an expert crowd monitoring and management framework for hajjlutful.karim/c6-08238202.pdf · 2020....

An Expert Crowd Monitoring and Management Framework for Hajj

Nidal Nasser1, Muhammad Anan1, Mohammad Faiz Chikh Awad2, Hesham Bin-Abbas3, Lutful Karim4

1Software Engineering Department, Alfaisal University-Riyadh, Saudi Arabia, {nnasser, manan}@alfaisal.edu

2King Saud University-Riyadh, Saudi Arabia, [email protected] 3Hesham Bin-Abbas, Institute of Innovation and Industrial Development, King Abdulaziz City for Science and Technology

Riyadh, Saudi Arabia, [email protected] 4School of ICT, Seneca College of Applied Arts and Technology, Toronto, Canada, [email protected]

Abstract— Hajj is a ritual practice where millions of pilgrims arrive in a limited area and required to transfer through dedicated paths to several locations. Congestions and overcrowded have been one of the biggest challenges to the authorities, and hence, encourages researchers to proposed practical solutions to preventing congestions and their consequences from happening. In this paper, we propose an Expert Crowd Monitoring and Management Framework as a substitution to the current manual crowd monitoring and management system. The framework was designed to be proactive in predicting potential problems accurately by utilizing smart monitoring of each path of rituals locations’ paths. The framework consists of Pilgrim Sensor Units, Data Collection Units, Database Unit, Expert Crowd Monitoring and Management Unit, Dashboard Units and Notification Unit.

Keywords—Crowd Management; Internet of Things; RFID; Wireless Sensor Networking.

I. INTRODUCTION Hajj is perceived as an event-timing of certain rituals. Two

to three million pilgrims, from various parts of the world, come to Mecca to perform Hajj in 4-5 days every year requiring them to tour across several locations in Mecca. Each of the rituals’ locations has a set of paths to reach. Rules of Hajj’s plan determine the capacity of each path and who should pass on it. Even so, the Hajj authorities face difficulties in executing the plan that are reflected by their consequences, i.e. tragedies such as what happened in September 2015 (Hajj 1436). The widely used (Information and Communication Technology) ICTs such as e-bracelet, smartphones, RFID, WSN and Wi-Fi have attracted researchers to develop solutions for Hajj crowd monitoring and management. Existing solutions have dealt with easing issues of performing Hajj’s rituals such as offering Location-Based Services (LBSs), they are reactive with what could happen and have not been applied to large area case studies. In this paper, we propose an Expert Crowd Monitoring and Management Framework as a substitution to the current manual crowd monitoring and management system. The framework was designed to deal with the most complicated ritual – symbolic stoning, and to be proactive in predicting potential problems accurately by utilizing smart monitoring of each path of rituals locations’ paths. Dealing with the problems early will help in preventing congestions and their consequences from happening. The framework consists of Pilgrim Sensor Units, Data Collection Units, Database Unit, Expert Crowd

Monitoring and Management Unit, Dashboard Units and Notification Unit.

II. LITERATURE REVIEW The widely used ICTs such as e-bracelet, smartphones,

RFID, WSN and Wi-Fi have attracted researchers to develop solutions for Hajj crowd monitoring and management. Existing solutions have dealt with easing issues of performing Hajj’s rituals such as offering LBSs. They are reactive with what happen and have not been applied to large area case studies.

Today mobile smartphones come with built in technologies for LBSs. GPS, AGPS, Wi-Fi cards and digital compass are common devices present in today’s smartphones. LBSs technologies on the smartphones work together in finding exact positions. The GPS on the phone is used to determine the location of the phone and the Wi-Fi or mobile cell phone towers (Cell ID) are used to decrease the search time for the nearest GPS satellite. Today’s smartphone comes with context or location aware mobile software applications that utilize LBSs. These software applications have been developed specifically to use the geographical location of the phone to provide various services and facilities. Some of these services include map navigation, locating nearby restaurants and locating friends [13].

RFID is a technology used for automatic identification. RFID is a generic term for technologies that use radio waves to automatically identify entities, either live or inanimate. The objects are identified by a unique identifier or by more complex ways such as manufacturing history, temperature, or age. RFID systems consist of four main elements – the RFID tags or transponders, RFID readers, antennas and radio characteristics and a computer network used to connect the readers. The tag is the basic component of the system. Tags can be active, which can have a battery or passive (i.e., manual), which means the system is completely powered by the incoming RF signal transmitted by using the electromagnetic wave. The readers send RF signals to the tags and listen for responses. The antennas and radios are used to connect the reader and tag so that information can be transferred. The reader then sends information back to a computer which can use it for the task at hand. RFID tags can be read as long as they are within the range of a reader.

Wireless Sensor Networks (WSN) usually consists of large number of very cheap and tiny devices that allow establishing an

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efficient wireless network that could sense, process and transmit data about the surroundings. With these features, WSN is ready to use technology that could help achieve optimum solutions for many problems related to monitoring and managing crowds in Hajj in addition to many other services [8]. Energy consumption of sensors nodes should be optimum, so reaching that drives the design process of WSN.

The widely used ICTs for tackling Hajj crowd monitoring and management have advantages and limitations. The advantages encourage developing solutions of supporting Hajj management; while limitations [23, 8, 14] reflected on their natures, such as energy cost, distance, bandwidth, rate, etc., determine what kinds of applications we can develop. Even RFID technologies in religious events such as Hajj are still inadequate in outdoor system applications [14]; they are adopted widely in the solutions proposed for effective management of Hajj events [23, 13, 8, 2, 14, 9, 21, 22, 18, 11, 19]. Mobile technologies with the GPS present applications work well outdoors provided that there is a transparent sky for GPS receivers to work correctly, but the satellite signals are blocked or unreliable inside buildings. In addition, crowd sensing through mobile devices [1, 21, 22, 17, 16] and using social network data [1] to develop applications for guiding pilgrims suffering from overcrowd situations cannot be adopted since not all the pilgrims carry mobile devices and who carry maybe not aware enough to use the applications installed on them. In addition, it is impossible at crowd places to recharge the devices’ batteries. Even though there have been several methods proposed for tracking persons in video using image processing techniques, only few solutions work in real time [6]. The solutions are not adopted widely for effective Hajj management.

To the best of our knowledge, existing management of Hajj event does utilize ICT solutions to manage pilgrims moving between places of Hajj rituals particularly between Mina’s tents and Jamarat (Figure 1). Crowds cannot be avoided in Hajj but overcrowd can be.

Existing solutions [23, 13, 2, 14, 1, 3, 9, 21, 22, 12, 18, 11, 17, 19, 15, 7, 6, 24, 16] have converged on dealing with problems resulting from crowd or overcrowd. They are based on modeling pilgrim’s location and aspects related to the location, tracking to identify missing pilgrims and monitoring sick pilgrims, aged pilgrims and the ones with disabilities, and to offer the required services. These solutions are reactive solutions in nature. Furthermore, scalability, security, availability and reliability should be considered in evaluation of any solution for effective management of Hajj event, which are not estimated clearly in existing solutions.

While the solutions of crowd density estimating [14, 20, 4], intelligent agents [12] and ambient intelligence [10] are promoting developing proactive solutions, which can predict if overcrowd is going to happen and how to guide pilgrims facing difficulties. The solutions of intelligent agents are able to adapt and show rational behavior to recognize the environment and to do action. The solutions of ambient intelligence depend on using ways of influencing and modifying the behavior of individuals in crowds, which is primarily used for purposes of monitoring and early detection of crowd-related emergencies.

Fig. 1. Pilgrims moving towards Jamarat

III. RESEARCH METHODOLIGY In this paper, our aim is to design a proposed framework for

crowd monitoring and management, which would have two stages:

• Stage I – Perceiving and modeling the problem

• Stage II – Designing the proposed framework

A. Stage I – Perceiving and modeling the problem In our project we’re focusing on monitoring and managing

each of the paths leading to ritual locations in Mina area. For example, there are five main paths to reach the symbolic stoning location that are depicted in Figures 2-6.

Fig. 2. Ground floor of Jamarat

Fig. 3. First floor of Jamarat


Fig. 4. Second floor of Jamarat

Fig. 5. Third floor of Jamarat

Fig. 6. Fourth floor of Jamarat

The problem can be perceived as a discrete event dynamic system where system entities include ritual paths modeled as queues, discrete-state, event-driven system of which the state evolution depends entirely on the occurrence of asynchronous discrete events over time.

Modeling the problem has two steps:

1. Numbering the paths of each Hajj’s ritual location: for the location of Symbolic stoning ritual paths numbering is depicted in the Figures 7 to 11:

Fig. 7. Numbering the paths of reaching symbolic stoning ritual location via floor 0






2. Constructing the graphical models of the paths of each ritual location within Mina area. For the location of symbolic stoning ritual, the graphical models of its paths are depicted in the Figures 12 to 16.

B. Stage II – Designing the proposed framework: The target of the framework design is to substitute the

framework for existing human power of crowd monitoring and management. Figure 17 shows that the framework consists of Pilgrim Sensor Units, Data Collection Units, Database Unit, Expert Crowd Monitoring and Management Unit, Dashboard Units and Notification Unit.

The Pilgrim Sensor Units are responsible for identifying pilgrim’s information such as personal info, health status and position.

The Data Collection Units are responsible for activating pilgrim sensor units and reading data at the entrance and exit locations of each path leading to a ritual location during the period of performing the ritual.

The Database Unit is responsible for storing the data collected by the Data Collection Units and the data resulting from running the Expert Crowd Monitoring and Management Unit. In addition, it stores the status of Data Collection Units (i.e., active or inactive), Dashboard Units and Notification Unit.

The Expert Crowd Monitoring and Management Unit is responsible for representing the graphical models of rituals’ locations paths in a knowledgebase, instant monitoring of paths’ crowds, determining proactively performance estimation and status of individual rituals locations’ paths, interpreting the statuses and performance estimation of each ritual location’s paths and takes suitable crowd management decisions based on the Hajj’s plan rules regarding regimenting process. The Dashboard Unit graphically displays the array of performance estimation of the path. In the case of receiving path warning status, the unit will send a notification message to the Notification Unit to close the path or paths leading to the affected path and direct the regiments who approaching them to other less crowding paths. For example, if the path 45i-45o “warning” status was sent to the Expert Management and Monitoring Unit, it would send a notification message to the Notification Unit to close the paths 4i-4o and 5i-5o. Similarly, in the case of 3.45i-3.45o, if its status was “warning” the paths 3i-3o, 4i-4o and 5i-5o would be closed. In the case of closing a path, redirecting the regiments who are approaching it according to their regimenting schedules is the responsibility of the

assigned taskforce after receiving necessary notifications from the monitoring system.

The Dashboard Units are responsible for displaying paths’ performance estimation arrays.

The Notification Unit is responsible for dealing with warning status messages and other emergencies messages regarding monitoring aged and sick pilgrims.

Fig. 17. The proposed framework

Other Hajj Authorities

Pilgrim Sensor Unit

Data Collection Unit

Database Unit

Expert Crowd monitoring and Management Unit

Dashboard Unit

Notification Unit

Medical Care Center

Civil Defense


Fig. 12. A graphical model of the paths of reaching symbolic stoning ritual location via floor 0





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IV. RESULTS AND DISCUSSIONS

The performance of the proposed crowd monitoring and management framework was evaluated using three different scheduling mechanisms and based on the example in Fig. 16. The applied scheduling mechanisms are: First In First Out (FIFO), Strict Priority Queuing, Weighted Round Robin (WRR). Traffic arrival was based on Markov arrivals to the paths and fixed processing rate.

Fig. 17. Modeling pilgrims paths as queueing systems based on the model in Fig 16

The implemented system is composed of two major parts. The first part generates an exponentially distributed random number. The second part processes arriving traffic (pilgrims) from multiple paths and makes all required calculations. Calculations for response time is performed separately and tracking information is used for each source individually to track number of pilgrims arrived from each path, which gives an indication about the waiting time of pilgrims.

We assume that each path has a maximum capacity of 2500 pilgrims per minute. When the arrival rates of pilgrims are within acceptable ranges, then the path should be able to process arriving pilgrims as they come and any one waiting to be processed without having any overloaded or congestion scenarios. This means that the path fill will fluctuate as shown in Fig. 18.

For M/D/1 queue, if the load on the queue is greater than one ( ρ >1), then more pilgrims will be arriving than what can be processed which causes overloading to occur.

For arrival rate of 2000 pilgrims per minute, 8.0)104.0(2000 3 =××== −Mλρ which is in the

acceptable range, where λ represents the arrival rate and M represents the processing rate. In other words, the path will not be congested or overloaded as long as future paths are processing pilgrims without any delay

25002000)104.0/(12000/1 3

Fig. 21. Average response time for FIFO, Priority and WRR queueing systems using variable arrival rate and based proactive monitoring

approach

In Fig. 21, the average response time is shown for FIFO, Priority and WRR queueing systems using variable arrival rate and based on the proactive monitoring approach. The response time in FIFO and priority queueing is higher than the one using WRR because they both will be holding people for most of the time. As arrival rate gets higher, the response time for Priority and FIFO gets much higher, but with WRR it becomes almost constant because it guarantees its share all the time. The WRR outperforms the FIFO and the Priority at higher rates since proactive monitoring will help in dynamically lowering the arrival rates, which causes the time between successive arrivals to be bigger. The proposed system adopted the WRR scheduling approach since it efficiently utilizes the available capacity within the output path and minimizes the average response time.

V. CONCLUSION In this paper, we proposed an Expert Crowd

Monitoring and Management Framework for Hajj. The framework was designed to be proactive in predicting potential problems accurately by utilizing smart monitoring of rituals locations’ paths. An important part of this study aimed to examine the relative performance that different traffic sources will receive when traffic from different sources mixes together at joint paths. This will help in implementing the most appropriate mechanism at each ritual location’s paths and take suitable crowd management decisions based on the Hajj’s plan rules regarding regimenting process. The performance of the proposed crowd monitoring and management framework was evaluated using three different scheduling mechanisms: FIFO, Priority Queuing, and WRR. It was found that the WRR with proactive monitoring outperformed other approaches since it will help in dynamically lowering the arrival rates, which causes the time between successive arrivals to be bigger. The

proposed proactive monitoring and management system is very essential in predicting potential problems accurately by utilizing smart monitoring of each path of rituals locations’ paths.

VI. ACKNOWLEDGMENT Authors would like to thank King Abdulaziz City for

Science and Technology for funding and supporting this work through the research grant 452-34-ات .

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