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Road Condition Map Via Smartphone-An Android Application


Affiliations
1 PIMT, Mandi Gobindgarh-147301, India
 

Monitoring condition of ever expanding road networks is challenging and expensive. Smartphones can provide a novel solution to the problem. This paper focuses on the possibility of using smartphones as community sensor network for road condition monitoring. Rapid increase in the use of smartphones by wide population and the availability of low cost sensors in them further supports the use of smartphone for the task. This research work was conducted in cities like Khanna, Mandi Gobindgarh and nearby villages (Punjab, India) by covering a long distance. Experimental program for data collection, processing and displaying the road condition as colored lines on Google® maps is presented. These Google maps can be used by commuters to estimate the road condition. The performance of the proposed work was evaluated using svm with 93.75% of accuracy. Further, this research work helps in continuous monitoring of road condition.

Keywords

Google Map, Road Anomaly, Smartphones, Support Vector Machine.
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  • Road Condition Map Via Smartphone-An Android Application

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Authors

Rajiv Kumar
PIMT, Mandi Gobindgarh-147301, India

Abstract


Monitoring condition of ever expanding road networks is challenging and expensive. Smartphones can provide a novel solution to the problem. This paper focuses on the possibility of using smartphones as community sensor network for road condition monitoring. Rapid increase in the use of smartphones by wide population and the availability of low cost sensors in them further supports the use of smartphone for the task. This research work was conducted in cities like Khanna, Mandi Gobindgarh and nearby villages (Punjab, India) by covering a long distance. Experimental program for data collection, processing and displaying the road condition as colored lines on Google® maps is presented. These Google maps can be used by commuters to estimate the road condition. The performance of the proposed work was evaluated using svm with 93.75% of accuracy. Further, this research work helps in continuous monitoring of road condition.

Keywords


Google Map, Road Anomaly, Smartphones, Support Vector Machine.