• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.860-863
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• 2010

Wireless sensor networks consist of small, autonomous devices with wireless networking capabilities. In order to further increase the applicability in real world applications, minimizing energy consumption is one of the most critical issues. Therefore, accurate energy model is required for the evaluation of wireless sensor networks. In this paper, we analyze the energy consumption for wireless sensor networks. To estimate the lifetime of sensor node, we have measured the energy characteristics of sensor node based on Telosb platforms running TinyOS. Based on the proposed model, the estimated lifetime of a battery powered sensor node can use about 6.925 months for 10 times motion detection per hour.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2007.10a
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• pp.518-521
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• 2007

The functional wireless sensor node for u-healthcare application was developed. The developed sensor node can check the abnormality of ECG in some simple software in ROM of microprocess in the sensor node. The ECG signal is one of very important health signal form human body, and wavelike signal which is sampled as a sampling frequency between 100 and 400 Hz for digitalization, so the wireless data dor ECG signal is some heavy in Zigbee communication. Thus the sensor send the ECG signal to other sensor nodes or base station when it find abnormality in ECG signal is key technology to reduce the traffic between sensor nodes in wireless sensor network for u-healthcare, The sensor node does not need to transmit ECG data all time in wireless sensor network and to server. Using these sensor nodes, the healthcare system can dramatically reduce wireless data packet overload, the power consumption of battery in the sensor nodes and thus increase the reliability of the wireless system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.8
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• pp.1820-1831
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• 2011

When both types of periodic and aperiodic tasks are required to run on a sensor node platform with limited energy resources, we propose an energy-efficient hybrid task scheduling technique that guarantees the deadlines of real-time tasks and provides non-real-time tasks with good average response time. The proposed hybrid task scheduling technique achieved better performance than existing EDF-based DVS scheduling techniques available in the literature, the FIFO-based TinyOS scheduling technique, and the task-clustering based non-preemptive real-time scheduling technique.

• The KIPS Transactions:PartA
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• v.18A no.6
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• pp.255-264
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• 2011

A sensor network is a special network that makes physical data sensed by sensor nodes and manages the data. The sensor network is a technology that can apply to many parts of field. It is very important to transmit the data to a user at real-time. The core of the sensor network is a sensor node and small operating system that works in the node. TinyOS developed by UC Berkeley is a sensor network operating system that used many parts of field. It is event-driven and component-based operating system. Basically, it uses non-preemptive scheduler. If an urgent task needs to be executed right away while another task is running, the urgent one must wait until another one is finished. Because of that property, it is hard to guarantee real-time requirement in TinyOS. According to recent study, Priority Level Scheduler, which can let one task preempt another task, was proposed in order to have fast response in TinyOS. It has restrictively 5 priorities, so a higher priority task can preempt a lower priority task. Therefore, this paper suggests Preemptive EDF(Earliest Deadline First) Scheduler that guarantees a real-time requirement and reduces average respond time of user tasks in TinyOS.

• Journal of Institute of Control, Robotics and Systems
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• v.14 no.7
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• pp.720-725
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• 2008

This paper proposes a system architecture for USN with a service robot to provide more active assisted living services for elderly persons by monitoring their mental and physical well-being with USN environments at home, hospital, or silver town. Sensors embedded in USN are used to detect preventive measures for chronic disease. Logged data are transferred to main controller of a service robot via wireless channel in which the analysis of data is performed. For the purpose of handling emergency situations, it needs real-time processing on gathering variety sensor data, routing algorithms for sensor nodes to a moving sink node and processing of logged data. This paper realized multi-hop sensor network to detect user movements with biometric data transmission and performed algorithms on Xenomai, a real-time embedded Linux. To leverage active sensing, a mobile robot is used of which task was implemented with a priority to process urgent data came from the sink-node. This software architecture is anticipated to integrate sensing, communication and computing with real-time manner. In order to verify the usefulness of a proposed system, the performance of data transferring and processing on a real-time OS with non real-time OS is also evaluated.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.689-709
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• 2010

In this paper, a low cost, low power but multifunctional wireless sensor node is presented for the impedance-based SHM using piezoelectric sensors. Firstly, a miniaturized impedance measuring chip device is utilized for low cost and low power structural excitation/sensing. Then, structural damage detection/sensor self-diagnosis algorithms are embedded on the on-board microcontroller. This sensor node uses the power harvested from the solar energy to measure and analyze the impedance data. Simultaneously it monitors temperature on the structure near the piezoelectric sensor and battery power consumption. The wireless sensor node is based on the TinyOS platform for operation, and users can take MATLAB$^{(R)}$ interface for the control of the sensor node through serial communication. In order to validate the performance of this multifunctional wireless impedance sensor node, a series of experimental studies have been carried out for detecting loose bolts and crack damages on lab-scale steel structural members as well as on real steel bridge and building structures. It has been found that the proposed sensor nodes can be effectively used for local wireless health monitoring of structural components and for constructing a low-cost and multifunctional SHM system as "place and forget" wireless sensors.

• Journal of the Korea Society of Computer and Information
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• v.11 no.6 s.44
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• pp.143-150
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• 2006

In this paper, we have implemented a ubiquitous healthcare system that can measure and check the blood pressure of human in anytime and anywhere. The implemented prototype are composed of blood pressure measurement terminal, data gathering base node, and medial information server. The implemented node constructs a sensor network using the Zigbee protocol and is ported the TinyOS. The data gathering base node is linux-based node that can transfer a sensed medial data through wireless LAN. And, the medical information server stores the processed medical data and can promptly notify the urgent status to the connected medical team. Through experiment, we confirmed the possibility of ubiquitous healthcare system based on sensor network using the Zigbee.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.1
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• pp.227-232
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• 2011

The QRS complex in ECG analysis is possible to obtain much information that is helpful for diagnosing different types of cardiovascular disease. This paper presents the preprocessor method to detect R-peak, RR interval, and HRV in wireless sensor node. The derivative of the electrocardiogram is efficiency of preprocessing method for resource hungry wireless sensor node with low computation. We have implemented R-peak and RR interval detection application based on dECG for wireless sensor node. The sensor node only transfers meaning parameter of ECG. Thus, implementation of sensor node can save power, reduce traffic, and eliminate congestion in a WSN.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.9A
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• pp.884-891
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• 2006

A wireless sensor node is typically battery operated and energy constrained. Therefore it is critical to design efficient power management technique and scheduling technique. In this paper, we propose an OS-level power management technique for energy saving of wireless sensor node, it is called EA-SENTAS (Energy-Aware Sensor Node TAsk Scheduling). It can decrease the energy consumption of a wireless sensor node to use task scheduling technique that shut down components or use low power mode of each component when not needed. Simulation results show that EA-SENTAS saves energy up to 56 percent to compare with conventional duty cycle.

• The KIPS Transactions:PartC
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• v.14C no.4
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• pp.371-382
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• 2007

In this paper, we propose a real-time sensor node platform that efficiently manages periodic and aperiodic tasks. Since existing sensor node platforms available in literature focus on minimizing the usage of memory and power consumptions, they are not capable of supporting the management of tasks that need their real-time execution and fast average response time. We first analyze how to structure periodic or aperiodic task decomposition in the TinyOS-based sensor node platform as regard to guaranteeing the deadlines of ail the periodic tasks and aiming to providing aperiodic tasks with average good response time. Then we present the application and efficiency of the proposed real-time sensor node platform in the sensor node equipped with a low-power 8-bit microcontroller, an IEEE802.15.4 compliant 2.4GHz RF transceiver, and several sensors. Extensive experiments show that our sensor node platform yields efficient performance in terms of three significant, objective goals: deadline miss ratio of periodic tasks, average response time of aperiodic tasks, and processor utilization of periodic and aperiodic tasks.