Secure Smart Wearable Computing through Artificial Intelligence-Enabled Internet of Things and Cyber-Physical Systems for Health Monitoring

Ramasamy, Lakshmana Kumar; Khan, Firoz; Shah, Shahin; Prasad, Balusupati Veera Venkata Siva; Iwendi, Celestine; Biamba, Cresantus

doi:10.3390/s22031076

Cited by 67 publications

(52 citation statements)

References 38 publications

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“…Different researchers have used advanced technologies such as IoT, AI, fog computing, and big data in different fields for various purposes [ 13 , 14 ]. For example, Ngabo et al [ 15 ] proposed a recommendation system based on IoMT and ML for patient diet.…”

Section: Related Workmentioning

confidence: 99%

An ML-Enabled Internet of Things Framework for Early Detection of Heart Disease

Muhammad

Almoteri

Mujlid

et al. 2022

BioMed Research International

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Healthcare occupies a central role in sustainable societies and has an undeniable impact on the well-being of individuals. However, over the years, various diseases have adversely affected the growth and sustainability of these societies. Among them, heart disease is escalating rapidly in both economically settled and undeveloped nations and leads to fatalities around the globe. To reduce the death ratio caused by this disease, there is a need for a framework to continuously monitor a patient’s heart status, essentially doing early detection and prediction of heart disease. This paper proposes a scalable Machine Learning (ML) and Internet of Things-(IoT-) based three-layer architecture to store and process a large amount of clinical data continuously, which is needed for the early detection and monitoring of heart disease. Layer 1 of the proposed framework is used to collect data from IoT wearable/implanted smart sensor nodes, which includes various physiological measures that have significant impact on the deterioration of heart status. Layer 2 stores and processes the patient data on a local web server using various ML classification algorithms. Finally, Layer 3 is used to store the critical data of patients on the cloud. The doctor and other caregivers can access the patient health conditions via an android application, provide services to the patient, and inhibit him/her from further damage. Various performance evaluation measures such as accuracy, sensitivity, specificity, F1-measure, MCC-score, and ROC curve are used to check the efficiency of our proposed IoT-based heart disease prediction framework. It is anticipated that this system will assist the healthcare sector and the doctors in diagnosing heart patients in the initial phases.

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Section: Related Workmentioning

confidence: 99%

An ML-Enabled Internet of Things Framework for Early Detection of Heart Disease

Muhammad

Almoteri

Mujlid

et al. 2022

BioMed Research International

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“…Supply chain networks are improving with blockchain technology in many blockchain startups [ 20 , 21 ]. The authors of [ 22 , 23 ] conducted research on COVID-19 patient health analysis using blockchain technology. The security-based patient-centric healthcare was developed in [ 24 – 26 ].…”

Section: Related Workmentioning

confidence: 99%

Cloud-based blockchain technology to identify counterfeits

2022

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Multi-stakeholder and organizational involvement is an integral part of the medicine supply chain. Keeping track of the activities associated with medical products is difficult when the system is complex. Their complexity limits transparency and data provenance. Deficiencies within existing supply chains result in the counterfeiting of drugs, illegal imports, and inefficient operations. Due to these limitations, product integrity is compromised, resulting in product wastage. Visibility of the entire product supply chain is crucial for the pharmaceutical industry in terms of product safety and reduction of manufacturing costs. The Cloud-based Blockchain-powered architecture of the system provides a platform for addressing the need of pharma-material traceability, data storage, privacy of data, and quality assurance. This framework comprises of the identification of activities through tagging, information sharing in a secure environment; cloud-based storage using an off-chain Interplanetary File System (IPFS) and an on-chain couch DB; and access to this information that is controlled by the system's regulator. Electronic drug records will be accessed via a smart contract in Hyperledger Blockchain. The system assists in identifying false and cross-border products through the manufacturer and country of origin. A scan will identify counterfeit medications, showing that they are unauthorized products which may pose a risk to patients. Our experiments demonstrated the efficiency and usability of the design platform. Finally, we benchmarked the system using Hyperledger Caliper.

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“…In addition, most linked systems, known as Cyber-Physical Systems (CPS), are built by combining several elements such as humans and the physical environment, intelligent objects, and embedded devices and infrastructure [39]. A few significant difficulties might harm the IoT and CPS, such as security vulnerabilities and ethical concerns [40]. Cybersecurity in the context of wearable devices has received much attention.…”

Section: Cyber Securitymentioning

confidence: 99%

The Effectiveness of IoT Based Wearable Devices and Potential Cybersecurity Risks: A Systematic Literature Review from the Last Decade

et al. 2022

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Wearable technology has enormous promise, particularly for data collection for cutting-edge health research, and its popularity has soared in recent years. This study aims to provide IoT-based wearable devices' effectiveness and potential cybersecurity threats to these innovative technologies. Using the PRISMA-2020 (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) methodology, we conducted a scoping study to understand better the application of inexpensive, consumer-grade wearables for health research from a population health viewpoint. Scopus databases yielded a total of 43 articles. Our findings show that academics and research participants are tremendously interested in this technology, but they are also wary about using wearables. These devices are still vulnerable to cybersecurity assaults such as data privacy and security in healthcare. However, blockchain technology is a potential alternative for integrating with IoT-based wearables to ensure data privacy. Furthermore, according to the findings, wearables have an increasingly diverse range of applications, including COVID-19 prediction, fertility tracking, heat-related sickness, pharmacological effects, and psychological therapies; they also include underrepresented populations, such as those with rare diseases. In low-resource environments, there is a lack of research on wearable devices.

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Secure Smart Wearable Computing through Artificial Intelligence-Enabled Internet of Things and Cyber-Physical Systems for Health Monitoring

Cited by 67 publications

References 38 publications

An ML-Enabled Internet of Things Framework for Early Detection of Heart Disease

An ML-Enabled Internet of Things Framework for Early Detection of Heart Disease

Cloud-based blockchain technology to identify counterfeits

The Effectiveness of IoT Based Wearable Devices and Potential Cybersecurity Risks: A Systematic Literature Review from the Last Decade

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