AI and Social Networking Capabilities to Transform Traditional Asset Management

RedBite Solutions has secured Innovate UK funding for £1 million project to transform its asset tracking software 'itemit'. Fueled by transparency and openness, itemit will leverage advanced AI and machine learning algorithms to create a social network-style approach to asset management.

Recent, tragic, events in social housing have highlighted the need for change in the way assets that are owned, managed and used by different parties are monitored and maintained. Asset end-users, such as housing tenants should have access to up-to-date and accurate information on asset maintenance and inspection schedules. All relevant feedback, reports and concerns from end-users should be valued and used to enhance and inform asset management decision-making.

"The Grenfell Tower tragedy highlights the need for a drastic change in the way assets that are owned, managed and used by different parties are maintained and monitored. As evidenced in the Tower's fire risk assessment report, the condition of critical assets was directly linked to the extent of the tragedy. Our aim is to empower members of our society at a very poignant time to engage with a transparent and trustworthy change that addresses pertinent concerns that are shared by so many," said RedBite Solutions CEO, Dr. Alex Wong.

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The project team will work towards creating a user-centred digital asset management solution that provides transparency to asset end-users about the assets they rely upon and interact with as well as working to ensure incoming data from maintenance contractors and end-users is analysed and incorporated into decision-making. The itemit asset management solution proposed is unique in that all parties with an interest in an asset will be using the same integrated system to engage with assets.

"The output from this project is an innovative, digital platform for all asset stakeholders that incorporates new algorithms developed together with CUED. Two public reference sites, in the social housing and university markets, will be created by the project. These combined innovations are disruptive in that, for the first time in the infrastructure industry, users are given the opportunity to provide actionable input to asset managers," said Dr Ajith Parlikad, Senior Lecturer in Industrial Systems at the Institute for Manufacturing (IfM) and CSIC Investigator.

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Artificial Intelligence and machine learning algorithms will be developed to interpret the data received from all parties in order to compute a condition assessment score, determine appropriate intervention actions and develop a decision-support system for asset management. The result will be enhanced decision-making based on the value of infrastructural assets to tenants, asset usage and feedback from end-users.