Fuzzy assisted fog and cloud computing with MIoT system for performance analysis of health surveillance system

Selvakanmani, S.; Sumathi, M.

doi:10.1007/s12652-020-02156-y

Cited by 10 publications

(4 citation statements)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Selvakanmani and Sumathi [ 20 ] have proposed the blockchain and smart contract-based framework for cloud-edge computing in the healthcare system, thus providing data privacy, security, latency, cost-effective storage, and data availability.…”

Section: Related Workmentioning

confidence: 99%

“…After closer analysis of the related work and other models [ 4 , 20 – 23 ], we have found that most of the security networks are centralized in nature which rely on third-party sources for security and data exchange. The healthcare system is spread across heterogeneous platforms and devices, which enforces the developer to think about a decentralized framework for easy data exchange with complete security and privacy.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Blockchain and IPFS Integrated Framework in Bilevel Fog-Cloud Network for Security and Privacy of IoMT Devices

Mehbodniya

Neware

Vyas

et al. 2021

Computational and Mathematical Methods in Medicine

View full text Add to dashboard Cite

Internet of Medical Things (IoMT) has emerged as an integral part of the smart health monitoring system in the present world. The smart health monitoring deals with not only for emergency and hospital services but also for maintaining a healthy lifestyle. The industry 5.0 and 5/6G has allowed the development of cost-efficient sensors and devices which can collect a wide range of human biological data and transfer it through wireless network communication in real time. This led to real-time monitoring of patient data through multiple IoMT devices from remote locations. The IoMT network registers a large number of patients and devices every day, along with the generation of huge amount of big data or health data. This patient data should retain data privacy and data security on the IoMT network to avoid any misuse. To attain such data security and privacy of the patient and IoMT devices, a three-level/tier network integrated with blockchain and interplanetary file system (IPFS) has been proposed. The proposed network is making the best use of IPFS and blockchain technology for security and data exchange in a three-level healthcare network. The present framework has been evaluated for various network activities for validating the scalability of the network. The network was found to be efficient in handling complex data with the capability of scalability.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Blockchain and IPFS Integrated Framework in Bilevel Fog-Cloud Network for Security and Privacy of IoMT Devices

Mehbodniya

Neware

Vyas

et al. 2021

Computational and Mathematical Methods in Medicine

View full text Add to dashboard Cite

show abstract

“… Yang et al (2020) developed a smart and interconnected system for cardiac health management in the context of a large-scale IoT network. Selvakanmani & Sumathi (2021) reported a robust mechanism using fog computing in association with cloud computing to enable a secure healthcare model.…”

Section: Literature Reviewmentioning

confidence: 99%

A comprehensive secure system enabling healthcare 5.0 using federated learning, intrusion detection and blockchain

Almalki,

Alshahrani,

Khan

2024

PeerJ Computer Science

View full text Add to dashboard Cite

Recently, the use of the Internet of Medical Things (IoMT) has gained popularity across various sections of the health sector. The historical security risks of IoMT devices themselves and the data flowing from them are major concerns. Deploying many devices, sensors, services, and networks that connect the IoMT systems is gaining popularity. This study focuses on identifying the use of blockchain in innovative healthcare units empowered by federated learning. A collective use of blockchain with intrusion detection management (IDM) is beneficial to detect and prevent malicious activity across the storage nodes. Data accumulated at a centralized storage node is analyzed with the help of machine learning algorithms to diagnose disease and allow appropriate medication to be prescribed by a medical healthcare professional. The model proposed in this study focuses on the effective use of such models for healthcare monitoring. The amalgamation of federated learning and the proposed model makes it possible to reach 93.89 percent accuracy for disease analysis and addiction. Further, intrusion detection ensures a success rate of 97.13 percent in this study.

show abstract

“…One of the main challenges of IPSs when wanting to accurately estimate location is dealing with the uncertainty inherent to the applied technologies in these systems [6][7][8] due to calibration issues, data loss, indoor obstacles or battery consumption limitations.…”

Section: Introductionmentioning

confidence: 99%

UJAmI Location: A Fuzzy Indoor Location System for the Elderly

Albín-Rodríguez

Robles

López

et al. 2021

IJERPH

View full text Add to dashboard Cite

Due to the large number of elderly people with physical and cognitive issues, there is a strong need to provide indoor location systems that help caregivers monitor as many people as possible and with the best quality possible. In this paper, a fuzzy indoor location methodology is proposed in a smart environment based on mobile devices and Bluetooth Low Energy (BLE) beacons where a set of Received Signal Strength Indicators (RSSI) is received by mobile devices worn by the inhabitants. The use of fuzzy logic and a fuzzy linguistic approach is proposed to deal with the imprecise nature of the RSSI values, which are influenced by external factors such as radio waves, causing significant fluctuations. A case study carried out at the Smart Lab of the University of Jaén (UJAmI Smart Lab) is presented to demonstrate the effectiveness of the proposed methodology, where our proposal is compared with a non-fuzzy logic approach, obtaining an accuracy of 91.63%, approximately 10 points higher than the methodology without using fuzzy logic. Finally, our theoretical proposal is accompanied by a description of the UJAmI Location system, which applies the theory to the functionality of locating elderly people in indoor environments.

show abstract

Fuzzy assisted fog and cloud computing with MIoT system for performance analysis of health surveillance system

Cited by 10 publications

References 22 publications

Blockchain and IPFS Integrated Framework in Bilevel Fog-Cloud Network for Security and Privacy of IoMT Devices

Blockchain and IPFS Integrated Framework in Bilevel Fog-Cloud Network for Security and Privacy of IoMT Devices

A comprehensive secure system enabling healthcare 5.0 using federated learning, intrusion detection and blockchain

UJAmI Location: A Fuzzy Indoor Location System for the Elderly

Contact Info

Product

Resources

About