Evaluation of Electromagnetic Dosimetry of Wireless Systems in Complex Indoor Scenarios With Human Body Interaction

Aguirre, Erik; Arpon, Javier; Azpilicueta, Leyre; Bilbao, Silvia De Miguel; Ramos, Victoria; Falcone, and Francisco J.

doi:10.2528/pierb12070904

Cited by 58 publications

(57 citation statements)

References 46 publications

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“…A government agency such as the European Council issued a directive as to the minimum health and safety requirements regarding the exposure of workers to the risks arising from physical agents (electromagnetic fields) [43,44]. As there have been advances in wireless technologies for healthcare applications and networks, many works in areas such as characterizing electric field (E-field) exposure within the wireless (WiFi) environments [45,46] and the evaluation of electromagnetic dosimetry of wireless systems in complex indoor scenarios with human body interaction [47] or in sensor networks [48] have already been done. Thus, it is not within the scope of this review article to review the impacts to humans by sensor devices and mHealth networks environment whilst it is important to consider those challenges along with managing privacy issues.…”

Section: Diseases Based Geographic Areas Relationships Modelling Techmentioning

confidence: 99%

Systematic Predictive Analysis of Personalized Life Expectancy Using Smart Devices

Kang¹,

Adibi²

2018

Technologies

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With the emergence of technologies such as electronic health and mobile health (eHealth/mHealth), cloud computing, big data, and the Internet of Things (IoT), health related data are increasing and many applications such as smartphone apps and wearable devices that provide wellness and fitness tracking are entering the market. Some apps provide health related data such as sleep monitoring, heart rate measuring, and calorie expenditure collected and processed by the devices and servers in the cloud. These requirements can be extended to provide a personalized life expectancy (PLE) for the purpose of wellbeing and encouraging lifestyle improvement. No existing works provide this PLE information that is developed and customized for the individual. This article is based on the concurrent models and methodologies to calculate and predict life expectancy (LE) and proposes an idea of using multi-phased approaches to the solution as the project requires an immense and broad range of work to accomplish. As a result, the current prediction of LE, which was found to be up to a maximum of five years could potentially be extended to a lifetime prediction by utilizing generic health data. In this article, the novel idea of the solution proposing a PLE on an individual basis, which can be extended to lifetime is presented in addition to the existing works.

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Section: Diseases Based Geographic Areas Relationships Modelling Techmentioning

confidence: 99%

Systematic Predictive Analysis of Personalized Life Expectancy Using Smart Devices

Kang¹,

Adibi²

2018

Technologies

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“…Different applications of this algorithm can be found in the literature, like the analysis of wireless propagation in closed environments [15][16][17][18], interference analysis [19] or electromagnetic dosimetry evaluation in wireless systems [20].…”

Section: Ray Launching Technique and Simulation Scenariomentioning

confidence: 99%

Analysis of Radio Wave Propagation for ISM 2.4GHz Wireless Sensor Networks in Inhomogeneous Vegetation Environments

Azpilicueta

Lopez

Aguirre

et al. 2014

Proceedings of International Electronic Conference on Sensors and Applications

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Abstract:The use of wireless networks has experienced exponential growth due to the improvements in terms of battery life and low consumption of the devices. However, it is compulsory to conduct previous radio propagation analysis when deploying a wireless sensor network. These studies are necessary to perform an estimation of the range coverage, in order to optimize the distance between devices in an actual network deployment. In this work, the radio channel characterization for ISM 2.4 GHz Wireless Sensor Networks (WSNs) in an inhomogeneous vegetation environment has been analyzed. This analysis allows designing environment monitoring tools based on ZigBee and WiFi where WSN and smartphones cooperate, providing rich and customized monitoring information to users in a friendly manner. The impact of topology as well as morphology of the environment is assessed by means of an in-house developed 3D Ray Launching code, to emulate the realistic operation in the framework of the scenario. Experimental results gathered from a measurement campaign conducted by deploying a ZigBee Wireless Sensor Network, are analyzed and compared with simulations in this paper. The scenario where this network is intended to operate is a combination of buildings and diverse vegetation species. To gain insight in the effects of radio propagation, a OPEN ACCESSSensors 2014, 14 23651 simplified vegetation model has been developed, considering the material parameters and simplified geometry embedded in the simulation scenario. An initial location-based application has been implemented in a real scenario, to test the functionality within a context aware scenario. The use of deterministic tools can aid to know the impact of the topological influence in the deployment of the optimal Wireless Sensor Network in terms of capacity, coverage and energy consumption, making the use of these systems attractive for multiple applications in inhomogeneous vegetation environments.

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“…A 3D in-house developed RL algorithm has been used for the characterization of wireless propagation in the ground floor of a department of the Public University of Navarre (UPNA, Pamplona, Spain). The algorithm has been explained in detail in [25] and it has been validated in the literature for different applications, like the analysis of wireless propagation in closed environments [26][27][28][29], interference analysis [30] or electromagnetic dosimetry evaluation [31]. It is based on Geometrical Optics (GO) and Geometrical Theory of Diffraction (GTD).…”

Section: Indoor Scenario Simulation and Characterizationmentioning

confidence: 99%

Analysis of Wireless Sensor Network Topology and Estimation of Optimal Network Deployment by Deterministic Radio Channel Characterization

Aguirre

López-Iturri

Azpilicueta

et al. 2014

Proceedings of International Electronic Conference on Sensors and Applications

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Abstract:One of the main challenges in the implementation and design of context-aware scenarios is the adequate deployment strategy for Wireless Sensor Networks (WSNs), mainly due to the strong dependence of the radiofrequency physical layer with the surrounding media, which can lead to non-optimal network designs. In this work, radioplanning analysis for WSN deployment is proposed by employing a deterministic 3D ray launching technique in order to provide insight into complex wireless channel behavior in context-aware indoor scenarios. The proposed radioplanning procedure is validated with a testbed implemented with a Mobile Ad Hoc Network WSN following a chain configuration, enabling the analysis and assessment of a rich variety of parameters, such as received signal level, signal quality and estimation of power consumption. The adoption of deterministic radio channel techniques allows the design and further deployment of WSNs in heterogeneous wireless scenarios with optimized behavior in terms of coverage, capacity, quality of service and energy consumption. OPEN ACCESSSensors 2015, 15 3767

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Evaluation of Electromagnetic Dosimetry of Wireless Systems in Complex Indoor Scenarios With Human Body Interaction

Cited by 58 publications

References 46 publications

Systematic Predictive Analysis of Personalized Life Expectancy Using Smart Devices

Systematic Predictive Analysis of Personalized Life Expectancy Using Smart Devices

Analysis of Radio Wave Propagation for ISM 2.4GHz Wireless Sensor Networks in Inhomogeneous Vegetation Environments

Analysis of Wireless Sensor Network Topology and Estimation of Optimal Network Deployment by Deterministic Radio Channel Characterization

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