• Journal of IKEEE
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• v.26 no.3
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• pp.341-348
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• 2022

Wi-Fi Sensing, which uses Wi-Fi technology to sense the surrounding environments, has strong potentials in a variety of sensing applications. Recently several advanced deep learning-based solutions using CSI (Channel State Information) data have achieved high performance, but it is still difficult to use in practice without explicit data collection, which requires expensive adaptation efforts for model retraining. In this study, we propose a Channel State Information Automatic Labeling System (CALS) that automatically collects and labels training CSI data for deep learning-based Wi-Fi sensing systems. The proposed system allows the CSI data collection process to efficiently collect labeled CSI for labeling for supervised learning using computer vision technologies such as object detection algorithms. We built a prototype of CALS to demonstrate its efficiency and collected data to train deep learning models for detecting the presence of a person in an indoor environment, showing to achieve an accuracy of over 90% with the auto-labeled data sets generated by CALS.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.6
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• pp.81-87
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• 2023

SAE J2601 and SAE J2799, the communication protocols between a hydrogen refueling station and a fuel cell electric vehicle, only cover hydrogen charging. In this paper, we measure the hydrogen detection, current, and voltage of a fuel cell electric vehicle and transmit the sensor data to the hydrogen refueling station by changing the WiFi protocol. A small-scale laboratory model was built using Raspberry Pi for sensing, controlling, and transmitting sensor data of a fuel cell electric vehicle. The sensor data was stored in the database of the hydrogen refueling station, and a dashboard was configured using Grafana to analyze the stored data. When hydrogen is detected, the dispenser valve of the hydrogen refueling station is locked. Then, we measured the average transmission delay according to the WiFi protocol. The results showed that IEEE 802.11a is the most suitable WiFi protocol for transmitting sensor data between the hydrogen refueling station and the fuel cell electric vehicle.

• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.111-118
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• 2023

In this paper, we propose a WiFi-based joystick with an acceleration sensor and a vibration sensor that can be used in flight simulators and VR fields. The flight simulator is a technology belonging to the ICT and SW application field and provides a simulation environment that reproduces the aircraft environment. Existing flight simulator control devices are fixed to a specific device and the user's activity area is limited. In this paper, a 3D space manipulation device was implemented for the user's free use of space. In addition, the proposed control device is designed as a WiFi communication board and display that displays information and performs 3-axis sensing for accurate and sophisticated control compared to existing VR equipment controllers. And the applicability was confirmed by implementing a Unity-based virtual environment. As a result of the implementation device verification, it was confirmed that the control device operates normally through the communication interface, It was confirmed that the sensing values in the game and the sensing values measured on the implemented board matched each other. The results of this study can be used for VR and various metaverse related contents in addition to flight simulators.

• Journal of Korea Multimedia Society
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• v.19 no.2
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• pp.451-459
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• 2016

The damages on the crops by the wild animals such as wild boars and water deer are serious in rural areas these days. In this paper, a low-cost and adaptive system based on open source for sensing and repelling farm pest animals is proposed. The system contains the server which is Arduino Due connected with the wireless communication modules such as RF, Zigbee, and WiFi module, speaker, and so on. It also has the sensing modules and LED blinkers which communicates with the server by wireless modules. Once a detecting signal is transmitted to the server. The server is waked up from sleep mode and the repelling subsystems such as loud speaker and LED blinker(s) are activated to scare the unwanted animal away. The total system is managed by Android smartphone easily.

• Advances in Computational Design
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• v.9 no.3
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• pp.187-211
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• 2024

WiFi sensing integration enables non-intrusive and is utilized in applications like Human Activity Recognition (HAR) to leverage Multiple Input Multiple Output (MIMO) systems and Channel State Information (CSI) data for accurate signal monitoring in different fields, such as smart environments. The complexity of extracting relevant features from CSI data poses computational bottlenecks, hindering real-time recognition and limiting deployment on resource-constrained devices. The existing methods sacrifice accuracy for computational efficiency or vice versa, compromising the reliability of activity recognition within pervasive environments. The lightweight Compact Convolutional Transformer (CCT) algorithm proposed in this work offers a solution by streamlining the process of leveraging CSI data for activity recognition in such complex data. By leveraging the strengths of both CNNs and transformer models, the CCT algorithm achieves state-of-the-art accuracy on various benchmarks, emphasizing its excellence over traditional algorithms. The model matches convolutional networks' computational efficiency with transformers' modeling capabilities. The evaluation process of the proposed model utilizes self-collected dataset for CSI WiFi signals with few daily activities. The results demonstrate the improvement achieved by using CCT in real-time activity recognition, as well as the ability to operate on devices and networks with limited computational resources.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.3
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• pp.794-814
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• 2012

We propose a novel method for improving Wi-Fi positioning accuracy while reducing the energy consumption of mobile devices. Our method presents three contributions. First, we jointly and intelligently select the optimal subset of access points for positioning via maximum mutual information criterion. Second, we further propose local discriminant embedding algorithm for nonlinear discriminative feature extraction, a process that cannot be effectively handled by existing linear techniques. Third, to reduce complexity and make input signal space more compact, we incorporate clustering analysis to localize the positioning model. Experiments in realistic environments demonstrate that the proposed method can lower energy consumption while achieving higher accuracy compared with previous methods. The improvement can be attributed to the capability of our method to extract the most discriminative features for positioning as well as require smaller computation cost and shorter sensing time.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.422-424
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• 2010

Recently the car attached many ECUs and entertainment devices to provide the easiness maintenance and driver's convenience. CAN and MOST networks have been used to manage and control those devices in the car. Wireless network also has been established to receive information from external. These days a car navigation system with GPS is being integrated with CAN, MOST and Wireless network. In these circumstances, the car navigation system can have HMI function to integrate and control the car networks' devices. To solve the GPS problems such as positioning errors or losing signals from satellites in the tunnels and urban canyons, this paper designs and implements a method for positioning vehicle by using the sensing data of sensors and Wi-Fi devices based on this integrated environment.

• Journal of Communications and Networks
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• v.16 no.2
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• pp.238-244
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• 2014

A key technical challenge in TV white spaces is the efficient spectrum usage without interfering with primary users. This paper considers available spectrum discovery scheme using in-band sensing signal to support super Wi-Fi services effectively. The proposed scheme in this paper adopts non-contiguous orthogonal frequency-division multiplexing (NC-OFDM) to utilize the fragmented channel in TV white space due to microphones while this channel cannot be used in IEEE 802.11af. The proposed solution is a novel available spectrum discovery scheme by exploiting the advantages of a sensing signaling. The proposed method achieves considerable improvement in throughput and delay time. The proposed method can use more subcarriers for transmission by applying NC-OFDM in contrast with the conventional IEEE 802.11af standard. Moreover, the increased number of wireless microphones (WMs) hardly affects the throughput of the proposed method because our proposal only excludes some subcarriers used by WMs. Additionally, the proposed method can cut discovery time down to under 10 ms because it can find available channels in real time by exchanging sensing signal without interference to the WM.

• Journal of Satellite, Information and Communications
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• v.12 no.3
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• pp.98-102
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• 2017

In this paper, we study RF-powered backscatter cognitive radio networks to improve the performance for the secondary user which is backscatter radio based wireless sensors. In our proposed model, we consider an avoiding the doubly round-trip attenuation to add a carrier emitter and utilization of spectrum sensing information. When the primary channel is busy, the secondary user is able to harvest RF energy from the channel through a hybrid-access point (H-AP) and a carrier emitter. When the channel becomes idle, the secondary user will be use the harvested energy to operate wireless sensors, to use the sensing and to backscatter through the carrier emitter. We model mathematically the deterministic and multisource elements of a number of tagged channels. In the proposed communication environment, we show the BER performance of the backscatter communication using WiFi signal.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.10
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• pp.1994-2000
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• 2016

Technology that can determine the location of individuals is required in a variety of applications such as location based control, a personalized advertising. Missing-child prevention and support for field trips, and applications such as push events based on the user's location is endless. In particular, the technology that can determine the location without interruption in the indoor and outdoor spaces have been studied a lot recently. Because emphasizing on accuracy of the positioning, many conventional research have constraints such as using of additional sensing devices or special mounting devices. The algorithm proposed in this paper has the purpose of performing the positioning only with standard equipment of the smart phone that has the most users. In this paper, sensor Fusion with GPS, WiFi Radio Map, Accelerometer sensor and Particle Filter algorithm is designed and implemented. Experimental results of this algorithm shows superior performance than the other compared algorithm. This could confirm the possibility of using proposed algorithm on actual environment.