AgriSense Soil and Pest Solutions using Deep Learning

Agriculture is a vast domain. It contributes to over 24% of the Gross Domestic Product (GDP) of Pakistan [1]. According to research almost 45% of world population depends on agriculture for its livelihood [2]. Since agriculture is such a broad sector it has several type

Project Title

AgriSense Soil and Pest Solutions using Deep Learning

Project Area of Specialization

Artificial Intelligence

Project Summary

Agriculture is a vast domain. It contributes to over 24% of the Gross Domestic Product (GDP) of Pakistan [1]. According to research almost 45% of world population depends on agriculture for its livelihood [2]. Since agriculture is such a broad sector it has several types of different problems. So, in our project we have focused on providing solution to two areas of agriculture: soil and pests.

AgriSense is a Mobile Application which aims to deliver a common platform as a network of farmers to share their experiences to solve problems effectively which they confront during cultivation process related to soil and pest.

When the farmers face agricultural problems, they apply their own limited knowledge to find solution to that problem. AgriSense will use machine learning to detect the pests and soil to advice medicine and prevention techniques. For this purpose, the farmer has to click an image of the concerned area of their field and upload it with the description explaining the issue, and the app then can share insights and will propose the use of most impactful medicine or methods for that problem. The data of soil and pest problems used in ML will obtained from crowed sourcing. Further-more the application will be able to aid the cultivators by informing them about which type of crop is best suitable for their particular type of soil to get maximum growth.

[1] https://www.pbs.gov.pk/content/agriculture-statistics#:~:text=â??Agriculture constitutes the largest,source of foreign exchange earnings.

[2] https://www.sciencedirect.com/topics/social-sciences/agricultural-population

Project Objectives

The project aims to provide a platform to farmers where they can get help from experts and find best solution and prevention methods to their problem. Not only will the farmers get the solutions to their problems but also suggestions about which types of crops they should cultivate based on their soil type, for making more benefit.

Project Implementation Method

There are two types of problems on which the app will focus soil problems and pest problems. The data will be gathered through crowd sourcing and will be categorized in the stated problems. The expert farmers will share their experiences and knowledge to solve the issues of other farmers. More-over if maximum number of expert users will agree to a proposed solution, that solution will be rated as effective for that problem. After the solution is rated as effective it will be sent for training to the deep learning model, when the data is trained the system will be able to answer the questions posted by the famers on its own. There will be a machine learning model trained by available dataset to help farmers with the selection of crops to cultivate based on their soil type.

Benefits of the Project

Benefits of Project:

• A proper platform to find solutions to soil and pest problems: The famers will have a common platform to share their queries and knowledge and help each other in finding solutions to newer problems.

• Soil-Crop Relevancy: Farmers will get to know about which crops are suited to which soil types.

• The farmers will carry out their farming without any alarm: When the farmers have a solution to their problems, they will not hesitate to cultivate rather they will tend to seed more crops.  

• The solution is bound to help increase the yield of he crops: After the soil is nutritious and the pest are treated, the land and crops will produce more.

• The Greater the Yield the Greater the Economy:The abundant crops will meet the consumption requirement of the nation whereas the additional crops may be exported to other countries, as the exports rise, and the imports fall the economy of the country will boost. 

Technical Details of Final Deliverable

Prototype: An interactive user-interface and complete look of the mobile application.

Frontend: The product which the end-user will interact with. 

Backend (Micro-services): Storage, retrieval, updating and deletion of data will be possible on request of the users.

API Integration: With the integration of frontend with backend, the application will become dynamic and user will be able to deal with real data.

Training Machine Learning Model: A feature which will enable farmers to know which crops they should cultivate based on their soil type for maximum profit.

Developing and Training Deep Learning Model: The application will be able to answer farmer's queries on its own using the previously answered solution of expert users and deep learning algorithm.

Testing the Complete Application: Testing the application will help identifying the hidden bugs or errors.

Hosting Backend Services:  The application will be available as a final product to everyone.

Final Deliverable of the Project

Software System

Core Industry

IT

Other Industries

Agriculture

Core Technology

Artificial Intelligence(AI)

Other Technologies

Cloud Infrastructure

Sustainable Development Goals

Decent Work and Economic Growth, Industry, Innovation and Infrastructure

Required Resources

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