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Power internet of Things Access System based on Low Power Communication technology

Power Internet of Things Access System Based on Low Power Co...

引用

international conference on Communication systems and Network Technologies (CSNT)

作者： Zhigang Jiang Liming Ren Bing Zhu Jiafeng Jiang School of Computer Science and Technology University of Science and Technology of China Hefei China School of Department of Electronic Information and Electrical Engineering Hefei University Hefei China School of Computer and Information Hefei University of Technology Hefei China School of Information Engineering Inner Mongolia University of Science and Technology Baotou China

ISBN: (数字)9798331531935

ISBN: (纸本)9798331531942

In response to the issues of data transmission energy efficiency and network coverage in the power internet of Things system, this study introduces an access scheme based on low-power communication technology. By optimizing the network architecture and communication protocol, the aim is to improve the energy efficiency of sensor nodes in the power internet of Things and reduce communication latency. Firstly, an access scheme based on low power wide area network (LPWAN) technology is designed. LoRa (Long Range Radio) or NB-IoT (Narrow Band internet of Thing) is selected as the communication protocol. By optimizing the working mode of sensor nodes, periodic transmission and event-driven mechanism are adopted. Secondly, an adaptive data transmission mechanism is designed to dynamically adjust the transmission frequency and rate according to environmental changes to ensure reliability under different network conditions. Furthermore, deep sleep mode and power consumption scheduling algorithm are adopted, and the network architecture adopts star topology to ensure the efficiency of signal coverage and data forwarding, and the secure transmission of data information is guaranteed by encryption and authentication mechanism. Finally, through simulation and actual deployment, the performance of the scheme in the actual environment is verified, and its stability and data transmission efficiency under different network scales are evaluated. The battery life of periodic wake-up mode is significantly lower than that of deep sleep mode. Under low-frequency transmission (once an hour), the battery life is 320 days. In periodic wake-up mode, the average power consumption of sensor nodes is significantly higher than that of deep sleep mode. At low frequency transmission, average power consumption is 3.5 mW and battery life drops to 75 days. The power internet of Things access system based on low-power communication technology proposed in this work effectively solves the bottleneck pr

关键词： Power demand Protocols Network architecture Communications technology Energy efficiency Stability analysis Delays Batteries internet of Things Thermal stability

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Classification Types of Apples In Real Time Using SSD Mobilenet

Classification Types of Apples In Real Time Using SSD Mobile...

引用

Control & Automation, Electronics, Robotics, internet of Things, and Artificial Intelligence (CERIA), IEEE international conference on

作者： Fahrurrozi Lubis Ainul Hizriadi Arya Pratama Tarigan Deddy F Sihombing Department of Information Technology Universitas Sumatera Utara Medan Indonesia

ISBN: (数字)9798331511166

ISBN: (纸本)9798331511173

Apples are one type of fruit commodity that is very easy and often found in Indonesia. In classifying the types of apples, it is determined by several parameters, including weight, size, weight, characteristics, color, and many others. The grouping of apples in terms of shape and skin color is an important factor in the identification process. At the stage of identifying the type of apple manually by the human eye, the perception tends to be subjective due to color composition factors such as royal gala apples, fuji apples, and Washington apples. Therefore, we need a tool with a system that can select apples based on the type. This real-time apple type classifier will use the SSD-MobileNet method which is used for feature extraction and the SSD model will be used for object detection in the image. This study resulted in an accuracy of 92.6% for Royal Gala Apples 94.7%, Fuji Apples 92%, and Washington Apples 91.2%.

关键词： Accuracy image color analysis Shape Robot vision systems Object detection Feature extraction Real-time systems Skin internet of Things Robots

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Improving gesture recognition with object tracking and image stabilization to communicate with industrial Cobots

Improving gesture recognition with object tracking and image...

引用

international IEEE conference on signal-image Technologies and internet-based System

作者： Victor Medina Heierle Leire Varona Fontanal Víctor Fernández-Carbajales Cañete Tree Technology S.A. Spain

Collaborative robots (Cobots) coexist and interact with human workers in industrial environments to accomplish certain tasks. In this project, a set of static and dynamic gestures have been defined to allow humans to communicate with the cobots, simplifying the operation of the cobot from the distance. For the cobot not to confuse these gestures with random movement of the workers, and to distinguish different gestures from each other, each gesture consist of a specific sequence of movements. If either the person or the cobot move during the performance of a gesture sequence, misdetections can occur. In this work, we propose a methodology that combines a traditional image stabilization algorithm with region extraction using information from object tracking algorithms to reduce gesture misdetections by compensating for the movement of a subject within the image while performing a gesture. Our results show that while we cannot see much improvement (measured in terms of the distance of pose points to the reference point of the gesture detector) with simply using information from the tracking algorithm, the improvement more than triples when combined with a traditional Kalman-based image stabilization algorithm.

关键词： Service robots Collaboration Gesture recognition Detectors Object tracking Data mining Task analysis

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Remote Sensing image Mosaic technology based on Improved SIFT Algorithm 11th

Remote Sensing Image Mosaic Technology Based on Improved SIF...

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11th international conference on Communications, signal Processing, and systems, CSPS 2022

作者： Wang, Meng Wang, Feng-kun Anhui Technical College of Mechanical and Electrical Engineering Anhui Wuhu241002 China

ISBN: (纸本)9789819926527

To solve the problem of a large amount of computation and low efficiency of the traditional remote sensing image mosaic algorithm, an Improved SIFT feature matching image mosaic algorithm is proposed. Aiming at the disadvantage of too many dimensions of feature point descriptors in SIFT algorithm, a dimension reduction scheme is proposed. Centered on the feature point, concentric circles are constructed with the radius of 2 pixels, 4 pixels and 6 pixels respectively. The region is divided according to the distance from the feature point. If the distance is close, the weight is high, and if the distance is far, the weight is low. The region is divided into 4, 8, and 16 partitions, so as to generate a 56-dimensional descriptor. Furthermore, the feature points in the image matching are divided into two data sets, namely, maximum and minimum. The best matching point is selected by calculating the distance between the maximum and minimum, which reduces the amount of calculation of image matching and saves the algorithm time. Finally, the weighted smoothing method is used for image mosaic. Experimental tests were carried out on the three situations of remote sensing image scaling, rotation, and gray change. The results show that the proposed algorithm can effectively reduce the calculation amount and accelerate the stitching speed, and the stitching effect is ideal. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Pixels

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Multi-Domain image Translation Adversarial Network based on Artificial Intelligence 3

Multi-Domain Image Translation Adversarial Network Based on ...

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3rd international conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Zhang, Lili College of Digital Art and Media Shandong University of Art & Design Jinan China

ISBN: (纸本)9798331508456

Traditional image translation methods often face difficulties such as differences in cross domain data distribution and difficulty in maintaining semantic consistency. Therefore, this article cites a generative adversarial network (GAN) based approach to capture mapping relationships between different domains. Firstly, this article adopts the Conditional Generative Adversarial Network (cGAN) framework to generate multi domain images. Next, this article introduces a shared encoder and multiple decoder structure. Finally, this article improved the performance of image translation results through optimization. In the experimental results, our method performed well on multiple standard datasets. The SSIM (Structural Similarity Index) value for the ink painting to oil painting task remains stable at around 0.88, and the PSNR (Peak signal to Noise Ratio) reaches 32.5 dB. In terms of diversity generation, this method also significantly improves the diversity and visual naturalness of image translation. Finally, the method proposed in this article significantly improves the quality and diversity of style transfer. © 2025 IEEE.

关键词： Generative adversarial networks

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Power internet of Things Access System based on Low Power Communication technology 14

Power Internet of Things Access System Based on Low Power Co...

引用

14th IEEE international conference on Communication systems and Network Technologies, CSNT 2025

作者： Jiang, Zhigang Ren, Liming Zhu, Bing Jiang, Jiafeng School of Computer Science and Technology University of Science and Technology of China Anhui Hefei230000 China School of Department of Electronic Information and Electrical Engineering Hefei University Anhui Hefei230000 China School of Computer and Information Hefei University of Technology Anhui Hefei230000 China School of Information Engineering Inner Mongolia University of Science and Technology Inner Mongolia Baotou014017 China

ISBN: (纸本)9798331531935

关键词： internet of things

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IoT based Line of Control Monitoring System

IoT based Line of Control Monitoring System

引用

Machine Learning and Autonomous systems (ICMLAS), international conference on

作者： Taniya Petkar Department of Computer Science And Medical Engineering Faculty of Engineering and Technology Datta Meghe Institute of Higher Education and Research (DU) Wardha Maharashtra India

ISBN: (数字)9798331505745

ISBN: (纸本)9798331505752

This paper presents a novel line-of-control (LoC) monitoring system that leverages the internet of Things (IoT) to improve border security. The system creates a strong infrastructure for real-time monitoring throughout critical border regions, especially the Line of Control, by utilizing IoT devices, sensors, and communication technologies. The coverage, timeliness, and data quality of conventional border surveillance systems are frequently compromised. As opposed to this, the suggested system makes use of a wirelessly networked network of intelligent sensors, such as infrared, acoustic, and video cameras. By utilizing sophisticated image processing algorithms and machine learning to analyze the gathered data, the system is able to differentiate between regular activities and any security risks. To help security staff make decisions quickly, real-time updates are transmitted to a centralized control center. Integration with cloud computing also makes data analysis, retrieval, and storage simpler and guarantees data accessibility for forensic investigations and trend research.

关键词： Data analysis Surveillance Scalability Machine learning Cameras Real-time systems Sensor systems Security internet of Things Intelligent sensors

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21st international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and systems, NEW2AN 2021 and 14th conference on internet of Things and Smart Spaces, ruSMART 2021

21st International Conference on Next Generation Teletraffic...

引用

21st international conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and systems, NEW2AN 2021 and 14th conference on internet of Things and Smart Spaces, ruSMART 2021

ISBN: (纸本)9783030977764

The proceedings contain 41 papers. The special focus in this conference is on Next Generation Teletraffic and Wired/Wireless Advanced Networks and systems. The topics include: The Challenges with internet of Things Security for Business;Using a Machine Learning Model for Malicious URL Type Detection;network Slice Degradation Probability as a Metric for Defining Slice Performance Isolation;Geometrical Approach to the Plane Tessellation in the IEEE 802.11 Networks Channel Planning;Heuristic Design Algorithm for Scheduling of URLLC and eMBB Traffics in 5G Cellular Networks;Application of Neural Network to Demodulate SEFDM signals;the Effect of Error Burst When Using a Decision Feedback Algorithm for Receiving Non-orthogonal Multi-frequency signals;instantaneous Interference Evaluation Model for Smart Antennas in 5G Ultra-Dense Networks;selecting a Receiver for Wideband Spectrum Sensing in Cognitive Radio systems based on an Assessment of the signal Environment Complexity;smart Contract Enabled Decentralized Reputation System for E-Commerce Reviews;Analysis of Nonlinear Distortions of FTN signals Transmitted Through TWT Amplifier;Application of Wavelet Transform for ECG Processing;investigation Methods of Dehydrated Protein Films for Biomolecular Electronics;Predicting Energy Consumption for UAV-Enabled MEC Using Machine Learning Algorithm;Deep Learning Approach for Predicting Energy Consumption of Drones based on MEC;Simulation and Experimental Study of Multi-source Application Layer ARQ for FANET;fiber-Optic Recirculating Memory Loop for Wideband Microwave signal;on Smart Greenhouse Issues;structural Shifts on Derivatives Markets at the Time of Increasing Digitalization and Post-pandemic Transformation of the Market;specifics of Forming an Innovation Sector When Developing Industry 4.0 technology;preface.

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Single-Stage Grasping Algorithm for the Manipulator based on Rotational Gaussian Encoding 13

Single-Stage Grasping Algorithm for the Manipulator Based on...

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13th IEEE international conference on CYBER technology in Automation, Control, and Intelligent systems, CYBER 2023

作者： Liu, Zhenghao Liu, Yizhe Yang, Guowei Chen, Dongyue Jia, Tong College of Information Science and Engineering Northeastern University Shenyang China Foshan Graduate School of Innovation Northeastern University China Northeastern University Key Laboratory of Data Analytics and Optimization for Smart Industry Ministry of Education China

ISBN: (纸本)9798350315196

As we all know, there is an unsolved problem for robots to accurately and quickly grasp unknown objects in an unstructured environment. In order to describe the pose information of objects more accurately, a rotational Gaussian encoding method is proposed in this paper. Different from the traditional 2-D Gaussian encoding to represent ground-truth, this method introduces rotation information based on 2-D Gaussian. Grasping is made more accurate and robust by treating the grasp pose as a rotating bounding box in the image plane. In addition, a balanced loss function is introduced in this paper. This loss function not only solves the problem of positive and negative sample imbalance in the traditional cross-entropy loss but also reduces the penalty of points around the Gaussian center location. In this paper, a pixel-level single-stage grasping algorithm is designed in an end-to-end manner without the intermediate process of using anchor points, which saves time and improves the accuracy of grasping simultaneously. Then, the proposed model in this paper is evaluated on two standard datasets, Cornell Dataset and Jacquard Dataset, achieving 96.8% and 94.7% accuracy, respectively. Finally, we use a 6 DoF UR5e robotic arm for real-world grasping experiments. The success rate of single-object grasping is 94.7% and the time to generate the grasp frame is 8 ms. Experiments demonstrat that the algorithm is equally effective in real-world environments and has a faster detection time. © 2023 IEEE.

关键词： signal encoding

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CVulDetector: Cross-domain Vulnerability Detection based on Transfer Learning

CVulDetector: Cross-domain Vulnerability Detection Based on ...

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IEEE international conference on signal and image Processing (ICSIP)

作者： Guoqiang Zeng Wen Zhou Zhongyuan Qin Xin Sun Wen Wang School of Cyber Science and Engineering Southeast University Nanjing China Internet Technology Center State Grid Zhejiang Electric Power Co. Ltd. Research Institute Hangzhou China Internet Department State Grid Zhejiang Electric Power Co. Ltd Hangzhou China

Software vulnerabilities pose a significant threat to computer security, and accurate identification of vulnerabilities has become a challenging task. Although previous work on deep learning-based vulnerability detection has achieved some success, it still faces issues such as 1) insufficient feature extraction capability of the models, and 2) unrealistic assumption of identical distribution between the source and target domains. To address these problems, we propose CVulDetector, a cross-domain vulnerability detection scheme based on transfer learning. Our approach incorporates both natural language characteristics and semantic syntax information of programs, enabling a more comprehensive description of program features. By employing two neural network models, we extract vulnerability-rich features and fine-tune the model using limited labeled data from the target domain after pre-training on a wide range of features from the source domain. Experimental evaluation on three CWE datasets shows an F1-score of 90.6%.

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