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IoT-Based Framework for Crowd Management

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Mobile Solutions and Their Usefulness in Everyday Life

Abstract

Seasonally, a huge number of people visit public places (e.g., holy places like El-Harm El-Madini El-Harm El-Makki (KSA), railway stations like Mumbai suburban railway (India), or sports events in big stadiums). Crowd management is critical in these situations in order to avoid crowd disasters (e.g., stampede and suffocation). Therefore, there is an urgent need for a framework to manage these crowds in order to save people’s lives. This framework shall be smart and efficient in terms of crowd time management and exerted efforts. The proposed framework is based on IoT and supports mobile device interaction through smart applications with a fairly simple interface to suit all ages. The aim is to strongly support administrators controlling and distributing visitors over the given place. The framework consists of three layers: sensor, management, and interface layers. The sensor layer is responsible for crowd data acquisition. The management layer acts as a middleware between sensors and interface layers. It includes web services which are responsible for collecting and analyzing the data coming from the sensors. It then notifies administrators about overcrowded areas to take the suitable decisions. Afterwards, the suitable decision (e.g., close/open doors and roads) will be taken and transferred to the interface layer. The interface layer is formed by user-friendly applications that communicate information between the management layer and the visitors. It provides mobile applications that aim to inform visitors about (1) current opening roads and doors, (2) how to find noncrowded areas, and (3) how to locate their groups and friends. The proposed framework provides high availability, reliability, usability, and performance.

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References

  1. Da Xu L, He W, Li S (2014) Internet of things in industries: a survey. IEEE Trans Ind Inf 10(4):2233–2243

    Article  Google Scholar 

  2. Atzori L, Iera A, Morabito G (2010) The internet of things: a survey. Comput Netw 54(15):2787–2805

    Article  Google Scholar 

  3. Sharma D, Bhondekar AP, Shukla AK, Ghanshyam C (2016) A review on technological advancements in crowd management. J Ambient Intell Humaniz Comput:1–11. https://doi.org/10.1007/s12652-016-0432-x

    Article  Google Scholar 

  4. Ge W, Collins RT, Barry Ruback R (2012) Vision-based analysis of small groups in pedestrian crowds. IEEE Trans Pattern Anal Mach Intell 34(5):1003–1016

    Article  Google Scholar 

  5. Georgoudas IG, Sirakoulis GC, Andreadis IT (2011) An anticipative crowd management system preventing clogging in exits during pedestrian evacuation processes. IEEE Syst J 5(1):129–141

    Article  Google Scholar 

  6. Yin H, Li D, Zheng X (2014) An energy based method to measure the crowd safety. Transport Res Proc 2:691–696

    Article  Google Scholar 

  7. Ghazi Abuarafah A, Khozium MO, AbdRabou E (2012) Real-time crowd monitoring using infrared thermal video sequences. J Am Sci 8(3):133–140

    Google Scholar 

  8. Yaseen S, Al-Habaibeh A, Su D, Otham F (2013) Real-time crowd density mapping using a novel sensory fusion model of infrared and visual systems. Saf Sci 57:313–325

    Article  Google Scholar 

  9. Khozium MO, Abuarafah AG, AbdRabou E (2012) A proposed computerbased system architecture for crowd management of pilgrims using thermography. Life Sci J 9(2):377–383

    Google Scholar 

  10. Butenuth M, Burkert F, Schmidt F, Hinz S, Hartmann D, Kneidl A, Borrmann A, Sirmacek B (2011) Integrating pedestrian simulation, tracking and event detection for crowd analysis. IEEE Int Conf Comput Vis Workshops (ICCV Workshops):150–157

    Google Scholar 

  11. Hussein Al-Hashedi A, Arshad MRM, Baharudin AS, Mohamed HH (2013) RFID applications in Hajj management system. IEEE Int Conf RFID-Tech App (RFID-TA):1–6

    Google Scholar 

  12. Mitchell RO, Rashid H, Dawood F, AlKhalidi A (2013) Hajj crowd management and navigation system: people tracking and location based services via integrated mobile and RFID systems. Int Conf Comput App Tech:1–7

    Google Scholar 

  13. Nair AM, Daniel SJ (2014) Design of wireless sensor networks for pilgrims tracking and monitoring. Int J Innov Sci Eng Res 1(2):1–6

    Google Scholar 

  14. Basalamah A (2016) Sensing the crowds using bluetooth low energy tags. IEEE Access 4:4225–4233

    Article  Google Scholar 

  15. Mohandes MA (2015) Mobile technology for socio-religious events: a case study of NFC technology. IEEE Technol Soc Mag 34(1):73–79

    Article  Google Scholar 

  16. Mohandes M, Haleem MA, Kousa M, Balakrishnan K (2013) Pilgrim tracking and identification using wireless sensor networks and GPS in a mobile phone. Arab J Sci Eng 38(8):2135–2141

    Article  Google Scholar 

  17. Amro A, Nijem Q (2012) Pilgrims “Hajj” tracking system (e-Mutawwif). Contemp Eng Sci 5(9):437–446

    Google Scholar 

  18. Ulicny B, Moskal J, Kokar MM (2013) Situational awareness from social media. STIDS:87–93

    Google Scholar 

  19. Yamin M., Al-Ahmadi HM, Al Muhammad A. Integrating social media and mobile apps into Hajj management. In 3rd international conference on computing for sustainable global development (INDIACom), 2016, pp. 1368–1372

    Google Scholar 

  20. Mohamed MF (2016) Service replication taxonomy in distributed environments. SOCA 10(3):317–336

    Article  Google Scholar 

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Correspondence to Marwa F. Mohamed .

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Mohamed, M.F., Shabayek, A.ER., El-Gayyar, M. (2019). IoT-Based Framework for Crowd Management. In: Paiva, S. (eds) Mobile Solutions and Their Usefulness in Everyday Life. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-93491-4_3

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  • DOI: https://doi.org/10.1007/978-3-319-93491-4_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-93490-7

  • Online ISBN: 978-3-319-93491-4

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