• Title/Summary/Keyword: Occupancy Sensor

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Map-Building for Path-Planning of an Autonomous Mobile Robot Using a Single Ultrasonic Sensor (단일 초음파센서를 이용한 자율 주행 로봇의 경로 계획용 지도작성)

  • Kim, Young-Geun;Kim, HaK-Il
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.51 no.12
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    • pp.577-582
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    • 2002
  • The objective of this paper is to produce a weighted graph map for path-planning of an autonomous mobile robot(AMR) based on the measurements from a single ultrasonic sensor, which are acquired when the autonomous mobile robot explores unknown indoor circumstance. The AMR navigates in th unknown space by following the wall and gathers the range data using the ultrasonic sensor, from which the occupancy grid map is constructed by associating the range data with occupancy certainties. Then, the occupancy grid map is converted to a weighted graph map suing morphological image processing and thinning algorithms. the path- planning for autonomous navigation of a mobile robot can be carried out based on the occupancy grid map. These procedures are implemented and tested using an AMR, and primary results are presented in this paper.

Map building for path planning of an autonomous mobile robot using an ultrasonic sensor (초음파센서를 이용한 자율 주행 로봇의 경로 계획용 지도작성)

  • 이신제;오영선;김학일;김춘우
    • 제어로봇시스템학회:학술대회논문집
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    • 1996.10b
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    • pp.900-903
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    • 1996
  • The objective of this paper is to make the weighted graph map for path planning using the ultrasonic sensor measurements that are acquired when an A.M.R (autonomous mobile robot) explores the unknown circumstance. First, The A.M.R navigates on unknown space with wall-following and gathers the sensor data from the environments. After this, we constructs the occupancy grid map by interpreting the gathered sensor data to occupancy probability. For the path planning of roadmap method, the weighted graph map is extracted from the occupancy grid map using morphological image processing and thinning algorithm. This methods is implemented on an A.M.R having a ultrasonic sensor.

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Adjustment of delay time of occupancy sensor using normal distribution (정규분포를 이용한 재실감지 센서의 시간지연 설정)

  • Jeong, Young-Hoon;Song, Sang-Bin;Gwark, Jae-Young;Yeo, In-Seon
    • Proceedings of the KIEE Conference
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    • 1999.07g
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    • pp.3156-3158
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    • 1999
  • Occupancy sensor is a efficient light control system which light on/off automatically and reduces the unnecessary power waste. From now the research on occupancy sensor is restricted to the selection of the appropriate place or sensor. Exist occupancy sensor changes the delay time by manually to the place or situation, so it is unreliable. The delay time can been changed by the average time of the occupied and the preset time, but it is not enough to reliable. In this paper, so to acquire the reliance the average and the standard deviation of the occupied time change the delay time automatically and protect the malfunction from the detector. And to embody it, AT89C52 microcontroller is adopted to the control circuit. It is verified by simulation and experiment results of output characteristic for randomized input.

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A Study on Occupancy Estimation Method of a Private Room Using IoT Sensor Data Based Decision Tree Algorithm (IoT 센서 데이터를 이용한 단위실의 재실추정을 위한 Decision Tree 알고리즘 성능분석)

  • Kim, Seok-Ho;Seo, Dong-Hyun
    • Journal of the Korean Solar Energy Society
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    • v.37 no.2
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    • pp.23-33
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    • 2017
  • Accurate prediction of stochastic behavior of occupants is a well known problem for improving prediction performance of building energy use. Many researchers have been tried various sensors that have information on the status of occupant such as $CO_2$ sensor, infrared motion detector, RFID etc. to predict occupants, while others have been developed some algorithm to find occupancy probability with those sensors or some indirect monitoring data such as energy consumption in spaces. In this research, various sensor data and energy consumption data are utilized for decision tree algorithms (C4.5 & CART) for estimation of sub-hourly occupancy status. Although the experiment is limited by space (private room) and period (cooling season), the prediction result shows good agreement of above 95% accuracy when energy consumption data are used instead of measured $CO_2$ value. This result indicates potential of IoT data for awareness of indoor environmental status.

Energy Saving System using Occupancy Sensors and Smart Plugs (재실감지 센서와 스마트 플러그를 이용한 에너지 절약 시스템)

  • Jung, Kyung Kwon;Seo, Choon Weon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.52 no.10
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    • pp.161-167
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    • 2015
  • This paper presented an occupancy-based energy saving system for appliance energy saving in smart house. The developed system is composed of a sensing system and a home gateway system. The sensing system is set of wireless sensor nodes which have pyroelectric infrared (PIR) sensor to detect a motion of human and set of smart plugs which measure the current using CT (current transformer) sensor and send the current to home gateway wirelessly. We measured current consumption of appliances in real time using smart plugs, and checked the occupation of residents using occupancy sensors installed on the door and room. The proposed system saves electric energy to switch off the supply power of unnecessary usages in the unoccupied spaces. Experiments conducted have shown that electric energy usage of appliances can be saved about 34% checked by using occupation.

Noise Removal for Improvement of Occupancy-grid Map

  • Kim, Young-Geun;Choi, Chang-Min;Kim, Hak-Il
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.138.4-138
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    • 2001
  • The purpose of this research is to build a quality-improved occupancy grid map for path-planning of an autonomous mobile robot(AMR) based on the measurements from a single ultrasonic sensor, which are acquired when the autonomous mobile robot explores unknown indoor environment. The AMR navigates in the unknown space by following the wall and gathers the range data using the ultrasonic sensor, from which the occupancy grid map is constructed by associating the range data with occupancy certainties. In order to increase the quality of the map we modify the Bayesian probability updating rule, reject non-systematic measurement errors and correct the predictable error of the AMR itself. These procedures are implemented and tested using an AMR, and primary results are presented in this paper.

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Feasibility Research of the Active RFIDs for the Smart Occupancy Detection (지능형 재실 감지 서비스를 위한 능동형 RFID의 적용 타당성 연구)

  • Choi, Yeon-Suk;Park, Byoung-Tae
    • Journal of the Korea Safety Management & Science
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    • v.13 no.2
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    • pp.147-155
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    • 2011
  • For an effective energy management in intelligent buildings it is necessary to gather information about position/absence of people and the level of population. In this paper the smart occupancy detection system based on the active RFID is developed to satisfy such a demand. The performance of the developed system is tested and verified through various experiments. Furthermore the feasibility test of the active RFID tag is performed to verify whether it can be used as a location-based occupancy sensor. The developed core technology can be also applied to other fields such as security, healthcare, smart home, etc.

Automatic setting of delay time of an occupancy sensor using an adder circuit (인체감지 센서의 시간지연 설정)

  • 정영훈;송상빈;여인선
    • Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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    • 1998.11a
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    • pp.162-165
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    • 1998
  • A certain degree of energy saving can be possible by controlling the delay time of occupancy sensor. In this paper a control circuit is designed for automatic control of delay time setting appropriate to different situations using a digital counter, two latches and an adder. The delay time is controlled by adjusting the time constant of RC circuit through on-off control of switching devices according to adder output, which determines the base current level of switching devices. And from PSpice simulation it is verified to function properly.

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Real-time People Occupancy Detection by Camera Vision Sensor (카메라 비전 센서를 활용하는 실시간 사람 점유 검출)

  • Gil, Jong In;Kim, Manbae
    • Journal of Broadcast Engineering
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    • v.22 no.6
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    • pp.774-784
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    • 2017
  • 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 can not detect static people. If the tradeoff of cost and performance is satisfied, the camera sensors are expected to replace the current PIRs. In this paper, we propose vision sensor-based occupancy detection being composed of tracking, recognition and detection. Our softeware is designed to meet the real-time processing. In experiments, 14.5fps is achieved at 15fps USB input. Also, the detection accuracy reached 82.0%.

Bed Side Monitoring System using Occupancy Sensor and Doppler Radar (Occupancy 센서와 도플러 Radar를 이용한 침상 모니터링 시스템)

  • Kang, Byung Wuk;Yoo, Sun Kook
    • Journal of Korea Multimedia Society
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    • v.21 no.3
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    • pp.382-390
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    • 2018
  • A major accident occurring on the bed is falls that occur during at times when the care of nurses or protectors is inadequate, which is fatal to patients or the elderly. In particular, Enuresis or sleepiness caused by sleep apnea increases the risk of falls. Therefore, it is very important to detect falls and sleep apnea of patients without infringing privacy in the bed to patient's safety and accident prevention. In this paper, we reviewed the technologies developed for bed monitoring and implemented a non-intrusive monitoring system. The Occupancy Sensor allows the temperature of the bed and surrounding area to be extracted to enable track of the patient's motion. The Doppler Radar detects the patient's movements at normal times and the respiration state when patients have no movement during sleeping. It is specially designed for real-time monitoring of falling and respiration during sleeping through contactless multi-sensing while solving patient's privacy problems.