CattleVision

Introduction

CattleVision is an innovative full-stack web platform designed for progressive dairy farmers, veterinary institutes, and cooperative societies. The platform aims to streamline the identification and management of cattle breeds through advanced image recognition technology.

System Overview

CattleVision provides a seamless experience for users to identify cattle breeds by uploading images or using a web-camera stream. The backend processes these images using a fast classification script, leveraging models like ResNet or EfficientNet. The frontend then displays the identified breed along with visual heatmaps to explain the classification decision. The platform is built using FastAPI for the backend and React.js for the frontend.

Functional Requirements

• As a dairy farmer, I should be able to upload an image of a cow or buffalo to identify its breed.
• As a veterinary institute staff, I should be able to use a web-camera stream to capture a photo of cattle for breed identification.
• As a cooperative society member, I should be able to view visual heatmaps that explain the breed classification.
• As a system administrator, I should ensure the platform provides universal access as pre-approved by the API supervisor.

User Personas

• Dairy Farmer: Individuals managing dairy farms who need efficient tools for cattle management.
• Veterinary Institute Staff: Professionals working in veterinary institutes who require accurate breed identification for research and treatment.
• Cooperative Society Member: Members of cooperative societies involved in cattle management and breeding programs.
• System Administrator: Personnel responsible for maintaining the platform's accessibility and performance.

Core User Flows

• Dairy farmer uploads image -> System processes image -> Breed is identified -> Visual heatmap is displayed.
• Veterinary staff uses web-camera -> System captures photo -> Breed is identified -> Visual heatmap is displayed.
• Cooperative member accesses platform -> Views breed identification and heatmap.
• System administrator configures universal access settings -> Ensures platform accessibility.

Visuals Colors and Theme

• primary: #2A9D8F (Teal)
• primary_light: #A8DADC (Light Teal)
• secondary: #E63946 (Coral Red)
• accent: #F4A261 (Sandy Orange)
• highlight: #F4A261 (Amber)
• bg: #F1FAEE (Off White)
• surface: rgba(42, 157, 143, 0.8)
• text: #1D3557 (Dark Blue)
• text_muted: #457B9D (Muted Blue)
• border: rgba(233, 69, 96, 0.2)

Signature Design Concept

The CattleVision homepage will feature an interactive 3D farm landscape using @react-three/fiber and @react-three/drei. Users can navigate through a virtual farm where each section represents a different feature of the platform. For example, clicking on a barn opens the image upload feature, while a pasture leads to the web-camera stream. This immersive experience will engage users and provide an intuitive way to explore the platform's capabilities.

Interaction Model & Motion Direction

The landing page will utilize a "parallax" interaction model, creating a layered depth effect as users scroll through the site. Decorative elements like clouds and birds will move at different speeds, enhancing the storytelling aspect. Internal pages will adopt a "static" model for clarity and ease of use.

Non-Functional Requirements

• The platform must support high availability and scalability to accommodate a growing number of users.
• Ensure data privacy and security for all uploaded images and user information.
• Provide multilingual support to cater to a diverse user base.

Tech Stack

• Frontend: React.js
• Backend: FastAPI (Python)
• Database: MySQL or MariaDB
• AI Models: ResNet or EfficientNet for image classification
• Orchestration: Docker, Kubernetes

Assumptions and Constraints

• The platform assumes users have access to a stable internet connection for uploading images and using web-camera features.
• The system is constrained by the accuracy and speed of the AI models used for breed classification.

Glossary

• Breed Identification: The process of determining the breed of cattle using image recognition technology.
• Heatmap: A visual representation highlighting areas of interest in an image that influenced the classification decision.
• Universal Access: Ensuring the platform is accessible to all users, regardless of device or location.