KISAN PAKISTAN

Precision agriculture is revolutionizing the concept of smart farming in the entire world. Smart and precise agriculture is the key to producing the best yield of crops. The major portion of the agrarian community is illiterate worldwide, which is unaware of smart farming and intelligent. Our resear

Project Title

KISAN PAKISTAN

Project Area of Specialization

Internet of Things

Project Summary

Precision agriculture is revolutionizing the concept of smart farming in the entire world. Smart and precise agriculture is the key to producing the best yield of crops. The major portion of the agrarian community is illiterate worldwide, which is unaware of smart farming and intelligent. Our research is a bridge between agricultural research and computer technologists. Our proposed framework will reflect an intelligent and secure system equipped with related sensors; wireless communication systems implanted in farms. Hardware will integrate with the android application (prototype) to manage to plant in farms. Plus a web interface to manage knowledge of the latest crops and already feed crops knowledgebase of a system by admin end. Our project is to create a repository to store crop data (knowledgebase) and to get sensed data for decision-making. Guidelines will be provided via an interactive interface for illiterate users. According to the UN Food and Agricultural Organization (FAO), the global population is set to reach 10 billion by the year 2050. Therefore, internationally, agriculture is seeing rapid adoption of Artificial Intelligence (AI), leverage big data, Internet of Things (IoT) and Machine Learning (ML) in terms of agricultural products and in-field farming techniques. In this context, Pakistani farmers need the latest technologies to get information about weather patterns, seeds, pesticides, problems facing their peer group, latest prices, updates, and farming related banking services. 

Literacy is one of the hurdles to adopt the latest technologies. In Pakistan and other developing countries, farmer’s experience does matter to grow the crops, which leads to the loss of production. Therefore, Precision Agriculture is failed due to illiteracy. The other issue is the communication gap between agricultural researchers and technology researchers. Both are working and providing advancements in their own domains neither the concern about the awareness of farmers. This research will be a bridge between agricultural research and computer technologists. Our underlying work is for illiterate farmers to provide all types of agriculture-related support to their doorstep.  We need a system that guides/answers to the following question of illiterate farmers.

• Which crops are suitable to plant for a specific type of soil?
• Which are the best cultivation practices for specific crop and soil?
• Which are suitable and best pesticides and fertilizers for a crop?

In this context, our research question is

“To what extent illiterate farmers can be benefited by a smart system?” 

Followings are the three phases of the project:

Phase - I: Applied research on different crucial agricultural issues

Phase - II: Performance optimization by mobile app

Phase – III: System Integration

Project Objectives

According to the UN Food and Agricultural Organization (FAO), the global population is set to reach 10 billion by the year 2050. Therefore, internationally, agriculture is seeing rapid adoption of Artificial Intelligence (AI), leverage big data, Internet of Things (IoT) and Machine Learning (ML) in terms of agricultural products and in-field farming techniques. In this context, Pakistani farmers need the latest technologies to get information about weather patterns, seeds, pesticides, problems facing their peer group, latest prices, updates, and farming related banking services.

The project is planned to analyze the existing techniques through the development of new Artificial Intelligence-based experimentation followed by improvements to ultimately design and develop systems. 

The objective of the project is to create a repository of all the data to make decisions. This will be achieved by Artificial Intelligence, Internet of things (IoT) and wireless communication networks. The main objectives are:

1. To investigate the traditional techniques.
2. To study and analyze the soil factors for fertility.
3. To recommend the best suitable crops for specific soil.
4. To suggest a suitable time to cultivate a specific crop, time for seeding and harvesting.
5. To study and analyze the disease symptoms to provide a solution online.
6. To study and analyze, the types of fertilizers.
7. To study and analyze the weather patterns.
8. To design a Prototype (mobile app).
9. To analyze, the farming results grounded by the Prototype (evaluation).
10. To update (re-designing) prototype if the results will not be improved.
11. To provide a platform to market agricultural products.
12. To develop a mechanism of secure transportation and traceability of agricultural products.
13. To support illiterate farmers a live network will be the build-up for their guidance in any agriculture problem.

Project Implementation Method

The goal of this research is to disseminate agricultural information to illiterate farmers according to their mental model. A community-based website will be designed where daily based updates will be shared. These automatic updates will be sent to the e-boards at the field office in the form of images/pictures and on their cell phones to stay updated with current updates.

First Part: The envisioned system gets real-time values using sensors implanted in farms to make recommendations about planting, seeding, irrigations, fertilizer, pesticides, cultivation and which plants to be grown. The fortitude of soil nutrients determination regularly in the agricultural field is difficult due to manual testing in laboratories. It causes the negligence of the farmers about the nutrient level in the soil and improper use of fertilizer at the inappropriate time. Soil fertility is measured on the basis of soil macro elements Nitrogen (N), Phosphorus (P) and Potassium (K) and micro-nutrients like Ca, Mg, Fe, etc. PH probe will be implanted as a detection sensor in soil under observation for cultivation. We tested many soil samples to measure micro and macronutrient contents using a pH probe and we concluded that soil pH is a characteristic that diagnoses the qualified acidity or alkalinity. Soil is considered acidic for a pH of below 5, and very acidic for a pH below 4. Contrariwise, the soil is considered alkaline above a pH of 7.5 and very alkaline above a pH of 8. Similarly, for a pH 7 soil is neutral that reflects ideal fertility for soil. Environmental factors like soil moisture, humidity and temperature, the intensity of light and meteorological factors will be captured by implanted sensors. The sensed data from sensors will be stored on the server for analyzing the present condition of the soil. Microcontroller grabs data from sensors and transmits to a web server where rule base analysis is performed to match between predefined conditions and the current state of plants grabbed through sensors. A Fuzzy rule-based engine works on this real-time collected data to compare and match between knowledgebase data. After mapping the conditions to rules the average plant's feasibility rating is generated. Generated results are then shaped up in the form of recommendations for farmers on the app dashboard. 

Second Part: By implementing such a setup in a user-friendly environment even an illiterate user can use/entertain technological services in the field of agriculture simply by signing in (himself or by assistance of officials) an online web community which will be updated with all useful data/information and that will be interconnected with the e-boards at union-council/field office and also by getting the information via cell phones in the form of picture messages and national/local/international language.

Benefits of the Project

The outcomes of this project will clearly provide the illiterate farmers with the deficiency of major soil nutrients namely nitrogen, phosphorous and potassium (NPK) along with micronutrients. Our underlying system will recommend the best suitable crops and fertilizers for a specific land by determining soil fertility level. Experimental simulations will be carried out to understand the functionality and precision of the intended system. From a pilot study carried out, it is clear that the proposed system is a low cost, equipped with precision, accuracy and intelligent IoT based system that intimates the uneducated farmer about the fertilizer to be used at right time automatically via mobile app, SMS, E-portal. It will be used as a helping tool for the farmers in agricultural activities in an interactive way and for high yielding of crops too. The prototype will help illiterate farmers to make a decision on the followings: 

1. Soil Report
   • Analyzing the soil quality
   • Choosing the crop for that soil
2. Weather Pattern
   • General Pattern of the weather
   • Weather forecast pattern
3. Seeding
   • Selection of seeds according to the soil and water requirement
   • Determine the number of fertilizers and pesticides based on soil
4. Cultivation
   • The decision on tillage and type of fertilizers
   • Timing of water to be given and the number of pesticides
5. Disease Solution
   • Disease Symptoms
   • Frequency of pesticides
6. Harvesting
   • Determine the harvesting method
   • Storage Requirement

Technical Details of Final Deliverable

The Proposed Recommender System gets real-time values by sensors implanted in user farms to make recommendations about suitable crops to grow, fertilizers, pesticides, and irrigations to put recommendations. Microcontroller grabs data from sensors and transmits to the web servers (fog nodes) where rule base analysis will perform to match between predefined conditions and the current state of crops grabbed through sensors. After mapping, the conditions to rules the average feasibility of a specific crop will generate. Then values of sensors will be processed on the server and a list of crops with their feasibility will be sent to the user’s mobile app. From where users can decide and schedule the planting process of crops in farms where they implanted the sensors setup.

 Our research is a bridge between agricultural research and computer technologists. Our proposed framework will reflect an intelligent and secure system equipped with related sensors; wireless communication systems implanted in farms. Hardware will integrate with the android application (prototype) to manage to plant in farms. Plus a web interface to manage knowledge of the latest crops and already feed crops knowledgebase of a system by admin end. Our project is to create a repository to store crop data (knowledgebase) and to get sensed data for decision-making. Guidelines will be provided via an interactive interface for illiterate users.

Experimental Setup

Hardware devices and sensors composed of the system are listed below.

• Micro-controller (Arduino Built-in wifi)
• Microcontroller (Arduino MEGA)
• Arduino starter kit
• Arduino GSM Shield 2 (Antenna Connector)
• Battery, Charging wire, jumper wire( f 2 f), customize jumper wires
• Humidity/Temperature Sensor (DHT11)   
• Bluetooth Module
• Light Intensity Module (digital)
• Soil moisture Sensor
• Arduino project case box
• pH Sensor
• Sensor Poles

Final Deliverable of the Project

HW/SW integrated system

Core Industry

IT

Other Industries

Agriculture

Core Technology

Internet of Things (IoT)

Other Technologies

Artificial Intelligence(AI)

Sustainable Development Goals

Decent Work and Economic Growth

Required Resources

If you need this project, please contact me on contact@adikhanofficial.com