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Bychkovsky, V., Chen, K., Goraczko, H., Hu, H., Hull, B., Miu, A., Shih, E., Zhang, Y., Madden S. and Balakrishnan, H. (2006) The Cartel: A Distributed Mobile Sensor Computing System. 4th International Conference on Embedded Networked Sensor Systems, Boulder, November 2006, 125-138.
http://dx.doi.org/10.1145/1182807.1182866

has been cited by the following article:

• TITLE: Real Time Speed Bump Detection Using Gaussian Filtering and Connected Component Approach

  AUTHORS: W. Devapriya, C. Nelson Kennedy Babu, T. Srihari

  KEYWORDS: Intelligent Transportation System, Speed Bumps, Driver Assistance System, Gaussian and Median Filtering, Connected Component Analysis

  JOURNAL NAME: Circuits and Systems, Vol.7 No.9, July 12, 2016

  ABSTRACT: An Intelligent Transportation System (ITS) is a new system developed for the betterment of user in traffic and transport management domain area for smart and safe driving. ITS subsystems are Emergency vehicle notification systems, Automatic road enforcement, Collision avoidance systems, Automatic parking, Map database management, etc. Advance Driver Assists System (ADAS) belongs to ITS which provides alert or warning or information to the user during driving. The proposed method uses Gaussian filtering and Median filtering to remove noise in the image. Subsequently image subtraction is achieved by subtracting Median filtered image from Gaussian filtered image. The resultant image is converted to binary image and the regions are analyzed using connected component approach. The prior work on speed bump detection is achieved using sensors which are failed to detect speed bumps that are constructed with small height and the detection rate is affected due to erroneous identification. And the smartphone and accelerometer methodologies are not perfectly suitable for real time scenario due to GPS error, network overload, real-time delay, accuracy and battery running out. The proposed system goes very well for the roads which are constructed with proper painting irrespective of their dimension.