Embark on a ground-breaking journey towards maritime safety with our cutting-edge project: the Virtual Reality (VR) Training Application for Enclosed Spaces at Sea. This innovative initiative is designed to revolutionize safety training for maritime professionals, focusing on the challenges posed by emergencies within confined ship spaces.
Objective: Our primary goal is to elevate maritime safety by immersing professionals in realistic VR simulations that replicate various enclosed spaces found on ships, including engine rooms, cargo holds, and storage areas. Through these simulations, we aim to equip individuals with the skills and knowledge needed to navigate challenging scenarios, such as fire incidents, gas leaks, and other emergencies.
Impact: By honing in on critical aspects such as air quality monitoring, proper PPE usage, and specialized firefighting techniques, our VR Training Application strives to significantly enhance the safety and preparedness of maritime professionals navigating the challenges of confined environments at sea. Aligned with industry demands, this project pioneers advanced training methodologies that prioritize realism, interactivity, and the practical development of essential skills for the maritime workforce.
The CSAMGuard project presents an innovative approach to combat Child Sexual Abuse Material (CSAM) by focusing on the detection and prevention of CSAM link shortening and modification through the use of a machine learning (ML) model. This method promises enhanced accuracy and a reduction in false positives compared to traditional approaches like blacklisting or heuristic methods.
Our central focus is on the development and implementation of the Central CSAM Intelligence System (CCIS), a sophisticated and specialized system dedicated to identifying and disrupting CSAM link shortening and modification. The CCIS incorporates multiple key services to address the CSAM challenge, including a CSAM Scanner designed to identify potential CSAM links, a CSAM Blocker to prevent access to them, and a CSAM Reporter responsible for notifying relevant authorities, including Link Shortening Service Providers.
The project aim is to develop, for the food & drink sector, innovative technology that provides greatly enhanced resource usage efficiency & reduction in waste production both within individual food & drink companies but also across their supply chains. The Supply Chain Overall Resource Effectiveness (SCORE) system developed will extend existing performance improvement systems by greatly extending the range of performance metrics able to measure levels of resource usage inefficiency & waste production. SCORE will also add critical capability for identifying & permanently resolving root causes of resource usage inefficiency & waste production and enable prediction of emerging negative trends & sudden adverse changes. Innovative technology developed will develop advanced modelling capability for determining the precedence & causal relationships between individual SCORE metrics and use of these relationships to build simulation models for trend prediction & root cause analysis. Overseeing SCORE will be an autonomous decision system that selects optimum solutions for emerging & sudden resource efficiency and waste production issues.
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Within refrigerated and shelf-life constrained food supply chains extremely high levels of demand fluctuations arise preventing organisations achieving the high levels of customer service required by large retail customers whilst ensuring high levels of waste are not produced. In order to resolve these problems more effective management of demand is required from procurement of basic materials by processers and manufacturers through to distribution of finished goods to retail customers. To achieve this aim this project will develop a novel Autonomous & Intelligent Demand Management (AIDMT) approach by structuring the causal and planning relationships between retail demand forecasts, production schedules and capacity plans as autonomous control networks. These networks will be constructured using the basic principles of gene transcription regulatory control that when applied to demand management enable fast and flexible responses to demand fluctuations.
This ASDT Project (Autoplan) is designed to remove the failings of existing operations planning systems in managing highly variable manufacturing environments. In such organisations the high frequency with which process and supply chain disruptions occur and changes in product design and customer demands happen, form major barriers to increasing the competitiveness and maintaining the high rate of growth.
Finite Capacity Resource (FCR) planning involves deciding when customers’ jobs are sequenced through shop floor manufacturing areas. Such plans recognise that jobs need to be scheduled when all necessary equipment and labour resources are available and that these resources have limited capacity. Unfortunately FCR plans are subject to frequent and major disruptions caused by for example equipment breakdowns, delays in raw material delivery and changes to customers’ orders.
The result is that frequent manual planning revisions are undertaken that are slow and resource intensive. The autonomous planning processes to be developed will enable faster and more effective planning responses. They will be developed by applying the basic principles and characteristics of the regulatory control networks involved in the biological process of gene transcription. The application principles used have been developed and proof-of-concept tested as part of an EPSRC-funded Systems Biology feasibility project.
With 25,000+ planners in 9,000+ UK manufacturers the total time and resource loss represents a major opportunity to significantly improve UK productivity and competitiveness.
This project aims to provide a software platform for companies to match empty vehicles and space to available loads in its simplest form. Too many commercial vehicles globally run empty or partially empty for parts of their journey. This software aims to reduce the total amount of empty running by load matching and thus reduce carbon emissions. The project will also be extended to passenger transport such as taxis and potentially freight carrying ships and barges.
A mobile application has also been produced for owner drivers and courier companies.
Additional functionality includes a carbon emissions calculator, a journey cost calculator and a data intelligence tool which can provide detailed information on the movement of goods between locations and regions.