TIH IIT Bombay SASYAM AI Agrithon
About TIH IIT Bombay
TIH Foundation for IoT & IoE (TIH-IoT) has been setup as a Section-8 company (not-for-profit) by IIT Bombay under the National Mission on Interdisciplinary Cyber-Physical Systems (NM-ICPS), being implemented by the Department of Science and Technology (DST), Government of India. The Technology Innovation Hub for IoT & IoE (TIH-IoT) at IIT Bombay is focusing on creating a self-sustaining innovation continuum by fostering translational research for technology & product development and building highly knowledgeable human resource and a vibrant start-up ecosystem in the technology vertical of Internet of Things (IoT). The goal is to help India become a pioneer in technology-led economic growth and prepare the country to be the world leader in the technology arena.
About SASYAM AI Agrithon
The SASYAM-AI Agrithon is an initiative of TIH-IoT, IIT Bombay, with a focus on building the ML-ready dataset and crop pest–disease detection models, running through the ongoing Kharif and Rabi cropping seasons. The Agrithon aims to provide an opportunity for agriculture and engineering/science students to build the dataset and develop models.
The scheme invites applications from motivated students to contribute towards the development of data and models leveraging AI/ML, computer vision and Gen-AI vision language models for priority crops as follows:
| Kharif Crops | Rabi Crops |
|---|---|
| Bajra (Pearl Millet) | Mustard |
| Black Gram (Urad) | Safflower |
| Soyabean | Pea |
| Sorghum | Masur (Lentil) |
| Green Gram (Moong) | Chickpea |
| Ridge Gourd | Wheat |
| Bitter Gourd | Carrot |
| Maize | Onion |
| Turmeric | Cabbage |
| Cowpea | Cauliflower |
| Ginger | Garlic |
| Sunflower | Fenugreek (Methi) |
| Sugarcane | Custard Apple |
| Cluster Bean (Guar) | Sapota (Chikoo) |
| Rice | Grapes |
| Pigeon Pea | Strawberry |
| Groundnut | Cashew Nut |
| Cotton | Mango |
| Finger Millet (Ragi) | Papaya |
| Kidney Bean (Rajma) | Citrus |
| Okra | Dragon Fruit |
| Tomato | Guava |
| Brinjal | Jackfruit |
| Capsicum | Watermelon |
| Muskmelon | |
| Cucumber |
Eligibility
- The Agrithon is for an individual person with Indian citizenship. Please apply in any one of these categories:
- Category A: For agriculture students: Diploma, B.Sc., M.Sc., or Ph.D. students in agriculture, agriculture technology or allied disciplines.
- Category B: For technology and Science students: ITI, diploma, B.Sc, M.Sc, B.E /B.Tech, M.E /M.Tech, PhD from any discipline.
- Category C: Participants who possess the knowledge of agriculture or allied sciences. Farmers and farm laborers can participate in this drive. The salaried employees from the agriculture domain need to submit an NOC from their employer.
- Any student who is currently availing CHANAKYA Fellowship from TIH-IoT, IIT Bombay will not be able to participate in this Hackathon.
Expectation from Participants
- Participants are expected to dedicate 1 to 2 hours per day for field data collection.
- Visit actual agricultural fields, experimental fields or legitimate crop-growing locations and observe the designated crops.
- Capture the data as per standard data collection procedure (SoPs) generated by TIH-IoT, IIT Bombay.
- Ensure that the submitted photographs are properly identified, classified and validated before submission.
- Submit the photographs and associated information through the official Agrithon submission platform within the stipulated period.
- The classified image data must be submitted weekly to TIH-IoT team.
Training support for data collection:
- After submission of the application form, TIH-IoT team will contact you and share the guidelines for below:
- Detailed SOPs, sample photos, instructional videos, and data collection guidelines will be shared directly with all registered participants.
- Online SOP Training: Online webinars on SOPs covering angle, distance, light intensity, infected region focus, and framing guidelines.
- Offline Hands-on Training: Will be conducted at State Agricultural Universities
Roles / Responsibilities & Award Structure:
| Participants | Deliverables | Award Announcement | Award |
|---|---|---|---|
| Category A (Agri Students) |
2–3 Kharif + 2–3 Rabi crops, covering 1 healthy + 5 unhealthy classes
(1–2 major pests and 2–3 major diseases) per crop. Target: ≥800 validated images/class/crop/month. Validation accuracy: 70–80%. Preferred: 5,000+ images/crop/month. For every season – Kharif, Late Kharif & Rabi (period of 3 months), 15,000+ images per crop/person are expected. |
Nov 2026: Based on Kharif data, submitted between Aug–Oct 2026. Jan 2027: Based on Late Kharif data gathered from Oct–Dec 2026. Mar 2027: Based on Rabi data, gathered from Dec 2026–Feb 2027. |
Top 10 Winners: ₹30K each Next 20 Winners: ₹15K each Top 10 Winners: ₹30K each Next 20 Winners: ₹15K each Top 10 Winners: ₹30K each Next 20 Winners: ₹15K each |
|
Category B (Technology / Engineering / Science, etc. students – any branch / course) |
One Kharif + one Rabi crop, covering 1 healthy + 3 unhealthy classes
(1–2 major pests and 1–2 major diseases) per crop. Target: ≥400 validated images/class/crop/month. Preferred: 2,000+ images/crop/month. Develop VLM & object detection models (using YOLO, ConvNeXt, BLIP, etc.) for the 2 crops. |
Jan 2027: Based on VLM & Object Detection models developed
for Kharif crop data, gathered during Kharif / Late Kharif season. Mar 2027: Based on VLM & Object Detection models developed for Rabi crop data, gathered during Rabi 2026–2027 season. |
Top 10 Winners: ₹30K each Next 20 Winners: ₹15K each Top 10 Winners: ₹30K each Next 20 Winners: ₹15K each |
|
Category C (Participants who possess knowledge of agriculture or allied sciences) |
2–3 Kharif + 2–3 Rabi crops, covering 1 healthy + 5 unhealthy classes
per crop (1–2 major pests and 2–3 major diseases) per crop. Target: ≥1,000 validated images/class/crop/month. Validation accuracy: ≥90%. Preferred: 6,000+ images/crop/month. |
Nov 2026: Based on Kharif data, submitted between Aug–Oct 2026. Jan 2027: Based on Late Kharif data gathered from Oct 2026–Jan 2027. Mar 2027: Based on Rabi data, gathered from Dec 2026–Feb 2027. |
Top 10 Winners: ₹40K each Top 10 Winners: ₹40K each Top 10 Winners: ₹40K each |
The best performer will be announced every month. The award will be given based on the consistent performance in Kharif & Rabi seasons.
Top twenty participants from each category will be eligible for free training on ‘AI/ML technology for image-based crop pest/disease identification’, to be held in Summar season 2027, by TIH IIT, Bombay. Free access to the AI/ML model development platform will be given to the top 50 consistent & best performers after successful completion of all phases.
How to apply
- Applications will only be accepted through the application form (Applications will be considered only after final submission).
- NOC formats category A & B (download and edit).
- Declaration format for category C for self-employed or unemployed (download and edit.)
- NOC format for category C for employed (download and edit).
For more details/ queries about Agrithon, the information webinar has planned Webinar of Agri- Hackthon | Meeting-Join | Microsoft Teams
| Day | Date | Time |
|---|---|---|
| Friday | 21 Aug 2026 | 8:30 am – 9:00 am |
| Tuesday | 25 Aug 2026 | 8:30 am – 9:00 am |
| Monday | 31 Aug 2026 | 5:00 pm – 5:30 pm |
Applications Open
Last Date to Apply – Rolling Call till Rabi 2027
Applications will be considered only after final submission. Saving the form does not complete the submission process.
However, participants should start gathering the data to complete the target.
Disclaimer
Contact
- Dr. Rutuja Chavan, Mob: 8888576577, Email: rutuja.chavan@tihiitb.org
- Mr. Nachiket Deshpande, Mob: 9623324538, Email: Nachiket.Deshpande@tihiitb.org