A Smart Mobile System for the Real-Time Tracking and Management of Service Queues

et.al., Mohammed Ghazal

doi:10.12785/ijcds/050402

Cited by 10 publications

(6 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Other than that, users can also join multiple queues without the need to be there physically. Another solution to the issue of consumers' frustration with high wait times linked with certain services is by developing a smart mobile system that has real-time tracking and management of service queues [1]. This intelligent queue management system is designed to deliver real-time visual and auditory updates on response demands via a smartphone app.…”

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Smart Management Waiting System for Outpatient Clinic

Nasrudin

Zainuddin

Ahmad

et al. 2023

ARASET

View full text Add to dashboard Cite

Queuing has become a common occurrence in malls, train stations, and others. Queuing especially in healthcare intuitions has become a center of attraction because of the long waiting time either at the registration or in receiving treatments. Therefore, in solving this problem, a smart management waiting system for outpatient clinics is developed by using AppGyver and Backendless as the data storage. This system will be operating by QR code scanning for administrators to obtain patients’ personal information before patients obtain the queue number via MyQUEUE mobile application (patients’ interface). By providing queue numbers through the mobile application, patients don’t have to wait in a small uncomfortable waiting lounge instead patients can wait at their desired places such as cafeteria, in their car, and others. Patients also don’t have to worry about missing their turns because there will be a 10 minutes reminder before their turn. Other than that, there is a feature that digitalized the appointment details which means patients don’t have to worry about missing their appointment book or card. The performance of both systems which are the patients’ interface and administrators’ interface is successfully designed and the output obtained. The administrator is able to assign queue numbers, notify patients 10 minutes before consultation time, and assign follow-up appointments to patients.

show abstract

Section: Literature Reviewmentioning

confidence: 99%

“…As the world's population grows, queueing becomes a common occurrence in public places like malls, banks, transit hubs, and even hospitals [1,2]. Therefore, previous researchers believe it is important to determine the role of technology readiness on the success of smart cities, including the use of the smart waiting system.…”

Section: Introductionmentioning

confidence: 99%

Smart Management Waiting System for Outpatient Clinic

Nasrudin

Zainuddin

Ahmad

et al. 2023

ARASET

View full text Add to dashboard Cite

show abstract

“…The user interface (UI) is made simple and easy to use for the user by having the ticket and status board seem like their real-world equivalents, as shown in Figure 2 below. While subsection B elaborates on the streaming and queue management unit, subsection A describes the registration and verification unit and the system's workflow [6].…”

Section: Adaptive Active Queue Management Based On Model Predictive C...mentioning

confidence: 99%

A Brief Review on Queue Management Systems for different Applications

2023

TBEAH

View full text Add to dashboard Cite

Queue management technology helps to reduce actual and predicted customer wait times, improve customer satisfaction, and provide the data to your managers needed to further optimize service, Queue Management System (QMS)presents a viable solution for different applications. It is employed to manage lines in a queue area in a variety of circumstances and locales. The article discusses the concepts of Queue Management Systems for Hospitals, Satellite Networks Based on Traffic Prediction, using Deep Neural Networks (DNN). Managing high patient loads in tertiary care hospitals represents a significant challenge in streamlining health service delivery. At several hospital service locations, including the registration, lab, and bill payment counters, patients must frequently wait in line. In these circumstances, Queue Management Systems (QMS) offer a practical patient management option. Satellite Internet the Adaptive Random Early Detection (ARED) queue management algorithm is proposed to be improved by traffic prediction based on a dynamic triple exponential smoothing model, smoothing coefficient optimization of the model using a differential evolutionary algorithm, and a cubic function based on traffic prediction. Customers and the administrative staff of the company can use a queue management system that uses the Open-CV platform and CNN algorithm for image processing, together with real-time person detection and people count recording. This essay also discusses several techniques in relation to their applications. With services that have medium to lengthy waiting periods, the proposed method seeks to reduce customer discontent. Keyword : Adaptive random early detection, CNN image processing, cubic function, differential evolution algorithm, dynamic triple exponential smoothing model, System for Managing Hospitals.

show abstract

“…Research challenges include: Managing and effectively utilizing big data techniques for WoT; Supporting convergence for WoT-related standards and technologies; Embedding security, privacy and trust as intrinsic building blocks of WoT systems; Creating intelligent and adaptive natural user interfaces and interactions for WoT devices, infrastructure and systems; and Designing, developing and implementing WoT applications. The first SI of WoTBD, volume 5, issue 4, July 2016 [1][2][3][4][5][6][7] The main idea of the paper entitled "Sentiment analysis of Social Sensors for local services improvement" by Olivera Kotevska, and Ahmed Lbath addressed processing and categorization of microblogging data and identified the sentiment level of each category in order to provide a better understanding of public needs and concerns. The objectives of this research are measuring the sentiment at certain area and topic to determine the relevant services and promote recommendations in decision-making [8].…”

Section: Introductionmentioning

confidence: 99%