• Journal of Environmental Health Sciences
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• v.41 no.5
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• pp.299-304
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• 2015

Objectives: A people-counting system measures real-time occupancy through motion detection. Accurate people-counting can be used to calculate suitable ventilation demands. This study determined the optimum motion threshold for a people-counting system. Methods: In a closed room with two occupants moving constantly, different thresholds were tested for the accuracy of a people-counting system. The experiments were conducted at 150, 300, 450 and 600 lux. These levels of brightness included the illumination levels of most public indoor areas. The experiments were repeated with three types of clothing coloration. Results: Overall, a threshold of 16 provided the lowest mean error percentage for the people-counting system. Brightness and clothing color did not have a significant impact on the results. Conclusion: A people-counting system could be used with threshold of 16 for most indoor environments.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1890-1897
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• 2021

People counting is an important technology to provide application services such as smart home, smart building, smart car, etc. Due to the social distancing of COVID-19, the people counting technology attracted public attention. People counting system can be implemented in various ways such as camera, sensor, wireless, etc. according to service requirements. People counting system using WiFi AP uses WiFi CSI data that reflects multipath information. This technology is an effective solution implementing indoor with low cost. The conventional WiFi CSI-based people counting technologies have low accuracy that obstructs the high quality service. This paper proposes a deep learning people counting system based on WiFi CSI data. Data preprocessing using auto-encoder, data augmentation that transform WiFi CSI data, and a proposed deep learning model improve the accuracy of people counting. In the experimental result, the proposed approach shows 89.29% accuracy in 6 subjects.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.35-40
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• 2021

People counting data is crucial for most business owners, since they can derive meaningful information about customers movement within their businesses. For example, owners of the supermarkets can increase or decrease the number of checkouts counters depending on number of occupants. Also, it has many applications in smart buildings, too. Where it can be used as a smart controller to control heating and cooling systems depending on a number of occupants in each room. There are advanced technologies like camera-based people counting system, which can give more accurate counting result. But they are expensive, hard to deploy and privacy invasive. In this paper, we propose a method and a hardware sensor for counting people passing through a passage or an entrance using IR Infrared sensors. Proposed sensor operates at low voltage, so low power consumption ensure long duration on batteries. Moreover, we propose a new method that distinguishes human body and other objects. Proposed method is inexpensive, easy to install and most importantly, it is real-time. The evaluation of our proposed method showed that when counting people passing one by one without overlapping, recall was 96% and when people carrying handbag like objects, the precision was 88%. Our proposed method outperforms IR Infrared based people counting systems in term of counting accuracy.

• IEMEK Journal of Embedded Systems and Applications
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• v.19 no.1
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• pp.39-46
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• 2024

In this paper, we propose an efficient method for estimating the number of people and their locations using multiple IR-UWB radar sensors. Using three IR-UWB radar sensors in the indoor space, the measured signal from the target is processed to remove the clutter using rejection methods. Then, to further remove the clutter and to determine the presence of the human, the time-frequency image representing the micro-Doppler is obtained and classified by a convolutional neural network. Finally, the system finds the number of human objects and estimates each position in a two-dimensional space. In experiments using the measured data, the system successfully estimated the location and number of individuals with a high accuracy ≈ 88.68 %.

• Particle and aerosol research
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• v.6 no.3
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• pp.123-129
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• 2010

As the indoor activity increases in recent years, the indoor air quality becomes more important. One of the major contaminants in office space is the copy machines and the laser based printers. These devices usually emit nano-particles and chemical species that may give some health effect. The amount of particles generated by the printers and copy machines depend on printer models, printing speed, toners, papers, humidity and so on. To evaluate the emission rate of nano-particles from Laser Printers, the mass concentration measurement method has been used (BAM, 2004). However, the mass concentration measurement method for nano-particles is tedious and time consuming. Therefore, for the development of a new nano-particle counting method, the nano-particle emission characteristics and size distributions are evaluated.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.30 no.1
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• pp.28-37
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• 2019

In this paper, we propose a real-time system for counting people. The proposed system uses an impulse radio ultra-wideband(IR-UWB) radar to estimate the number of people in a given location. The proposed system uses learning-based classification methods to count people more accurately. In other words, a feature vector database is constructed by exploiting the pattern of reflected signals, which depends on the number of people. Subsequently, a classifier is trained using this database. When a newly received signal data is acquired, the system automatically counts people using the pre-trained classifier. We validated the effectiveness of the proposed algorithm by presenting the results of real-time estimation of the number of people changing from 0 to 10 in an indoor environment.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.7
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• pp.935-941
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• 2020

People estimation is important to provide IoT services. Most people counting technologies use camera or sensor data. However, the conventional technologies have the disadvantages of invasion of privacy and the need to install extra infrastructure. This paper proposes a method for estimating the number of people using a Wi-Fi AP. We use channel state information of Wi-Fi and analyze that using deep learning technology. It can be achieved by pre-installed Wi-Fi infrastructure that reduce cost for people estimation and privacy infringement. The proposed algorithm uses a k-binding data for pre-processing process and a 1D-CNN learning model. Two APs were installed to analyze the estimation results of six people. The result of the accurate number estimation was 64.8%, but the result of classifying the number of people into classes showed a high result of 84.5%. This algorithm is expected to be applicable to estimate the density of people in a small space.

• Journal of Integrative Natural Science
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• v.15 no.2
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• pp.73-81
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• 2022

본 연구는 다중이용시설 이용자들의 쾌적함과 안전 그리고 시설내부 에너지 사용량의 최적 절감을 위하여 이용자수를 분석예측한 정보에 따른 공기질품질제어시스템 운영을 통해 국민 중심의 안전하고 쾌적한 서비스를 제공할 필요로 수행되었다. 이를 위하여 실내유동인구수를 카운팅하는 로컬시스템을 제작하고 수집된 유동인구 카운팅 정보를 시계열 모델링을 기반으로 분석예측하는 연구를 진행하였다. 개발된 시스템 성능평가 결과 유동인구 카운팅시스템은 95% 이상 정확도를 보여주었고, 예측시스템은 83~95% 정확도를 확보하였다. 본 연구결과 개발된 시스템은 다중이용시설에 즉시 적용가능하며 향후 남녀노소 인식을 진행하고 이를 예측한 정보에 의한 보다 다양한 서비스 개발을 추진할 계획이다.

• Journal of Korean Society of Environmental Engineers
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• v.28 no.6
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• pp.588-595
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• 2006

Indoor radon($^{222}Rn$) concentrations of subway stations in Seoul area were measured to survey the environmental indoor radon levels and to identify sources of radon. The radon concentration of indoor air by method of long-term measuring with a-track detector were surveyed at 232 subway stations from 1998 to 2004. And the radon concentration in ground-water was measured with a method of alpha particle counting. To trace main source of radon, 8 out of 232 stations were selected and their radon concentrations in tunnel and on platform were analyzed. Total geometric mean and arithmetic mean of radon concentrations in all stations from 1998 to 2004 were $1.40{\pm}1.94pCi/L,\;1.65{\pm}1.07$ respectively. Geometric means of radon concentrations on platform and concourse were $1.54{\pm}1.96pCi/L,\;1.23{\pm}1.88pCi/L$ respectively, with higher concentration at the platform than at the concourse. The geological structure was significantly correlated to the indoor radon concentration in subway stations region. Radon concentrations of adjacent tunnel and ground-water of subway station was significantly correlated to the indoor radon concentration in subway stations. And There was a significant difference in radon concentration, depending on the depth levels in platform of subway stations(p<0.05).

• The Korean Journal of Malacology
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• v.21 no.1
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• pp.19-24
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• 2005

This study was undertaken with the intent to describe the influence of water temperature and food concentration on the filtration rates of the Asiatic clam, Corbicula fluminea. The clams were collected at Lake Geumho near Yeongsan river, during March 2001. Food organism, Scenedesmus sp. (KMCC FC-34), was indoor-cultured in f/2 medium, and was used to measure the filtration rate of the clams. Filtration rate of the clams was measured by indirect method. Cell concentrations of food organisms were determined by direct counting cells using the hemacytometer under the light microscope. The filtration rate of the clams increased with water temperature up to circa $25^{\circ}C$. Above this temperature, the filtration rate decreased rapidly. The minimal filtration rate of the clams was recorded at $5^{\circ}C$. Thermal coefficient, $Q_10$ values at low temperature range were much higher than those at high temperature range. These results indicate the asiatic clam is more sensitive in cold water like most of marine bivalves. There was a strong reversed correlation between filtration rate and food concentration. Filtration rate of the clams was reduced as food concentration was increased.