AI-Powered Interactive Multimodal Vision system for Agriculture Applications
AI in Agriculture
Project description
The lack of cultivation space is the major hindrance to the progression of food quantity. To address this challenge, the project aims to develop an AI-powered crop monitoring system in an indoor environment that would leverage multimodal data information to deliver a transformational approach for proactive plant health evaluation. This will help growers take preventive actions, reduce disease-induced plant damages, increase the yield, and reduce the overall labor cost for the business operation in parallel.
Project outcome
Prototype product & publication.
Project details
| Length of commitment | Around a year |
| Start time | Fall (August/September) Summer (May/June) |
| In-person, remote, or hybrid? | Hybrid Project |
| Level of collaboration | Individual student project |
| Benefits | Students may be selected for RA position, based on their performance |
| Who is eligible | Juniors & Seniors |
Core partners
- Prof. Jinjun Xiong (CSE)
jinjun@buffalo.edu
Project mentor
Sreyasee Das Bhattacharjee
Assistant Professor of Research & Training
Computer Science & Engineering
Phone: (716) 645-4769
Email: sreyasee@buffalo.edu
Start the project
- Email the project mentor using the contact information above to express your interest and get approval to work on the project. (Here are helpful tips on how to contact a project mentor.)
- After you receive approval from the mentor to start this project, click the button to start the digital badge. (Learn more about ELN's digital badge options.)
Preparation activities
Once you begin the digital badge series, you will have access to all the necessary activities and instructions. Your mentor has indicated they would like you to also complete the specific preparation activities below. Please reference this when you get to Step 2 of the Preparation Phase.
Reading literature, programming for prototype building and deploying, and writing reports
Keywords
Computer Science and Engineering (CSE), AI, Machine Learning, Data Analytics, Intelligent machine, Agriculture & Computer vision