• International conference on construction engineering and project management
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• 2007.03a
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• pp.88-95
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• 2007

In this paper, the authors discussed the overview of a method for estimating working area for development of a monitoring system for labor management using RFID technology. RSSI (Receive Signal Strength Indication) data of RFID tag was obtained from readers set around the indoor space. An estimating model of the working area was prepared. The model had a range of the percentage of correctly classified from 61% to 95%. According to the result, the possibility of the monitoring system and the factors necessary to develop for practical were proposed.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.491-496
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• 2005

In this paper, the authors explained the overview of a method for detecting location of worker for development of a monitoring system for project progress management using RFID technology. Data is the RSSI (Receive Signal Strength Indication) from RFID tag attached to the worker installing a rolling shutter, and was obtained from antennas and RFID readers set around the construction site. Neural network was done using RSSI collected and the area where worker is performing a task, and an estimation model of the working area was prepared. The network had a range of the percentage of correctly classified from 62% to 92%. The authors suggested the method to make estimate by using integrated networks prepared in respect of RFID readers, and showed the percentage of correctly classified of 84.3%. According to the result, the authors confirmed the possibility of the monitoring system with RFID technology, and mentioned the factors necessary to develop for further practical use.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.6
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• pp.1123-1128
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• 2016

Recently BLE beacon has been widely used as a method for measuring the indoor location in the IoT Technique. But it requires a filtering technique for the measurement of the correct position. It is used the most fixed beacon. It is not accurate that calculates the position information through the identification of the beacon signal. Therefore, filtering is important. So it takes a lot of time, position measurement and filtering. Thus, we is to measure the exact position at the indoor using a mobile beacon. The measured beacon signal is composed of an ontology for reuse in the same pattern. RSSI is measured the receiver is the distance of the beacon. And this value configure the location ontology to be normalized by the relationship analysis between the values. The ontology is a method for calculating the position information of the moving beacon. It can detect fast and accurate indoor position information and provide the service.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.05a
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• pp.326-327
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• 2016

A study on Ontology-based indoor positioning techniques using BLE Beacon. Recently BLE beacon has been widely used as a technique for measuring the indoor location. But it requires a filtering technique for the measurement of the correct position, and uses the most fixed beacon. It is not accurate that calculates the position information through the identification of the beacon signal. Therefore, filtering is important. So it takes a lot of time, position measurement and filtering. Thus, we is to measure the exact position at the indoor using a mobile beacon. The measured beacon signal is composed of an ontology for reuse in the same pattern. RSSI is measured the receiver is the distance of the beacon. And this value configure the location ontology to be normalized by the relationship analysis between the values. The ontology is a method for calculating the position information of the moving beacon. It may be detected fast and accurate indoor position information.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.4
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• pp.1854-1868
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• 2018

A wireless body-sensor network (WBSN) refers to a network-configured environment in which sensors are placed on both the inside and outside of the human body. The sensors are much smaller and the energy is more constrained when compared to traditional wireless sensor network (WSN) environments. The critical nature of the energy-constraint issue in WBSN environments has led to numerous studies on the reduction of energy consumption of WBSN sensors. The transmission-power-control (TPC) technique adjusts the transmission-power level (TPL) of sensors in the WBSN and reduces the energy consumption that occurs during communications. To elaborate, when transmission sensors and reception sensors are placed in various parts of the human body, the transmission sensors regularly send sensor data to the reception sensors. As the reception sensors receive data from the transmission sensors, real-time measurements of the received signal-strength indication (RSSI), which is the value that indicates the channel status, are taken to determine the TPL that suits the current-channel status. This TPL information is then sent back to the transmission sensors. The transmission sensors adjust their current TPL based on the TPL that they receive from the reception sensors. The initial TPC algorithm made linear or binary adjustments using only the information of the current-channel status. However, because various data in the WBSN environment can be utilized to create a more efficient TPC algorithm, many different types of TPC algorithms that combine human movements or fuse TPC with other algorithms have emerged. This paper defines and discusses the design and development process of an efficient TPC algorithm for WBSNs. We will describe the WBSN characteristics, model, and closed-loop mechanism, followed by an examination of recent TPC studies.