{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,15]],"date-time":"2026-01-15T05:49:32Z","timestamp":1768456172606,"version":"3.49.0"},"reference-count":30,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2019,11,11]],"date-time":"2019-11-11T00:00:00Z","timestamp":1573430400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"ITRA, Media Lab Asia, MHRD, India","award":["ITRA\/i5(6i)\/Mobile\/CARTS\/o2\/2015"],"award-info":[{"award-number":["ITRA\/i5(6i)\/Mobile\/CARTS\/o2\/2015"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Sen. Netw."],"published-print":{"date-parts":[[2020,2,29]]},"abstract":"<jats:p>Traffic congestion on urban roadways is a serious problem requiring novel ways to detect and mitigate it. Determining the routes that lead to the traffic congestion segment is also vital in devising mitigation strategies. Further, crowdsourcing this information allows for use of these strategies quickly and in places where infrastructure is not available. In this work, we present an unconventional method, using the barometer sensor of mobile phones to (a) detect road traffic congestion and (b) estimate the paths that lead to the congested road segment. We make the observation that roads are not completely flat and very often, altitude varies along the road. The barometer sensor chips are sensitive enough to measure these variations and consume very little energy of the mobile phone, compared to other sensors such as the GPS or accelerometer. We devise a feature set to map the rate of change of this altitude as the user moves into activities characterized as \u201cstill\u201d and \u201cmotion,\u201d which are further used by the traffic congestion detection algorithm (RoadSphygmo) to classify the group of users as being in \u201cmoving,\u201d \u201ccongestion,\u201d \u00a0or \u201cstuck\u201d states. To estimate the paths that lead to the congested road segment, we compare the user\u2019s barometer sensor readings with a pre-stored road signature of barometer values using Dynamic Time Warping (DTW). We show that by using correlation of barometer sensor values, we can determine if users are in the same vehicle. We crowdsource this information from multiple mobile phones and use majority voting technique to improve the accuracy of traffic congestion detection and path estimation. We find a significant increase in the accuracies using crowdsourced information as compared to individual mobile phones. Further, we show that we can use barometer sensor for other applications such as bus occupancy, boarding\/deboarding of a vehicle, and so on. The validation of the state determined by RoadSphygmo is done by comparing it with average GPS speed calculated during the same time period. The path estimation is validated over different intersections and considering various cases of commuter travel. The results obtained are promising and show that the traffic state determination and the estimation of the path taken by the commuter can achieve high accuracy.<\/jats:p>","DOI":"10.1145\/3364697","type":"journal-article","created":{"date-parts":[[2019,11,11]],"date-time":"2019-11-11T18:13:30Z","timestamp":1573496010000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":7,"title":["BaroSense"],"prefix":"10.1145","volume":"16","author":[{"given":"Anuj","family":"Dimri","sequence":"first","affiliation":[{"name":"University of Utah, USA"}]},{"given":"Harsimran","family":"Singh","sequence":"additional","affiliation":[{"name":"University of Utah, USA"}]},{"given":"Naveen","family":"Aggarwal","sequence":"additional","affiliation":[{"name":"UIET, Panjab University, Chandigarh, India"}]},{"given":"Bhaskaran","family":"Raman","sequence":"additional","affiliation":[{"name":"IIT Bombay, Maharashtra, India"}]},{"given":"K. K.","family":"Ramakrishnan","sequence":"additional","affiliation":[{"name":"University of California, Riverside, California, USA"}]},{"given":"Divya","family":"Bansal","sequence":"additional","affiliation":[{"name":"PEC University of Technology, Chandigarh, India"}]}],"member":"320","published-online":{"date-parts":[[2019,11,11]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2019. Accelerometer datasheet. Retrieved from: https:\/\/ae-bst.resource.bosch.com\/media\/_tech\/media\/datasheets\/BST-BMA400-DS000.pdf.  2019. Accelerometer datasheet. Retrieved from: https:\/\/ae-bst.resource.bosch.com\/media\/_tech\/media\/datasheets\/BST-BMA400-DS000.pdf."},{"key":"e_1_2_1_2_1","unstructured":"2019. Accelerometer power. Retrieved from: https:\/\/www.electronicspecifier.com\/sensors\/accelerometer-boasts-ultra-low-power-consumption.  2019. Accelerometer power. Retrieved from: https:\/\/www.electronicspecifier.com\/sensors\/accelerometer-boasts-ultra-low-power-consumption."},{"key":"e_1_2_1_3_1","unstructured":"2019. Barometer power. Retrieved from: https:\/\/www.electronicspecifier.com\/sensors\/barometric-pressure-sensor-provides-low-current-consumption.  2019. Barometer power. Retrieved from: https:\/\/www.electronicspecifier.com\/sensors\/barometric-pressure-sensor-provides-low-current-consumption."},{"key":"e_1_2_1_4_1","doi-asserted-by":"publisher","DOI":"10.1108\/SR-05-2013-678"},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1145\/1961189.1961199"},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1177\/0361198105191700119"},{"key":"e_1_2_1_7_1","volume-title":"Proceedings of the 8th International Conference on Communication Systems and Networks (COMSNETS\u201916)","author":"Dimri Anuj","unstructured":"Anuj Dimri , Harsimran Singh , Naveen Aggarwal , Bhaskaran Raman , Diyva Bansal , and K. K. Ramakrishnan . 2016. RoadSphygmo: Using barometer for traffic congestion detection . In Proceedings of the 8th International Conference on Communication Systems and Networks (COMSNETS\u201916) . IEEE, 1--8. Anuj Dimri, Harsimran Singh, Naveen Aggarwal, Bhaskaran Raman, Diyva Bansal, and K. K. Ramakrishnan. 2016. RoadSphygmo: Using barometer for traffic congestion detection. In Proceedings of the 8th International Conference on Communication Systems and Networks (COMSNETS\u201916). IEEE, 1--8."},{"key":"e_1_2_1_8_1","unstructured":"Globalsat. 2014. Globalsat em-506 GPS module. Retrieved from: https:\/\/www.globalsat.com.tw\/ftp\/download\/EM-506RE%20Hardware%20Data%20Sheet%20V1.7.pdf.  Globalsat. 2014. Globalsat em-506 GPS module. Retrieved from: https:\/\/www.globalsat.com.tw\/ftp\/download\/EM-506RE%20Hardware%20Data%20Sheet%20V1.7.pdf."},{"key":"e_1_2_1_9_1","volume-title":"Proceedings of the 4th International Conference on Communication Systems and Networks (COMSNETS\u201912)","author":"Han Jun","year":"2012","unstructured":"Jun Han , Emmanuel Owusu , Le T. Nguyen , Adrian Perrig , and Joy Zhang . 2012 . Accomplice: Location inference using accelerometers on smartphones . In Proceedings of the 4th International Conference on Communication Systems and Networks (COMSNETS\u201912) . IEEE, 1--9. Jun Han, Emmanuel Owusu, Le T. Nguyen, Adrian Perrig, and Joy Zhang. 2012. Accomplice: Location inference using accelerometers on smartphones. In Proceedings of the 4th International Conference on Communication Systems and Networks (COMSNETS\u201912). IEEE, 1--9."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.trc.2009.10.006"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/2821650.2821665"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/2830571.2830576"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/2370216.2370272"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.proche.2009.07.133"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2015.2426955"},{"key":"e_1_2_1_16_1","volume-title":"Professional Android Sensor Programming","author":"Milette Greg","unstructured":"Greg Milette and Adam Stroud . 2012. Professional Android Sensor Programming . John Wiley 8 Sons. Greg Milette and Adam Stroud. 2012. Professional Android Sensor Programming. John Wiley 8 Sons."},{"key":"e_1_2_1_17_1","doi-asserted-by":"publisher","DOI":"10.1109\/TCSVT.2008.927109"},{"key":"e_1_2_1_18_1","volume-title":"Archan Misra, Rajesh Krishna Balan, and Sharad Agarwal.","author":"Muralidharan Kartik","year":"2014","unstructured":"Kartik Muralidharan , Azeem Javed Khan , Archan Misra, Rajesh Krishna Balan, and Sharad Agarwal. 2014 . Barometric phone sensors: More hype than hope! In Proceedings of the 15th Workshop on Mobile Computing Systems and Applications. ACM , 12. Kartik Muralidharan, Azeem Javed Khan, Archan Misra, Rajesh Krishna Balan, and Sharad Agarwal. 2014. Barometric phone sensors: More hype than hope! In Proceedings of the 15th Workshop on Mobile Computing Systems and Applications. ACM, 12."},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.1145\/1814433.1814463"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/2668332.2668343"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1145\/2426656.2426670"},{"key":"e_1_2_1_22_1","volume-title":"Digital pressure sensor. Document number: BST-BME280-DS001-10. Revision_1.1 May 7th","author":"Sensortec Bosch","year":"2015","unstructured":"Bosch Sensortec . 2015. Digital pressure sensor. Document number: BST-BME280-DS001-10. Revision_1.1 May 7th ( 2015 ). Retrieved from https:\/\/raw.githubusercontent.com\/SeeedDocument\/Grove-Barometer_Sensor-BME280\/master\/res\/Grove-Barometer_Sensor-BME280-.pdf. Bosch Sensortec. 2015. Digital pressure sensor. Document number: BST-BME280-DS001-10. Revision_1.1 May 7th (2015). Retrieved from https:\/\/raw.githubusercontent.com\/SeeedDocument\/Grove-Barometer_Sensor-BME280\/master\/res\/Grove-Barometer_Sensor-BME280-.pdf."},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2006.883935"},{"key":"e_1_2_1_24_1","doi-asserted-by":"publisher","DOI":"10.4236\/jtts.2012.21003"},{"key":"e_1_2_1_25_1","doi-asserted-by":"publisher","DOI":"10.1109\/ITSC.2006.1707366"},{"key":"e_1_2_1_26_1","doi-asserted-by":"publisher","DOI":"10.1109\/TITS.2012.2190509"},{"key":"e_1_2_1_27_1","volume-title":"The Free Encyclopedia. Retrieved from: https:\/\/en.wikipedia.org\/w\/index.php?title&equals;Dynamic_time_warping8oldid&equals;729379715.","unstructured":"Wikipedia. 2016. Dynamic time warping\u2014Wikipedia , The Free Encyclopedia. Retrieved from: https:\/\/en.wikipedia.org\/w\/index.php?title&equals;Dynamic_time_warping8oldid&equals;729379715. Wikipedia. 2016. Dynamic time warping\u2014Wikipedia, The Free Encyclopedia. Retrieved from: https:\/\/en.wikipedia.org\/w\/index.php?title&equals;Dynamic_time_warping8oldid&equals;729379715."},{"key":"e_1_2_1_28_1","volume-title":"Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems (ITSC\u201916)","author":"Won Myounggyu","unstructured":"Myounggyu Won , Shaohu Zhang , Appala Chekuri , and Sang H. Son . 2016. Enabling energy-efficient driving route detection using built-in smartphone barometer sensor . In Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems (ITSC\u201916) . IEEE, 2378--2385. Myounggyu Won, Shaohu Zhang, Appala Chekuri, and Sang H. Son. 2016. Enabling energy-efficient driving route detection using built-in smartphone barometer sensor. In Proceedings of the 19th IEEE International Conference on Intelligent Transportation Systems (ITSC\u201916). IEEE, 2378--2385."},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/1247660.1247686"},{"key":"e_1_2_1_30_1","doi-asserted-by":"publisher","DOI":"10.1109\/PLANS.2012.6236933"}],"container-title":["ACM Transactions on Sensor Networks"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3364697","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3364697","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,17]],"date-time":"2025-06-17T23:54:22Z","timestamp":1750204462000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3364697"}},"subtitle":["Using Barometer for Road Traffic Congestion Detection and Path Estimation with Crowdsourcing"],"short-title":[],"issued":{"date-parts":[[2019,11,11]]},"references-count":30,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2020,2,29]]}},"alternative-id":["10.1145\/3364697"],"URL":"https:\/\/doi.org\/10.1145\/3364697","relation":{},"ISSN":["1550-4859","1550-4867"],"issn-type":[{"value":"1550-4859","type":"print"},{"value":"1550-4867","type":"electronic"}],"subject":[],"published":{"date-parts":[[2019,11,11]]},"assertion":[{"value":"2017-11-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-09-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2019-11-11","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}