Wireless sensor networks for health monitoring

Jafari, Roozbeh; Encarnacao, Andre Villanova; Zahoory, A.; Dabiri, Foad; Noshadi, Hyduke; Sarrafzadeh, Majid

doi:10.1109/mobiquitous.2005.65

Cited by 91 publications

(45 citation statements)

References 4 publications

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“…Pemegang peranan penting dalam UMS ini adalah penggunaan wireless sensor node [8]. Data parameter air yang terdiri dari: data temperatur, pH, DO dan EC diperoleh dari unit sensor yang secara langsung kontak dengan sumber air.…”

Section: Hasil Dan Pembahasanunclassified

Komunikasi Data Berbasis Protokol UDP pada Sistem Ubiquitous Mobile Sensing Kualitas Sumber Air

Darsono¹,

Adianto

Apriani

2016

Indonesian J. Comput. Cybern. Syst.

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Section: Hasil Dan Pembahasanunclassified

Komunikasi Data Berbasis Protokol UDP pada Sistem Ubiquitous Mobile Sensing Kualitas Sumber Air

Darsono¹,

Adianto

Apriani

2016

Indonesian J. Comput. Cybern. Syst.

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“…Well-known projects and prototype architectures in this area include MIThril [4], CustoMed [11], Wearable e-Textiles [5], Wearable Motherboard [17], e-Textile [12], and RFab-Vest [10]. Growth in this area has been largely fueled by the recent technological advancements in embedded processors, availability of lightweight sensor nodes, and advances in wireless networking.…”

Section: Introductionmentioning

confidence: 99%

“…As a result, both computation bandwidth and power consumption turn out to be serious constraints while designing sensor network-based computing platforms for high-end biomonitoring applications. This has led to a trememdous interest in architectures, design methods and software analysis techniques specifically targeted towards wireless BANs and wearable-computing related applications such as biomonitoring (for example, see [6,7,11,13] and the references therein).…”

Section: Introductionmentioning

confidence: 99%

Cache-aware optimization of BAN applications

Liang

Chakraborty³

et al. 2009

Des Autom Embed Syst

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Body-area sensor network or BAN-based health monitoring is increasingly becoming a popular alternative to traditional wired biomonitoring techniques. However, most biomonitoring applications need continuous processing of large volumes of data, as a result of which both power consumption and computation bandwidth turn out to be serious constraints for sensor network platforms. This has resulted in a lot of recent interest in design methods, modeling and software analysis techniques specifically targeted towards BANs and applications running on them. In this paper we show that appropriate optimization of the application running on the communication gateway of a wireless BAN and accurate modeling of the microarchitectural details of the gateway processor can lead to significantly better resource usage and power savings. In particular, we propose a method for deriving the optimal order in which the different sensors feeding the gateway processor should be sampled, to maximize cache re-use. Our case study using a faint fall detection application -from the geriatric care domain -which is fed by a number of smart sensors to detect physiological and physical gait signals of a patient show very attractive energy savings in the underlying processor. Alternatively, our method can be used to improve the sampling frequency of the sensors, leading to higher reliability and better response time of the application.

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“…Aggregation is useful for building such models that can be later used for various mining techniques (clustering, classification, etc.). In this paper, we are interested in the continuous approximation of aggregates for long-term monitoring in sensor networks that have a variety of real world applications such as monitoring air pollution [2], wild life habitats [3] and health conditions of residents [4]. In these applications, there is usually a query node in the network which continuously evaluates the aggregate query for all sensors.…”

Section: Introductionmentioning

confidence: 99%

Region Sampling: Continuous Adaptive Sampling on Sensor Networks

Lin

Arai

Gunopulos

et al. 2008

2008 IEEE 24th International Conference on Data Engineering

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Abstract-Satisfying energy constraints while meeting performance requirements is a primary concern when a sensor network is being deployed. Many recent proposed techniques offer error bounding solutions for aggregate approximation but cannot guarantee energy spending. Inversely, our goal is to bound the energy consumption while minimizing the approximation error. In this paper, we propose an online algorithm, Region Sampling, for computing approximate aggregates while satisfying a pre-defined energy budget. Our algorithm is distinguished by segmenting a sensor network into partitions of non-overlapping regions and performing sampling and local aggregation for each region. The sampling energy cost rate and sampling statistics are collected and analyzed to predict the optimal sampling plan. Comprehensive experiments on real-world data sets indicate that our approach is at a minimum of 10% more accurate compared with the previously proposed solutions.

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Wireless sensor networks for health monitoring

Cited by 91 publications

References 4 publications

Komunikasi Data Berbasis Protokol UDP pada Sistem Ubiquitous Mobile Sensing Kualitas Sumber Air

Komunikasi Data Berbasis Protokol UDP pada Sistem Ubiquitous Mobile Sensing Kualitas Sumber Air

Cache-aware optimization of BAN applications

Region Sampling: Continuous Adaptive Sampling on Sensor Networks

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