On Road Anomalies Prediction using Support Vector Machine


Authors : B.SAILAJA, B.PADMAJA.

Volume/Issue : Volume 4 - 2019, Issue 6 - June

Google Scholar : https://goo.gl/DF9R4u

Scribd : https://bit.ly/2Jd6ZU7

As the number of vehicles in the cities increased day by day, the issues related to road security have ended up being more complex. Anomalies on road pavement cause distress to drivers and travelers, and may cause mechanical damages or even mishaps. Governments invest many Euros consistently on road development, frequently leads to automobile overloads and blockage on urban roads on a day by day analysis. In such specific circumstances, giving road condition data to various stakeholders is a significant errand for driver security, accommodation and solace. This might be accomplished by continually reviewing road surface for inconsistencies and undertaking remedial measures as needed, for example, fixing of roads or advising the stakeholders. This paper mainly concentrates on detection of road anomalies using Support Vector machine algorithm there by providing the information about road conditions through the large amount of data set being collected including the data of different anomaly road conditions like potholes and speed bumps etc. to the public.

Keywords : Data Mining, Anomalies, Speed Bump, Potholes.

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