PROJECTS
We work very closely with UK/EU and international universities and industrial partners to create commercial and research opportunities for product development and innovation which have social economic and environmental impact. We formulate research propositions in partnership with universities, industrial partners and other stakeholders. We work closely with UK funding agencies (EPSRC, Innovate UK), European funding agencies (EIT Digital) and the European Commission. In essence, our approach to research and innovation is characterized by international synergy, interdisciplinary perspectives, and proactive engagement with academic partners and funding agencies. This places us at the forefront of impactful research, poised to make a difference on a global scale.
The EMIA PROJECT Epi-Terrestrial Multi-Modals Input Assimilation
Unlike conventional machine learning algorithms in traffic CCTV, EMIA proposes a refocus of implementing road safety standards by extracting human centric parameters from existing traffic CCTV, as well as extending the reach of information by incorporating and analyzing video footage transmitted from enrolled dashcams among frequent road users. The source of the footage will be anonymized, and any unsuitable footage will be automatically deleted prior to transmission. In addition, EMIA proposes Ai conversion of existing LIDAR points cloud data of Singapore and Virtual Singapore into a High-Definition structure that can be interactive with humans and Ai within the AIMU. This new approach enables faster conversion and easier automatic assimilation and computation of change in urban infrastructure, coastal erosion, traffic diversion and evacuation in a flooding disaster especially in cities susceptible to climate change. Finally, EMIA will mesh the traffic Big Data in the AIMU superconstruct for synchronization and data interaction so that this new form of city Ai will be useful for semi-supervised computation for optimized traffic. These efforts contribute to 6 of 17 United Nation Sustainable Development Goals.
Flood Ultra-Cognitive Dendrite (FLUD)
Interactive Coventry Ltd, in collaboration with Coventry University and a Malaysian industrial partner, has received a prestigious funding award to lead the development of an advanced urban flooding monitoring and forecasting platform.
The project titled “Flood Ultra-Cognitive Dendrite (FLUD)” will build upon state of the art research, and technologies in computational intelligence and machine learning, to develop an urban flooding monitoring and forecasting platform. FLUD aims to minimise the impact of flash floods through developing an economically sustainable and effective technical approach to flood-alert systems.
The proposed solution will provide accurate, and timely predictions enabling corresponding authorities to carry out pre-emptive actions in order to minimise the devastating effects of severe urban flooding, and support effective decision making in matters such as installation and maintenance of the necessary infrastructure, allocation of resources, traffic network management etc.
The developed system will be tested at two high-risk sites in Malaysia to validate its operational effectiveness with urban authorities. The final product will be benchmarked for utilisation in smart city projects in Malaysia, the UK, and other countries facing extreme urban flooding.
INTELLIGENT SAFETY WARNING SYSTEM FOR DRIVERS
Interactive Coventry is developing a driver assist device for identifying and modelling hazardous situations and providing real-time and offline feedback to the driver and to relevant stakeholders. This device utilises a unique multi-layered hybrid computational intelligence algorithm for defining, modelling, and identifying danger levels during driving.
We take a new holistic approach for identifying and modelling hazardous situations. Our approach considers the driver’s behavior and driving style as well as environmental factors in order to recognise potential dangerous situations, and produce feedback to assist the driver. Our solutions are able to identify a wide range of driving/road conditions such as weather, traffic, time of day/year, and individual driving styles to create a uniform measure of the driver’s performance. In order to achieve its goals our product proposes a unique combination of inputs and utilises a novel multilayer algorithm.
Digi CAV
The validation of high-level autonomy features requires large amounts of test data, which conventionally is achieved by accumulating miles on the road and dedicated proving grounds. A conventional new car model costs between $1-6 billion to take through from design to commercialisation, and as much as half of this can be validation costs. For highly automated vehicles (SAE Level 4+) vehicles currently in development, the validation costs are likely to be significantly higher, which will slow the introduction and take-up through increased costs.
The aim of this project is to de-risk the technical approach to build a simulation platform that would significantly reduce these validation costs.
AI Based Simulation For Labour Market
The project addresses the need to understand and gain evidence based insight into complex socio-economic and environmental dynamics of Saudi Arabia’s labour market.
It will achieve this through the use of novel nature-inspired Computational Intelligence (CI) and agent based modelling techniques which, when combined with relevant large multi-source datasets, will be used to model complex socio-economic conditions that affect labour mobility and diversification especially in the private sector.
Our AI solutions are supported by the NVIDIA inception program