Urban intelligence research aims to pave the way in rethinking the built environment and improve sustainability, resilience and service quality.
The built environment is increasingly embracing digital technologies, including control and automation systems. As such it is paving the way to smarter ways of managing our buildings and wider infrastructures. These smart built environments are facing increasing pressures to improve sustainability, resilience and service quality.
Our aim is to pave the way in rethinking the built environment, adapted to the challenges of the 21st century.
We will focus on four main areas:
- resilience and citizen engagement.
We will deliver a roadmap in urban intelligence research. To assist with this activity, the group will:
- cultivate collaborative links with University research institutes as active co-creation forums to nurture and crystallise urban intelligence research ideas
- initiate sustainable links and collaborations with local authorities to engage the urban value chain in our research
- establish links with our GW4 partners to deliver globally competitive research
- foster links with our European research collaborators
- nurture research links with our non-EU collaborators.
Our multidisciplinary research group is collaborating with over 30 organisations in the UK and across Europe on several UKRI and Horizon2020 project.
Our research projects include:
TABEDE aims to allow all buildings to integrate energy grid demand response schemes through a low cost extender for Building Management Systems (BMS) systems or as a standalone system, which is independent of communication standards and integrates innovative flexibility algorithms.
Demand response integration tEchnologies
Demand Response Integration tEchnologies (DRIvE) will unlock the demand response potential of residential and tertiary buildings in the distribution grid. It will do this through a comprehensive platform for the seamlessly existing assets and buildings to achieve optimal operations in the next generation of Smart Grids, paving the way to a fully deployed DR market in the distribution network.
Building information modelling energy efficiency training (BIMEET)
BIMEET aims to establish a Building Information Modelling (BIM) based EU-wide standardised qualification framework for an energy efficiency framework. BIMEET will address some of the challenges facing the construction sector as they work towards achieving increasingly ambitious energy efficiency objectives, as well as using the latest digital technology for BIM.
PENTAGON: Unlocking European grid local flexibility through augmented energy conversion capabilities at district level
PENTAGON aims to pave the way for a new generation of eco-districts, leveraging on enhanced energy systems, and a high level integrated management platform simultaneously acting on different energy carriers.
THERMOSS: Building and district thermal retrofit and management solutions
THERMOSS aims to produce an outstanding contribution to the wider deployment of advanced building heating and cooling technologies in the EU. It aims to significantly enhance energy efficiency of residential buildings and to facilitate their connection to district heating and cooling networks.
REACH: Assessing and enhancing building resilience in response to post-earthquake landslides in China
Understanding how communities recover from landslides associated with large earthquakes will be the subject of a new Natural Environment Research Council (NERC) funded collaboration between Cardiff University’s Sustainable Places Research Institute, the Building Research Establishment (BRE) Trust Centre for Sustainable Construction and the Chengdu Institute of Technology-State Key Laboratory of Geohazard Prevention and Geoenvironment Protection.
piSCES: Smart cluster energy system for the fish processing industry
The aim of the piSCES (smart cluster energy system) project is to reduce the cost and carbon footprint of energy networks in the fish processing industry by implementing smart grid technologies. This will be done by modelling the usage profile of their energy network and optimising that against the wholesale energy market and any available onsite generation.