Abstract
A considerable amount of research has addressed Internet of Things and connected communities. It is possible to exploit the sensing capabilities of connected communities, by leveraging the continuously growing use of cloud computing solutions and mobile devices. The pervasiveness of mobile sensors also enables the Mobile Crowd Sensing (MCS) paradigm, which aims at using mobile-embedded sensors to extend monitoring of multiple (environmental) phenomena in expansive urban areas. In this article, we discuss our approach with a cloud-based platform to pave the way for applying crowd sensing in urban scenarios. We have implemented a complete solution for environmental monitoring of several pollutants, like noise, air, electromagnetic fields, and so on in an urban area based on this paradigm. Through extensive experimentation, specifically on noise pollution, we show how the proposed infrastructure exhibits the ability to collect data from connected communities, and enables a seamless support of services needed for improving citizens’ quality of life and eventually helps city decision makers in urban planning.
- W. Alberts. 2015. Traffic Noise and Motorway Pavements, Geneva, Switzerland.Google Scholar
- F. Alton Everest and K. Pohlmann. 2009. Master Handbook of Acoustics 5th ed., T. Electronics.Google Scholar
- L. Alves, T. Brasileiro, R. Araujo, D. Florencio, L. Firmino, C. Almeida, B. Alencar, M. L. Oiticica, V. Araujo, and B. Araujo. 2016. Comparison of noise pollution complaints concentration mapped in three capitals of Brazilian northeast. In Proceedings of the 22nd International Congress on Acoustics (ICA’16). 1--9.Google Scholar
- Italian Official Gazette. 1995. LQ 26/10/1995/447 - Framework Law on Environmental Noise Pollution, Italy.Google Scholar
- H. Bendtsen. 2010. Noise Barrier Design: Danish and Some European Examples. Danish Road Institute - Road Directorate and University of California Pavement Research Center. Reprint Report: UCPRC-RP-2010-04.Google Scholar
- Mario A. Bochicchio and Antonella Longo. 2009. A multi-purpose architecture for collaborative web labs. In Proceedings of the 9th IEEE International Conference on Advanced Learning Technologies (ICALT’09), 70--74. DOI:https://doi.org/10.1109/ICALT.2009.192 Google Scholar
Digital Library
- Mario A. Bochicchio and Antonella Longo. 2012. Delivering collaborative web labs as a service for engineering education. Int. J. Online Eng. 8, 2 (2012), 4--10. DOI:https://doi.org/10.3991/ijoe.v8i2.1897 Google Scholar
Cross Ref
- X. Chen, N. Ding, A. Jindal, Y. C. Hu, M. Gupta, and R. Vannithamby. 2015. Smartphone Energy Drain in the Wild: Analysis and Implications. In Proceedings of the 2015 ACM SIGMETRICS International Conference on Measurement and Modeling of Computer Systems (SIGMETRICS’15). ACM. 151--164. Google Scholar
Digital Library
- EEA (European Environmental Agency). 2014. Noise in Europe 2014. EEA Report no. 10/2014. Publication Office of the European Union. Luxembourg.Google Scholar
- FIWARE. 2014. FIWARE Architecture. (2014). Retrieved November 1, 2016 from https://forge.fiware.org/plugins/mediawiki/wiki/fiware/index.php/FIWARE_Architecture.Google Scholar
- V. Gandhi, J. K. Vimal, J. Kumar, S. Bhati, and R.D. Swami. 2016. Status of Ambient Noise Level in India. National Ambient Noise Monitoring Network: NANMN/02/2015-16. New Delhi, India.Google Scholar
- R. K. Ganti. 2011. Mobile crowdsensing: Current state and future challenges. IEEE Commun. Mag. 49, 11 (2011), 32--39. Google Scholar
Cross Ref
- D. Gates. 2011. Advanced Decibel Meter. v1.0 [Mobile Application Software]. Retrieved from https://play.google.com/store/apps/details?id=com.tufat.vol_meter1_pro8hl=it.Google Scholar
- M. Golfarelli and S. Rizzi. 2009. Data Warehouse Design: Modern Principles and Methodologies 1st ed., McGraw-Hill.Google Scholar
- Google. 2016. Google Play Store - City Soundscape. (2016). Retrieved November 1, 2016 from https://play.google.com/store/apps/details?id=it.albaproject.citysoundscape.Google Scholar
- Bin Guo, Zhiwen Yu, Xingshe Zhou, and Daqing Zhang. 2014. From participatory sensing to mobile crowd sensing. In Proceedings of the 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS’14). 593--598. DOI:https://doi.org/10.1109/PerComW.2014.6815273 Google Scholar
Cross Ref
- Z. Guo, M. Zhou, and G. Jiang. 2008. Adaptive sensor placement and boundary estimation for monitoring mass objects. IEEE Trans. Syst. Man Cybern. - Part B Cybern. 38, 1 (2008), 222--232. Google Scholar
Digital Library
- M. S. Hammer, T. K. Swinburn, and R. L. Neitzel. 2014. Environmental noise pollution in the United States: Developing an effective public health response. Environ Health Perspect 122 (2014), 115--119.Google Scholar
Cross Ref
- Z. X. Han. 2015. Noise monitoring and adverse health effects in residents in different functional areas of Luzhou, China. Asia-Pacific J. Public Health 27, 2S (2015), 93S--99S. Google Scholar
Cross Ref
- S. Heggen. 2012. Integrating participatory sensing and informal science education. In Proceedings of the 2012 ACM Conference on Ubiquitous Computing (UbiComp’12). 552--555. Google Scholar
Digital Library
- D. Hoaglin, B. Iglewicz, and J. Tukey. 1986. Performance of some resistant rules for outlier labeling. J. Am. Stat. Assoc. 82 (1986), 1147--1149. Google Scholar
Cross Ref
- IEEE Internet of Things (IoT) Scenarios 8 Use Cases. 2015. Social Sensors. Retrieved from https://iot.ieee.org/images/files/pdf/scenarios/IEEE_IoT_Service_UseCases_Social_Sensors_clean.pdf.Google Scholar
- ISO/TS (International Organization for Standardization). 2003. Acoustics - Assessment of Noise Annoyance by means of Social and Socio-Acoustic Surveys. ISO/TS 15666:2003.Google Scholar
- ISPRA (Istituto Superiore per la Protezione e la Ricerca Ambientale). 2014. X Report - Quality of the Urban Environment. Edition 2014. Online Report 53/2014. ISBN: 978-88-448-0685-9. Retrieved from http://www.isprambiente.gov.it/public_files/X_Rapporto_aree_urbane_ed_2014.pdf.Google Scholar
- ISTAT (Istituto Nazionale di Statistica). 2014. Qualità dell’Ambiente Urbano 2013. Online report. Retrieved from https://www.istat.it/it/files/2014/07/Dati-ambientali.pdf?title=Qualit%C3%A0+dell%27ambiente+urbano+−+22%2Flug%2F2014+−+Testo+integrale.pdf.Google Scholar
- ITU (International Telecommunication Union). 2016. ICT Facts and Figures 2016. ICT Data and Statistics Division. Report. Geneva, Switzerland. Retrieved from http://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2016.pdf.Google Scholar
- Jacob R. Job, Kyle Myers, Koorosh Naghshineh, and Sharon A. Gill. 2016. Uncovering spatial variation in acoustic environments using sound mapping. PLoS One 11, 7 (2016), 1--19. DOI:https://doi.org/10.1371/journal.pone.0159883 Google Scholar
Cross Ref
- Rob Jozwiak, Joey Jraige, Basel Tawil, Colin Novak, and Helen Ule. 2015. Case Study of Acoustic Mapping of International Transportation Route and Its Effect on the Local Community. Bruel and Kjaer Knowledge Center. Case Studies. Retrieved from https://www.bksv.com/media/doc/bn0470.pdf.Google Scholar
- Kenneth Kaliski, Eddie Duncan, and James Cowan. 2007. Community and regional noise mapping in the United States. Sound Vib. (2007), 14--17.Google Scholar
- Eiman Kanjo. 2010. NoiseSPY: A real-time mobile phone platform for urban noise monitoring and mapping. Mob. Networks Appl. 15, 4 (2010), 562--574. DOI:https://doi.org/10.1007/s11036-009-0217-y Google Scholar
Digital Library
- Chucri A. Kardous and Peter B. Shaw. 2014. Evaluation of smartphone sound measurement applications. J. Acoust. Soc. Am. 135, 4, EL186-EL192 (2014). Google Scholar
Cross Ref
- Matti Karjalainen and Ville Pulkki. 2015. Communication Acoustics: An Introduction to Speech, Audio and Psychoacoustics. John Wiley 8 Sons Inc. New York, United States. ISBN-13: 9781118866542.Google Scholar
- Z. Khan, A. Anjum, K. Soomro, and M. A. Tahir. 2015. Towards cloud based big data analytics for smart future cities. Journal of Cloud Computing 4, 1. DOI:10.1186/s13677-015-0026-8 Google Scholar
Cross Ref
- Simone Leao, Kok Leong Ong, and Adam Krezel. 2014. 2Loud?: Community mapping of exposure to traffic noise with mobile phones. In Environmental Monitoring and Assessment. 6193--6206. DOI:https://doi.org/10.1007/s10661-014-3848-9 Google Scholar
Cross Ref
- A. Longo, M. Zappatore, and M. A. Bochicchio. 2015. Towards massive open online laboratories: An experience about electromagnetic crowdsensing. In Proceedings of the 12th International Conference on Remote Engineering and Virtual Instrumentation (REV’15). 43--51. Google Scholar
Cross Ref
- Mobile Essentials. 2017. Sound Meter Pro. v2.3. [Mobile Application Software]. Retrieved from https://play.google.com/store/apps/details?id=com.soundmeter.app8hl=it.Google Scholar
- T. -H. Nguyen and I. H. Khoo. 2014. A case study on noise mapping for container terminals at the Port of Los Angeles. Int. J. Appl. or Innov. Eng. Manag. 3, 8 (2014), 76--84.Google Scholar
- M. Hammer and S. Betzler. 2014. National Survey of State and Local Noise Activity. Network for Public Health Law (NPHL). Survey. Retrieved from https://www.networkforphl.org/_asset/3rvh8q/5-23-13Survey_of_noise_activity_4.pdf.Google Scholar
- Serkan Ozer, Hasan Yilmaz, Murat Yeil, and Pervin Yeil. 2009. Evaluation of noise pollution caused by vehicles in the city of Tokat, Turkey. Sci. Res. Essay 4, 11 (2009), 1205--1212.Google Scholar
- L. Peeples. 2009. iSniff: Pocket-size pollution sensors promise big improvement in monitoring personal environment. Sci. Am. (2009).Google Scholar
- Performance Audio LLC. 2016. Decibel Meter Pro. v3.1. [Mobile Software Application] Retrieved from https://itunes.apple.com/it/app/decibel-meter-pro/id382776256?mt=8.Google Scholar
- Public Health Association of Australia (PHAA). 2014. Environmental Noise Policy. Retrieved from https://www.phaa.net.au/documents/item/248.Google Scholar
- S. Rajasegarar, C. Leckie, M. Palaniswami, and J. C. Bezdek. 2007. Quarter sphere based distributed anomaly detection in wireless sensor networks. In Proceedings of the IEEE International Conference on Communications, 2007 (ICC’07). 3864--3869. DOI:https://doi.org/10.1109/ICC.2007.637 Google Scholar
Cross Ref
- Rajib Kumar Rana, Chun Tung Chou, Salil S. Kanhere, Nirupama Bulusu, and Wen Hu. 2010. Ear-phone : An end-to-end participatory urban noise mapping system. In Proceedings of the International Conference on Information Processing in Sensor Networks (IPSN). 105--116. DOI:https://doi.org/10.1145/1791212.1791226 Google Scholar
Digital Library
- X. Sheng, X. Xiao, and J. Tang. 2012. Sensing as a Service: A cloud computing system for mobile phone sensing. In Proceedings of IEEE Sensors. 1--4. DOI: 10.1109/ICSENS.2012.6411516 Google Scholar
Cross Ref
- SoftNoise. 2017. SoftNoise GmbH: Developers of Predictor-LimA. Retrieved from https://www.softnoise.com/index.html.Google Scholar
- SoundPlan. SoundPlan GmbH Software. 2017. Retrieved from http://www.soundplan.eu/english/products-and-services/soundplan-software/.Google Scholar
- TNS Opinion 8 Social. 2013. Attitudes of Europeans Towards Urban Mobility - Special Eurobarometer 406. Retrieved from http://ec.europa.eu/commfrontoffice/publicopinion/archives/ebs/ebs_406_en.pd.Google Scholar
- R. Wu, B. Zhang, W. Hu, L. Liu, and J. Yang. 2015. Application of noise mapping in environmental noise management in hangzhou, china. In Proceedings of EuroNoise 2015 (Maastricht, The Netherlands).Google Scholar
- F. Xia, C. H. Hsu, X. Liu, H. Liu, F. Ding, and W. Zhang. 2015. The power of smartphones. Multimed. Syst. 21, 1 (2015), 87--101. Google Scholar
Digital Library
- Jun Xiao, Xiaodong Li, and Zhihui Zhang. 2016. Daily-based health risk assessment of construction noise in Beijing, China. P. Lercher (ed.). In International Journal of Environmental Research and Public Health 13, 11 (2016), 1--18. DOI:10.3390/ijerph13111045. Google Scholar
Cross Ref
- Y. Xiao, P. Simoens, P. Padmanabhan, K. Ha, and S. Mahadev. 2013. Lowering the barriers to large-scale mobile crowdsensing. In Proceedings of the 14th Workshop on Mobile Computing Systems and Applications (HotMobile’13). 9:1--9:6. DOI:https://doi.org/10.1145/2444776.2444789 Google Scholar
Digital Library
- L. H. Xie, M. Cai, and E. D. Li. 2013. Comprehensive evaluation of traffic noise pollution based on population exposure. Procedia - Soc. Behav. Sci. 96 (2013), 2179--2186. DOI:https://doi.org/http://dx.doi.org/10.1016/j.sbspro.2013.08.246 Google Scholar
Cross Ref
- M. Zhou. 2011. 3D traffic noise mapping in city central area. Adv. Mater. Res. 250 (2011), 2796--2799. Google Scholar
Cross Ref
- M. A. Zytoon. 2016. Opportunities for environmental noise mapping in saudi arabia: A case of traffic noise annoyance in an urban area in Jeddah City. Int. J. Environ. Res. Public Health 13 (2016), 1--19. Google Scholar
Cross Ref
Index Terms
Crowd-Sourced Data Collection for Urban Monitoring via Mobile Sensors
Recommendations
Workshop on Pervasive Urban Applications
On 12 June 2011, the first International Workshop on Pervasive Urban Applications (PURBA) was held in conjunction with the International Conference on Pervasive Computing (Pervasive 2011) in San Francisco. The workshop aimed to bring together ...
Urban ageing: technology, agency and community in smarter cities for older people
C&T '15: Proceedings of the 7th International Conference on Communities and TechnologiesDespite the widespread popularity of smart cities in policy and research fields, and the ever-increasing ageing population in urban areas, ageing issues have seldom been addressed in depth in smart city programs. The main focus has hitherto been on ...
Crowd-sourced urban life monitoring: urban area characterization based crowd behavioral patterns from Twitter
ICUIMC '12: Proceedings of the 6th International Conference on Ubiquitous Information Management and CommunicationLocation-based social network sites are recently attracting a great deal of attention by combing Web-based social network and the real-world location tagging in an integrated way, where people can publish their life logs about their real-world ...






Comments