{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T02:18:44Z","timestamp":1760235524436,"version":"build-2065373602"},"reference-count":39,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T00:00:00Z","timestamp":1630368000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001659","name":"Deutsche Forschungsgemeinschaft","doi-asserted-by":"publisher","award":["HO4770\/7-1","SE3163\/1-1"],"award-info":[{"award-number":["HO4770\/7-1","SE3163\/1-1"]}],"id":[{"id":"10.13039\/501100001659","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"<jats:p>Crowdsensing offers a cost-effective way to collect large amounts of environmental sensor data; however, the spatial distribution of crowdsensing sensors can hardly be influenced, as the participants carry the sensors, and, additionally, the quality of the crowdsensed data can vary significantly. Hybrid systems that use mobile users in conjunction with fixed sensors might help to overcome these limitations, as such systems allow assessing the quality of the submitted crowdsensed data and provide sensor values where no crowdsensing data are typically available. In this work, we first used a simulation study to analyze a simple crowdsensing system concerning the detection performance of spatial events to highlight the potential and limitations of a pure crowdsourcing system. The results indicate that even if only a small share of inhabitants participate in crowdsensing, events that have locations correlated with the population density can be easily and quickly detected using such a system. On the contrary, events with uniformly randomly distributed locations are much harder to detect using a simple crowdsensing-based approach. A second evaluation shows that hybrid systems improve the detection probability and time. Finally, we illustrate how to compute the minimum number of fixed sensors for the given detection time thresholds in our exemplary scenario.<\/jats:p>","DOI":"10.3390\/s21175880","type":"journal-article","created":{"date-parts":[[2021,8,31]],"date-time":"2021-08-31T22:58:15Z","timestamp":1630450695000},"page":"5880","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Performance Evaluation of Hybrid Crowdsensing and Fixed Sensor Systems for Event Detection in Urban Environments"],"prefix":"10.3390","volume":"21","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1359-363X","authenticated-orcid":false,"given":"Matthias","family":"Hirth","sequence":"first","affiliation":[{"name":"User-Centric Analysis of Multimedia Data Group, TU Ilmenau, 98693 Ilmenau, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5036-5206","authenticated-orcid":false,"given":"Michael","family":"Seufert","sequence":"additional","affiliation":[{"name":"Chair of Communication Networks, University of W\u00fcrzburg, 97070 W\u00fcrzburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stanislav","family":"Lange","sequence":"additional","affiliation":[{"name":"Department of Information Security and Communication Technology, NTNU, 7491 Trondheim, Norway"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Markus","family":"Meixner","sequence":"additional","affiliation":[{"name":"Chair of Communication Networks, University of W\u00fcrzburg, 97070 W\u00fcrzburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Phuoc","family":"Tran-Gia","sequence":"additional","affiliation":[{"name":"Chair of Communication Networks, University of W\u00fcrzburg, 97070 W\u00fcrzburg, Germany"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2021,8,31]]},"reference":[{"key":"ref_1","first-page":"128","article-title":"Recent Development and Applications of SUMO-Simulation of Urban MObility","volume":"5","author":"Krajzewicz","year":"2012","journal-title":"Int. J. Adv. Syst. Meas."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Hirth, M., Lange, S., Seufert, M., and Tran-Gia, P. (2018, January 19\u201323). Performance Evaluation of Mobile Crowdsensing for Event Detection. Proceedings of the 5th International Workshop on Crowd Assisted Sensing, Pervasive Systems and Communications, Athens, Greece.","DOI":"10.1109\/PERCOMW.2018.8480332"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"2419","DOI":"10.1109\/COMST.2019.2914030","article-title":"A Survey on Mobile Crowdsensing Systems: Challenges, Solutions and Opportunities","volume":"21","author":"Capponi","year":"2019","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"363","DOI":"10.14569\/IJACSA.2017.080351","article-title":"Crowdsensing: Socio-technical Challenges and Opportunities","volume":"8","author":"Noureen","year":"2017","journal-title":"IJACSA"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"161","DOI":"10.1109\/MCOM.2016.7509395","article-title":"Sparse Mobile Crowdsensing: Challenges and Opportunities","volume":"54","author":"Wang","year":"2016","journal-title":"IEEE Commun. Mag."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/2770876","article-title":"Smartroad: Smartphone-based Crowd Sensing for Traffic Regulator detection and identification","volume":"11","author":"Hu","year":"2015","journal-title":"ACM Trans. Sens. Netw. (TOSN)"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Lane, N.D., Chon, Y., Zhou, L., Zhang, Y., Li, F., Kim, D., Ding, G., Zhao, F., and Cha, H. (2013, January 11\u201315). Piggyback CrowdSensing (PCS): Energy Efficient Crowdsourcing of Mobile Sensor Data by Exploiting Smartphone App Opportunities. Proceedings of the ACM Conference on Embedded Networked Sensor Systems, Roma, Italy.","DOI":"10.1145\/2517351.2517372"},{"key":"ref_8","doi-asserted-by":"crossref","unstructured":"Farshad, A., Marina, M.K., and Garcia, F. (2014, January 5\u20139). Urban WiFi Characterization via Mobile Crowdsensing. Proceedings of the IEEE Network Operations and Management Symposium (NOMS), Krakow, Poland.","DOI":"10.1109\/NOMS.2014.6838233"},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1109\/MCOM.2011.6069707","article-title":"Mobile Crowdsensing: Current State and Future Challenges","volume":"49","author":"Ganti","year":"2011","journal-title":"IEEE Commun. Mag."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Guo, B., Yu, Z., Zhou, X., and Zhang, D. (2014, January 24\u201328). From Participatory Sensing to Mobile Crowd Sensing. Proceedings of the IEEE International Conference on Pervasive Computing and Communications Workshops (PERCOM), Budapest, Hungary.","DOI":"10.1109\/PerComW.2014.6815273"},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"De Caro, N., Colitti, W., Steenhaut, K., Mangino, G., and Reali, G. (2013, January 21). Comparison of Two Lightweight Protocols for Smartphone-based Sensing. Proceedings of the IEEE Symposium on Communications and Vehicular Technology in the Benelux (SCVT), Namur, Belgium.","DOI":"10.1109\/SCVT.2013.6735994"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"1449","DOI":"10.1109\/TMC.2019.2960328","article-title":"Joint Scheduling and Incentive Mechanism for Spatio-Temporal Vehicular Crowd Sensing","volume":"20","author":"Fan","year":"2019","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2208","DOI":"10.1109\/TNET.2019.2938453","article-title":"Data-Driven Pricing for Sensing Effort Elicitation in Mobile Crowd Sensing Systems","volume":"27","author":"Jin","year":"2019","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/COMST.2015.2415528","article-title":"Incentives for Mobile Crowd Sensing: A Survey","volume":"18","author":"Zhang","year":"2016","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Koutsopoulos, I. (2013, January 14\u201319). Optimal Incentive-driven Design of Participatory Sensing Systems. Proceedings of the IEEE Conference on Computer Communications (INFOCOM), Turin, Italy.","DOI":"10.1109\/INFCOM.2013.6566934"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"114","DOI":"10.1109\/MNET.2017.1500151","article-title":"QUOIN: Incentive Mechanisms for Crowd Sensing Networks","volume":"32","author":"Ota","year":"2018","journal-title":"IEEE Netw."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"2536","DOI":"10.1109\/TITS.2017.2750169","article-title":"Crowdsensing-Based Consensus Incident Report for Road Traffic Acquisition","volume":"19","author":"Wang","year":"2017","journal-title":"IEEE Trans. Intell. Transp. Syst."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1001","DOI":"10.1109\/TMC.2019.2955688","article-title":"Expertise-aware Truth Analysis and Task Allocation in Mobile Crowdsourcing","volume":"20","author":"Zhang","year":"2019","journal-title":"IEEE Trans. Mob. Comput."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"17545","DOI":"10.1109\/ACCESS.2018.2805837","article-title":"A Blockchain Based Privacy-Preserving Incentive Mechanism in Crowdsensing Applications","volume":"6","author":"Wang","year":"2018","journal-title":"IEEE Access"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"2294","DOI":"10.1109\/TNET.2019.2944984","article-title":"Enabling Data Trustworthiness and User Privacy in Mobile Crowdsensing","volume":"27","author":"Wu","year":"2019","journal-title":"IEEE\/ACM Trans. Netw."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Dasari, V.S., Kantarci, B., Pouryazdan, M., Foschini, L., and Girolami, M. (2020). Game Theory in Mobile CrowdSensing: A Comprehensive Survey. Sensors, 20.","DOI":"10.3390\/s20072055"},{"key":"ref_22","first-page":"1","article-title":"A Survey of Mobile Crowdsensing Techniques: A Critical Component for the Internet of Things","volume":"2","author":"Liu","year":"2018","journal-title":"ACM Trans. Cyber-Phys. Syst."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"2849","DOI":"10.1109\/COMST.2019.2910855","article-title":"Data-oriented Mobile Crowdsensing: A Comprehensive Survey","volume":"21","author":"Liu","year":"2019","journal-title":"IEEE Commun. Surv. Tutor."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3139256","article-title":"Quality of Information in Mobile Crowdsensing: Survey and Research Challenges","volume":"13","author":"Restuccia","year":"2017","journal-title":"ACM Trans. Sens. Netw. (TOSN)"},{"key":"ref_25","unstructured":"He, S., Shin, D.H., Zhang, J., and Chen, J. (May, January 27). Toward Optimal Allocation of Location Dependent Tasks in Crowdsensing. Proceedings of the IEEE Conference on Computer Communications (INFOCOM), Toronto, ON, Canada."},{"key":"ref_26","doi-asserted-by":"crossref","unstructured":"Pournajaf, L., Xiong, L., Sunderam, V., and Goryczka, S. (2014, January 14\u201318). Spatial Task Assignment for Crowd Sensing with Cloaked Locations. Proceedings of the IEEE International Conference on Mobile Data Management (MDM), Brisbane, QLD, Australia.","DOI":"10.1109\/MDM.2014.15"},{"key":"ref_27","doi-asserted-by":"crossref","unstructured":"Roitman, H., Mamou, J., Mehta, S., Satt, A., and Subramaniam, L. (2012, January 2). Harnessing the Crowds for Smart City Sensing. Proceedings of the International Workshop on Multimodal Crowd Sensing, Maui, HI, USA.","DOI":"10.1145\/2390034.2390043"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1448","DOI":"10.1109\/TC.2002.1146711","article-title":"Grid Coverage for Surveillance and Target Location in Distributed Sensor Networks","volume":"51","author":"Chakrabarty","year":"2002","journal-title":"IEEE Trans. Comput."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"621","DOI":"10.1016\/j.adhoc.2007.05.003","article-title":"Strategies and Techniques for Node Placement in Wireless Sensor Networks: A Survey","volume":"6","author":"Younis","year":"2008","journal-title":"Ad Hoc Netw."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1978802.1978811","article-title":"Coverage Problems in Sensor Networks: A Survey","volume":"43","author":"Wang","year":"2011","journal-title":"ACM Computing Surveys (CSUR)"},{"key":"ref_31","unstructured":"Karaliopoulos, M., Telelis, O., and Koutsopoulos, I. (May, January 26). User Recruitment for Mobile Crowdsensing over Opportunistic Networks. Proceedings of the IEEE Conference on Computer Communications (INFOCOM), Hong Kong, China."},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Zhang, D., Xiong, H., Wang, L., and Chen, G. (2014, January 13\u201317). CrowdRecruiter: Selecting Participants for Piggyback Crowdsensing under Probabilistic Coverage Constraint. Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing, Seattle, WA, USA.","DOI":"10.1145\/2632048.2632059"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1109\/MCOM.2014.6871666","article-title":"Opportunities in Mobile Crowd Sensing","volume":"52","author":"Ma","year":"2014","journal-title":"IEEE Commun. Mag."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1109\/MNET.2018.1700442","article-title":"Robust Mobile Crowd Sensing: When Deep Learning Meets Edge Computing","volume":"32","author":"Zhou","year":"2018","journal-title":"IEEE Netw."},{"key":"ref_35","unstructured":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt (DLR) (2021, August 10). Simulation of Urban Mobility (SUMO). Available online: http:\/\/www.dlr.de\/ts\/en\/desktopdefault.aspx\/tabid-9883\/16931_read-41000\/."},{"key":"ref_36","unstructured":"City of W\u00fcrzburg (2021, August 10). Population W\u00fcrzburg, Germany as of 31.12.2019. Available online: https:\/\/www.wuerzburg.de\/buerger\/statistikstadtforschung\/bevoelkerung\/31501.Bevoelkerung.html."},{"key":"ref_37","unstructured":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt (DLR) and Others (2021, August 10). SUMO-Routing. Available online: https:\/\/sumo.dlr.de\/docs\/Simulation\/Routing.html#routing_algorithms."},{"key":"ref_38","unstructured":"Deutsches Zentrum f\u00fcr Luft- und Raumfahrt (DLR) and Others (2021, August 10). SUMO\u2014Vehicle Type Parameter Defaults. Available online: http:\/\/sumo.dlr.de\/wiki\/Vehicle_Type_Parameter_Defaults."},{"key":"ref_39","unstructured":"National Association of City Transportation Officials (2021, August 10). Urban Street Design Guide. Available online: https:\/\/nacto.org\/publication\/urban-street-design-guide\/design-controls\/design-hour\/."}],"container-title":["Sensors"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/17\/5880\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T06:54:02Z","timestamp":1760165642000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1424-8220\/21\/17\/5880"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021,8,31]]},"references-count":39,"journal-issue":{"issue":"17","published-online":{"date-parts":[[2021,9]]}},"alternative-id":["s21175880"],"URL":"https:\/\/doi.org\/10.3390\/s21175880","relation":{},"ISSN":["1424-8220"],"issn-type":[{"type":"electronic","value":"1424-8220"}],"subject":[],"published":{"date-parts":[[2021,8,31]]}}}