Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/33529
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dc.contributor.authorJabeen, R-
dc.contributor.authorRasekh, M-
dc.contributor.authorBalachandran, W-
dc.date.accessioned2026-06-28T17:58:57Z-
dc.date.available2026-06-28T17:58:57Z-
dc.date.issued2026-06-28-
dc.identifierORCiD: Wamadeva Balachandran https://orcid.org/0000-0002-4806-2257-
dc.identifier.citationJabeen, R., Rasekh, M. and Balachandran, W. (2026) 'Real-Time Synchronisation in Low-Power Wireless Sensor Networks: From Industry to Healthcare', Technologies, 14 (7), 394, pp. 1–43. doi: 10.3390/technologies14070394.en-GB
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/33529-
dc.descriptionData Availability Statement: No new data were created or analysed in this study. Data sharing is not applicable to this article.en-GB
dc.description.abstractThe growing demand for real-time data synchronisation has increased the importance of supervisory control systems in industrial automation, smart grids, healthcare monitoring, and environmental applications. Low-power wireless sensor networks (LPWSNs) have emerged as key enablers of scalable and energy-efficient monitoring. However, achieving reliable synchronisation remains challenging due to latency, energy constraints, scalability limitations, security vulnerabilities, and data integrity concerns. This review examines the role of time synchronisation in supervisory control systems and evaluates how LPWSNs support real-time monitoring and decision-making. Established synchronisation protocols, including Reference Broadcast Synchronisation (RBS), the Flooding Time Synchronisation Protocol (FTSP), and the Timing-Sync Protocol for Sensor Network (TPSN), are analysed in terms of accuracy, energy efficiency, and scalability. Key optimisation strategies, such as clock drift compensation, data aggregation and compression, and edge computing, are also discussed. Recent advances, including artificial intelligence and machine learning (AI/ML)-based predictive synchronisation, blockchain, software-defined networking (SDN), and 5G-enabled LPWSNs, are reviewed across industrial, energy, healthcare, and agricultural applications. The review critically evaluates their benefits and trade-offs and identifies remaining challenges related to cybersecurity, energy efficiency, and large-scale deployment. Finally, future research directions are outlined to support robust, scalable, and efficient real-time synchronisation in LPWSNs.en-GB
dc.description.sponsorshipThis work received no external funding.en-GB
dc.format.extentpp. 1–43-
dc.format.mediumElectronic-
dc.languageEnglishen-GB
dc.language.isoengen-GB
dc.publisherMDPIen-GB
dc.rightsCreative Commons Attribution 4.0 International-
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/-
dc.subjectreal-time synchronisationen-GB
dc.subjectsupervisory control systemsen-GB
dc.subjectlow-power wireless sensor networks (LPWSNs)en-GB
dc.subjectInternet of Things (IoT)en-GB
dc.subjectindustrial automationen-GB
dc.subjectsmart healthcareen-GB
dc.subjectenergy efficiencyen-GB
dc.subjectscalabilityen-GB
dc.titleReal-Time Synchronisation in Low-Power Wireless Sensor Networks: From Industry to Healthcareen-GB
dc.typeArticleen-GB
dc.date.dateAccepted2026-06-26-
dc.identifier.doihttps://doi.org/10.3390/technologies14070394-
dc.relation.isPartOfTechnologiesen-GB
pubs.issue7-
pubs.publication-statusPublished online-
pubs.volume14-
dc.identifier.eissn2227-7080-
dc.rights.licensehttps://creativecommons.org/licenses/by/4.0/legalcode.en-
dcterms.dateAccepted2026-06-26-
dc.rights.holderThe authors-
dc.contributor.orcidBalachandran, Wamadeva [0000-0002-4806-2257]-
dc.identifier.number394-
Appears in Collections:Department of Electronic and Electrical Engineering Research Papers

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