AgroVision Analytics is a modern frontend-only Agritech Analytics SaaS dashboard designed to help farmers, researchers, and agricultural organizations monitor farm conditions through beautiful data visualizations and actionable insights.

The platform converts raw agricultural sensor data into an intuitive dashboard that enables users to understand soil conditions, crop health, and environmental trends at a glance.

The application is built entirely on the frontend using realistic mock datasets and focuses on delivering an exceptional user experience with responsive design, interactive charts, and clean analytics.

• Beautiful analytics dashboard
• Responsive KPI cards
• Interactive charts
• Smart insights
• Live status indicators
• Responsive grid layout
• Animated components

Monitor:

• Current Moisture
• Historical Trends
• Weekly Analysis
• Monthly Analysis
• Field Comparison
• Moisture Health Indicators

Track:

• Current Temperature
• Daily Trends
• Weekly Trends
• Monthly Trends
• Maximum Temperature
• Minimum Temperature
• Average Temperature

Visualize:

• Nitrogen Levels
• Phosphorus Levels
• Potassium Levels
• Nutrient Comparison
• Soil Fertility Score

Includes:

• Line Charts
• Area Charts
• Bar Charts
• Pie Charts
• Radial Charts
• Trend Graphs
• Comparison Charts
• Progress Indicators

All charts are interactive and responsive.

Optimized for:

• Desktop
• Laptop
• Tablet
• Mobile

Features:

• Clean SaaS design
• Beautiful spacing
• Professional typography
• Smooth animations
• Responsive components
• Reusable UI system

Includes dedicated pages for:

• My Profile
• Account Settings
• Farm Access
• Notification Preferences

Generate analytics reports using frontend mock data.

Features:

• Report cards
• Summary widgets
• Data visualization
• Export UI

Configure:

• Measurement Units
• Alert Thresholds
• Farm Preferences
• Notification Settings

• React
• TypeScript
• Vite
• Tailwind CSS

• Lucide React
• Framer Motion
• Recharts
• Zustand

• Zustand

• Framer Motion

• Recharts

.
├── assets/
├── .aistudio/
├── src/
│   ├── components/
│   │   ├── common/
│   │   ├── dashboard/
│   │   └── profile/
│   │
│   ├── data/
│   ├── layouts/
│   ├── store/
│   ├── types/
│   ├── utils/
│   │
│   ├── App.tsx
│   ├── index.css
│   └── main.tsx
│
├── .env.example
├── .gitignore
├── bun.lock
├── index.html
├── metadata.json
├── package.json
├── tsconfig.json
└── vite.config.ts

• KPI Cards
• Summary Cards
• Quick Statistics
• Health Overview

• Moisture History
• Daily Trends
• Weekly Trends
• Monthly Trends
• Field Comparison

• Current Temperature
• Temperature Trends
• Heat Alerts

• Nitrogen
• Phosphorus
• Potassium

• Analytics Reports
• Performance Summary
• Historical Analysis

• Units
• Alert Thresholds
• Preferences

The application uses realistic frontend mock data.

Data includes:

• Soil Moisture
• Temperature
• Nitrogen
• Phosphorus
• Potassium
• Soil Health Score
• Sensor Status
• Alert Levels

No external APIs or databases are used.

• Improve agricultural decision making
• Simplify farm monitoring
• Visualize agricultural data
• Create intuitive analytics dashboards
• Deliver responsive user experiences

✔ Desktop

✔ Laptop

✔ Tablet

✔ Mobile

• Professional SaaS Dashboard
• Premium Card Design
• Interactive Charts
• Responsive Sidebar
• Beautiful Navigation
• Animated Components
• Modern Forms
• Consistent Design System

• Fast Vite Development
• Optimized React Components
• Lazy Rendering
• Responsive Charts
• Lightweight UI

This application is completely frontend-based.

Data is generated using realistic mock datasets.

No:

• Backend
• Database
• Authentication
• External APIs
• Cloud Services

Suitable for:

• Smart Farming
• Precision Agriculture
• Agricultural Research
• Farm Monitoring
• Educational Demonstrations
• Agritech Dashboards

git clone https://github.com/your-username/agrovision-analytics.git

cd agrovision-analytics

npm install

npm run dev

npm run build

npm run preview

Screens include:

• Landing Page
• Analytics Dashboard
• Soil Moisture
• Temperature Analytics
• NPK Dashboard
• Reports
• Settings
• User Profile
• Account Settings
• Farm Access
• Notification Preferences

• Live IoT Integration
• AI Crop Health Prediction
• Weather Forecast Integration
• Satellite Imagery
• Farm Mapping
• Multi-language Support
• Offline Support
• Progressive Web App
• Data Export (CSV/PDF)
• Role-Based Authentication

Vijay Kumar

Computer Science Engineering Student

This project is developed for educational and frontend development purposes.