• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.29 no.5
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• pp.19-25
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• 2015

The management of energy resources for efficient utilization of the energy resources while reducing the system costs is a critical technical issue. Among many kinds of the energy resource management, the energy reduction for indoor lighting systems is getting much concern as a large portion of energy consumption has been made for indoor lightings. In this paper, an energy-efficient lighting control scheme for indoor lighting systems in order to reduce the energy consumption by controlling the luminous flux and the lighting direction under the illuminance constraints is proposed. With the use of the user location information for the luminaire which is closely located to the user, the proposed scheme firstly sets the light direction of the luminaire to be aligned to the user location. Then, an optimization problem to find the luminous flux of each luminaire is formulated in order to minimize the luminous flux sum of the luminaires with the constraints for the dynamic ragne of the luminous flux, and the light flux for each luminaire is determined by the solution of the problem. Simulation results show that the proposed scheme outperforms the luminaire control scheme with only the luminous flux control in the evaluation of satisfaction of the required illuminance level.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.1
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• pp.37-42
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• 2023

Wi-Fi Received Signal Strength Indicator (RSSI) is considered one of the most important sensor data types for indoor localization. However, collecting a RSSI fingerprint, which consists of pairs of a RSSI measurement set and a corresponding location, is costly and time-consuming. In this paper, we propose a Wi-Fi RSSI learning technique without true location data to overcome the limitations of static database construction. Instead of the true reference positions, inertial measurement unit (IMU) data are used to generate pseudo locations, which enable a trainer to move during data collection. This improves the efficiency of data collection dramatically. From an experiment it is seen that the proposed algorithm successfully learns the unsupervised Wi-Fi RSSI positioning model, resulting in 2 m accuracy when the cumulative distribution function (CDF) is 0.8.

• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.44-49
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• 2003

This paper describes a method of estimating miniature train location by color vision for development of an intelligent railway system model. In the teal world, to control trains automatically, GPS(Global Positioning System) is indispensable to determine the location of trains. A color vision system was used for estimating the location of trains in an indoor experiment. Two different rectangular color bars were attached to the top of each train as a means of identifying them. Several trains were detected where they were located on the track by color feature, geometric features and moment invariant, and tracked simultaneously. In the experiment the identity, location and direction of each train were estimated and transferred to the control computer using serial communication. Processing speed of up to 8 frames/sec could be achieved, which was enough speed for the real-time train control.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.1606-1611
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• 2005

The goal of this paper is to develop a self localization of mobile robot using UHF RFID landmark. We present landmark, a location sensing archetype system that uses UHF Radio Frequency Identification (UHF RFID) technology for locating objects inside buildings. The major advantage of landmark is that it improves the overall accuracy of locating objects by utilizing the concept of reference tags. Based on experimental analysis, we demonstrate that passive UHF RFID is a viable and cost-effective candidate for indoor location sensing. We conduct a series of experiments to evaluate performance of the positioning of the landmark System. In the standard setup, we place RF Reader which has two antennas and 25 tags in our lab. This research uses the assumption-based coordinates (ABC) algorithm[3] for determining the localization of robot. Also, we show how Radio Frequency Identification (UHF RFID) can be used in robot-assisted indoor navigation for the visually impaired. The experiments illustrate that passive UHF RFID tags can act as reliable landmark that trigger local navigation behaviors to achieve global navigation objectives.

• International journal of advanced smart convergence
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• v.13 no.1
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• pp.37-47
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• 2024

This study presents the results of designing a system that determines the location of a person in an indoor environment based on a single IMU sensor attached to the tip of a person's shoe in an area where GPS signals are inaccessible. By adjusting for human footfall, it is possible to accurately determine human location and trajectory by correcting errors originating from the Inertial Measurement Unit (IMU) combined with advanced machine learning algorithms. Although there are various techniques to identify stepping, our study successfully recognized stepping with 98.7% accuracy using an artificial intelligence model known as Long Short-Term Memory (LSTM). Drawing upon the enhancements in our methodology, this article demonstrates a novel technique for generating a 200-meter trajectory, achieving a level of precision marked by a 2.1% error margin. Indoor pedestrian navigation systems, relying on inertial measurement units attached to the feet, have shown encouraging outcomes.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.8 no.4
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• pp.84-92
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• 2009

In this paper, using the received signal strength of radio beacon such as Wi-Fi, Bluetooth, CDMA and GPS signal from the satellite, we propose the system of positioning which considered indoor and outdoor based on the Place Lab. Conventional Place Lab utilize the various positioning parameters to estimate the indoor location. However, this conventional system has limitations with respect to the range and efficiency of usage. Therefore, we defined the converged model of multisensor data and re-organized the Place Lab to overcome the limitation of a conventional system. Proposed system uses the radio beacon signal and GPS signal together to estimate the location. Furthermore, it provides the seamless PNS service with many mobile devices because this system realized by the OSGi bundle. This proposed system has evaluated the performance with SAMSUNG T*OMNIA SCH-M490 smart phone and the result shows the system is able to support the PNS service.

• KIEAE Journal
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• v.5 no.3
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• pp.41-48
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• 2005

Before occupation of an apartment housing, the builders are required to inform the test result of IAQ to the public. However, there is no simplified method to predict IAQ before measurement of pollutant concentration. In this study, a simplified way of predicting IAQ based on the distribution of indoor pollutant concentration is proposed. 7 different cases of air change rate have been simulated through CFD analysis to get the distribution ratio of each pollutant material and then simplified functions were used with CRIAQ1 values derived from CFD simulation to evaluate by comparing the influence of each material in the indoor pollutant concentration. Again, a lot of efforts which can improve the indoor air quality have been performed. Materials used in indoor space are labeled with their pollutant emission level. Installation of ventilation system in residential buildings will be regulated by a building codes sooner or later. But it is important to understand the fact that layout of walls, location or size of openings will influence the indoor air flow and pollutant concentration. And location of emitting material influences to indoor air pollutants distribution. But until now there is few recognition and consideration of these factors. Therefore, in this paper the effects of these factors is proved and some kind of guideline is made for designers after a comparison of typical apartment floor plan and a new type plan with their average pollutant concentration and its distribution of each room. CFD(Computational Fluid Dynamics) program was used to show the indoor air flow and pollutant concentration distribution. For this purpose, a typical $100m^2$ apartment floor plan was chosen as a case study model and several alternatives were reviewed to improve the IAQ performance. The simulation took place in the condition of natural ventilation through windows.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.12
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• pp.1855-1862
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• 2022

Various indoor location-based services can be provided through indoor presence determination and indoor positioning technology using Beacon. However, since the BLE signal advertised by the beacon has an unstable RSSI due to problems such as multi-path fading, it is difficult to guarantee the accuracy of indoor presence determination. In this paper, data were collected while the classroom door was open to ensure accuracy in various situations. Based on the collected data, we propose an indoor presence determination method considering the characteristics of the signal. The proposed method uses support vector machine, showed about 10% accuracy improvement compared to the results using raw RSSI only. This method has the advantage of being able to accurately determine indoor presence with only one receiver. It is expected that the proposed method can implement a low-cost system for determining indoor presence with high accuracy.

• Journal of Institute of Control, Robotics and Systems
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• v.13 no.7
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• pp.711-717
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• 2007

Location information will become increasingly important for future Pervasive Computing applications. Location tracking system of a moving device can be classified into two types of architectures: an active mobile architecture and a passive mobile architecture. In the former, a mobile device actively transmits signals for estimating distances to listeners. In the latter, a mobile device listens signals from beacons passively. Although the passive architecture such as Cricket location system is inexpensive, easy to set up, and safe, it is less precise than the active one. In this paper, we present a passive location system using Cricket Mote sensors which use RF and ultrasonic signals to estimate distances. In order to improve accuracy of the passive system, the transmission speed of ultrasound was compensated according to air temperature at the moment. Upper and lower bounds of a distance estimation were set up through measuring minimum and maximum distances that ultrasonic signal can reach to. Distance estimations beyond the upper and the lower bounds were filtered off as errors in our scheme. With collecting distance estimation data at various locations and comparing each distance estimation with real distance respectively, we proposed an equation to compensate the deviation at each point. Equations for proposed algorithm were derived to calculate relative coordinates of a moving device. At indoor and outdoor tests, average location error and average location tracking period were 3.5 cm and 0.5 second, respectively, which outperformed Cricket location system of MIT.

• Journal of IKEEE
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• v.26 no.2
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• pp.186-195
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• 2022

In this paper, we propose a new algorithm to improve the accuracy of indoor positioning techniques using Wi-Fi access points as beacon nodes. The proposed algorithm is based on the Weighted Centroid algorithm, a popular method widely used for indoor positioning, however, it improves some disadvantages of the Weighted Centroid method and also for other kinds of indoor positioning methods, by using the received signal strength correction method and genetic algorithm to prevent the signal strength fluctuation phenomenon, which is caused by the complex propagation environment. To validate the performance of the proposed algorithm, we conducted experiments in a complex indoor environment, and collect a list of Wi-Fi signal strength data from several access points around the standing user location. By utilizing this kind of algorithm, we can obtain a high accuracy positioning system, which can be used in any building environment with an available Wi-Fi access point setup as a beacon node.