Generalised network architectures for environmental sensing: case studies for a digitally enabled environment

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dc.contributor.authorMead, Mohammed Iqbal
dc.contributor.authorBevilacqua, M.
dc.contributor.authorLoiseaux, C.
dc.contributor.authorHallett, Stephen H.
dc.contributor.authorJude, Simon
dc.contributor.authorEmmanouilidis, Christos
dc.contributor.authorHarris, Jim A.
dc.contributor.authorLeinster, Paul
dc.contributor.authorMutnuri, S.
dc.contributor.authorTran, Trung Hieu
dc.contributor.authorWilliams, Leon
dc.date.accessioned2022-05-05T08:22:39Z
dc.date.available2022-05-05T08:22:39Z
dc.date.issued2022-04-08
dc.description.abstractA digitally enabled environment is a setting which incorporates sensors coupled with reporting and analytics tools for understanding, observing or managing that environment. Large scale data collection and analysis are a part of the emerging digitally enabled approach for the characterisation and understanding of our environment. It is recognised as offering an effective methodology for addressing a range of complex and interrelated social, economic and environmental concerns. The development and construction of the approach requires advances in analytics control linked with a clear definition of the issues pertaining to the interaction between elements of these systems. This paper presents an analysis of selected issues in the field of analytics control. It also discusses areas of progress, and areas in need of further investigation as sensing networks evolve. Three case studies are described to illustrate these points. The first is a physical analytics test kit developed as a part of the “Reinvent the Toilet Challenge” (RTTC) for process control in a range of environments. The second case study is the Cranfield Urban Observatory that builds on elements of the RTTC and is designed to allow users to develop user interfaces to monitor, characterise and compare a variety of environmental and infrastructure systems plus behaviours (e.g., water distribution, power grids). The third is the Data and Analytics Facility for National Infrastructure, a cloud-based high-performance computing cluster, developed to receive, store and present such data to advanced analytical and visualisation tools.en_UK
dc.description.sponsorshipEngineering and Physical Sciences Research Council (EPSRC): EP/P016782/1, EP/R013411/1, EP/R012202/1 and EP/R017727/1. Bill & Melinda Gates Foundationen_UK
dc.identifier.citationMead MI, Bevilacqua M, Loiseaux C, et al., (2022) Generalised network architectures for environmental sensing: case studies for a digitally enabled environment, Array, Volume 14, July 2022, Article number 100168en_UK
dc.identifier.issn2590-0056
dc.identifier.urihttps://doi.org/10.1016/j.array.2022.100168
dc.identifier.urihttp://dspace.lib.cranfield.ac.uk/handle/1826/17863
dc.language.isoenen_UK
dc.publisherElsevieren_UK
dc.rightsAttribution 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.subjectUbiquitous sensor networksen_UK
dc.subjectNetwork analyticsen_UK
dc.subjectIntegrated sensingen_UK
dc.subjectNetwork policy considerationsen_UK
dc.subjectLiving laboratoryen_UK
dc.subjectDigital environmenten_UK
dc.subjectInternet of thingsen_UK
dc.subjectUrban observatoryen_UK
dc.titleGeneralised network architectures for environmental sensing: case studies for a digitally enabled environmenten_UK
dc.typeArticleen_UK

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