A collaboration between UK and South Korea to develop the next generation, comprehensive AI system for the industrial sector.
A custom build industrial AI solution, installed on edge PC, can incur a capex cost of up to £5,000 and the engineering cost of £100,000. A more complex AI model increases the model complexity and required computational power for continued update training and updating.
This innovation provides a pre-trained model to reduce the engineering and model training costs while maintaining the accuracy of the prediction models.
APOE will be designed with minimal configuration required and cater for various energy management strategies to strategically recommend solutions to end-users to reduce energy and carbon costs on premise.
This cloud-based solution will ingest various real-time data (energy market data, ERP data, weather data, real time events) to pre-emptively inform users recommended energy strategies to reduce short to midterm energy costs.
In a typical engineering systems, multiple systems have different orders of precedence in making an asset controlling decision. These decisions are often overridden by human decision process to ensure maximum system reliability. This innovation assists operator to make better overall decision.
This system presents operators with the pros and cons of each decision and provide operator a recommendation solution to control the assets. The engine aims to reduce the complexity of decision-making process, freeing up more time for the operator to attend to more important tasks.
The AMOS (Asset Management & Optimisation System) project is an international collaboration between Enverse, Liverpool John Moores University (LJMU), IDB, and Seoul National University of Science and Technology (SEOULTECH). Supported by Innovate UK, the Korea Institute for Advancement of Technology (KIAT), and Korean Energy Technology Evaluation and Planning (KETEP), this initiative is part of a…
Enverse (UK), Liverpool John Moores University (UK), IDB.AI (SK) and Seoultech (SK) have entered into a collaborative consortium to bid for AI-powered industrial asset management and energy optimisations system. This collaborative R&D project is jointly funded by Innovate UK and KIAT (Korea Institute for Advancement of Technology). The AMOS (Asset Management & Optimisation System) project…