In this paper we present preliminary results of an audio-based traffic density estimation application, developed within the EU-FP7 project EAR-IT [1]. The algorithm exploits that the energy of environmental noise, generated by vehicles, is related to the prevalent traffic conditions. Noise analysis and derived restrictions were made to improve the solution, which was implemented on an embedded platform. This approach follows the current trends—distributed and local processing—and directly targets the requirements for smart cities and wireless sensor networks. Using traffic monitoring wireless sensors, provided by the testbed SmartSantander [2], development setup was established to support the audio related algorithm deployment, testing, and assessment.
Authors:
Nagy, György; Rodigast, Rene; Hollosi, Danilo
Affiliation:
Fraunhofer Institute for Digital Media Technology IDMT, Ilmenau, Germany
AES Convention:
136 (April 2014)
eBrief:145
Publication Date:
April 25, 2014
Click to purchase paper as a non-member or you can login as an AES member to see more options.
No AES members have commented on this paper yet.
To be notified of new comments on this paper you can subscribe to this RSS feed. Forum users should login to see additional options.
If you are not yet an AES member and have something important to say about this paper then we urge you to join the AES today and make your voice heard. You can join online today by clicking here.