Availability measure model for Assistive Care Loop Framework using wireless sensor networks
- Authors: Balasubramanian, Venki , Hoang, Doan
- Date: 2010
- Type: Text , Conference proceedings
- Relation: 6th International Conference on Intelligent Sensors, Sensor Networks and Information Processing, ISSNIP 2010,Brisbane, 7th-10th Dec, 2010 published in Proceedings of ISSNIP 2010 Sixth International Conference on Intelligent Sensors, Sensor Networks and Information Processing, p. 281-286
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- Description: Nowadays, body area wireless sensor networks (BAWSNs) applications are increasingly being used in in-house health monitoring systems. These applications have stringent timing requirements and often run continuously without interruptions. Hence, it becomes imperative to determine the operational continuity of the BAWSN applications by measuring their availability. The BAWSN applications rely on the collection of data within a critical time from all of the source sensor nodes rather than the data from an individual source. Subsequently, the measure of availability for a BAWSN application should be based on the time and the data delivery from all the sensor nodes. Taking into account these specific characteristics and the constraints of the BAWSN, we develop a model to measure the availability of a BAWSN application based on the unavailable time. The proposed model is evaluated through a series of experiments conducted in our existing Assistive Care Loop Framework (ACLF). Furthermore, we also develop an analogous theoretical model to evaluate the availability of a BAWSN application
Efficient spatio-temporal sensor deployments: A smart building application
- Authors: Linh, Nguyen , Guoqiang, Hu , Spanos, Costas J.
- Date: 2017
- Type: Text , Conference proceedings
- Relation: 13th IEEE International Conference on Control & Automation (ICCA); Ohrid, Macedonia; 03-06 July, 2017 p. 612-617
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- Description: The paper addresses the problem of efficiently deploying sensors in spatial environments, e.g. smart buildings, for the purpose of monitoring environmental phenomena. By modelling the environmental fields using spatio-temporal Gaussian processes, a new and efficient optimality criterion of minimizing prediction uncertainties is proposed to find the best sensor locations. Though the environmental processes spatially and temporally vary, the proposed approach of choosing sensor positions is not affected by time variations, which significantly reduces computational complexity of the optimization problem. The sensor deployment problem is then solved by a practically and feasibly polynomial algorithm, where its solutions are guaranteed. The proposed approaches were implemented in a real tested space in a university building, where the obtained results are highly promising.
Monitoring body motions related to Huntington disease by exploiting the 5G Paradigm
- Authors: Haider, Daniyal , Romain, Olivier , Kernec, Julien Le , Shah, Syed Yaseen , Farooq, Malik Muhammad Umer , Qadus, Zunaira
- Date: 2019
- Type: Text , Conference proceedings
- Relation: 2019 UK/ China Emerging Technologies (UCET); Glasgow UK; 21-22 August 2019 p. 1-4
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- Description: The modern wireless technology exploiting the full potential of 5G IoT is the future for healthcare sector. In the healthcare sector, the 5G technology will maximize the performance and will reduce the chances of damage to the patient by providing careful and advance activity monitoring scenarios. We have proposed the idea of monitoring different body posture in Huntington disease by exploiting the low cost wireless devices operating at 4.8 GHz frequency. The system captures the wireless channel information for three body motions and classification of these motions was performed by using support vector machine. The SVM used 10 time-domain features for the classification process by using three main kernel functions, such as, Linear, Polynomial and Radial basis function. The system minimizes all the external noise by using the microwave absorbing materials. This increases the performance and feasibility of sensing body motions.