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General Review of Smartphone Usability in Noise Mapping

Year 2024, , 804 - 814, 15.07.2024
https://doi.org/10.34248/bsengineering.1425362

Abstract

The global urban population is steadily increasing, with more than half of the world's population currently residing in cities, and this trend is expected to double by 2050. As urbanization continues, noise pollution becomes a significant concern, affecting over 60% of major city dwellers and impacting human health on both physiological and psychological levels. To address this issue, governments and organizations are striving to develop effective noise assessment, regulation, and mitigation policies. This literature review explores the role of noise mapping and the potential of smartphones in collecting noise data to inform these policies. Traditional noise mapping techniques and smartphone-based data collection methods are discussed, along with their importance in urban planning, environmental studies, and public health. Key research questions are identified, including the methodologies employed for smartphone-based noise mapping, the accuracy of smartphone-collected data compared to traditional measurements, practical applications, challenges, and emerging trends. The review reveals that smartphones offer a cost-effective and widespread means of gathering noise data, enabling real-time insights and enhancing various domains' practical applications. However, challenges such as data accuracy, privacy concerns, and device limitations must be addressed. The future of smartphone-based noise mapping looks promising, with advancements in sensor technologies, artificial intelligence, and data analysis tools empowering researchers, urban planners, and policymakers to make informed decisions about noise pollution in urban environments.

References

  • Aletta F, Kang J. 2015. Soundscape approach integrating noise mapping techniques: A case study in Brighton, UK. Noise Mapp, 2: 1–12.
  • Alvares-Sanches T, Osborne, P, White P. 2021. Mobile surveys and machine learning can improve urban noise mapping: Beyond A-weighted measurements of exposure. Sci Total Environ, 775: 1-13.
  • Andrachuk M, Marschke, M, Hings C, Armitage D. 2019. Smartphone technologies supporting community-based environmental monitoring and implementation: a systematic scoping review. Biolal Conserv, 237: 430–442.
  • Bangtao Z, Ming C, Luman W. 2019. Urban planning area traffic noise prediction based on noise mapping. In INTER-NOISE and NOISE-CON Congress and Conference Proceedings, Jun 16-19, Madrid, Spain, pp: 2016.
  • Berglund B, Lindvall T, Schwela DH. 2000. New who guidelines for community noise. Noise Vibrat Worldwide, 31(4): 24–29.
  • Bocher E, Petit G, Picaut J, Fortin N, Guillaume G. 2017. Collaborative noise data collected from smartphones. Data in Brief, 14: 498–503.
  • Bostanci B. 2018. Accuracy assessment of noise mapping on the main street. Arabian J Geo Sci, 11: 1-12.
  • Brambilla G, Pedrielli F. 2020. Smartphone-Based participatory soundscape mapping for a more sustainable acoustic environment. Sustain, 12: 1-20.
  • Cai M, Zou J, Xie J, Ma X. 2015. Road traffic noise mapping in Guangzhou using GIS and GPS. Applied Acoustics, 87: 94–102.
  • Can A, Audubert P, Aumond P, Geisler E, Guiu C, Lorino T, Rossa E. 2023. Framework for urban sound assessment at the city scale based on citizen action, with the smartphone application NoiseCapture as a lever for participation. Noise Mapp, 10: 1-24.
  • Celestina M, Hrovat J, Kardous CA. 2018. Smartphone-based sound level measurement apps: Evaluation of compliance with international sound level meter standards. Applied Acoustics, 139:119–128.
  • Cho DS, Kim JH, Manvell D. 2007. Noise mapping using measured noise and GPS data. Applied Acoustics, 68(9): 1054–1061.
  • de Kluijver H, Stoter J. 2003. Noise mapping and GIS: optimising quality and efficiency of noise effect studies. Comput Environ Urban Systems, 27(1): 85–102.
  • Dubey R., Bharadwaj S, Zafar MI, Bhushan Sharma V, Biswas S. 2020. Collaborative Noise Mapping Using Smartphone. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Scis, XXIV ISPRS Congress, August 31 - September 02, Nice, France, pp: 253–260.
  • Guideline for environmental noise measurement and assessment. 2010. URL: https://www.resmigazete.gov.tr/eskiler/2010/06/20100604-5.htm (accessed date: November 21, 2023).
  • Kanjo E. 2010. NoiseSPY: A Real-Time Mobile Phone Platform for Urban Noise Monitoring and Mapping. Mobile Networks and Applications, 15(4): 562–574.
  • Kardous CA, Shaw PB. 2016. Evaluation of smartphone sound measurement applications (apps) using external microphones-A follow-up study. The Journal of the Acoustical Society of America, 140(4): 327–333.
  • Lee HP, Garg S, Lim KM. 2020. Crowdsourcing of environmental noise map using calibrated smartphones. Applied Acoustics, 160: 1-9.
  • Luzzi S, Vassiliev AV. 2005. A comparison of noise mapping methods in Italian and Russian experiences. Forum Acusticum, August 29 - September 2, Budapest, Hungary, pp: 186.
  • Maisonneuve N, Stevens M, Ochab B. 2010. Participatory noise pollution monitoring using mobile phones. Information Polity, 15: 51–71.
  • Murphy E, Faulkner JP, Douglas O. 2020. Current State-of-the-Art and New Directions in Strategic Environmental Noise Mapping. Current Pollut Reports, 6(2): 54–64.
  • Murphy E, King EA. 2014a. Noise Mitigation Approaches. Environmental Noise Pollution. Elsevier, San Diego, USA, 1th ed., pp: 317.
  • Murphy E, King EA. 2014b. Environmental Noise and Health. Environmental Noise Pollution, Elsevier, San Diego, USA, 1th ed., pp: 317.
  • Murphy E, King EA. 2016c. Smartphone-based noise mapping: Integrating sound level meter app data into the strategic noise mapping process. Sci Total Environ, 562: 852–859.
  • Padilla-Ortiz AL, Machuca A, Ibarra-Zarate DI. 2023. Smartphones, a tool for noise monitoring and noise mapping: an overview. Inter J Environ Sci Technol, 20: 3521-3536
  • Picaut J, Fortin N, Bocher E, Petit G, Aumond P, Guillaume G. 2019. An open- Sci crowdsourcing approach for producing community noise maps using smartphones. Building Environ, 148: 20–33.
  • Socoró JC, Ribera G, Sevillano X, Alías F. 2015. Development of an Anomalous Noise Event Detection Algorithm for dynamic road traffic noise mapping. In Proceedings of the 22nd International Congress on Sound and Vibration, July 12-16, Florence, Italy, pp: 8091.
  • Tsai KT, Lin MD, Chen YH. 2009. Noise mapping in urban environments: A Taiwan study. Applied Acoustics, 70(7): 964–972.
  • Uygunol ODSS. 2009. Gsm baz istasyonlarında elektromanyetik kirlilik haritalarının coğrafi bilgi sistemi (cbs) yardımıyla oluşturulması Konya örneği. 12. Türkiye Harita Bilimsel ve Teknik Kurultayı, Mayıs 11-15, Ankara, Türkiye, pp: 542.
  • Ventura R, Mallet V, Issarny V, Raverdy PG, Rebhi F. 2017. Evaluation and calibration of mobile phones for noise monitoring application. J Acoustical Soc America, 142(5): 3084–3093.
  • World Bank. 2023. Urban development. global urban population trend. URL: https://www.worldbank.org/en/topic/urbandevelopment/overview#:~:text=Today%2C%20some%2056%25%20of%20the,people%20will%20live%20in%20cities (accessed date: December 15, 2023).
  • Yomralıoğlu T. 2000. Coğrafi bilgi sistemleri, temel kavramlar ve uygulamalar. Seçil Ofset, İstanbul, Türkiye, 1. Basım, pp: 479.
  • Zamora W, Calafate C, Cano JC, Manzoni P. 2017. Accurate ambient noise assessment using smartphones. Sensors, 17(4): 917.
  • Zhao B, Cai M, Wang L. 2019. Urban planning area traffic noise prediction based on noise mapping. InINTER-NOISE and NOISE-CON Congress and Conference Proceedings, June 16-19, Madrid, Spain, pp: 2008.
  • Zhou Z, Kang J, Zou Z, Wang H. 2017. Analysis of traffic noise distribution and influence factors in Chinese urban residential blocks. Environ Planning B: Urban Analytics City Sci, 44(3): 570–587.

General Review of Smartphone Usability in Noise Mapping

Year 2024, , 804 - 814, 15.07.2024
https://doi.org/10.34248/bsengineering.1425362

Abstract

The global urban population is steadily increasing, with more than half of the world's population currently residing in cities, and this trend is expected to double by 2050. As urbanization continues, noise pollution becomes a significant concern, affecting over 60% of major city dwellers and impacting human health on both physiological and psychological levels. To address this issue, governments and organizations are striving to develop effective noise assessment, regulation, and mitigation policies. This literature review explores the role of noise mapping and the potential of smartphones in collecting noise data to inform these policies. Traditional noise mapping techniques and smartphone-based data collection methods are discussed, along with their importance in urban planning, environmental studies, and public health. Key research questions are identified, including the methodologies employed for smartphone-based noise mapping, the accuracy of smartphone-collected data compared to traditional measurements, practical applications, challenges, and emerging trends. The review reveals that smartphones offer a cost-effective and widespread means of gathering noise data, enabling real-time insights and enhancing various domains' practical applications. However, challenges such as data accuracy, privacy concerns, and device limitations must be addressed. The future of smartphone-based noise mapping looks promising, with advancements in sensor technologies, artificial intelligence, and data analysis tools empowering researchers, urban planners, and policymakers to make informed decisions about noise pollution in urban environments.

References

  • Aletta F, Kang J. 2015. Soundscape approach integrating noise mapping techniques: A case study in Brighton, UK. Noise Mapp, 2: 1–12.
  • Alvares-Sanches T, Osborne, P, White P. 2021. Mobile surveys and machine learning can improve urban noise mapping: Beyond A-weighted measurements of exposure. Sci Total Environ, 775: 1-13.
  • Andrachuk M, Marschke, M, Hings C, Armitage D. 2019. Smartphone technologies supporting community-based environmental monitoring and implementation: a systematic scoping review. Biolal Conserv, 237: 430–442.
  • Bangtao Z, Ming C, Luman W. 2019. Urban planning area traffic noise prediction based on noise mapping. In INTER-NOISE and NOISE-CON Congress and Conference Proceedings, Jun 16-19, Madrid, Spain, pp: 2016.
  • Berglund B, Lindvall T, Schwela DH. 2000. New who guidelines for community noise. Noise Vibrat Worldwide, 31(4): 24–29.
  • Bocher E, Petit G, Picaut J, Fortin N, Guillaume G. 2017. Collaborative noise data collected from smartphones. Data in Brief, 14: 498–503.
  • Bostanci B. 2018. Accuracy assessment of noise mapping on the main street. Arabian J Geo Sci, 11: 1-12.
  • Brambilla G, Pedrielli F. 2020. Smartphone-Based participatory soundscape mapping for a more sustainable acoustic environment. Sustain, 12: 1-20.
  • Cai M, Zou J, Xie J, Ma X. 2015. Road traffic noise mapping in Guangzhou using GIS and GPS. Applied Acoustics, 87: 94–102.
  • Can A, Audubert P, Aumond P, Geisler E, Guiu C, Lorino T, Rossa E. 2023. Framework for urban sound assessment at the city scale based on citizen action, with the smartphone application NoiseCapture as a lever for participation. Noise Mapp, 10: 1-24.
  • Celestina M, Hrovat J, Kardous CA. 2018. Smartphone-based sound level measurement apps: Evaluation of compliance with international sound level meter standards. Applied Acoustics, 139:119–128.
  • Cho DS, Kim JH, Manvell D. 2007. Noise mapping using measured noise and GPS data. Applied Acoustics, 68(9): 1054–1061.
  • de Kluijver H, Stoter J. 2003. Noise mapping and GIS: optimising quality and efficiency of noise effect studies. Comput Environ Urban Systems, 27(1): 85–102.
  • Dubey R., Bharadwaj S, Zafar MI, Bhushan Sharma V, Biswas S. 2020. Collaborative Noise Mapping Using Smartphone. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Scis, XXIV ISPRS Congress, August 31 - September 02, Nice, France, pp: 253–260.
  • Guideline for environmental noise measurement and assessment. 2010. URL: https://www.resmigazete.gov.tr/eskiler/2010/06/20100604-5.htm (accessed date: November 21, 2023).
  • Kanjo E. 2010. NoiseSPY: A Real-Time Mobile Phone Platform for Urban Noise Monitoring and Mapping. Mobile Networks and Applications, 15(4): 562–574.
  • Kardous CA, Shaw PB. 2016. Evaluation of smartphone sound measurement applications (apps) using external microphones-A follow-up study. The Journal of the Acoustical Society of America, 140(4): 327–333.
  • Lee HP, Garg S, Lim KM. 2020. Crowdsourcing of environmental noise map using calibrated smartphones. Applied Acoustics, 160: 1-9.
  • Luzzi S, Vassiliev AV. 2005. A comparison of noise mapping methods in Italian and Russian experiences. Forum Acusticum, August 29 - September 2, Budapest, Hungary, pp: 186.
  • Maisonneuve N, Stevens M, Ochab B. 2010. Participatory noise pollution monitoring using mobile phones. Information Polity, 15: 51–71.
  • Murphy E, Faulkner JP, Douglas O. 2020. Current State-of-the-Art and New Directions in Strategic Environmental Noise Mapping. Current Pollut Reports, 6(2): 54–64.
  • Murphy E, King EA. 2014a. Noise Mitigation Approaches. Environmental Noise Pollution. Elsevier, San Diego, USA, 1th ed., pp: 317.
  • Murphy E, King EA. 2014b. Environmental Noise and Health. Environmental Noise Pollution, Elsevier, San Diego, USA, 1th ed., pp: 317.
  • Murphy E, King EA. 2016c. Smartphone-based noise mapping: Integrating sound level meter app data into the strategic noise mapping process. Sci Total Environ, 562: 852–859.
  • Padilla-Ortiz AL, Machuca A, Ibarra-Zarate DI. 2023. Smartphones, a tool for noise monitoring and noise mapping: an overview. Inter J Environ Sci Technol, 20: 3521-3536
  • Picaut J, Fortin N, Bocher E, Petit G, Aumond P, Guillaume G. 2019. An open- Sci crowdsourcing approach for producing community noise maps using smartphones. Building Environ, 148: 20–33.
  • Socoró JC, Ribera G, Sevillano X, Alías F. 2015. Development of an Anomalous Noise Event Detection Algorithm for dynamic road traffic noise mapping. In Proceedings of the 22nd International Congress on Sound and Vibration, July 12-16, Florence, Italy, pp: 8091.
  • Tsai KT, Lin MD, Chen YH. 2009. Noise mapping in urban environments: A Taiwan study. Applied Acoustics, 70(7): 964–972.
  • Uygunol ODSS. 2009. Gsm baz istasyonlarında elektromanyetik kirlilik haritalarının coğrafi bilgi sistemi (cbs) yardımıyla oluşturulması Konya örneği. 12. Türkiye Harita Bilimsel ve Teknik Kurultayı, Mayıs 11-15, Ankara, Türkiye, pp: 542.
  • Ventura R, Mallet V, Issarny V, Raverdy PG, Rebhi F. 2017. Evaluation and calibration of mobile phones for noise monitoring application. J Acoustical Soc America, 142(5): 3084–3093.
  • World Bank. 2023. Urban development. global urban population trend. URL: https://www.worldbank.org/en/topic/urbandevelopment/overview#:~:text=Today%2C%20some%2056%25%20of%20the,people%20will%20live%20in%20cities (accessed date: December 15, 2023).
  • Yomralıoğlu T. 2000. Coğrafi bilgi sistemleri, temel kavramlar ve uygulamalar. Seçil Ofset, İstanbul, Türkiye, 1. Basım, pp: 479.
  • Zamora W, Calafate C, Cano JC, Manzoni P. 2017. Accurate ambient noise assessment using smartphones. Sensors, 17(4): 917.
  • Zhao B, Cai M, Wang L. 2019. Urban planning area traffic noise prediction based on noise mapping. InINTER-NOISE and NOISE-CON Congress and Conference Proceedings, June 16-19, Madrid, Spain, pp: 2008.
  • Zhou Z, Kang J, Zou Z, Wang H. 2017. Analysis of traffic noise distribution and influence factors in Chinese urban residential blocks. Environ Planning B: Urban Analytics City Sci, 44(3): 570–587.
There are 35 citations in total.

Details

Primary Language English
Subjects Geomatic Engineering (Other), Environmental Problems
Journal Section Reviews
Authors

Faysal M. Omar 0009-0006-9509-2404

Bülent Bostancı 0000-0003-2255-2503

Publication Date July 15, 2024
Submission Date January 25, 2024
Acceptance Date May 22, 2024
Published in Issue Year 2024

Cite

APA Omar, F. M., & Bostancı, B. (2024). General Review of Smartphone Usability in Noise Mapping. Black Sea Journal of Engineering and Science, 7(4), 804-814. https://doi.org/10.34248/bsengineering.1425362
AMA Omar FM, Bostancı B. General Review of Smartphone Usability in Noise Mapping. BSJ Eng. Sci. July 2024;7(4):804-814. doi:10.34248/bsengineering.1425362
Chicago Omar, Faysal M., and Bülent Bostancı. “General Review of Smartphone Usability in Noise Mapping”. Black Sea Journal of Engineering and Science 7, no. 4 (July 2024): 804-14. https://doi.org/10.34248/bsengineering.1425362.
EndNote Omar FM, Bostancı B (July 1, 2024) General Review of Smartphone Usability in Noise Mapping. Black Sea Journal of Engineering and Science 7 4 804–814.
IEEE F. M. Omar and B. Bostancı, “General Review of Smartphone Usability in Noise Mapping”, BSJ Eng. Sci., vol. 7, no. 4, pp. 804–814, 2024, doi: 10.34248/bsengineering.1425362.
ISNAD Omar, Faysal M. - Bostancı, Bülent. “General Review of Smartphone Usability in Noise Mapping”. Black Sea Journal of Engineering and Science 7/4 (July 2024), 804-814. https://doi.org/10.34248/bsengineering.1425362.
JAMA Omar FM, Bostancı B. General Review of Smartphone Usability in Noise Mapping. BSJ Eng. Sci. 2024;7:804–814.
MLA Omar, Faysal M. and Bülent Bostancı. “General Review of Smartphone Usability in Noise Mapping”. Black Sea Journal of Engineering and Science, vol. 7, no. 4, 2024, pp. 804-1, doi:10.34248/bsengineering.1425362.
Vancouver Omar FM, Bostancı B. General Review of Smartphone Usability in Noise Mapping. BSJ Eng. Sci. 2024;7(4):804-1.

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