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There is growing research interest from many scientific, healthcare, and industrial applications toward the development of high-precision optical pH sensors that cover a broad pH range. Despite enthusiastic endeavors, however, it remains challenging to develop cost-effective, high-precision, and broadband working paper-strip-type optical pH measurement systems, particularly for on-site or in-the-field pH sensing applications. We develop a fluorescent array based on a KIz system for accurate pH level classification. Based on the indolizine fluorescent core skeleton, a library of 30 different pH-responsive fluorescent probes is rationally designed and efficiently synthesized. Spotting the compounds in a checkered pattern (5 × 6) allows for the development of a disposable compound array on wax-printed cellulose paper. Compounds sharing a single chemical core skeleton result in the interrogation of all the components of a system with a single excitation light, resulting in a simple system design for pH classification. Furthermore, we design a 3D-printed enclosure to capture the fluorescence pattern changes of the array by using an intelligent, smartphone-based, handheld pH detection system. Specifically, by exploiting a random forest-based machine learning algorithm on a smartphone, we can effectively analyze the fluorescence pattern changes. Our results suggest that our proposed system can classify pH levels in fine-grain (0.2 pH) units.
Hyungi Kim; Sungmin Lee; Jun Sik Min; Eunsu Kim; Junwon Choi; Jeonggil Ko; Eunha Kim. Fluorescent sensor array for high-precision pH classification with machine learning-supported mobile devices. Dyes and Pigments 2021, 193, 109492 .
AMA StyleHyungi Kim, Sungmin Lee, Jun Sik Min, Eunsu Kim, Junwon Choi, Jeonggil Ko, Eunha Kim. Fluorescent sensor array for high-precision pH classification with machine learning-supported mobile devices. Dyes and Pigments. 2021; 193 ():109492.
Chicago/Turabian StyleHyungi Kim; Sungmin Lee; Jun Sik Min; Eunsu Kim; Junwon Choi; Jeonggil Ko; Eunha Kim. 2021. "Fluorescent sensor array for high-precision pH classification with machine learning-supported mobile devices." Dyes and Pigments 193, no. : 109492.
Hepatic surface nodularity quantified on CT images has shown promising results in staging hepatic fibrosis in chronic hepatitis C. The aim of this study was to evaluate hepatic surface nodularity, serum fibrosis indices, and a linear combination of them for staging fibrosis in chronic liver disease, mainly chronic hepatitis B. We developed a semiautomated software quantifying hepatic surface nodularity on CT images. Hepatic surface nodularity and serum fibrosis indices were assessed in the development group of 125 patients to generate 3 linear models combining hepatic surface nodularity with the aspartate aminotransferase to platelet ratio index, fibrosis-4 index, or platelet count in reference to the METAVIR scoring system. The models were validated in 183 patients. Hepatic surface nodularity and serum fibrosis indices all significantly correlated with fibrosis stages. For binary classifications into cirrhosis (F4), advanced fibrosis (≥ F3), and significant fibrosis (≥ F2), hepatic surface nodularity was significantly different across categories. The areas under the curve (AUCs) of the best model were 0.901, 0.872, and 0.794 for cirrhosis, advanced fibrosis, and significant fibrosis, respectively, higher than serum fibrosis indices alone (0.797–0.802, 0.799–0.818, and 0.761–0.773). In the validation group, the same model likewise showed higher AUCs (0.872, 0.831, and 0.850) compared to serum fibrosis indices (0.722–0.776, 0.692–0.768, and 0.695–0.769; p < 0.001 for F4). Hepatic surface nodularity combined with serum blood test could be a practical method to predict cirrhosis, advanced fibrosis, and significant fibrosis in chronic liver disease patients, providing higher accuracy than using serum fibrosis indices alone.
Hyo Jung Cho; Jaewon Choi; BoHyun Kim; Jeonggil Ko; Joon-Il Choi; Jimi Huh; Jei Hee Lee; Jai Keun Kim. Combining hepatic surface nodularity and serum tests better predicts hepatic fibrosis stages in chronic liver disease. Abdominal Radiology 2021, 1 -11.
AMA StyleHyo Jung Cho, Jaewon Choi, BoHyun Kim, Jeonggil Ko, Joon-Il Choi, Jimi Huh, Jei Hee Lee, Jai Keun Kim. Combining hepatic surface nodularity and serum tests better predicts hepatic fibrosis stages in chronic liver disease. Abdominal Radiology. 2021; ():1-11.
Chicago/Turabian StyleHyo Jung Cho; Jaewon Choi; BoHyun Kim; Jeonggil Ko; Joon-Il Choi; Jimi Huh; Jei Hee Lee; Jai Keun Kim. 2021. "Combining hepatic surface nodularity and serum tests better predicts hepatic fibrosis stages in chronic liver disease." Abdominal Radiology , no. : 1-11.
This paper presents a year-long study of our project, aiming at (1) understanding the work practices of clinical staff in trauma intensive care units (TICUs) at a trauma center, with respect to their usage of clinical data interface systems, and (2) developing and evaluating an intuitive and user-centered clinical data interface system for their TICU environments. Based on a long-term field study in an urban trauma center that involved observation-, interview-, and survey-based studies to understand our target users and their working environment, we designed and implemented MediSenseView as a working prototype. MediSenseView is a clinical-data interface system, which was developed through the identification of three core challenges of existing interface system use in a trauma care unit—device separation, usage inefficiency, and system immobility—from the perspectives of three staff groups in our target environment (i.e., doctors, clinical nurses and research nurses), and through an iterative design study. The results from our pilot deployment of MediSenseView and a user study performed with 28 trauma center staff members highlight their work efficiency and satisfaction with MediSenseView compared to existing clinical data interface systems in the hospital.
Jaeyeon Park; Soyoung Rhim; Kyungsik Han; Jeonggil Ko. Disentangling the clinical data chaos: User-centered interface system design for trauma centers. PLOS ONE 2021, 16, e0251140 .
AMA StyleJaeyeon Park, Soyoung Rhim, Kyungsik Han, Jeonggil Ko. Disentangling the clinical data chaos: User-centered interface system design for trauma centers. PLOS ONE. 2021; 16 (5):e0251140.
Chicago/Turabian StyleJaeyeon Park; Soyoung Rhim; Kyungsik Han; Jeonggil Ko. 2021. "Disentangling the clinical data chaos: User-centered interface system design for trauma centers." PLOS ONE 16, no. 5: e0251140.
Improvements in small sized sensors allow the easy detection of the presence of Volatile Organic Compounds (VOCs) in the air using easy-to-deploy Internet of Things (IoT) devices. However, classifying what VOC exists in the environment still remains as a complex task. Knowing what VOCs are in the air can help us remove the main cause that vents VOC materials as a way to maintain clean air quality. In this work, we present VOCkit, an IoT sensor kit for non-chemical experts to easily detect and classify different types of VOCs. VOCkit combines miniature chemically-designed fluorometric sensors for recognizing VOCs with an embedded imaging system for classification. Exposing the fluorometric sensors with various VOCs, result in the photophysical property change of fluorescent compounds, which composes the sensors, and the synergistic combination of the changes create unique individual fluorescent color patterns respectively to the VOC material. The fluorescent color change pattern is captured using an embedded camera and the images are processed with machine learning algorithms on the embedded platform for VOC classification. Using 500 fluorometric sensor images collected for five different commonly contactable VOCs, we show the feasibility of VOC classification on small-sized IoT devices. For the VOC types of our interest, our results show a classification accuracy of 97%, implying the potential applicability of VOCkit for real-world usage.
Jungmo Ahn; Hyungi Kim; Eunha Kim; Jeonggil Ko. VOCkit: A low-cost IoT sensing platform for volatile organic compound classification. Ad Hoc Networks 2020, 113, 102360 .
AMA StyleJungmo Ahn, Hyungi Kim, Eunha Kim, Jeonggil Ko. VOCkit: A low-cost IoT sensing platform for volatile organic compound classification. Ad Hoc Networks. 2020; 113 ():102360.
Chicago/Turabian StyleJungmo Ahn; Hyungi Kim; Eunha Kim; Jeonggil Ko. 2020. "VOCkit: A low-cost IoT sensing platform for volatile organic compound classification." Ad Hoc Networks 113, no. : 102360.
Multiplexed analysis allows simultaneous measurements of multiple targets, improving the detection sensitivity and accuracy. However, highly multiplexed analysis has been challenging for point-of-care (POC) sensing, which requires a simple, portable, robust, and affordable detection system. In this work, we developed paper-based POC sensing arrays consisting of kaleidoscopic fluorescent compounds. Using an indolizine structure as a fluorescent core skeleton, named Kaleidolizine (KIz), a library of 75 different fluorescent KIz derivatives were designed and synthesized. These KIz derivatives are simultaneously excited by a single ultraviolet (UV) light source and emit diverse fluorescence colors and intensities. For multiplexed POC sensing system, fluorescent compounds array on cellulose paper was prepared and the pattern of fluorescence changes of KIz on array were specific to target chemicals adsorbed on that paper. Furthermore, we developed a machine-learning algorithm for automated, rapid analysis of color and intensity changes of individual sensing arrays. We showed that the paper sensor arrays could differentiate 35 different volatile organic compounds using a smartphone-based handheld detection system. Powered by the custom-developed machine-learning algorithm, we achieved the detection accuracy of 97 % in the VOC detection. The highly multiplexed paper sensor could have favorable applications for monitoring a broad-range of environmental toxins, heavy metals, explosives, pathogens.
Hyungi Kim; Sang-Kee Choi; Jungmo Ahn; Hojeong Yu; Kyoungha Min; Changgi Hong; Ik-Soo Shin; Sanghee Lee; Hakho Lee; Hyungsoon Im; Jeonggil Ko; Eunha Kim. Kaleidoscopic fluorescent arrays for machine-learning-based point-of-care chemical sensing. Sensors and Actuators B: Chemical 2020, 329, 129248 .
AMA StyleHyungi Kim, Sang-Kee Choi, Jungmo Ahn, Hojeong Yu, Kyoungha Min, Changgi Hong, Ik-Soo Shin, Sanghee Lee, Hakho Lee, Hyungsoon Im, Jeonggil Ko, Eunha Kim. Kaleidoscopic fluorescent arrays for machine-learning-based point-of-care chemical sensing. Sensors and Actuators B: Chemical. 2020; 329 ():129248.
Chicago/Turabian StyleHyungi Kim; Sang-Kee Choi; Jungmo Ahn; Hojeong Yu; Kyoungha Min; Changgi Hong; Ik-Soo Shin; Sanghee Lee; Hakho Lee; Hyungsoon Im; Jeonggil Ko; Eunha Kim. 2020. "Kaleidoscopic fluorescent arrays for machine-learning-based point-of-care chemical sensing." Sensors and Actuators B: Chemical 329, no. : 129248.
The ubiquitous deployment of smart wearable devices brings promises for an effective implementation of various healthcare applications in our everyday living environments. However, given that these applications ask for accurate and reliable sensing results of vital signs, there is a need to understand the accuracy of commercial-off-the-shelf wearable devices’ healthcare sensing components (e.g., heart rate sensors). This work presents a thorough investigation on the accuracy of heart rate sensors equipped on three different widely used smartwatch platforms. We show that heart rate readings can easily diverge from the ground truth when users are actively moving. Moreover, we show that the accelerometer is not an effective secondary sensing modality of predicting the accuracy of such smartwatch-embedded sensors. Instead, we show that the photoplethysmography (PPG) sensor’s light intensity readings are an plausible indicator for determining the accuracy of optical sensor-based heart rate readings. Based on such observations, this work presents a light-weight Viterbi-algorithm-based Hidden Markov Model to design a filter that identifies reliable heart rate measurements using only the limited computational resources available on smartwatches. Our evaluations with data collected from four participants show that the accuracy of our proposed scheme can be as high as 98%. By enabling the smartwatch to self-filter misleading measurements from being healthcare application inputs, we see this work as an essential module for catalyzing novel ubiquitous healthcare applications.
Jungmo Ahn; Ho-Kyeong Ra; Hee Jung Yoon; Sang Hyuk Son; Jeonggil Ko. On-Device Filter Design for Self-Identifying Inaccurate Heart Rate Readings on Wrist-Worn PPG Sensors. IEEE Access 2020, 8, 184774 -184784.
AMA StyleJungmo Ahn, Ho-Kyeong Ra, Hee Jung Yoon, Sang Hyuk Son, Jeonggil Ko. On-Device Filter Design for Self-Identifying Inaccurate Heart Rate Readings on Wrist-Worn PPG Sensors. IEEE Access. 2020; 8 (99):184774-184784.
Chicago/Turabian StyleJungmo Ahn; Ho-Kyeong Ra; Hee Jung Yoon; Sang Hyuk Son; Jeonggil Ko. 2020. "On-Device Filter Design for Self-Identifying Inaccurate Heart Rate Readings on Wrist-Worn PPG Sensors." IEEE Access 8, no. 99: 184774-184784.
Limitations in battery capacity has held back the active development of novel applications for the Internet of Things (IoT) or have caused embedded systems researchers to design a number of “go-around” schemes, which sacrifice various system performance metrics for energy efficiency. However, with the concept of simultaneous wireless information and power transfer (SWIPT), many researchers accept it as a potential technology that can be the basis of designing various next-generation low-power embedded computing systems. This work presents an experimental validation on RF-based SWIPT techniques. Specifically, using the Powercast P2110 Powerharvester Receiver, we evaluate its potential of being applied to various low-power embedded applications. We analyze the performance of these commercially available energy harvesting RF receivers in packet-based networks to show that energy harvesting in such cases are only possible with packets of long lengths in practical environments. Furthermore, we experimentally show that despite carrying energy, external noise factors on the wireless channel can deteriorate the RF-based energy harvesting performance due to high voltage amplitude fluctuations. Based on such observations, we present a set of system-level suggestions for future SWIPT-based system development.
KiSong Lee; Jeonggil Ko. RF-Based Energy Transfer Through Packets: Still a Dream? or a Dream Come True? IEEE Access 2019, 7, 163840 -163850.
AMA StyleKiSong Lee, Jeonggil Ko. RF-Based Energy Transfer Through Packets: Still a Dream? or a Dream Come True? IEEE Access. 2019; 7 (99):163840-163850.
Chicago/Turabian StyleKiSong Lee; Jeonggil Ko. 2019. "RF-Based Energy Transfer Through Packets: Still a Dream? or a Dream Come True?" IEEE Access 7, no. 99: 163840-163850.
Internet‐of‐Things (IoT) devices are typically resource constrained in terms of computing capabilities and battery power. Despite the efforts from the Internet Engineering Task Force (IETF) to established standards for IoT such as IPv6 over low‐power wireless personal area networks (6LoWPAN), routing protocol for low‐power lossy networks (RPL), and constrained application protocol (CoAP), certificate‐based Internet security protocols have not been fully addressed yet. We see the main cause of this being the size of the X.509‐based Internet certificates. Typically being 1 to 2 kB, the large size of these certificates can cause IEEE 802.15.4‐based IoT nodes to fragment the certificate into many smaller packet‐size chunks, which causes many packet transmissions to occur in the network. This work presents LightCert, a lightweight scheme to compress the size of the security certificates using the similarity of contents in X.509 certificates. Specifically, LightCert identifies common fields in a certificate and suppresses the transmission of these contents within the IoT subnet scope. This allows LightCert nodes to minimize the packet transmission overhead for supporting certificate‐based security mechanisms such as datagram transport layer security (DTLS), by as much as ∼37%. The added overhead of exchanging certificates when using LightCert is kept low to as much as ∼5 mJ of energy and ∼0.48 seconds of latency.
Hyuksang Kwon; Jeongseob Ahn; Jeonggil Ko. LightCert: On designing a lighter certificate for resource‐limited Internet‐of‐Things devices. Transactions on Emerging Telecommunications Technologies 2019, 30, 1 .
AMA StyleHyuksang Kwon, Jeongseob Ahn, Jeonggil Ko. LightCert: On designing a lighter certificate for resource‐limited Internet‐of‐Things devices. Transactions on Emerging Telecommunications Technologies. 2019; 30 (10):1.
Chicago/Turabian StyleHyuksang Kwon; Jeongseob Ahn; Jeonggil Ko. 2019. "LightCert: On designing a lighter certificate for resource‐limited Internet‐of‐Things devices." Transactions on Emerging Telecommunications Technologies 30, no. 10: 1.
Intra-body Communication (IBC) is a communication method using the human body as a communication medium, in which body-attached devices exchange electro-magnetic (EM) wave signals with each other. The fact that our human body consists of water and electrolytes allows such communication methods to be possible. Such a communication technology can be used to design novel body area networks that are secure and resilient towards external radio interference. While being an attractive technology for enabling new applications for human body-centered ubiquitous applications, network protocols for IBC systems is yet under-explored. The IEEE 802.15.6 standards present physical and medium access control (MAC) layer protocols for IBC, but, due to many simplifications, we find that its MAC protocol is limited in providing an environment to enable high data rate applications. This work, based on empirical EM wave propagation measurements made for the human body communication channel, presents IB-MAC, a centralized Time-division multiple access (TDMA) protocol that takes in consideration the transmission latency the body channel induces. Our results, in which we use an event-based simulator to compare the performance of IB-MAC with two different IEEE 802.15.6 standard-compliant MAC protocols and a state-of-the art TDMA-based MAC protocol for IBC, suggest that IB-MAC is suitable for supporting high data rate applications with comparable radio duty cycle and latency performance.
Seungmin Kim; Jeonggil Ko. IB-MAC: Transmission Latency-Aware MAC for Electro-Magnetic Intra-Body Communications. Sensors 2019, 19, 341 .
AMA StyleSeungmin Kim, Jeonggil Ko. IB-MAC: Transmission Latency-Aware MAC for Electro-Magnetic Intra-Body Communications. Sensors. 2019; 19 (2):341.
Chicago/Turabian StyleSeungmin Kim; Jeonggil Ko. 2019. "IB-MAC: Transmission Latency-Aware MAC for Electro-Magnetic Intra-Body Communications." Sensors 19, no. 2: 341.
Seungmin Kim; Jeonggil Ko. Analyzing Electro-Magnetic Wave Signal Characteristics for Intra-Body Communication Systems. Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers 2018, 102 -105.
AMA StyleSeungmin Kim, Jeonggil Ko. Analyzing Electro-Magnetic Wave Signal Characteristics for Intra-Body Communication Systems. Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers. 2018; ():102-105.
Chicago/Turabian StyleSeungmin Kim; Jeonggil Ko. 2018. "Analyzing Electro-Magnetic Wave Signal Characteristics for Intra-Body Communication Systems." Proceedings of the 2018 ACM International Joint Conference and 2018 International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers , no. : 102-105.
With the introduction of various advanced deep learning algorithms, initiatives for image classification systems have transitioned over from traditional machine learning algorithms (e.g., SVM) to Convolutional Neural Networks (CNNs) using deep learning software tools. A prerequisite in applying CNN to real world applications is a system that collects meaningful and useful data. For such purposes, Wireless Image Sensor Networks (WISNs), that are capable of monitoring natural environment phenomena using tiny and low-power cameras on resource-limited embedded devices, can be considered as an effective means of data collection. However, with limited battery resources, sending high-resolution raw images to the backend server is a burdensome task that has direct impact on network lifetime. To address this problem, we propose an energy-efficient pre- and post- processing mechanism using image resizing and color quantization that can significantly reduce the amount of data transferred while maintaining the classification accuracy in the CNN at the backend server. We show that, if well designed, an image in its highly compressed form can be well-classified with a CNN model trained in advance using adequately compressed data. Our evaluation using a real image dataset shows that an embedded device can reduce the amount of transmitted data by ∼71% while maintaining a classification accuracy of ∼98%. Under the same conditions, this process naturally reduces energy consumption by ∼71% compared to a WISN that sends the original uncompressed images.
Jungmo Ahn; Jaeyeon Park; Donghwan Park; Jeongyeup Paek; Jeonggil Ko. Convolutional neural network-based classification system design with compressed wireless sensor network images. PLOS ONE 2018, 13, e0196251 .
AMA StyleJungmo Ahn, Jaeyeon Park, Donghwan Park, Jeongyeup Paek, Jeonggil Ko. Convolutional neural network-based classification system design with compressed wireless sensor network images. PLOS ONE. 2018; 13 (5):e0196251.
Chicago/Turabian StyleJungmo Ahn; Jaeyeon Park; Donghwan Park; Jeongyeup Paek; Jeonggil Ko. 2018. "Convolutional neural network-based classification system design with compressed wireless sensor network images." PLOS ONE 13, no. 5: e0196251.
Understanding the engagement levels players have with a game is a useful proxy for evaluating the game design and user experience. This is particularly important for mobile games as an alternative game is always just an easy download away. However, engagement is a subjective concept and usually requires fine-grained highly disruptive interviews or surveys to determine accurately. In this paper, we present EngageMon, a first-of-its-kind system that uses a combination of sensors from the smartphone (touch events), a wristband (photoplethysmography and electrodermal activity sensor readings), and an external depth camera (skeletal motion information) to accurately determine the engagement level of a mobile game player. Our design was guided by feedback obtained from interviewing 22 mobile game developers, testers, and designers. We evaluated EngageMon using data collected from 64 participants (54 in a lab-setting study and another 10 in a more natural setting study) playing six games from three different categories including endless runner, 3D motorcycle racing, and casual puzzle. Using all three sets of sensors, EngageMon was able to achieve an average accuracy of 85% and 77% under cross-sample and cross-subject evaluations respectively. Overall, EngageMon can accurately determine the engagement level of mobiles users while they are actively playing a game.
Sinh Huynh; Seungmin Kim; Jeonggil Ko; Rajesh Krishna Balan; Youngki Lee. EngageMon. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2018, 2, 1 -27.
AMA StyleSinh Huynh, Seungmin Kim, Jeonggil Ko, Rajesh Krishna Balan, Youngki Lee. EngageMon. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies. 2018; 2 (1):1-27.
Chicago/Turabian StyleSinh Huynh; Seungmin Kim; Jeonggil Ko; Rajesh Krishna Balan; Youngki Lee. 2018. "EngageMon." Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 2, no. 1: 1-27.
This paper proposes an efficient architecture of HEVC in-loop filters (ILFs) with the target of providing effective multicore utilization for ultra-high definition video applications. While HEVC allows for a high level of parallelization, the issue of data dependencies at the ILF leads to inefficient parallel processing performance. The novel memory organization and management techniques address the data dependency-related issues between multiple processing units and enable to filter the flexible area on multicore decoder. In addition, we introduce the adaptive deblocking filtering order (ADFO) to minimize the impact of bus congestion when multiple cores interoperate for processing very large data. Furthermore, we design the deblocking filter with skip mode pipelining to achieve the high performance minimizing the increased cost and the power consumption. For SAO, we apply the window based parallel SAO filtering scheme. The resource sharing is considered throughout the entire architecture. Based on both experimental and analytical results, our proposed design can achieve more than 1.31 Gpixels/s and less than 2.6 Gpixels/s at maximum frequency 660MHz in single core, and consumes 56.2Kgates including 10.6Kgates for memory management architecture, which supports multicore decoder, and about 20.8mW power on average when synthesizing with the 28nm CMOS library. Moreover, the skip modes of DF improves both the performance and the power dissipation. The ADFO improves the performance of $\sim$9.17% when decoding 8K sequence on octa-core at 400MHz frequency. TpG (Throughput per Gate) is the highest among the related works.
Hyunmi Kim; Jeonggil Ko; Seongmo Park. An Efficient Architecture of In-Loop Filters for Multicore Scalable HEVC Hardware Decoders. IEEE Transactions on Multimedia 2017, 20, 810 -824.
AMA StyleHyunmi Kim, Jeonggil Ko, Seongmo Park. An Efficient Architecture of In-Loop Filters for Multicore Scalable HEVC Hardware Decoders. IEEE Transactions on Multimedia. 2017; 20 (4):810-824.
Chicago/Turabian StyleHyunmi Kim; Jeonggil Ko; Seongmo Park. 2017. "An Efficient Architecture of In-Loop Filters for Multicore Scalable HEVC Hardware Decoders." IEEE Transactions on Multimedia 20, no. 4: 810-824.
Bluetooth Low Energy (BLE) and the iBeacons have recently gained large interest for enabling various proximity-based application services. Given the ubiquitously deployed nature of Bluetooth devices including mobile smartphones, using BLE and iBeacon technologies seemed to be a promising future to come. This work started off with the belief that this was true: iBeacons could provide us with the accuracy in proximity and distance estimation to enable and simplify the development of many previously difficult applications. However, our empirical studies with three different iBeacon devices from various vendors and two types of smartphone platforms prove that this is not the case. Signal strength readings vary significantly over different iBeacon vendors, mobile platforms, environmental or deployment factors, and usage scenarios. This variability in signal strength naturally complicates the process of extracting an accurate location/proximity estimation in real environments. Our lessons on the limitations of iBeacon technique lead us to design a simple class attendance checking application by performing a simple form of geometric adjustments to compensate for the natural variations in beacon signal strength readings. We believe that the negative observations made in this work can provide future researchers with a reference on how well of a performance to expect from iBeacon devices as they enter their system design phases.
Jeongyeup Paek; Jeonggil Ko; Hyungsik Shin. A Measurement Study of BLE iBeacon and Geometric Adjustment Scheme for Indoor Location-Based Mobile Applications. Mobile Information Systems 2016, 2016, 1 -13.
AMA StyleJeongyeup Paek, Jeonggil Ko, Hyungsik Shin. A Measurement Study of BLE iBeacon and Geometric Adjustment Scheme for Indoor Location-Based Mobile Applications. Mobile Information Systems. 2016; 2016 ():1-13.
Chicago/Turabian StyleJeongyeup Paek; Jeonggil Ko; Hyungsik Shin. 2016. "A Measurement Study of BLE iBeacon and Geometric Adjustment Scheme for Indoor Location-Based Mobile Applications." Mobile Information Systems 2016, no. : 1-13.
As miniature-sized embedded computing platforms are ubiquitously deployed to our everyday environments, the issue of managing their power usage becomes important, especially when they are used in energy harvesting based self-organizing networks. One way to provide these devices with continuous power is to utilize RF-based energy transfer. Previous research in RF-based information and energy transfer builds up on the assumption that perfect channel estimation is easily achievable. However, as our preliminary experiments and many previous literature in wireless network systems show, making perfect estimations of the wireless channel is extremely challenging due to their quality fluctuations. To better reflect reality, in this work, we introduce an adaptive power allocation and splitting (APAS) scheme which takes imperfect channel estimations into consideration. Our evaluation results show that the proposed APAS scheme achieves near-optimal performances for transferring energy and data over a single RF transmission.
KiSong Lee; Jeonggil Ko. Adaptive Power Allocation and Splitting with Imperfect Channel Estimation in Energy Harvesting Based Self-Organizing Networks. Mobile Information Systems 2016, 2016, 1 -7.
AMA StyleKiSong Lee, Jeonggil Ko. Adaptive Power Allocation and Splitting with Imperfect Channel Estimation in Energy Harvesting Based Self-Organizing Networks. Mobile Information Systems. 2016; 2016 ():1-7.
Chicago/Turabian StyleKiSong Lee; Jeonggil Ko. 2016. "Adaptive Power Allocation and Splitting with Imperfect Channel Estimation in Energy Harvesting Based Self-Organizing Networks." Mobile Information Systems 2016, no. : 1-7.
The improvement in hardware capabilities of mobile devices has led to the active use of processor-heavy contents, such as multimedia files, on resource-limited platforms. In addition to simply enjoying such contents on mobile devices, recently commercialized protocols allow the real-time sharing of multimedia (or a mobile device's screen contents) with neighboring devices via wireless connection. However, unlike PC-scale computing platforms, use-case expansions on mobile devices face an additional technical challenge. Specifically, while the improved computation power is capable of handling processor-hungry applications, battery limitations hold back their full utilization. This paper acknowledges the fact that screen sharing on mobile devices can be attractive, but empirically show that minimizing the energy consumption is crutial, and introduces enhancements to the widely used H.264 encoder on mobile devices. Specifically, our enhancements target to minimize the transmission size of multimedia contents by analyzing the screen's dynamics. For contents with high dynamics, our scheme tries to maintain the video quality, while aggressively skipping frames for regions with minimal motion intensity. Our empirical evaluations show that the proposed light-weight enhancements reduce the size of a typical multimedia file by ~42%, while maintaining a high user-perceived quality (e.g., Structural SIMilarity measure) of 0.925. Wirelessly sharing this video results in ~31% lower frame transmission rate and up to ~21% power savings in less dynamic regions.
Keun-Woo Lim; Jisu Ha; Puleum Bae; Jeonggil Ko; Young-Bae Ko. Adaptive Frame Skipping With Screen Dynamics for Mobile Screen Sharing Applications. IEEE Systems Journal 2016, 12, 1577 -1588.
AMA StyleKeun-Woo Lim, Jisu Ha, Puleum Bae, Jeonggil Ko, Young-Bae Ko. Adaptive Frame Skipping With Screen Dynamics for Mobile Screen Sharing Applications. IEEE Systems Journal. 2016; 12 (2):1577-1588.
Chicago/Turabian StyleKeun-Woo Lim; Jisu Ha; Puleum Bae; Jeonggil Ko; Young-Bae Ko. 2016. "Adaptive Frame Skipping With Screen Dynamics for Mobile Screen Sharing Applications." IEEE Systems Journal 12, no. 2: 1577-1588.
Seungmin Kim; Jeonggil Ko. Poster. Proceedings of the 14th Annual International Conference on Digital Government Research 2016, 44 -44.
AMA StyleSeungmin Kim, Jeonggil Ko. Poster. Proceedings of the 14th Annual International Conference on Digital Government Research. 2016; ():44-44.
Chicago/Turabian StyleSeungmin Kim; Jeonggil Ko. 2016. "Poster." Proceedings of the 14th Annual International Conference on Digital Government Research , no. : 44-44.