Facility Management

High-risk industrial sectors, notably the chemical industry, frequently experience severe safety incidents during production. Traditional risk management approaches, heavily reliant on manual efforts, often suffer from inadequate supervision, incomplete coverage, and suboptimal control. Addressing these challenges, the tech provider offers an advanced solution combining artificial intelligence technologies such as computer vision, the Internet of Things (IoT), and big data analytics. By utilizing existing enterprise cameras and sophisticated algorithmic servers, it establishes a video-based intelligent analysis platform for hidden risk management. This platform enhances overall safety through comprehensive risk perception, proactive hazard identification, predictive warnings, and visual decision-making aids, aiming for widespread and intelligent safety management across high-risk industrial environments.

Driving sustainability, efficiency and carbon reduction in data centres is a complex and increasingly challenging requirement. The increased global use of high-definition video streaming, conversational AI modelling technologies and online meeting platforms puts increasing strain on data centres.  To meet these complex challenges, an AI, data-driven solution is required. The proprietary solution proposed herein is a data acquisition and analytics system designed for deployment in data centres.  The solution employs non-intrusive clip-on current transformers which are easily installed at electrical distribution boards, which continuously gather current signatures information at a high sampling rate. This enables AI algorithms to detect subtle changes and patterns in the electrical signature of each connected asset or device. Monitoring electrical assets has traditionally been complex and costly, requiring multiple sensors and expensive systems, and often requires deployment near to the asset or device to be monitored. This has led to widespread under-monitoring, resulting in expensive maintenance and significant energy inefficiencies. The solution extracts a proprietary set of deep energy data from electrical devices such as, uninterrupted power supplies (UPSs), Chillers, power distribution units (PDUs) and air conditioning and can be easily installed on both new and existing infrastructure. It offers real-time monitoring and reporting on important metrics such as real-time power usage effectiveness (PUE) and enables automation of sustainability reporting. This technology offers an industry-changing solution: a non-intrusive cost efficient AI-powered monitoring system that is easy to install. It generates a proprietary data set that fuels machine learning algorithms, enhancing efficiency and reducing total cost of ownership for data centre managers and owners.  The technology owner is seeking opportunities to demonstrate the capabilities in the data centre environment, preferably based in Singapore.