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AgriPulse β Real-Time Precision Agriculture Dashboard
Project Overview
- Project Title: AgriPulse β Real-Time Precision Agriculture Dashboard
- Domain: Agritech
- Technology Stack: Java 17, Spring Data JPA, MySQL, HTML, CSS, React
- Duration: 3 Weeks
Project Description
AgriPulse is a smart agriculture dashboard that provides real-time visualization and monitoring of key environmental parameters such as temperature, humidity, soil moisture, and light intensity using IoT sensor data. This web-based platform allows farmers and agronomists to make informed decisions about irrigation, fertilization, and crop health, promoting sustainable and precision farming. The system supports live alerts, historical analytics, and customizable charts for each field or sensor zone.
Key Objective
- Visualize real-time sensor data from the field (temperature, humidity, moisture, etc.).
- Enable zone-wise monitoring for multiple fields or greenhouses.
- Generate alerts when thresholds are breached (e.g., low soil moisture).
- Help farmers make timely decisions to improve yield and reduce waste.
- Store historical sensor data for comparison and forecasting.
- Support IoT integration via REST/MQTT protocols.
- Offer downloadable reports and intuitive analytics.
Core Feature
- Real-time dashboard with sensor readings (line, gauge, and bar charts)
- Support for multiple sensors and field zones
- Threshold settings with alerts (email/SMS)
- Interactive charts (daily/weekly/monthly trends)
- Sensor data history and export options (PDF/CSV)
- Admin panel to register sensors and configure zones
- Device health monitoring (e.g., last updated, battery level)
- User authentication and role-based access (e.g., Farmer, Admin, Agronomist)
Tools & Technologies Used
| Category | Tools / Technologies |
| Language | Java 17 |
| Framework | SpringBoot |
| ORM | Spring Data JPA |
| IOT data Integration | MQTT (via Mosquitto) or RESTful APIs from sensors |
| Websocket | Spring WebSocket for live data push |
| Notifications | Java Mail, Twilio (SMS) |
| Database | MySQL (main database), Redis (cache) |
| Authentication & Security | Spring Security + JWT |
| API Documentation | Swagger / SpringDoc OpenAPI |
| Logging | Log4j |
| FrontEnd | React.js |
| Visualization | JasperReports / Apache POI, Chart.js / Recharts |
| Building Tools & Dependencies | Maven, Git, Jenkins |
| Testing | Mockito, Postman (API Test) |
| Cloud and Deployment | Docker, AWS EC2, RDS |
Prerequisites
π» System Requirements
- Operating System: Windows / Linux / macOS
- Minimum 8 GB RAM (Recommended: 16 GB)
- Java JDK 17 installed and configured (JAVA_HOME set)
- Node.js with npm/yarn for React.js frontend
- MySQL and MongoDB installed locally or hosted via cloud
- MQTT broker (e.g., Eclipse Mosquitto) installed/configured
- Docker (for local development or deployment)
π¦ Software Dependencies
- Spring Boot (Java backend framework)
- Spring Data JPA and MongoDB (for structured + time-series data)
- Spring Security + JWT (authentication and role-based access)
- Spring WebSocket (for real-time sensor data push)
- React.js with Chart.js / Recharts (for dashboard visualization)
- Java Mail & Twilio (for alert notifications)
- Swagger / SpringDoc OpenAPI (API documentation)
- JasperReports / Apache POI (for report generation)
π§° Tools & Services
- IDE: IntelliJ IDEA / Eclipse (backend), VS Code (frontend)
- Version Control: Git + GitHub/GitLab
- Build Tool: Maven
- CI/CD: Jenkins (optional)
- Cloud Deployment: AWS EC2 (app hosting), RDS (MySQL), MongoDB Atlas (or local MongoDB), S3 (optional for static files)
- IoT Simulator or MQTT Publisher for testing sensor data
π Technical Knowledge
- Basic understanding of IoT sensor networks and MQTT protocol
- Familiarity with Spring Boot REST APIs and WebSocket setup
- Frontend development with React.js and charting libraries
- Working with both relational and NoSQL databases
- Implementing real-time data pipelines and UI updates
- Knowledge of time-series analysis and environmental parameters in farming
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