News Letter on Wireless Sensors Network Research: February -2019

Online human movement classification victimisation wrist-worn wireless sensors

The observation and analysis of human motion will offer valuable data for numerous applications. This work offers a comprehensive summary regarding existing ways, and a model system is additionally given, capable of police investigation completely different human arm and body movements victimisation wrist-mounted wireless sensors. The wireless units are equipped with 3 tri-axial sensors, Associate in Nursing measuring system, a gyro, and a meter. information acquisition was in serious trouble multiple activities with the assistance of the used model system. a brand new on-line classification algorithmic program was developed, that permits simple implementation on the used hardware. To explore the best configuration, multiple datasets were tested victimisation completely different feature extraction approaches, sampling frequencies, process window widths, and used sensing element mixtures. The applied informationsets were made victimisation data collected with the assistance of multiple subjects. Results show that almost one thousandth recognition rate may be achieved on coaching information, whereas nearly ninetieth may be reached on validation information, that weren’t used throughout the coaching of the classifiers. This shows high correlation within the movements of various persons, since the coaching and validation datasets were made of knowledge from completely different subjects. [1]

Cluster head choice for energy economical and delay-less routing in wireless detector network

Wireless detector network (WSN) is comprised of small, low-cost and power-efficient detector nodes that effectively transmit knowledge to the bottom station. the most challenge of WSN is that the distance, energy and time delay. the facility resource of the detector node could be a non-rechargeable battery. Here the bigger the gap between the nodes, higher the energy consumption. For having the effective transmission of information with less energy, the cluster-head approach is employed. it’s well-known that the time delay is directly proportional to the gap between the nodes and therefore the base station. The cluster head is chosen in such some way that it’s spatially nearer enough to the bottom station further because the detector nodes. So, the time delay are often considerably reduced. This, in turn, the transmission speed of the info packets are often hyperbolic. Firefly rule is developed for increasing the energy potency of network and lifelong of nodes by choosing the cluster head optimally. during this paper firefly with cyclic organisation is planned for choosing the most effective cluster head. The network performance is hyperbolic during this methodology in comparison to the opposite standard algorithms. [2]

Health risk assessment and decision-making for patient watching and decision-support victimisation Wireless Body device Networks

This paper proposes a generalized multi-sensor fusion approach and a health risk assessment and decision-making (Health-RAD) formula for continuous and remote patient watching functions employing a Wireless Body device Network (WBSN). Health-RAD determines the patient’s health condition severity level habitually and every time a essential issue is detected supported very important signs scores. Hence, an eternal health assessment and a watching of the development or the deterioration of the state of the patient is ensured. The severity level is delineate by a risk variable whose values vary between zero and one. the upper the danger worth, the a lot of essential the patient’s health condition is and therefore the more it needs medical attention. Moreover, we have a tendency to calculate the score of a significant sign exploitation its past and current worth, so assessing its standing supported its evolution throughout a amount of your time and not solely on sharp deviations. we have a tendency to propose a generalized multi-sensor information fusion approach irrespective of the quantity of monitored very important signs. The latter is used by Health-RAD to seek out the severity level of the patient’s health condition supported his/her very important signs scores. it’s supported a fuzzy illation system (FIS) and early warning score systems (EWS). This approach is tested with a antecedently projected energy-efficient information assortment approach, so forming an entire framework. The projected approach is evaluated on real aid datasets and therefore the results are compared with another approach from the literature in terms of information reduction, energy consumption, risk assessment of important signs, the patient’s health risk level determination and accuracy. The results show that each approaches have coherently assessed the health condition of various medical care Unit (ICU) patients. Yet, our projected approach overcomes the opposite approach in terms of energy consumption (around eighty six less energy consumption) and information reduction (around seventieth for sensing and over ninetieth for transmission). in addition, contrary to our projected framework, the approach taken from the literature needs AN offline model building and depends on on the market patient datasets. [3]

Multi-hop communication: Frog choruses inspire wireless detector networks

If you’ve ever camped by a lake, you recognize frogs build a racket at night; however what you would possibly not know is however useful and controlled their choruses extremely are. Frogs communicate with sound, Associate in Nursingd amid their tumult is an internally musical organization system that lets info get through a lot of clearly whereas conjointly allowing collective choruses and time to rest. Researchers from port University and University of Tsukuba sought-after to leverage this amphibious acumen for mathematical and technological aims. [4]

A Wireless device Network for Examination group action Management System

Every tutorial institute has special issues for student’s group action in examination halls. At present, in developing countries group action is typically taken exploitation paper sheets and therefore the previous classification system. The effectiveness of this vogue is low as a result of it’s extremely effortful, erring, prone to examination malpractices, time wastage, information manipulation, and impersonation among others. On the opposite hand, Wireless detector Network is anxious with exploitation sensors technology to amass, store, trace and transfer examination group action information to the host laptop for report generation and data analysis. [5]



[1] Online human movement classification using wrist-worn wireless sensors

Sarcevic P, Kincses Z, Pletl S. Online human movement classification using wrist-worn wireless sensors. Journal of Ambient Intelligence and Humanized Computing. 2019 Jan 29;10(1):89-106. (web link)

[2] Cluster head selection for energy efficient and delay-less routing in wireless sensor network

Sarkar A, Murugan TS. Cluster head selection for energy efficient and delay-less routing in wireless sensor network. Wireless Networks. 2019 Jan 15;25(1):303-20. (web link)

[3] Health risk assessment and decision-making for patient monitoring and decision-support using Wireless Body Sensor Networks

Habib C, Makhoul A, Darazi R, Couturier R. Health risk assessment and decision-making for patient monitoring and decision-support using wireless body sensor networks. Information Fusion. 2019 May 1;47:10-22. (web link)

[4] Multi-hop communication: Frog choruses inspire wireless sensor networks

Date: January 22, 2019

Source: Osaka University (web link)

[5] A Wireless Sensor Network for Examination Attendance Management System

I. F. Obayemi

Information and Communication Technology Unit, Ladoke Akintola University of Technology, Ogbomoso, Nigeria.

O. T. Arulogun

Department of Computer Science and Engineering, Ladoke Akintola University of Technology, Ogbomoso, Nigeria.

A. S. Falohun

Department of Computer Science and Engineering, Ladoke Akintola University of Technology, Ogbomoso, Nigeria. (web link)

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