survey

Intelligent Evacuation Management Systems: A Review

Authors:

Azhar Mohd Ibrahim,

Ibrahim Venkat,

K. G. Subramanian,

Ahamad Tajudin Khader,

Philippe De WildeAuthors Info & Claims

ACM Transactions on Intelligent Systems and Technology (TIST), Volume 7, Issue 3

Article No.: 36, Pages 1 - 27

https://doi.org/10.1145/2842630

Published: 01 February 2016 Publication History

Abstract

Crowd and evacuation management have been active areas of research and study in the recent past. Various developments continue to take place in the process of efficient evacuation of crowds in mass gatherings. This article is intended to provide a review of intelligent evacuation management systems covering the aspects of crowd monitoring, crowd disaster prediction, evacuation modelling, and evacuation path guidelines. Soft computing approaches play a vital role in the design and deployment of intelligent evacuation applications pertaining to crowd control management. While the review deals with video and nonvideo based aspects of crowd monitoring and crowd disaster prediction, evacuation techniques are reviewed via the theme of soft computing, along with a brief review on the evacuation navigation path. We believe that this review will assist researchers in developing reliable automated evacuation systems that will help in ensuring the safety of the evacuees especially during emergency evacuation scenarios.

References

[1]

S. Ali and M. Shah. 2008. Floor fields for tracking in high density crowd scenes. The 10th European Conference on Computer Vision (ECCV), Lecture Notes in Computer Science, Vol. 5303, Springer, 1--14.

Digital Library

[2]

D. W. Allan, Neil Ashby, and C. H. Clifford. 1997. The Science of Timekeeping. Technical Report, Hewlett Packard Application Note 1287.

[3]

H. Alnabulsi and J. Drury. 2014. Social identification moderates the effect of crowd density on safety at the Hajj. Proceedings of the National Academy of Sciences of the United States of America 111, 25 (2014), 1--6. http://doi.org/10.1073/pnas.1404953111.

[4]

A. M. Nair and S. J. Daniel. 2014. Design of wireless sensor networks for pilgrims tracking and monitoring. International Journal of Innovations in Scientific and Engineering Research 1, 2 (2014), 1--6.

[5]

S. Y. Z. Au, M. C. Ryan, M. S. Carey, and S. P. Whalley. 1993. Managing crowd safety in public venues: A study to generate guidance for venue owners and enforcing authority inspectors. HSE Contract Research Report 53, 1 (1993).

[6]

M. I. Azhar, A. A. Shafie, and M. M. Rashid. 2012. Human identification system based on moment invariant features. In International Conference on Computer and Communication Engineering (ICCCE 2012). 216--221.

[7]

M. I. Azhar, A. A. Shafie, and M. M. Rashid. 2013. Performance metrics in video surveillance system. Journal of Engineering Science and Technology 8, 2 (2013), 199--216.

[8]

S. Bandini, S. Manzoni, G. Mauri, S. Redaelli, and L. Vanneschi. 2008. GP generation of pedestrian behavioral rules in an evacuation model based on SCA. In Proceedings of the 8th International Conference on Cellular Automata for Research and Industry (ACRI’08). 409--416.

Digital Library

[9]

U. Blanke, G. Troster, T. Franke, and P. Lukowicz. 2014. Capturing crowd dynamics at large-scale events using participatory GPS-localization. In 2014 IEEE 9th International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP). 1--7.

[10]

L. W. Chen, J. H. Cheng, and Y. C. Tseng. 2012. Evacuation time analysis and optimization for distributed emergency guiding based on wireless sensor networks. In International Conference on Connected Vehicles and Expo (ICCVE).

Digital Library

[11]

L. Chittaro and D. Nadalutti. 2008. Presenting evacuation instructions on mobile devices by means of location aware 3D virtual environments. In Proceedings of the 10th International Conference on Human Computer Interaction with Mobile Devices and Services, ACM, 395--398.

Digital Library

[12]

L. Chittaro and D. Nadalutti. 2009. A mobile RFID-based system for supporting evacuation of buildings. Mobile Response, Lecture Notes in Computer Science. Springer, 22--31.

Digital Library

[13]

H. Chizari, F. Malekinezhad, M. R. Embi, Y. M. Yatim, S. A. Razak, M. Hamdan, and M. Bakhtiari. 2013. Agent-based approach for modeling evacuee uncertainty behavior using game theory model. Life Science Journal 10, 3 (2013), 1350--1355.

[14]

L. Chu. 2010. A RFID-based hybrid building fire evacuation system on mobile phone. In 2010 6th International Conference on Intelligent Information Hiding and Multimedia Signal Processing (IIH-MSP). 155--158.

Digital Library

[15]

N. Dalal and B. Triggs. 2005. Histograms of oriented gradients for human detection. Computer Vision and Pattern Recognition 2 (2005), 886--893.

Digital Library

[16]

P. H. Dana and B. M. Penrod. 1990. The role of GPS in precise time and frequency dissemination. GPS World (July/August), 38--43.

[17]

C. Eckel, M. El-Gambal, and R. Wilson. 2009. Risk Loving after the storm: A Bayesian-network study of Hurricane Katrina evacuees. Journal of Economic Behavior and Organization 69, 2 (2009), 110--124.

[18]

Z. X. Fang, X. L. Zong, Q. Q. Li, Q. P. Li, and S. W. Xiong. 2011. Hierarchical multi-objective evacuation routing in stadium using ant colony optimization approach. Journal of Transport Geography 19, 3 (2011), 443--451.

[19]

J. Fruin. 1981. Crowd disasters - A systems evaluation of causes and countermeasures. Inc. US National Bureau of Standards, pub. NBSIR, 81-3261, 146.

[20]

S. L. Garfinkel and H. Holtzman. 2006. Understanding RFID technology. RFID: Applications, Security and Privacy, Pearson Education, Inc., New Jersey, 15--36.

[21]

A. Golas, R. Narain, and M. C. Lin. 2014. Continuum modeling of crowd turbulence. Physical Review E 90, 4 (2014), 042816. http://doi.org/10.1103/PhysRevE.90.042816.

[22]

S. Gwynne, E. R. Galea, M. Owen, P. J. Lawrence, and L. Filippidis. 1999. A review of the methodologies used in the computer simulation of evacuation from the built environment. Building and Environment 34, 6 (1999), 741--749.

[23]

M. H. Han, H. J. Jeong, E. H. Kim, K. S. Suh, and W. T. Hwang. 2004. Prediction of evacuation time in radiological emergency using fuzzy system. Probabilistic Safety Assessment and Management, 3218--3223.

[24]

D. Helbing and P. Molnar. 1995. Social force model for pedestrian dynamics. Physical Review E 51, 5 (1995), 4282--4286.

[25]

D. Helbing, A. Johansson, and H. Z. Al-Abideen. 2007. Dynamics of crowd disasters: An empirical study. Physical Review E 75, 4 (2007), 046109.

[26]

D. Helbing and P. Mukerji. 2012. Crowd disasters as systemic failures: Analysis of the love parade disaster. EPJ Data Science 1, 7 (2012).

[27]

L. Hong, S. Yuling, and L. Yuanyuan. 2012. Modeling and path generation approaches for crowd simulation based on computational intelligence. Chinese Journal of Electronics 21, 4 (2012), 636--641.

[28]

Y. T. Hsu and S. Peeta. 2013. An aggregate approach to model evacuee behavior for no-notice evacuation operations. Transportation 40, 3 (2013), 671--696.

[29]

J. C. S. Jacques Junior, S. Raupp Musse, and C. R. Jung. 2010. Crowd analysis using computer vision techniques. IEEE Signal Processing Magazine 27, 5 (2010), 66--77.

[30]

J. Janacek. 2010. The evacuation plan design under uncertain times of transportation. WIT Transactions on the Built Environment 111 (2010), 83--92.

[31]

L. Jianfeng, and Z. Bin. 2009. A large-scale open space emergency evacuation model. In 2009 International Workshop on Intelligent Systems and Applications. 1--5.

[32]

A. Johansson, D. Helbing, H. Z. Al-Abideen, and S. Al-Bosta. 2008. From crowd dynamics to crowd safety: A video-based analysis. Advances in Complex Systems, 11, 4 (2008), 497--527.

[33]

A. Johansson. 2008. Data-Driven Modeling of Pedestrian Crowds, PhD. thesis, Dresden University of Technology, Dresden.

[34]

A. Johansson, M. Batty, K. Hayashi, O. Al Bar, D. Marcozzi, and Z. A. Memish. 2012. Crowd and environmental management during mass gatherings. The Lancet Infect Diseases, 12, 2 (2012), 150--156.

[35]

P. Kachroo, S. J. AI-Nasur, S. A. Wadoo, and A. Shende. 2008. Pedestrian Dynamics: Feedback Control of Crowd Evacuation, Understanding Complex Systems. Springer, New York.

[36]

M. Kobes, I. Helsloot, B. de Vries, and J. G. Post. 2010. Building safety and human behaviour in fire: A literature review. Fire Safety Journal, 45 (2010), 1--11.

[37]

N. Koshak and A. Fouda (2008). Analyzing pedestrian movement in mataf using GPS and GIS to support space redesign. In The 9th International Conference on Design and Decision Support Systems in Architecture and Urban Planning.

[38]

J. Kou, S. Xiong, H. Liu, and X. Zong. 2011. Particle swarm and NSGA-II based evacuation simulation and multi-objective optimization. In Proceedings of the IEEE International Conference on Natural Computation. 1265--1269.

[39]

B. Krausz and C. Bauckhage. 2012. Love parade 2010: Automatic video analysis of a crowd disaster. Computer Vision and Image Understanding 116, 3 (2010), 307--319.

Digital Library

[40]

R. S. C. Lee and R. L. Hughes. 2005. Exploring trampling and crushing in a crowd. Journal of Transportation Engineering (ASCE) 131, 8 (2005), 575--582.

[41]

H. Lee and H. Tseng. 2014. A planning model for evacuation in building. World Academy of Science, Engineering and Technology, International Science Index 94, International Journal of Social, Management, Economics and Business Engineering 8, 10 (2014), 2937--2941.

[42]

L. Li, W. Huang, I. Y. H. Gu, R. Luo, and Q. Tian. 2008. An efficient sequential approach to tracking multiple objects through crowds for real-time intelligent CCTV systems. IEEE Transactions on SMC 38, 5 (2008), 1254--1269.

Digital Library

[43]

Q. Li, Z. Fang, and Q. Li. 2010. Multi-objective evacuation route assignment model based on genetic algorithm. In 2010 18th International Conference Geo Informatics.

[44]

S. Li, A. Zhan, X. Wu, P. Yang, and G. Chen. 2011. Efficient emergency rescue navigation with wireless sensor networks. Journal of Information Science and Engineering 27, 1 (2011), 51--64.

[45]

J. Li, S. Lee, and W. Liu. 2013. Emergency response plans optimization for unexpected environmental pollution incidents using an open space emergency evacuation model. Process Safety and Environmental Protection 91, 3 (2013), 213--220.

[46]

C. H. Lin, P. Y. Chen, and W. T. Chen. 2013. An adaptive guiding protocol for crowd evacuation based on wireless sensor networks. In 2013 IEEE 77th Vehicular Technology Conference (VTC Spring). 1--5.

[47]

S. M. Lo, M. Liu, R. K. K. Yuen, and P. H. Zhang. 2009. An artificial neural-network based predictive model for pre-evacuation human response in domestic building fire. Fire Technology 45, 4 (2009), 431--449.

[48]

R. V. Maneesha, S. Anjitha, and P. Rekha. 2012. A novel wireless sensor network architecture for crowd disaster mitigation, In 2012 8th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM). 1--4.

[49]

M. Marrón-Romera, J. C. García, M. A. Sotelo, D. Pizarro, M. Mazo, J. M. Cañas, C. Losada, and A. Marcos. 2010. Stereo vision tracking of multiple objects in complex indoor environments. Sensors 10 (2010), 8865--8887.

[50]

D. B. Matellini, A. D. Wall, I. D. Jenkinson, J. Wang, and R. Pritchard. 2013. Modelling dwelling fire development and occupant escape using Bayesian network. Reliability Engineering and System Safety 114 (2013), 75--91.

[51]

R. Mehran, A. Oyama, M. Shah. 2009. Abnormal crowd behavior detection using social force model. In Computer Vision and Pattern Recognition (CVPR). 935--942.

[52]

D. Merico and R. Bisiani. 2007. Indoor navigation with minimal infrastructure. In Proceedings of the 4th Workshop on Positioning, Navigation and Communication (WPNC’07). 141--144.

[53]

R. O. Mitchell, H. Rashid, F. Dawood, and A. Alkhalidi. 2013. Hajj crowd management and navigation system: People tracking and location based services via integrated mobile and RFID systems. In 2013 International Conference on Computer Applications Technology (ICCAT). 1--7.

[54]

S. A. Mohammadi, M. R. Feizi Derakhshi, and R. Akbari. 2012. An adaptive multi-objective artificial bee colony with crowding distance mechanism. In 16th CSI International Symposium on Artificial Intelligence and Signal Processing (AISP 2012). 68--73.

[55]

M. Mohandes. 2010. RFID-based systems for pilgrims identification and tracking. The Journal of Applied Computational Electromagnetic Society (ACES) 25, 3 (2010), 273--282.

[56]

Y. Mowafi, A. Zmily, D. E. D. I. Abou-Tair, and D. Abu-Saymeh. 2013. Tracking human mobility at mass gathering events using WISP. In 2013 2nd International Conference on Future Generation Communication Technology (FGCT). 157--162.

[57]

A. Mulloni, H. Seichter, and D. Schmalstieg. 2011. Handheld augmented reality indoor navigation with activity-based instructions. In Proceedings of the 13th International Conference on Human Computer Interaction with Mobile Devices and Services (Mobile HCI).

Digital Library

[58]

C. Nicholson and B. Roebuck. 1995. The investigation of the Hillsborough disaster by the health and safety executive. Safety Science 18, 4 (1995), 249--259.

[59]

E. O’Neill, V. Kostakos, T. Kindberg, A. Schiek, A. Penn, D. Fraser, and T. Jones. 2006. Instrumenting the city: Developing methods for observing and understanding the digital cityscape. Ubiquitous Computing, 315--332.

Digital Library

[60]

D. Oberhagemann, 2012. Static and Dynamic Crowd Densities at Major Public Events. Technical Report vfdb TB 13-01, German Fire Protection Association.

[61]

S. Park, J. W. van de Lindt, R. Gupta, and D. Cox. 2012. Method to determine the locations of tsunami vertical evacuation shelters. Natural Hazards 63, 2 (2012), 891--908.

[62]

M. Peng and L. M. Zhang. 2013. Dynamic decision making for dam-break emergency management—Part 1. Theoretical framework. Natural Hazards and Earth System Sciences 13 (2013), 425--437.

[63]

Z. Peng, L. Hong, and W. A. Lin. 2013. Evacuation motion simulation based on artificial bee colony algorithm. Computer Engineering 39, 7 (2013), 261--264.

[64]

M. Popescu, J. M. Keller, and A. Zare. 2013. A framework for computing crowd emotions using agent based modeling. In Proceedings of the 2013 IEEE Symposium on Computational Intelligence for Creativity and Affective Computing.

[65]

W. Qing Jun, and Z. Ru Bo. 2008. LPP-HOG: A new local image descriptor for fast human detection. In IEEE International Symposium on Knowledge Acquisition and Modeling Workshop, KAM Workshop.

[66]

F. X. Qiao, R. X. Ge, and L. Yu. 2009. Fuzzy evaluation of contra-flow evacuation plans in Texas medical center. Advances in Soft Computing 52 (2009), 250--259.

[67]

K. M. Rahman, T. Alam, and M. Chowdhury. 2012. Location based early disaster warning and evacuation system on mobile phones using open street map. In 2012 IEEE Conference on Open Systems (ICOS). 1--6.

[68]

J. Ramik. 2001. Soft Computing: Overview and Recent Developments in Fuzzy Optimization. Research Report, Graduate School of Knowledge Science, Japan Advanced Institute of Science and Technology.

[69]

K. K. Rao and G. S. Raju. 2011. An overview on soft computing techniques. Communications in Computer and Information Science 169 (2011), 9--23.

[70]

K. S. Ravi, Mohammed Abdul Aziz, and B. Venkata Ramana. 2012. Pilgrims tracking and identification using RFID technology. Advances In Electrical Engineering Systems (AEES) 1, 2 (2012), 96--105.

[71]

F. Samadzadegan, and M. Yadegari. 2010. A biologically-inspired optimization algorithm for urban evacuation planning in disaster management. In Proceedings of ACRS.

[72]

G. Santos and B. E. Aguirre. 2004. A critical review of emergency evacuation simulation models. In Building Occupant Movement During Fire Emergencies, Gaithersburg, Maryland.

[73]

P. Sarshar, J. Radianti, O. C. Granmo, and J. J Gonzalez. 2013a. A Bayesian network model for evacuation time analysis during a ship fire. In 2013 IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE). 100--107.

[74]

P. Sarshar, J. Radianti, and J. Gonzalez. 2013b. Modeling panic in ship fire evacuation using dynamic Bayesian network. In 2013 3rd International Conference on Innovative Computing Technology (INTECH). 301--307.

[75]

Y. Sato and Y. Osana, Y. 2012. Office layout plan evaluation system using evacuation simulation considering other agents’ action, In IEEE International Conference on Systems, Man, and Cybernetics Conference Proceedings. 1911--1916.

[76]

J. Seidler, K. Meyer, and L. M. Gillivray. 1976. Collecting data on crowds and rallies: A new method of stationary sampling. Social Forces 55 (1976), 507--519.

[77]

A. A. Shafie, M. I. Azhar, and M. M. Rashid. 2014. Smart objects identification system for robotic surveillance. International Journal of Automation and Computing 11, 1 (2014), 59--71.

Digital Library

[78]

S. Sharma and S. Lohgaonkar. 2010. Simulation of agent behavior in a goal finding application. In IEEE SoutheastCon 2010: Energizing Our Future. 424--427.

[79]

S. Sharma, S. Otunba, K. Ogunlana, and T. Tripathy. 2012. Intelligent agents in a goal finding application for homeland security. In 2012 Proceedings of IEEE SoutheastCon. 1--5.

[80]

Y. Shelke, V. Patil, S. Dasale, and R. S. Jagale. 2014. Crowd control system using IR transmitter and receiver. International Journal of Research in Engineering and Technology (IJRET) 3, 3 (2014), 424--428.

[81]

R. A. Smith. 1995. Density velocity and flow relationships for closely packed crowds. Safety Sciences 18 (1995), 321--327.

[82]

K. Still. 2000. Crowd Dynamics, Ph.D. thesis, University of Warwick, Warwick.

[83]

A. Soni, A. Sharma, P. Kumar, V. Verma, and S. Sutar. 2014. Early disaster warning and evacuation system on mobile phones using google street map. International Journal of Engineering and Technical Research 2, 4 (2014). 1--3.

[84]

F. Taher, K. Cheverst, M. Harding, and D. Fitton. 2009. Formative studies for dynamic wayfinding support with in building situated displays and mobile devices. In Proceedings of the 8th International Conference on Mobile and Ubiquitous Multimedia.

Digital Library

[85]

Q. A. Tan, G. H. Huang, C. Z. Wu, Y. P. Cai, and X. P. Yan. 2009. Development of an inexact fuzzy robust programming model for integrated evacuation management under uncertainty. Journal of Urban Planning and Development (ASCE) 135, 1 (2009), 39--49.

[86]

P. P. Varaiya. 1993. Smart cars on smart roads: Problems of control. IEEE Transactions on Automatic Control 38 (1993), 195--207.

[87]

M. Verma and M. K. Thakur. 2010. Architectural space planning using genetic algorithms. The 2nd International Conference on Computer and Automation Engineering (ICCAE) 2, 268--275.

[88]

M. Versichele, T. Neutens, M. Delafontaine, and N. V. de Weghe. 2012a. The use of bluetooth for analysing spatiotemporal dynamics of human movement at mass events: A case study of the Ghent festivities. Applied Geography 32, 2 (2012), 208--220.

[89]

M. Versichele, T. Neutens, M. Delafontaine, and N. V. de Weghe. 2012b. Mobile mapping of sporting event spectators using bluetooth sensors: Tour of Flanders 2011. Sensors 12, 10 (2012), 14196--14213.

[90]

S. Wan. 2014. Dynamic differential evolution for emergency evacuation optimization. Advances in Swarm Intelligence, Lecture Notes in Computer Science, Vol. 8795. Springer. 392--400.

[91]

C. Wang, C. Li, Y. Liu, J. Cui, and T. Zhang. 2011. Behavior-based simulation of real-time crowd evacuation. In 2011 12th International Conference on Computer-Aided Design and Computer Graphics (CAD/Graphics). 456--461.

Digital Library

[92]

C. Wei, Q. Meng, W. Zheng, Z. Sun, L. Zheng, and C. Wang. 2012. A research on human emergency evacuation based on revised ACO-CA. In 2012 20th International Conference on Geo Informatics (GEOINFORMATICS). 1--7.

[93]

J. Weppner and P. Lukowicz. 2013. Bluetooth based collaborative crowd density estimation with mobile phones. In 2013 IEEE International Conference on Pervasive Computing and Communications (PerCom). 193--200.

[94]

M. Wirz, T. Franke, D. Roggen, E. Mitleton-Kelly, P. Lukowicz, and G. Troster. 2012. Inferring crowd conditions from pedestrians’ location traces for real-time crowd monitoring during city-scale mass gatherings. In 2012 IEEE 21st International Workshop on Enabling Technologies: Infrastructure for Collaborative Enterprises (WETICE). 367--372.

Digital Library

[95]

M. Wirz, T. Franke, D. Roggen, E. Mitleton-Kelly, P. Lukowicz, and G. Troster. 2013. Probing crowd density through smartphones in city-scale mass gatherings. EPJ Data Science 2, 1 (2013), 5.

[96]

X. Wu, G. Liang, K. K. Lee, and Y. Xu. 2009. Crowd density estimation using texture analysis and learning, Bulletin of Advanced Technology Research 3, 5 (2009), 35--41.

[97]

L. Xi, W. Hu, C. Shen, Z. Zhang, A. Dick, and A. van den Hengel. 2013. A survey of appearance models in visual object tracking. ACM Transactions on Intelligent Systems and Technology 4, 4, Article 58 (September 2013), 48 pages.

Digital Library

[98]

J. Xie, J. P. He, and Y. Zhang. 2006. Fuzzy synthesis assessment analysis of safety evacuation in subway station fire. Progress in Safety Science and Technology, 6 (2006).

[99]

M. Yamin, M. Mohammadian, X. Huang, and D. Sharma. 2008. RFID technology and crowded event management. In 2008 International Conference on Computational Intelligence for Modelling Control Automation. 1293--1297.

Digital Library

[100]

M. Yamin and Y. Ades. 2009. Crowd management with RFID and wireless technologies. In 1st International Conference on Networks and Communications (NETCOM’09). 439--442.

Digital Library

[101]

Z. Yu, L. Capra, O. Wolfson, and H. Yang. 2014. Urban computing: Concepts, methodologies, and applications. ACM Transactions on Intelligent Systems and Technology 5, 3, Article 38 (September 2014), 55 pages.

Digital Library

[102]

J. K. K. Yuen, E. W. M. Lee, and W. W. H. Lam. 2014. An intelligence-based route choice model for pedestrian flow in a transportation station. Applied Soft Computing 24 (2014), 31--39.

Digital Library

[103]

M. Yusoff, J. Ariffin, and A. Mohamed. 2011. A multi-valued discrete particle swarm optimization for the evacuation vehicle routing problem. Advances in Swarm Intelligence, Lecture Notes in Computer Science, Vol. 6728, Springer, 182--193.

Digital Library

[104]

Z. Zainuddin and L. E. Aik. 2012. Intelligent exit-selection behaviors during a room evacuation. Chinese Physics Letters 29, 1 (2012), 018901.

[105]

B. Zhan, D. N. Monekosso, P. Remagnino, S. A. Velastin, and L. Q. Xu. 2008. Crowd analysis: A survey. Machine Vision and Applications 19, 5/6 (2008), 345--357.

Digital Library

[106]

Q. Zhang, T. Chen, and X. Zhi. 2014. New framework of intelligent evacuation system of buildings. Procedia Engineering 71 (2014), 397--402.

[107]

Y. Zhao, M. Yuan, G. Su, and T. Chen. 2015. Crowd security detection based on entropy model. In Proceedings of the ISCRAM 2015 Conference.

[108]

V. W. Zheng, Y. Zheng, X. Xie, and Q. Yang. 2010. Collaborative location and activity recommendations with GPS history data. In Proceedings of the 19th International Conference on World Wide Web. ACM, New York, 1029--1038.

Digital Library

[109]

X. Zheng and M. Liu. 2010. Forecasting model for pedestrian distribution under emergency evacuation. Reliability Engineering & System Safety 95, 11 (2010), 1186--1192.

[110]

Y. J. Zheng, H. F. Ling, J. Y. Xue, and S. Y. Chen. 2014. Population classification in fire evacuation: A multiobjective particle swarm optimization approach. IEEE Transactions on Evolutionary Computation 18, 1 (2014), 70--81.

[111]

X. Zheng, T. Zhong, and M. Liu. 2009. Modeling crowd evacuation of a building based on seven methodological approaches. Building and Environment 44, 3 (2009), 437--445.

[112]

S. Zhou, D. Chen, W. Cai, L. Luo, M. Y. H. Low, F. Tian, V. S. H. Tay, D. W. S. Ong, and B. D. Hamilton. 2010. Crowd modeling and simulation technologies. ACM Transactions on Modeling and Computer Simulation 20 (2010), 1--35.

Digital Library

[113]

B. Zhu, T. Liu, and Y. C. Tang. 2008. Research on pedestrian evacuation simulation based on fuzzy logic. In 9th International Conference on Computer-Aided Industrial Design and Conceptual Design.

[114]

X. Zong, S. Xiong, Z. Fang, and Q. Li. 2010. Multi-ant colony system for evacuation routing problem with mixed traffic flow. In IEEE Congress on Evolutionary Computation (CEC). 1--6.

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Index Terms

Intelligent Evacuation Management Systems: A Review
1. Computing methodologies
  1. Artificial intelligence
2. General and reference
  1. Document types
    1. Surveys and overviews

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cover image ACM Transactions on Intelligent Systems and Technology

ACM Transactions on Intelligent Systems and Technology Volume 7, Issue 3

Regular Papers, Survey Papers and Special Issue on Recommender System Benchmarks

April 2016

472 pages

ISSN:2157-6904

EISSN:2157-6912

DOI:10.1145/2885506

Editor:
Yu Zheng
Microsoft Research, China

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Publication History

Published: 01 February 2016

Accepted: 01 October 2015

Revised: 01 September 2015

Received: 01 May 2015

Published in TIST Volume 7, Issue 3

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Kotkova EMatveev A(2024)FRAMEWORK OF THE INTELLIGENT EVACUATION CONTROL SYSTEMScientific and analytical journal «Vestnik Saint-Petersburg university of State fire service of EMERCOM of Russia»10.61260/2218-130X-2024-2-62-692024:2(62-69)Online publication date: 14-Jul-2024
https://doi.org/10.61260/2218-130X-2024-2-62-69
Ma YGelenbe ELiu K(2024)Impact of IoT System Imperfections and Passenger Errors on Cruise Ship Evacuation DelaySensors10.3390/s2406185024:6(1850)Online publication date: 13-Mar-2024
https://doi.org/10.3390/s24061850
Milasi SBenar NNazarian AShahzad M(2024)Unlocking the potential: A comprehensive meta-synthesis of Internet of Things in the sports industryProceedings of the Institution of Mechanical Engineers, Part P: Journal of Sports Engineering and Technology10.1177/17543371241229521Online publication date: 11-Feb-2024
https://doi.org/10.1177/17543371241229521
Gavidia-Calderon CKordoni ABennaceur ALevine MNuseibeh B(2024)The IDEA of Us: An Identity-Aware Architecture for Autonomous SystemsACM Transactions on Software Engineering and Methodology10.1145/365443933:6(1-38)Online publication date: 28-Jun-2024
https://dl.acm.org/doi/10.1145/3654439
Huang ZFang ZYe RChraibi M(2024)A Matrix Translation Model for Evacuation Path OptimizationIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.331251925:2(1374-1383)Online publication date: 1-Feb-2024
https://dl.acm.org/doi/10.1109/TITS.2023.3312519
Le TTran HBouzefrane S(2024)iTEVAC: an enhanced trusted evacuation system leveraging fog computing and IoTJournal of Information and Telecommunication10.1080/24751839.2024.2306787(1-35)Online publication date: 23-Jan-2024
https://doi.org/10.1080/24751839.2024.2306787
Dong FZhong QLiao YHirota KChen K(2024)Dynamic job shop scheduling performance evaluation based on green intelligent manufacturing and thermal efficiency improvementThermal Science and Engineering Progress10.1016/j.tsep.2024.10278553(102785)Online publication date: Aug-2024
https://doi.org/10.1016/j.tsep.2024.102785
Bhardwaj RBhargava AKumar V(2024)INFED: Enhancing fire evacuation dynamics through 3D congestion-aware indoor navigation frameworkSimulation Modelling Practice and Theory10.1016/j.simpat.2024.103010136(103010)Online publication date: Nov-2024
https://doi.org/10.1016/j.simpat.2024.103010
Li YLi CGuo CHuo F(2024)Dynamic coupling model of FDS and cellular automata considering trampling behaviorPhysica A: Statistical Mechanics and its Applications10.1016/j.physa.2023.129369633(129369)Online publication date: Jan-2024
https://doi.org/10.1016/j.physa.2023.129369
Li CHuo FZhou TWang DLi YJiang C(2024)Multifactor dynamic coupled model for building fire evacuation: Case study of the Karamay Friendship Palace fireJournal of Building Engineering10.1016/j.jobe.2024.110079(110079)Online publication date: Jun-2024
https://doi.org/10.1016/j.jobe.2024.110079
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