Overview:
The City Energy Consumption Heatmap is a smart city data visualization platform that maps and analyzes electricity usage across different neighborhoods, commercial districts, and industrial zones. It provides real-time and historical insights into energy consumption patterns, enabling city planners, utility companies, and policymakers to identify high-usage areas, detect inefficiencies, and promote energy conservation strategies.

Key Features:

1. Real-Time Consumption Tracking – Integrates with smart meters and utility databases to display live electricity usage.

2. Interactive Heatmap – Uses color-coded maps to visualize energy consumption intensity in various city zones.

3. Historical Data Analysis – Compares past and present energy usage trends to detect growth patterns or seasonal spikes.

4. Sector-Based Insights – Breaks down energy usage by residential, commercial, and industrial categories.

5. Peak Load Detection – Highlights time frames when energy demand is at its highest.

6. Renewable Energy Integration – Shows the percentage of power generated from renewable sources in each area.

7. Energy Efficiency Score – Assigns ratings to neighborhoods based on consumption per capita.

8. Anomaly Detection – Alerts when unusual spikes or drops in energy usage occur.

9. Policy Impact Tracking – Measures the effectiveness of energy-saving campaigns and infrastructure upgrades.

10. Public Awareness Dashboard – Allows citizens to view energy data for their locality to encourage responsible consumption.

Technology Stack:

• Backend: Node.js, PHP, or Java for API handling and data processing

• Frontend: HTML, CSS, Bootstrap, JavaScript (Leaflet.js, Mapbox, or Google Maps API for map visualization)

• Database: PostgreSQL or MongoDB for storing consumption logs and historical records

• Data Sources: Smart meters, IoT sensors, utility provider APIs

• Analytics & AI: Python (Pandas, NumPy, scikit-learn) for data processing and predictive modeling

• Visualization: D3.js, Chart.js for trend graphs and statistical displays

Use Cases:

• City Governments: Identify over-consuming zones to target with efficiency measures.

• Utility Companies: Optimize grid load management and prevent power outages.

• Urban Planners: Design energy-efficient smart city layouts.

• Environmental Groups: Track and promote sustainable energy usage.

• Citizens: Monitor personal and community energy footprints.

Outcome:
The system empowers cities with data-driven energy management, helping reduce waste, lower carbon emissions, and improve sustainability efforts.