Agriculture production is one of the pillars in our society to provide food and reduce the poverty and hunger. Pakistan is at present the 6th largest country across the globe to produce dry date fruit. Pakistan generates good revenue from the business of selling Dry Date Fruit locally as well as glo
Dry Date Fruit Classification Using Robotic
Agriculture production is one of the pillars in our society to provide food and reduce the poverty and hunger. Pakistan is at present the 6th largest country across the globe to produce dry date fruit. Pakistan generates good revenue from the business of selling Dry Date Fruit locally as well as globally, but unfortunately, still, traditional techniques are being used from pre-harvesting to post-harvesting. Because of traditional methods of business in this field, the industry is unable to meet the requirement of the market as per the latest trends prevails globally. Now as days technology has proven its importance for all aspects of life to support human beings in many ways to reduce not only the excessive human efforts but also causes the increased profit rate for any business. Robotization for Dry Date Fruit is proposed in this project to be used in the agriculture sector to maximize production. In Pakistan, still, there is no such datasets available for dry date classification decision’s purpose, and neither system developed for the support of the industry. Three different kinds of dry date fruit datasets will be developed for meeting the objective and development of the system of this proposed project. This system will support to industry for the processing of classification of date fruit prior to the pit stage.
To develop a dataset of dry date fruit of Aseel & Fasli.
To develop a model for the classification of dry date fruit.
To train and test the model.
To validate the model in a real environment for classification using robotic hardware.
After the development of a model, it will be tested in a real environment for validation purposes. This project will be implemented in Khajoor(Date) industry for classification. It is consists of different hardware components that perform an autonomous task.
It will be an autonomous hardware-based classification system, which supports the industry to meet the demand of the market.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Raspberry PI 4 Model B (4 Gb) | Equipment | 1 | 16000 | 16000 |
| Raspberry PI 5MP camera NoIR Camera Module | Equipment | 1 | 4800 | 4800 |
| 6 DOF Robot metal alloy arm | Equipment | 1 | 12000 | 12000 |
| Mechanical Robotic Claw/Gripper | Equipment | 2 | 650 | 1300 |
| Mg996R servo motors | Equipment | 6 | 580 | 3480 |
| Class 10 32GB ultra micro SD card | Equipment | 1 | 1400 | 1400 |
| Jumper wires(M to M, M to F, F to F) | Equipment | 6 | 130 | 780 |
| Micro HDMI cable | Equipment | 1 | 500 | 500 |
| HDMI to HDMI cable | Equipment | 1 | 500 | 500 |
| Power supply for raspberry pi | Equipment | 1 | 450 | 450 |
| Total in (Rs) | 41210 |
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