Crime Pattern Analysis using Karnataka Police Data and Time Series Forecasting.
This project analyzes crime patterns in Karnataka using Karnataka police data and employs the Prophet time series forecasting model to predict future crime trends. The goal is to provide insights that can help law enforcement agencies enhance their strategies for crime prevention and resource allocation.
Understanding crime patterns is crucial for effective policing and community safety. This project utilizes historical crime data from the Karnataka police to analyze trends over time and forecast future occurrences using the Prophet time series forecasting model.
- Programming Languages: Python.
- Libraries: Pandas, NumPy, Matplotlib, Seaborn, Statsmodels, fbprophet.
- Data Visualization: Plotly, Dash (optional for interactive dashboards).
The dataset used for this project is sourced from the Karnataka Police Department and includes records of crimes across different districts over a specific period.
The project employs the Prophet model for time series forecasting, which is designed to handle seasonality and trends in data.
Results show crime trends in specific districts, revealing important patterns in criminal activity. Forecasts indicate potential increases or decreases in incidents, providing valuable insights for law enforcement.