Internet of Cognitive Things in healthcare

System Architecture

The Internet of Things (IoT) is a communication paradigm that envisions a near future in which the objects of everyday life will be equipped with devices that will make them able to communicate with one another and with users, becoming an integral part of the Internet. Our system architecture deploys a 3-layer (sensor-edge-cloud) structure, with the edge layer enabling system adaptivity in real-time.
The sensor layer is the closest layer to the patient and is composed of several sensor nodes mounted on the body for collecting bio-signals, patient activities, and context information.
The sensor nodes are resource constrained in terms of available energy and processing power. Therefore, they are only capable of performing simple preprocessing, and often delegate signal analysis to the upper layers.  At the edge layer, the gateway device is a network-enabled local computer performing several tasks (e.g., data fusion, local processing, compression, and encryption) on collected data before transferring it to the cloud layer. In addition, the edge layer is responsible for sending optimal settings such as power level, sampling rate, duration of sensing and scheduling sleeping times for the sensor to maximize the battery life in the sensor.  In this project, we try to use the concept of real-time edge computing to improve the energy efficiency of sensors.





Amiri, Delaram; Anzanpour, Arman; Azimi, Iman; Levorato, Marco; Rahmani, Amir M; Liljeberg, Pasi; Dutt, Nikil

Edge-Assisted Sensor Control in Healthcare IoT Inproceedings

2018 IEEE Global Communications Conference (GLOBECOM), pp. 1–6, 2018.

Abstract | Links | BibTeX


Anzanpour, Arman; Azimi, Iman; Gotzinger, Maximilian; Rahmani, Amir M; Taherinejad, Nima; Liljeberg, Pasi; Jantsch, Axel; Dutt, Nikil D

Self-awareness in remote health monitoring systems using wearable electronics Inproceedings

Design, Automation & Test in Europe Conference & Exhibition, DATE 2017, Lausanne, Switzerland, March 27-31, 2017, pp. 1056–1061, 2017.

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