ReformAI

ReformAI predicts recidivism risk, recommends rehab programs, and maps crime trends with a Safety Index. Using AI, we prevent crime, support reintegration, and create safer communities.

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ReformAI

ReformAI predicts recidivism risk, recommends rehabilitation programs, and maps area safety (Green, Orange, Red) using AI and real-time crime data.

Inspiration

Our inspiration came from crime documentaries and real-world statistics showing that nearly 44% of released prisoners reoffend within three years. We wanted to create a data-driven solution to break this cycle by providing predictive insights and targeted rehabilitation programs.

What it does

  • Recidivism Prediction: Assesses reoffending risk (1-10) using machine learning models.
  • Rehabilitation Suggestions: Provides tailored support like job training, mental health care, or supervision.
  • Safety by Area Index: Uses crime data to map locations as Safe (Green), Unsafe (Orange), or Super Unsafe (Red).

How we built it

  • Backend: Flask, Scikit-Learn for ML model training and API development.
  • Frontend: Android app using Java & XML for user interaction.
  • Data Sources: FBI Crime Data API, Kaggle datasets for crime statistics and recidivism data.
  • API Integration: Retrofit for seamless data retrieval between app and backend.

Challenges we ran into

  • Data Preprocessing: Cleaning and structuring large datasets with missing values and inconsistencies.
  • Bias in AI Models: Ensuring fairness in risk predictions to avoid reinforcing systemic biases.
  • Real-Time Crime Data Integration: Managing API requests and geospatial filtering efficiently.
  • UI/UX Optimization: Designing an intuitive interface for law enforcement and policymakers.

Accomplishments that we're proud of

  • Successfully developed an AI-powered risk assessment model with high accuracy.
  • Built an Android app that provides real-time insights for users.
  • Implemented a Safety by Area Index to enhance public safety awareness.
  • Integrated real-world crime data APIs to improve decision-making.

What we learned

  • The importance of data ethics and fairness in AI-driven criminal justice solutions.
  • How to optimize ML models for better accuracy and interpretability.
  • The challenges of real-time data handling and API performance tuning.
  • How technology can be leveraged to assist policymakers in crime prevention efforts.

What's next for ReformAI

  • Google Maps Integration to visualize crime hotspots dynamically.
  • Real-time Notifications for users about high-risk areas.
  • Improved AI Bias Detection to ensure fair predictions.
  • Partnerships with law enforcement agencies for real-world implementation.

ReformAI helps law enforcement and policymakers prevent crime through data-driven decision-making.

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