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Saturation Prediction for Crowdsensing Based Smart Parking System
( Mihui Kim ),( Junhyeok Yun ) 한국정보처리학회 2019 Journal of information processing systems Vol.15 No.6
Crowdsensing technologies can improve the efficiency of smart parking system in comparison with present sensor based smart parking system because of low install price and no restriction caused by sensor installation. A lot of sensing data is necessary to predict parking lot saturation in real-time. However in real world, it is hard to reach the required number of sensing data. In this paper, we model a saturation predication combining a time-based prediction model and a sensing data-based prediction model. The time-based model predicts saturation in aspects of parking lot location and time. The sensing data-based model predicts the degree of saturation of the parking lot with high accuracy based on the degree of saturation predicted from the first model, the saturation information in the sensing data, and the number of parking spaces in the sensing data. We perform prediction model learning with real sensing data gathered from a specific parking lot. We also evaluate the performance of the predictive model and show its efficiency and feasibility.
Mihui Kim,Yesol Kim,Mona Choi 한국간호과학회 2021 한국간호과학회 학술대회 Vol.2021 No.10
Aim: Peripheral artery disease (PAD) is a chronic atherosclerotic obstructive disease accompanied by functional impairment. Text messaging interventions were used to provide feedback related to target goals, enhance motivation, and remind without restricting places, thereby lead to improve physical activity. Therefore, timely intervention through text messages appropriate for participants" situations will help change to targeted behavior. This study aimed to establish of text message library using behavior change wheel (BCW) framework to support the intervention program developed for exercise behavior for patients with PAD. Method: Based on the BCW framework, this study was conducted in three stages: First, we identified exercise barriers in PAD patients and analyze behavior mechanisms to mapping them to behavioral capabilities, opportunities, and motivation models (COM-B). Second, to overcome exercise barriers, we selected and linked the appropriate intervention functions to behavioral changes. Third, we developed a library of text messages by intervention functions according to the levels defined in the BCT taxonomy. Result: In the first phase, we reviewed the existing literature and interviewed 15 patients with PAD, classifying the barriers to exercise performance into six categories: (a) lacking time, (b) poor condition, (c) unwillingness to exercise, (d) leg pain, (e) bad weather, and (f) forgetting exercise. In the second phase, we selected five intervention functions (training, enablement, estimation, persuasions, and environment restructuring) of the BCW framework for behavioral change by overcoming the barriers, and each barrier and intervention function were linked. In the third stage, we were mapping the barrier-intervention function-BCT taxonomy label and developed a total of 113 text messages according to the definition of the BCT taxonomy label. Conclusion: We developed a text messaging library based on the BCW framework. In the following studies, we will utilize the text messaging library for exercise interventions to change the sedentary behavior of PAD patients.
Privacy-Preservation Using Group Signature for Incentive Mechanisms in Mobile Crowd Sensing
Kim, Mihui,Park, Younghee,Dighe, Pankaj Balasaheb Korea Information Processing Society 2019 Journal of information processing systems Vol.15 No.5
Recently, concomitant with a surge in numbers of Internet of Things (IoT) devices with various sensors, mobile crowdsensing (MCS) has provided a new business model for IoT. For example, a person can share road traffic pictures taken with their smartphone via a cloud computing system and the MCS data can provide benefits to other consumers. In this service model, to encourage people to actively engage in sensing activities and to voluntarily share their sensing data, providing appropriate incentives is very important. However, the sensing data from personal devices can be sensitive to privacy, and thus the privacy issue can suppress data sharing. Therefore, the development of an appropriate privacy protection system is essential for successful MCS. In this study, we address this problem due to the conflicting objectives of privacy preservation and incentive payment. We propose a privacy-preserving mechanism that protects identity and location privacy of sensing users through an on-demand incentive payment and group signatures methods. Subsequently, we apply the proposed mechanism to one example of MCS-an intelligent parking system-and demonstrate the feasibility and efficiency of our mechanism through emulation.
Kim, Wansik,Yeo, Hwanyong,Lee, Juyoung,Kim, Young-Gon,Seo, Mihui,Kim, Sosu The Institute of Internet 2022 International journal of advanced smart convergenc Vol.11 No.2
In this paper, w-band frequency synthesizer was developed for frequency-modulated continuous wave (FMCW) radar sensors. To achieve a small size and high performance, We designed and manufactured w-band MMIC chips such as up-converter one-chip, multiplier, DA (Drive Amplifier) MMIC(Monolithic Microwave Integrated Circuit), etc. And interposer technology was applied between the W-band multiplier and the DA MMIC chip. As a result, the measured phase noise was -106.10 dBc@1MHz offset, and the frequency switching time of the frequency synthesizer was less than 0.1 usec. Compared with the w-band frequency synthesizer using purchased chips, the developed frequency synthesizer showed better performance.
Saturation Prediction for Crowdsensing Based Smart Parking System
Kim, Mihui,Yun, Junhyeok Korea Information Processing Society 2019 Journal of information processing systems Vol.15 No.6
Crowdsensing technologies can improve the efficiency of smart parking system in comparison with present sensor based smart parking system because of low install price and no restriction caused by sensor installation. A lot of sensing data is necessary to predict parking lot saturation in real-time. However in real world, it is hard to reach the required number of sensing data. In this paper, we model a saturation predication combining a time-based prediction model and a sensing data-based prediction model. The time-based model predicts saturation in aspects of parking lot location and time. The sensing data-based model predicts the degree of saturation of the parking lot with high accuracy based on the degree of saturation predicted from the first model, the saturation information in the sensing data, and the number of parking spaces in the sensing data. We perform prediction model learning with real sensing data gathered from a specific parking lot. We also evaluate the performance of the predictive model and show its efficiency and feasibility.
무선랜 환경에서 AP 로드 밸런싱을 위한 AP-개시 플로우 리다이렉션 메커니즘
김미희 ( Mihui Kim ),채기준 ( Kijoon Chae ) 한국인터넷정보학회 2009 인터넷정보학회논문지 Vol.10 No.2
IEEE802.11 무선랜은 공항과 같은 공공의 장소에서 널리 사용되고 있으며 캠퍼스나 회사의 네트워킹 영역을 증대하고 있고, 최근 메쉬 네트워크나 다른 3세대 이동 통신 네트워크과의 통합 형태의 네트워크를 구성하기 위한 중요 기술로 주목 받고있다. 무선랜 환경에서의 액세스 포인트 (AP) 간 로드 밸런싱 문제는 효율적인 자원 관리나 트래픽의 QoS 지원을 위해 중요한 문제이지만, 기존 연구들에서는 노드가 네트워크에 진입하는 시점이나 로밍 시점에 로드 밸런싱을 위한 AP 선택에 초점을 맞추고 있다. 본 논문에서는 AP의 가용성 모니터링을 통해 진정한 의미의 로드 밸런싱을 위한 AP-개시 플로우 리다이렉션 메커니즘을 제안한다. AP 자신의 가용자원이 거의 사용하게 되면, 즉 특정 임계치 이상 사용하게 되면, 자신이 서비스하고 있는 노드가 로밍 가능한 이웃 AP들에게 그들의 가용자원에 관하여 쿼리를 하여 entropy나 chi-square와 같은 통계적인 방법을 이용하여 AP 간 트래픽 분포도에 대해 계산하고, 리다이렉트할 플로우들을 결정하여 선택된 노드들을 트리거하여 플로우 리다이렉션을 수행한다. 시뮬레이션 결과, 제안된 플로우 리다이렉션 메커니즘이 다양한 측면에서의 성능향상을 입증할 수 있었다. IEEE802.11 Wireless LAN (WLAN) is being widely used in public space such as airport, and increases the networking boundary in campus and enterprise, and it has lastly attracted considerable attention for mesh network and converged network with other 3G mobile communication networks. In WLAN, load balancing among Access Points (AP) is an important issue for efficient resource management or supporting the Quality of Service (QoS) of traffic, but most researches focused on the AP selection in network entry or roaming of Stations (STA). In this paper, we propose an AP-Initiated Flow Redirection (FR) for AP load balancing by monitoring AP`s availability in the true sense. When the AP`s resource becomes almost saturated, that is used more than a specific threshold, the AP queries the roaming possible neighbor APs about their availability and calculates the distribution of traffic load with statistical methods such as entropy or chi-square. Finally, the AP decides flows and new APs for redirection and performs it. Our simulation results show that our FR mechanism increases the performance in the various views.