Smart sensor architecture for mobile-terminal-centric ambient intelligence

Jantunen, Iiro; Laine, Hannu; Huuskonen, Pertti; Trossen, Dirk; Ermolov, Vladimir

doi:10.1016/j.sna.2007.04.014

Cited by 40 publications

(22 citation statements)

References 2 publications

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“…In Fig. 6, we summarize the core architectural components that constitute body sensor system designs in terms of above aspects, and categorize some existing BAN projects, such as CodeBlue [47], AID-N [19], SMART [12], CareNet [28], ASNET [46], MITHril [37], WHMS [34], WiMoCa [16] and MIMOSA [27]. With regards to BAN applications, Fig.…”

Section: A Taxonomy Of Body Sensor Projectsmentioning

confidence: 99%

Body Area Networks: A Survey

et al. 2010

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Section: A Taxonomy Of Body Sensor Projectsmentioning

confidence: 99%

Body Area Networks: A Survey

et al. 2010

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“…Internet/WiFi/Cellular networks are used in CareNet [8], WiMoCA [9], and MIMOSA [10]. In more detail, CareNet effectively addresses reliability as well as privacy-preserving patient data transmission.…”

Section: Related Workmentioning

confidence: 99%

Vertical Handover Algorithm for WBANs in Ubiquitous Healthcare with Quality of Service Guarantees

Van

Liu

2017

Information

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Abstract:Recently, Wireless Body Area Networks (WBANs) have become an emerging technology in healthcare, where patients are equipped withwearable and implantable body sensor nodes to gather sensory information for remote monitoring. The increasing development of coordinator devices on patients enables the internetworking of WBANs in heterogeneous wireless networks to deliver physiological information that is collected at remote terminals in a timely fashion. However, in this type of network, providing a seamless handover with a guaranteed Quality of Service (QoS), especially emergency services, is a challenging task. In this paper, we proposed an effective Multi-Attribute Decision-Making (MADM) handover algorithm that guarantees seamless connectivity. A patient's mobile devices automatically connect to the best network that fulfills the QoS requirements of different types of applications. Additionally, we integrated a Content-Centric Networking (CCN) processing module into different wireless networks to reduce packet loss, enhance QoS and avoid unnecessary handovers by leveraging in-network caching to achieve efficient content dissemination for ubiquitous healthcare. Simulation results proved that our proposed approach forthe model with CCN outperforms the model without CCN and Received Signal Strength Vertical Handoff (RSS-VHD) in terms of the number of handovers, enhancing QoS, packet loss, and energy efficiency.

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“…The requirements for an environment to be called intelligent are fulfilled by Bluetooth standard [9]. This technology has been included in the data transportation network of many proposals for intelligent environment systems [11][12][13]. Actually, Bluetooth protocols have significant potential to support deterministic behavior, i.e., real-time, asynchronous communication [14].…”

Section: Bluetooth Applied To Intelligent Systemsmentioning

confidence: 99%

Low Power Multi-Hop Networking Analysis in Intelligent Environments

Etxaniz¹,

Aranguren²

2017

Preprint

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Intelligent systems are driven by the latest technological advances in so different areas as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues on embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide.

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Smart sensor architecture for mobile-terminal-centric ambient intelligence

Cited by 40 publications

References 2 publications

Body Area Networks: A Survey

Body Area Networks: A Survey

Vertical Handover Algorithm for WBANs in Ubiquitous Healthcare with Quality of Service Guarantees

Low Power Multi-Hop Networking Analysis in Intelligent Environments

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