Abstract
This book chapter presents technological aspects regarding cognitive radio and communication technology for IoT (Internet of Things). In addition, health monitoring by cognitive radio for IoT is a technological challenge for communication because it involves the connection of electronic devices used for medical monitoring. For medical monitoring in the IoT context, it should consider the risks of electromagnetic interference between medical devices and aggregators (4G/5G cellular phone). The cellular phones emit EM radiation during the ringing, sending/receiving data and standby phase. In hospital are used for monitoring sophisticated devices, the inference can occur due to the medical staff and patients who useb cellular phone for personal commutation. Cognitive radio can solve the inference problem for electronic device networks connected by WLAN, through radio links. The IoT requirements, such as cognitive radio and 5G, are integrated parts of the Future Internet. For IoT cognitive radio the requirement is to reduce the channel inference with primary licensed users and alternative spectrum management (e.g. each unlicensed user will sense and access the spectrum when the spectrum is unoccupied by licensed users) to reduce the EMI. The scientific literature shows that there have been numerous concerns to model the cognitive radio using various algorithms, such as fuzzy logic, neural networks, hidden Markov model, genetic algorithms or classification algorithms. In our research we used cognitive radio modelling for medical devices by several algorithms, such as neural network and genetic algorithms.
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This paper was partially supported by ESTABLISH, WINS@HI and EmoSpaces projects.
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Aileni, R.M., Suciu, G., Suciu, V., Pasca, S., Strungaru, R. (2019). Health Monitoring Using Wearable Technologies and Cognitive Radio for IoT. In: Rehmani, M., Dhaou, R. (eds) Cognitive Radio, Mobile Communications and Wireless Networks. EAI/Springer Innovations in Communication and Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-91002-4_6
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