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Smart Safety Monitoring System for Vehicles

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Wen-Qiang YinAuthors Info & Claims

BDIOT '18: Proceedings of the 2018 2nd International Conference on Big Data and Internet of Things

Pages 84 - 87

https://doi.org/10.1145/3289430.3289467

Published: 24 October 2018 Publication History

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Abstract

This paper introduces the design idea and hardware and software realization of a smart safety monitoring system for vehicles, in order to satisfy drivers' driving, and health and safety needs. This system collects and analyses driver's behavior inter-dimensionally through multiple sensors placed on the car and the smart band which the driver wears. It detects drunk and fatigue driving, heart rate, blood pressure, body temperature, etc. The experiments show that this system works fairly well in preventing driving hazards and in monitoring the driver's health. The system's effectiveness and reliability in real-time are demonstrated.

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Kashevnik ALashkov IAxyonov AIvanko DRyumin DKolchin AKarpov A(2021)Multimodal Corpus Design for Audio-Visual Speech Recognition in Vehicle CabinIEEE Access10.1109/ACCESS.2021.30627529(34986-35003)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3062752
Kashevnik ALashkov IPonomarev ATeslya NGurtov A(2020)Cloud-Based Driver Monitoring System Using a SmartphoneIEEE Sensors Journal10.1109/JSEN.2020.297538220:12(6701-6715)Online publication date: 15-Jun-2020
https://doi.org/10.1109/JSEN.2020.2975382

Index Terms

Smart Safety Monitoring System for Vehicles
1. Software and its engineering
  1. Software creation and management
    1. Designing software
      1. Software implementation planning
        Software design techniques

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Published In

BDIOT '18: Proceedings of the 2018 2nd International Conference on Big Data and Internet of Things

October 2018

217 pages

ISBN:9781450365192

DOI:10.1145/3289430

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Deakin University

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Association for Computing Machinery

New York, NY, United States

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Published: 24 October 2018

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Guilin University of Electronic Technology

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BDIOT 2018

BDIOT 2018: 2018 2nd International Conference on Big Data and Internet of Things

October 24 - 26, 2018

Beijing, China

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Overall Acceptance Rate 75 of 136 submissions, 55%

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Kashevnik ALashkov IAxyonov AIvanko DRyumin DKolchin AKarpov A(2021)Multimodal Corpus Design for Audio-Visual Speech Recognition in Vehicle CabinIEEE Access10.1109/ACCESS.2021.30627529(34986-35003)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3062752
Kashevnik ALashkov IPonomarev ATeslya NGurtov A(2020)Cloud-Based Driver Monitoring System Using a SmartphoneIEEE Sensors Journal10.1109/JSEN.2020.297538220:12(6701-6715)Online publication date: 15-Jun-2020
https://doi.org/10.1109/JSEN.2020.2975382

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Recommendations

Smart driver monitoring system

Driving to safety: real-time danger spot and drowsiness monitoring system

Enhancing Driving Safety via Smart Sensing Techniques

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