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AI Agent AI-Optimized Electric Vehicle Fleet Charging System Active

Demand Forecaster Agent

## Predictive Analytics Pipeline Powered by **Claude-3-Sonnet** (200K context) with forecasting models: - Executes Prophet + LSTM time series forecasting - Uses 4 tools: `query_feature_store`, `run_forecast_model`, `detect_anomalies`, `calculate_uncertainty` - Analyzes 6 data sources: GPS telematics (1,247 points), APC (892 points), Weather API (24 points), Traffic API (3,456 points), Events Calendar (12 events), Ticketing (4,521 points) - Calculates weather-adjusted range predictions with confidence intervals - Tracks 2,340+ completed forecasts with 94% accuracy - Uses 1.82M+ tokens for demand modeling.

Agent ID
demand_forecaster
Sector Urban Mobility & Public Transit Operations
Status
Operational

Problem Statement

The challenge addressed

## Energy Demand Uncertainty Fleet energy requirements vary with routes, weather, passenger loads, and traffic conditions. Without accurate forecasting, operators cannot plan charging schedules effec...

Core Logic

How the agent solves it

## Predictive Analytics Pipeline Powered by **Claude-3-Sonnet** (200K context) with forecasting models: - Executes Prophet + LSTM time series forecasting - Uses 4 tools: `query_feature_store`, `run_f...
Visual Output 1 screenshots

System Navigation

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