The AI in Farming project is developed as a smart AI solution using computer vision for quick and cost-effective livestock weight and breed estimation. Traditional livestock scales are bulky, expensive, and not portable. This project simplifies the process, making it easy for livestock trading by providing accurate information with a mobile solution. With this innovative mobile computer vision system, users will be able to obtain this information quickly and efficiently, streamlining the livestock trading process. 

The client needs a cost-effective solution for farmers to monitor the health of their livestock without expensive scales. They wanted to improve productivity and accuracy for butcher shops and meat processors, reducing errors in weight estimates. Their requirement was also to assist consumers in making informed livestock purchases and promote better animal care by providing accurate weight and breed identification for growth tracking and medication dosage. 

• Image Capture: Users can easily capture images of cow using their mobile phones, providing visual data for the AI solution Application. 

• Online Image Upload: Users can conveniently upload the captured image to the AI solution through an online web API, ensuring seamless data transfer from their mobile devices. 

• Decision-Enhancing Results: The AI solution processes the uploaded image and provides users with valuable information to make decisions based on the data extracted through computer vision i.e: Weight and Breed.

The client sought a Smart AI solution with computer vision that could provide information about animals without relying on large weighing scales. Our approach began with a thorough understanding of the client’s requirements, and we crafted a well-defined plan with clear objectives and timelines.  

Our dedicated team of developers employed top-notch tools and technologies, including Python, Tensorflow, and both iOS and Android platforms. They trained an algorithm to recognize crucial details such as livestock breed, height, weight, and other vital information. To facilitate user interaction, we developed iOS and Android apps, allowing end-users to input new livestock images for predictive analysis. 

Despite encountering challenges along the way, we successfully delivered a solution that aligned with the client’s needs within specified timeline. Testing was conducted to ensure the system’s flawless operation. In the end, we developed a Smart AI solution with computer vision that precisely met the client’s requirements handling various types of animal information.

• Data Quality: Ensuring accurate training data for the AI model was a challenge. 

• Algorithm Training: Fine-tuning the model for animal feature recognition was mandatory for proper Algorithm training. 

• User-Friendly Interface: It was a prime task of the developers to design an easy-to-use app. 

• Integration: The integration process is carefully handled combining computer vision with mobile apps. 

• Performance: It was challenging to maintain performance by ensuring quick and correct results.