sensor Networks, vol. 16, no. 6, pp. 1–12, 2020.
11. P. V. Reddy, S. Srinivas, and R. Kumar, “IoT enabled smart agriculture monitoring system using cloud computing,” IEEE International Conference on IoT and Applications (ICIOT), pp. 1–6, 2022.
12. S. Kaur and A. Gulati, “A machine learning based crop recommendation system for precision agriculture,” International Journal of Recent Technology and Engineering, vol. 9, no. 3, pp. 112–118, 2021.
13. R. Gupta, M. Jain, and S. Chatterjee, “Blockchain-based secure agri-supply chain management for transparent transactions,” IEEE Access, vol. 9, pp. 73015–73028, 2021.
14. D. Patel and P. Sharma, “Cloud-based agricultural data analytics platform for farmer decision support,” International Journal of Scientific & Technology Research, vol. 10, no. 2, pp. 450–455, 2021.
2. P. Alves, A. Valente, and R. Campos, “Digital-twin-based irrigation management system for water saving,” Computers and Electronics in Agriculture, vol. 210, pp. 1–12, 2023.
3. X. Chen, Y. Sun, and Q. Liu, “AI-driven testing and debugging framework for complex intelligent systems,” IEEE Access, vol. 11, pp. 14523–14534, 2023.
4. L. Gao, H. Zhang, and Y. Zhang, “OpenCV-based real-time monitoring and surveillance system,” International Journal of Computer Applications, vol. 182, no. 10, pp. 25–31, 2018.
5. M. S. Alam, A. Rahman, and M. Hossain, “IoT-based robot monitoring system for remote agricultural environments,” International Journal of Advanced Computer Science and Applications, vol. 12, no. 4, pp. 67–74, 2021.
6. K. Akilan, R. S. Babu, and V. Reddy, “Design of IoT-enabled surveillance platform for hazardous environments,” International Journal of Emerging Technologies in Engineering Research, vol. 8, no. 7, pp. 12–18, 2020.
7. Y. Wu and C. Deng, “Wireless distributed sensing for environmental monitoring using ZigBee networks,” Sensors, vol. 19, no. 14, pp. 1–15, 2019.
8. J. Park, S. Kim, and E. Lee, “Development of a cost-efficient autonomous monitoring robot for agricultural applications,” IEEE Transactions on Automation Science and Engineering, vol. 17, no. 4, pp. 1634–1646, 2020.
9. F. Silva, C. Santos, and M. Souza, “GPS and imaging-based real-time environmental monitoring for smart-forest ecosystem management,” Sustainable Computing: Informatics and Systems, vol. 23, pp. 91–101, 2019.
10. A. Al-Mamun, H. Zahir, and R. Khan, “Wireless IoT monitoring framework for industrial and agricultural systems,” International Journal of Distributed Sensor Networks, vol. 16, no. 6, pp. 1–12, 2020.
11. P. V. Reddy, S. Srinivas, and R. Kumar, “IoT enabled smart agriculture monitoring system using cloud computing,” IEEE International Conference on IoT and Applications (ICIOT), pp. 1–6, 2022.
12. S. Kaur and A. Gulati, “A machine learning based crop recommendation system for precision agriculture,” International Journal of Recent Technology and Engineering, vol. 9, no. 3, pp. 112–118, 2021.
13. R. Gupta, M. Jain, and S. Chatterjee, “Blockchain-based secure agri-supply chain management for transparent transactions,” IEEE Access, vol. 9, pp. 73015–73028, 2021.
14. D. Patel and P. Sharma, “Cloud-based agricultural data analytics platform for farmer decision support,” International Journal of Scientific & Technology Research, vol. 10, no. 2, pp. 450–455, 2021.
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