Inference of driver behavior using correlated IoT data from the vehicle telemetry and the driver mobile phone

• Autorzy: da Silva Daniel Alves , Sousa Torres José Alberto , Pinheiro Alexandre , de Caldas Filho Francisco L. , Mendonça Fabio L. L. , Praciano Bruno J. G. , Oliveira Kfouri Guilherme , de Sousa Jr Rafael T.

Identyfikatory

DOI

10.15439/2019F263

• Konferencja: Federated Conference on Computer Science and Information Systems (14 ; 01-04.09.2019 ; Leipzig, Germany)
• Języki publikacji: EN

Abstrakty

EN

The drivers' behavior in traffic is a determining factor for the rate of accidents on roads and highways. This paper presents the design an intelligent IoT system capable of inferring and warning about road traffic risks and danger zones, based on data obtained from the vehicles and their drivers mobile phones, thus helping to avoid accidents and seeking preserve the lives of the passengers. The proposed approach is to collect vehicle telemetry data and mobile phone sensors data through an IoT network and then to analyze the drivers' behavior while driving, along with data from the environment. The results of the inference serve to alert the drivers about incidents in their trajectory as well as to provide feedback on how they are driving. The proposal is validated using a developed prototype to test its data collection and inference features in a small scale experiment.

Słowa kluczowe

EN

Internet of things; vehicular networks; driving behaviour; inference; OBD II; Android

PL

Internet rzeczy; sieci komunikacyjne; zachowanie kierowcy; wnioskowanie; OBD II; samodiagnostyka pojazdu; Android

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2019
• Tom: Vol. 18
• Strony: 487--491
• Opis fizyczny: Bibliogr. 17 poz., il., wz.

Twórcy

autor

da Silva Daniel Alves

• Department of Electrical Engineering, University of Brasília, Brasília, Brasil

autor

Sousa Torres José Alberto

• Department of Electrical Engineering, University of Brasília, Brasília, Brasil

autor

Pinheiro Alexandre

• Department of Electrical Engineering, University of Brasília, Brasília, Brasil

autor

de Caldas Filho Francisco L.

• Department of Electrical Engineering, University of Brasília, Brasília, Brasil

autor

Mendonça Fabio L. L.

• Department of Electrical Engineering, University of Brasília, Brasília, Brasil

autor

Praciano Bruno J. G.

• Department of Electrical Engineering, University of Brasília, Brasília, Brasil

autor

Oliveira Kfouri Guilherme

• Department of Electrical Engineering, University of Brasília, Brasília, Brasil

autor

de Sousa Jr Rafael T.

• Department of Electrical Engineering, University of Brasília, Brasília, Brasil

Bibliografia

• 1. Brasil. (2019) Portal oficial de notícias da Polícia Rodoviária Federal: Balanço PRF 2018. [Online]. Available: https://www.prf.gov. br/agencia/prf-registra-diminuicao-no-numero-de-acidentes-e-mortes-nas-rodovias-federais-em-2018
• 2. J. Ferreira Júnior and G. Pessin, “Análise de perfil de motoristas: Detecção de eventos por meio de smartphones e aprendizado de máquina,” in Anais do WOCCES 2016 Workshop de Comunicação em Sistemas Embarcados Críticos, 2016, pp. 76–85.
• 3. FGV-SP. (2019) Pesquisa anual do uso de TI da Fundação Getúlio Vargas-SP. [Online]. Available: https://eaesp.fgv.br/ensinoeconhecimento/centros/cia/pesquisa
• 4. S. R. Muramudalige and H. D. Bandara, “Demo: Cloud-based vehicular data analytics platform,” in Proceedings of the 14th Annual International Conference on Mobile Systems, Applications, and Services Companion, ser. MobiSys ’16 Companion. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2938559.2948849. ISBN 978-1-4503-4416-6 pp. 1–1. [Online]. Available: http://doi.acm.org/10.1145/2938559.2948849
• 5. M. Amarasinghe, S. Kottegoda, A. L. Arachchi, S. Muramudalige, H. M. N. Dilum Bandara, and A. Azeez, “Cloud-based driver monitoring and vehicle diagnostic with obd2 telematics,” in 2015 IEEE International Conference on Electro/Information Technology (EIT), May 2015. http://dx.doi.org/10.1109/EIT.2015.7293433. ISSN 2154-0373 pp. 505–510.
• 6. E. Borgia, “The Internet of Things vision: Key features, applications and open issues,” Computer Communications, vol. 54, pp. 1–31, Dec. 2014. [Online]. Available: http://dx.doi.org/10.1016/j.comcom.2014.09.008
• 7. S. R. Department. (2016) Internet of things (iot) connected devices installed base worldwide from 2015 to 2025 (in billions). [Online]. Available: https://www.statista.com/statistics/471264/iot-number-of-connected-devices-worldwide/
• 8. A. Al-Fuqaha, M. Guizani, M. Mohammadi, M. . Aledhari, and M. Ayyash, “Internet of things: A survey on enabling technologies, protocols, and applications,” IEEE Communications Surveys Tutorials, vol. 17, no. 4, pp. 2347–2376, Fourthquarter 2015. http://dx.doi.org/10.1109/COMST.2015.2444095
• 9. B. Xiao, R. Rahmani, Yuhong Li, D. Gillblad, and T. Kanter, “Intelligent data-intensive iot: A survey,” in 2016 2nd IEEE International Conference on Computer and Communications (ICCC), Oct 2016. http://dx.doi.org/10.1109/CompComm.2016.7925122 pp. 2362–2368.
• 10. T. Xu, J. B. Wendt, and M. Potkonjak, “Security of iot systems: Design challenges and opportunities,” in 2014 IEEE/ACM International Conference on Computer-Aided Design (ICCAD), Nov 2014. http://dx.doi.org/10.1109/ICCAD.2014.7001385. ISSN 1092-3152 pp. 417–423.
• 11. G. Castignani, T. Derrmann, R. Frank, and T. Engel, “Driver behavior profiling using smartphones: A low-cost platform for driver monitoring,” IEEE Intelligent Transportation Systems Magazine, vol. 7, no. 1, pp. 91–102, Spring 2015.
• 12. G. Castignani, T. Derrmann, R. Frank, and T. Engel, “Driver behavior profiling using smartphones: A low-cost platform for driver monitoring,” IEEE Intelligent Transportation Systems Magazine, vol. 7, no. 1, pp. 91–102, 2015.
• 13. V. Astarita, G. Guido, D. Mongelli, and V. P. Giofrè, “A co-operative methodology to estimate car fuel consumption by using smartphone sensors,” Transport, vol. 30, no. 3, pp. 307–311, 2015.
• 14. B. P. Puig, “Smartphones for smart driving: a proof of concept,” unpublished master’s thesis for master’s degree, Universitat Politecnica de Catalunya, Barcelona, 2013.
• 15. C. C. d. M. Silva, F. L. d. Caldas, F. D. Machado, F. L. Mendonça, and R. T. de Sousa Júnior, “Proposta de auto-registro de serviços pelos dispositivos em ambientes de iot,” 34o Simpósio Brasileiro de Telecomunicações e Processamento de Sinais, 2016.
• 16. Hongyang Zhao, Huan Zhou, Canfeng Chen, and J. Chen, “Join driving: A smart phone-based driving behavior evaluation system,” in 2013 IEEE Global Communications Conference (GLOBECOM), Dec 2013. doi: 10.1109/GLOCOM.2013.6831046. ISSN 1930-529X pp. 48–53.
• 17. J. Paefgen, F. Kehr, Y. Zhai, and F. Michahelles, “Driving behavior analysis with smartphones: Insights from a controlled field study,” in Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia, ser. MUM ’12. New York, NY, USA: ACM, 2012. http://dx.doi.org/10.1145/2406367.2406412. ISBN 978-1-4503-1815-0 pp. 36:1–36:8. [Online]. Available: http://doi.acm.org/10.1145/2406367.2406412

Uwagi

1. This research work is supported by the Brazilian research and innovation Agencies CAPES (Grants 23038.007604/2014-69 FORTE and 88887.115692/2016-00), CNPq (Grant 465741/2014-2 INCT-CyberSecurity), and FAPDF (Grants 0193.001366/2016 UIoT and 0193.001365/2016 SSDDC), as well as the LATITUDE/UnB Laboratory (Grant 23106.099441/2016-43 SDN), the Ministry of the Economy (Grants 005/2016DIPLA, 011/2016 SEST and 083/2016 ENAP), the Institutional Security Office of the Presidency of the Republic of Brazil (Grant 002/2017), and the IEEE VTS Centro-Norte Brasil Chapter.

2. Track 3: Network Systems and Applications

3. Technical Session: 3rd Workshop on Internet of Things - Enablers, Challenges and Applications

4. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).