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Full-Text Articles in Engineering

Scalable And Fully Distributed Localization In Large-Scale Sensor Networks, Miao Jin, Su Xia, Hongyi Wu, Xianfeng David Gu Jun 2017

Scalable And Fully Distributed Localization In Large-Scale Sensor Networks, Miao Jin, Su Xia, Hongyi Wu, Xianfeng David Gu

Electrical & Computer Engineering Faculty Publications

This work proposes a novel connectivity-based localization algorithm, well suitable for large-scale sensor networks with complex shapes and a non-uniform nodal distribution. In contrast to current state-of-the-art connectivity-based localization methods, the proposed algorithm is highly scalable with linear computation and communication costs with respect to the size of the network; and fully distributed where each node only needs the information of its neighbors without cumbersome partitioning and merging process. The algorithm is theoretically guaranteed and numerically stable. Moreover, the algorithm can be readily extended to the localization of networks with a one-hop transmission range distance measurement, and the propagation of …


A Novel Approach To Complex Human Activity Recognition, Md Osman Gani Apr 2017

A Novel Approach To Complex Human Activity Recognition, Md Osman Gani

Dissertations (1934 -)

Human activity recognition is a technology that offers automatic recognition of what a person is doing with respect to body motion and function. The main goal is to recognize a person's activity using different technologies such as cameras, motion sensors, location sensors, and time. Human activity recognition is important in many areas such as pervasive computing, artificial intelligence, human-computer interaction, health care, health outcomes, rehabilitation engineering, occupational science, and social sciences. There are numerous ubiquitous and pervasive computing systems where users' activities play an important role. The human activity carries a lot of information about the context and helps systems …


Analysis Of Feature Detector And Descriptor Combinations With A Localization Experiment For Various Performance Metrics, Ertuğrul Bayraktar, Pinar Boyraz Jan 2017

Analysis Of Feature Detector And Descriptor Combinations With A Localization Experiment For Various Performance Metrics, Ertuğrul Bayraktar, Pinar Boyraz

Turkish Journal of Electrical Engineering and Computer Sciences

The purpose of this study is to provide a detailed performance comparison of feature detector/descriptor methods, particularly when their various combinations are used for image-matching. The localization experiments of a mobile robot in an indoor environment are presented as a case study. In these experiments, 3090 query images and 127 dataset images were used. This study includes five methods for feature detectors (features from accelerated segment test (FAST), oriented FAST and rotated binary robust independent elementary features (BRIEF) (ORB), speeded-up robust features (SURF), scale invariant feature transform (SIFT), and binary robust invariant scalable keypoints (BRISK)) and five other methods for …


Design And Theoretical Analysis Of Advanced Power Based Positioning In Rf System, Lei Wang Jan 2017

Design And Theoretical Analysis Of Advanced Power Based Positioning In Rf System, Lei Wang

Doctoral Dissertations

"Accurate locating and tracking of people and resources has become a fundamental requirement for many applications. The global navigation satellite systems (GNSS) is widely used. But its accuracy suffers from signal obstruction by buildings, multipath fading, and disruption due to jamming and spoof. Hence, it is required to supplement GPS with inertial sensors and indoor localization schemes that make use of WiFi APs or beacon nodes. In the GPS-challenging or fault scenario, radio-frequency (RF) infrastructure based localization schemes can be a fallback solution for robust navigation. For the indoor/outdoor transition scenario, we propose hypothesis test based fusion method to integrate …


Heterogeneous Multi-Sensor Fusion For 2d And 3d Pose Estimation, Hanieh Deilamsalehy Jan 2017

Heterogeneous Multi-Sensor Fusion For 2d And 3d Pose Estimation, Hanieh Deilamsalehy

Dissertations, Master's Theses and Master's Reports

Sensor fusion is a process in which data from different sensors is combined to acquire an output that cannot be obtained from individual sensors. This dissertation first considers a 2D image level real world problem from rail industry and proposes a novel solution using sensor fusion, then proceeds further to the more complicated 3D problem of multi sensor fusion for UAV pose estimation.

One of the most important safety-related tasks in the rail industry is an early detection of defective rolling stock components. Railway wheels and wheel bearings are two components prone to damage due to their interactions with the …


Development And Experimental Evaluation Of A 3d Ultra-Wideband Localization System, Ali Muqaibel Jan 2017

Development And Experimental Evaluation Of A 3d Ultra-Wideband Localization System, Ali Muqaibel

Turkish Journal of Electrical Engineering and Computer Sciences

In this paper, an ultra-wideband (UWB) synthetic aperture radar system that can perform 3D localization of objects is implemented. The system consists of a moving platform that positions two UWB horn antennas. The 3D image construction is performed using the delay-sum beamforming algorithm. Experiments were performed using two data acquisition techniques, namely, background measurements technique and change detection. The former can be used for imaging stationary targets while the latter is applicable for moving objects. At different distances and orientations from the antennas, various targets were imaged. Through-wall imaging was also considered. The system is augmented with a graphical user …


Ego-Localization Navigation For Intelligent Vehicles Using 360° Lidar Sensor For Point Cloud Mapping, Tyler Naes Jan 2017

Ego-Localization Navigation For Intelligent Vehicles Using 360° Lidar Sensor For Point Cloud Mapping, Tyler Naes

Electronic Theses and Dissertations

With its prospects of reducing vehicular accidents and traffic in highly populated urban areas by taking the human error out of driving, the future in automobiles is leaning towards autonomous navigation using intelligent vehicles. Autonomous navigation via Light Detection And Ranging (LIDAR) provides very accurate localization within a predefined, a priori, point cloud environment that is not possible with Global Positioning System (GPS) and video camera technology. Vehicles may be able to follow paths in the point cloud environment if the baseline paths it must follow are known in that environment by referencing objects detected in the point cloud …