This project aims to provide comprehensive analysis and insights into crime patterns and trends using various techniques such as map-based analysis, month-based analysis, age-based analysis, crime prediction, crime sentiment analysis, and a model for resource allocation, crime prediction, sentiment analysis for social media comments for finding probable criminal activities.
- Utilizes maps to visualize crime hotspots, aiding in understanding geographic patterns of criminal activities.
- Provides detailed views of crime distribution across different regions, enabling targeted interventions and resource allocation.
- Analyzes crime data based on months to identify seasonal trends and variations in criminal activities.
- Helps in understanding temporal patterns and planning preventive measures accordingly.
- Focuses on age demographics to study crime trends for women and sensitive age groups like the elderly and children.
- Provides insights into vulnerable age categories and potential areas for social interventions.
- Utilizes machine learning models to predict potential crime occurrences based on historical data and relevant factors.
- Aids law enforcement agencies in proactive planning and resource allocation.
- Analyzes public sentiment related to crime through social media and other sources.
- Provides a sentiment score to gauge public perception and concerns regarding safety and security.
- A model for finding the nearest police station containing needed resources for the user-reported crime.
- Maximizes efficiency in resource utilization and response to varying crime scenarios.
- A model for predicting the most probable criminals based on the previous data for criminals including the time range, the locations of the crimes, and the crime type.
- Javascript: Integrating Google Maps API
- Python: Machine learning models
- Html/CSS: Website design
- Flask: Prediction model deployment
- Firebase: Realtime data storage and deployment
- Streamlit: Other models deployment
- Huggingface: Other models deployment
- AWS Amplify: Website deployment
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Make Sure you have Python 3.x and Node.js installed in your system installed on your system.
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Clone the repository:
git clone https://github.com/CID123456/crime-analysis-project.git
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Install dependencies in backend:
cd backend pip install -r requirements.txt python app.py
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Install live-server
npm install live-server
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Run in root directory (containing the index.html):
live-server
Demo video link - https://youtu.be/gC80tkqQN64