Major chunk of Pakistan?s economy is agriculture based. Improving the productivity of agriculture farms is very important for the overall growth of the economy. This productivity is heavily dependent on using the right machinery at the right time in farms, in a cost-effective manner. According to a
Authenticating use of Agriculture Machinery using Data Analytics and AI
Major chunk of Pakistan’s economy is agriculture based. Improving the productivity of agriculture farms is very important for the overall growth of the economy. This productivity is heavily dependent on using the right machinery at the right time in farms, in a cost-effective manner. According to a survey conducted by Agriculture Department Government of Punjab, 47% of agriculture machinery is under-utilized in the Punjab Province. In Pakistan, state-of-art technology needs to be deployed to smartly utilize the available farm machinery. Which could drastically increase the production of our farms and have a positive impact on our economy.
In this project, we are proposing a smart system where the machinery owners would be able to rent out their under-utilized machinery to a recipient in need of it. We are using state of art technology including Internet-of-Things (IoT), Cloud, Data Analytics and Artificial Intelligence (AI) for efficient resource allocation and authentication of the rented machinery.
The system comprises of two mobile applications interfaced with the IoT module and a cloud based architecture maintaining a database, AI scripts are also deployed on cloud. The Data from IoT that is placed on the agriculture machinery is collected via a smartphone and sent over to cloud, where it is analyzed and processed through the AI algorithms. We are able to determine the accurate work area of machinery, the duration of work, classify the implement type and perform other analysis. Figure below provides an overview of the project.

The first step is to develop a recipient mobile app which would enable the user to select the available resources after logging in. The app is interfaced with an already built IOT module. IOT module is placed on the agriculture machinery. The IOT module would be Bluetooth enabled that would send data via Bluetooth to the smartphone. The smartphone app collects the data. The data would then be transferred to cloud via WIFI/3G/4G technology.
The data sent to the cloud will show.
The data is stored in a cloud based data store such as AWS S3. The AI models for achieving the objectives as mentioned above are trained on a local machine and the trained model is deployed on cloud.
The process would then be stream lined on cloud where upon each entry in S3, the data is imported and pre-processed. The pre-processed data would be passed to the trained AI scripts which would store the result in a DB service. The AI module would be made available as an API using cloud services like API Gateway. After which we could call the API from web, mobile app etc.

1. Service Provider Mobile Application
The Service Provider with available machinery would be able to rent out his machinery using the service provider mobile application.
2. Service Recipient Mobile Application
The Service Recipient would be able to look for available machineries nearby and reserve a machinery. This Application would also be interfaced with the IoT placed on machinery for data collection.
3. Cloud Architecture
A database of all services and records would be deployed on cloud. The cloud services would also help streamline the data collection process. The AI module will be deployed on cloud and the Web portal would also be hosted on it.
4. AI Module
The AI module is the core of the system which would enable the authentication process of rented machinery, by measuring precise work area, determining the number of runs on a field, classifying the machinery implement type and generate a bill based on the calculated values.
5. Web Portal / Dashboard
On one of the web portal, the administrator will be able to see how and where the farm machinery is used.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| TI 2056 IoT Sensor Tag | Equipment | 6 | 8000 | 48000 |
| Cloud Resources (S3, Lambda, RDS) | Equipment | 1 | 10000 | 10000 |
| IoT Packaging/PCB | Equipment | 6 | 2000 | 12000 |
| Data Collection, Printing, Stationary, Overheads etc | Miscellaneous | 1 | 10000 | 10000 |
| Total in (Rs) | 80000 |
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