Key result
An IoT-based healthcare system using bio-medical sensors was implemented to analyze cloud data via signal analysis techniques for anomaly detection.
Why the study?
IoT healthcare devices often feature specific cloud interfaces but lack adequate capabilities to analyse the data.
The study presents a technical implementation of an IoT-based healthcare framework utilizing biomedical sensors and signal analysis for anomaly detection in cloud data.
Answers are grounded in this paper and cite their sources.
Technical feasibility of IoT sensor-based anomaly detection shown; leaves open prospective validation before cardiovascular practice adoption.
In the past few years, the idea of trading information while multiple devices are connected and communicating with each other, has grabbed huge attention. For processing this large amount of information, data connectivity and data analytics techniques have become essential for making decisions in variety of areas. Applying Internet of Things (IoT) solutions in healthcare systems is one of the rising areas that researchers are interested in. The usage of IoT technology has brought convenience for patients and physicians by real-time monitoring and managing healthcare and patient information. Corporations are in competition with each other to create IoT based devices with specific cloud interface but with least capability to analyse the data. In this research, an implementation of IoT based healthcare system using bio-medical sensors has been presented. This paper also aims to provide the analysis of cloud data acquired through biomedical sensors using signal analysis techniques for anomaly detection.
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Nawaz et al. (2020) studied this question. IoT-based healthcare system with signal analysis was evaluated on Anomaly detection in cloud data acquired through biomedical sensors. An IoT-based healthcare system using bio-medical sensors was implemented to analyze cloud data via signal analysis techniques for anomaly detection.
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