Abstract
Encouraging people to walk rather than using other means of transportation is an important factor towards personal health and environmental sustainability. However, given the large number of pedestrian accidents recorded every year, the need for safe urban environments is increasing. Taking advantage of the potential of citizen-science for crowdsourcing data and creating awareness, we developed a smartphone application for enhancing the safety of pedestrians while walking in cities. Using the application, citizens will monitor the urban sidewalks and update a crowdsourcing platform with the detected barriers and damages that hinder safe walking, along with their location on a city map. To help users assign the correct type of obstacle, and authorities to assess the urgency, a Convolutional Neural Network (CNN) model for barrier and damage recognition is embedded in the application. The results of a user evaluation, based on a group of volunteers who used the application in real conditions, demonstrate the potential of using the application in conjunction with a smart city framework.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
Notes
- 1.
- 2.
- 3.
- 4.
- 5.
- 6.
- 7.
- 8.
- 9.
- 10.
References
Bierings, R., Jansonius, N.: Luminance and pedestrians’ perceived ability to see after dark: mapping the Netherlands using a citizen science network of smartphone users. Light. Res. Technol. 51(2), 231–242 (2019). https://doi.org/10.1177/1477153518758355
Bolaños, M., Radeva, P.: Simultaneous food localization and recognition. In: 23rd International Conference on Pattern Recognition (ICPR), pp. 3140–3145 (2016)
Bonney, R., et al.: Citizen science: a developing tool for expanding science knowledge and scientific literacy. Bioscience 59(11), 977–984 (2009). https://doi.org/10.1525/bio.2009.59.11.9
Furnari, A., Farinella, G.M., Battiato, S.: Recognizing personal locations from egocentric videos. IEEE Trans. Hum.-Mach. Syst. 47(1), 6–18 (2017)
Haklay, M.E.: Beyond quantification: a role for citizen science and community science in a smart city. In: Proceedings of the Data and City Workshop. Data and City Workshop, Meynooth University, Ireland (2015). https://discovery.ucl.ac.uk/id/eprint/1470344/
Kapenekakis, I., Chorianopoulos, K.: Citizen science for pedestrian cartography: collection and moderation of walkable routes in cities through mobile gamification. Hum.-Centric Comput. Inf. Sci. 7(1), 10 (2017). https://doi.org/10.1186/s13673-017-0090-9
Maramis, C., et al.: Developing a novel citizen-scientist smartphone app for collecting behavioral and affective data from children populations. In: O’Hare, G.M.P., O’Grady, M.J., O’Donoghue, J., Henn, P. (eds.) MobiHealth 2019. LNICST, vol. 320, pp. 294–302. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-49289-2_23
Mirri, S., Prandi, C., Salomoni, P.: Personalizing pedestrian accessible way-finding with mPASS. In: 13th IEEE Annual Consumer Communications & Networking Conference (CCNC), pp. 1119–1124. IEEE, Las Vegas (2016). https://doi.org/10.1109/CCNC.2016.7444946
Papageorgiou, G., Hadjigeorgiou, K., Ness, A.N.: Exploring the prospects of developing a smartphone application for pedestrians. In: 2020 19th International Symposium INFOTEH-JAHORINA (INFOTEH), pp. 1–5 (2020). https://doi.org/10.1109/INFOTEH48170.2020.9066287
Sas-Bojarska, A., Rembeza, M.: Planning the city against barriers. Enhancing the role of public spaces. Procedia Eng. 161, 1556–1562 (2016). https://doi.org/10.1016/j.proeng.2016.08.626
Schrepp, M., Hinderks, A., Thomaschewski, J.: Applying the user experience questionnaire (UEQ) in different evaluation scenarios. In: Marcus, A. (ed.) DUXU 2014. LNCS, vol. 8517, pp. 383–392. Springer, Cham (2014). https://doi.org/10.1007/978-3-319-07668-3_37
Schrepp, M., Hinderks, A., Thomaschewski, J.: Construction of a benchmark for the user experience questionnaire (UEQ). Int. J. Interact. Multimed. Artif. Intell. 4, 40–44 (2017). https://doi.org/10.9781/ijimai.2017.445
Smith, S.F., et al.: Connecting pedestrians with disabilities to adaptive signal control for safe intersection crossing and enhanced mobility: system requirements [year 2]. Technical report FHWA-JPO-19-751, U.S. Department of Transportation, Intelligent Transportation Systems Joint Program Office (2019). https://rosap.ntl.bts.gov/view/dot/43627
Theodosiou, Z., Lanitis, A.: Visual lifelogs retrieval: state of the art and future challenges. In: 2019 14th International Workshop on Semantic and Social Media Adaptation and Personalization (SMAP) (2019)
Theodosiou, Z., Partaourides, H., Atun, T., Panayi, S., Lanitis, A.: A first-person database for detecting barriers for pedestrians. In: 15th International Conference on Computer Vision Theory and Applications, VISAPP, vol. 5, pp. 660–666 (2020). https://doi.org/10.5220/0009107506600666
Verdecchia, R., Malavolta, I., Lago, P.: Guidelines for architecting android apps: a mixed-method empirical study. In: 2019 IEEE International Conference on Software Architecture (ICSA), pp. 141–150. IEEE, Hamburg (2019). https://doi.org/10.1109/ICSA.2019.00023
Wang, T., Cardone, G., Corradi, A., Torresani, L., Campbell, A.T.: Walksafe: a pedestrian safety app for mobile phone users who walk and talk while crossing roads. In: Proceedings of the Twelfth Workshop on Mobile Computing Systems & Applications - HotMobile 2012, p. 1. ACM Press, San Diego (2012). https://doi.org/10.1145/2162081.2162089
WHO: global status report on road safety 2018: summary. Technical report WHO/NMH/NVI/18.20. WHO, Geneva (2018). https://www.who.int/violence_injury_prevention/road_safety_status/2018/en/
Acknowledgements
This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 739578 complemented by the Government of the Republic of Cyprus through the Directorate General for European Programmes, Coordination and Development.
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Thoma, M., Theodosiou, Z., Partaourides, H., Tylliros, C., Antoniades, D., Lanitis, A. (2021). A Smartphone Application Designed to Detect Obstacles for Pedestrians’ Safety. In: Paiva, S., Lopes, S.I., Zitouni, R., Gupta, N., Lopes, S.F., Yonezawa, T. (eds) Science and Technologies for Smart Cities. SmartCity360° 2020. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 372. Springer, Cham. https://doi.org/10.1007/978-3-030-76063-2_25
Download citation
DOI: https://doi.org/10.1007/978-3-030-76063-2_25
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-76062-5
Online ISBN: 978-3-030-76063-2
eBook Packages: Computer ScienceComputer Science (R0)