IoT solutions for public and commercial spaces.
Key Components of an IoT System
Internet-of-Things solutions always come with a system of connected hardware, and software.
Products & Solutions
Digital Twin System
Digital Twin System enables “real-time synchronization” in a digital environment through real-time data feedback and analog technology, thereby supporting monitoring, diagnosis, and prediction.
By integrating building information models and IoT sensors, the system can achieve energy savings of up to 20% to 30%.
HVAC system optimization:
The system dynamically adjusts the cooling water temperature and fan speed based on real-time pedestrian flow, indoor and outdoor temperature, humidity, and carbon dioxide concentration.
Expected energy saving effect:
After integrating digital doppelgangers to optimize HVAC, a large office building successfully reduced energy consumption by 25%.
Smart lighting control:
Occupancy Detection: combined with AI algorithms, automatically turns off lights and air conditioning in unoccupied rooms.
It senses the intensity of natural light and automatically adjusts motorized blinds and light brightness to maximize the use of natural light.
Expected energy saving effect:
By using digital avatars to monitor energy usage in the store, nearly 30% of energy consumption has been successfully saved.
Fault Warning：
Virtual Diagnostics: Maintenance personnel can view the operating status of pipelines through the interface, quickly locating energy leaks or the causes of equipment inefficiency.
Predictive Maintenance: The system issues alerts before equipment failure leads to performance degradation (and wasted electricity), ensuring that equipment is always in optimal energy efficiency.
Expected energy saving effect:
The additional 10% – 15% savings on top of automation mainly come from avoiding inefficiencies caused by equipment “operating with defects”.
Smart City Planning:
Smart cities use digital avatars to simulate traffic flow and energy consumption to enhance urban resilience.
Traffic light self-optimization: The duration of red and green lights is dynamically adjusted based on real-time traffic flow, reducing stop-and-go idling by vehicles. The optimized traffic flow can effectively reduce regional carbon emissions.
Expected energy saving effect:
Smart street light network: Street lights not only adjust their brightness according to sunlight, but can also detect “pedestrian traffic” through digital clones. In deserted areas at night, the brightness can be adjusted to 20%, which alone can save more than 40% of street light energy consumption.
