Irregularity Finding in Roads Conditions using Data Mining: A Survey

Road conditions play a vital role now days. Irregularity in road surface can cause accidents, vehicle failure and discomfort in drivers and passengers. Governments spend lots of amount every year in maintenance of roads for keeping roads in proper condition. But more maintenance work can increase the traffic, causing disturbance in road users. To avoid disturbances caused by road irregularity,this system can detect road irregularity using Smartphone sensors. The approach is based on data mining. In this, it used scikit-learn, a python module, and Weka, as tools for data-mining. All cleaning data process was made using python language. The final outputs show that it is possible to find out road irregularity

Towards Comfortable Cycling: A Practical Approach to Monitor the Conditions in Cycling Paths

This is a no brainer. Using bicycles to commute is the most sustainable form of transport, is the least expensive to use and are pollution-free. Towns and cities have to be made bicycle-friendly to encourage their wide usage. Therefore, cycling paths should be more convenient, comfortable, and safe to ride. This paper investigates a smartphone application, which passively monitors the road conditions during cyclists ride. To overcome the problems of monitoring roads, we present novel algorithms that sense the rough cycling paths and locate road bumps. Each event is detected in real time to improve the user friendliness of the application. Cyclists may keep their smartphones at any random orientation and placement. Moreover, different smartphones sense the same incident dissimilarly and hence report discrepant sensor values. We further address the aforementioned difficulties that limit such crowd-sourcing application. We evaluate our sensing application on cycling paths in Singapore, and show that it can successfully detect such bad road conditions.Comment: 6 pages, 5 figures, Accepted by IEEE 4th World Forum on Internet of Things (WF-IoT) 201

Anomaly detection in roads with a data mining approach

Road condition has an important role in our daily live. Anomalies in road surface can cause accidents, mechanical failure, stress and discomfort in drivers and passengers. Governments spend millions each year in roads maintenance for maintaining roads in good condition. But extensive maintenance work can lead to traffic jams, causing frustration in road users. In way to avoid problems caused by road anomalies, we propose a system that can detect road anomalies using smartphone sensors. The approach is based in data-mining algorithms to mitigate the problem of hardware diversity. In this work we used scikit-learn, a python module, and Weka, as tools for data-mining. All cleaning data process was made using python language. The final results show that it is possible detect road anomalies using only a smartphone.European Structural and Investment Funds in the FEDER component, through the Operational Competitiveness and Internationalization Programme (COMPETE 2020)This research is sponsored by the Portugal Incentive System for Research and Technological Development. Project in co-promotion nº 002797/2015 (INNOVCAR 2015-2018)info:eu-repo/semantics/publishedVersio

スマートフォンセンサーを用いた道路路面粗さの広域簡易推計手法の開発

首都大学東京, 2014-09-30, 博士（工学）首都大学東