A framework for collaborative computing and multi-sensor data fusion in body sensor networks

Fortino, Giancarlo; Galzarano, Stefano; Gravina, Raffaele; Li, Wenfeng

doi:10.1016/j.inffus.2014.03.005

Cited by 259 publications

(97 citation statements)

References 25 publications

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“…Edge cloud and remote cloud serve as the storage and computing infrastructure of the system. The variety of terminals, such as smart terminals, humanoid robots, smart clothing and smart cars, etc., utilize various radio access technologies, forming the cognitive sensing layer (or the infrastructure layer) of the system [29][30][31][32].…”

Section: Network Architecture Of 5g-csysmentioning

confidence: 99%

A 5G Cognitive System for Healthcare

Chen

Yang

Hao

et al. 2017

BDCC

119

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Developments and new advances in medical technology and the improvement of people's living standards have helped to make many people healthier. However, there are still large design deficiencies due to the imbalanced distribution of medical resources, especially in developing countries. To address this issue, a video conference-based telemedicine system is deployed to break the limitations of medical resources in terms of time and space. By outsourcing medical resources from big hospitals to rural and remote ones, centralized and high quality medical resources can be shared to achieve a higher salvage rate while improving the utilization of medical resources. Though effective, existing telemedicine systems only treat patients' physiological diseases, leaving another challenging problem unsolved: How to remotely detect patients' emotional state to diagnose psychological diseases. In this paper, we propose a novel healthcare system based on a 5G Cognitive System (5G-Csys). The 5G-Csys consists of a resource cognitive engine and a data cognitive engine. Resource cognitive intelligence, based on the learning of network contexts, aims at ultra-low latency and ultra-high reliability for cognitive applications. Data cognitive intelligence, based on the analysis of healthcare big data, is used to handle a patient's health status physiologically and psychologically. In this paper, the architecture of 5G-Csys is first presented, and then the key technologies and application scenarios are discussed. To verify our proposal, we develop a prototype platform of 5G-Csys, incorporating speech emotion recognition. We present our experimental results to demonstrate the effectiveness of the proposed system. We hope this paper will attract further research in the field of healthcare based on 5G cognitive systems.

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Section: Network Architecture Of 5g-csysmentioning

confidence: 99%

A 5G Cognitive System for Healthcare

Chen

Yang

Hao

et al. 2017

BDCC

119

View full text Add to dashboard Cite

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“…Multi-sensor nodes data fusion is one of the common CBSNs that are integral to joint data analysis like synchronized data integration and classification, filtering, time-dependent solutions. CBSNs can usually program using C-SPINE [18], wherein the extension of SPINE framework is imperative [19]. Using the C-SPINE, the e-shake CBSN systems were developed [20].…”

Section: Improving the Battery Lifementioning

confidence: 99%

Innovative Data Transmission and Routing Strategies of Wireless Body Area Sensor Networks: Taxonomy, Review, Issues and Constraints of State of the Art Contributions in Recent Literature

Reddy¹,

Ram²

2018

IJET

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Wireless body area sensor networks (WBASN) is an effective solution that has proposed in terms of improving the solutions and their varied benefits that have been achieved from the usage of WBASN solutions in communication, healthcare domain. From the review of stats on rising number of wireless devices and solutions that are coming up which is embraced by the people as wearable devices, implants for medical diagnostic solutions, etc. reflect the growing demand for effective models. However, the challenge is about the effective performance of such solutions with optimal efficiency. Due to certain intrinsic factors like numerous standards that are available, and due to the necessity for identifying the best solutions that are based on application requirements. Some of the key issues that have to be considered in the process of WBASN are about the impacts that are taking place from the wireless medium, the lifetime of batteries in the WBASN devices and the other significant condition like the coexistence of the systems among varied other wireless networks that are constituted in the proximity. In this study, scores of models that have propose pertaining to MAC protocols for WBASN solutions have reviewed to understand the efficacy of the existing systems, and a scope for process improvement has explored for conducting in detail research and developing a solution.

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“…In particular, the BMFAdapter [10] and the SPINEAdapter [11][12][13] enable the management of environmental and wearable sensor networks.…”

Section: Agent-oriented Modeling and Simulation Of Iot Networkmentioning

confidence: 99%

Agent-oriented Modeling and Simulation of IoT Networks

Fortino

2016

Annals of Computer Science and Information Systems

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Abstract-Internet of Things (IoT) networks are being continually developed in several domains, however no systematic processes for their modeling and simulation exist so far. In this paper, an agent-oriented approach to IoT networks modeling is proposed by exploiting the ACOSO model. As IoT networks share many substantial features/issues with multi-agent systems (MAS) [3] and SOs may be effectively modeled as agents, in this paper an agent-oriented approach to model IoT networks is presented. In particular, the ACOSO (Agent-based Cooperative Smart Object)-based SO model [4] has been exploited to describe, from the agent perspective, SO main features, relationships and interactions.Moreover, in order to analyze IoT networks at SO communication level, the Omnet++ [5] network simulation platform has been used to evaluate bottlenecks and issues in specifically defined scenarios. The rest of the paper is organized as follows: in Section II, the ACOSO-based SO model and other concrete examples of the Agent-oriented Modeling (AoM) applied to the SO-based IoT context are

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A framework for collaborative computing and multi-sensor data fusion in body sensor networks

Cited by 259 publications

References 25 publications

A 5G Cognitive System for Healthcare

A 5G Cognitive System for Healthcare

Innovative Data Transmission and Routing Strategies of Wireless Body Area Sensor Networks: Taxonomy, Review, Issues and Constraints of State of the Art Contributions in Recent Literature

Agent-oriented Modeling and Simulation of IoT Networks

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