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Ambient Intelligence in Systems to Support Wellbeing of Drivers

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Guide to Ambient Intelligence in the IoT Environment

Abstract

The possibilities of ambient intelligence in the healthcare sector are multifaceted, ranging from supporting physical to mental wellbeing in various ways. Ambient intelligence can play an important role in supporting emotional wellbeing and reducing discomfort. Real-time capability in systems to provide support during discomfort can be useful in scenarios which are traditionally neglected. Absence of concern about wellbeing among commercial vehicle drivers during stressful driving situations may lead to accidents and poor lifestyle. Ambient intelligence can play a role in determining such situations to support the drivers when it is required. The availability of low-cost Internet of Thing (IoT ) based components has opened up opportunities in areas where resources are constrained. In the current chapter, the focus is on improving the wellbeing of commercial vehicle drivers in a low-income setting. The chapter focuses on understanding the concepts of discomfort and wellbeing through a detailed qualitative study followed by a possible solution approach to address the ongoing challenges. A low-cost wearable IoT-enabled system along with a long-term analytic support is proposed to improve the wellbeing of drivers using ambient intelligence. The entire system is built up using a connectivity framework. The low-cost IoT device would enable support for discomfort for community who traditionally do not receive such support. Wellbeing of drivers is important for improved driving quality and better traffic management . A system in place to support drivers in real time, named Bap re Bap is presented here in the context of Bangladesh .

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References

  1. Acampora G, Cook DJ, Rashidi P (2013) A survey on ambient intelligence in healthcare. In: Proceedings of the IEEE 101.12, pp 2470–2494. https://doi.org/10.1109/jproc.2013.2262913

    Article  Google Scholar 

  2. Bohn J, Coroama V, Langheinrich M, Mattern F, Rohs M (2005) Social, economic, and ethical implications of ambient intelligence and ubiquitous computing. Ambient intelligence. Springer, Berlin, Heidelberg, pp 5–29

    Google Scholar 

  3. Memon M, Wagner SR, Pedersen CF, Beevi FHA, Hansen FO (2014) Ambient assisted living healthcare frameworks, platforms, standards, and quality attributes. Sensors 14(3):4312–4341

    Article  Google Scholar 

  4. Ericsson E (2001) Independent driving pattern factors and their influence on fuel-use and exhaust emission. Journal on Transportation Research Part D: Transport and Environment, Elsevier, Vol 6, Issue 5, pp 325–345. https://doi.org/10.1016/s1361-9209(01)00003-7

    Article  Google Scholar 

  5. Iqbal ST, Horvitz E, Ju YC, Mathews E (2011) Hang on a Sec!: effects of proactive mediation of phone conversations while driving. In: Proceedings of the SIGCHI conference on human factors in computing systems (CHI ’11). ACM, New York, NY, USA, pp 463–472. http://dx.doi.org/10.1145/1978942.1979008

  6. Jonsson I-M, Nass C, Endo J, Reaves B, Harris H, Le Ta J, Chan N, Kerkenbush NL, Lasome CE (2003) The emerging role of electronic diaries in the management of diabetes mellitus. AACN Adv Crit Care 14(30:371–378

    Google Scholar 

  7. Mahmud K, Gope K, Chowdhury SMR (2012).Possible causes & solutions of traffic jam and their impact on the economy of City. J Manag Sustain 2(2):112

    Google Scholar 

  8. Ahmed N (2010) Reliable framework for unreliable RFID devices. In: 2010 8th IEEE international conference on pervasive computing and communications workshops (PERCOM Workshops), IEEE

    Google Scholar 

  9. Demiris G, Oliver DP, Dickey G, Skubic M, Rantz M (2008) Findings from a participatory evaluation of a smart home application for older adults. Technol Health Care16(2):111–118

    Google Scholar 

  10. Hu TY, Xie X, Li J (2013) Negative or positive? The effect of emotion and mood on risky driving. Transp Rese Part F Traffic Psychol Behav 16(2013):29–40

    Article  Google Scholar 

  11. Choudhury CF, Ben-Akiva ME (2013) Modelling driving decisions: a latent plan approach. Transportmetrica A Transp Sci 9(6):546–566

    Article  Google Scholar 

  12. Miyajima C, Angkititrakul P, Takeda K (2013) Behavior signal processing for vehicle applications. APSIPA Trans Signal Inf Process 2(2013):e2

    Article  Google Scholar 

  13. Abedin J (2008) Accidents or Murders? http://www.daily-sun.com/home/printnews/304913. Accessed 2018

  14. Bonsall P, Liu R, Young W (2005) Modelling safety-related driving behaviour-impact of parameter values. Transp Res Part A Policy Pract 39(5):425–444

    Google Scholar 

  15. Ranney TA (1994) Models of driving behavior: a review of their evolution. Accident Anal Prev 26(6):733–750

    Article  Google Scholar 

  16. Toledo T, Koutsopoulos HN, Ben-Akiva M (2009) Estimation of an integrated driving behavior model. Transp Res Part C: Emerg Technol 17(4):365–380

    Article  Google Scholar 

  17. Mierlo JV, Maggetto G, Burgwal EV, Gense R, (2004). Driving style and traffic measures-influence on vehicle emissions and fuel consumption. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering 218, 1 (2004), 43–50

    Article  Google Scholar 

  18. Iqbal ST, Ju YC, Horvitz E, (2010) Cars, calls, and cognition: investigating driving and divided attention. In: Proceedings of the SIGCHI conference on human factors in computing systems (CHI ’10). ACM, New York, NY, USA, pp 1281–1290. DOI:http://dx.doi.org/10.1145/1753326.1753518

  19. World Health Organization and others (2011) Mobile phone use: a growing problem of driver distraction. http://www.who.int/violence_injury_prevention/publications/road_traffic/distracted_driving/en/index.html

  20. Strayer DL, Drews FA, (2007). Cell-phone–induced driver distraction. Current Dir Psychol Sci 16(3):128–131

    Article  Google Scholar 

  21. Crundall D, Loon EV, Underwood G (2006) Attraction and distraction of attention with roadside advertisements. Accident Anal Prev 38(4):671–677

    Article  Google Scholar 

  22. Pollatsek A, Fisher DL, Pradhan A (2006) Identifying and remedying failures of selective attention in younger drivers. Curr Dir Psychol Sci 15(5):255–259. DOI:http://dx.doi.org/10.1111/j.1467-8721.2006.00447.x

    Article  Google Scholar 

  23. Mathias JL, Lucas LK (2009) Cognitive predictors of unsafe driving in older drivers: a meta-analysis. IPG Int Psychogeriatr 21(4):637–653. DOI:http://dx.doi.org/10.1017/S1041610209009119

    Article  Google Scholar 

  24. Okonkwo OC, Crowe M, Wadley VG, Ball K (2008) Visual attention and selfregulation of driving among older adults. Int Psychogeriatr 20(2):162–173. Issue 01. DOI:http://dx.doi.org/10.1017/S104161020700539X

  25. Pollatsek A, Romoser MRE, Fisher DL (2012) Identifying and remediating failures of selective attention in older drivers. Curr Dir Psychol Sci 21(1):3–7

    Article  Google Scholar 

  26. Salvucci DD (2013) Distraction beyond the driver: predicting the effects of in-vehicle interaction on surrounding traffic. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 3131–3134

    Google Scholar 

  27. Clarke DD, Ward P, Bartle C, Truman W (2006) Young driver accidents in the UK: the influence of age, experience, and time of day. Accident Anal Prev 38(5):871–878

    Article  Google Scholar 

  28. Abdu R, Shinar D, Meiran N (2012) Situational (state) anger and driving. Transp Rese Part F Traffic Psychol Behav 15(5):575–580

    Article  Google Scholar 

  29. Islam MM, Choudhury CF, (2012) A violation behavior model for non-motorized vehicle drivers in heterogeneous traffic streams. In: Transportation research board 91st annual meeting

    Google Scholar 

  30. Gunatillake T, Cairney P, Akcelik R (2000) Traffic management performance: development of a traffic frustration index (2000)

    Google Scholar 

  31. Zafiroglu A, Healey J, Plowman T (2012) Navigation to multiple local transportation futures: cross-interrogating remembered and recorded drives. In: Proceedings of the 4th international conference on automotive user interfaces and interactive vehicular applications. ACM, pp 139–146

    Google Scholar 

  32. Valck ED, Groot ED, Cluydts R (2003) Effects of slow-release caffeine and a nap on driving simulator performance after partial sleep deprivation. Percept Motor Skills 96(1):67–78

    Google Scholar 

  33. Webb TL, Sheeran P, Totterdell P, Miles E, Mansell W, Baker S (2012) Using implementation intentions to overcome the effect of mood on risky behaviour. Br J Soc Psychol 51(2):330–345

    Article  Google Scholar 

  34. Lajunen T, Summala H (1995) Driving experience, personality, and skill and safety-motive dimensions\in drivers’ self-assessments. Personal Individ Diff 19(3):307–318

    Article  Google Scholar 

  35. McCartt AT, Shabanova VI, Leaf WA (2003) Driving experience, crashes and traffic citations of teenage beginning drivers. Accident Anal Prev 35(3):311–320

    Article  Google Scholar 

  36. Gulian E, Glendon AI, Matthews G, Davies DR, Debney LM (1990) The stress of driving: a diary study. Work Stress 4(1):7–16. http://dx.doi.org/10.1080/02678379008256960

    Article  Google Scholar 

  37. Caird JK, Willness CR, Steel P, Scialfa C (2008) A meta-analysis of the effects of cell phones on driver performance. Accid Anal Prev 40(4):1282–1293

    Article  Google Scholar 

  38. Caird JK, Johnston KA, Willness CR, Asbridge M, Steel P (2014) A meta-analysis of the effects of texting on driving. Accid Anal Prev 71(2014):311–318

    Article  Google Scholar 

  39. Dell N, Vaidyanathan V, Medhi I, Cutrell E, Thies W (2012) Yours is better!: participant response bias in HCI. In: Proceedings of the SIGCHI conference on human factors in computing systems. ACM, pp 1321–1330

    Google Scholar 

  40. Ahmed SI, Jackson SJ, Ahmed N, Ferdous HS, Rifat MR, Rizvi ASM, Ahmed S, Mansur RS (2014) Protibadi: a platform for fighting sexual harassment in urban bangladesh. In: Proceedings of the 32nd annual ACM conference on human factors in computing systems. ACM, pp 2695–2704

    Google Scholar 

  41. Toyama K (2015) Geek heresy: rescuing social change from the cult of technology. PublicAffairs

    Google Scholar 

  42. Ahmed SI, Ahmed N, Hussain F, Kumar N (2016) Computing beyond gender-imposed limits. In: Proceedings of the second workshop on computing within limits. ACM, p 6

    Google Scholar 

  43. Ahmed SI, Jackson SJ, Rifat MR (2015a) Learning to fix: knowledge, collaboration and mobile phone repair. In: Proceedings of the seventh international conference on information and communication technologies and development. ACM, p 4

    Google Scholar 

  44. Ahmed SI, Mim NJ, Jackson SJ (2015b). Residual mobilities: infrastructural displacement and post-colonial computing. In: Proceedings of the 33rd annual ACM conference on human factors in computing systems. ACM, pp 437–446

    Google Scholar 

  45. Assignmentpoint.com (2015) Traffic Jam in City. http://www.assignmentpoint.com/arts/modern-civilization/traffic-jam-dhaka-city.html. Accessed July 2015

  46. Dhakatribune.com (2013) Congestion costs Tk200bn every year: Survey http://www.dhakatribune.com/bangladesh/2013/jul/14/congestion-costs-tk200bn-every-year-survey. Accessed July 2015

  47. Prothomalo.com (2016) http://www.prothomalo.com/bangladesh/article/831007/. Accessed July 2017

  48. The Daily Observer. SC orders company to compensate victim’s family. http://www.observerbd.com/2016/04/16/146874.php

  49. Dhakatribune.com (2015) Bus driver remanded for killing CNG drivers. http://www.dhakatribune.com/bangladesh/crime/2015/12/23/bus-driver-remanded-for-killing-cng-driver/

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Ahmed, N. et al. (2019). Ambient Intelligence in Systems to Support Wellbeing of Drivers. In: Mahmood, Z. (eds) Guide to Ambient Intelligence in the IoT Environment. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-030-04173-1_10

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  • DOI: https://doi.org/10.1007/978-3-030-04173-1_10

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