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检索条件"任意字段=International Conference on Signal-Image Technology and Internet-Based Systems"

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internet of Things Data Aggregation based on image Information Hiding 23

Internet of Things Data Aggregation Based on Image Informati...

引用

7th international conference on Digital signal Processing, ICDSP 2023

作者： Yang, Yanxiang University of Melbourne Australia

ISBN: (纸本)9781450398626

In the era of intelligent information technology of 5G, smart buildings, promoted by the internet of Things, enhance the ability of indoor monitoring and equipment management. The acquisition and transmission of Architectural Physical Environment Data (APED) is a crucial part of the internet of Things (IoT). Traditional methods rely on many sensors and multiple types of network channels, resulting in problems such as many data transmissions and increased communication bandwidth requirements. Therefore, a data aggregation strategy based on data hiding technology is proposed. All the temporal data is hidden in the existing image through a customized lightweight codec scheme and communication protocol based on binary coding, and the data is aggregated into image(s) for uploading without reducing the fidelity of the image, to improve the efficiency of data transmission. The paper uses APED to conduct simulation experiments to verify the feasibility of the technique. The scheme can be extended to other similar internet of Things applications. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.

关键词： internet of things

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Research and Design of a Robot Controller based on MicroPython 17

Research and Design of a Robot Controller Based on MicroPyth...

引用

17th international Congress on image and signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2024

作者： Chen, Dafang Shanghai Jinshan District Youth Activity Center Shanghai201500 China

ISBN: (纸本)9798331507398

With the rapid development of internet of Things technology and embedded systems, the application of robotics technology has become an important role in the field of modern technology. However, traditional robot control units often use C language to develop low-level drivers and application programs, which is difficult to develop and has a long cycle, making it a high threshold for non professional developers. Therefore, exploring a robot controller with high compatibility, rich library functions, and high development efficiency is of great significance. MicroPython is a scripting language, and as a lightweight Python implementation, its concise syntax and rich library functions provide new ideas for the development of robot controllers. This article aims to study the design and implementation of a robot controller based on MicroPython. It will comprehensively introduce the research methods and development process of the controller from three aspects: hardware development, firmware design and burning, and image processing applications, providing a new robot controller solution. With the rapid development of internet of Things technology and embedded systems, the application of robotics technology has become an important role in the field of modern technology. However, traditional robot control units often use C language to develop low-level drivers and application programs, which is difficult to develop and has a long cycle, making it a high threshold for non professional developers. Therefore, exploring a simple, easy-to-use, and highly efficient robot controller is of great significance. © 2024 IEEE.

关键词： Firmware

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PLC signal Level based Traffic Light System Using RPi: An Experimental Setup 3

PLC Signal Level Based Traffic Light System Using RPi: An Ex...

引用

3rd international conference for Advancement in technology, ICONAT 2024

作者： Kumawat, Ashok Kumar Manipal University Jaipur Dept. of Mechatronics Engineering Jaipur India

ISBN: (纸本)9798350354171

It is necessary to regularly enhance the traffic light system's control using the newest technology. The PLC-based systems that are now in use make it difficult to adopt modern technologies like artificial intelligence, machine learning, and the internet of things etc. This work aims to convert the logic level signal based on PLC to a logic level signal based on Raspberry Pi. A raspberry pi is used as the control unit in the development of an experimental four direction-based traffic light prototype. Two different types of logic level converters are used in this system to create signals that are compatible with both 24 V traffic light system and Raspberry Pi. Python programming on the Raspberry Pi is used to control the entire system. © 2024 IEEE.

关键词： Traffic signals

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Research of technology about Video Control based on Real-time Transmission 7

Research of Technology about Video Control Based on Real-tim...

引用

7th IEEE international conference on Information systems and Computer Aided Education, ICISCAE 2024

作者： Wang, Haoxue Li, Jinglan Liu, Huaiqiang Linyi University Linyi China

ISBN: (纸本)9798350350760

With the increasing demand for multimedia on the internet, video technology has gradually become the mainstream of multimedia transmission on the internet. In order to avoid overflow and underflow of buffer in transmission and to ensure the continuity of image of human visual pair, this paper proposes an algorithm to force the transmission rate to be adjusted, considering that the video bit rate cannot be completely the same as the change of network bandwidth. Combining with the characteristics of VTP adaptive coding and packaging scheme, an improved packaging scheme is proposed for real-time video control. The experimental results of end-to-end video transmission system show that video transmission control technology can improve packet loss rate and real-time transmission. ©2024 IEEE.

关键词： Packet loss

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The Analysis of Network Course in Intelligent image Acquisition Education System based on Deep Learning 4

The Analysis of Network Course in Intelligent Image Acquisit...

引用

4th international signal Processing, Communications and Engineering Management conference, ISPCEM 2024

作者： Ge, Qianqian Wei, Cuncun Wu, Dongyan Zhejiang Business Technology Institute Zhejiang Ningbo315012 China

ISBN: (纸本)9798331528676

The internet, big data, and intelligent robots have transformed online education. This study introduces an Enhanced Convolutional Neural Network (CNN+) model optimized with refined weight initialization and strategic activation functions for image recognition. The CNN+ model achieves 99.5% accuracy on MNIST and 75.2% on CIFAR-10, with the Sigmoid-ReLU hybrid boosting performance to 99.2% and 72.3% respectively. These optimizations underscore the importance of strategic CNN architecture choices in enhancing performance, supporting advancements in online education platforms. The CNN+ model represents a significant breakthrough in image recognition for online education. ©2024 IEEE.

关键词： Adversarial machine learning

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ORLQ: A Link Quality-based Routing Protocol for UWSN 8th

ORLQ: A Link Quality-Based Routing Protocol for UWSN

引用

8th international conference on Information Science, Communication and Computing

作者： Luo, Xinman Qiongtai Normal Univ Haikou 570100 Hainan Peoples R China

ISBN: (纸本)9789819617838;9789819617814;9789819617807

With the advancement of underwater internet of Things (IoT) technology, Underwater Wireless Sensor Networks (UWSN) have gradually become a forward-looking technology for marine resource exploration. Faced with the highly dynamic characteristics of UWSN links, it is important to design a reliable and energy-balanced routing scheme. To this end, this paper proposes an Opportunistic Routing protocol based on Link Quality (ORLQ) to address these issues. The Chan algorithm is used to establish distance relationships among nodes in UWSN, thereby obtaining the coordinates of ordinary nodes. based on this, the signal-to-Noise Ratio (SNR) of received data packets is a key factor affecting link quality. The Shannon theorem is used to evaluate the data packet throughput of the link and is used as an influencing factor for the next hop node, designing a link quality metric. Simulation results show that ORLQ outperforms existing routing protocols in terms of network throughput and energy efficiency.

关键词： Chan algorithm link quality opportunistic routing

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Smart Agriculture: CNN-based systems for Early Detection and Diagnosis of Plant Diseases and Pests 2

Smart Agriculture: CNN-based Systems for Early Detection and...

引用

2nd international conference on Intelligent Cyber Physical systems and internet of Things (ICoICI)

作者： Nishitha, Panchareddy Sarika, Tuniki Navya, Soleti Peneti, Subhashini Rajeshwari, Dablikar Vijayakumari, E. N. MLR Inst Technol Hyderabad Dept Comp Sci & Informat Technol Hyderabad India CMR Engn Coll Dept Informat Technol Hyderabad India MLR Inst Technol Dept Comp Sci & Engn Hyderabad India

ISBN: (纸本)9798331540661;9798331540678

Pests impact agricultural production, prompting the need for efficient disease detection in plants. Traditional methods, reliant on manual observation, are time- consuming and imprecise. It uses the Convolutional Neural Network (CNN) for prediction of diseases. The CNNs enhance precision, offering farmers a more effective and streamlined method for disease detection, potentially transforming agricultural practicesUsing transfer learning and pre-trained models, the system successfully extracts information from photographs submitted via a user-friendly website. The CNN based algorithm analyzes these photos using powerful image pre-processing techniques, giving farmers and individuals precise insights into recognized diseases or pest infestations. Plant photos obtained with cellphones are processed using CNN, a specialized image recognition system. A CNN is an effective method in the AI, which scans the image and produces the maximum correct output. It is primarily used in image recognition tasks, where it processes input in the form of pixels. The website design not only allows for easy image submission but also provides results and probable therapy recommendations. This comprehensive solution, which combines cutting-edge CNN technology, transfer learning, and an easy-to-use web interface, enables users to proactively protect their crops, resulting in a more resilient and sustainable agricultural ecosystem.

关键词： Convolutional Neural Network (CNN) Disease Detection Transfer Learning Agricultural Production image Pre-Processing

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A Dual Approach with CycleGANs-based Face Reconstruction and ViT-based Classification 7

A Dual Approach with CycleGANs-based Face Reconstruction and...

引用

IEEE 7th international conference on Advanced Technologies, signal and image Processing (ATSIP)

作者： Ouannes, Laila Ben Khalifa, Anouar Ben Amara, Najoua Essoukri Univ Sousse Ecole Natl Ingenieurs Sousse LATIS Lab Adv Technol & Intelligent Syst Sousse 4023 Tunisia Univ Jendouba Inst Natl Technol & Sci Kef Le Kef 7100 Tunisia

ISBN: (纸本)9798350351491;9798350351484

Facial recognition technology plays a crucial role in various domains, including security, surveillance, and biometric authentication. However, the accuracy of conventional facial recognition systems is significantly compromised in degraded conditions, characterized by head pose variations, occlusions, and variations in lighting. In this study, we propose an innovative approach to address this challenge by integrating advanced deep-learning techniques. Specifically, we leverage Cycle Generative Adversarial Networks (CycleGANs) for facial reconstruction and vision Transformers (ViT) for recognition in degraded conditions. GANs are employed to enhance the quality of degraded facial images by generating high-resolution reconstructions from low-quality inputs. The reconstructed images are then fed into Transformer-based models, which extract discriminative features for robust recognition. To evaluate the effectiveness of our approach, we conducted extensive experiments using publicly available datasets of degraded facial images: the EURECOM Kinect Face Dataset and the IST-EURECOM Light Field Face Database. Our results demonstrate significant improvements in face recognition accuracy compared to traditional methods, particularly in scenarios with low-resolution or occluded faces. Furthermore, we analyze the computational efficiency and scalability of our proposed approach, highlighting its potential for real-world deployment.

关键词： Degraded face recognition face reconstruction CycleGANs Vision Transformers

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Multi-Frequency Water-based Piston Source Superimposed Excitation Channel Equalization technology 2

Multi-Frequency Water-Based Piston Source Superimposed Excit...

引用

2nd IEEE international conference on image Processing and Computer Applications, ICIPCA 2024

作者： Shi, Jiajun Jilin University Changchun China

ISBN: (纸本)9798350360240

This study aims to explore the application of channel equalization technology with multi-frequency water-based piston source superimposed excitation in underwater acoustic communication systems. Underwater acoustic communication is crucial for ocean resource development, but it is affected by the complexity of underwater propagation media and frequency-selective fading. The study involves QPSK signal modulation and the use of the Bellhop acoustic toolbox to simulate underwater multi-path channels, replicating real underwater communication environments. At the receiving end, a bandpass filter is employed to select the corresponding frequency of the QPSK signal, followed by coherent demodulation to restore it to baseband. To address temporal interference and frequency-selective fading, a decision feedback equalizer is introduced for temporal equalization. Through experimentation and simulation, low bit error rate reception signals are achieved, demonstrating the effectiveness of this channel equalization technology in enhancing the quality of underwater acoustic communication systems. © 2024 IEEE.

关键词： Decision feedback equalizers

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Research on the Application of image Preprocessing technology based on Computer Deep Learning in Wireless Communication systems 4

Research on the Application of Image Preprocessing Technolog...

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4th IEEE international conference on Power, Electronics and Computer Applications, ICPECA 2024

作者： Xu, Xiaoqing School of Information Engineering Eurasia University Shaanxi Xi'an China

ISBN: (纸本)9798350359589

This paper proposes a radio frequency signal identification method based on deep neural network. First, this article abstracts the radio frequency signal into a plane diagram and converts the radio frequency signal identification problem into object detection in image recognition. Then, it is combined with the latest international artificial intelligence technology to further enhance the intelligence of radio frequency signals. At the same time, the ability to identify complex electromagnetic interference is enhanced. Then this paper proposes a method to identify interference signals through radio spectrum images based on deep learning technology, and designs experiments to verify the identification accuracy of this method. The effectiveness of this method was verified through field sampling of a total of 5,432 samples of 15 categories. The proposed method can correctly identify the wave pattern and frequency characteristics of radio frequency signals, with an accuracy rate of 87.14%. The simulation results show that this method is universal and has good identification accuracy for interference at other frequency points. © 2024 IEEE.

关键词： convolutional neural network deep network image object detection radio frequency learning Radio wave recognition

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