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dc.contributor.authorN., Fadzil
dc.contributor.authorN. H., Abu Bakar
dc.contributor.authorS. M., Idrus
dc.contributor.authorA. I., Azmi
dc.contributor.authorS. H., Mohammad
dc.contributor.authorN., Ali
dc.date.accessioned2022-05-13T07:10:31Z
dc.date.available2022-05-13T07:10:31Z
dc.date.issued2021-12
dc.identifier.citationInternational Journal of Nanoelectronics and Materials, vol.14 (Special Issue), 2021, pages 227-236en_US
dc.identifier.issn1985-5761 (Printed)
dc.identifier.issn1997-4434 (Online)
dc.identifier.urihttp://dspace.unimap.edu.my:80/xmlui/handle/123456789/75210
dc.descriptionLink to publisher's homepage at http://ijneam.unimap.edu.myen_US
dc.description.abstractPublic social distancing has been a great concern for the worldwide community as the World Health Organization (WHO) has declared the COVID-19 pandemic as a Public Health Emergency of International Concern (PHEIC). With regards to this global issue, this paper will share the latest commercially available solution and technology on crowd monitoring systems to determine the number of people in confined and crowded spaces at airport terminals which may have the potential for contagious diseases infection. Estimation of crowd dynamics is essential for crowd monitoring to ensure public safety by reducing the possibility of being infected by the COVID-19 virus. In this report a number of commercial and under development crowd monitoring products are reviewed and presented. Research and development of crowd monitoring technology is increasingly demanding to monitor crowds at strategic locations such as entry and exit points of closed areas to ensure public safety and to control the pandemic. In particular for the strategic area at the airport terminal, an efficient crowd monitoring solution is expected to support huge data collection and real time analysis, as well as providing online monitoring of crowds based on non-contact sensors for movement counting to restrain COVID-19 outbreaks.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subject.otherCrowd Monitoring, Covid-19en_US
dc.subject.otherMachine learningen_US
dc.subject.otherThermal Detectionen_US
dc.subject.otherImage Processingen_US
dc.titleRecent development of crowd monitoring technology solution for Covid-19 prevention at airport terminalen_US
dc.typeArticleen_US
dc.identifier.urlhttp://ijneam.unimap.edu.my
dc.contributor.urlsevia@utm.myen_US


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