Low cost crowd counting using audio tones
With mobile devices becoming ubiquitous, collaborative applications have become increasingly pervasive. In these applications, there is a strong need to obtain a count of the number of mobile devices present in an area, as it closely approximates the size of the crowd. Ideally, a crowd counting solu...
| Main Authors: | , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | en_US |
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Association for Computing Machinery (ACM)
2014
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| Online Access: | http://hdl.handle.net/1721.1/90539 https://orcid.org/0000-0001-9010-6519 |
| _version_ | 1826206682200408064 |
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| author | Kannan, Pravein Govindan Venkatagiri, Seshadri Padmanabha Chan, Mun Choon Ananda, Akhihebbal L. Peh, Li-Shiuan |
| author2 | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory |
| author_facet | Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Kannan, Pravein Govindan Venkatagiri, Seshadri Padmanabha Chan, Mun Choon Ananda, Akhihebbal L. Peh, Li-Shiuan |
| author_sort | Kannan, Pravein Govindan |
| collection | MIT |
| description | With mobile devices becoming ubiquitous, collaborative applications have become increasingly pervasive. In these applications, there is a strong need to obtain a count of the number of mobile devices present in an area, as it closely approximates the size of the crowd. Ideally, a crowd counting solution should be easy to deploy, scalable, energy efficient, be minimally intrusive to the user and reasonably accurate. Existing solutions using data communication or RFID do not meet these criteria. In this paper, we propose a crowd counting solution based on audio tones, leveraging the microphones and speaker phones that are commonly available on most phones, tackling all the above criteria. We have implemented our solution on 25 Android phones and run several experiments at a bus stop, aboard a bus, within a cafeteria and a classroom. Experimental evaluations show that we are able to achieve up to 90% accuracy and consume 81% less energy than the WiFi interface in idle mode. |
| first_indexed | 2024-09-23T13:36:55Z |
| format | Article |
| id | mit-1721.1/90539 |
| institution | Massachusetts Institute of Technology |
| language | en_US |
| last_indexed | 2024-09-23T13:36:55Z |
| publishDate | 2014 |
| publisher | Association for Computing Machinery (ACM) |
| record_format | dspace |
| spelling | mit-1721.1/905392022-10-01T16:02:00Z Low cost crowd counting using audio tones Kannan, Pravein Govindan Venkatagiri, Seshadri Padmanabha Chan, Mun Choon Ananda, Akhihebbal L. Peh, Li-Shiuan Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science Peh, Li-Shiuan With mobile devices becoming ubiquitous, collaborative applications have become increasingly pervasive. In these applications, there is a strong need to obtain a count of the number of mobile devices present in an area, as it closely approximates the size of the crowd. Ideally, a crowd counting solution should be easy to deploy, scalable, energy efficient, be minimally intrusive to the user and reasonably accurate. Existing solutions using data communication or RFID do not meet these criteria. In this paper, we propose a crowd counting solution based on audio tones, leveraging the microphones and speaker phones that are commonly available on most phones, tackling all the above criteria. We have implemented our solution on 25 Android phones and run several experiments at a bus stop, aboard a bus, within a cafeteria and a classroom. Experimental evaluations show that we are able to achieve up to 90% accuracy and consume 81% less energy than the WiFi interface in idle mode. 2014-10-02T16:47:09Z 2014-10-02T16:47:09Z 2012-11 Article http://purl.org/eprint/type/ConferencePaper 9781450311694 http://hdl.handle.net/1721.1/90539 Pravein Govindan Kannan, Seshadri Padmanabha Venkatagiri, Mun Choon Chan, Akhihebbal L. Ananda, and Li-Shiuan Peh. 2012. Low cost crowd counting using audio tones. In Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems (SenSys '12). ACM, New York, NY, USA, 155-168. https://orcid.org/0000-0001-9010-6519 en_US http://dx.doi.org/10.1145/2426656.2426673 Proceedings of the 10th ACM Conference on Embedded Network Sensor Systems (SenSys '12) Creative Commons Attribution-Noncommercial-Share Alike http://creativecommons.org/licenses/by-nc-sa/4.0/ application/pdf Association for Computing Machinery (ACM) MIT web domain |
| spellingShingle | Kannan, Pravein Govindan Venkatagiri, Seshadri Padmanabha Chan, Mun Choon Ananda, Akhihebbal L. Peh, Li-Shiuan Low cost crowd counting using audio tones |
| title | Low cost crowd counting using audio tones |
| title_full | Low cost crowd counting using audio tones |
| title_fullStr | Low cost crowd counting using audio tones |
| title_full_unstemmed | Low cost crowd counting using audio tones |
| title_short | Low cost crowd counting using audio tones |
| title_sort | low cost crowd counting using audio tones |
| url | http://hdl.handle.net/1721.1/90539 https://orcid.org/0000-0001-9010-6519 |
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