Skip to main content
SpringerLink
Log in

Public Transportation Occupancy Rate

  • Chapter
  • First Online:
Sustainable, Innovative and Intelligent Societies and Cities

Part of the book series: EAI/Springer Innovations in Communication and Computing ((EAISICC))

  • 156 Accesses

Abstract

European cities face increasingly more challenges caused by road traffic. Most people use individual cars, but this represents a huge demand on the existing infrastructures. As an alternative, public transportation is a good solution for the environment, safety, and affordability. Therefore, a lot of city centers are already investing in this solution, although one of the main issues pointed out as an obstacle is the lack of real-time information and the unpredictability of its use. To fulfill this necessity, computer vision systems are widely used in this type of application. However, financial costs and topics related to users’ privacy arise which can lead to future problems. ioCity project aims to improve existing solutions by keeping its costs low and its reliability as high as possible by mitigating its negative aspects. The solution developed uses ubiquitous passive technologies; it is pervasive, modular, and maintains the user’s privacy. This work presents the first approach to the conception and implementation of a low-cost system capable of monitoring the occupation rate on a bus with, at least, 70% accuracy.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 149.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 199.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. D.C. Bogatinoska, R. Malekian, J. Trengoska, W.A. Nyako, Advanced sensing and internet of things in Smart Cities [online]. (IEEE Xplore, 2016). Available at: https://ieeexplore.ieee.org/document/7522218. Accessed 27 Apr 2022

  2. A. Christodoulou, P. Christidis, Measuring Congestion in European Cities, EUR 30033 EN (Publications Office of the European Union, Luxembourg, 2020)

    Google Scholar 

  3. 2021 6th International Conference on Inventive Computation Technologies [ICICT 2021]. A Review of AI for Urban Planning: Towards Building Sustainable Smart Cities [online] (IEEE, Coimbatore, 2021). Available at: https://ieeexplore.ieee.org/abstract/document/9358548. Accessed 28 July 2022

  4. J. Wannenburg, R. Malekian, Body sensor network for mobile health monitoring, a diagnosis and anticipating system. IEEE Sensors J. 15(12), 6839–6852 (2015)

    Article  Google Scholar 

  5. Y. Ning, W. Zhong-qin, R. Malekian, W. Ru-chuan, A. Abdullah, Design of accurate vehicle location system using RFID. Electron. Electr. Eng. 19(8) (2013)

    Google Scholar 

  6. M. Bruglieri, F. Bruschi, A. Colorni, A. Luè, R. Nocerino, V. Rana, A real-time information system for public transport in case of delays and service disruptions. Transp. Res. Procedia 10, 493–502 (2015)

    Article  Google Scholar 

  7. P. Medviď, M. Gogola, S. Kubaľák, Occupancy of public transport vehicles in Slovakia. Transp. Res. Procedia 44, 153–159 (2020)

    Article  Google Scholar 

  8. J. Wood, Z. Yu, V. Gayah, Development and evaluation of frameworks for real-time bus passenger occupancy prediction. Int. J. Transp. Sci. Technol. (2022)

    Google Scholar 

  9. A. Murdan, V. Bucktowar, V. Oree, M. Enoch, Low-cost bus seating information technology system. IET Intell. Transp. Syst. 14(10), 1303–1310 (2020)

    Article  Google Scholar 

  10. D. Hensher, J. Rose, A. Collins, Identifying commuter preferences for existing modes and a proposed Metro in Sydney, Australia with special reference to crowding. Public Transp. 3(2), 109–147 (2011)

    Article  Google Scholar 

  11. Z. Li, D. Hensher, Crowding and public transport: A review of willingness to pay evidence and its relevance in project appraisal. Transp. Policy 18(6), 880–887 (2011)

    Article  Google Scholar 

  12. Instituto Nacional de Estatística, IP., Mobilidade e funcionalidade do território nas Áreas Metropolitanas do Porto e de Lisboa 2017 [online] (2018). Available at: https://www.ine.pt/xportal/xmain?xpid=INE&xpgid=ine_publicacoes&PUBLICACOESpub_boui=349495406&PUBLICACOESmodo=2&xlang=pt. Accessed 20 Apr 2022

  13. A. Coentrão, Em Lisboa e Porto, o transporte público ainda é para quem não tem alternativa [online] (PÚBLICO, 2018). Available at: https://www.publico.pt/2018/11/28/local/noticia/lisboa-porto-transporte-publico-nao-alternativa-1852696. Accessed 2 May 2022

  14. Moovit, Public transit facts & statistics for Lisboa [online] (Moovitapp, 2022). Available at: https://moovitapp.com/insights/en/Moovit_Insights_Public_Transit_Index_Portugal_Lisboa-2460. Accessed 27 Apr 2022

  15. C. Tomás, Os transportes continuam a ser o elefante na sala quando se fala de alterações climáticas [Online] (Expresso, 2018). Available at: https://expresso.pt/sociedade/2018-11-30-Os-transportes-continuam-a-ser-o-elefante-na-sala-quando-se-fala-de-alteracoes-climaticas#gs.85vvtp. Accessed 26 Apr 2022

  16. L. Mikkelsen, R. Buchakchiev, T. Madsen, H. Schwefel, Public transport occupancy estimation using WLAN probing. 2016 8th International Workshop on Resilient Networks Design and Modeling (RNDM) (2016)

    Google Scholar 

  17. D.K. Boyle, TCRP Synthesis 77: Passenger Counting Systems: A Synthesis of Transit Practice. Transportation Research Board of the National Academies, Washington, DC (2008)

    Google Scholar 

  18. P. Lengvenis, R. Simutis, V. Vaitkus, R. Maskeliunas, Application of computer vision systems for passenger counting in public transport. Electron. Electr. Eng. 19(3), 69 (2013)

    Google Scholar 

  19. L. Abdulrazzaq, M. Abdulkareem, M. Mat Yazid, M. Borhan, M. Mahdi, Traffic congestion: Shift from private car to public transportation. Civil Eng J 6(8), 1547–1554 (2020)

    Article  Google Scholar 

  20. M.R. André, Como se resolvem as insuportáveis filas de trânsito, Shifter [Online] (2018). Available: https://shifter.pt/2018/03/mobilidade-lisboa/. Accessed 27 Apr 2022

  21. Iocity.research.iotech.pt, ioCity [online] (2022). Available at: https://iocity.research.iotech.pt/. Accessed 28 July 2022

  22. W. Loga, K. Brzozowski, A. Ryguła, A method for estimating the occupancy rates of public transport vehicles using data from weigh-in-motion systems, in Communications in Computer and Information Science, (Springer, Cham, 2016), pp. 426–435

    Google Scholar 

  23. B. Agard, C. Morency, M. Trépanier, Mining public transport user behaviour from smart card data. IFAC Proc. Vol. 39(3), 399–404 (2006)

    Article  Google Scholar 

  24. B. George, H. Zangl, T. Bretterklieber, G. Brasseur, Seat occupancy detection based on capacitive sensing. IEEE Trans. Instrum. Meas. 58(5), 1487–1494 (2009)

    Article  Google Scholar 

  25. A. Zeeman, M. Booysen, G. Ruggeri, B. Lagana, Capacitive seat sensors for multiple occupancy detection using a low-cost setup. 2013 IEEE International Conference on Industrial Technology (ICIT)(2013)

    Google Scholar 

  26. H. Nguyen, N. Gulati, Y. Lee, R. Balan, Real-time detection of seat occupancy & hogging, in Proceedings of the 2015 International Workshop on Internet of Things towards Applications (2015)

    Google Scholar 

  27. Chao-Ho Chen, Yin-Chan Chang, Tsong-Yi Chen, Da-Jinn Wang, People counting system for getting in/out of a bus based on video processing, in 2008 Eighth International Conference on Intelligent Systems Design and Applications (2008)

    Google Scholar 

  28. D. Liciotti, A. Cenci, E. Frontoni, A. Mancini, P. Zingaretti, An intelligent RGB-D video system for bus passenger counting. Intell. Auton. Syst. 14, 473–484 (2017)

    Google Scholar 

  29. T. Yang, Y. Zhang, D. Shao, Y. Li, Clustering method for counting passengers getting in a bus with single camera. Opt. Eng. 49(3), 037203 (2010)

    Article  Google Scholar 

  30. S. Mukherjee, B. Saha, I. Jamal, R. Leclerc, N. Ray, A novel framework for automatic passenger counting, in 2011 18th IEEE International Conference on Image Processing (2011)

    Google Scholar 

  31. M. Stec, V. Herrmann, B. Stabernack, Using time-of-flight sensors for people counting applications, 2019 Conference on Design and Architectures for Signal and Image Processing (DASIP) (2019)

    Google Scholar 

  32. Google, Grab a seat and be on time with new transit updates on Google Maps [online] (2019). Available at: https://www.blog.google/products/maps/grab-seat-and-be-time-new-transit-updates-google-maps/. Accessed 30 May 2022

  33. Dilax.com. DILAX SLS-1000: Sensing with Care [online] (2022). Available at: https://www.dilax.com/en/sls-1000. Accessed 16 May 2022

  34. Dilax.com. Automatic Passenger Counting (APC): Sensors & Systems [online] (2022). Available at: https://www.dilax.com/en/products/automatic-passenger-counting. Accessed 16 May 2022

  35. Y. Kim, C. Theobalt, J. Diebel, J. Kosecka, B. Miscusik, S. Thrun, Multi-view image and ToF sensor fusion for dense 3D reconstruction, in 2009 IEEE 12th International Conference on Computer Vision Workshops, ICCV Workshops (2009)

    Google Scholar 

  36. H. Lu, A. Tuzikas, R. Radke, A zone-level occupancy counting system for commercial office spaces using low-resolution time-of-flight sensors. Energy Build. 252, 111390 (2021)

    Article  Google Scholar 

  37. J. Andrew, M. Kowsika, A. Vakil, J. Li, A motion induced passive infrared (PIR) sensor for stationary human occupancy detection, in Location and Navigation Symposium (PLANS) (IEEE/ION Position, 2020) pp. 1295–1304

    Google Scholar 

  38. S. Gokturk, H. Yalcin, C. Bamji, A time-of-flight depth sensor – system description, issues and solutions, in 2004 Conference on Computer Vision and Pattern Recognition Workshop (n.d.)

    Google Scholar 

  39. STMicroelectronics, VL53L5CX – STMicroelectronics [online] (2022). Available at: https://www.st.com/en/imaging-and-photonics-solutions/vl53l5cx.html. Accessed 19 May 2022

  40. P. Bhagwat, Bluetooth: Technology for short-range wireless apps. IEEE Internet Comput. 5(3), 96–103 (2001)

    Article  Google Scholar 

  41. J. Yin, Z. Yang, H. Cao, T. Liu, Z. Zhou, C. Wu, A survey on bluetooth 5.0 and mesh. ACM Trans. Sensor Netw. 15(3), 1–29 (2019)

    Article  Google Scholar 

  42. S. Darroudi, C. Gomez, J. Crowcroft, Bluetooth low energy mesh networks: A standards perspective. IEEE Commun. Mag. 58(4), 95–101 (2020)

    Article  Google Scholar 

  43. J. Yang, C. Poellabauer, P. Mitra, C. Neubecker, Beyond beaconing: Emerging applications and challenges of BLE. Ad Hoc Netw. 97, 102015 (2020)

    Article  Google Scholar 

  44. C. Gomez, J. Oller, J. Paradells, Overview and evaluation of bluetooth low energy: An emerging low-power wireless technology. Sensors 12(9), 11734–11753 (2012)

    Article  Google Scholar 

  45. J. Lin, T. Talty, O. Tonguz, On the potential of bluetooth low energy technology for vehicular applications. IEEE Commun. Mag. 53(1), 267–275 (2015)

    Article  Google Scholar 

  46. F. Dian, A. Yousefi, S. Lim, A practical study on Bluetooth Low Energy (BLE) throughput, in 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON) (IEEE, 2018), pp. 768–771.

    Google Scholar 

  47. STMicroelectronics. VL53L5CX – STMicroelectronics [online] (2022). Available at: https://www.st.com/en/imaging-and-photonics-solutions/vl53l5cx.html. Accessed 23 May 2022

  48. Nordicsemi.com. Software and other Downloads – nRF52832 Product Brief [online] (2022). Available at: https://www.nordicsemi.com/-/media/Software-and-other-downloads/Product-Briefs/nRF52832-product-brief.pdf?la=en&hash=2F9D995F754BA2F2EA944A2C4351E682AB7CB0B9. Accessed 23 May 2022.

  49. 2018. High Frequency Ceramic Solutions – 2.4GHz Mini Antenna, SMT. 3rd ed. [online] (Johanson Technology, Camarillo, 2018), pp. 1–5. Available at: https://www.johansontechnology.com/datasheets/2450AT18A100/2450AT18A100.pdf. Accessed 23 May 2022.

  50. Bluetooth® Technology Website, Understanding Bluetooth Range | Bluetooth® Technology Website [online] (2022). Available at: https://www.bluetooth.com/learn-about-bluetooth/key-attributes/range/. Accessed 23 May 2022

  51. St.com. STM32L431xx [online] (2022). Available at: https://www.st.com/resource/en/datasheet/stm32l431cc.pdf. Accessed 16 May 2022

  52. Infocenter.nordicsemi.com, nRF52832 Product Specification v1.8 [online] (2022). Available at: https://infocenter.nordicsemi.com/pdf/nRF52832_PS_v1.8.pdf. Accessed 16 May 2022

  53. Texas Instruments, TPS6305x Single Inductor Buck-Boost with 1-A Switches and Adjustable Soft Start [online] (2022). Available at: https://www.ti.com/lit/ds/symlink/tps63051.pdf?ts=1652720570889&ref_url=https%253A%252F%252Fwww.ti.com%252Fproduct%252FTPS63051. Accessed 16 May 2022

  54. Texas Instruments, bq27441-G1 System-Side Impedance Track Fuel Gauge [online] (2022). Available at: https://www.ti.com/lit/ds/symlink/bq27441-g1.pdf?ts=1652720924490&ref_url=https%253A%252F%252Fwww.ti.com%252Fdocument-viewer%252FBQ27441-G1%. Accessed 16 May 2022

  55. 2022. BQ2407x Standalone 1-Cell 1.5A Linear Battery Chargers with Power Path [online]. Available at: https://www.ti.com/lit/ds/symlink/bq24075.pdf?ts=1652680615845&ref_url=https%253A%252F%252Fwww.ti.com%252Fproduct%252FBQ24075. Accessed 16 May 2022

  56. Quectel.com, Wuwctel BG96 Mini PCIe [online] (2022). Available at: https://www.quectel.com/wp-content/uploads/pdfupload/Quectel_BG96_Mini_PCIe_LPWA_Specification_V1.0.pdf. Accessed 16 May 2022

  57. STMicroelectronics, X-NUCLEO-53L5A1 – STMicroelectronics [online] (2022). Available at: https://www.st.com/en/evaluation-tools/x-nucleo-53l5a1.html. Accessed 23 May 2022

  58. Nordicsemi.com, nRF52 DK – Development kit for Bluetooth Low Energy and Bluetooth mesh [online] (2022). Available at: https://www.nordicsemi.com/Products/Development-hardware/nrf52-dk. Accessed 23 May 2022

Download references

Acknowledgements

This work was developed in the framework of ioCity project (no 045397), which was co-financed by Portugal 2020, under the North Portugal Regional Operational Programme (NORTE 2020) through the European Regional Development Fund (ERDF).

Author information

Authors and Affiliations

  1. CENTITVC – Centre for Nanotechnology and Smart Materials, Vila Nova de Famalicão, Portugal

    Pedro Silva, Joana Campos, José Matos, José Salgado, Carla Salazar & Hugo Costa

  2. IOTECH – Innovation on Technology, Trofa, Portugal

    Filipe Portela & Daniel Carneiro

Authors
  1. Pedro Silva
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Joana Campos
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. José Matos
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. José Salgado
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Carla Salazar
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Hugo Costa
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Filipe Portela
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Daniel Carneiro
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pedro Silva .

Editor information

Editors and Affiliations

  1. Information Systems Department, Algoritmi Research Center, University of Minho, Guimarães, Portugal

    Carlos Filipe da Silva Portela

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this chapter

Check for updates. Verify currency and authenticity via CrossMark

Cite this chapter

Silva, P. et al. (2023). Public Transportation Occupancy Rate. In: da Silva Portela, C.F. (eds) Sustainable, Innovative and Intelligent Societies and Cities. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-031-30514-6_16

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-30514-6_16

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-30513-9

  • Online ISBN: 978-3-031-30514-6

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Search

Navigation