• Journal of the Korea Institute of Information and Communication Engineering
• /
• v.11 no.3
• /
• pp.627-633
• /
• 2007

This paper describes position tracking system of a container trailer approaching to a gantry crane for loading or unloading a container into or from a ship, respectively. Proposed position tracking system informs the trailer driver of right position to stop the car under a gantry crane. To measure the location of a trailer, we used Cricket Mote modules which adopted RF and ultrasound technology. We present an elaborate method to improve position errors occurring at sensing and calculate three dimensional position by triangulation along with how to reduce location tracking interval for real-time monitoring. The location information was transmitted to a Personal Digital Assistant (PDA) periodically through Bluetooth communication for guidance of the trailer driver. In indoor and outdoor tests, position errors were less than 3 cm and location tracking interval was 0.5 second on average.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2008.06a
• /
• pp.279-280
• /
• 2008

• Proceedings of the KSR Conference
• /
• 2003.10c
• /
• pp.568-573
• /
• 2003

This paper proposed to recognize and tracking the ID and location when a person and objects moved from indoor using RFID a type of passive tag. An antenna was installed in both sides of a door due to the limitation of a recognition distance. And frequency bandwidth was used to the 134.2kHz bandwidth to pass and bend several obstacles. Because a type of passive tag is a semi -permanent and miniaturization, it has applied to this paper.

• The Journal of Korean Institute of Information Technology
• /
• v.17 no.2
• /
• pp.71-77
• /
• 2019

With 5G standards proceeding in earnest and increasing demand for services of indoor localization, research on indoor location recognition is being studied in various industrial fields, and research based on fingerprint recognition technology using Wireless Local Area Network (WLAN) is representative. In this paper, we propose an indoor positioning system based on fingerprinting technique that uses Cloud Radio Access Network (C-RAN) architecture and Channel State Information (CSI). In order to improve the performance in indoor positioning, we combined existing fingerprinting method and K nearest neighbor (KNN) technology which is one of the machine running technique. The performance improvements of the proposed indoor positioning system was verified by comparative experiments with the existing localization technique in a indoor localizztion testbed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.4
• /
• pp.315-325
• /
• 2014

In ubiquitous environment, User's location information is very important to serve personalized service to user. Previous works consider only User's locations in the big buildings and assume APs are fixed. Normal home environment, However, is consists of small spaces. And the state of APs is highly fluid. Previous research has focused on indoor localization in the building where has stationary AP environment. However, in this paper, we propose as User's Location Predicting System that finds out a space where a user is located based on Wi-Fi Fingerprint approach in home environments. The results that conducted real home environments are using the system show more than 80% accuracy.

• The Journal of Korean Institute of Next Generation Computing
• /
• v.14 no.6
• /
• pp.57-65
• /
• 2018

Conventional RF signal-based indoor localization techniques such as BLE or Wi-Fi based fingerprinting method show considerable localization errors even in small-scale indoor environments due to unstable received signal strength(RSS) of RF signals. Therefore, it is difficult to apply the existing RF-based fingerprinting techniques to large-scale indoor environments such as airports and department stores. In this paper, instead of RF signal we use the geomagnetic sensor signal for indoor localization, whose signal strength is more stable than RF RSS. Although similar geomagnetic field values exist in indoor space, an object movement would experience a unique sequence of the geomagnetic field signals as the movement continues. We use a deep neural network model called the recurrent neural network (RNN), which is effective in recognizing time-varying sequences of sensor data, to track the user's location and movement path. To evaluate the performance of the proposed geomagnetic field based indoor positioning system (IPS), we constructed a magnetic field map for a campus testbed of about $94m{\times}26$ dimension and trained RNN using various potential movement paths and their location data extracted from the magnetic field map. By adjusting various hyperparameters, we could achieve an average localization error of 1.20 meters in the testbed.

• Journal of Korean Society for Atmospheric Environment
• /
• v.14 no.E
• /
• pp.1-7
• /
• 1998

This paper presents an experimental study for understanding the indoor air quality in a room. A model room, which had a ceiling-mounted supply and a sidewall-mounted exhaust, was used to examine the effect of air exchange rate (AER) and contaminant source location (CSL) as a function of the elapsed time. A tracer gas method, using carbon monoxide tracer, gas analyzers, and a data acquisition system, was applied to study the ventilation air distribution and the tracer removal efficiency, so-called pollutant removal efficiency, in the model room. The experiment was composed of two parts; firstly the AER was varied to examine its effect on the ventilation air distribution and the ventilation effectiveness and secondly both AER and CSL were considered to determine their effect on the pollutant removal efficiency. It was found that the ventilation effectiveness in the model was proportional to AER but not linearly. It was also found that changing the CSL can improve the pollutant removal efficiency. In some cases, the efficiency improvement by increasing AER was achieved by simply changing CSL.

• Journal of Institute of Control, Robotics and Systems
• /
• v.14 no.9
• /
• pp.925-930
• /
• 2008

Many sensor network applications require that each node's sensor data stream be annotated with its physical location in some coordinate system. Equipping GPS on every sensor node is often expensive and does not work in indoor deployments. Recently, cricket-based localization system is often used for indoor localization system. It is very important to know the exact position of beacons in cricket-based localization system for identifying moving sensor node's position. In this paper, a new method, Mobile Listener Detect Algorithm (MLD) which can automatically calculate the unknown newly installed beacons is proposed. For the verification of the feasibility of the proposed scheme, we have conducted several experiments.

• Proceedings of the Korean Institute of Communication Sciences Conference
• /
• 2006.07a
• /
• pp.345-345
• /
• 2006

• The KIPS Transactions:PartC
• /
• v.17C no.3
• /
• pp.251-258
• /
• 2010

In an indoor localization method taking the lateration-based approach, the location of a target is estimated with the location of anchor points (APs) and the approximated distances between the target and APs using received signal strength (RSS) measurements. The accuracy of distance estimation affects the localization accuracy of a lateration-based method. Since a radio propagation environment varies randomly in time and space, the highest RSSs do not necessarily give the best estimation of the distances between a target and APs. Thus, all APs hearing a target have been used for localization. However, the accuracy of a lateration-based method degrades if more APs beyond a certain threshold are used because the area of polygon with the APs increases. In this paper, we focus on reducing the size of the polygon to further increase the localization accuracy. We use the centroid of the polygon as a reference point to estimate the relative location of a target in the polygon. Once the relative location is estimated, only the APs which are closest to the target are used for localization to reduce the area of the polygon with the APs. We validate the proposed method by implementing an indoor localization system and evaluating the accuracy of the proposed method in the various experimental environments.