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Paper ID:IJSREM63522

AGRO-TECH

Stream/Area:

-

Subject:

-

Paper ID:

IJSREM63522

Volume:

10 |

5 |

May 2026

Pages:

1-3

Publication Frequency:

Monthly (12 issues per year)

DOI
Digital Object Identifier
10.55041/IJSREM63522

License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

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Authors

Jeevitha A V

Jeevitha A V

Department of Computer Science & Engineering (AI&ML)

Rajeev Institute of Technology

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Rakshith B R

Rakshith B R

Department of Computer Science & Engineering (AI&ML)

Rajeev Institute of Technology

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Ankith V S

Ankith V S

Department of Computer Science & Engineering (AI&ML)

Rajeev Institute of Technology

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Rakshitha M

Rakshitha M

Department of Computer Science & Engineering (AI&ML)

Rajeev Institute of Technology

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Mentors

Kannika Lakshmi D G

Kannika Lakshmi D G

Department of Computer Science & Engineering (AI&ML)

Rajeev Institute of Technology

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Abstract

Agro-tech is an integrated mobile solution developed using Android Studio and Firebase Console that seeks to offer a safe and efficient computing environment for farm monitoring and predictive analytics. The system is meant for use by farmers, researchers, and agribusiness firms interested in adopting modern technology in agriculture through the use of a user-friendly interface and technical prowess to revolutionize traditional and labor-intensive agricultural processes. With the help of Firebase Cloud Functions in machine learning processes and Real-time Database in proper data management, the platform ensures high levels of accuracy and efficiency in disease detection and harvest prediction. In addition to that, the Agro-tech system makes modern agriculture more effective by providing real-time monitoring, disease detection, and yield predictions for crops based on artificial intelligence. The use of cloud services and Firebase helps the system provide relevant information and make decisions effectively and securely.

KEYWORDS

Key words: Agriculture Machine Learning Mobile App Android Studio Firebase Console.

Cite This Article

Jeevitha A V, Rakshith B R, Ankith V S, Rakshitha M, Kannika Lakshmi D G, "AGRO-TECH," International Journal of Scientific Research in Engineering and Management, vol. 10, no. 5, pp. 1-3, May 2026. https://doi.org/10.55041/IJSREM63522

Full Article/Conclusion

The proposed Agro-tech solution makes it possible for interested parties to monitor farming activities from afar, making sure that site visits become unnecessary in the process. Reliability, speed, and flexibility in monitoring crops is provided. The solution significantly reduces manual work and paperwork by providing quick solutions to problems such as weed and disease management. This is a total solution that ensures accuracy and efficiency in farming practices. Further, Agro-tech is a platform that ensures sustainable and data-driven farming through the use of technologies like machine learning and cloud computing. This technology assists farmers in making sound decisions on matters relating to crop health, irrigation, and productivity, thus increasing efficiency in agriculture and minimizing expenses incurred during farming activities. It features a user-friendly interface and an automated process.

References

[1]. Professor Raut S. Y. et al., "Safe Digital Management Systems Based on Centralized Database," Vol. 3, Issue 5, May 2017. [2]. K. Ramesh et al., "From Conventional Approaches to Safe Digital Ones," Vol. 2, Issue 3, 2023. [3]. Anand A. and Divya P., "A Comprehensive Online Management System for Efficient Resource Distribution," International Journal of Modern Engineering Research, Vol. 2(4), 2631–2634, 2019. [4]. M. A. Imran and H. Rahman, "Recognition Systems and their Use in Data Management," International Journal of Computer Applications, Vol. 118, No. 5, May 2015. [5]. Alexander. J, "Stakeholders Centralized Digital Architectures," IEEE: Control Engineering and Computing, 14(1):22-26, April 2003. [6]. K. P. Kaliyamurthie, R. Udayakumar, D. Parameswari, and S. N. Mugunthan, "Highly Secured Data Systems over Networks," Indian Journal of Science and Technology | Print ISSN: 0974-6846 | Online ISSN: 0974-5645, Vol. 9, 2018. [7]. Swaminathan, B., and Dinesh, "Advanced Scientific Research and Technology: Multi-security using Biometrics," Vol. 2(2), 195–203, 2018. [8]. R. Sharma, S. Gupta, and P. Verma, "Mobile-Based Weed Identification and Management: A Real-Time Approach," International Journal of Agricultural Science and Technology, Vol. 5, Issue 2, June 2024. [9]. J Smith and L Brown, "Real-time Livestock Health Monitoring using Cloud Integration and Firebase Systems," Journal of Veterinary Technology and Informatics, Vol. 8, Issue 1, March 2023.

Editorial & Review Transparency

Publication Date

5/19/2026

Peer Review Type

Double-Blind Peer Review

Review Rounds: 2

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