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Plant and Soil Health Analyzer: An AI-Driven Web- Based Agricultural Decision Support System
Authors
1 2 3 4 5 Department. Of Computer Science Engineering, Rajarajeshwari College of Engineering, Bengaluru, Karnataka, India.
Article Information
- Published In
- Volume 5, Issue 6 (2025)
- Published Online
- November-December 2025
- Pages
- 212-218
- Article Type
- Original Article
References
[1] S. P. Mohanty, D. P. Hughes, and M. Salathé, "Using Deep Learning for Image-Based Plant Disease Detection," Frontiers in Plant Science, vol. 7, pp. 1419, 2016.
[2] J. Smith, A. Brown, and L. Johnson, "Drone-based Crop Surveillance and Monitoring," IEEE Transactions on AgriTech, vol. 12, no. 3, pp. 112–119, 2018.
[3] H. Patel, R. Kumar, and P. Sharma, "IoT-Enabled Smart Agriculture: Soil Nutrient Monitoring and Analysis," International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE), vol. 7, no. 5, pp. 2362–2369, 2019.
[4] V. Raj and A. Mehta, "AgroAI: Smart Crop Recommendation System Using Soil Data and Climate Patterns," Elsevier - Computers in Agriculture, vol. 8, no. 2, pp. 85–95, 2020.
[5] K. Kumar, R. Singh, and P. Verma, "Precision Agriculture: An Integrated Approach Using IoT, Drones, and AI," Journal of Agricultural Informatics, vol. 9, no. 4, pp. 25–36, 2021.
[6] TensorFlow Documentation. "TensorFlow: An End-to-End Open- Source Machine Learning Platform." Available at: https://www.tensorflow.org/
[7] OpenCV Documentation. "Open Source Computer Vision Library." Available at: https://opencv.org/
[8] Arduino IDE Documentation. "Arduino Software Development Environment." Available at: https://www.arduino.cc/
[9] PlantVillage Dataset. "Open Access Dataset for Plant Disease Detection." Available at: https://plantvillage.psu.edu/
[10] Government of India. "Soil Health Card Scheme." Ministry of Agriculture & Farmers Welfare, 2020. Available at: https://www.soilhealth.dac.gov.in
[2] J. Smith, A. Brown, and L. Johnson, "Drone-based Crop Surveillance and Monitoring," IEEE Transactions on AgriTech, vol. 12, no. 3, pp. 112–119, 2018.
[3] H. Patel, R. Kumar, and P. Sharma, "IoT-Enabled Smart Agriculture: Soil Nutrient Monitoring and Analysis," International Journal of Innovative Research in Computer and Communication Engineering (IJIRCCE), vol. 7, no. 5, pp. 2362–2369, 2019.
[4] V. Raj and A. Mehta, "AgroAI: Smart Crop Recommendation System Using Soil Data and Climate Patterns," Elsevier - Computers in Agriculture, vol. 8, no. 2, pp. 85–95, 2020.
[5] K. Kumar, R. Singh, and P. Verma, "Precision Agriculture: An Integrated Approach Using IoT, Drones, and AI," Journal of Agricultural Informatics, vol. 9, no. 4, pp. 25–36, 2021.
[6] TensorFlow Documentation. "TensorFlow: An End-to-End Open- Source Machine Learning Platform." Available at: https://www.tensorflow.org/
[7] OpenCV Documentation. "Open Source Computer Vision Library." Available at: https://opencv.org/
[8] Arduino IDE Documentation. "Arduino Software Development Environment." Available at: https://www.arduino.cc/
[9] PlantVillage Dataset. "Open Access Dataset for Plant Disease Detection." Available at: https://plantvillage.psu.edu/
[10] Government of India. "Soil Health Card Scheme." Ministry of Agriculture & Farmers Welfare, 2020. Available at: https://www.soilhealth.dac.gov.in
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