1. AI-Enabled Intelligent Video Surveillance and Analytics
AI video surveillance technology achieves the transition from passive recording to proactive intelligent analytics by integrating deep learning algorithms into conventional security cameras. Core functions: face recognition for blacklist alerts, VIP guest identification, and employee attendance; behavior analysis for perimeter intrusion detection, crowd gathering alarms, abandoned/moved object detection, and person fall detection; people counting for zone-based real-time occupancy heat maps and conversion rate analysis; vehicle analytics for license plate recognition, vehicle type identification, and parking space detection.
2. IoT Sensor Network and Environmental Intelligence
The IoT sensor network enables comprehensive perception of the hotel environment. Sensor types: environmental sensors for temperature, humidity, CO2, PM2.5, PM10, TVOC, noise, and illuminance; energy sensors including smart electricity meters, water meters, gas meters, and ultrasonic cooling/heating energy meters; equipment status sensors for vibration monitoring, current monitoring, temperature monitoring, and switch status; occupancy sensors including infrared human presence detection, millimeter-wave radar presence detection, Bluetooth Beacon, and UWB positioning.
3. Digital Twin and BIM-Based O&M Management
Digital twin technology builds a virtual mapping of ELV systems through BIM models plus real-time data plus AI algorithms. Technical architecture: data layer comprising BIM model geometric information plus real-time sensor data plus historical O&M data; model layer comprising Unity3D/Unreal Engine visualization engines plus physics simulation engines; application layer comprising asset management, energy simulation, fault diagnosis, and optimization scenario modeling. Functional scenarios: equipment locating — clicking a device in the twin model displays real-time parameters and historical data; energy simulation — modifying operating parameters to simulate energy-saving effects.
4. Automated Control and Intelligent O&M Solutions
Automated control adopts an edge computing plus cloud collaboration architecture. The edge layer (RTU/PLC/DDC) handles real-time control with response times under 100 ms; the cloud platform handles global optimization strategy issuance and data analytics. AIOps intelligent O&M functions: fault prediction — ML models analyze historical equipment operating data to predict failure probability; root cause analysis — correlates alarm information across multiple systems to automatically pinpoint the fault root cause; self-healing recovery — automatically executes preset fault recovery scripts such as restarting services or switching to standby.