IECE - Institute of Emerging and Computer Engineers

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    Academic Editor
    Contributions by role
    Reviewer 3
    Editor 3
    ORCID
    0000-0001-6632-0144
    Weimin Zhang
    Beijing Institute of Technology, China
    Summary
    Edited Journals
    IECE Transactions on Intelligent Systematics
    IECE Contributions
    Articles
    0
    Edited
    3
    Free Access | Research Article | Feature Paper | 26 May 2024
    Pedestrian Trajectory Reconstruction for Indoor Movement Based on Foot-Mounted IMU
    by
    Yeqing Wang
    ,
    Binbin Wang
    IECE Transactions on Intelligent Systematics | Volume 1, Issue 1: 19-29, 2024 | DOI:10.62762/TIS.2024.136995
    Abstract
    A pedestrian navigation system (PNS) that only relies on the foot-mounted IMU is useful for various applications, especially under some severe conditions, such as tracking of firefighters and miners. Due to the complexity of the indoor environment, signal occlusion problems could lead to the failure of certain positioning methods. In complex environments such as fire rescue and emergency rescue, the barometric altimeter fails because of the influence of air pressure and temperature. This paper used an improved zero velocity detection algorithm to improve the accuracy of gait detection. Then, combine the Kalman filter with the zero velocity update algorithm to recognize gait accurately and ta... More >
    Graphical Abstract
    Pedestrian Trajectory Reconstruction for Indoor Movement Based on Foot-Mounted IMU
    Free Access | Research Article | 25 May 2024 | Cited: 3
    Deep Prediction Network Based on Covariance Intersection Fusion for Sensor Data
    by
    Hanchi Ren
    ,
    Yeqing Wang
    ,
    Huijun Ma
    IECE Transactions on Intelligent Systematics | Volume 1, Issue 1: 10-18, 2024 | DOI:10.62762/TIS.2024.136898
    Abstract
    To predict future trends based on the data from sensors is an important technology for many applications, such as the Internet of Things, smart cities, etc. Based on the predicted results, further decisions and system controls can be made. Raw sensor data sets are often complex non-linear data with noise, which results in the difficulty of accurate prediction. This paper proposes a distributed deep prediction network based on a covariance intersection (CI) fusion algorithm in which the deep learning networks, such as long-term and short-term memory networks (LSTM) and gated recurrent unit networks (GRU) are fused by CI fusion algorithm to effectively develop the performance of prediction. Mo... More >
    Graphical Abstract
    Deep Prediction Network Based on Covariance Intersection Fusion for Sensor Data
    Free Access | Research Article | 15 May 2024 | Cited: 2
    Visual Feature Extraction and Tracking Method Based on Corner Flow Detection
    by
    Jiaxi Li
    ,
    Binbin Wang
    ,
    Huijun Ma
    ,
    Longfei Gao
    ,
    Heran Fu
    IECE Transactions on Intelligent Systematics | Volume 1, Issue 1: 3-9, 2024 | DOI:10.62762/TIS.2024.136895
    Abstract
    Frontend feature tracking based on vision is the process in which a robot captures images of its surrounding environment using a camera while in motion. Each frame of the image is then analyzed to extract feature points, which are subsequently matched between pairwise frames to estimate the robot’s pose changes by solving for the variations in these points. While feature matching methods that rely on descriptor-based approaches perform well in cases of significant lighting and texture variations, the addition of descriptors increases computational costs and introduces instability. Therefore, in this paper, a novel approach is proposed that combines sparse optical flow tracking with Shi-Tom... More >
    Graphical Abstract
    Visual Feature Extraction and Tracking Method Based on Corner Flow Detection