• Journal of Broadcast Engineering
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• v.24 no.2
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• pp.353-356
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• 2019

The main functionality of occupancy sensors is to determine the existence of humans in the space. If the space is occupied, a light is on and for vacancy, the light automatically turns off. In this letter, the functionality is realized by the utilization of color information. The color information of incoming people is saved. For outgoing people, their color distribution is compared with the saved information, thus providing the recognition of the outgoing people. For the comparison, four similarity metrics are examined to validate the proposed method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.666-669
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• 2000

Localization is the process of aligning the robot's local coordinates with the global coordinates of a map. A mobile robot's location is basically computed by a dead reckoning scheme, but this position information becomes increasingly inaccurate during navigation due to odometry errors. In this paper, the method of building a map of a robot's environment using ultrasonic sensor data and the occupancy grid map scheme is briefly presented. Then, the search and matching algorithms to compensate for the odometry error by comparing the local map with the reference map are proposed and verified by experiments. It is shown that the compensated error is not accumulated and exists within the limited range.

• Journal of Broadcast Engineering
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• v.23 no.2
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• pp.274-282
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• 2018

Most occupancy sensors installed in buildings, households and so forth are pyroelectric infra-red (PIR) sensors. One of disadvantages is that PIR sensor can not detect the stationary person due to its functionality of detecting the variation of thermal temperature. In order to overcome this problem, the utilization of camera vision sensors has gained interests, where object tracking is used for detecting the stationary persons. However, the object tracking has an inherent problem such as tracking drift. Therefore, the recognition of humans in static trackers is an important task. In this paper, we propose a CNN-based human recognition to determine whether a static tracker contains humans. Experimental results validated that human and non-humans are classified with accuracy of about 88% and that the proposed method can be incorporated into practical vision occupancy sensors.

• The Journal of the Korea Contents Association
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• v.10 no.9
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• pp.45-56
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• 2010

This paper reports a new mechanism for congestion controls. The proposed congestion detection algorithm can be provided with delay and unnecessary energy consumption. Conventional congestion control methods decide congestion by queue occupancy or mean packet arrival rate of MAC layer only, however, our method can perform precise detection by considering queue occupancy and mean packet arrival rate. In addition, the congestion avoiding method according to congestion degree and scheduling method using priority for real time packets are proposed. Finally, simulation results show that proposed congestion detection and control methods outperforms conventional scheduling schemes for wireless sensor network.

• International Journal of Automotive Technology
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• v.7 no.7
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• pp.827-832
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• 2006

Occupant classification and position detection have been significant research areas in intelligent safety systems in the automotive field. The detection and classification of seat occupancy open up new ways to control the safety system. This paper deals with a novel algorithm development, hardware implementation and testing of a prototype intelligent safety system for occupant classification and position detection for in-vehicle environment. Borland C++ program is used to develop the novel algorithm interface between the sensor and data acquisition system. MEMS strain gauge hermatic pressure sensor containing micromachined integrated circuits is installed inside the passenger seat. The analog output of the sensor is connected with a connector to a PCI-9111 DG data acquisition card for occupancy detection, classification and position detection. The algorithm greatly improves the detection of whether an occupant is present or absent, and the classification of either adult, child or non-human object is determined from weights using the sensor. A simple computation algorithm provides the determination of the occupant's appropriate position using centroidal calculation. A real time operation is achieved with the system. The experimental results demonstrate that the performance of the implemented prototype is robust for occupant classification and position detection. This research may be applied in intelligent airbag design for efficient deployment.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.14 no.6
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• pp.235-243
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• 2014

In this paper, we propose an efficient control system for intelligent LED indoor lighting. The proposed an efficient control system for intelligent LED indoor lighting were included to elements such as daylight intensity measured through the PIR sensor and illuminance sensor at lighting style by the schedule defined and the occupancy detection. And it was controlled lighting through to the wireless sensor network, and was designed for the energy savings. Also, the lighting control of indoor lighting based on occupancy detection detect fine movements using a PIR sensor. And an unnecessary lighting intensity control of the window-side and the inside were controlled according to daylight level measurement result using the light sensor. In daylight inflow many case, the window-side lighting was to automatically darker, and in daylight inflow less case, was designed to be automatically bright. The efficiency validate results of an efficient control system for intelligent LED indoor lighting, the brightness of the indoor light were to maximize the energy saving by controlling in real time when entering as indoor a little that external lighting or daylight.

• Journal of Broadcast Engineering
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• v.23 no.5
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• pp.642-655
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• 2018

Occupancy sensors installed in buildings and households turn off the light if the space is vacant. Currently PIR(pyroelectric infra-red) motion sensors have been utilized. Recently, the researches using camera sensors have been carried out in order to overcome the demerit of PIR that cannot detect stationary people. The detection of moving and stationary people is a main functionality of the occupancy sensors. In this paper, we propose an on-line human occupancy tracking method using convolutional neural network (CNN) and self-organizing map. It is well known that a large number of training samples are needed to train the model offline. To solve this problem, we use an untrained model and update the model by collecting training samples online directly from the test sequences. Using videos capurted from an overhead camera, experiments have validated that the proposed method effectively tracks human.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.58 no.3
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• pp.598-604
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• 2009

This paper proposes a vehicle detector with an anisotropic magnetoresistive (AMR) sensor and addresses experimental results to show the detector's performance. The detector consists of an AMR sensor and mechanical and electronic apparatuses. The AMR sensor, composed of four magnetoresistors, senses disturbance of the earth's magnetic field caused by a vehicle moving over the sensor and then produces an output indicative of the moving vehicle. This paper verifies performance of the detector on the basis of experimental results obtained from the field tests carried under the two traffic conditions on local highways in Korea. First, I show the vehicle counting performance on a low speed congested highway by comparing the vehicle counts measured by the detector with the exact counts. Second, both vehicle counts and average speeds calculated from the measured point-occupancy on another continuously free running highway are compared with the reference values obtained from a loop detector which has two independent loop coils, where I have used several performance indices including mean absolute percentage error (MAPE) to show the performance consistency between the two types of detectors.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.670-671
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• 2022

In this paper, we intend to develop a new TOF sensor that provides object occupancy information and location information by fusing the pixel value of the camera and the distance value of the TOF sensor. The developed sensor can be applied to school buses, school buses, city buses, and trucks (applicable to passenger vehicles).

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2012.05a
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• pp.277-278
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• 2012