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AI3SD Video: Artificial Intelligence for Safer Urban Space

AI3SD Video: Artificial Intelligence for Safer Urban Space
AI3SD Video: Artificial Intelligence for Safer Urban Space
The ever-growing adoption of big data technologies, smart sensing, data science and artificial intelligence is enabling the development of new intelligent urban spaces with real-time monitoring and advanced cyber-physical situational awareness capabilities. The advancement of cyber-physical situational awareness is experimented for achieving safer smart city spaces in Europe and beyond. The deployment of digital twins leads to understanding real-time situation awareness and risks of potential physical and/or cyber-attacks on urban critical infrastructure specifically. The critical extraction of knowledge using digital twins, which ingest, process and fuse observation data and information, prior to machine reasoning can also be performed. In this cyber behavior detection modules, which identify unusualness in cyber traffic networks can be deployed together with a physical behaviour detection module, based on computer vision and statistical methods. The two modules function within the so-called Malicious Attacks Information Detection System (MAIDS) digital twin.
AI, AI3SD Event, Artificial Intelligence, Big Data, Chemistry, Data Science, Data Sharing, Datasets, Machine Learning, Materials Discovery, ML
Sabeur, Zoheir
e6e98155-eadb-4b0f-ba88-ba5c313f0e24
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f
Sabeur, Zoheir
e6e98155-eadb-4b0f-ba88-ba5c313f0e24
Frey, Jeremy G.
ba60c559-c4af-44f1-87e6-ce69819bf23f
Kanza, Samantha
b73bcf34-3ff8-4691-bd09-aa657dcff420
Niranjan, Mahesan
5cbaeea8-7288-4b55-a89c-c43d212ddd4f

Sabeur, Zoheir (2021) AI3SD Video: Artificial Intelligence for Safer Urban Space. Frey, Jeremy G., Kanza, Samantha and Niranjan, Mahesan (eds.) AI3SD Autumn Seminar Series 2021. 13 Oct - 15 Dec 2021. (doi:10.5258/SOTON/AI3SD0173).

Record type: Conference or Workshop Item (Other)

Abstract

The ever-growing adoption of big data technologies, smart sensing, data science and artificial intelligence is enabling the development of new intelligent urban spaces with real-time monitoring and advanced cyber-physical situational awareness capabilities. The advancement of cyber-physical situational awareness is experimented for achieving safer smart city spaces in Europe and beyond. The deployment of digital twins leads to understanding real-time situation awareness and risks of potential physical and/or cyber-attacks on urban critical infrastructure specifically. The critical extraction of knowledge using digital twins, which ingest, process and fuse observation data and information, prior to machine reasoning can also be performed. In this cyber behavior detection modules, which identify unusualness in cyber traffic networks can be deployed together with a physical behaviour detection module, based on computer vision and statistical methods. The two modules function within the so-called Malicious Attacks Information Detection System (MAIDS) digital twin.

Video
AI3SDAutumnSeminar-081221-ZoheirSabeur - Version of Record
Available under License Creative Commons Attribution.
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More information

Published date: 8 December 2021
Additional Information: Zoheir Sabeur is Professor of Data Science and Artificial Intelligence at Bournemouth University (2019-present). He is also Visiting Professor of Data Science at Colorado School of Mines, Golden, Colorado, USA (2017-present). Zoheir was Science Director at the School of Electronics and Computer Science, IT Innovation Centre, University of Southampton (2009-2019). He led his data science research teams in more than 30 large projects as Principal Investigator (PI). The research was mainly supported with research grants (totalling £8.0M) and awarded by the European Commission (under FP5, FP6, FP7 and H2020), Innovate UK, DSTL, NERC and Industries. Prior to Southampton, Zoheir worked as Director and Head of Research, at BMT Group Limited (1996-2009), where he led his teams in the development of advanced environmental information systems, in particular the PROTEUS system for the UK O&G Industries and UK Government. Prior to that, Zoheir held several academic appointments in Computing as Senior Research Fellow at Oxford Brookes University(1993-1995), SERC Research Fellow at University of Leeds(1991-1993) and University of Strathclyde(1990-1991). He also worked as a Research Scientist in the Intensive Computing Lattice QCD Group at the University of Wuppertal, Germany (1987). Zoheir graduated with a PhD and MSc in Particle Physics from the University of Glasgow (1985-1990). His PhD was on "Lattice QCD at High Density with Dynamical Fermions". This was in fact his earliest involvement in "Data Science" using vector machines for intensive computing and understanding hadron matter thermodynamics, under the UK Lattice QCD Grand-Challenge. In the last decade or so, Zoheir's long research career, focussed more on fundamentals of Artificial Intelligence, knowledge extraction for human, natural, or industrial processes behaviour understanding. These are being investigated in context of cyber-physical security, healthcare, industrial, environmental systems, and more. Zoheir has published over 130 papers in scientific journals, conference proceedings and books. He is peer reviewer, member of international scientific committees and editing board of various science and engineering conferences and journals. Zoheir chairs the OGC Digital Global Grid System Specification and Domain Working Groups, and co-chairs the AI and Data Science Task Group at the BDVA. He is Fellow of the British Computer Society; Member of the Institute of Physics; and Fellow of IMaREST.
Venue - Dates: AI3SD Autumn Seminar Series 2021, 2021-10-13 - 2021-12-15
Keywords: AI, AI3SD Event, Artificial Intelligence, Big Data, Chemistry, Data Science, Data Sharing, Datasets, Machine Learning, Materials Discovery, ML

Identifiers

Local EPrints ID: 453345
URI: http://eprints.soton.ac.uk/id/eprint/453345
PURE UUID: 4a846f8d-3623-498d-9695-fa3fd849bbd3
ORCID for Jeremy G. Frey: ORCID iD orcid.org/0000-0003-0842-4302
ORCID for Samantha Kanza: ORCID iD orcid.org/0000-0002-4831-9489
ORCID for Mahesan Niranjan: ORCID iD orcid.org/0000-0001-7021-140X

Catalogue record

Date deposited: 13 Jan 2022 17:50
Last modified: 14 Jan 2022 02:53

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Contributors

Author: Zoheir Sabeur
Editor: Jeremy G. Frey ORCID iD
Editor: Samantha Kanza ORCID iD
Editor: Mahesan Niranjan ORCID iD

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