• International Journal of Internet, Broadcasting and Communication
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• v.10 no.2
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• pp.51-59
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• 2018

Health care has attracted a lot of attention, recently due to an increase in life expectancy and interest in health. Various biometric data of the user are collected by using the air pressure sensor, gyro sensor, acceleration sensor, and heart rate sensor to perform the Smart Health Care Activity Tracker function. Basically, smartphone application is made and tested for biometric data collection, but the Arduino platform and bio-signal measurement sensor are used to confirm the accuracy of the measured value of the smartphone. Use the Google Maps API to set user goals and provide guidance on the location of the user and the points the user wants. Also, the basic configuration of the main UI is composed of the screen of the camera, and it is possible for the user to confirm the forward while using the application, so that accident prevention is possible.

• Smart Media Journal
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• v.5 no.3
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• pp.74-80
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• 2016

In this paper, we propose an accident-prevention smart monitoring system for Haenyeo(Woman diver) using Zigbee module and GPS sensor. This system can collect such information as the diving location, the body temperature, the depth of diving, and the diving time of a Woman diver working under the water and then respond immediately to an accident occurring. The research developed a smart Teawak and smart swimming goggles which can measure the state of a Woman diver and her diving activities. Smart Teawak, the buoy tool while a Woman diver is collecting seafoods under water, is able to receive GPS and transmit the data from smart swimming goggles and Zigbee Module to IHSS(IoT based Haenyeo Safety service Software) server. In addition, IHSS, a responsive web, provides the diving location and the state of a Woman diver on the smart phone. As a result, the system will be useful in the aspects of Woman diver' health care and the safety, furthermore, which will significantly contribute to global marketing of Woman diver with its being designated as a UNESCO intangible cultural asset.

• Journal of Sensor Science and Technology
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• v.29 no.5
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• pp.293-302
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• 2020

Food safety has emerged as a growing concern for human health in recent times. Consuming contaminated food may lead to serious health problems, and therefore, a system for monitoring food freshness that is both non-detrimental to the quality of food and highly accurate is required to ensure that only high-quality fresh food packages are provided to the customers. This paper proposes a method to monitor and detect food quality using a compact smart sensor tag. The smart tag is composed of three ultra-low-power sensors, which monitor four major indicators of food freshness: temperature, humidity, and the concentrations of ammonia and hydrogen sulfide gases. An RF energy scavenging circuit is integrated into the smart sensor tag to harvest energy from radio waves at a high frequency of 13.56 MHz to supply sufficient power to the tag. Experimental results show that the proposed energy harvester can efficiently obtain energy at a distance of approximately 40 cm from a 4 W reader. In addition, the proposed smart sensor tag can operate without any battery, thereby eliminating the requirement of frequent battery replacement and consequently decreasing the cost. Meanwhile, the freshness of preserved pork is continuously monitored under two conditions--room temperature and refrigerator temperature--both of which are the most common temperatures under which food is generally stored. The food-monitoring experiments are conducted over a period of one week using the proposed battery-less tag. Based on the experimental results, the food assessment is classified into four categories: fresh, normal, low, and spoiled.

• Journal of the Korea institute for structural maintenance and inspection
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• v.17 no.2
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• pp.1-9
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• 2013

In recent years, numerous mega-size and complex civil infrastructures have been constructed worldwide. For the more precise construction and maintenance process management of these civil infrastructures, the application of a variety of smart sensor-based structural health monitoring (SHM) systems is required. The efficient management of both sensors and collected databases is also very important. Recently, several kinds of database access technologies using Quick Response (QR) code and Augmented Reality (AR) applications have been developed. These technologies provide software tools incorporated with mobile devices, such as smart phone, tablet PC and smart pad systems, so that databases can be accessed very quickly and easily. In this paper, an AR-based structural health monitoring technique is suggested for sensor management and the efficient access of databases collected from sensor networks that are distributed at target structures. The global positioning system (GPS) in mobile devices simultaneously recognizes the user location and sensor location, and calculates the distance between the two locations. In addition, the processed health monitoring results are sent from a main server to the user's mobile device, via the RSS (really simple syndication) feed format. It can be confirmed that the AR-based structural health monitoring technique is very useful for the real-time construction process management of numerous mega-size and complex civil infrastructures.

• Structural Engineering and Mechanics
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• v.30 no.2
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• pp.191-209
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• 2008

A structural monitoring system based on cheap and wireless monitoring system is investigated in this paper. Due to low-cost and low power consumption, micro-electro-mechanical system (MEMS) is suitable for wireless monitoring and the use of MEMS and wireless communication can reduce system cost and simplify the installation for structural health monitoring. For system identification using wireless MEMS, a finite element (FE) model updating method through correlation with the initial analytical model of the structure to the measured one is used. The system identification using wireless MEMS is evaluated experimentally using a three storey frame model. Identification results are compared to ones using data measured from traditional accelerometers and results indicate that the system identification using wireless MEMS estimates system parameters with reasonable accuracy. Another smart sensor considered in this paper for structural health monitoring is Lead Zirconate Titanate (PZT) which is a type of piezoelectric material. PZT patches have been applied for the health monitoring of structures owing to their simultaneous sensing/actuating capability. In this paper, the system identification for building structures by using PZT patches functioning as sensor only is presented. The FE model updating method is applied with the experimental data obtained using PZT patches, and the results are compared to ones obtained using wireless MEMS system. Results indicate that sensing by PZT patches yields reliable system identification results even though limited information is available.

• Smart Structures and Systems
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• v.3 no.3
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• pp.299-320
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• 2007

Smart sensors densely distributed over structures can provide rich information for structural monitoring using their onboard wireless communication and computational capabilities. However, issues such as time synchronization error, data loss, and dealing with large amounts of harvested data have limited the implementation of full-fledged systems. Limited network resources (e.g. battery power, storage space, bandwidth, etc.) make these issues quite challenging. This paper first investigates the effects of time synchronization error and data loss, aiming to clarify requirements on synchronization accuracy and communication reliability in SHM applications. Coordinated computing is then examined as a way to manage large amounts of data.

• International Journal of Computer Science & Network Security
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• v.21 no.2
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• pp.221-228
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• 2021

Recent improvements on the quality, fidelity and availability of biometric data have led to effective human physical activity detection (HPAD) in real time which adds significant value to applications such as human behavior identification, healthcare monitoring, and user authentication. Current approaches usually use machine-learning techniques for human physical activity recognition based on the data collected from wearable accelerometer sensor from a single wearable smart device on the user. However, collecting data from a single wearable smart device may not provide the complete user activity data as it is usually attached to only single part of the user's body. In addition, in case of the absence of the single sensor, then no data can be collected. Hence, in this paper, a continuous HPAD will be presented to effectively perform user activity detection with mobile service infrastructure using multiple wearable smart devices, namely smartphone and smartwatch placed in various locations on user's body for more accurate HPAD. A case study on a comprehensive dataset of classified human physical activities with our HAPD approach shows substantial improvement in HPAD accuracy.

• Smart Structures and Systems
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• v.30 no.6
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• pp.583-599
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• 2022

In this paper, a multi-objective wireless sensor network configuration optimization method is proposed. The proposed method aims to determine the optimal information and lifespan wireless sensor network for structural health monitoring of large-scale infrastructures. In particular, cluster-based wireless sensor networks with multi-type of sensors are considered. To optimize the lifetime of the wireless sensor network, a cluster-based network optimization algorithm that optimizes the arrangement of cluster heads and base station is developed. On the other hand, based on the Bayesian inference, the uncertainty of the estimated parameters can be quantified. The coefficient of variance of the estimated parameters can be obtained, which is utilized as a holistic measure to evaluate the estimation accuracy of sensor configurations with multi-type of sensors. The proposed method provides the optimal wireless sensor network configuration that satisfies the required estimation accuracy with the longest lifetime. The proposed method is illustrated by designing the optimal wireless sensor network configuration of a cable-stayed bridge and a space truss.

• Journal of the Korean Society for Nondestructive Testing
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• v.27 no.4
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• pp.328-338
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• 2007

One of main advantages of composite using smart material as reinforcement can be controlled cracks behavior inside the composite. If the smart composite is applied as part of the structure, the use of the shape memory effect of the smart material is the best way to protect the propagation of cracks generated in the structure while use. In this study, the optical manufacturing conditions for the smart composite were derived. In order to evaluate the shape memory effect by shape memory alloy, the tensile load was applied to the smart composite and stress distribution was inspected. And then, the smart composite was heated to a certain temperature and the shape memory alloy would shrink to the original shape. Finally, at this point the recovering status of stress using photoelastic instrument was discussed.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2013.04a
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• pp.830-834
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• 2013

This study presents a method to monitor cable force of a long-span cable-stayed bridge using a smart piezoelectric sensor system. The following approaches are implemented in order to achieve the objective. Firstly, the method to utilize piezoelectric materials for the health monitoring of stay cables is presented. For strain measurement of a stay cable, a PZT-embedded smart skin is designed to overcome the difficulties of bonding PZT sensors directly on stay cables. Secondly, a piezoelectric strain monitoring system for stay cables is designed. For the operation of the sensor board, the Imote2 sensor platform is used to provide the computation, wireless communication and power supply units. The feasibility of the proposed monitoring system is then evaluated on a full-scale cable of a cable-stayed bridge.