Smart healthcare IoT applications based on fog computing: architecture, applications and challenges

AbstractThe history of human development has proven that medical and healthcare applications for humanity always are the main driving force behind the development of science and technology. The advent of Cloud technology for the first time allows providing systems infrastructure as a service, platform as a service and software as a service. Cloud technology has dominated healthcare information systems for decades now. However, one limitation of cloud-based applications is the high service response time. In some emergency scenarios, the control and monitoring of patient status, decision-making with related resources are limited such as hospital, ambulance, doctor, medical conditions in seconds and has a direct impact on the life of patients. To solve these challenges, optimal computing technologies have been proposed such as cloud computing, edge computing, and fog computing technologies. In this article, we make a comparison between computing technologies. Then, we present a common architectural framework based on fog computing for Internet of Health Things (Fog-IoHT) applications. Besides, we also indicate possible applications and challenges in integrating fog computing into IoT Healthcare applications. The analysis results indicated that there is huge potential for IoHT applications based on fog computing. We hope, this study will be an important guide for the future development of fog-based Healthcare IoT applications.

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Future Aspects and Research Perspectives of the Internet of Things

Integration and Implementation of the Internet of Things Through Cloud Computing - Advances in Web Technologies and Engineering ◽

10.4018/978-1-7998-6981-8.ch001 ◽

2021 ◽

pp. 1-18

Author(s):

Harshit Bhardwaj ◽

Pradeep Tomar ◽

Aditi Sakalle ◽

Taranjeet Singh ◽

Divya Acharya ◽

...

Keyword(s):

Internet Of Things ◽

Fog Computing ◽

The Internet ◽

Literature Analysis ◽

Healthcare Applications ◽

Web Based ◽

Iot Applications ◽

Research Perspectives ◽

Software Production ◽

The Internet Of Things

Fog computing has latency, particularly for healthcare applications, which is of the utmost importance. This research aims to be a comprehensive literature analysis of healthcare innovations for fog computing. All of these components involved special abilities. In sequence, developers must be qualified to write stable, healthy IoT programs in four distinct fields of software production: embedded, server, tablet, and web-based. Furthermore, the distributed results, IoT structure essence, dispersed abilities in programming play a deciding position. This chapter discusses the difficulties in creating the IoT method and summarizing findings and observations. Experiences of the need for and co-presence of various kinds of skills in software creation in the construction of IoT applications are discussed.

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Leveraging Fog Computing for a Secure and Smart Healthcare

International Journal of Recent Technology and Engineering - 2 ◽

10.35940/ijrte.b3864.078219 ◽

2019 ◽

Vol 8 (2) ◽

pp. 6117-6122

Keyword(s):

Cloud Computing ◽

Homomorphic Encryption ◽

Fog Computing ◽

Healthcare Services ◽

Decision Fusion ◽

Sensor Data ◽

Smart Sensors ◽

Healthcare Applications ◽

Smart Healthcare ◽

Iot Devices

From hairbrushes to scales, all devices have sensors embedded in them to collect and communicate data. Smart Healthcare is proving to be an exciting and dynamic area with lots of room for new innovations and the increasing consumer demand for proactive health monitoring devices. Having India poised to spend a lot on healthcare, recent innovations using IoT devices and big data analytics can propel the healthcare industry into the future. Smart healthcare providers are leveraging cloud computing with fog computing to optimize their healthcare services. These smart healthcare applications depend mainly on the raw sensor data collected, aggregated, and analyzed by the smart sensors. Smart sensors these days generate myriad amount of data like text, image, audio, and video that require real-time or batch processing. Aggregating these diverse data from various types of resources remains a dispute till date. To resolve this issue, we have proposed a softwarized infrastructure that integrates cloud computing and fog computing, message brokers, and Tor for supple, safe, viable, and a concealed IoT exploitation for smart healthcare applications and services. Our proposed platform employs machine-to-machine (M2M) messaging, data fusion and decision fusion, and uses rule-based beacons for seamless data management. Our proposed flexBeacon system provides an IoT infrastructure that is nimble, secure, flexible, private, and reasonable. We have also proposed an M2M transceiver and microcontroller for flawless data incorporation of smart healthcare applications and services. Based on the IoT devices’ technical capabilities and resource availability, some systems are capable of making use of homomorphic encryption and zero knowledge proofs. The proposed flexBeacon platform offers seamless management and data aggregation without loss of accuracy. The cost of implementing a softwarized IoT for smart healthcare is also greatly reduced.

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Remote Pain Monitoring Using Fog Computing for e-Healthcare: An Efficient Architecture

Sensors ◽

10.3390/s20226574 ◽

2020 ◽

Vol 20 (22) ◽

pp. 6574

Author(s):

Syed Rizwan Hassan ◽

Ishtiaq Ahmad ◽

Shafiq Ahmad ◽

Abdullah Alfaify ◽

Muhammad Shafiq

Keyword(s):

Cloud Computing ◽

Monitoring System ◽

Fog Computing ◽

Self Report ◽

Healthcare Applications ◽

Computing Architecture ◽

Computing Paradigm ◽

Smart Healthcare ◽

Number Of Patients ◽

Iot Devices

The integration of medical signal processing capabilities and advanced sensors into Internet of Things (IoT) devices plays a key role in providing comfort and convenience to human lives. As the number of patients is increasing gradually, providing healthcare facilities to each patient, particularly to the patients located in remote regions, not only has become challenging but also results in several issues, such as: (i) increase in workload on paramedics, (ii) wastage of time, and (iii) accommodation of patients. Therefore, the design of smart healthcare systems has become an important area of research to overcome these above-mentioned issues. Several healthcare applications have been designed using wireless sensor networks (WSNs), cloud computing, and fog computing. Most of the e-healthcare applications are designed using the cloud computing paradigm. Cloud-based architecture introduces high latency while processing huge amounts of data, thus restricting the large-scale implementation of latency-sensitive e-healthcare applications. Fog computing architecture offers processing and storage resources near to the edge of the network, thus, designing e-healthcare applications using the fog computing paradigm is of interest to meet the low latency requirement of such applications. Patients that are minors or are in intensive care units (ICUs) are unable to self-report their pain conditions. The remote healthcare monitoring applications deploy IoT devices with bio-sensors capable of sensing surface electromyogram (sEMG) and electrocardiogram (ECG) signals to monitor the pain condition of such patients. In this article, fog computing architecture is proposed for deploying a remote pain monitoring system. The key motivation for adopting the fog paradigm in our proposed approach is to reduce latency and network consumption. To validate the effectiveness of the proposed approach in minimizing delay and network utilization, simulations were carried out in iFogSim and the results were compared with the cloud-based systems. The results of the simulations carried out in this research indicate that a reduction in both latency and network consumption can be achieved by adopting the proposed approach for implementing a remote pain monitoring system.

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Low-latency and energy-efficient scheduling in fog-based IoT applications

TURKISH JOURNAL OF ELECTRICAL ENGINEERING & COMPUTER SCIENCES ◽

10.3906/elk-1810-47 ◽

2019 ◽

pp. 1406-1427 ◽

Cited By ~ 5

Author(s):

DADMEHR RAHBARI ◽

MOHSEN NICKRAY

Keyword(s):

Intelligent Transportation Systems ◽

Data Transfer ◽

Smart Cities ◽

Fog Computing ◽

Transportation Systems ◽

Healthcare Applications ◽

Iot Applications ◽

Priority Algorithms ◽

Processing Power ◽

Resource Management Algorithms

In today’s world, the internet of things (IoT) is developing rapidly. Wireless sensor network (WSN) as an infrastructure of IoT has limitations in the processing power, storage, and delay for data transfer to cloud. The large volume of generated data and their transmission between WSNs and cloud are serious challenges. Fog computing (FC) as an extension of cloud to the edge of the network reduces latency and traffic; thus, it is very useful in IoT applications such as healthcare applications, wearables, intelligent transportation systems, and smart cities. Resource allocation and task scheduling are the NP-hard issues in FC. Each application includes several modules that require resources to run. Fog devices (FDs) have the ability to run resource management algorithms because of their proximity to sensors and cloud as well as the proper processing power. In this paper, we review the scheduling strategies and parameters as well as providing a greedy knapsack-based scheduling (GKS) algorithm for allocating resources appropriately to modules in fog network. Our proposed method was simulated in iFogsim as a standard simulator for FC. The results show that the energy consumption, execution cost, and sensor lifetime in GKS are better than those of the first-come-first-served (FCFS), concurrent, and delay-priority algorithms.

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A Panorama of Cloud Platforms for IoT Applications Across Industries

Sensors ◽

10.3390/s20092701 ◽

2020 ◽

Vol 20 (9) ◽

pp. 2701

Author(s):

Sami Yangui

Keyword(s):

Fog Computing ◽

Relevant Literature ◽

Critical Role ◽

Critical Research ◽

Research Directions ◽

Platform As A Service ◽

Iot Applications ◽

Industrial Iot ◽

Future Challenges ◽

Cloud Environments

Internet of Things (IoT) applications can play a critical role in business and industry. Industrial IoT (IIoT) refers to the use of IoT technologies in manufacturing. Enabling IIoT applications in cloud environments requires the design of appropriate IIoT Platform as-a-Service (IIoT PaaS) to support and ease their provisioning (i.e., development, deployment and management). This paper critically reviews the IIoT PaaS architectures proposed so far in the relevant literature. It only surveys the architectures that are suitable for IIoT applications provisioning and it excludes regular IoT solutions from its scope. The evaluation is based on a set of well-defined architectural requirements. It also introduces and discusses the future challenges and the research directions. The critical review discusses the PaaS solutions that focus on the whole spectrum of IoT verticals and also the ones dealing with specific IoT verticals. Existing limitations are identified and hints are provided on how to tackle them. As critical research directions, the mechanisms that enable the secure provisioning, and IIoT PaaS interaction with virtualized IoT Infrastructure as-a-Service (IaaS) and fog computing layer are discussed.

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Implementation analysis of IoT-based offloading frameworks on cloud/edge computing for sensor generated big data

Complex & Intelligent Systems ◽

10.1007/s40747-021-00434-6 ◽

2021 ◽

Author(s):

Karan Bajaj ◽

Bhisham Sharma ◽

Raman Singh

Keyword(s):

High Speed ◽

Smart Cities ◽

Fog Computing ◽

Edge Computing ◽

Computation Offloading ◽

Performance Parameters ◽

Iot Applications ◽

Time Sensitivity ◽

Implementation Analysis ◽

Increasing Demand

AbstractThe Internet of Things (IoT) applications and services are increasingly becoming a part of daily life; from smart homes to smart cities, industry, agriculture, it is penetrating practically in every domain. Data collected over the IoT applications, mostly through the sensors connected over the devices, and with the increasing demand, it is not possible to process all the data on the devices itself. The data collected by the device sensors are in vast amount and require high-speed computation and processing, which demand advanced resources. Various applications and services that are crucial require meeting multiple performance parameters like time-sensitivity and energy efficiency, computation offloading framework comes into play to meet these performance parameters and extreme computation requirements. Computation or data offloading tasks to nearby devices or the fog or cloud structure can aid in achieving the resource requirements of IoT applications. In this paper, the role of context or situation to perform the offloading is studied and drawn to a conclusion, that to meet the performance requirements of IoT enabled services, context-based offloading can play a crucial role. Some of the existing frameworks EMCO, MobiCOP-IoT, Autonomic Management Framework, CSOS, Fog Computing Framework, based on their novelty and optimum performance are taken for implementation analysis and compared with the MAUI, AnyRun Computing (ARC), AutoScaler, Edge computing and Context-Sensitive Model for Offloading System (CoSMOS) frameworks. Based on the study of drawn results and limitations of the existing frameworks, future directions under offloading scenarios are discussed.

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