Department of Computer Engineering, Thakur College of Engineering and Technology, Mumbai, India.
International Journal of Science and Research Archive, 2026, 19(02), 1116-1124
Article DOI: 10.30574/ijsra.2026.19.2.1128
Received on 02 APril 2026; revised on 13 May 2026; accepted on 15 May 2026
Agriculture could be a very critical field and act as a key contributor to the enhancement of the food security, especially in countries like India, where many people depend on farming. Sometimes crops get sick, and we no longer detect until it is too late. We also do not always have access to experts who can help us. This can lead to financial losses for the farmers. To remedy those problems, we created a tool that uses artificial intelligence to anticipate crop diseases and help prevent them. This device uses an algorithm called Convolutional Neural Network, which is visualized with images of crop leaves to detect diseases. The program has layers that help it identify what diseases look like, what colors and textures to look for. This helps the device detect the disorder of a crop, even when it is miles just started. When the device detects a disorder, it gives us records such as what signs are there that may have caused it, and how to address it. We also made it so that people who are not comfortable with computer systems can use it. The device can communicate with us in our languages, so farmers can get help even if they no longer speak the equivalent language, like the computer. We tried to use the machine. It worked well. It can help farmers make choices and not lose as many plants. By detecting diseases and providing accurate recommendations, the tool makes it easier for farmers to develop larger meals. Maybe one day we can add tools to the toolkit to help farmers even more, such as tools to display the climate.
Smart Agriculture; Crop Disease Prediction; Convolutional Neural Network; Deep Learning; Image Processing; Voice Assistance
Preview Article PDF
Kiran Patil and Harshali Patil. Smart crop disease prediction and preventive management. International Journal of Science and Research Archive, 2026, 19(02), 1116-1124. Article DOI: https://doi.org/10.30574/ijsra.2026.19.2.1128.






