Pak Agri-IoT (Pakistan Agriculture-Internet of Things) Smart Farming Based Decision Support System for Optimum Crops Yield

Project Title

Pak Agri-IoT (Pakistan Agriculture-Internet of Things) Smart Farming Based Decision Support System for Optimum Crops Yield

Project Area of Specialization Internet of ThingsProject Summary

Agriculture in Pakistan is the main source of food and exports, whereas, it lacks the use of Smart Farming and right cultivation techniques. This is important to overcome the related problems, like pests and disease control, land preparation, effective irrigation, fertilizer utilization and observation of crop condition.  Proposed project aims to overcome the said problems by providing the remote sensing unit integrated with cloud and android application for enablement of precision agriculture thus improving productivity and increase in yields and profitability.       Currently the information about the progress of crops is collected manually and there is no centralized national database. Centralized national database where the progress of crops can be collected from the deployed sensors in real-time followed by solid policy decisions is a necessary requirement. Therefore, there exist a need of Solar Powered Real-time Monitoring system in smart decision making utilized for optimal yield. Therefore, this project aims to develop Agri-IoT (Agriculture-Internet of Things) using remote units and android application to collect real-time data for processing, and analysis to improve the overall farming operations and management.

Hardware Requirements:

Temperature and humidity sensor:

   This sensor is basically a cost efficient digital humidity & temperature sensor. This sensor supplies digital output and therefore can be directly connected to data pins of microcontroller in spite of using ADC.

Water Level Sensor:

Water level sensor, otherwise called drift balls, are round, tube shaped, have a place or correspondingly melded items, produced using either unbending or adaptable material, that are light in water and different fluids.

Ph Sensor:

The availability of nutrients is as essential to plant growth as it is to animals and livings organisms. In optimizing a plant's growth potential and yielding highly productive harvests

GPS sensors:

Typically associated with the automotive and cellular communication industries, GPS sensors are also advantageous to smart agriculture.

Cameras:

The application of (smart) cameras for process control, mapping, and advanced  imaging  in agriculture  has  become an  element  of precision  farming  that  facilitates  the conservation  of  fertilizer,  pesticides,  and  machine  time

Software Requirements:

Cloud and data base layer:

Data from multiple sensors will be collected and database according to the types of crop and geographical location will be developed. This data base will be updated in realtime.

Android/IOS Layer:

An Android App Will be created with English and Urdu Versions. (App will have login restrictions such as Master-Slave method). After the data collection, the overall data will be gathered in cloud and transferred to the mobile app through cloud. 

Project Objectives

This project has diverse scope as it introduces the modern technology in the area of agriculture. Advancement in the agriculture sector will directly raise the economy of Pakistan which will put Pakistan on the road of stability.

The main objectives of this project are as follow

• Development of remote sensing unit of Agri-IoT that will be deployed in the field of interest.
• Development of Online data base to store the data from multiple nodes and its integration with online services like
  • Weather forecast
  • Crops observation
  • GPS and location-based services
• Development of IOT based Solar powered sensors to collect agriculture/Farm data and maximize the yield of crops
• Development of cloud based android application which will fetch and use the real-time data for processing and analysis/.
• Cloud Based Database which will include the data of farms, historical weather data of the region, crops and optimal requirements to enhance the productivity of crop cycle.
• Development of Basic logic based Decision support system software at the cloud which will take into consideration the available data from sensors, impact of weather patterns and accordingly provide suggestions, irrigation and alarms needed for optimal yield for each site.

Project Implementation Method

The project implementation will be divided into following modules as shown in Table

No.	Project Modules	Description of Implementation Layers
1	Field Instrumentation Layer	WIFI based solar power modules Water proof Temperature sensor, Soil moisture sensor, PH sensor, Pressure sensor, Humidity sensor, CO2 detection sensor, Nitrogen, phosphorus, potassium sensor, LDR sensor, Tilt sensor, Piezo sensor, Solar panel Backup battery, GPS module Back Up battery LCD Display This module will be developed in collaboration with local industry and university researchers
2	Cloud and Data base layer	• Data from multiple sensors will be collected and database according to the types of crop and geographical location will be developed. This data base will be updated in realtime
3	Android/IOS Layer	An Android App Will be created with English and Urdu Versions. (App will have login restrictions such as Master-Slave method)  Sensors are placed in farms at different places that will gather the data from the soil. After the data collection, the overall data will be gathered in cloud and transferred to the mobile app through cloud.  As a result, the director can check the update of crop at their own place at any time and monitor the farmer’s working and process.

No.

1

2

3

Benefits of the Project

• Automation boosts efficiency, with smart devices, and multiple processes that can be activated at the same time gives direct access to data from field sensor.
• Use for leverage precise forecasting. So that we maximize the yield information of past data of farm and historical weather data of the fields.
• IoT technology helps better control agricultural processes to reduce production risks and enhances the ability to foresee production result by making farming more connected and precision agriculture helps to reduce overall costs and improve the quality and quantity of product.
• As per survey the IOT in agriculture will increase about to 20% annually. At the same time, the global smart agriculture market size is expected  to triple by 2025, reaching $15.3 billion.
•  The expected outcome of our project would be a Decision support system for crops yield using remote sensing unit (WIFI/GSM) with a support of hardware that will be a solar pole and  will take into considerations the available data from sensors, GPS module, LCD display and cameras.

Technical Details of Final Deliverable

The IOT based Monitoring framework will be based on an integrated Android based decision Support System comprising of integrated Sensors, Networking, Cloud and Decision Support layers to provide suggestions and alarms needed for optimal yield. 

The deliverable of this project will provide the condition of the crop detected from the circuit of various sensors in a mobile application. The humidity sensors and temperature sensors check the physical condition of crop and write in the app with the location of that fields. For location tracing we have implemented the GPS sensor in our hardware. When the app get notified by the present conditions, the conditions will then compared by the optimum conditions of that crop and hence show the results whether it have to harvest, need more water or fertilizer etc.   The IOT based Monitoring framework will be based on an integrated Android based decision Support System comprising of integrated Sensors, Networking, Cloud and Decision Support layers to provide suggestions and alarms needed for optimal yield.

Final Deliverable of the Project HW/SW integrated systemCore Industry ITOther IndustriesCore Technology Internet of Things (IoT)Other TechnologiesSustainable Development Goals Decent Work and Economic GrowthRequired Resources

Elapsed time in (days or weeks or month or quarter) since start of the project	Milestone	Deliverable
Month 1	Research and Survey for System Requirements	Literature Review and Product Feasibility report
Month 2	Planning of hardware	prototype model
Month 3	Pole Creation	Installation of hardware and gathering information
Month 4	Development of online database system	Transferring data and integration of data with online system
Month 5	Decision Support System	Designing android app
Month 6	Integration of hardware and software	Final Integrated System
Month 7	Testing and improvisation	Working model
Month 8	Documentation	Final Report