| Idea Name: |
Smart Agri Vision |
| Slogan: |
Eat healthy, stay healthy |
| Supervisor Name: |
Dr. Rafia Mumtaz |
| Supervisor Designation: |
Associate Professor |
| Supervisor School: |
SEECS |
| Supervisor Department: |
School of Electrical Engineering and Computer Science |
| Contact number: |
0342 5563343 |
| Email ID: |
[email protected] |
| Abstract: |
| The proposed system uses real-time image processing along with state-of-the-art deep learning classification techniques to detect crops' health. |
| What is the unmet need in society that your idea will fulfill ? |
| Currently, there is no system to detect wheat rust levels in Pakistan. As a result, farmers spray on whole wheat fields and wheat natural health drops. By using our system, farmers can detect wheat rust severity levels. So spray with respect to rust level. |
| Who needs it ? How many would benefit ? |
| Our proposed system is used by farmers or landlords to detect wheat rust and its severity. They can save wheat crops and their natural nutrition. |
| How will the solution works |
| Our proposed system is used to capture pictures of wheat leaves with help of a camera in a specific format by our prototype or can upload it on our web portal. After that segmentation is used to remove background from leaves of wheat. Finally, a deep learning model is used to detect wheat rust severity levels and suggestion is given by our system. |
| Who are your competitors ? How is your solution different |
| There are other systems available that provide partial services compared to the proposed system like Background removal. Our system improves upon those systems by providing a full-fledged image pre-processing system and wheat rust detection using DL thus giving us an edge in the market. |
| Status: |
new |
| Entry Date & Time: |
2021-12-15 (1526) |
