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Proceedings ArticleDOI

Real time in-vehicle air quality monitoring using mobile sensing

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TLDR
A novel mobile sensing system is proposed to monitor and understand change in VIAQ, built by using an Android Smartphone and a mobile sensor, is independent of car age and model, and monitors ViaQ at all times.
Abstract
Vehicle Indoor Air Quality (VIAQ) is a very important parameter that we often tend to ignore in our daily driving. VIAQ can worsen due to build-up of carbon dioxide (CO2), carbon monoxide (CO) and other harmful gases emitted by vehicles. Poor VIAQ can lead to short term health conditions like drowsiness, breathlessness, discomfort and headache. Drowsiness while driving is a predominant health condition that leads to large number of accidents and deaths all over the world. Standard equipment of air intake and recirculation in both low end and high end cars do not completely support pervasive maintenance of VIAQ. Due to unavailability of miniaturized sensors, a general purpose solution to this problem was rarely studied and addressed. In this work, we propose a novel mobile sensing system to monitor and understand change in VIAQ. Our mobile sensing system is general purpose, built by using an Android Smartphone and a mobile sensor, is independent of car age and model, and monitors VIAQ at all times.

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Citations
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Journal ArticleDOI

An IoT-Based Vehicle Accident Detection and Classification System Using Sensor Fusion

TL;DR: This work presents an IoT-based automotive accident detection and classification (ADC) system, which uses the fusion of smartphone’s built-in and connected sensors not only to detect but also to report the type of accident.
Proceedings ArticleDOI

Modeling IoT Enabled Automotive System for Accident Detection and Classification

TL;DR: An IoT based system has been developed in this work to report the occurrence, location as well as the type of road accident, which uses Naïve Bayes classifier for classification.
Journal ArticleDOI

Real-Time In-Vehicle Air Quality Monitoring System Using Machine Learning Prediction Algorithm.

TL;DR: In this paper, a real-time cloud-based in-vehicle air quality monitoring system that enables the prediction of the current and future cabin air quality is presented, using machine learning algorithms that can measure the drivers' drowsiness and fatigue based on the air quality presented in the cabin car.
Proceedings ArticleDOI

Vehicle Fall Severity Modeling using IoT and K-Nearest Neighbor Algorithm

TL;DR: An IoT system is presented, which can detect and classify the occurrence of a vehicle fall event with the help of inbuilt sensors of a contemporary smartphone and a k-Nearest Neighbor based fall occurrence and classification model.
References
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Chapter 2 Measurement of Thermal Balance of Man

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Book ChapterDOI

Drone to the Rescue: Relay-Resilient Authentication using Ambient Multi-sensing

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