• Spatial Information Research
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• v.23 no.3
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• pp.1-10
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• 2015

Due to recent improvement of various sensor technologies, indoor positioning becomes available. However, Indoor positioning technologies by Wi-Fi radio map and acceleration sensor and digital campus still have a certain level of errors and a number of researches have been done to increase the positioning accuracy of the indoor positioning. If we could provide a room level accuracy, indoor location based services with current indoor positioning methods such as Wi-Fi radio map and acceleration sensors would be possible. In this paper, we propose an indoor map matching method to provide a room level accuracy based on hidden markov model.

• The Journal of Korea Robotics Society
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• v.4 no.4
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• pp.312-319
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• 2009

This paper proposes a low-complexity indoor localization method of mobile robot under the dynamic environment by fusing the landmark image information from an ordinary camera and the distance information from sensor nodes in an indoor environment, which is based on sensor network. Basically, the sensor network provides an effective method for the mobile robot to adapt to environmental changes and guides it across a geographical network area. To enhance the performance of localization, we used an ordinary CCD camera and the artificial landmarks, which are devised for self-localization. Experimental results show that the real-time localization of mobile robot can be achieved with robustness and accurateness using the proposed localization method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.349-350
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• 2019

The autonomous driving drones experimented in the existing indoor corridor environment was a way to give the steering command to the drones by the neural network operation of the notebook due to the limitation of the operation performance of the drones. In this paper, to overcome these limitations, we have studied autonomous driving in indoor corridor environment using NVIDIA Jetson TX2 board.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.4
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• pp.378-384
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• 2015

Indoor localization is becoming one of the most important technologies for smart mobile applications with different requirements from conventional outdoor location estimation algorithms. Fingerprinting location estimation techniques based on neural networks have gained increasing attention from academia due to their good generalization properties. In this paper, we propose a novel location estimation algorithm based on an ensemble of multiple neural networks. The neural network ensemble has drawn much attention in various areas where one neural network fails to resolve and classify the given data due to its' inaccuracy, incompleteness, and ambiguity. To the best of our knowledge, this work is the first to enhance the location estimation accuracy in indoor wireless environments based on a neural network ensemble using fingerprinting training data. To evaluate the effectiveness of our proposed location estimation method, we conduct the numerical experiments using the TGn channel model that was developed by the 802.11n task group for evaluating high capacity WLAN technologies in indoor environments with multiple transmit and multiple receive antennas. The numerical results show that the proposed method based on the NNE technique outperforms the conventional methods and achieves very accurate estimation results even in environments with a low number of APs.

• IEMEK Journal of Embedded Systems and Applications
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• v.11 no.3
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• pp.143-151
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• 2016

In this paper, a real-time air quality monitoring system based on wireless network is designed and implemented for industrial park or multiuse facilities. The existing gas detector is high price and hard to apply the remote monitoring system. On the other hand, demand for air quality monitoring is increasing because of industrial gas accident, air pollution, and so on. In Korea, indoor air regulation was established by law. According to indoor air regulation, CO2, CO, and NO2 are important gases as the air quality standard. So we study the gas detector for indoor air quality and the wireless network system. The wireless network consist of sensor network and WCDMA to apply various place. To verify the performance of the implemented gas detector, the gas measurement experiment is performed in laboratory environment by using the realized gas detecting wireless sensor node. And we evaluate the experiment results.

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

• The Journal of the Korea institute of electronic communication sciences
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• v.6 no.6
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• pp.903-908
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• 2011

The purpose of this paper is to provider an indoor location measuring method, apparatus and Service available for mobile wireless network. This paper introduces positioning technology such as Basic Technology Element and QoS(Quality of Service) etc. of WPS(WiFi Positioning System) for mobile wireless network. An apparatus for sectionalizing an indoor area for indoor location measurement includes several steps. For example, a sector number input step, a sectionalization calculating step, a storing unit step etc. Also, This paper show advance Indoor positioning result.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.11 no.4
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• pp.31-38
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• 2011

In this paper, we propose an autonomous Indoor lighting control system in which indoor lighting devices are autonomously controlled such that electricity bills are minimized in our daily life. Our focus is to utilize Passive Infrared (PIR) sensors to detect the presence of human being indoor and automatically to control indoor lighting electric devices. A control algorithm is also devised to control the whole system. We justify the proposed system by demonstrating specific applications in our everyday life. Cost survey and experimental results also demonstrate the efficiency of the proposed system in real life.

• New & Renewable Energy
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• v.5 no.3
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• pp.22-25
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• 2009

For increasing the output voltage, six SMD(surface mount device) type AlGaAs/GaAs solar cells were connected in series. The electrical properties of the array were measured and compared with one sun (100 mW/$cm^2$) and indoor light (480 lux) conditions. Under one sun condition, output power was 21.57 mW and it was $14.67\;{\mu}W$ under indoor light condition. Under the indoor light condition, the intensity of the light is very low compared to one sun condition. Thus the Voc(open circuit voltage) and Isc (short circuit current) of the sample under indoor light condition decreased very much compared to that of under the one sun condition. This kind of solar cell power supply can be used as a power source for ubiquitous sensor network (USN).

• Journal of Sensor Science and Technology
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• v.24 no.5
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• pp.342-347
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• 2015

We introduce an indoor broadcasting system using light-emitting diode (LED) lamps coupled with a 220 V power line. Two couplers connected to the power line constitute a power line communication (PLC) link. The transmission path from an LED lamp to a photodetector forms a visible light communication (VLC) link in free space. When the LED lamp is coupled to the power line, a composite PLC-VLC link is formed, making it possible to transmit a VLC signal beyond line-of-sight. In experiments, a 4 kHz analog signal modulated with a 100 kHz carrier was sent to the power line by a PLC coupler, and LED lamps coupled to the power line detected the signal and radiated it to multiple VLC receivers in the room. This configuration is useful in expanding an indoor VLC sensor network to adjacent rooms or constructing a voice broadcasting system in a building or apartments with existing power lines.