Pub Date : 2019-10-01DOI: 10.1109/GCCE46687.2019.9015603
Megha Quamara, B. B. Gupta, S. Yamaguchi
In this paper, we present a remote temperature monitoring system for IoT-based smart homes using MQTT-driven communication. We implement the proposed system on MQTTBox to discuss its various performance aspects. Moreover, we discuss the state-of-the-art work in the domain.
{"title":"MQTT-driven Remote Temperature Monitoring System for IoT-based Smart Homes","authors":"Megha Quamara, B. B. Gupta, S. Yamaguchi","doi":"10.1109/GCCE46687.2019.9015603","DOIUrl":"https://doi.org/10.1109/GCCE46687.2019.9015603","url":null,"abstract":"In this paper, we present a remote temperature monitoring system for IoT-based smart homes using MQTT-driven communication. We implement the proposed system on MQTTBox to discuss its various performance aspects. Moreover, we discuss the state-of-the-art work in the domain.","PeriodicalId":303502,"journal":{"name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","volume":"475 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115312686","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/GCCE46687.2019.9015523
Y. Okazaki, Tadashi Ishiguro
We have newly developed a next-generation portable pulse wave analysis platform that can measure both radial augmentation index (rAI) and aortic PWV (aoPWV) with a smartphone/tablet to prevent future disease.
{"title":"A Novel Pulse Wave Analyzer for Personal Health Monitoring","authors":"Y. Okazaki, Tadashi Ishiguro","doi":"10.1109/GCCE46687.2019.9015523","DOIUrl":"https://doi.org/10.1109/GCCE46687.2019.9015523","url":null,"abstract":"We have newly developed a next-generation portable pulse wave analysis platform that can measure both radial augmentation index (rAI) and aortic PWV (aoPWV) with a smartphone/tablet to prevent future disease.","PeriodicalId":303502,"journal":{"name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123147266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/GCCE46687.2019.9015385
Chaxiong Yukonhiatou, T. Yoshihisa, Tomoya Kawakami, Y. Teranishi, S. Shimojo
Due to the widespread of recent object detection technologies, various real-time object detection systems such as human detection systems and car detection systems are deployed in banks, airports and so on. In most of these systems, camera devices continuously send their original recorded images to processing computers even when their target objects for detection are not recorded. This causes a large amount of communication traffic such as exceeds bandwidth usage, delays for data transmission. The communication traffic can be reduced by continuously sending rough images and re-sending clear images only when clear images that have objects recorded are required for the applications. For instance, a image that recorded a human. However, detecting objects in the rough images decreases its accuracy. In this paper, to evaluate the performance of our proposed progressive quality improvement approach, we investigate the accuracy of object detections changing the qualities of images.
{"title":"A Performance Evaluation of Object Detections by Progressive Quality Improvement Approach","authors":"Chaxiong Yukonhiatou, T. Yoshihisa, Tomoya Kawakami, Y. Teranishi, S. Shimojo","doi":"10.1109/GCCE46687.2019.9015385","DOIUrl":"https://doi.org/10.1109/GCCE46687.2019.9015385","url":null,"abstract":"Due to the widespread of recent object detection technologies, various real-time object detection systems such as human detection systems and car detection systems are deployed in banks, airports and so on. In most of these systems, camera devices continuously send their original recorded images to processing computers even when their target objects for detection are not recorded. This causes a large amount of communication traffic such as exceeds bandwidth usage, delays for data transmission. The communication traffic can be reduced by continuously sending rough images and re-sending clear images only when clear images that have objects recorded are required for the applications. For instance, a image that recorded a human. However, detecting objects in the rough images decreases its accuracy. In this paper, to evaluate the performance of our proposed progressive quality improvement approach, we investigate the accuracy of object detections changing the qualities of images.","PeriodicalId":303502,"journal":{"name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121832167","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/GCCE46687.2019.9015492
Yegang Du, Yuto Lim, Yasuo Tan
In the near future, smart home systems will play more and more important role to provide comfortable and safe life to human. Today, we already have some realistic way to monitor the daily life of human and recognize their activities by cameras or wireless sensing technology. However, the current research still faces the challenge to the prediction of human activities. In this paper, we analyse the similarity between human activities of daily living and deep neural networks. Inspired by this, the paper proposes a method to predict human activity by deep learning model and evaluates the performance of the approach with real world data. Compared with the traditional algorithm, our approach reaches higher prediction accuracy. In the future, we will try to improve the prediction accuracy and add more kinds of activities.
{"title":"Activity Prediction using LSTM in Smart Home","authors":"Yegang Du, Yuto Lim, Yasuo Tan","doi":"10.1109/GCCE46687.2019.9015492","DOIUrl":"https://doi.org/10.1109/GCCE46687.2019.9015492","url":null,"abstract":"In the near future, smart home systems will play more and more important role to provide comfortable and safe life to human. Today, we already have some realistic way to monitor the daily life of human and recognize their activities by cameras or wireless sensing technology. However, the current research still faces the challenge to the prediction of human activities. In this paper, we analyse the similarity between human activities of daily living and deep neural networks. Inspired by this, the paper proposes a method to predict human activity by deep learning model and evaluates the performance of the approach with real world data. Compared with the traditional algorithm, our approach reaches higher prediction accuracy. In the future, we will try to improve the prediction accuracy and add more kinds of activities.","PeriodicalId":303502,"journal":{"name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116640728","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes an adaptive beamforming scheme with service quality assurance for vehicle communications to provide reliable and stable data transmissions. In the proposed scheme, serving beams with variable beamwidth are adopted by base station (BS) to transmit signals due to the different path loss of different propagation distance. Additionally, an adaptive searching algorithm is developed in the scheme to optimize the beamwidth and directions of the serving beams. Theoretical analysis and simulations are conducted to prove the achievable reliability and stability performance.
{"title":"Adaptive Beamforming Scheme with Service Quality Assurance for Vehicle Communications Using Map Data","authors":"Shuangbing Li, Xiyang Yin, Yuting Tian, Junyao Zhang, Feng Tian, Dapeng Li, Yongan Guo","doi":"10.1109/GCCE46687.2019.9015510","DOIUrl":"https://doi.org/10.1109/GCCE46687.2019.9015510","url":null,"abstract":"This paper proposes an adaptive beamforming scheme with service quality assurance for vehicle communications to provide reliable and stable data transmissions. In the proposed scheme, serving beams with variable beamwidth are adopted by base station (BS) to transmit signals due to the different path loss of different propagation distance. Additionally, an adaptive searching algorithm is developed in the scheme to optimize the beamwidth and directions of the serving beams. Theoretical analysis and simulations are conducted to prove the achievable reliability and stability performance.","PeriodicalId":303502,"journal":{"name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","volume":"487 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116692846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/GCCE46687.2019.9015537
K. Minami, Takayoshi Kitamura, Tomoko Izumi, Y. Nakatani
There are many different musical abilities, and previous researchers have developed various tests to measure them. For a DJ, the ability to find the changing points in phrases and melodies while listening to music is essential. This beat count ability cannot be measured by existing music aptitude tests because it is completely different from other musical abilities. In this research, we developed a measurement system for beat count ability and verified its reliability and validity. First, we selected appropriate tracks and created a method to accurately measure this ability. Then we developed a system and conducted an experiment with users who had various levels of musical experience. The results suggest that our measurement system can accurately measure one's beat count ability, especially for beginners who are learning how to DJ.
{"title":"Proposal of a Beat Count Ability Measurement for Learning DJ Mixing","authors":"K. Minami, Takayoshi Kitamura, Tomoko Izumi, Y. Nakatani","doi":"10.1109/GCCE46687.2019.9015537","DOIUrl":"https://doi.org/10.1109/GCCE46687.2019.9015537","url":null,"abstract":"There are many different musical abilities, and previous researchers have developed various tests to measure them. For a DJ, the ability to find the changing points in phrases and melodies while listening to music is essential. This beat count ability cannot be measured by existing music aptitude tests because it is completely different from other musical abilities. In this research, we developed a measurement system for beat count ability and verified its reliability and validity. First, we selected appropriate tracks and created a method to accurately measure this ability. Then we developed a system and conducted an experiment with users who had various levels of musical experience. The results suggest that our measurement system can accurately measure one's beat count ability, especially for beginners who are learning how to DJ.","PeriodicalId":303502,"journal":{"name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116949177","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/GCCE46687.2019.9015373
Hideyuki Tanaka, Y. Matsumoto
We propose an autonomous guidance and landing control system for drone in indoor environment using a camera and visual markers. We developed a hybrid marker that combines a conventional AR marker and a high-accuracy marker developed by AIST, in order to achieve both the guidance of drones from a long distance and the accurate landing control based on localization at a short distance. We demonstrated the effectiveness through experiments using a prototype of the guidance and landing system.
{"title":"Autonomous Drone Guidance and Landing System Using AR/high-accuracy Hybrid Markers","authors":"Hideyuki Tanaka, Y. Matsumoto","doi":"10.1109/GCCE46687.2019.9015373","DOIUrl":"https://doi.org/10.1109/GCCE46687.2019.9015373","url":null,"abstract":"We propose an autonomous guidance and landing control system for drone in indoor environment using a camera and visual markers. We developed a hybrid marker that combines a conventional AR marker and a high-accuracy marker developed by AIST, in order to achieve both the guidance of drones from a long distance and the accurate landing control based on localization at a short distance. We demonstrated the effectiveness through experiments using a prototype of the guidance and landing system.","PeriodicalId":303502,"journal":{"name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125273021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/GCCE46687.2019.9015469
Daisuke Uenoyama, H. Yoshiura, Masatsugu Ichino
Iris authentication is attracting increasing attention due to its high accuracy. However, it imposes a psychological burden because the person to be authenticated must closely approach the camera in order for it to capture a high-quality image of the person's iris region. One way to reduce the burden is to combine iris authentication with periocular authentication. Following this approach, we focused on increasing the accuracy of iris authentication at a distance by using more periocular features and the XGBoost algorithm to fuse the scores. Test results show that our proposed method is more accurate than a method using AdaBoost.
{"title":"Personal Authentication of Iris and Periocular Recognition using XGBoost","authors":"Daisuke Uenoyama, H. Yoshiura, Masatsugu Ichino","doi":"10.1109/GCCE46687.2019.9015469","DOIUrl":"https://doi.org/10.1109/GCCE46687.2019.9015469","url":null,"abstract":"Iris authentication is attracting increasing attention due to its high accuracy. However, it imposes a psychological burden because the person to be authenticated must closely approach the camera in order for it to capture a high-quality image of the person's iris region. One way to reduce the burden is to combine iris authentication with periocular authentication. Following this approach, we focused on increasing the accuracy of iris authentication at a distance by using more periocular features and the XGBoost algorithm to fuse the scores. Test results show that our proposed method is more accurate than a method using AdaBoost.","PeriodicalId":303502,"journal":{"name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125330375","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/GCCE46687.2019.9015213
Donghyun Lee, Hosung Park, Minkyu Lim, Ji-Hwan Kim
This study proposes a syllable-level long short-term memory (LSTM) recurrent neural network (RNN)-based language model for a Korean voice interface in intelligent personal assistants (IPAs). Most Korean voice interfaces in IPAs use word-level $n$ -gram language models. Such models suffer from the following two problems: 1) the syntax information in a longer word history is limited because of the limitation of $n$ and 2) The out-of-vocabulary (OOV) problem can occur in a word-based vocabulary. To solve the first problem, the proposed model uses an LSTM RNN-based language model because an LSTM RNN provides long-term dependency information. To solve the second problem, the proposed model is trained with a syllable-level text corpus. Korean words comprise syllables, and therefore, OOV words are not presented in a syllable-based lexicon. In experiments, the RNN-based language model and the proposed model achieved perplexity (PPL) of 68.74 and 17.81, respectively.
{"title":"Syllable-Level Long Short-Term Memory Recurrent Neural Network-based Language Model for Korean Voice Interface in Intelligent Personal Assistants","authors":"Donghyun Lee, Hosung Park, Minkyu Lim, Ji-Hwan Kim","doi":"10.1109/GCCE46687.2019.9015213","DOIUrl":"https://doi.org/10.1109/GCCE46687.2019.9015213","url":null,"abstract":"This study proposes a syllable-level long short-term memory (LSTM) recurrent neural network (RNN)-based language model for a Korean voice interface in intelligent personal assistants (IPAs). Most Korean voice interfaces in IPAs use word-level $n$ -gram language models. Such models suffer from the following two problems: 1) the syntax information in a longer word history is limited because of the limitation of $n$ and 2) The out-of-vocabulary (OOV) problem can occur in a word-based vocabulary. To solve the first problem, the proposed model uses an LSTM RNN-based language model because an LSTM RNN provides long-term dependency information. To solve the second problem, the proposed model is trained with a syllable-level text corpus. Korean words comprise syllables, and therefore, OOV words are not presented in a syllable-based lexicon. In experiments, the RNN-based language model and the proposed model achieved perplexity (PPL) of 68.74 and 17.81, respectively.","PeriodicalId":303502,"journal":{"name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126736300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2019-10-01DOI: 10.1109/GCCE46687.2019.9015478
M. Bezha, N. Nagaoka
Proper usage of the batteries can impact how long the battery in PV/EV systems will last. But the correct estimation of State of Health (SoH) can affect the total cost of the system and its efficiency. As a matter of fact, the battery cost in EV applications is (35–50) % of the total cost of the cars. Their classification of deterioration and which application to send them next is the main concern. In this paper the proposed method was based on ANN algorithm, expressed by two NN structures in cascade. Where the first NN structure use V and I waveform and number of cycles as an optional input, and the output is the internal impedance parameters which is used as main input for the second NN in order to estimate finally the SoH of the battery pack system. A structure with 1 and 2 hidden layers is proposed. The estimation is finished within 42 seconds and with error of 1.8% in the worst case. By correctly estimating the SoH of the battery we can extend its usage for a little longer or preparing it to be used in PV systems, where the need for high current and dynamic characteristics during discharging it's not the same as in EV.
{"title":"A Fast Diagnosis for Classification of re-used Li-ion Batteries for PV and EV Systems by the ANN Model","authors":"M. Bezha, N. Nagaoka","doi":"10.1109/GCCE46687.2019.9015478","DOIUrl":"https://doi.org/10.1109/GCCE46687.2019.9015478","url":null,"abstract":"Proper usage of the batteries can impact how long the battery in PV/EV systems will last. But the correct estimation of State of Health (SoH) can affect the total cost of the system and its efficiency. As a matter of fact, the battery cost in EV applications is (35–50) % of the total cost of the cars. Their classification of deterioration and which application to send them next is the main concern. In this paper the proposed method was based on ANN algorithm, expressed by two NN structures in cascade. Where the first NN structure use V and I waveform and number of cycles as an optional input, and the output is the internal impedance parameters which is used as main input for the second NN in order to estimate finally the SoH of the battery pack system. A structure with 1 and 2 hidden layers is proposed. The estimation is finished within 42 seconds and with error of 1.8% in the worst case. By correctly estimating the SoH of the battery we can extend its usage for a little longer or preparing it to be used in PV systems, where the need for high current and dynamic characteristics during discharging it's not the same as in EV.","PeriodicalId":303502,"journal":{"name":"2019 IEEE 8th Global Conference on Consumer Electronics (GCCE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115072677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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