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Cited by 30IoT and GPS-based Vehicle Safety SystemsTraffic and Road SafetyIoT and Edge/Fog Computing

The DOI matches its Crossref record.

An intelligent smartphone based approach using IoT for ensuring safe driving

Mamun, Mohd Abdullah Al, Puspo, Jinat Afroj, Das, Amit Kumar·2017·2017 International Conference on Electrical Engineering and Computer Science (ICECOS)
DOI 10.1109/icecos.2017.8167137
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Abstract

Road accident is a widespread problem all over the world. The number of the vehicle is increasing rapidly. Therefore, the probability of an accident is also increasing. So in this paper, we propose an IoT-based system for providing safe driving. It will collect data using smartphone and show the driver about the condition of the road. We have developed an Android based application which will collect data from a vehicle and send it to its nearest IoT-Fog server for processing the data quickly. We also developed two algorithms using k-means clustering approach which find the location of road anomalies and accident prone area. The result will be shown in Google map of driver's smartphone. This information will be stored in cloud for further use. We have tested our proposed system through statistical as well as experimental evaluations. Simulation result shows that our approach can provide better performance compared to state-of-the-art methods.

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Crossref · 10.1109/icecos.2017.8167137

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  • [33] clusters accelerometer data with the K-Means algorithm to distinguish normal from abnormal roads.

    “Accelerometer data are also used in [33], clustered by the K-Means algorithm to distinguish normal from abnormal roads.”

    From A Review of Machine Learning and IoT in Smart Transportation (2019) · cites this paper as [33]

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Research works printed but not linked: 21

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Metadata

Authors
Mamun, M. A. A., Puspo, J. A., & Das, A. K.
Affiliations
East West University (BD)
ORCID
Das, Amit Kumar
Venue
2017 International Conference on Electrical Engineering and Computer Science (ICECOS)
Publisher
IEEE
Published
2017-08
Pages
217-223
DOI
10.1109/icecos.2017.8167137
OpenAlex
W2774386491
Cited by
30
References
0
Citations by year
2025: 1 · 2024: 3 · 2023: 3 · 2022: 5 · 2021: 6 · 2020: 3 · 2019: 9
FWCI
7.72
Type
conference paper
Language
en
Open access
closed
Topics
  • Physical Sciences › Engineering › Automotive Engineering › IoT and GPS-based Vehicle Safety Systems
  • Physical Sciences › Engineering › Safety, Risk, Reliability and Quality › Traffic and Road Safety
  • Physical Sciences › Computer Science › Computer Networks and Communications › IoT and Edge/Fog Computing
Keywords
driving safety, traffic accident prevention, Internet of Things, mobile application, Android, fog computing, K-means clustering, road anomaly detection, Google Maps, cloud storage, vehicle data collection

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