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Feed-forward Neural Network based Algorithm for Intelligent Positioning of Direction Finding Crossings 16

Feed-forward Neural Network based Algorithm for Intelligent ...

引用

16th International conference on Signal processing systems, ICSPS 2024

作者： Li, Pangzhe Hu, Dexiu Zhao, Chuang Information Engineering University Signal Processing Laboratory China

ISBN: (纸本)9781510689251

This paper proposes a feed-forward neural network(FNN) based algorithm for intelligent positioning of angle of arrival(AOA) to address the problems of complex computation, slow positioning speed and low positioning accuracy of traditional cross-location direction finding methods. The algorithm obtains the position of a known target from the available data, calculates its angle of arrival at the observatory, combines them into data pairs, and inputs them into a constructed neural network to obtain the corresponding model. The network can then locate unknown targets. It is verified that the algorithm has reliable localization accuracy and higher robustness than conventional algorithms. The proposed method also shows that the training of the neural network on the basis of a large amount of data can greatly reduce the operation time and achieve real-time target localization. © 2025 SPIE.

关键词： Neural network models

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Analysis and design of pervasive computing intelligent surveillance system integrating optical sensors and behavioral analysis for industrial internet 2

Analysis and design of pervasive computing intelligent surve...

引用

2nd International conference on Big Data, Computational Intelligence, and Applications, BDCIA 2024

作者： Yao, Di Luo, Chenyao Cheng, Weiwei Song, Huaju Beijing100083 China Portland Institute Nanjing University of Posts and Telecommunications Nanjing210003 China School of Electronic and Optical Engineering Nanjing University of Science and Technology Nanjing210094 China School of Environmental Science NanJing XiaoZhuang University Nanjing210017 China

ISBN: (纸本)9781510689053

Nowadays, the surveillance system performing as an indispensable part for modern industrial Internet has attracted much attention. With the continuous progress of microprocessor technology, sensor technology, particularly optical sensors, and network technology, it has entered the era of pervasive computing, which leads to the breakthrough of the surveillance system and the emergence of intelligent environment safety monitoring systems. However, the intelligence of surveillance systems is still a significant challenge. In this paper, we propose a surveillance system for detecting and recognizing people based on their behaviors from images or video sequences using computer vision techniques and optical sensor data, which is implemented by designing the system architecture through a hierarchical structure, applying key techniques such as background subtraction, modeling, and optical sensing analysis, and experimentally processing and testing a variety of behavioral samples. The alarm information generated by the proposed surveillance system aided by pervasive computing system can be delivered to remote terminals. Experimental results reveal that the environmental monitoring and alarm information can be processed in real time with devices, such as cell phones, telephones, and PCs. Therefore, the proposed approach can improve the performance of the surveillance systems. © 2025 SPIE.

关键词： Alarm systems

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Research on Improved TDOA Algorithm for Shallow Water Underwater Positioning 16

Research on Improved TDOA Algorithm for Shallow Water Underw...

引用

16th International conference on Signal processing systems, ICSPS 2024

作者： Shen, Biyue Rong, Shaowei Ji, Lingxian Wu, Kaiyuan Li, Jiaju Deng, Xiangyu Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Faculty of Artificial Intelligence Industry Kunming University of Science and Technology Kunming650500 China

ISBN: (纸本)9781510689251

Accurate positioning in shallow water regions is crucial for various underwater applications. TDOA algorithms estimate the signal source location by measuring the time differences of signal arrival at multiple receivers. However, these methods often suffer from Non-Line-of-Sight (NLOS) errors and noise, leading to reduced positioning accuracy in shallow water environments. This research proposes an improved TDOA estimation algorithm that utilizes cross-correlation techniques to mitigate NLOS errors and combines the strengths of the Chan and Taylor algorithms to enhance positioning precision. The proposed algorithm addresses challenges such as time ambiguity and alpha-stable noise, offering advantages in TDOA modeling for underwater positioning. Implementation details are provided, including the design of matching basis functions, time delay matching procedures, algorithm flow, and computational steps. Simulation tests validate the effectiveness of the algorithm, demonstrating significant improvements in positioning accuracy. The computational complexity is also analyzed to assess the algorithm's practicality. Finally, the research findings are summarized, and directions for future work are discussed. © 2025 SPIE.

关键词： Time difference of arrival

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A Separation of Speech Sources Based on Dual MVDR Beamformer

A Separation of Speech Sources Based on Dual MVDR Beamformer

引用

2025 systems of Signals Generating and processing in the Field of on Board Communications, SOSG 2025

作者： The, Quan Trong Duy, Dinh Truong Posts and Telecommunications Institute of Technology Faculty of Information Security Hanoi Viet Nam

ISBN: (纸本)9798331532635

Microphone arrays (MA) techniques are widely applied into numerous acoustic devices for speech enhancement. Because of the spatial information, MA beamforming has the capacity of processing multiple desired or undesired sources in a complex and annoying environment, approximately localizing sound. Nowadays, various applications that are arising in the field of teleconference systems, hands-free mobile phones, automatic speech recognition, smart-home, surveillance equipment present new challenges for speech enhancement algorithms. Minimum Variance Distortionless Response (MVDR) beamformer is the most effective algorithm for saving the original clean speech data, eliminating the unwanted background noise without speech distortion. Because of the different microphone sensitivities, the error of sampling rate, the inaccurate estimation of preferred incident angle of useful signal, the imprecise MA distribution or designed MA geometry, the MVDR beamformer's performance significantly degraded. In this article, the author considered the problem of separating sound speech in the realistic consecutive conversation between two speakers. The authors proposed an additive method, which enhances the MVDR beamformer's evaluation in extracting each individual. The promising results obtained have confirmed the effectiveness of the author's proposed method in real-life situations. The author's illustrated approach can be integrated into a multi-channel signal processing system for solving several complex problems. © 2025 IEEE.

关键词： Speech enhancement

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Hand Gesture Recognition Method based on mmWave Radar with MobileViT and Knowledge Distillation 16

Hand Gesture Recognition Method based on mmWave Radar with M...

引用

16th International conference on Signal processing systems, ICSPS 2024

作者： Zhang, Xiangqun Ge, Zhizhou Lu, Kai Du, Genyuan Shen, Jiawen Gao, Xiangqian School of Information Engineering Xuchang University Xuchang461000 China Henan International Joint Laboratory of Polarization Sensing and Intelligent Signal Processing Xuchang461000 China Henan Shengshi Hengxin Technology Co. Ltd Xuchang461111 China

ISBN: (纸本)9781510689251

Human-hand gesture recognition using millimetre wave radar is attractive in human-computer interfaces, industrial Internet of Things, and smart home. However, the existing CNN or RNN model is so complex and large that it is hard to apply to mobile vision tasks and embedded devices. This paper proposes dual lightweight convolutional neural networks, MobileViT and knowledge distillation, to solve this problem. Firstly, we acquire the original radar echoes of frequency-modulated continuous wave (FWCW) signal and reshape the three-dimensional matrix by Chirps * Samples * Frames. Then, we perform the signal processing method to eliminate the noise and static background. Secondly, we employ the Fast Fourier Transform to extract the hand gestures feature map of distance and Doppler information. Finally, the feature map is input into the modified MobileViT to recognize dynamic hand gestures, and knowledge distillation models is used to simplify the model structure. The experimental results show that the parameter space complexity of the constructed model is reduced to 0.018 M, and the computational complexity is 0.082 GFLOPs after knowledge distillation *** method is verified in 12 complex gesture. It has the potential to be applied in mobile tasks and embedded devices. © 2025 SPIE.

关键词： Fast Fourier transforms

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Edge computing and big data analysis integration framework in smart grid edge gateway

Edge computing and big data analysis integration framework i...

引用

2024 International conference on Physics, Photonics, and optical Engineering, ICPPOE 2024

作者： Liu, Yuan Zhang, Wei Liu, Liguo Li, Xuehua Yang, Chenjie Wang, Yukui State Grid Information & Telecommunication Co. Ltd. Beijing branch Beijing China

ISBN: (数字)9781510689121

ISBN: (纸本)9781510689114

This study aims to enhance the data processing efficiency, real-time performance, and system reliability of smart grids by integrating edge computing and big data analysis in smart grid edge gateways. This study shows how advanced technologies like edge devices, edge computing nodes, big data analytics modules, and control systems can be utilized in a real grid setting to enhance operational efficiency and grid prediction ability through a comprehensive architecture design and implementation. In the research, we concentrated on data real-time processing, transmission mechanism, and system architecture design, and we validated the framework's efficiency with real cases. Studies indicate that the integration of edge computing and big data analysis in an organic manner can enhance the data processing abilities of the power grid, decrease delays, and offer robust backing for optimal power grid management. This framework is capable of satisfying the requirements of current smart grids, as well as possessing strong scalability and adaptability, providing a robust groundwork for the advancement of future smart grids. © 2025 SPIE.

关键词： Mobile edge computing

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An Adaptive Steering Vector - Based Dual Microphone System’s Evaluation 3rd

An Adaptive Steering Vector - Based Dual Microphone System’...

引用

3rd International conference on Advances in information and Communication Technology, ICTA 2024

作者： The, Quan Trong Anh, Pham Tuan Hanoi Viet Nam Vietnam - Korea University of Information and Communication The University of Da Nang Danang Viet Nam

ISBN: (纸本)9783031809422

Nowadays, due to the development of smart home and smart voice-controlled devices, the concern of noise reduction and speech enhancement are getting much attention. Basically, most signal processing algorithms include separating the noisy speech in each frame, estimating, tracking and updating noise statistics for mitigating noise. Recently, scholars and researchers are focusing on studying the space domain in the scenario of multichannel case with an appropriate microphone array (MA). MA owns the high directivity beampattern toward the speech source at a certain direction while eliminating all interference, which come from other directions. Minimum Variance Distortionless Response (MVDR) is commonly installed in most acoustics devices, such as: surveillance equipment, conferencing systems or mobile phones. Because of the different sensitivities of MA, the error of direction of arrival of interest signal or imprecise MA distribution, the overall MVDR beamformer’s evaluation often corrupted. In this paper, the authors introduce a new method for adaptive updating of the steering vector to enhance MVDR beamformer’s performance. The illustrated experiment has confirmed the advantage of suggested techniques in improving the speech quality in the term of signal-to-noise ratio (SNR)from 8.8 to 10.3 (dB), reducing speech distortion to 6.9 (dB). The proposed methods are suitable for applying into multi-channel systems for signal processing in realistic recording environments. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Noise abatement

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Development of an Entry-Exit Decision Algorithm for Bus Passenger Counting Using Cameras 16

Development of an Entry-Exit Decision Algorithm for Bus Pass...

引用

2024 16th International conference on Graphics and Image processing, ICGIP 2024

作者： Nishiura, Tsubasa Yokoyama, Soichiro Yamashita, Tomohisa Kawamura, Hidenori Sato, Yoshimi Hasegawa, Rei Hirasawa, Miyuki Faculty of Information Science and Technology Hokkaido University Kita 14 Nishi 9 Kita-ku Hokkaido Sapporo060-0814 Japan C’s Lab Co. Ltd. 3 Kita 1-jo Nishi 7-chome Chuo-ku Hokkaido Sapporo060-0001 Japan

ISBN: (数字)9781510688780

ISBN: (纸本)9781510688773

In recent years, entry-exit management technologies have gained attention due to the rise of smart cities and the proliferation of IoT devices. These technologies are used not only in indoor environments like offices and retail stores but also in outdoor settings such as public transportation. Particularly in public transport, there is growing demand for Origin-Destination (OD) data collection to better understand passenger movement. In this study, we developed a system to estimate the number of passengers boarding and alighting from buses by installing cameras at the bus doors and capturing video footage of passengers. The system utilizes person detection and tracking algorithms to estimate passenger trajectories and applies a deep neural network (DNN) model to classify whether a detected individual is boarding or alighting. We introduced a DNN model for binary classification to determine whether individuals are inside or outside the bus, using bounding box and time information. By performing a grid search, we identified optimal model parameters. The system was tested using both YOLOR and the latest YOLOv10 object detectors, and the MPNTrack person tracking algorithm. The combination of YOLOv10 and the DNN model achieved an error rate of 11.7% for the entrance camera, while YOLOR and the DNN model achieved an error rate of 0.803% for the exit camera, significantly improving the accuracy over previous methods. This study demonstrates that integrating object detection, tracking, and DNN-based classification improves the accuracy of passenger counting systems, which is crucial for the effective management of public transportation systems. © 2025 SPIE.

关键词： Deep neural networks

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Forest Fire Prevention and Detection System 5

Forest Fire Prevention and Detection System

引用

5th IEEE International conference on Power, Electronics and Computer Applications, ICPECA 2025

作者： Jayakody, Lasitha Edirisinghe, Chamathka Senasinghe, Tharush Dissanayake, Shaminda Gamage, Narmada Pandithage, Dinithi Wijayaraja, Jaliya L. Sri Lanka Institute of Information Dept. of Computer Systems Engineering Malabe Sri Lanka

ISBN: (纸本)9798331533694

Forest fires pose significant threats to both the environment and human life, necessitating the development of advanced detection and prevention systems. In this study, we propose an integrated IoT (Internet of Things)-based system for early detection and management of forest fires. The system incorporates a range of sensors including heat, gas, and thermal imaging sensors, along with IoT technology for real-Time monitoring and communication. Utilizing image processing techniques and (ML) Machine Learning algorithms, the system can accurately detect fires, predict their spreading patterns, and analyze environmental conditions. Key features include the deployment of disposable heat sensors for temperature monitoring, IoT sensors for gas detection and weather monitoring, and a centralized processing node for data analysis. Alerts are sent to nearby authorities and residents, while automated firefighting devices are activated to suppress fires until backup arrives. Experimental results demonstrate the effectiveness of the proposed system in early detection and prevention of forest fires. © 2025 IEEE.

关键词： Temperature sensors

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Quantum Technology Fueling the Next Generation optical Communication: Challenges and Pathways 5th

Quantum Technology Fueling the Next Generation Optical Commu...

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5th EAI International conference on Cognitive Computing and Cyber Physical systems, IC4S 2024

作者： Venkateswara Rao, Ch. Pareek, Prakash Mishra, Jitendra K. Department of Electronics and Communication Engineering Indian Institute of Information Technology Ranchi Jharkhand834010 India Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram534202 India

ISBN: (纸本)9783031770777

information transmission through light has attained significant advancements in the fields of both optical fiber communication (OFC) and optical wireless communication (OWC) systems. These advancements have been examined by numerous researchers by employing pioneering modulation schemes, adaptive optics, advanced signal processing algorithms, advancement in materials, and employing sophisticated network architectures for wide variety of applications such as: military;defense;healthcare;satellite;internet of things;and telecommunications. However, the primary factors which affecting the OFC systems are signal attenuation, dispersion, reliability, robustness, and security even though there exists a predominant development. In addition, atmospheric attenuation (due to absorption and scattering), turbulences, climate conditions (fog, rain, snow, dense fog etc,.), alignment and tracking, interference, range constraints, and security are the major challenges in OWC systems in spite of having advanced approaches from past few decades. Hence, these challenges are need to be addressed in order to achieve reliable and high-speed data transmission. This could be possible with the integration of OFC and OWC with emerging quantum communication technologies (quantum key distribution, quantum entanglement, quantum repeaters, quantum sensing, and quantum secured OWC links). Therefore, this work presents the recent advancements in the fields of OFC and OWC systems with the state-of-art-of techniques and approaches. The primary research challenges related to security, speed, range, capacity and adaptability of both OWC and OFC are outlined. In addition, the possible integration of these systems with quantum communication technologies and the recent progression have been outlined. Finally, the possibility of future research direction towards the quantum OFC, quantum OWC have been discussed for ensuring and revealing the full potential of quantum enhanced optical communication systems.

关键词： Adaptive optics

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