Project Overview:

The Real-Time Crime Analytics Dashboard is a data-driven web application that allows users (e.g., law enforcement, researchers, or public users) to analyze, visualize, and predict crime trends across regions using historical and live crime data. It utilizes data science and big data techniques to provide interactive visual insights, detect crime hotspots, and predict future crime rates based on patterns.

This system aims to help in crime prevention and planning by making real-time and predictive analytics easily accessible through a modern web interface.

Key Features:

1. Crime Trend Visualization (daily/monthly/yearly)

2. Interactive Crime Heatmap (by city/state)

3. Filter Crimes by type, region, date range

4. Real-time Crime Alerts from public APIs or police feeds

5. Crime Prediction Module using Machine Learning

6. Upload CSV datasets for custom analysis

7. Role-Based Access: Admin (police) / Public

Technologies Used:

Backend Options:

• PHP with MySQL (Laravel or Core PHP)

• Java with Spring Boot + PostgreSQL

• Node.js with Express + MongoDB

Frontend:

• HTML5, CSS3, Bootstrap

• JavaScript (AJAX, Chart.js, Leaflet.js or Google Maps)

Data Science / ML (Python Scripts):

• Pandas, NumPy, Matplotlib for data analysis

• Scikit-learn or Prophet for crime forecasting

• Jupyter Notebook or Flask API to run models

Big Data Stack (Optional):

• Apache Kafka – Live crime feed stream

• Apache Spark – Data cleaning and transformation

• Hadoop / Hive – For storing huge datasets

System Architecture:

1. Data Sources:

   • Open government crime datasets (e.g., Kaggle)

   • Real-time APIs from police departments or simulated feed

   • Uploaded CSV/Excel by users

2. Data Processing:

   • Clean and preprocess using Python or Spark

   • Store processed data in a database

3. Prediction Engine:

   • Train models on past crime data to forecast incidents

   • Example models: Decision Tree, ARIMA, Random Forest

4. Web Dashboard:

   • Visualize analytics (bar graphs, line charts, pie charts)

   • Display maps with hotspots and real-time updates

5. Alerts:

   • Email/SMS notifications for high-risk areas (optional)