CASE STUDY

IoT-Driven Precision Farming

  • Artificial Intelligence
  • 8 months ago
IoT-Driven Precision Farming
IoT-Driven Precision Farming

Client:

Our customer is a leading provider of technology solutions to the farming industry.

Industry:

Farming and Agriculture

Background:

The customer specializes in precision agriculture and approached us to develop a solution for predicting Mildew disease in crops. Precision agriculture uses information technology to optimize crop health and productivity. With the increasing demand for food and challenges faced by farmers, such as climate change and limited resources, our customer aimed to provide a proactive disease prediction solution.

Challenges:

  • Developing a cost-effective and efficient solution targeting farmers, with a user-friendly interface.
  • Ensuring the solution is meaningful, easy to use, and accessible for non-tech-savvy farmers.

Solution:

We implemented a precision farming Internet of Things (IoT) solution, capturing data (temperature and humidity) from devices placed on the farm. These devices were interfaced with controllers and sensors. The collected data was then transferred to a web-based application using an external API developed using Laravel.

To address different crop conditions and disease severity, we designed algorithms that could predict the chances of Mildew disease and presented the results in a graphical format. The application also provided guidance for immediate and future decisions, including precise fertilizer recommendations and spraying quantity for the farm.

Result:

Within three months of deployment, our customer witnessed improved crop yield efficiency. The provided solution enabled sustainable growth while reducing costs. The application offered a comprehensive view of crop conditions with real-time data available 24/7. It supported secure and authorized web-based access from anywhere.

Key Takeaways:

  • Precision agriculture and IoT can significantly enhance farming practices.
  • Developing user-friendly solutions tailored to the needs of non-tech-savvy farmers is crucial.
  • Proactive disease prediction and data-driven decision-making can improve crop yield and reduce costs.

Recommendations:

Other players in the farming and agriculture industry can benefit from implementing precision farming solutions like this one. It can help them optimize crop health, increase efficiency, and make informed decisions based on real-time data. Customization based on specific farming conditions and diseases should be considered.

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