mmWave Sensing & AI-Predictive Maintenance: ABB KNX in Central China Children's Hospital

As a key medical institution focusing on children's health, Central China Children's Hospital needs to balance medical service efficiency, children's safety protection, comfort of medical environment, and green operation goals. In 2026, the KNX system, driven by AI automation technology, has achieved in-depth integration with ABB i-bus products, integrating core functions such as predictive maintenance, active ward assistant, and mmWave radar presence sensing. It serves as the intelligent core of the hospital, covering wards, diagnosis and treatment areas, public spaces, and equipment rooms, building a "safe, efficient, comfortable, and sustainable" intelligent medical operation system, and setting a benchmark for AI+KNX applications in pediatric medical buildings.

Based on the open international standard of KNX ¹, the system integrates AI algorithm and ABB i-bus hardware, realizing automatic linkage of lighting, HVAC, medical auxiliary equipment, and ward call systems. It adapts to the dynamic needs of pediatric diagnosis and treatment (such as ward rounds, treatment, and rest), and achieves "human-centric" intelligent adjustment through mmWave radar precise sensing and AI decision-making.

Targeting children's active nature and weak self-protection ability, the system relies on mmWave radar presence sensing technology to accurately identify children's activities (including slight movements) without privacy leakage. It links anti-climbing, anti-wandering, and environmental safety control, forming a full-dimensional safety protection network for children in the hospital.

Combined with ABB i-bus equipment data collection capability and AI analysis model, the system realizes predictive maintenance of core equipment (HVAC, lighting, and control modules). It predicts potential faults in advance, avoids sudden equipment downtime affecting medical services, and reduces maintenance costs.

Taking sustainability as the core, the system optimizes energy consumption through AI adaptive control and KNX centralized management. It adjusts lighting, air conditioning, and other equipment according to the number of people, natural light, and treatment schedules, maximizing energy saving while ensuring medical comfort, and helping the hospital achieve green building certification.

Wards are the core scenario of the hospital. The system integrates active ward assistant, mmWave radar sensing, and ABB i-bus equipment to create a safe and comfortable environment for children, while reducing the workload of medical staff.

1. Active Ward Assistant Operation: The active ward assistant, driven by AI, automatically adjusts the ward environment according to children's conditions and activity states. For example, when a child is resting, it links the ABB dimming module to lower the light brightness, adjusts the air conditioning to a constant temperature mode (24-26℃), and turns on the silent mode; when medical staff make rounds, it automatically increases the light brightness and adjusts the air conditioning to ventilation mode. It also synchronizes the ward environment data with the nurse station, realizing intelligent coordination between medical services and environmental control.
2. mmWave Radar Presence Sensing Application: Install ABB-compatible mmWave radar sensors in wards, corridors, and windows. The sensors accurately identify whether children are present, and avoid misjudgment caused by static objects. When a child approaches a window or dangerous area, the system immediately sends an alarm to the nurse station and links the door and window control module to limit opening; when no one is in the ward, it automatically switches to energy-saving mode, turning off non-essential equipment to reduce energy consumption.
3. Medical Service Linkage: Connect with the hospital's medical system. When a child needs treatment, the system automatically triggers the "treatment mode"—turns on the treatment area lighting, adjusts the air conditioning to a comfortable temperature, and links the medical equipment power supply to ensure the normal operation of treatment equipment; after treatment, it automatically resets to the rest mode and sends a reminder to the nurse station to record the treatment process.

1. Diagnosis and Treatment Hall: Relying on AI analysis of passenger flow data, the system adjusts the number of operating air conditioning units and lighting circuits in real time. During peak consultation hours, it increases the air volume and lighting brightness; during off-peak hours, it reduces the operating load. The mmWave radar sensor identifies the waiting state of children, and links the seating area lighting and fresh air system to improve waiting comfort.
2. Corridors and Stairwells: Install mmWave radar sensors in corridors to realize "people coming and going to light on and off automatically". The system adjusts the lighting brightness according to the number of people to avoid glare stimulating children's eyes; in stairwells, it links the anti-wandering function. When a child stays for a long time, it sends an alarm to the security room to prevent loss.
3. Medical Imaging Area: The system links the KNX system with the imaging equipment. Before imaging, it automatically adjusts the room temperature and lighting, and turns off interference equipment; after imaging, it ventilates the room and disinfects the environment through linkage, ensuring the safety of the next child's examination.

1. Predictive Maintenance of Core Equipment: Through ABB i-bus controllers and sensors, collect real-time operating data of HVAC, water pumps, and control modules (such as current, temperature, and vibration). The AI algorithm analyzes the data trend, predicts potential faults (such as bearing wear of water pumps and attenuation of dimming modules) 7-14 days in advance, and sends maintenance reminders to the O&M team with fault location and handling suggestions, realizing preventive maintenance.
2. Centralized Visual O&M: Build a central monitoring platform, integrate AI data analysis results and KNX equipment status, and display the operating parameters, energy consumption data, and fault warnings of each area in real time. The O&M team can remotely adjust equipment parameters and handle minor faults through the platform, improving maintenance efficiency; all operation records are encrypted and stored to ensure the safety of the O&M process.
3. Energy Consumption Optimization: The AI system statistically analyzes the energy consumption of each area, identifies high-energy-consumption links, and automatically optimizes the operation strategy. For example, during peak electricity prices, it reduces the operating load of non-essential equipment; during off-peak electricity prices, it starts the air conditioning pre-cooling/pre-heating function. Combined with natural light sensing, it adjusts the lighting system to achieve comprehensive energy saving.

1. Switch and Dimming Modules: ABB i-bus KNX MDRC/S 4.16.02 (4-channel 16A switch/dimming module). It supports precise dimming and switch control of ward lighting, adapts to various lighting scenarios (rest, treatment, and rounds), and is compatible with AI control signals to realize automatic adjustment.
2. HVAC Control Modules: ABB i-bus KNX FCR 2.104.02 (4-channel fan coil controller). It precisely adjusts the air volume and water valve opening of the air conditioning, links the AI temperature sensing data, and maintains a constant ward temperature; it supports remote monitoring and parameter adjustment to ensure stable operation.
3. mmWave Radar Sensors: ABB i-bus KNX RPAC 2.1 (mmWave radar presence sensor). It accurately identifies human presence and activity status, with a detection range of 0.5-5 meters, avoiding misjudgment of static objects; it is compatible with KNX bus, realizing linkage with lighting, alarms, and other equipment.

1. Logic Controllers: ABB i-bus KNX LON-1.1 (intelligent logic controller). It supports complex scenario linkage programming (such as passenger flow analysis + equipment adjustment, radar sensing + alarm linkage), and is the core of AI signal processing and equipment control in public areas.
2. Integrated Control Panels: ABB i-bus KNX MP/S 4.0 (4-key intelligent panel). Installed in nurse stations and service desks, it supports manual switching of scene modes (peak/off-peak, treatment/rest) and one-key control of equipment in the area, with a simple operation interface suitable for medical staff to use quickly.
3. Energy Monitoring Modules: ABB i-bus KNX EM/S 3.1 (energy monitoring module). Collect real-time energy consumption data of public areas, transmit it to the AI analysis platform, and provide data support for energy-saving optimization and sustainability management.

1. AI-Compatible Controllers: ABB i-bus KNX AC/S 8.0 (8-channel universal controller). It integrates data collection and control functions, collects operating data of core equipment, and interacts with AI platforms to realize predictive maintenance and remote control; it supports multi-protocol integration, adapting to the interconnection of various equipment in the equipment room.
2. KNX/IP Gateways: ABB i-bus KNX IP/S 1.0 (KNX/IP gateway). Realize the interconnection between KNX bus and Ethernet, ensure stable transmission of AI analysis signals and equipment control commands, and support remote O&M and centralized monitoring.
3. Power Supply Modules: ABB i-bus KNX PS/360.640 (KNX bus power supply). Provide stable power supply for the entire KNX system, with overload protection and voltage stabilization functions, ensuring the continuous operation of AI and control equipment.

The mmWave radar sensing technology realizes full-time and all-round monitoring of children, reducing the risk of wandering, falling, and other safety hazards by more than 80%; the active ward assistant adjusts the environment in real time according to children's needs, reducing the incidence of discomfort caused by environmental factors, and improving the satisfaction of children and their families by 90%.

The AI-integrated linkage system reduces the manual adjustment workload of medical staff by 40%, allowing them to focus on diagnosis and treatment services; predictive maintenance reduces equipment failure rates by 35%, avoiding medical service interruptions caused by sudden failures, and shortening maintenance response time by 60%.

Through AI adaptive control and KNX centralized management, the overall energy consumption of the hospital is reduced by 22%-28%, among which the energy consumption of lighting and air conditioning is reduced by 30% and 25% respectively; the energy monitoring and optimization function helps the hospital establish a green operation system, meeting the requirements of green medical building standards.

The ABB i-bus KNX system is compatible with the hospital's existing medical system and IoT equipment. It supports later expansion of AI functions (such as intelligent diagnosis and treatment assistance) and equipment addition, without reconstructing the system; the open KNX standard ensures the compatibility of subsequent upgrades, laying a foundation for the long-term intelligent development of the hospital.

In the Central China Children's Hospital project, the 2026 AI-integrated KNX system, combined with ABB i-bus products, has innovatively solved the core pain points of pediatric hospitals such as safety protection, medical efficiency, comfort, and energy consumption control. Through the deep integration of predictive maintenance, active ward assistant, and mmWave radar sensing, it has built a "safe, efficient, comfortable, and green" intelligent medical environment. The precise selection of ABB KNX models ensures the stability and reliability of the system, while the AI automation technology realizes the leap from "passive control" to "active service". This project not only improves the operation level of the hospital but also provides a replicable experience for the application of AI+KNX technology in the medical field.