Revolutionizing Farming Practices with AI and Low-Code Technologies | FarmersSavvy App
Published Jun 14 2023 12:00 AM 5,720 Views
Copper Contributor

Introduction

Agriculture contributes a massive portion of Kenya’s GDP, accounting for 22.43% of gross domestic product (GDP) in 2021, 22.62% in 2020, and 20.86% in 2019. However, the sector has faced various challenges attributed to climate change, supply chain, and, more importantly, lack of information on proper farming practices, raising concerns about farm produce quality.

 

In 2022, it was reported that a Fast-food chain KFC, could not buy potatoes grown by Kenyan Farmers due to quality approval procedur.... It was certain that the quality of farm produce was low due to the farming practices employed by the farmers and the entire supply chain process, including storage practices.

 

Recognizing the need for improved farming practices and information access, a team of four individuals, namely Pius Mutuma, Hillary Kisera, Faith Sylvia Achieng, and Ann Mary Maina, developed FarmersSavvy—an innovative solution aimed at enhancing crop yield and improving the overall quality of farm produce. By leveraging AI and low-code technologies, FarmersSavvy provides farmers with valuable insights and guidance on best farming practices.

 

Technologies Used

 

  • AI Builder: AI Builder is utilized in FarmersSavvy to enable AI image analysis for crop health detection. It was utilized to train images of crops that were frosty, powdery, and healthy. This feature is aimed at helping farmers in identifying potential issues and taking appropriate action.
  • SharePoint: FarmersSavvy integrates with SharePoint, utilizing a SharePoint list for efficient data storage and management. This integration ensures seamless data handling and analysis.
  • PowerApps: PowerApps is another essential application used in the development of FarmersSavvy. It enables the creation of a user-friendly interface, allowing farmers to easily input and retrieve data on their crops. PowerApps simplifies the app development process and ensures accessibility for farmers of varying technological proficiency.

 

Step-by-Step Approach of Building the App

 

  • Problem Identification and Team Formation

The team, comprising Pius Mutuma, Hillary Kisera, Faith Sylvia Achieng, and Ann Mary Maina, recognized the challenges faced by Kenyan farmers, such as low-quality farm produce due to inadequate farming practices. We came together with a shared vision to develop a solution that addresses these challenges.

 

  • Conceptualization and Design:

We envisioned FarmersSavvy as an application that leverages AI and low-code technologies, including PowerApps. We focused on creating an intuitive and user-friendly interface, ensuring that farmers can easily interact with the app to input and retrieve data on their crops.

 

  • Integration of AI Builder, SharePoint, and PowerApps

To enable AI-driven crop health detection, we integrated the AI Builder technology from PowerApps into FarmersSavvy. We developed an AI model capable of analyzing images to detect the health of crops. Furthermore, we utilized SharePoint as a data storage and management solution to streamline data handling.

 

What does this solution offer?

 

  • AI-driven Crop Health Analysis: The app utilizes AI Builder to analyze images of crops and detect their health status. This feature helps farmers identify potential issues such as pests, diseases, or nutrient deficiencies, allowing them to take timely action to protect their crops.

 

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  • Data Management and Analysis: The app integrates with SharePoint, utilizing a SharePoint list for efficient data storage and management. Farmers can easily input and retrieve data on their crops, ensuring accurate record-keeping and streamlined data analysis. This feature enables farmers to track the progress of their crops, identify trends, and make informed decisions based on real-time data.

 

  • Personalized Agricultural Insights: FarmersSavvy provides personalized support and guidance based on AI-driven data analysis. It offers farmers valuable information on best farming practices, including soil preparation techniques, appropriate fertilizer usage, pest and disease management strategies, and optimal harvesting methods. These insights are tailored to the specific needs and characteristics of each farmer's crops.

 

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  • Disease Management and Improved Output: By analyzing farm data and providing real-time insights, FarmersSavvy helps farmers effectively manage diseases and optimize their crop output. The AI-powered analysis enables farmers to monitor crop health, track growth patterns, and identify any abnormalities promptly. With this information, farmers can adjust irrigation schedules, optimize fertilizer application, and implement targeted pest and disease control measures.

 

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  • User-Friendly Interface: FarmersSavvy is designed with a user-friendly interface, making it accessible to farmers of all technological proficiency levels. The app, built using PowerApps, provides a simple and intuitive platform for farmers to input data, access insights, and retrieve recommendations easily. This ensures that even farmers with limited technological experience can utilize the app effectively.

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  • Future Enhancements: FarmersSavvy serves as a foundation for future advancements. The team behind the app envisions incorporating additional features, such as a live chatbot for real-time support and an image analysis automation feature with prompt responses. These enhancements will further streamline the farming process and provide farmers with enhanced tools and resources.

Summary

The success of FarmersSavvy is attributed to the collaborative efforts of the team members, each leveraging their strengths. The comprehensive solution developed by the team addresses the unique needs of farmers, fostering innovation and progress. We have received immense positive feedback on this project, recognizing its potential to address farming challenges effectively. The team intends to further enhance the app by incorporating additional features, such as a live chatbot for real-time support and an image analysis automation feature with prompt responses.

 

Version history
Last update:
‎Jun 12 2023 12:38 PM
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