W.A.N.T.E.D
Watch and Analyze Nationwide Trends in Evolving Deviance
Crime Intelligence | Geospatial Analytics | Cloud-Native AI
Overview
W.A.N.T.E.D is a cloud-native system built to analyze, visualize, and forecast crime evolution patterns across India using AI models, geospatial tools, and real-time data pipelines. It introduces the concept of a 'Crime Genome' – vectorized crime profile modeling that treats crime patterns as structured, analyzable entities rather than raw event logs.
Key Features
Crime Genome
Vectorized crime profile modeling treating crime patterns as structured entities.
Demographic Transition Models
Population-linked crime analysis.
Semantic Vector-Based Search
Using Sentence Transformers for semantic crime search.
GPU-Accelerated Anomaly Detection
cuML/cuDF for high-performance analysis.
Interactive Geospatial Visualization
Heatmaps and network graphs via Folium.
Technology Stack
Algorithms & Methods
Crime Genome Vectorization
Structured vector representation of crime patterns for analysis.
Semantic Search
Sentence Transformer embeddings for crime pattern similarity.
GPU Anomaly Detection
cuML-accelerated outlier detection on crime data.
System Architecture
Data Pipeline
Crime data ingestion, preprocessing, vectorization
Analysis Engine
Pattern detection, demographic transition modeling
Geospatial Layer
Heatmaps, network graphs, interactive visualization
Search Module
Semantic vector-based crime search
Results & Outcomes
- Crime Genome vectorization framework implemented
- GPU-accelerated analysis pipeline operational
- Interactive geospatial crime visualization delivered
- Semantic search across crime patterns functional