Project Overview
A UK metropolitan council with a 450,000 population wanted to build a Smart City digital twin platform — integ...
Technology Stack
Compliance & Standards
The Challenge
A UK metropolitan council with a 450,000 population wanted to build a Smart City digital twin platform — integrating real-time data from IoT sensors (traffic, air quality, flood sensors, waste collection GPS), utilities (smart meters via Ofgem DCC API), and council operational systems to create a live operational dashboard. UK GDPR for IoT personal data, Ofgem DCC data access requirements, WCAG 2.1 AA for the council dashboard, and DLUHC Smart Cities framework were the requirements. Budget: £100,000.
Our Approach
Traffic sensors
UTMC (Urban Traffic Management and Control) standard XML feeds from council traffic management system.
Air quality sensors
DEFRA AURN (Automatic Urban and Rural Network) data API + council-deployed Aeroqual sensors via REST API.
Flood sensors
Environment Agency Real Time flood monitoring API (RLOI gauging stations).
Waste collection GPS
vehicle GPS tracking API from waste management fleet telematics (Quartix API).
All sensors
time-series data pipeline → AWS IoT Core → Kinesis Data Streams → TimescaleDB.
CityGML 3D city model
- OS MasterMap 3D Building Heights + Ordnance Survey terrain data.
- Three.js
WebGL rendering
3D city model in browser — GPU-accelerated, handles 450,000 population area.
Sensor overlay
- IoT sensor readings visualised on 3D model (traffic flow heatmap, air quality colour gradient, flood risk zones).
- Real-time update: WebSocket connection — sensor readings update every 30 seconds without page reload.
Performance
- Core Web Vitals LCP <
- 2.5s on council standard hardware.
Ofgem DCC Smart Meter Integration
- Ofgem Data Communications Company (DCC) data access: council registered as Data User for energy management purposes.
- Smart meter half-hourly consumption data for council-owned buildings (estates, leisure centres, offices).
Energy consumption dashboard
building-level consumption vs benchmarks (CIBSE TM54 operational energy benchmarks), anomaly detection (spike or sustained high consumption flagged for estates team).
UK GDPR
council building smart meter data — not personal data (council entity, not individual).
UK GDPR IoT Architecture
Street-level
IoT
traffic cameras with ANPR are personal data (vehicle registration = personal data).
Traffic sensor data
ClickMasters used aggregated flow counts (not individual vehicle data) — no personal data in traffic sensors.
Air quality and flood sensors
environmental data, not personal data.
Waste GPS
- vehicle locations, not driver personal data (fleet management).
- The design deliberately excluded personal data from all IoT feeds — no DPIA required for digital twin data flows.
The Results
Platform live at 16 weeks, £92,000 — under budget.
Real-time dashboard operational: 14 IoT sensor types integrated.
Air quality alert response time: 6.2 hours (manual) → 22 minutes (automated alert from DEFRA AURN data).
Flood sensor alerts: 4 events detected and council notified pre-incident (previously 2 post-incident notifications in prior year).
Council energy use (estates): baseline established — 18% anomalous consumption events identified in Q1.
DLUHC Smart Cities framework: council invited to share platform at national Smart Cities showcase.
“22 minutes for air quality alert versus 6.2 hours manually. In a pollution incident near schools, those 5 hours make a real difference. The flood sensor detections were the most operationally valuable — 4 pre-incident alerts versus previously being notified after flood events had started. The DLUHC Smart Cities showcase was the endorsement we needed to expand the programme." — Director of Digital Services, UK Metropolitan Council (name withheld)”
Project Details
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