Nasogastric Tube Dislodgment Detection in Rehabilitation Patients Based on Fog Computing with Warning Sensors and Fuzzy Petri Net

Li, Chien Ming; Ho, Yueh Ren; Chen, Wei Ling; Lin, Chia Hung; Chen, Ming Yu; Chen, Yong Zhi

doi:10.18494/sam.2019.1993

Cited by 4 publications

(4 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To identify nasogastric (NG) tube dislodgment over several days or weeks for ongoing insertion of the NG tube, a digital warning tool was developed [162]. The proposed assistance tool was built using a fuzzy Petri net (FPN) and dexter-to-sinister light-controlled sensors on the foundation of the FC.…”

Section: Healthcare Servicesmentioning

confidence: 99%

Fuzzy Theory in Fog Computing: Review, Taxonomy, and Open Issues

et al. 2022

View full text Add to dashboard Cite

Geographically dispersed Fog Computing architecture ubiquitously connected to a range of heterogeneous nodes at the edge of the network can provide cooperative flexible, and variable computations, communications, and storage services. Several fog computing methods, models, and techniques have been used to solve cloud issues. The fuzzy theory has also been used in many aspects of fog computing. Objectives: This work presents a systematic literature review of the use of fuzzy theory in Fog Computing, highlighting the main practical motivations, classification types in research approaches, fuzzy methods used, popular evaluation tools, open issues, and future trends. Methods: The investigations were systematically performed using fuzzy theory in fog computing, and four databases which are ScienceDirect, Web of Science (WoS), Scopus, and IEEE Xplore Digital Library from 2015 to 2022, were used to analyse their performance evaluation, architecture, and applications. Results: 94 articles were selected based on fuzzy theory in fog computing using different methods, models, and techniques, based on the proposed exclusion and inclusion criteria. The results of the taxonomy were divided into five major classes: task and resource management, intrusion detection systems, trust management, and healthcare services. Discussion: Applications requiring real-time, low latency, and quick responses are well suited for fog computing. These studies show that resource sharing improves the fog computing architecture by delivering reduced latency, distributed processing, improved scalability, better security, fault tolerance, and privacy. Conclusion: The majority of the time, research areas on fuzzy theory in fog computing are crucially significant. We conclude that this review will enhance research capacity, thereby expanding and creating new research domains.

show abstract

Section: Healthcare Servicesmentioning

confidence: 99%

Fuzzy Theory in Fog Computing: Review, Taxonomy, and Open Issues

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In Ref. [13], a digital alarm system based on fog calculation is designed to detect the displacement of Nasogastric tube, the elements and their attributes are described by using fuzzy Petri net. Ref.…”

Section: Related Workmentioning

confidence: 99%

Resource Constrained Profit Optimization Method for Task Scheduling in Edge Cloud

et al. 2020

View full text Add to dashboard Cite

Edge cloud is a cloud computing system built on edge infrastructure. Task scheduling optimization is the key technology to ensure the quality of service in edge cloud. However, the openness of the edge cloud environment challenges the load balancing and profit optimization of task scheduling. In this paper, we analyze the business process and optimization factors of task scheduling in edge cloud. First, we propose a resource constrained task scheduling profit optimization algorithm (RCTSPO), which consists of clustering preprocessing, classification, profit matrix construction and optimal scheduling strategy calculation. Clustering preprocessing gathers similar tasks into one class and perform a classification on the clustered tasks. Then construct the profit matrix for resource constrained task scheduling, and the optimal task scheduling strategy is obtained based on the constructed profit matrix. Second, Petri nets are used to construct the different components of edge cloud, such as resource, task, user request and virtual machine, thus forming the task scheduling model of edge cloud. Third, the properties of task scheduling model are verified by using the related theory and tools of Petri nets. Finally, several experiments are done to evaluate the proposed method, the simulation results show that the algorithm not only achieves the maximum profit, but also performs well in terms of time, reliability and load balancing of task scheduling.

show abstract

“…• Sensor data related to the medical field and action network: The ubiquitous devices sense and perform the corresponding action by communicating signals from patients body to the control room via the certain usages of the protocols such as 6LowPAN [23], wifi [24], and Zigbee [25].…”

Section: Fog Computingmentioning

confidence: 99%

Influence of Montoring: Fog and Edge Computing

Prasad

Bhavsar

Tanwar

2019

SCPE

View full text Add to dashboard Cite

The evolution of the Internet of Things (IoT) has augmented the necessity for Cloud, edge and fog platforms. The chief benefit of cloud-based schemes is they allow data to be collected from numerous services and sites, which is reachable from any place of the world. The organizations will be benefited by merging the cloud platform with the on-site fog networks and edge devices and as result, this will increase the utilization of the IoT devices and end users too. The network traffic will reduce as data will be distributed and this will also improve the operational efficiency. The impact of monitoring in edge and fog computing can play an important role to efficiently utilize the resources available at these layers. This paper discusses various techniques involved for monitoring for edge and fog computing and its advantages. The paper ends with a case study to demonstarte the need of monitoring in fog and edge in the healthcare system.

show abstract

Nasogastric Tube Dislodgment Detection in Rehabilitation Patients Based on Fog Computing with Warning Sensors and Fuzzy Petri Net

Cited by 4 publications

References 11 publications

Fuzzy Theory in Fog Computing: Review, Taxonomy, and Open Issues

Fuzzy Theory in Fog Computing: Review, Taxonomy, and Open Issues

Resource Constrained Profit Optimization Method for Task Scheduling in Edge Cloud

Influence of Montoring: Fog and Edge Computing

Contact Info

Product

Resources

About