Detecting and Alerting Damaged Roads Using Smart Street System

Authors(2) :-Shathish Kumar, Dr. A. Jayachandran

Develop an infrastructure-free approach for anomaly detection and identification based on data collected through a smartphone application (SMART STREET). The approach is capable of effectively finding the damaged roads and effectively classifying roadway obstacles and knowing its type using machine learning algorithms, and accelerometer in smartphone ,as well as prioritizing actionable ones in need of immediate attention based on a proposed “anomaly index.” We explore some algorithms that combine clustering with classification and introduce appropriate regularization in order to concentrate on a sparse set of most relevant features, which has the effect of reducing over fitting.I introduce, combines novel metrics of obstacle irregularity computed based on the data captured and alerting system by the smartphone application (Smart Street). It Results by capturing the location of damaged road and transferring it to the corporation by an alert message .The data collector in corporation will receive the alert message and instruct the corporation to take necessary action for repairing the road.

Authors and Affiliations

Shathish Kumar
Department of M.Sc(Software Engineering), PSN College of Engineering & Technology, Tirunelveli,Tamilnadu,India
Dr. A. Jayachandran
Department of M.Sc(Software Engineering), PSN College of Engineering & Technology, Tirunelveli,Tamilnadu,India

Connected Autonomous Vehicles, Support Vector Machine, Mean Squared Error, Sparse Support Vector Machine, Receiver Operating Characteristics, Area under the ROC Curve.

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Publication Details

Published in : Volume 2 | Issue 2 | March-April 2017
Date of Publication : 2017-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 744-750
Manuscript Number : CSEIT1722212
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Shathish Kumar, Dr. A. Jayachandran, "Detecting and Alerting Damaged Roads Using Smart Street System", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 2, Issue 2, pp.744-750, March-April-2017.
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