Stay at Home Reservation: The Mitigation Step in Covid-19 Pandemic

The Covid-19 pandemic condition that has hit the world has had a significant impact on various sectors. Health facilities need information system support in their services. Breaking the distribution chain can be done by maintaining a physical distance. However, in reality, people are still indifferent. There is a possibility that the patient is infected but shows no symptoms or is lying to the point of endangering medical personnel. In addition, there is a stigma in the community so that they are afraid to go to health facilities. Even though it cannot be denied that in certain conditions patients should still have their conditions checked by a doctor. The development of this online registration system aims to reduce the risk of contact between patients and medical personnel. The real-time queue monitoring feature helps patients to wait in line anywhere, so they are not in the patient's waiting room. This system is able to provide real-time queues for examinations in all polyclinics. This can reduce public anxiety about coming to health facilities. Index Terms— Covid-19; Health Facilities; Online Reservation; Pandemic; Realtime Queues

Q-CAM: Queue Monitoring System using Camera

Development and design of mobile queue counter monitoring system is an alternative way for people who visit service premises to monitor queue number through phone without having to be at the place to wait for their turn. A long waiting line and waiting time are the reasons why this project had been developed. Many related systems had been introduced by different companies but due the high cost of installation and maintenance, some service companies had difficulties to implement the system. However, the proposed mobile queue counter monitoring system called Q-CAM is an add-on device which will be installed with the existing system and uses only ESP32 camera and FTDI Programmer as hardware development. A smartphone application is developed by using MIT App Inventor to ease the customer to monitor queue number on the app. In this work, the hardware designs of the propose device is described. Furthermore, the steps to develop the smartphone app is demonstrated. Preliminary experimental results show that the average time required to display a captured queue number image on the app were 5 seconds (during strong Wi-Fi signal) and 10.8 seconds (during weak Wi-Fi signal).

An optimized queue management system to improve patient flow in the absence of appointment system

PurposeThe aim of this research study is to develop a queue assessment model to evaluate the inflow of walk-in outpatients in a busy public hospital of an emerging economy, in the absence of appointment systems, and construct a dynamic framework dedicated towards the practical implementation of the proposed model, for continuous monitoring of the queue system.Design/methodology/approachThe current study utilizes data envelopment analysis (DEA) to develop a combined queuing–DEA model as applied to evaluate the wait times of patients, within different stages of the outpatients' department at the Combined Military Hospital (CMH) in Lahore, Pakistan, over a period of seven weeks (23rd April to 28th May 2014). The number of doctors/personnel and consultation time were considered as outputs, where consultation time was the non-discretionary output. The two inputs were wait time and length of queue. Additionally, VBA programming in Excel has been utilized to develop the dynamic framework for continuous queue monitoring.FindingsThe inadequate availability of personnel was observed as the critical issue for long wait times, along with overcrowding and variable arrival pattern of walk-in patients. The DEA model displayed the “required” number of personnel, corresponding to different wait times, indicating queue build-up.Originality/valueThe current study develops a queue evaluation model for a busy outpatients' department in a public hospital, where “all” patients are walk-in and no appointment systems. This model provides vital information in the form of “required” number of personnel which allows the administrators to control the queue pre-emptively minimizing wait times, with optimal yet dynamic staff allocation. Additionally, the dynamic framework specifically targets practical implementation in resource-poor public hospitals of emerging economies for continuous queue monitoring.

ASYMPTOTIC PEAK UTILISATION IN HETEROGENEOUS PARALLEL CPU/GPU PIPELINES: A DECENTRALISED QUEUE MONITORING STRATEGY

Widespread heterogeneous parallelism is unavoidable given the emergence of General-Purpose computing on graphics processing units (GPGPU). The characteristics of a Graphics Processing Unit (GPU)—including significant memory transfer latency and complex performance characteristics—demand new approaches to ensuring that all available computational resources are efficiently utilised. This paper considers the simple case of a divisible workload based on widely-used numerical linear algebra routines and the challenges that prevent efficient use of all resources available to a naive SPMD application using the GPU as an accelerator. We suggest a possible queue monitoring strategy that facilitates resource usage with a view to balancing the CPU/GPU utilisation for applications that fit the pipeline parallel architectural pattern on heterogeneous multicore/multi-node CPU and GPU systems. We propose a stochastic allocation technique that may serve as a foundation for heuristic approaches to balancing CPU/GPU workloads.