ArticleSensors (Basel, Switzerland)2022
Secure Smart Wearable Computing through Artificial Intelligence-Enabled Internet of Things and Cyber-Physical Systems for Health Monitoring.
Article in Sensors (Basel, Switzerland), 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
15 citing papers in PubMed, 108 citations in OpenAlex.
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- Nurses' perspectives on AI-Enabled wearable health technologies: opportunities and challenges in clinical practice.BMC nursing · 2025Article
- Distributed Sensor Network Calibration Under Sensor Nonlinearities with Applications in Aerodynamic Pressure Sensing.Sensors (Basel, Switzerland) · 2025Article
- Bibliometric Analysis of Research Articles on Embedded Internet of Health Things (IoHT) Fall Detection in the Elderly Published from 2006 to 2025.Journal of multidisciplinary healthcare · 2025Review
- AI-Reinforced Wearable Sensors and Intelligent Point-of-Care Tests.Journal of personalized medicine · 2024Review
- Computational Frontiers in Aptamer-Based Nanomedicine for Precision Therapeutics: A Comprehensive Review.ACS omega · 2024Review
- AI-Guided Computing Insights into a Thermostat Monitoring Neonatal Intensive Care Unit (NICU).Sensors (Basel, Switzerland) · 2023Article
- A Review of Artificial Intelligence in Embedded Systems.Micromachines · 2023Review
- Using Machine Learning Algorithms to Predict Patient Portal Use Among Emergency Department Patients With Diabetes Mellitus.Journal of clinical medicine research · 2023Article
- Public perceptions on the application of artificial intelligence in healthcare: a qualitative meta-synthesis.BMJ open · 2023Article
- Federated Learning via Augmented Knowledge Distillation for Heterogenous Deep Human Activity Recognition Systems.Sensors (Basel, Switzerland) · 2022Article
- Mathematical Framework for Wearable Devices in the Internet of Things Using Deep Learning.Diagnostics (Basel, Switzerland) · 2022Article
- Development of a Low-Power IoMT Portable Pillbox for Medication Adherence Improvement and Remote Treatment Adjustment.Sensors (Basel, Switzerland) · 2022Article
- An ML-Enabled Internet of Things Framework for Early Detection of Heart Disease.BioMed research international · 2022Article
- Cloud-based blockchain technology to identify counterfeits.Journal of cloud computing (Heidelberg, Germany) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 4 institutions in 4 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The functionality of the Internet is continually changing from the Internet of Computers (IoC) to the "Internet of Things (IoT)". Most connected systems, called Cyber-Physical Systems (CPS), are formed from the integration of numerous features such as humans and the physical environment, smart objects, and embedded devices and infrastructure. There are a few critical problems, such as security risks and ethical issues that could affect the IoT and CPS. When every piece of data and device is connected and obtainable on the network, hackers can obtain it and utilise it for different scams. In medical healthcare IoT-CPS, everyday medical and physical data of a patient may be gathered through wearable sensors. This paper proposes an AI-enabled IoT-CPS which doctors can utilise to discover diseases in patients based on AI. AI was created to find a few disorders such as Diabetes, Heart disease and Gait disturbances. Each disease has various symptoms among patients or elderly. Dataset is retrieved from the Kaggle repository to execute AI-enabled IoT-CPS technology. For the classification, AI-enabled IoT-CPS Algorithm is used to discover diseases. The experimental results demonstrate that compared with existing algorithms, the proposed AI-enabled IoT-CPS algorithm detects patient diseases and fall events in elderly more efficiently in terms of Accuracy, Precision, Recall and F-measure.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.