Browsing by Author "Chen, Ling-Jyh"

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A Study of Comfort Measuring System Using Taxi Trajectories
(2011)
Tung, Li-Ping
;
Chien, Tsung-Hsun
;
Wang, Ting-An
;
Lin, Cheng-Yu
;
Jeng, Shyh-Kang
The comfort of rides has been identified as one of the top criteria that affects passengers' satisfaction with public transportation systems. Conventional comfort measurement approaches rely on professional measure tools or interviews from passengers, which are costly, time-consuming, and not yet feasible. The concept of Internet of Things (IoT) is a new solution to answer this problem. The idea of IoT is to interconnect state-of-the-art digital products in physical world to provide more powerful applications. Vehicles equipped with GPS devices and wireless access technologies are parts of the IoT elements in traffic networks. We use the GPS data to measure the comfort level of vehicle rides, and provide a detailed comfort statistics as a value added service. Using real data collected from one of the Taipei taxi service providers, we show that over 95% taxi trajectories are viewed as comfortable. In addition, rides without passengers get higher comfort scores than with passengers. We also give the rankings of all taxi drivers according to a number of criteria, such as the comfort score and the number of loads. With the ranking results, we can track back to the trajectories and infer drives' driving behaviors, road conditions, and traffic conditions. We believe that the proposed solution has the potential to provide a representative comfort measurement service for taxi services and additional value-added services for public transportation systems.
Appliance Control by TDoA-based Localization and Gesture Recognition
(2018-01-01)
Chiang, Ting-Hui
;
Chen, Yan-Ann
;
Chang, Chun-Ting
;
Chen, Ling-Jyh
;
Tseng, Yu-Chee
Smart home is one of the major Internet of Things (IoT) applications. When realizing a smart home, designing an intuitive interaction for appliance control has become a crucial issue. A control intention to an appliance comprises two main meanings, identification and control command. But, previous works seldom deliver these two meanings at the same time. To fully convey the control intention, this paper proposes a scheme of intuitive appliance control that tracks and recognizes hand moving trajectory and hand gestures respectively by exploiting acoustic information. We utilize a 3D positioning method based on time difference of arrival (TDoA) of acoustic signals to detect the trajectory of a hand movement for appliance identification and design a gesture recognition method by Doppler effect for control command. We validate the effectiveness of the proposed scheme via real-life experiments. The results show that average locating errors to the targets are 5.24 degrees and 10.35 degrees in the horizontal and vertical planes respectively and the accuracy of gesture recognition is 96.66%. Since human's eyesight is horizontal to the ground, locating an object in the vertical view is error-prone. We also provide a scroll gesture to assist the appliance selection.
Calorie Map: An Activity Intensity Monitoring System based on Wireless Signals
(2017-01-01)
Chiang, Ting-Hui
;
Chuang, Yi-Ta
;
Ke, Chia-Liang
;
Chen, Ling-Jyh
;
Tseng, Yu-Chee
Recently, elder care services, especially for those with chronic diseases, have become an important application in the field of IoT. Several studies have reported that the progress of chronic diseases can be slowed down effectively by moderate physical activities. In this paper, we propose an activity intensity monitoring system to support continuous monitoring of indoor calorie consumption. The system uses wireless signals to infer calorie burned in walking. In the proposed system, Bluetooth smart beacons are deployed in various spaces of a house. The elders who wear smart wristbands are continuously monitored for their locations by received wireless signals. The system has the following features. First, it utilizes wireless signals as location and activity intensity indicators; inertial sensors are only used in the training stage. Second, it is semi-training free and only needs relatively short training time to start using the monitoring services. Finally, the system is map-free, in the sense that it can be easily deployed without constructing the interior map of the house. A prototype system is implemented on a smartphone to evaluate the feasibility of the proposed system.
DEMO: LASS: A Location-Aware Sensing System for Participatory PM2.5 Monitoring
(2016)
Chen, Ling-Jyh
;
Hsu, Wuulong
;
Cheng, MingWei
;
Lee, Hu-Cheng
;
交大名義發表
Exploiting Mobility for Location Promotion in Location-based Social Networks
(2014)
Zhu, Wen-Yuan
;
Peng, Wen-Chih
;
Chen, Ling-Jyh
;
交大名義發表
;
National Chiao Tung University
In this paper, we target the location promotion problem in location-based social networks (LBSNs). The location promotion problem is given a location, we select a set of users as seeds to influence as many users as possible who are likely to visit a selected location. Specifically, we model the location promotion problem as an influence maximization problem on a graph and explore the independent cascading diffusion model on the graph. To determine the propagation probability of the edges of our proposed graph, the relation between users and the selected location should be detected. A property of LBSN is that the major reason of users visiting a location is based on their mobility. Therefore, we propose a mobility model DMM (Distance-based Mobility Model) to model each user\'s mobility. DMM exploits random walk with restart and the power law property of users\' movements. Based on DMM and the selected location, the propagation probability of edges can be derived. In the evaluation, we show the performance of our proposed algorithms on two real datasets.
Exploiting Viral Marketing for Location Promotion in Location-Based Social Networks
(2016-12)
Zhu, Wen-Yuan
;
Peng, Wen-Chih
;
Chen, Ling-Jyh
;
Zheng, Kai
;
Zhou, Xiaofang
With the explosion of smartphones and social network services, location-based social networks (LBSNs) are increasingly seen as tools for businesses (e.g., restaurants and hotels) to promote their products and services. In this article, we investigate the key techniques that can help businesses promote their locations by advertising wisely through the underlying LBSNs. In order to maximize the benefit of location promotion, we formalize it as an influence maximization problem in an LBSN, i.e., given a target location and an LBSN, a set of k users (called seeds) should be advertised initially such that they can successfully propagate and attract many other users to visit the target location. Existing studies have proposed different ways to calculate the information propagation probability, that is, how likely it is that a user may influence another, in the setting of a static social network. However, it is more challenging to derive the propagation probability in an LBSN since it is heavily affected by the target location and the user mobility, both of which are dynamic and query dependent. This article proposes two user mobility models, namely the Gaussian-based and distance-based mobility models, to capture the check-in behavior of individual LBSN users, based on which location-aware propagation probabilities can be derived. Extensive experiments based on two real LBSN datasets have demonstrated the superior effectiveness of our proposals compared with existing static models of propagation probabilities to truly reflect the information propagation in LBSNs.
Exploiting Viral Marketing for Location Promotion in Location-Based Social Networks
(2016-12)
Zhu, Wen-Yuan
;
Peng, Wen-Chih
;
Chen, Ling-Jyh
;
Zheng, Kai
;
Zhou, Xiaofang
With the explosion of smartphones and social network services, location-based social networks (LBSNs) are increasingly seen as tools for businesses (e.g., restaurants and hotels) to promote their products and services. In this article, we investigate the key techniques that can help businesses promote their locations by advertising wisely through the underlying LBSNs. In order to maximize the benefit of location promotion, we formalize it as an influence maximization problem in an LBSN, i.e., given a target location and an LBSN, a set of k users (called seeds) should be advertised initially such that they can successfully propagate and attract many other users to visit the target location. Existing studies have proposed different ways to calculate the information propagation probability, that is, how likely it is that a user may influence another, in the setting of a static social network. However, it is more challenging to derive the propagation probability in an LBSN since it is heavily affected by the target location and the user mobility, both of which are dynamic and query dependent. This article proposes two user mobility models, namely the Gaussian-based and distance-based mobility models, to capture the check-in behavior of individual LBSN users, based on which location-aware propagation probabilities can be derived. Extensive experiments based on two real LBSN datasets have demonstrated the superior effectiveness of our proposals compared with existing static models of propagation probabilities to truly reflect the information propagation in LBSNs.
Exploring Sequential Probability Tree for Movement-Based Community Discovery
(2014-11-01)
Zhu, Wen-Yuan
;
Peng, Wen-Chih
;
Hung, Chih-Chieh
;
Lei, Po-Ruey
;
Chen, Ling-Jyh
In this paper, we tackle the problem of discovering movement-based communities of users, where users in the same community have similar movement behaviors. Note that the identification of movement-based communities is beneficial to location-based services and trajectory recommendation services. Specifically, we propose a framework to mine movement-based communities which consists of three phases: 1) constructing trajectory profiles of users, 2) deriving similarity between trajectory profiles, and 3) discovering movement-based communities. In the first phase, we design a data structure, called the Sequential Probability tree (SP-tree), as a user trajectory profile. SP-trees not only derive sequential patterns, but also indicate transition probabilities of movements. Moreover, we propose two algorithms: BF (standing for breadth-first) and DF (standing for depth-first) to construct SP-tree structures as user profiles. To measure the similarity values among users\' trajectory profiles, we further develop a similarity function that takes SP-tree information into account. In light of the similarity values derived, we formulate an objective function to evaluate the quality of communities. According to the objective function derived, we propose a greedy algorithm Geo-Cluster to effectively derive communities. To evaluate our proposed algorithms, we have conducted comprehensive experiments on two real data sets. The experimental results show that our proposed framework can effectively discover movement-based user communities.
Measuring Link Characteristics of Power Line Communication Systems
(2013)
Lee, Wei-Xian
;
Tung, Li-Ping
;
Ho, Yao-Hua
;
Chen, Ling-Jyh
;
資訊工程學系
Knowing link characteristics of a network connection is essential for the efficient design, management, and usage of a network. In view of the proliferation of power line communication systems, in this work, we propose a novel measurement approach, called PLC-Probe, to concurrently measure link capacity and available bandwidth of PLC links. PLC-Probe uses \'train-chirps\' to probe the network, and it combines the strengths of the packet train and packet chirp approaches for estimation of link characteristics. Using testbed experiment, we evaluate the proposed approach and show that PLC-Probe is accurate, stable, and robust against cross traffic. Moreover, PLC-Probe is simple, effective, and applicable to other multi-rated PLC-like networks.
MetroNet: a disruption-tolerant approach for mobile downloads on metro systems
(2014-08-01)
Tung, Li-Ping
;
Chen, Yi-Chao
;
Lan, Kun-chan
;
Chen, Ling-Jyh
;
交大名義發表
In this study, we propose a disruption-tolerant network based system called MetroNet, which exploits the precise schedules of metro systems to pre-fetch data and facilitate mobile Internet downloads, even if an end-to-end path between the source (i.e. content sources) and the destination (i.e. users) does not exist contemporaneously. Using a comprehensive set of simulations, as well as real-world scenarios of the Taipei and Atlanta metro systems, we demonstrate that MetroNet can handle the intermittent Internet connectivity caused by mobility and therefore provide a better mobile download service. The simulation results demonstrate that the proposed call admission control algorithm utilises the network resource effectively and provides better quality of service for mobile users than the first-come-first-serve and least-first algorithms. Copyright (C) 2013 John Wiley & Sons, Ltd.
Modeling User Mobility for Location Promotion in Location-based Social Networks
(2015-01-01)
Zhu, Wen-Yuan
;
Peng, Wen-Chih
;
Chen, Ling-Jyh
;
Zheng, Kai
;
Zhou, Xiaofang
With the explosion of smartphones and social network services, location-based social networks (LBSNs) are increasingly seen as tools for businesses (e.g., restaurants, hotels) to promote their products and services. In this paper, we investigate the key techniques that can help businesses promote their locations by advertising wisely through the underlying LBSNs. In order to maximize the benefit of location promotion, we formalize it as an influence maximization problem in an LBSN, i.e., given a target location and an LBSN, which a set of k users (called seeds) should be advertised initially such that they can successfully propagate and attract most other users to visit the target location. Existing studies have proposed different ways to calculate the information propagation probability, that is how likely a user may influence another, in the settings of static social network. However, it is more challenging to derive the propagation probability in an LBSN since it is heavily affected by the target location and the user mobility, both of which are dynamic and query dependent. This paper proposes two user mobility models, namely Gaussian-based and distance based mobility models, to capture the check-in behavior of individual LBSN user, based on which location-aware propagation probabilities can be derived respectively. Extensive experiments based on two real LBSN datasets have demonstrated the superior effectiveness of our proposals than existing static models of propagation probabilities to truly reflect the information propagation in LBSNs.
NB-IoTtalk: A Service Platform for Fast Development of NB-IoT Applications
(2019-02-01)
Lin, Yi-Bing
;
Tseng, Hung-Chun
;
Lin, Yun-Wei
;
Chen, Ling-Jyh
;
資訊工程學系
Narrowband Internet of Things (NB-IoT) is considered as a promising wireless communications technology for Internet of Things (IoT) especially for the outdoor environment. Many outdoor IoT applications involve large numbers of homogeneous NB-IoT devices. It is tedious to specify and accommodate these devices during application development. To resolve this issue, this paper proposes a service platform for fast development of NB-IoT applications called NB-IoTtalk. This platform utilizes a tag mechanism to provide an easy-to-manipulate graphical user interface to accommodate a large number of NB-IoT devices in an application and transparently show them in a visual map. Our approach automatically creates and parses the device profile used to interpret the payload of an NB-IoT message. We then use a smart parking lot application as an example to investigate the event-triggered reporting of NB-IoT in terms of the time-to-live (TTL) report frequency and the outage detection accuracy. This paper provides the guidelines to set the TTL interval for event-triggered NB-IoT applications.
Performance of Splitting LTE-WLAN Aggregation
(2019-10-01)
Lin, Yi-Bing
;
Tseng, Hung-Chun
;
Wang, Li-Chang
;
Chen, Ling-Jyh
;
資訊工程學系
LTE-WLAN aggregation (LWA) combines the radio resources of LTE and WLAN to take advantage of Wi-Fi's high availability and indoor coverage, which provides better usage of both WLAN and LTE. In LWA, a user data radio bearer (DRB) is split if its packets are delivered through both LTE and Wi-Fi. For a split DRB, it is important to determine the LTE-to-WLAN ratio (LWR) or the ratio of packets delivered by LTE over WLAN. Based on WLAN's Received Signal Strength Indicator (RSSI), we propose a simple LWR selection rule. Using this rule, we describe a user plane implementation for LWA, where the adaptive LWA routing procedure can be easily implemented in the Radio Resource Management (RRM) and the Packet Data Convergence Protocol (PDCP) layer at the LTE eNB. In our implementation, the maximum LWA throughput is 99.14 percent of the optimal cases, and the packet loss rates are less than 0.0042 percent.
Sensor Calibration for Floor Detection by D2D Communications
(2017-01-01)
Chiang, Ting-Hui
;
Chen, Ling-Jyh
;
Tseng, Yu-Chee
;
資訊工程學系
;
Department of Computer Science
Recent advances in technology have led to the rapid development of the Internet of Things (IoT) and the use of smartphones. The phenomenon has been widely influenced by the use of smart sensors, the accuracy of which is critical to the quality of service provided. Hence, it is vital that sensors are calibrated at both the device and software levels. Some applications even rely on environment-dependent sensing results. Floor detection by barometers is one example, where the pressure of a floor actually depends on the base reference pressure. This observation motivates us to study the floor detection problem by using barometers with device-to-device (D2D) communications. In this paper, we propose the Floor Calibration Protocol (FCP), which enables a mobile device to be calibrated with other mobile devices and anchor devices by considering both temporal and spatial factors. We conducted trace-based simulations to evaluate the proposed scheme and compared its performance with that of state-of-the-art approaches to validate the efficacy of our protocol.
Using known vectors to improve data dissemination in opportunistic networks
(2014-01-01)
Huang, Jyh-How
;
Chen, Ying-Yu
;
Tung, Li-Ping
;
Chen, Ling-Jyh
;
資訊工程學系
An opportunistic network is a type of challenged network in which contacts are intermittent, an end-to-end path rarely exists between the source and the destination, disconnection and reconnection are common occurrences, and link performance is highly variable or extreme. Conventional methods of data dissemination in opportunistic networks rely on a meta-message exchange scheme, called the summary vector (SV), to prevent redundant transmission of data bundles that already exist on receivers. We consider that the SV scheme is costly in terms of the data transmission overhead, which is unaffordable in opportunistic networks. Hence, we propose an alternative scheme, called the known vector (KV), to improve the efficiency of meta-message exchanges for data transmission in opportunistic networks. Using a comprehensive set of simulations with realistic network scenarios, we demonstrate that the KV scheme can be easily integrated into existing opportunistic network routing protocols (e.g., Epidemic and PRoPHET routing). Moreover, it can reduce the communication overhead significantly, thereby improving energy efficiency for data transmission in opportunistic networks.
Wireless Location Tracking by a Sensor-Assisted Particle Filter and Floor Plans in a 2.5-D Space
(2018-01-01)
Lo, Chi-Chung
;
Chiang, Ting-Hui
;
Lee, Tsu-Kuang
;
Chen, Ling-Jyh
;
Tseng, Yu-Chee
Indoor localization systems have attracted considerable attention recently. A lot of works have used wireless signals from existing base stations to track users' locations. The major challenge to such systems is the signal-drifting problem. A promising direction to conquer this problem is to fuse the tracked wireless signals with inertial sensing data. In this work, we consider location tracking in a multi-floor building, which we call a 2.5-D space, by taking wireless signals, inertial sensing data, and indoor floor plans of a 2.5-D space as inputs and building a SPF (sensor-assisted particle filter) model to fuse these data. Inertial sensors are to capture human mobility, while particles reflect our belief of the user's potential locations. Our work makes the following contributions. First, we propose a model to partition a 2.5-D space into multiple floors connected by stairs and elevators and further partition each floor, according to its floor plan, into logical units connected by passages. Second, based on the 2.5D space model, we then propose particle sampling and resampling mechanisms over the logical units using wireless signal strengths and inertial sensing data to adjust our beliefs of the user's potential locations. Third, to conquer the signal-drifting problem, we propose a weighting mechanism to control the distribution of particles based on user's activities of walking on grounds/stairs and taking elevators. A prototype has been developed and tested to verify the model and its accuracy.
y A Study of Comfort Measuring System Using Taxi Trajectories
(2011)
Tung, Li-Ping
;
Chien, Tsung-Hsun
;
Wang, Ting-An
;
Lin, Cheng-Yu
;
Jeng, Shyh-Kang
The comfort of rides has been identified as one of the top criteria that affects passengers\' satisfaction with public transportation systems. Conventional comfort measurement approaches rely on professional measure tools or interviews from passengers, which are costly, time-consuming, and not yet feasible. The concept of Internet of Things (IoT) is a new solution to answer this problem. The idea of IoT is to interconnect state-of-the-art digital products in physical world to provide more powerful applications. Vehicles equipped with GPS devices and wireless access technologies are parts of the IoT elements in traffic networks. We use the GPS data to measure the comfort level of vehicle rides, and provide a detailed comfort statistics as a value added service. Using real data collected from one of the Taipei taxi service providers, we show that over 95% taxi trajectories are viewed as comfortable. In addition, rides without passengers get higher comfort scores than with passengers. We also give the rankings of all taxi drivers according to a number of criteria, such as the comfort score and the number of loads. With the ranking results, we can track back to the trajectories and infer drives\' driving behaviors, road conditions, and traffic conditions. We believe that the proposed solution has the potential to provide a representative comfort measurement service for taxi services and additional value-added services for public transportation systems.