System Requirements Document (SRD) for Rising-Rover

1. Introduction

The Rising-Rover project is a Smart Agriculture Rover application designed to revolutionize modern farming practices by integrating IoT sensor data, ESP32-CAM image input, and machine learning for crop analysis. This platform aims to provide real-time monitoring, smart irrigation suggestions, crop recommendations, and obstacle alerts, all through a professional-grade SaaS dashboard. The project is tailored for deployment in India (IN), ensuring compatibility with local agricultural needs and environmental conditions.

This document outlines the system requirements for the Rising-Rover project, including functional and non-functional requirements, user personas, visual design, and technical specifications.

2. System Overview

The Rising-Rover system is a modular, production-ready application that combines IoT, AI, and modern web technologies to deliver a comprehensive smart agriculture solution. The system consists of the following components:

1. Frontend: A responsive web application built with React and Tailwind CSS, featuring a modern glassmorphism UI.
2. Backend: A FastAPI-based server that handles REST APIs, WebSocket connections, and ML inference.
3. IoT Integration: Direct connection to Arduino/ESP32 hardware for real-time sensor data and image capture.
4. Machine Learning Module: A Python-based model for crop recommendation and plant health analysis.
5. Database: PostgreSQL for structured data storage and MongoDB for unstructured data like images.

The system is designed to be scalable, modular, and user-friendly, ensuring it meets the needs of farmers, agronomists, and agricultural researchers.

3. Functional Requirements

• As a User, I should be able to view real-time sensor data on a dashboard.
• As a User, I should be able to view a live camera feed from the ESP32-CAM.
• As a User, I should be able to control the rover remotely (e.g., move, start watering).
• As a User, I should be able to view a GPS-based map for rover tracking.
• As a User, I should be able to receive alerts for low moisture levels or obstacles.
• As a User, I should be able to view crop recommendations based on sensor and image data.
• As a User, I should be able to toggle between dark and light modes for the UI.
• As a User, I should be able to view graphs and charts for historical sensor data.
• As a User, I should be able to receive notifications for critical events (e.g., low battery, system errors).

4. User Personas

4.1 Farmer

• Description: Primary user responsible for managing the farm.
• Goals: Monitor crop health, optimize irrigation, and receive actionable insights.
• Pain Points: Lack of real-time data, inefficient irrigation, and crop selection challenges.

4.2 Agronomist

• Description: Agricultural expert providing guidance to farmers.
• Goals: Analyze data trends, recommend best practices, and ensure sustainable farming.
• Pain Points: Limited access to accurate field data and difficulty in providing timely advice.

4.3 Researcher

• Description: Academic or industry professional studying agricultural trends.
• Goals: Collect and analyze data for research purposes.
• Pain Points: Lack of integrated platforms for data collection and analysis.

5. Visuals Colors and Theme

Color Palette

• Primary: #2A9D8F (Emerald Green)
• Primary Light: #A8DADC (Light Aqua)
• Secondary: #E63946 (Crimson Red)
• Accent: #F4A261 (Vibrant Orange)
• Highlight: #FFD166 (Golden Yellow)
• Background (bg): #F1FAEE (Soft White)
• Surface: rgba(42, 157, 143, 0.8) (Semi-transparent Emerald)
• Text: #1D3557 (Deep Navy)
• Text Muted: #457B9D (Muted Blue)
• Border: rgba(69, 123, 157, 0.2) (Subtle Blue)

6. Signature Design Concept

Concept: "Interactive Smart Farm Dashboard"

The homepage will feature an interactive 3D farm environment built using @react-three/fiber and @react-three/drei. Users will navigate a virtual farm where:

• Rover Path Visualization: A 3D rover moves along a simulated path, highlighting real-time GPS data.
• Sensor Data Hotspots: Clicking on specific areas (e.g., soil patches, plants) will display sensor data in pop-up cards.
• Dynamic Weather Effects: Real-time weather conditions (e.g., rain, sun) will be simulated based on live data.
• Interactive Rover Control: Users can drag and drop waypoints on the 3D map to control the rover's movement.

Animations will include smooth transitions, hover effects, and spring physics using framer-motion. The design will captivate users while providing a functional, data-rich experience.

7. Interaction Model & Motion Direction

Interaction Model: Parallax

The landing page will use a parallax scrolling effect to create depth and engagement. Layers will include:

• Background: Animated clouds and sun.
• Midground: 3D farm elements like crops and irrigation systems.
• Foreground: Interactive rover and sensor data overlays.

Motion Direction

• Scroll-triggered animations: Sections will reveal with fade-ins and slide-ins.
• Hover effects: Buttons and cards will scale slightly with a shadow effect.
• Spring physics: Interactive elements like the rover control panel will have springy, tactile feedback.

8. Non-Functional Requirements

• Performance: The system must handle up to 100 concurrent users with minimal latency.
• Scalability: The backend should support horizontal scaling to accommodate future growth.
• Security: Data must be encrypted in transit (HTTPS) and at rest.
• Usability: The UI must be intuitive and accessible, adhering to WCAG 2.1 standards.
• Reliability: The system should have 99.9% uptime.

9. Tech Stack

Frontend

• React with Vite
• Tailwind CSS
• Framer Motion
• Chart.js

Backend

• FastAPI
• PostgreSQL
• WebSocket for real-time updates

IoT Integration

• Arduino Mega
• ESP32-CAM

Machine Learning

• Python
• Scikit-learn or TensorFlow Lite

Deployment

• Docker
• Kubernetes (optional for scaling)

10. Assumptions and Constraints

• The system assumes reliable internet connectivity for real-time updates.
• IoT hardware must be pre-configured with WiFi credentials.
• The ML model will provide generalized crop recommendations, not region-specific advice.

11. Glossary

• IoT: Internet of Things
• ESP32-CAM: A low-cost camera module with WiFi capabilities.
• FastAPI: A modern web framework for building APIs with Python.
• JWT: JSON Web Token, used for authentication.
• WCAG: Web Content Accessibility Guidelines.