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dc.contributor.authorAlofe, Olasunkanmi Matthew
dc.contributor.authorFatema, Kaniz
dc.contributor.authorAzad, Muhammad Ajmal
dc.contributor.authorKurugollu, Fatih
dc.date.accessioned2020-09-04T11:30:19Z
dc.date.available2020-09-04T11:30:19Z
dc.date.issued2020
dc.identifier.citationAlofe, O, M., Fatema, K., Azad, M., A., and Kurugollu, F. (2020). ‘Persation: an IoT based personal safety prediction model aided solution’. International Journal of Computing and Digital Systems, pp. 1-11.en_US
dc.identifier.issn2210-142X
dc.identifier.urihttp://hdl.handle.net/10545/625155
dc.description.abstractThe number of attacks on innocent victims in moving vehicles, and abduction of individuals in their vehicles has risen alarmingly in the past few years. One common scenario evident from the modus operandi of this kind of attack is the random motion of these vehicles, due to the driver’s unpredictable behaviours. To save the victims in such kinds of assault, it is essential to offer help promptly. An effective strategy to save victims is to predict the future location of the vehicles so that the rescue mission can be actioned at the earliest possibility. We have done a comprehensive survey of the state-of-the-art personal safety solutions and location prediction technologies and proposes an Internet of Things (IoT) based personal safety model, encompassing a prediction framework to anticipate the future vehicle locations by exploiting complex analytics of current and past data variables including the speed, direction and geolocation of the vehicles. Experiments conducted based on real-world datasets demonstrate the feasibility of our proposed framework in accurately predicting future vehicle locations. In this paper, we have a risk assessment of our safety solution model based on OCTAVE ALLEGRO model and the implementation of our prediction model.en_US
dc.description.sponsorshipN/Aen_US
dc.language.isoenen_US
dc.publisherUniversity of Bahrainen_US
dc.relation.urlhttps://journal.uob.edu.bh/handle/123456789/4034en_US
dc.subjectIoT, mobile application, vehicle location identification, GPS, location predictionen_US
dc.titlePersation: an IoT based personal safety prediction model aided solutionen_US
dc.typeArticleen_US
dc.contributor.departmentUniversity of Derbyen_US
dc.contributor.departmentAston University, Birminghamen_US
dc.identifier.journalInternational Journal of Computing and Digital Systemsen_US
dcterms.dateAccepted2020-07-17
dc.author.detailSTF4965en_US


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