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Road Quality and Ghats Complexity analysis using Android sensors

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TLDR
A mobile sensing system (android application) for road irregularity detection using Android OS based smart phone sensors and research in identifying braking events - frequent braking indicates congested traffic conditions - and bumps on the roads to characterize the type of road is described.
Abstract
Importance of the road infrastructure for the society could be the same as importance of blood vessels for humans. Road surface quality should be monitored and repaired on a regular basis. It is very difficult to design a optimal system which gathers the road condition data and processes it. Participatory sensing approach can be mostly used for such data collection.The paper is describes a mobile sensing system (android application) for road irregularity detection using Android OS based smart phone sensors. Selected data processing algorithms are discussed and their evaluation presented with true positive rate as high as 90% using real world data. The optimal parameters for the algorithms are determined as well as recommendations for their application.Continuously keeping track on road and traffic conditions in a city is a problem widely studied. Many methods have available towards addressing this problem. But this methods proposed require dedicated hardware such as GPS devices and accelerometers in vehicles or cameras on roadside and near traffic signals. All such proposed are unaffordable tothe common man regarding of monetary cost and human effort required. We extend a prior study to improve the algorithm based on using accelerometer, GPS and magnetometer sensor readings for trafficand road conditions detection. We are specifically made research in identifying braking events - frequent braking indicates congested traffic conditions - and bumps on the roads to characterize the type of road.

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Journal ArticleDOI

Smartphone-Based Vehicle Telematics: A Ten-Year Anniversary

TL;DR: In this paper, the authors summarized the first ten years of research in smartphone-based vehicle telematics, with a focus on user-friendly implementations and the challenges that arise due to the mobility of the smartphone.
Posted Content

Smartphone-based Vehicle Telematics - A Ten-Year Anniversary

TL;DR: This paper summarizes the first ten years of research in smartphone-based vehicle telematics, with a focus on user-friendly implementations and the challenges that arise due to the mobility of the smartphone.
Journal ArticleDOI

Deep Learning-Based Speed Bump Detection Model for Intelligent Vehicle System Using Raspberry Pi

TL;DR: Deep learning and computer vision based speed bump detection model is proposed, which assist and control the driving behavior of an IVS before it reaches to speed bump and found to be more efficient and comparable with state-of-art techniques.
Proceedings ArticleDOI

Advance Driver Assistance System (ADAS) — Speed bump detection

TL;DR: A novel method is presented to achieve speed bump detection and recognition either to alert or to interact directly with the vehicle, without the investment of special sensors, hardware, Smartphone and GPS.
Proceedings ArticleDOI

Real time speed bump detection using Gaussian filtering and connected component approach

TL;DR: Gaussian filtering, median filtering and connected component analysis are used to detect speed bump in this proposed method that go well with the roads that are constructed with proper painting.
References
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Proceedings ArticleDOI

Nericell: rich monitoring of road and traffic conditions using mobile smartphones

TL;DR: Nericell is presented, a system that performs rich sensing by piggybacking on smartphones that users carry with them in normal course, and addresses several challenges including virtually reorienting the accelerometer on a phone that is at an arbitrary orientation, and performing honk detection and localization in an energy efficient manner.
Proceedings ArticleDOI

Wolverine: Traffic and road condition estimation using smartphone sensors

TL;DR: This work extends a prior study to improve the algorithm based on using accelerometer, GPS and magnetometer sensor readings for traffic and road conditions detection and proposes Wolverine - a non-intrusive method that uses sensors present on smartphones.
Book ChapterDOI

Distributed road surface condition monitoring using mobile phones

TL;DR: A pattern recognition system for detecting road condition from accelerometer and GPS readings and proposes a speed dependence removal approach for feature extraction and demonstrates its positive effect in multiple feature sets for the road surface anomaly detection task.
Journal ArticleDOI

A Study on the Use of Smartphones for Road Roughness Condition Estimation

TL;DR: Features and relationship of acceleration vibration that may be useful to express or estimate road roughness condition are explored and results show that acceleration data collected by smartphone sensors at different driving speeds has different significant linear relationships with road Roughness condition.
Proceedings ArticleDOI

Road Hazard Detection and Sharing with Multimodal Sensor Analysis on Smartphones

TL;DR: This study proposes a framework with built-in multimodal sensor analysis capability, and enables easy and rapid development of signal and image processing-based smart mobile applications.
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