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    Volume 2, Issue 4 (Online First) - Table of Contents
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    Online First
    Citations: 0, 0,  0   |   Viewed: 1633, Download: 229
    Free Access | Research Article | 31 December 2024
    Intelligent Logistics Management Robot Path Planning Algorithm Integrating Transformer and GCN Network
    by
    Hao Luo
    ,
    Jianjun Wei
    ,
    Shuchen Zhao
    ,
    Ankai Liang
    ,
    Zhongjin Xu
    ,
    Ruxue Jiang
    IECE Transactions on Internet of Things | Volume 2, Issue 4: 95-112, 2024 | DOI:10.62762/TIOT.2024.918236
    Abstract
    This study focuses on optimizing multimodal robot route planning in intelligent logistics management by integrating Transformer models, Graph Neural Networks (GNNs), and Generative Adversarial Networks (GANs). Using a graph structure representing map information, cargo distribution, and robot states, spatial and resource constraints are considered to optimize paths. Extensive simulations based on real logistics datasets demonstrate significant improvements over traditional methods, with an average 15\% reduction in path length, 20% improvement in time efficiency, and 10% reduction in energy consumption. These results underscore the effectiveness and superiority of the proposed multimodal pat... More >
    Graphical Abstract
    Intelligent Logistics Management Robot Path Planning Algorithm Integrating Transformer and GCN Network
    Free Access | Research Article | 08 December 2024
    Optimized CNNs for Rapid 3D Point Cloud Object Recognition
    by
    Tianyi Lyu
    ,
    Dian Gu
    ,
    Peiyuan Chen
    ,
    Yaoting Jiang
    ,
    Zhenhong Zhang
    ,
    Huadong Pang
    ,
    Li Zhou
    ,
    Yiping Dong
    IECE Transactions on Internet of Things | Volume 2, Issue 4: 83-94, 2024 | DOI:10.62762/TIOT.2024.758153
    Abstract
    This study introduces a method for efficiently detecting objects within 3D point clouds using convolutional neural networks (CNNs). Our approach adopts a unique feature-centric voting mechanism to construct convolutional layers that capitalize on the typical sparsity observed in input data. We explore the trade-off between accuracy and speed across diverse network architectures and advocate for integrating an L1 penalty on filter activations to augment sparsity within intermediate layers. This research pioneers the proposal of sparse convolutional layers combined with L1 regularization to effectively handle large-scale 3D data processing. Our method’s efficacy is demonstrated on the MVTec... More >
    Graphical Abstract
    Optimized CNNs for Rapid 3D Point Cloud Object Recognition
    Free Access | Research Article | 19 November 2024
    IoT-based Smart Home Automation Using Gesture Control and Machine Learning for Individuals with Auditory Challenges
    by
    Baleegha Fatima
    ,
    Bilal Mushtaq
    ,
    Muhammad Ammar Iqbal
    ,
    Abbas Ahmed
    IECE Transactions on Internet of Things | Volume 2, Issue 4: 74-82, 2024 | DOI:10.62762/TIOT.2024.723193
    Abstract
    This paper reviews advancements in assistive technology for deaf and hard of hearing individuals, highlighting the Internet of Things' (IoTs) pivotal role in enhancing their daily lives. Despite progress in sign language technologies, communication barriers persist. To address these gaps, we developed a video-based American Sign Language (ASL) identification system. Our approach utilizes MediaPipe for hand tracking, OpenCV for image normalization, and Gesture Control Convolutional Neural Network (CNN) for gesture localization. Implemented in Python, the system records video streams, filters hand regions, and recognizes ASL letter gestures with high accuracy. Leveraging computer vision and ma... More >
    Graphical Abstract
    IoT-based Smart Home Automation Using Gesture Control and Machine Learning for Individuals with Auditory Challenges
    Free Access | Research Article | 23 October 2024
    The Impact of Supply Chain Finance on Integrated Business Performance of New Energy Vehicle Enterprises
    by
    Chunsheng Wang
    ,
    Shuyan Zhou
    ,
    Jing Ye
    ,
    Haohan Hu
    ,
    Xuetong Wu
    ,
    Zhangcai He
    ,
    Hong Ding
    IECE Transactions on Internet of Things | Volume 2, Issue 4: 63-73, 2024 | DOI:10.62762/TIOT.2024.262824
    Abstract
    With the rapid development of the new energy vehicle (NEV) industry, supply chain finance (SCF) has become one of the key factors promoting the prosperity of this industry. Based on in total 884 samples, this study investigates the impact of SCF on the integrated business performance of NEV enterprises. Through empirical analysis, it is confirmed that SCF significantly and positively affects the integrated business performance. In addition, the results of the mediation effect test indicate that by alleviating financing constraints of small and medium-sized enterprises, SCF enables the improvement of firms' overall business performance. These findings provide new insights to NEV enterprises'... More >
    Graphical Abstract
    The Impact of Supply Chain Finance on Integrated Business Performance of New Energy Vehicle Enterprises