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收集所有交通大學研究人員與學生個人或團體所發表之各項學術著作，涵蓋期刊論文、教師專書、學位論文等項。;;Collections of Publications of NCTU Researchers and Students Like Journal Papers and Thesis.

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Now showing 1 - 10 of 32

Design and Implementation of Image Electronic Fence with 5G technology for Smart Farms
(2019-01-01)
Hsu, Ching-Kuo
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Chiu, Yen-Hao
;
Wu, Kun-Ru
;
Liang, Jia-Ming
;
Chen, Jen-Jee
The 5G era brings the rapid development of the Internet of Things (IoT). New technologies, such as image recognition, have promoted the traditional agriculture to a new milestone. Through advanced research and development of image recognition, it can intelligently monitor the growth of crops and effectively reduce agricultural damages, while avoiding crops being stolen and reducing the manpower of farms. In this paper, we design and implement an image electronic fence based on the technology of image recognition and sensor fusion with 5G technology for smart farms. By applying cameras and beacon tags, our system can identify whether the incoming/leaving people are authorized or not at the entry and exit of farms. In addition, with the high speed and low latency of 5G technology, the video data of cameras can be transmitted in a flash and fused with the beacon detection. In this way, the incoming/leaving people can be identified efficiently so as to avoid the farms being damaged. Based on field trials, we validate that the identification accuracy of our system approaches 90% in average.
Enhanced scheduling schemes with energy conservation for dynamic point selection in cloud radio access networks
(2020-02-01)
Hsu, Ching-Kuo
;
Liang, Jia-Ming
;
Wu, Kun-Ru
;
Chen, Jen-Jee
;
Tseng, Yu-Chee
In 5G mobile communications, Cloud-RAN (C-RAN) (Camps-Mur et al. in IEEE Commun Mag 57:99-105, 2019) is proposed to provide broadband services. It separates computation entities, i.e., baseband units (BBUs), from base stations and puts all BBUs in a centralized cloud. Existing researches have investigated how to enhance user equipments (UEs) to receive data from multiple collaborative cells by leveraging the dynamic point selection(DPS) technology. Collaborative transmission may cause higher energy consumption for UEs. Although 3GPP has defined the discontinuous reception (DRX) mechanism by regulating UEs to turn off their radio interfaces in a periodical manner, how to well coordinate DRX with DPS under the C-RAN architecture is still left as an open issue. This paper is the first one addressing this resource optimization problem in C-RAN with DPS, which asks how to optimize DRX parameters of UEs by considering their quality-of-service (QoS). We prove this problem to be NP-complete, and then propose two effective and efficient DPS solutions, called serving-ratio(SR) scheme and cost-aware (CA) scheme. SR serves UEs based on a special 'serving ratio' to ensure UEs receiving continuous subframes, especially for those in cell intersections. On the other hand, CA exploits the strategies of minimal scheduling costs to balance energy and throughput efficiency in a perspective way. Extensive simulation results validate that our schemes can successfully achieve higher system throughput, provide better resource utilization, and serve more UEs while guaranteeing their QoS and saving considerable energy as compared to existing schemes.
Three-Stage DRX Scheduling for Joint Downlink Transmission in C-RAN
(2020-02-01)
Liang, Jia-Ming
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Hsu, Ching-Kuo
;
Chen, Jen-Jee
;
Wu, Kun-Ru
;
Tseng, Yu-Chee
Cloud-RAN (C-RAN) is a promising network architecture to provide 5G broadband services. In C-RAN, the base stations (BSs) are separated as the computation entities (i.e., Baseband Units (BBUs)) and the radio entities (i.e., Remote Radio Heads (RRHs)), where the BBUs are put in a centralized cloud to realize centrally control and the RRH are left at cell sites for signal transmission. With C-RAN, multiple collaborative cells can transmit data to user equipments (UEs) by Joint Transmission (JT) technology to improve network efficiency. On the other hand, 3GPP standard has defined the Discontinuous Reception (DRX) mechanism, which allows UEs to turn off their radio interfaces periodically to save their energy. However, how to cooperate DRX with JT under the C-RAN architecture is still an open issue. Therefore, this letter studies how to optimize UEs' DRX parameters while considering their quality-of-service (QoS) in C-RAN with JT. To solve this problem, we propose an energy-efficient JT scheduling scheme. The main idea of our scheme is to well pair UEs and BSs with the consideration of joint transmission quality and then optimizes DRX parameters to further save energy. Extensive simulation results show that our scheme can improve system throughput, well utilize resource and save UEs' energy consumption.
A Web-based Camera Dispatch System for Video Surveillance with Dynamic Requirements
(2015-01-01)
Li, Kuan-Yi
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Liang, Jia-Ming
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Fan, Chung-Shuo
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Tseng, Yu-Chee
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Lin, Yi-Ting
Video surveillance systems are commonly used to monitor environments, such as factories, shopping malls, offices, and schools, for safety and security. However, traditional closed-circuit television cameras can only capture static scenes. When unexpected events happen, such as fire accidents or stranger intrusion, the recorded video data cannot provide immediate and precise information. In this work, we design a camera dispatch system for video surveillance with pan-tilt-zoom (PTZ) cameras, which can monitor event-areas/targets real-timely and flexibly. Users can dynamically define the monitoring requirements, such as pixel-per-foot and viewing-angle of the event-areas/targets. Then, a dispatch algorithm will decide the most necessary cameras and corresponding settings to monitor the event-areas/targets immediately. The control panel is implemented as a web-based service. The demo shows that users can easily monitor potential event-areas/targets anywhere, anytime through a web browser.
Smart Interactive Education System Based on Wearable Devices
(2019-08-01)
Liang, Jia-Ming
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Su, Wei-Cheng
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Chen, Yu-Lin
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Wu, Shih-Lin
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Chen, Jen-Jee
Due to the popularity of smart devices, traditional one-way teaching methods might not deeply attract school students' attention, especially for the junior high school students, elementary school students, or even younger students, which is a critical issue for educators. Therefore, we develop an intelligent interactive education system, which leverages wearable devices (smart watches) to accurately capture hand gestures of school students and respond instantly to teachers so as to increase the interaction and attraction of school students in class. In addition, through multiple physical information of school students from the smart watch, it can find out the crux points of the learning process according to the deep data analysis. In this way, it can provide teachers to make instant adjustments and suggest school students to achieve multi-learning and innovative thinking. The system is mainly composed of three components: (1) smart interactive watch; (2) teacher-side smart application (App); and (3) cloud-based analysis system. Specifically, the smart interactive watch is responsible for detecting the physical information and interaction results of school students, and then giving feedback to the teachers. The teacher-side app will provide real-time learning suggestions to adjust the teaching pace to avoid learning disability. The cloud-based analysis system provides intelligent learning advices, academic performance prediction and anomaly learning detection. Through field trials, our system has been verified that can potentially enhance teaching and learning processes for both educators and school students.
Energy-Efficient Uplink Scheduling for Ultra-Reliable Communications in NB-IoT Networks
(2018-01-01)
Liu, Pei-Yi
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Wu, Kun-Ru
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Liang, Jia-Ming
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Chen, Jen-Jee
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Tseng, Yu-Chee
The 3GPP Narrowband Internet of Thing (NB-IoT) is the promising technology that can provide multiple types of resource unit (RU) with a special repetition mechanism to improve the scheduling flexibility and transmission reliability. Since the IoT devices need to operate for a very long time, the energy consumption becomes a critical issue. In this paper, we study how to guarantee the quality of service (QoS) while minimizing the energy consumption for IoT devices. We first model the problem and then propose an energy-efficient scheme, which consists of two stages. The first stage tries to incur the lowest energy consumption of devices and satisfy their QoS requirement. The second stage determines the scheduling order to ensure the delay constraint while maintaining energy efficiency. Simulation results show that our scheme can serve more devices while saving their energy.
A Survey of Intelligent Video Surveillance Systems: History, Applications and Future
(2015-01-01)
Fan, Chung-Shuo
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Liang, Jia-Ming
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Lin, Yi-Ting
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Wu, Kun-Ru
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Li, Kuan-Yi
With advances in wireless network infrastructure providing powerful support for surveillance video communications, it is practical to meet the needs of intelligent surveillance systems in a wide range of applications. This survey offers a comprehensive overview of state-of-the-art technologies for intelligent video surveillance systems so as to provide researchers in this field with a summary of the progress achieved to date. The evolution of surveillance systems is outlined as well. In addition, the representative technologies for environment modeling, object classification, object tracking, behavioral analysis, and database implementation are summarized. Finally, we list several detailed discussions on possible future research directions.
Energy-efficient scheduling scheme with spatial and temporal aggregation for small and massive transmissions in LTE-M networks
(2019-01-01)
Liang, Jia-Ming
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Chang, Po-Yen
;
Chen, Jen-Jee
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資訊工程學系
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Department of Computer Science
Machine-to-machine (M2M) communication is one of the key technologies to realize Internet of Things (IoT). Since IoT applications are mainly for smart sensing, such as metering, home surveillance, disaster detection, and e-health, their special sensing/uploading behaviors will result in periodic and/or event-driven small data transmissions, which may potentially decrease the radio resource efficiency. On the other hand, due to the frequent communication nature of sensing data for IoT applications, the power consumption is increasing dramatically. To reduce the power consumption of IoT devices, the 3rd Generation Partnership Project (3GPP) has defined the discontinuous reception/discontinuous transmission (DRX/DTX) mechanism to allow devices to turn off their radio interfaces and go to sleep in various patterns. However, how to optimize the DRX/DTX scheduling while improving the resource efficiency is still an open issue. In this paper, we investigate an uplink resource allocation problem over long-term evolution machine-to-machine (LTE-M) networks, which is standardized by 3GPP to improve performance on IoT. In this network, we consider the periodic, event-driven, and query-based IoT traffic while minimizing the devices' power consumption. We prove this problem to be NP-complete and propose an aggregation-efficient DRX/DTX scheduling (AEDS) scheme. This scheme takes advantage of both spatial and temporal data aggregation while applying DRX/DTX for energy saving. Specifically, the scheme consists of three phases. The first phase exploits long-term static scheduling for periodic data to ensure the latency and data rate while minimizing the devices' wake-up time. The second phase tries to decrease devices' power consumption through precisely determining their DRX/DTX configurations. Finally, the third phase employs short-term dynamic scheduling for event-driven and query-based data to improve transmission efficiency. Therefore, both small data and power consumption problems are relieved. Extensive simulation results show that the proposed scheme can improve resource efficiency, enlarge network capacity while reducing power consumption compared to the existing schemes. (C) 2018 Elsevier B.V. All rights reserved.
Energy-Efficient Dynamic Point Selection for Cloud Radio Access Networks (C-RAN)
(2017-01-01)
Hsu, Ching-Kuo
;
Liang, Jia-Ming
;
Wu, Kun-Ru
;
Chen, Jen-Jee
;
Tseng, Yu-Chee
Cloud-RAN (C-RAN) is a promising network architecture for next-generation wireless communications. C-RAN separates computation entities, i. e., Baseband Units (BBUs) from base stations (BSs), and puts BBUs in a cloud located at a centralized network. With C-RAN, user equipments (UEs) can receive data from multiple collaborative cells and thus can leverage the dynamic point selection (DPS) technology to improve network efficiency. To save the energy of UEs, 3GPP LTE-A has defined the Discontinuous Reception (DRX) mechanism to allow UEs to turn off their radio interfaces and go to sleep in a periodical manner. However, how to cooperate DRX with DPS under the C-RAN architecture is still an open issue. Therefore, this paper addresses the resource allocation problem in C-RAN by asking how to optimize the energy conservation of UEs based on DRX while reserving sufficient bandwidths for UEs considering their quality-of-service (QoS) in C-RAN with DPS. To solve this problem, we propose an energy-efficient DPS scheduling scheme. The key idea of our scheme is to serve the UEs in the intersection of cells continuously and allocate resource tightly to avoid additional wake-up intervals. Extensive simulation results show that our scheme can serve more UEs while enhancing throughput and reducing their energy consumption as compared to the existing schemes.
Spatial and Temporal Aggregation for Small and Massive Transmissions in LTE-M Networks
(2017-01-01)
Chang, Po-Yen
;
Liang, Jia-Ming
;
Chen, Jen-Jee
;
Wu, Kun-Ru
;
Tseng, Yu-Chee
Machine-to-machine (M2M) communication is one of the key technologies to realize Internet of Things (IoT). Since IoT applications are mainly for smart sensing, such as metering, home surveillance, disaster detection, and e-health, their special sensing/uploading behaviors will result in periodic and/or eventdriven small data transmissions, which may potentially decrease the radio resource efficiency. On the other hand, the widespread deployment of IoT raises the concurrent massive connectivity of IoT devices. How to solve these two problems is a critical issue. In this paper, we investigate an uplink resource allocation problem which considers the periodic, event-driven, and query-based IoT traffic behaviors over LTE-M. The proposed approach takes advantage of data aggregation and both spatial and temporal reuse. Our solution exploits long-term static scheduling for periodic data to ensure the latency and data rate, and employs short-term dynamic scheduling for event-driven, query-based data to improve transmission efficiency. Therefore, both small data and massive connectivity problems are relieved. Extensive simulation results show that the proposed scheme can improve resource efficiency and enlarge network capacity effectively.

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