Power Saving in Medical Compressed Air System by Real-time Artificial Intelligence and Edge Computer

The research is an 18 months project led by our leading expert in communication technology Professor Gaoyong Lao, and our senior chief engineer Mr. Kevin Witt who has worked in compressed air industrial for over 40 years. The project will also have input from academic staff from the engineering department at the Bedford University and our NHS hospital partners.
Current research and development have indicated that up to 60% of energy costs can be saved through optimisation at both the production facility and system level. Since 2007, SHJ has developed and implemented an intelligent compressed air system by the integration of advanced communication technology, edge computer, artificial intelligence (AI), Blockchain technique, allowing real-tie monitoring and control of medical gas system. With our recently developed SCADA (Supervisory Control and Data Acquisition) and IoT (Internet of Things) network, this will allow real time data to be collected from all sources on the IoT networks, and for further big data analysis and diagnosis, in turn will generate A.I. decision support system to optimise the efficient use of the compressed air system.
The benefit of this research will provide estate officers to:
• Access real time measurements related to the system, has an eagle-eye view of every event
• Save on staff cost, control larger and more complex processes with a smaller, less specialised staff
• Save power and reduce carbon footprint.
We will welcome the opportunity to present this at IHEEM conference.