Every Device. Every District. Every Moment.
Real-time IoT monitoring with AI anomaly detection across all 18 Hong Kong districts.
What it shows
Live telemetry, watched by AI
- 1Devices stream readings from across the districts in real time.
- 2AI models flag anomalies and forecast maintenance needs.
- 3Alerts and dashboards keep operators ahead of failures.
Air quality
Good
Temperature
24.6°C
Occupancy
63%
Anomalies
2 flagged
Capabilities
What the demo illustrates
Real-time Device Dashboard
Live telemetry from every connected device, district by district.
AI Anomaly Detection
Isolation Forest + LSTM flag unusual readings as they happen.
Predictive Maintenance Alerts
Prophet-based forecasting warns before equipment fails.
Multi-site Management
Monitor many sites and districts from a single view.
Environmental Monitoring
Air quality, temperature, and occupancy across the network.
API & Webhook Integrations
Push events into your existing systems in real time.
By industry
Where it applies
- Monitor campus environmental conditions and occupancy in real time.
- Detect anomalies in building systems before they disrupt teaching.
- Track site sensors for safety-relevant conditions across locations.
- Predictive alerts on equipment health to reduce unplanned downtime.
- District-level environmental and mobility telemetry across Hong Kong.
- Anomaly detection surfaces issues the moment readings drift.
- Continuous condition monitoring of distributed infrastructure assets.
- Forecast maintenance windows from live sensor trends.
Coverage
All 18 Hong Kong districts
Designed from the ground up for Hong Kong's 18 districts — from Sham Shui Po to Sai Kung.
Under the hood
Technical stack
Protocols
MQTT · HTTP · CoAP · LoRaWAN
Anomaly detection
Isolation Forest + LSTM
Predictive maintenance
Prophet forecasting
Infrastructure
AWS IoT Core (APAC) · TLS encryption
Related work
Projects using the IoT platform
18-District IoT Environmental Monitoring
Real-time device telemetry paired with causal analytics across all 18 Hong Kong districts.
Live telemetry across 18 HK districts
Construction Site Safety Pathways
Modelling the causal pathway from site conditions to incidents so resources go where they move the needle.
Projected: effect estimate per safety measure
Infrastructure Reliability Drivers
Estimating how design and process changes cause shifts in asset reliability and lifecycle cost.
Projected: ranked reliability drivers
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