AI-Powered Global Event Monitoring & Trend Analysis System

Context & Objective

Development of an AI-powered, government-grade trend detection system that monitors global events in real-time and visualizes them on an interactive map. The platform enables users to query historical date ranges and understand what's happening around the world through aggregated, scored, and geographically-positioned event data.

The system uses AI for event classification and entity extraction, while prioritizing transparency and auditability through documented mathematical formulas for trend scoring.

Scope of Work

• Design and implementation of a global news ingestion and analysis system
• Event extraction and classification across 20 categories
• Location extraction and geographic positioning
• Trend scoring using a documented formula
• API for historical trend queries
• Interactive map-based visualization

Key Platform Characteristics

• Weighted scoring combining volume, deviation, corroboration, and geographic concentration
• Source credibility tiering
• Category-based severity scoring across 20 event types
• Geographic clustering for map-based visualization

Governance & Auditability Characteristics

• Source bias mitigation through corroboration scoring and credibility tiers
• Full traceability from raw data to final trend scores
• Designed for government and institutional requirements