Research Interests:
We propose an indoor localization method using FPFE (Fingerprint Feature Extraction) with Bluetooth Low Energy (BLE) beacon fingerprints. FPFE apples either AE or PCA to extract features of beacon fingerprints and then measures the... more
We propose an indoor localization method using FPFE (Fingerprint Feature Extraction) with Bluetooth Low Energy (BLE) beacon fingerprints. FPFE apples either AE or PCA to extract features of beacon fingerprints and then measures the similarity between the features using the concept of the Minkowski distance. FPFE selects k RPs with the k smallest Minkowski distances for estimating the position of the target device. Experiments are conducted to evaluate the localization error of FPFE. The experimental results show that the FPFE achieves an average error of 0.68 m which is better than those of other related BLE fingerprint-based localization methods.
Research Interests:
Research Interests:
This paper proposes to design and implement a guidance system to guide new students, such as freshmen, to navigate buildings within the campus as an experience to design and implement similar systems in the context of smart cities. The... more
This paper proposes to design and implement a guidance system to guide new students, such as freshmen, to navigate buildings within the campus as an experience to design and implement similar systems in the context of smart cities. The proposed system consists of three main subsystems: the marker-based cyber-physical interaction (CPI) system, the indoor positioning (IP) system, and the augmented-reality (AR) system. With the help of visible markers and invisible markers, the CPI system allows the users to do interactions between the physical and cyber environments, the IP system produces accurate user position information, the AR system provides the users with good user experiences. An Android application, named Engfi Gate, is developed to realize the system design in the test environment. This paper also shows the comparisons of the proposed system with other related systems.
Research Interests:
This paper proposes an indoor location-based augmented reality framework (ILARF) for the development of indoor augmented-reality (AR) systems. ILARF integrates an indoor localization unit (ILU), a secure context-aware message exchange... more
This paper proposes an indoor location-based augmented reality framework (ILARF) for the development of indoor augmented-reality (AR) systems. ILARF integrates an indoor localization unit (ILU), a secure context-aware message exchange unit (SCAMEU), and an AR visualization and interaction unit (ARVIU). The ILU runs on a mobile device such as a smartphone and utilizes visible markers (e.g., images and text), invisible markers (e.g., Wi-Fi, Bluetooth Low Energy, and NFC signals), and device sensors (e.g., accelerometers, gyroscopes, and magnetometers) to determine the device location and direction. The SCAMEU utilizes a message queuing telemetry transport (MQTT) server to exchange ambient sensor data (e.g., temperature, light, and humidity readings) and user data (e.g., user location and user speed) for context-awareness. The unit also employs a web server to manage user profiles and settings. The ARVIU uses AR creation tools to handle user interaction and display context-aware inform...
Research Interests:
This paper proposes to design and implement a guidance system to guide new students, such as freshmen, to navigate buildings within the campus as an experience to design and implement similar systems in the context of smart cities. The... more
This paper proposes to design and implement a guidance system to guide new students, such as freshmen, to navigate buildings within the campus as an experience to design and implement similar systems in the context of smart cities. The proposed system consists of three main subsystems: the marker-based cyber-physical interaction (CPI) system, the indoor positioning (IP) system, and the augmented-reality (AR) system. With the help of visible markers and invisible markers, the CPI system allows the users to do interactions between the physical and cyber environments, the IP system produces accurate user position information, the AR system provides the users with good user experiences. An Android application, named Engfi Gate, is developed to realize the system design in the test environment. This paper also shows the comparisons of the proposed system with other related systems.
Research Interests:
This paper proposes a fingerprint-based indoor localization method, named FPFE (fingerprint feature extraction), to locate a target device (TD) whose location is unknown. Bluetooth low energy (BLE) beacon nodes (BNs) are deployed in the... more
This paper proposes a fingerprint-based indoor localization method, named FPFE (fingerprint feature extraction), to locate a target device (TD) whose location is unknown. Bluetooth low energy (BLE) beacon nodes (BNs) are deployed in the localization area to emit beacon packets periodically. The received signal strength indication (RSSI) values of beacon packets sent by various BNs are measured at different reference points (RPs) and saved as RPs’ fingerprints in a database. For the purpose of localization, the TD also obtains its fingerprint by measuring the beacon packet RSSI values for various BNs. FPFE then applies either the autoencoder (AE) or principal component analysis (PCA) to extract fingerprint features. It then measures the similarity between the features of PRs and the TD with the Minkowski distance. Afterwards, k RPs associated with the k smallest Minkowski distances are selected to estimate the TD’s location. Experiments are conducted to evaluate the localization erro...
Research Interests:
We propose an indoor localization method using FPFE (Fingerprint Feature Extraction) with Bluetooth Low Energy (BLE) beacon fingerprints. FPFE apples either AE or PCA to extract features of beacon fingerprints and then measures the... more
We propose an indoor localization method using FPFE (Fingerprint Feature Extraction) with Bluetooth Low Energy (BLE) beacon fingerprints. FPFE apples either AE or PCA to extract features of beacon fingerprints and then measures the similarity between the features using the concept of the Minkowski distance. FPFE selects k RPs with the k smallest Minkowski distances for estimating the position of the target device. Experiments are conducted to evaluate the localization error of FPFE. The experimental results show that the FPFE achieves an average error of 0.68 m which is better than those of other related BLE fingerprint-based localization methods.
Research Interests:
This paper proposes to design, develop and implement a fast and markerless mobile augmented reality system to achieve the registration for, the visualization of, and the interaction with machines in indoor smart factories with Industry... more
This paper proposes to design, develop and implement a fast and markerless mobile augmented reality system to achieve the registration for, the visualization of, and the interaction with machines in indoor smart factories with Industry 4.0 vision. A lightweight deep-learning image detection module based on MobileNets running on mobile devices is used to detect/recognize different machines and different portions of machines. Internet of Things (IoT) networking allows machines and sensors in machines to report data, such as machine settings and machine states, to the cloud-side server. Thus, augmented information associated with a machine portion can be derived from the server and superimposed with the portion image shown on the device display. Furthermore, interaction methods based on touch gestures and distance calculation are also implemented. A prototype system is developed and tested in a mechanical workshop for the purpose of validation and evaluation. The system is shown to achieve high detection accuracy, intuitive visualization, and unique interaction modes.
Research Interests:
This paper proposes to design, develop and implement a fast and markerless mobile augmented reality system to achieve the registration for, the visualization of, and the interaction with machines in indoor smart factories with Industry... more
This paper proposes to design, develop and implement a fast and markerless mobile augmented reality system to achieve the registration for, the visualization of, and the interaction with machines in indoor smart factories with Industry 4.0 vision. A lightweight deep-learning image detection module based on MobileNets running on mobile devices is used to detect/recognize different machines and different portions of machines. Internet of Things (IoT) networking allows machines and sensors in machines to report data, such as machine settings and machine states, to the cloud-side server. Thus, augmented information associated with a machine portion can be derived from the server and superimposed with the portion image shown on the device display. Furthermore, interaction methods based on touch gestures and distance calculation are also implemented. A prototype system is developed and tested in a mechanical workshop for the purpose of validation and evaluation. The system is shown to achieve high detection accuracy, intuitive visualization, and unique interaction modes.
Research Interests:
A guidance system is needed when freshmen explore their new building environment. With the advancements of mobile technologies, a guidance system using mobile computing devices such as mobile phones or tablets could aid freshmen in... more
A guidance system is needed when freshmen explore their new building environment. With the advancements of mobile technologies, a guidance system using mobile computing devices such as mobile phones or tablets could aid freshmen in locating the desired destination with ease. The proposed system consists of three main subsystems: the marker-based cyber-physical interaction (CPI) system, the indoor positioning (IP) system, and the augmented-reality (AR) system. With the help of visible markers and invisible markers, the CPI system allows the users to do interactions between the physical and cyber environments; the IP system produces accurate user position information; the AR system provides the users with good user experiences. An Android application, named Engfi Gate, is developed to realize the system design in the test environment. This paper also shows the comparisons of the proposed system with other related systems. Furthermore, the design architecture of Engfi Gate system can b...
Research Interests:
PINUS, an indoor weighted centroid localization (WCL) method with crowdsourced calibration, is proposed in this paper. It relies on crowdsourcing to do the calibration for WCL to improve localization accuracy without the device diversity... more
PINUS, an indoor weighted centroid localization (WCL) method with crowdsourced calibration, is proposed in this paper. It relies on crowdsourcing to do the calibration for WCL to improve localization accuracy without the device diversity problem. Smartphones and Bluetooth Low Energy (BLE) beacon devices are applied to realize PINUS for the sake of design validation and performance evaluation.