International Journal of Technology Management and Information System (IJTMIS) eISSN: 2710-6268 [Vol. 1 No. 2 December 2019]
Journal website: http://myjms.mohe.gov.my/index.php/ijtmis
DEVELOPING SMART QUEUING (SMARTQ) APPLICATION USING GEOFENCING
Aminuddin Abdul Basir1, Nurul Najwa Abdul Rashid2*, Syafnidar Abdul Halim3 and Alya Geogiana Buja4
1 2 3 4 Faculty of Computer and Mathematical Sciences, University Teknologi MARA, MALAYSIA
*Corresponding author: [email protected]
Article Information:
Article history:
Received date : 12 October 2019 Revised date : 23 November 2019 Accepted date : 6 December 2019 Published date : 16 December 2019 To cite this document:
Abdul Basir, A., Abdul Rashid, N., Abdul Halim, S., & Buja, A. (2019).
DEVELOPING SMART QUEUING (SMARTQ) APPLICATION USING GEOFENCING. International Journal Of Technology Management And Information System, 1(2), 10-19.
Abstract: Queuing can be cumbersome, tedious, and sometimes unsystematic which is inefficient and causes people leave or not join the queue to begin with. A survey has been conducted at two public organizations to determine time taken for user to complete their queue and to observe the current queuing system available at most premises. Most premises or organizations use ticket-based queuing system where user have to predict the status of the queue themselves and have to come to the premises to join queue without proper planning. The problems with current queuing system are fatigue, wasted waiting time, and inadequate information about the current situation of the queue. With the increasing use of mobile phone and internet accessibility, mobile queuing can be implemented where user can take part in the queue via mobile device without them to come to the premises. Hence, development of SmartQ which is a queue management mobile application with geo-fencing feature can tackle this issue by implementing the mobile queuing for two organization2. This mobile application also supports multi-organization queue. This mobile application also aids user to get information about the current status of queue at the organization such as number of people in queue and estimated waiting time. The geo-fence feature helps the organization to limit number of users that can join queue within certain range from the premise. Geo-
1. Introduction
Queue can be defined as a line or sequence of people or vehicles awaiting their turn to be attended to or to proceed, while queuing means take one’s place in a queue (Hyun Lee, 2017). In daily activities, queuing always occurred whenever people have interest in mutual service at a same particular period and there are limited capabilities to satisfy or provide service to all the interested individual at once. For example, a queue of people at ticket windows or vehicles waiting in line at the toll. The reason for queuing is to accomplish or get the service intended in a fair and organized manner. Queue management system is used to control queues which add ability to manage and streamline queues in order to reduce waiting periods and improve service efficiency (Hyun Lee, 2017). Queuing management systems are critical components in any sector of business (Carvalho
& Belo, 2016). It is important for the service provider to provide efficient queuing system to maintain high customer satisfaction. Besides, queue management system can help record, predict, and calculate the statistic of the queuing pattern such as customers’ arrival rate, queuing behavioral over time, and average waiting time which can help in decision making. Queuing systems, even smart ones, whereby a client gets a digital ticket from a machine or online and waits for a turn, face many limitations in terms of creating an improved user experience (Ghazal, Hamouda, & Ali, 2015).
Morgan Stanley Research estimated more people would access the Internet through mobile devices than desktop devices after 2014 which change of consumer behavior puts a spotlight on mobile distribution channels, which are defined as mobile device-based logistics that allow the company to communicate and engage with customers in an interactive and relevant manner (Qin, Tang, Jang, & Lehto, 2017). The number of smartphone users is expected to continuously grow with 5.5 billion people expected to be using smartphone devices by 2022 (McLean, Al-Nabhani, & Wilson, 2018). Mobile applications and smartphones enable the company to provide information and services at the time and place needed (Qin et al., 2017). The rapid advancement of mobile technology and the subsequent service innovation deriving from it is causing consumer behavior to evolve in terms of how consumers interact and utilize service delivery channels that are accessible to consumers anytime, anywhere (McLean et al., 2018). Smartphone brings mobile computing to the next level which increase productivity and accessibility.
user from take part in the queue given their location. In the future, this mobile application can be improved by including more organizations and allowing users to join queue from multiple organizations from different locations.
Keywords: geofencing, mobile application, queuing system.
The sensors built into the smartphone as well as its portability and programmability have made it a device with almost limitless applications. Geographical position turns out to be the most relevant environmental feature for context-aware applications which gave rise to a particular offspring of context-aware systems, commonly known as location-based services (LBS) that take the user’s position into consideration to tailor its application-specific service to the needs of the user at given whereabouts (Garzon, Arbuzin, & Kupper, 2017). The geo-fencing technique can be used to filter the customers which only customer within certain range can acquire the service provided. Hence, due to the high smartphone usage and the high waiting time of current queuing management system. Queue management mobile application with geo-fencing technique can be implemented to improvise the current queuing system which bring mobility and help to manage queue by reducing waiting time.
2. Problem Statement
Queuing to get a service become major things due to the expenditure of the service and the growing number of client or customer intended for the service. Thus, it is quite challenging to reduce waiting time, maintain high customer satisfaction, and provide high quality service. The main reason to manage the queue is to provide efficient service to the customer in a fair manner. From the user side of view, it is essential and in nature to their desire to acquire and complete the intended service as fast as possible. User always prefer service provider that bring ease to their customer and provide good customer service experience that bring appeal to them.
Unfortunately, physical queue such as crowd barriers or stanchions although prevent queue jumping quite well, it is not efficient to the large number of customers and service with high service completion time which can cause fatigue and emotionally degrade customer service. Putting your visitors inside a labyrinth of rope barriers also has adverse effect on their psychological state (Kirill Tšernov, 2017). Meanwhile, the current kiosk-based queues did not manage large crowd quite well due to the high average waiting time which cause some patron to abandon the queue. Although kiosk-based queue doesn’t require patron to be exactly physically in the queue, it still require the patron to be in the waiting area without abilities to manage the position in the queue.
Once patron missed their position in the queue, they need to start over. Furthermore, ticket queuing is a non-personal way of interaction between a customer and a business (Hyun Lee, 2017). These problems require new solution in the queue management system that can boost the efficiency of the system. With the growing number of smartphone users, and high capabilities of networking, mobile queue management can be implemented via smartphone app which can increase the rate of accessibilities that allow user to be in the queue virtually anywhere and anytime. It is also possible to bring additional features to the system that can improve customer experience in getting the service such as live monitoring and remote queuing via geo-fencing technique to securing position in the queue and filter customer by only allowing customer in certain range or location to access the service. By keep the customer informed customer can fill in the waiting period with other activities for more quality time. Thus, queue management mobile application can improvise the
3. Literature Review
Queue management system is a technique of managing waiting line or crowd intended for a service in ordered manner (Hyun Lee, 2017) where the crowd or waiting line occurred is due to the increasing demand exceeding the supply that can be provided by service provider (Carvalho &
Belo, 2016; Ghazal et al., 2015), and because of high completion time (Liang, 2013). The main reason for the queue management system is to minimize waiting time (Carvalho & Belo, 2016;
Klimek, 2017), provide high quality service (Carvalho & Belo, 2016; Liang, 2013), and maintaining high customer satisfactory level (Carvalho & Belo, 2016) which is essential especially to the private sector (Ghazal et al., 2015).
There are numbers of method available as a solution for managing the queue such as physical barrier like stanchions (Hyun Lee, 2017; Klimek, 2017), kiosk based ticketing system (Ghazal et al., 2015; Hyun Lee, 2017), and mobile queuing (Ghazal et al., 2015) where user be able to queue virtually via mobile device. Despite from various technique of managing the queue, it brings equal purpose which help to manage the crowd. According to Hyun Lee (2017) each solution has their advantages and disadvantages over the other where the business model determined the effectiveness of each solution. Table 1 below shows typical type of current queue management system and issue for each system.
Table 1: Type of Queue Management System Type of queue
management system
Technique Issue
Physical management Stanchions or belt barrier is used to create queuing line where customer need to follow
to obtain service and prevent from queue jumping.
Cause fatigue to the patron where they have to physically queue to
obtain service.
Sign-in sheet Either electronically or by using paper, patron will fill in sign-in sheet template with required information before acquiring
service.
Quite cumbersome and slow. No protection or privacy to the patron’s private information.
Ticket-based management
Visitor need to take ticket that represent the position in the queue and wait to be called
in the waiting area.
The ticket may got damage and there will be less interaction with
the customers.
Digital management Allow user to take number or fill in information by themselves by using digital
device such as smartphones.
Relatively expensive and quite new technology which the user
and staff need to adapt.
Human management Can be any type of queue management system but with human assistant involve to
improve the system.
Customer must be treated as infinite where the personal server must be treated as infinite as well which is costly to this kind of
system
The SmartQ mobile application falls under the digital management category where the user will take position in queue and specify type of service required via mobile device. The main advantage of mobile queuing is people always bring their mobile device together (Li, Han, Cheng, & Sun, 2014) hence allowing people to take part into the queue with ease despite of their location.
Queuing model or queuing system compose of a few major components such as input source, queuing process, queue discipline, service mechanism (Hillier, 2015) and phase (Hyun Lee, 2017).
The operation of the model work by the assumption of customer generated by input source over time, customer join queuing process if service cannot be acquired instantly, queue discipline model such as single channel single phase, single channel multiple phase, multiple channel single phase, and multiple channel multiple phase (Hyun Lee, 2017). Figure 1 shows the flow of basic single channel single phase queuing model or queuing system.
Input source or calling population can be explain as the number of customers that interested in the service in randomly pattern of arrival time (Hillier, 2015) where Poisson distribution is used to simulate the arrival intensity of customer (Meng et al., 2017). Queuing system or queue management system consist of queuing process, service discipline, and service mechanism. Queue is a process where customer from the input source wait before acquiring service (Hillier, 2015).
Service mechanism also known as server is where the service can be acquired by the customer (Hillier, 2015). Waiting time can be reduced by using multiple server configuration, but system cost will be increase as well (Meng et al., 2017). There are various of service discipline can be applied to the queuing model such as first-come-first-served, last-in first-out, or priority discipline in which these disciplines determined the selection of customer from the queue to acquire service in service mechanism (Hillier, 2015).
Figure 1: Queue Model
Location Based Service (LBS) is a service that use the user’s location via wireless application (Mohsen, Tao, Li, & Gao, 2017; Raflesia, Lestarini, Taufiqurrahman, & Firdaus, 2017) to accomplish and provide various service to the user (Raflesia et al., 2017). LBS consist of two type of services which is push and pull where push service is accomplished without user request while the pull service require the user to request the service to obtain information (Raflesia et al., 2017).
Geo-fencing technology is a part of LBS implemented in mobile device where a virtual region is established to trigger action when user entering or leaving the region (Garzon, Elbehery, Deva, &
Kupper, 2016; Raflesia et al., 2017) where user’s current position can be retrieved by using Global Positioning System (GPS) (Mohsen et al., 2017; Passarella et al., 2017) embedded in user’s smartphones (Khan & Shahzad, 2016). GPS use satellite to determine position which consist of two-dimension operation and three-dimension operation where latitude and longitude can be determined by using two-dimension operation while three-dimension operation be able to determine latitude, longitude, and elevation (Rafter, Anvari, & Box, 2017). There are circular geo- fencing and polygonal geo-fencing in which only circular geo-fencing is supported by Android API (Helmy & Helmy, 2017). The geo-fencing can be set up according to developer’s requirement where the latitude, longitude, radius, duration, and type of transition can be specified (Google Inc, 2017).
In this SmartQ mobile application, the geo-fencing technology has two purposes. First, it establishes barrier that allow only users within the geo-fenced area can enter the queue. The second purpose is to trigger the server when an active user entering the premises as a notification to the server that the user has arrived to update the position of user in the queuing system if necessary.
4. Application Development
In this SmartQ system, a smartphone will interact with the server via an internet connection.
Database is used to store data while the server is responsible for data processing while GPS will use satellite to determine the user’s location. The smart queuing mobile application used geo-fence technology to create a boundary. Only user within the geo-fence area is allowed to get a queuing number. The mobile application was connected to the server via REST API where request to server will be sent through HTTP request and the server will response back in form of JSON. Android application will consume the JSON and retrieve necessary data.
The user will request and retrieve data via HTTP request and JSON. Whenever user login, register, view service, join queue, monitor queue, or cancel queue, the data will be requested and passed to the table in the database accordingly. Figure 2 shows the system architecture of the developing SmartQ application.
5. Results and Discussion
A functionality test has been conducted to ensure all the functionalities are work well as expected.
The test was conducted at UiTM Melaka Kampus Jasin area and focusing on the accuracy of geofencing feature of the SmartQ mobile application. In this testing, geofence area being set within 200 meters of radius centered at coordinate 2.228422, 102.455306. By
Figure 2: SmartQ System Architecture
Figure 3: SmartQ Mobile Application with Plotted Geo-Fence Area
using integrated GPS of the mobile phone, the location of user can be retrieved and can be compared to the geo-fenced area to trigger the mobile phone whether to allow the user to take part in the queue or not. When user is located outside the geo-fence area, the button to join the queue as shown in figure 3 will be disabled. The button will be enabled if the user was located inside the geo-fence area and allowing the user to take part in the queue.
This test is repeated 2 times to prove the accuracy and reliability of this feature. Two movement which replicate user entering and exiting the geo-fenced area are recorded. For each movement, there will be six different distances location from the center coordinate of the geo-fence area. At each distance location, the status of button and trigger behaviour will be observed. All the result for this test was recorded as in figure 4.
The geo-fence features in the SmartQ mobile application is accurate and reliable. The button is enabled when user inside the geo-fence area and disabled when user outside the geo-fence area conclude that the mobile app only allow user inside the geo-fence area to take part in the queue.
The status of the button will be changed automatically when user get through into or out the geo- fence border which is 200 meters from the center radius.
Figure 4: Test Result
6. Conclusion
In this article, geo-fencing technique is used in developing a mobile SmartQ application for multiple organizations. By having this SmartQ mobile application, it allows the user to take part in queue from certain distance that has been specified using geo-fence area. It also allows the user to monitor and estimate the waiting time. This SmartQ mobile application is a centralized platform for the user to queue at multiple organizations. The SmartQ mobiles application also be able to limit number of users by using geo-fence technique. This feature helps the organizations to limit number of user be able to join the queue in certain range to maximize the number of successful queue. 53 For the testing of this mobile application, functionality testing and accuracy of geo-fence feature testing was conducted. The functionality testing was conducted to make sure the mobile app is working as intended while the testing for accuracy of geo-fence feature was conducted to test the reliability and accuracy of user limitation on joining the queue using the geo-fence technique given the user current location. Overall, SmartQ mobile application is an effective system that provide mobile queuing and give convenience to customer to maintain customer satisfactory and perform as a centralized platform for user to queue at multiple organizations.
References
Hyun Lee. (2017). The Definitive Guide to Queue Management Systems | Qminder. Retrieved March 18, 2018, from https://www.qminder.com/what-is-queuemanagement-system/
Carvalho, A., & Belo, O. (2016). Predicting waiting time in customer queuing systems. In 2016 IEEE International Conference on Knowledge Engineering and Applications (ICKEA) (pp.
155–159). IEEE. https://doi.org/10.1109/ICKEA.2016.7803010
Ghazal, M., Hamouda, R., & Ali, S. (2015). An IoT Smart Queue Management System with Real- Time Queue Tracking. 2015 Fifth International Conference on e-Learning (econf), 257-262.
Qin, M., Tang, C.-H. (Hugo), Jang, S. (Shawn), & Lehto, X. (2017). Mobile app introduction and shareholder returns. Journal of Hospitality and Tourism Management, 31, 173–180.
https://doi.org/10.1016/J.JHTM.2016.11.006
McLean, G., Al-Nabhani, K., & Wilson, A. (2018). Developing a Mobile Applications Customer Experience Model (MACE)- Implications for Retailers. Journal of Business Research, 85, 325–336. https://doi.org/10.1016/J.JBUSRES.2018.01.018
Garzon, S. R., Elbehery, M., Deva, B., & Kupper, A. (2016). Reliable Geofencing: Assisted Configuration of Proactive Location-based Services. In 2016 IEEE International Conference on Mobile Services (MS) (pp. 204–207). IEEE. https://doi.org/10.1109/ MobServ.2016.42 Liang, C.-C. (2013). Customers Waiting in Front of a Retail Store. In 2013 46th Hawaii
International Conference on System Sciences (pp. 1310–1316). IEEE.
https://doi.org/10.1109/ HICSS.2013.160
Rauno Rüngas. (2014). Why Queue Barriers Are Ineffective | Qminder. Retrieved April 23, 2018, from https://www.qminder.com/why-queue-barriers-areineffective/
Li, Q., Han, Q., Cheng, X., & Sun, L. (2014). QueueSense: Collaborative recognition of queuing on mobile phones. In 2014 Eleventh Annual IEEE International Conference on Sensing, Communication, and Networking (SECON) (pp. 230– 238). IEEE. https://doi.org/10.1109/
SAHCN.2014.6990358
Hillier, F. (2015). Introduction to Operations Research. Penn Plaza, New York: McGraw-Hill Education
Klimek, R. (2017). Context-aware and pro-active queue management systems in intelligent environments (pp. 1077–1084). https://doi.org/10.15439/2017F362
Meng, Y., Liu, X., & Zhou, M. (2017). A novel model to determine the optimal number of servers in finite input source fuzzy queueing system. In 2017 36th Chinese Control Conference (CCC) (pp. 4175–4180). IEEE. https://doi.org/10.23919/ ChiCC.2017.8028013
Mohsen, W. A., Tao, C., Li, Q., & Gao, J. (2017). A Viewpoint on Location-Based Mobile Apps Testing. In 2017 IEEE Third International Conference on Big Data Computing Service and Applications (BigDataService) (pp. 305–312). IEEE. https://doi.org/10.1109/
BigDataService.2017.58
Raflesia, S. P., Lestarini, D., Taufiqurrahman, & Firdaus. (2017). Geofencing based technology towards child abuse prevention. In 2017 International Conference on Electrical Engineering
and Computer Science (ICECOS) (pp. 160–162). IEEE.
https://doi.org/10.1109/ICECOS.2017.8167125
Khan, J., & Shahzad, S. (2016). Android Architecture and Related Security Risks. Asian Journal of Technology & Management Research, 5(December 2015), 2249–2892
Rafter, C. B., Anvari, B., & Box, S. (2017). Traffic responsive intersection control algorithm using GPS data. In 2017 IEEE 20th International Conference on Intelligent Transportation Systems (ITSC) (pp. 1–6). IEEE. https://doi.org/10.1109/ ITSC.2017.8317795
Helmy, J., & Helmy, A. (2017). Demo abstract: Alzimio: A mobile app with geofencing, activity- recognition and safety features for dementia patients. In 2017 IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS) (pp. 994–995). IEEE.
https://doi.org/10.1109/INFCOMW.2017.8116527
Google Inc. (2017). Geofencing API | Google Developers. Retrieved May 10, 2018, from https://developers.google.com/location-context/geofencing/
Misra, A., & Dubey, A. (2013). Android Security: Attacks and Defenses. Boca Raton, FL: CRC Press
Google Inc. (2018). Overview | Maps SDK for Android | Google Developers. Retrieved May 10, 2018, from https://developers.google.com/maps/documentation/android-sdk/intro
Passarella, R., Raflesia, S. P., Lestarini, D., Taufiqurrahman, Malik, R. F., Sutarno, … Rifai, A.
(2017). Disaster mitigation management using geofencing in Indonesia. In 2017 11th International Conference on Telecommunication Systems Services and Applications (TSSA) (pp. 1–4). IEEE. 58 https://doi.org/10.1109/TSSA.2017.8272909
Karu, M. (2013). Implementing a service software to relieve waiting line frustration. Tartu University Viljandi Culture Academy.
