University of Bahrain
Scientific Journals

Persation: an IoT Based Personal Safety Prediction Model Aided Solution

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dc.contributor.author Alofe, Olasunkanmi Matthew
dc.contributor.author Fatema, Kaniz
dc.contributor.author Azad, Muhammad Ajmal
dc.contributor.author Kurugollu, Fatih
dc.date.accessioned 2020-07-21T14:03:39Z
dc.date.available 2020-07-21T14:03:39Z
dc.date.issued 2020-07-01
dc.identifier.issn 2210-142X
dc.identifier.uri https://journal.uob.edu.bh:443/handle/123456789/4034
dc.description.abstract The 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.language.iso en en_US
dc.publisher University of Bahrain en_US
dc.rights Attribution-NonCommercial-NoDerivatives 4.0 International *
dc.rights.uri http://creativecommons.org/licenses/by-nc-nd/4.0/ *
dc.subject IoT en_US
dc.subject mobile application en_US
dc.subject vehicle location identification en_US
dc.subject GPS en_US
dc.subject location prediction en_US
dc.title Persation: an IoT Based Personal Safety Prediction Model Aided Solution en_US
dc.type Article en_US
dc.volume 9 en_US
dc.pagestart 1 en_US
dc.pageend 11 en_US
dc.source.title International Journal of Computing and Digital Systems en_US
dc.abbreviatedsourcetitle IJCDS en_US


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