Wireless Sensor networks (WSNs) are greatly applied in agriculture practices for sense farm inputs like fertilizers, irrigation requirements, pesticides and environmental parameters. These parameters are processed and analyzed to determine the right amount of farm inputs for managing and improving c
Precision Farming
Wireless Sensor networks (WSNs) are greatly applied in agriculture practices for sense farm inputs like fertilizers, irrigation requirements, pesticides and environmental parameters. These parameters are processed and analyzed to determine the right amount of farm inputs for managing and improving crop yield. Our project focuses on feature detection using machine learning classifiers by employing Raspberry Pi as base station for in-situ sensors in field. Following is the frame work of our proposed project:
(https://drive.google.com/file/d/1cABYmqoZv1H57SVPTpXVb_9Gi6j6mxR8/view?usp=sharing)
To synthesis the theorotical and practical skills learns during BE.
To introduce automation and technolgies at low cost to farmng
To design feature extraction system for crop identification
Feature detection using machine learning classifiers by employing Raspberry Pi as base station for in-situ sensors in field. Following is the frame work of our proposed project:
(https://drive.google.com/file/d/1cABYmqoZv1H57SVPTpXVb_9Gi6j6mxR8/view?usp=sharing)
Farm Autoamation and better descisions for crop managemnt and imrovment.
To learn to manage technical project
Feature detection using machine learning classifiers by employing Raspberry Pi as base station for in-situ sensors in field. Following is the frame work of our proposed project:
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Rapsberry Pi | Equipment | 4 | 10000 | 40000 |
| Raspberry Pi Camera | Equipment | 4 | 5000 | 20000 |
| SD Card for Raspberry PI | Equipment | 4 | 1500 | 6000 |
| Miscellaneous | Miscellaneous | 1 | 10000 | 10000 |
| Raspberry Pi Power Source | Equipment | 4 | 500 | 2000 |
| Total in (Rs) | 78000 |
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