Guo B, Wang Z, Yu Z, Wang Y, Yen NY, Huang R, Zhou X (2015) Mobile crowd sensing and computing: the review of an emerging human-powered sensing paradigm. ACM Comput Surv 48(1):1–33
Article
Google Scholar
Lane ND, Miluzzo E, Lu H, Peebles D, Choudhury T, Campbell AT (2010) A survey of mobile phone sensing. IEEE Commun Mag 48(9):140–150
Article
Google Scholar
Xiao Y, Simoens P, Pillai P, Ha K, Satyanarayanan M (2013) Lowering the barriers to large-scale mobile crowdsensing. Proceedings of the 14th workshop on mobile computing systems and applications, HotMobile’14. ACM, Jekyll Island, pp 9–14
Google Scholar
Feese S, Burscher MJ, Jonas K, Tröster G (2014) Sensing spatial and temporal coordination in teams using the smartphone. Hum Cent Comput Inf Sci 4(1):1–18
Article
Google Scholar
Cardone G, Cirri A, Corradi A, Foschini L (2014) The participact mobile crowd sensing living lab: the testbed for smart cities. IEEE Commun Mag 52(10):78–85
Article
Google Scholar
Mafrur R, Nugraha IGD, Choi D (2015) Modeling and discovering human behavior from smartphone sensing life-log data for identification purpose. Hum Cent Comput Inf Sci 5(1):1–18
Article
Google Scholar
Xu J, Xiang J, Yang D (2015) Incentive mechanisms for time window dependent tasks in mobile crowdsensing. IEEE T Wirel Commun 14(11):6353–6364
Article
Google Scholar
Wu FJ, Luo T (2014) WiFiScout: a crowdsensing WiFi advisory system with gamification-based incentive. 11th international conference on mobile Ad Hoc and sensor systems, MASS’14. IEEE, Pennsylvania, pp 533–534
Chapter
Google Scholar
Peng D, Wu F, Chen G (2015) Pay as how well you do: a quality based incentive mechanism for crowdsensing. In: Proceedings of the 16th international symposium on mobile Ad Hoc networking and computing, MobiHoc’15. ACM, Hangzhou, pp 177–186
Cardone G, Foschini L, Bellavista P, Corradi A, Borcea C, Talasila M, Curtmola R (2013) Fostering participaction in smart cities: a geo-social crowdsensing platform. IEEE Commun Mag 51(6):112–119
Article
Google Scholar
Lee JS, Hoh B (2010) Sell your experiences: a market mechanism based incentive for participatory sensing. In: International conference on pervasive computing and communications, PerCom’10. IEEE, Mannheim, pp 60–68
Lee JS, Hoh B (2010) Dynamic pricing incentive for participatory sensing. Pervasive Mob Comput 6(6):693–708
Article
Google Scholar
Yang D, Xue G, Fang X, Tang J (2012) Crowdsourcing to smartphones: incentive mechanism design for mobile phone sensing. In: Proceedings of the 18th annual international conference on mobile computing and networking, MobiCom’11. ACM, Istanbul, pp 173–184
Koutsopoulos I (2013) Optimal incentive-driven design of participatory sensing systems. In: Proceedings of conference on computer communications, INFOCOM’13. IEEE, Turin, pp 1402–1410
Duan L, Kubo T, Sugiyama K, Huang J, Hasegawa T, Walrand J (2012) Incentive mechanisms for smartphone collaboration in data acquisition and distributed computing. In: Proceedings of conference on computer communications, INFOCOM’12. IEEE, Florida, pp 1701–1709
Krontiris I, Albers A (2012) Monetary incentives in participatory sensing using multi-attributive auctions. Int J Parallel Emergent Distrib Syst 27(4):317–336
Article
Google Scholar
Restuccia F, Das SK, Payton J (2015) Incentive mechanisms for participatory sensing: survey and research challenges. ACM Trans Sens Netw. doi:10.1145/0000000.0000000
Google Scholar
Gao H, Liu CH, Wang W, Zhao J, Song Z, Su X, Crowcroft J, Leung KK (2015) A survey of incentive mechanisms for participatory sensing. IEEE Commun Surv Tutor 17(2):918–943
Article
Google Scholar
Jaimes LG, Vergara-Laurens IJ, Raij A (2015) A survey of incentive techniques for mobile crowd sensing. IEEE Internet Things J 2(5):370–380
Article
Google Scholar
Zhang X, Yang Z, Sun W, Liu Y, Tang S, Xing K, Mao X (2016) Incentives for Mobile Crowd Sensing: a Survey. IEEE Commun Surv Tutor 18(1):54–67
Article
Google Scholar
Agarwal V, Banerjee N, Chakraborty D, Mittal S (2013) USense–a smartphone middleware for community sensing. In: 14th international conference on mobile data management, MDM’13. IEEE, Milan, pp 56–65
Koukoumidis E, Peh LS, Martonosi MR (2011) SignalGuru: leveraging mobile phones for collaborative traffic signal schedule advisory. In: Proceedings of the 9th international conference on mobile systems applications and services, MobiSys’11. ACM, Washington, pp 127–140
Chessa S, Corradi A, Foschini L, Girolami M (2016) Empowering mobile crowdsensing through social and ad hoc networking. IEEE Commun Mag 54(7):108–114
Article
Google Scholar
Khan WZ, Xiang Y, Aalsalem MY, Arshad Q (2013) Mobile phone sensing systems: a survey. IEEE Commun Surv Tutor 15(1):402–427
Article
Google Scholar
Ganti RK, Ye F, Lei H (2011) Mobile crowdsensing: current state and future challenges. IEEE Commun Mag 49(11):32–39
Article
Google Scholar
Chon Y, Lane ND, Li F, Cha H, Zhao F (2012) Automatically characterizing places with opportunistic crowdsensing using smartphones. In: Proceedings of the 2012 ACM conference on ubiquitous computing, Ubicomp’12. ACM, Pittsburgh, pp 481–490
Campbell AT, Eisenman SB, Lane ND, Miluzzo E, Peterson RA, Lu H, Zheng X, Musolesi M, Fodor K, Ahn GS (2008) The rise of people-centric sensing. IEEE Internet Comput 12(4):12–21
Article
Google Scholar
Wang Y, Jia X, Jin Q, Ma J (2015) QuaCentive: a quality-aware incentive mechanism in mobile crowdsourced sensing (MCS). J Supercomput. doi:10.1007/s11227-015-1395-y
Google Scholar
Yang D, Xue G, Fang X, Tang J (2016) Incentive mechanisms for crowdsensing: crowdsourcing with smartphones. IEEE ACM Trans Netw 24(3):1732–1744
Article
Google Scholar
Haderer N, Rouvoy R, Seinturier L (2013) A preliminary investigation of user incentives to leverage crowdsensing activities. In: International conference on pervasive computing and communications workshops, PERCOM’13. IEEE, San Diego, pp 199–204
Jaimes LG, Vergara-Laurens I, Chakeri A (2014) SPREAD, a crowd sensing incentive mechanism to acquire better representative samples. In: International conference on pervasive computing and communications workshops, PERCOM’14. IEEE, Budapest, pp 92–97
Tsujimori T, Thepvilojanapong N, Ohta Y, Zhao Y, Tobe Y (2014) History-based incentive for crowd sensing. In: Proceedings of the international workshop on web intelligence and smart sensing, IWWISS’14. ACM, Saint Etienne, pp 1–6
Thepvilojanapong N, Zhang K, Tsujimori T, Ohta Y, Zhao Y, Tobe Y (2013) Participation-aware incentive for active crowd sensing. In: 10th international conference on high performance computing and communications & embedded and ubiquitous computing, HPCC_EUC’13. IEEE, New York, pp 2127–2134
Biswas A, Chander D, Dasgupta K, Mukherjee K, Singh M, Mukherjee T (2015) PISCES: participatory incentive strategies for effective community engagement in smart cities. In: Proceedings of the 3rd AAAI conference on human computation and crowdsourcing, HCOMP-15. AAAI Publishing, pp 23–31
Christin D, Büttner C, Repp N (2012) CachedSensing: exploring and documenting the environment as a treasure hunt. In: 37th conference on local computer networks workshops, LCN’ 12. IEEE, Florida, pp 973–981
Gong X, Chen X, Zhang J, Poor HV (2015) Exploiting social trust assisted reciprocity (STAR) toward utility-optimal socially-aware crowdsensing. IEEE Trans Signal Inform Process Netw 1(3):195–208
Article
Google Scholar
Gong X, Chen X, Zhang J, Poor HV (2014) From social trust assisted reciprocity (STAR) to utility-optimal mobile crowdsensing. In: Signal and information processing global conference, GlobalSIP’14. IEEE, Atlanta, pp 742–745
Jaimes LG, Vergara-Laurens I, Raij A (2014) A crowd sensing incentive algorithm for data collection for consecutive time slot problems. In: 6th Latin–America conference on communications, LATINCOM’14. IEEE, Cartagena, pp 1–5
Foremski P, Gorawski M, Grochla K, Polys K (2015) Energy-efficient crowdsensing of human mobility and signal levels in cellular networks. Sensors 15(9):22060–22088
Article
Google Scholar
Chen X, Liu N (2016) Smart parking by mobile crowdsensing. Int J Smart Home 10(2):219–234
Article
Google Scholar
Pryss R, Reichert M, Langguth B, Schlee W (2015) Mobile crowd sensing services for tinnitus assessment, therapy, and research. In: The 4th international conference on mobile services, MS ’15. IEEE, New York, pp 352–359
Sherchan W, Jayaraman PP, Krishnaswamy S, Zaslavsky A, Loke S, Sinha, A (2012) Using on-the-move mining for mobile crowdsensing. In: 13th international conference on mobile data management, MDM’12. IEEE, Bengaluru, pp 115–124
Sun J (2013) An incentive scheme based on heterogeneous belief values for crowd sensing in mobile social networks. In: Global communications conference, GLOBECOM’13. IEEE, Atlanta pp 1717–1722
Sun J, Ma H (2014) Heterogeneous-belief based incentive schemes for crowd sensing in mobile social networks. J Netw Comput Appl 42:189–196
Article
Google Scholar
Greene CS, Millward AA, Ceh B (2011) Who is likely to plant a tree? The use of public socio-demographic data to characterize client participants in a private urban forestation program. Urban For Urban Green 10(1):29–38
Article
Google Scholar
Mukherjee T, Chander D, Eswaran S, Singh M, Varma P, Chugh A, Dasgupta K (2015) Janayuja: a people-centric platform to generate reliable and actionable insights for civic agencies. In: Proceedings of the 2015 annual symposium on computing for development, DEV ‘15. ACM, London, pp 137–145
Talasila M, Curtmola R, Borcea C (2016) Crowdsensing in the Wild with Aliens and Micropayments. IEEE Pervas Comput 15(1):68–77
Article
Google Scholar
Gant LM, Shimshock K, Allen-Meares P, Smith L, Miller P, Hollingsworth LA, Shanks T (2009) Effects of Photovoice: civic engagement among older youth in urban communities. J Commun Pract 17(4):358–376
Article
Google Scholar
Jin H, Su L, Xiao H, Nahrstedt K (2016) Inception: incentivizing privacy-preserving data aggregation for mobile crowd sensing systems. In: Proceedings of the 17th international symposium on mobile Ad Hoc networking and computing, MobiHoc’16. ACM, Paderborn, pp 341–350
Michael K, Michael MG (2013) No limits to watching? Commun ACM 56(11):26–28
Article
Google Scholar
Sprake J, Rogers P (2014) Crowds, citizens and sensors: process and practice for mobilising learning. Pers Ubiquitous Comput 18(3):753–764
Article
Google Scholar
Ogie R (2016) Bring your own device: an overview of risk assessment. IEEE Consum Electron Mag 5(1):14–119
Article
Google Scholar
Christin D, Reinhardt A, Kanhere SS, Hollick M (2011) A survey on privacy in mobile participatory sensing applications. J Syst Software 84(11):928–1946
Article
Google Scholar
Gustarini M, Wac K, Dey AK (2015) Anonymous smartphone data collection: factors influencing the users’ acceptance in mobile crowd sensing. Pers Ubiquitous Comput 20(1):65–82
Article
Google Scholar
Otto C, Klare B, Jain AK (2015) An efficient approach for clustering face images. In: International conference on biometrics 2015, ICB’15. IEEE, Phuket, pp 243–250
Krontiris I, Maisonneuve N (2011) Participatory sensing: the tension between social translucence and privacy. In: Salgarelli L, Bianchi G, Blefari-Melazzi N (eds) Trustworthy internet. Springer, Milan, pp 159–170
Mukherjee T, Chander D, Mondal A, Dasgupta K, Kumar A, Venkat A (2014) CityZen: A cost-effective city management system with incentive-driven resident engagement. In: 15th international conference on mobile data management, MDM’14. IEEE, Brisbane, pp 289–296
Beresford AR, Kübler D, Preibusch S (2012) Unwillingness to pay for privacy: a field experiment. Econ Lett 117(1):25–27
Article
Google Scholar
Zhang Y, Fang Y, Zhong S (2015) Incentive mechanism design for smartphone crowdsensing. In: 5th international conference on big data and cloud computing, BDCloud’15. IEEE, Dalian, pp 287–292
Xiong H, Zhang D, Chen G, Wang L, Gauthier V (2015) Crowdtasker: Maximizing coverage quality in piggyback crowdsensing under budget constraint. In: Pervasive computing and communications, PerCom’15. IEEE, Missouri, pp 55–62
Zhang D, Xiong H, Wang L, Chen G (2014) CrowdRecruiter: selecting participants for piggyback crowdsensing under probabilistic coverage constraint. In: Proceedings of the international joint conference on pervasive and ubiquitous computing, Ubicomp’14, ACM, Seattle, pp 703–714
Lane ND, Chon Y, Zhou L, Zhang Y, Li F, Kim D, Ding G, Zhao F, Cha H (2013) Piggyback CrowdSensing (PCS): energy efficient crowdsourcing of mobile sensor data by exploiting smartphone app opportunities. In: Proceedings of the 11th conference on embedded networked sensor systems, SenSys ‘13. ACM, New York, pp 7–20
Jiang C, Gao L, Duan L, Huang J (2015) Economics of peer-to-peer mobile crowdsensing. In: Global communications conference, GLOBECOM’15. IEEE, San Diego, pp 1–6
Gao L, Hou F, Huang J (2015) Providing long-term participation incentive in participatory sensing. In: Proceedings of conference on computer communications, INFOCOM’15. IEEE, Kowloon, pp 2803–2811
Kandhway K, Kotnis B (2016) Game theoretic analysis of tree based referrals for crowd sensing social systems with passive rewards. In: 8th international conference on communication systems and networks, COMSNETS’16. IEEE, Bangalore, pp 1–6
Tang JC, Cebrian M, Giacobe NA, Kim HW, Kim T, Wickert DB (2011) Reflecting on the DARPA red balloon challenge. Commun ACM 54(4):78–85
Article
Google Scholar
Angelopoulos CM, Nikoletseas S, Raptis TP, Rolim JD (2014) Characteristic utilities, join policies and efficient incentives in mobile crowdsensing systems. In: Wireless Days,WD’14. IEEE & IFIP, Rio de Janeiro, pp 1–6
Angelopoulos CM, Evangelatos O, Nikoletseas S, Raptis TP, Rolim JD, Veroutis K (2015) A user-enabled testbed architecture with mobile crowdsensing support for smart, green buildings. In: International conference on communications, ICC’15. IEEE, London, pp 573–578
Angelopoulos CM, Nikoletseas S, Raptis TP, Rolim J (2015) Design and evaluation of characteristic incentive mechanisms in Mobile Crowdsensing Systems. Simul Model Pract Theory 55:95–106
Article
Google Scholar
Jaimes LG, Vergara-Laurens I, Labrador MA (2012) A location-based incentive mechanism for participatory sensing systems with budget constraints. In: International conference on pervasive computing and communications, PerCom ’12. IEEE, Lugano, pp 103–108
Jin H, Su L, Chen D, Nahrstedt K, Xu J (2015) Quality of information aware incentive mechanisms for mobile crowd sensing systems. In: Proceedings of the 16th international symposium on mobile Ad Hoc networking and computing, MobiHoc’15. ACM, Hangzhou, pp 167–176
Wang J, Tang J, Yang D, Wang E, Xue G (2016) Quality-aware and fine-grained incentive mechanisms for mobile crowdsensing. In: 36th international conference on distributed computing systems, ICDCS’16. IEEE, Nara, pp 354–363
Perera C, Zaslavsky A, Christen P, Georgakopoulos D (2014) Sensing as a service model for smart cities supported by internet of things. Trans Emerg Telecommun Technol 25(1):81–93
Article
Google Scholar
Sheng X, Tang J, Xiao X, Xue G (2013) Sensing as a service: challenges, solutions and future directions. IEEE Sens J 13(10):3733–3741
Article
Google Scholar
Zhang X, Yang Z, Zhou Z, Cai H, Chen L, Li X (2014) Free market of crowdsourcing: incentive mechanism design for mobile sensing. IEEE Trans Parall Distrb 25(12):3190–3200
Article
Google Scholar
Wen Y, Shi J, Zhang Q, Tian X, Huang Z, Yu H, Cheng Y, Shen X (2015) Quality-driven auction-based incentive mechanism for mobile crowd sensing. IEEE Trans Veh Technol 64(9):4203–4214
Article
Google Scholar
Luo T, Tan HP, Xia L (2014) Profit-maximizing incentive for participatory sensing. In: The 33rd annual IEEE international conference on computer communications, INFOCOM’14. IEEE, Toronto, pp 127–135
Han K, Zhang C, Luo J, Hu M, Veeravalli B (2016) Truthful scheduling mechanisms for powering mobile crowdsensing. IEEE T Comput 65(1):294–307
Article
MathSciNet
Google Scholar
Sirsikar S, Powar V (2015) Mobile crowd sensing using voronoi based approach. Int J Comput Sci Appl 8(1):17–19
Google Scholar
Wang J, Wang Y, He Y (2015) Lowering the technical threshold for organizers to create and deliver mobile crowd sensing applications. Int J Distrib Sens Netw 2015(10):1–15
Google Scholar
Holderness T, Turpin E (2015) From social media to GeoSocial intelligence: crowdsourcing civic co-management for flood response in Jakarta Indonesia. In: Nepal S et al (eds) Social media for government services, vol 2E. Springer International Publishing, Switzerland, pp 115–133
Chapter
Google Scholar
Liu Y, Li F, Wang Y (2016) Incentives for delay-constrained data query and feedback in mobile opportunistic crowdsensing. Sensors 16(7):1138. doi:10.3390/s16071138
Article
MathSciNet
Google Scholar
Zhang D, Wang L, Xiong H, Guo B (2014) 4W1H in mobile crowd sensing. IEEE Commun Mag 52(8):42–48
Article
Google Scholar
Sun J (2016) Marginal quality-based long-term incentive mechanisms for crowd sensing. Int J Commun Syst 29(5):942–958
Article
Google Scholar
Sun X, Li J, Zheng W, Liu H (2016) Towards a Sustainable incentive mechanism for participatory sensing. In: 1st international conference on internet-of-things design and implementation, IoTDI’16. IEEE, Berlin, pp 49–60
Salim F, Haque U (2015) Urban computing in the wild: a survey on large scale participation and citizen engagement with ubiquitous computing, cyber physical Systems, and internet of Things. Int J Hum Comput Stud 81:31–48
Article
Google Scholar
Nan W, Guo B, Huangfu S, Yu Z, Chen H, Zhou X (2014) A cross-space, multi-interaction-based dynamic incentive mechanism for mobile crowd sensing. In: Ubiquitous intelligence and computing, 2014 IEEE 11th Intl Conf on and IEEE 11th Intl Conf on and Autonomic and Trusted Computing, and IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops UTC-ATC-ScalCom’14, pp 179–186
Guo B, Nan W, Yu Z, Xie X, Chen H, Zhou X (2015) TaskMe: a cross-community, quality-enhanced incentive mechanism for mobile crowd sensing. In: Adjunct proceedings of the international joint conference on pervasive and Ubiquitous computing and proceedings of the international symposium on wearable computers. ACM, Osaka, pp 49–52
Guo B, Chen H, Yu Z, Nan W, Xie X, Zhang D, Zhou X (2016) TaskMe: toward a dynamic and quality-enhanced incentive mechanism for mobile crowd sensing. Int J Hum Comput Stud. doi:10.1016/j.ijhcs.2016.09.002
Google Scholar
Reddy S, Estrin D, Hansen M, Srivastava M (2010) Examining micro-payments for participatory sensing data collections. In Proceedings of the 12th international conference on Ubiquitous computing, Ubicomp’10. ACM, Copenhagen, pp 33–36
Zhang M, Yang P, Tian C, Tang S, Wang B (2016) Toward optimum crowdsensing coverage with guaranteed performance. IEEE Sens J 16(5):1471–1480
Article
Google Scholar
Wang L, Zhang D, Wang Y, Chen C, Han X, M’hamed A (2016) Sparse mobile crowdsensing: challenges and opportunities. IEEE Commun Mag 54(7):161–167
Article
Google Scholar
Kawajiri R, Shimosaka M, Kahima H (2014) Steered crowdsensing: incentive design towards quality-oriented place-centric crowdsensing. In: Proceedings of the international joint conference on pervasive and ubiquitous computing, UbiComp’14. ACM, Seattle, pp 691–701
Sarma S, Kandhway K, Kotnis B, Kuri (2016) Urban monitoring using participatory sensing: an optimal budget allocation approach. In: 8th international conference on communication systems and networks, COMSNETS’16. IEEE, Bangalore, pp 1–6
Sun J, Ma H (2014) A behavior-based incentive mechanism for crowd sensing with budget constraints. In: International conference on communications, ICC’14. IEEE, Sydney, pp 1314–1319
Sun J, Ma H (2014) Collection-behavior based multi-parameter posted pricing mechanism for crowd sensing. In: International conference on communications, ICC’14. IEEE, Sydney, pp 227–232
Micholia P, Karaliopoulos M, Koutsopoulos I (2016) Mobile crowdsensing incentives under participation uncertainty. In: Proceedings of the 3rd workshop on mobile sensing, computing and communication, MobiHoc’16. ACM, Paderborn, pp 29–34
Tuite K, Snavely N, Hsiao DY, Tabing N, Popovic Z (2011) PhotoCity: training experts at large-scale image acquisition through a competitive game. In: Proceedings of the conference on human factors in computing systems, SIGCHI’11. ACM, Vancouver, pp 1383–1392
Hoh B, Yan T, Ganesan D, Tracton K, Iwuchukwu T, Lee JS (2012) Trucentive: a game-theoretic incentive platform for trustworthy mobile crowdsourcing parking services. In: 15th international conference on intelligent transportation systems, iTSC’12. IEEE, Anchorage, pp 160–166
Talasila M, Curtmola R, Borcea C (2014) Alien vs. Mobile user game: Fast and efficient area coverage in crowdsensing. In: 6th international conference on mobile computing, applications and services, MobiCASE’14. IEEE, Austin, pp 65–74
Rula JP, Bustamante FE (2015) Crowdsensing Under (Soft) Control. In: Conference on computer communications, INFOCOM’15. IEEE, Kowloon, pp 2236–2244
Albers A, Krontiris I, Sonehara N, Echizen I (2013) Coupons as monetary incentives in participatory sensing. In: 12th IFIP conference on e-business, e-services and e-society. Springer, Berlin, pp 226–237
Mendez D, Labrador MA (2012) Density maps: determining where to sample in participatory sensing systems. In 3rd FTRA international conference on mobile, Ubiquitous, and intelligent computing, MUSIC ’12. IEEE, Vancouver, pp 35–40
Ra MR, Liu B, La Porta TF, Govindan R (2012) Medusa: a programming framework for crowd-sensing applications. In: Proceedings of the 10th international conference on mobile systems, applications, and services, MobiSys’12. ACM, Low Wood Bay, pp 337–350
Tomasic A, Zimmerman J, Steinfeld A, Huang Y (2014) Motivating contribution in a participatory sensing system via quid-pro-quo. In: Proceedings of the 17th conference on computer supported cooperative work & social computing, CSCW’14. ACM, Baltimore, pp 979–988
Lan KC, Chou CM, Wang HY (2012) An incentive-based framework for vehicle-based mobile sensing. Procedia Comput Sci 10:1152–1157
Article
Google Scholar
Tham CK, Luo T (2014) Fairness and social welfare in service allocation schemes for participatory sensing. Comput Netw 73:58–71
Article
Google Scholar
Zaman S, Abrar N, Iqbal A (2015) Incentive model design for participatory sensing: technologies and challenges. In: International conference on networking systems and security, NSysS’15. Sohel, pp 1–6
Han K, Graham EA, Vassallo D, Estrin D (2011) Enhancing motivation in a mobile participatory sensing project through gaming. In Privacy, security, risk and trust (PASSAT) and 3rd international conference on social computing, SocialCom’11. IEEE, Massachusetts, pp 1443–1448
Waze (2016) http://www.waze.com. Accessed 6 Mar 2016
Schweizer I, Meurisch C, Gedeon J, Bärtl R, Mühlhäuser M (2012) Noisemap: multi-tier incentive mechanisms for participative urban sensing. In: Proceedings of the 3rd international workshop on sensing applications on mobile phones, SenSys’12. ACM, Toronto, pp 9–13
Maisonneuve N, Stevens M, Ochab B (2010) Participatory noise pollution monitoring using mobile phones. Inform Polity 15(2):51–71
Google Scholar
Kanjo E (2010) Noisespy: a real-time mobile phone platform for urban noise monitoring and mapping. Mobile Netw Appl 15(4):562–574
Article
Google Scholar
Crowdsignal (2016) http://www.crowdsignals.io/. Accessed 8 Mar 2016
PREMISE (2016) https://www.premise.com/faq/. Accessed 9 Mar 2016
Hasenfratz D, Saukh O, Sturzenegger S, Thiele L (2012) Participatory air pollution monitoring using smartphones. In: 2nd international workshop on mobile sensing, IPSN’12. ACM, Beijing, pp 1–5
Von Kaenel M, Sommer P, Wattenhofer R (2011) Ikarus: large-scale participatory sensing at high altitudes. In: Proceedings of the 12th workshop on mobile computing systems and applications, HotMobile ‘11. ACM, Phoenix, pp 63–68
Deng L, Cox LP (2009) Livecompare: grocery bargain hunting through participatory sensing. In: Proceedings of the 10th workshop on mobile computing systems and applications, HotMobile ‘10. ACM, Santa Cruz, p 4
Ogie RI, Dunn S, Holderness T, Turpin E (2017) Assessing the vulnerability of pumping stations to trash blockage in coastal mega-cities of developing nations. Sustain Cities Soc 28:53–66
Article
Google Scholar
Zimmer M, Proferes NJ (2014) A topology of Twitter research: disciplines, methods, and ethics. Aslib J Inform Manag 66(3):250–261
Article
Google Scholar
Ogie R, Holderness T, Dunbar M, Turpin E (2016) Spatio-topological network analysis of hydrological infrastructure as a decision support tool for flood mitigation in coastal mega-cities. Environ Plann B. doi:10.1177/0265813516637608
Google Scholar
Lane ND (2012) Community-aware smartphone sensing systems. IEEE Internet Comput 16(3):60–64
Article
Google Scholar
Guo B, Yu Z, Zhou X, Zhang D (2014) From participatory sensing to mobile crowd sensing. In: International conference on pervasive computing and communications workshops, PERCOM’14. IEEE, Budapest, pp 593–598
Guo B, He H, Yu Z, Zhang D, Zhou X (2012) GroupMe: supporting group formation with mobile sensing and social graph mining. In: 9th international conference on mobile and Ubiquitous systems: computing, networking, and services, MobiQuitous’12. Springer, Berlin, pp 200–211
Dimitriou T, Krontiris I (2015) Privacy-respecting auctions as incentive mechanisms in mobile crowd sensing. In: Akram RN, Jajodia S (eds) Information security theory and practice, WISTP’ 15. Springer International Publishing, Crete, pp 20–35
Chapter
Google Scholar
Gisdakis S, Giannetsos T, Papadimitratos P (2014) Sppear: security & privacy-preserving architecture for participatory-sensing applications. In: Proceedings of the 2014 ACM conference on security and privacy in wireless & mobile networks, WiSec’14. ACM, Oxford, pp 39–50
Li Q, Cao G (2014) Providing efficient privacy-aware incentives for mobile sensing. In: 34th international conference on distributed computing systems, ICDCS’14. IEEE, Madrid, pp 208–217
Krontiris I, Dimitriou T (2015) A platform for privacy protection of data requesters and data providers in mobile sensing. Comput Commun 65:43–54
Article
Google Scholar
Ma H, Zhao D, Yuan P (2014) Opportunities in mobile crowd sensing. IEEE Commun Mag 52(8):29–35
Article
Google Scholar
Jaimes LG, Chakeri A, Lopez J, Raij A (2015) A cooperative incentive mechanism for recurrent crowd sensing. In: SoutheastCon’15. IEEE, Lauderdale, pp 1–5
Ji S, Chen T (2014) Crowdsensing incentive mechanisms for mobile systems with finite precisions. In: International conference on communications, ICC’14. IEEE, Sydney, pp 2544–2549
Ji S, Chen T (2016) Incentive mechanisms for discretized mobile crowdsensings. IEEE Trans Wirel Commun 15(1):146–161
Article
MathSciNet
Google Scholar
Anawar S, Yahya S (2013) Empowering health behaviour intervention through computational approach for intrinsic incentives in participatory sensing application. In: International conference on research and innovation in information systems, ICRIIS’13. IEEE, Kuala Lumpur, pp 281–285
Ueyama Y, Tamai M, Arakawa Y, Yasumoto K (2014) Gamification-based incentive mechanism for participatory sensing. In: Pervasive computing and communications workshops, PERCOM’14. IEEE, Budapest, pp 98–103
D’Hondt E, Stevens M, Jacobs A (2013) Participatory noise mapping works! An evaluation of participatory sensing as an alternative to standard techniques for environmental monitoring. Pervasive Mobile Comput 9(5):681–694
Article
Google Scholar
Perez P, Holderness du Chemin T, Turpin E, Clarke R (2015) Citizen-driven flood mapping in Jakarta: a self-organising socio-technical system. In: International conference on self-adaptive and self-organizing systems workshops, SASO’15. IEEE, Boston, pp 174–178