The farmer-friendly app won accolades and first prize at the National-level Hackathon conducted by COHORT in Hyderabad
KARIMNAGAR, APRIL 07, 2025: The digital technologies such as machine learning (ML), the Internet of Things (IoT), Artificial Intelligence (AI), Robotics, drones and machine vision are playing a significant role in modernising Indian agricultural processes. These technologies have the potential to revolutionise the agricultural sector by optimising resource utilisation, enabling precision agriculture, and improving productivity, efficiency and sustainability.
Freshly, the students of Jyothishmathi Institute of Technology and Sciences (JITS), Karimnagar, viz Ajith – IV Year, CSE A, Akshith – IV Year, CSM A and Ramesh – IV Year, CSE C, presented a project AI Crop Care, an AI-powered solution to detect crop diseases and promote sustainable farming practices, at the National Level Hackathon conducted at COHORT, Hyderabad. The students secured first prize among the 92 competing teams and were awarded a cash prize of ₹10,000, certificates, and event T-shirts for their outstanding performance. Event was organised by Cohort Hyderabad and SRM Institute of Science and Technology, Ramawaram, Chennai, Tamil Nadu state.
The team under the guidance JITS CSE HoD R Jegadesan developed an advanced agricultural solution integrating IoT and deep learning to empower farmers with real-time insights and smart decision-making. Utilizing Raspberry Pi sensors, the system continuously monitors temperature, soil moisture, and environmental conditions, ensuring optimal crop health. The deep learning-based disease detection feature enables early identification of plant diseases through image analysis. Additionally, our system offers AI-driven irrigation recommendations, optimizing water usage and improving yield efficiency. With agriculture news updates and market insights, farmers stay informed about the latest trends and government policies, fostering sustainable and technology-driven farming practices.
The solution consists of three key components: the sensor module, the AI-based disease detection module, and the mobile application. The sensor module, powered by Raspberry Pi, is deployed in the farmer’s field to continuously monitor temperature, soil moisture, and other environmental parameters, enabling farmers to make informed decisions regarding irrigation and crop health. The AI-based disease detection module allows farmers to capture crop images using their mobile device, which are then analyzed by a deep learning model to detect potential diseases early, helping in preventive action and reducing crop losses. The mobile application acts as the central hub, displaying real-time sensor data, weather updates, agriculture news, and government policy updates. This integrated system empowers farmers with technology-driven insights, enhancing productivity, reducing risks, and optimizing resource usage for more efficient and sustainable farming.
The students used the following technology viz 1. IoT: Raspberry Pi: Serves as the primary microcontroller, collecting real-time sensor data. Temperature and Soil Moisture Sensors: Monitor environmental conditions to assist in irrigation management. 2. Cloud Services: MongoDB Atlas: Stores sensor data and user inputs for easy access and retrieval. • Android Studio’s Default Cloud Storage Bucket: Used for storing images captured for disease detection. 3. Deep Learning: • TensorFlow/Keras: Pre-trained deep learning models are used to detect plant diseases from captured images. 4. Backend Development: • Flask: The AI disease detection model is deployed using Flask to process images, monitoring environments and return results 5. App Development: • Flutter: The mobile app is made using Flutter.
