This project creates low-power sensing systems using spiking neural networks to detect threats in public spaces.

This project develops resilient AI systems to protect data integrity and quality of AI on the Edge.

This project develops a multi-model AI system to accurately identify and count wildlife in camera trap images.

This project develops tangible interfaces to assist young people with neurodiversity to manage online harms.

This project develop an augmented reality-based Smart City demonstrator using Lego towards public engagement

We organised a PETRAS Showcase and Networking Event at Cardiff to bring together like minded people

This project design, develop and manage Smart Home Lab research infrastructure

CyberASAP helps academics in UK universities commercialise their cyber security ideas.

This project aim to develop an MSc module on Edge Analytics in collaboration with two leading Indian Universities.

This project aims to integrate the outcomes ICE project, into a decision support mechanism at Thales UK.

This project aims to strengthen international collaborations by setting up a series of collaborative projects across partners.

This project demonstrates how to utilise a digital platform to be benefited by sustainable circular supply chain.

This secondment aims to explore how to add layers of resilience to built environments.

This fellowship aims to explore how can we use low-cost multi-sensors to detect cyber attacks against ICS.

The project aims tackl rural isolation, improve farm security and bolster the tourism industry

This project aims to explore how IoT can help to conduct wildlife research.

This project aims to create a semantically enriched quarriable smart city data markets.

This project aims to analyse vulnerabilities of interactions between edge devices, cloud platforms and legacy ICS systems.

This project aims to develop a 100 node testbed to support data science and edge computing research.

This project aims to explore how IoT can be taught efficitnely and effectively in University settings

We explore how our previously proposed guideline can be used to design ‘new’ IoT applications.

The Sensing as a Service (S2aaS) model promotes data exchange/trading between data owners and data consumers.

This project implemented and evaluated Fog computing and its applications.

This project explores the use of natural language to give instructions that might be interpreted by Internet of Things (IoT) devices in a domestic ‘smart home’ environment.

The OpenIoT middleware infrastructure supports flexible configuration and deployment of algorithms for collection, and filtering information streams.