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检索条件"任意字段=International Conference on Advances in Intelligent Control and Computer Engineering"

共 47502 条记录，以下是101-110 订阅

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IoT-based Door Automation and Smart Health Monitoring System 3

IoT-based Door Automation and Smart Health Monitoring System

引用

3rd international conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Chaurasiya, Ruchi Yadav, Shakshi Malik, Swagata Belwal, Meena Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (纸本)9798331527549

This project presents the design of an automated access control system that aims to enhance security through the use of an ultrasonic motion sensor and a live heartbeat check. This system makes use of an ultrasonic sensor which detects any motion within a certain radius directing a signal to the controller based on Arduino. The controller is able to communicate with a script written in Python that queries API for the pulse of the user in question. Using these parameters,the system compares the real-time heartbeat of the pulse taken against the thresholds set *** the parameters exceed the range,the control unit within the Arduino will trigger the servo to unlock the door. Another scenario the parameters are within range,the door will remain closed. Such a system is able to increase the control measures in biological information system as it enables people to open the door while maintaining their hands free. The outcome demonstrates that by combining simple hardware components with data processing techniques, a reliable and secure automated access system can be created with minimal manual intervention, improving security while ensuring ease of use. © 2025 IEEE.

关键词： Access control

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An innovative study on an intelligent logistics handling robots

An innovative study on an intelligent logistics handling rob...

引用

2024 international conference on computer Application and Information Security, ICCAIS 2024

作者： Zhong, Yuling Yao, Rui Guangdong Polytechnic of Industuy and Commerce Guangzhou 510000 China South China Normal University Guangzhou 510000 China

ISBN: (纸本)9781510689312

With the advancement of Industry 4.0 and the logistics industry, traditional manual handling is gradually phasing out, giving rise to the emergence of intelligent logistics handling robots. The robot in this study integrates laser radar, cameras, and a robotic arm, utilizing STM32 as the main control unit and leveraging IoT technology. It demonstrates precise navigation and obstacle avoidance, efficient object recognition and handling, and supports remote control and monitoring. Additionally, it exhibits excellent adaptability across various environments. From an economic perspective, this robot effectively reduces labor costs while enhancing operational efficiency. © The Authors.

关键词： intelligent logistics handling object recognition and grasping remote control

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Integrating Big Data Analytics in Soil Quality Assessment: Techniques, Challenges, and Applications 3

Integrating Big Data Analytics in Soil Quality Assessment: T...

引用

3rd international conference on intelligent and Innovative Technologies in Computing, Electrical and Electronics, IITCEE 2025

作者： Mohammed, Shehu Singh, Arun Hanif, Md Abu Lovely Professional University Department of Computer Applications Phagwara India Lovely Professional University Department of Computer Science and Engineering Phagwara India Department of Computer Science 365 5th Ave New YorkNY110016 United States

ISBN: (纸本)9798331515911

This review paper investigates the application of Big Data analytics, focusing on soil quality assessment, with an emphasis on the innovative benefits offered by modern data-driven techniques for improved soil management. With world food demands rising, the importance for real-time and exact soil quality monitoring has increased. Although still useful, traditional approaches to modeling are limited in their ability to capture the spatial and temporal variability of soil properties. Big Data analytics sits as the answer to the above by facilitating extensive and large volume data processing resulting in better, on-demand and scalable soil quality assessment. In the paper, we describe machine learning algorithms, remote sensing and geospatial analysis as key techniques to mine soil data at scales and resolutions unprecedented so far. We also critically evaluate the challenge of data integration (heterogeneity, scalability and multi-disciplinarity). These analytics are scalable for assessment and decision-making in precision agriculture, sustainable land management and environmental conservation. Thus, this paper synthesizes current research and practical implications in support of the need for Big Data analytics within soils and soil sciences to cover also future challenges. Future research directions are also highlighted, including the importance of improved data acquisition and algorithmic advances as well greater synergy between Big Data and conventional soil science practices.. © 2025 IEEE.

关键词： Data quality

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Integration of Process Optimization and Automation: A Way to AI Powered Digital Transformation 1

Integration of Process Optimization and Automation: A Way to...

引用

1st international conference on advances in computer Science, Electrical, Electronics, and Communication Technologies, CE2CT 2025

作者： Kotte, Kulasekhara Reddy Thammareddi, Latha Kodi, Divya Anumolu, Venkateswara Rao Arun Kumar, K. Joshi, Shubham INC SLRI Solutions India India Cyber Security Senior Data Analyst Truist Financial India Technical Architect ERP Solutions- Information Technology India Big Data Architect India Bipin Tripathi Kumaon Institute of Technology Department of Computer Science & Engineering Almora India

ISBN: (纸本)9798331518578

One of the most important factors facilitating AI-powered digital transformation is the combination of process automation and optimisation. Organisations may improve operational efficacy, save costs, and streamline procedures by utilising cutting-edge technology like robotic process automation (RPA), machine learning (ML), and artificial intelligence (AI). While automation seeks to reduce human participation in repetitive and rule-based operations, process optimisation concentrates on improving current business processes to attain improved productivity. The development of intelligent, adaptable, and self-improving systems is made possible by the combination of these two methodologies. Predictive findings, real-time decision-making, and customised customer experiences are further made possible by AI-driven analytics. This connection promotes innovation, scalability, and agility across sectors, giving businesses a competitive edge in the quickly changing digital market. The article examines the main principles, advantages, and difficulties of this shift and provides a road map for businesses looking to automate and optimise processes using AI in order to attain operational excellence and sustainable growth. © 2025 IEEE.

关键词： Decision making

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Development of intelligent Operation and Maintenance and Communication Devices for Distribution Network 13th

Development of Intelligent Operation and Maintenance and Com...

引用

13th international conference on Clean and Green Energy

作者： Zhong, Zhaobin Chen, Xiaojun Ye, Qing Zhang, Qiran Chen, Tao Chen, Junhong China Southern Power Grid Technol Co Ltd Guangzhou Peoples R China Guangdong Prov Key Lab New Technol Smart Grid Guangzhou Peoples R China

ISBN: (纸本)9789819618149;9789819618125;9789819618118

Distribution network automation equipment has been widely installed and used in the power grid, which plays a very important role in improving the reliability and quality of power supply. However, due to the wide range of distribution network automation equipment points, poor operating environment, and a large workload of inspection and maintenance of operating units, it is urgent to take the initiative to find defects through technical means, so as to warn and eliminate equipment defects and hidden dangers in advance, and achieve rapid fault location and isolation. In order to meet the requirements of transforming electric power network into digital, networked and intelligent new power system, an intelligent operation, maintenance and communication device of distribution network is proposed. The device supports wireless 5G, wired Ethernet, Bluetooth and other communication modes, and has a variety of communication interfaces such as RJ45, RS485 and RS232. It can adapt to various external devices according to application scenarios. The software supports intelligent operation and maintenance functions such as distribution network device status data collection, device defect management and control, and device local Bluetooth operation and maintenance, and supports IPSec tunnel encryption mode, which meets the intelligent operation and maintenance and encrypted communication requirements of distribution network automation devices, and effectively improves the digitalization and intelligent features of distribution network automation devices. The device has been tested by the third party testing organization and has high operating stability.

关键词： Distribution network Communication devices intelligent operation and maintenance

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advances in AI for Women’s Healthcare: A Review of Deep Learning and NLP Approaches 3

Advances in AI for Women’s Healthcare: A Review of Deep Lea...

引用

3rd international conference on intelligent Data Communication Technologies and Internet of Things, IDCIoT 2025

作者： Choudhary, Jyoti Thakur, Madhuri School of Computer Science and Engineering Lovely Professional University Punjab India

ISBN: (纸本)9798331527549

Women’s health faces critical challenges, particularly in maternal and reproductive healthcare, where complications significantly contribute to global mortality rates. Despite advancements in medical science, inequities in healthcare access and diagnosis persist, especially in underserved regions. Innovative approaches leveraging artificial intelligence (AI) technologies, such as deep learning (DL) and natural language processing (NLP), are transforming healthcare by enabling early diagnosis, personalized treatment, and scalable preventive care. This paper evaluates the transformative role of these AI-driven methods in addressing critical women’s health issues, including cancer detection, maternal health, and reproductive disorders, with a focus on advancements from 2018 to 2023. These years represent a period of rapid AI evolution and its integration into healthcare systems. The present study captures important challenges like restricted diversity of datasets, issues concerning transparency in models, and obstacles in actual deployment. It collates findings to give a global perspective of AI development in women's health. It is also prepared with practical future action steps for its research to lead AI-influenced innovations shaping the future of women's healthcare. © 2025 IEEE.

关键词： Deep learning

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Energy Efficient and SecurityAware Task off Loading for Multi-Tier Edge Cloud Computing Systems 1

Energy Efficient and SecurityAware Task off Loading for Mult...

引用

1st international conference on intelligent Systems and Computational Networks, ICISCN 2025

作者： Divya, S. Saranya, S. Mahendra Engineering College Department of Computer Science and Engineering Namakkal India

ISBN: (纸本)9798331529246

The massive progression of the multi-tier edge cloud computing systems integration has created the possibility of data orchestration and resource control in edge and cloud layers. However, there are many shortcomings, including inappropriate methods of scheduling tasks and security breaches that prevent scalability. To solve these problems, we designed an energy-efficient and security-aware task offloading framework for multi-tier edge cloud computing. Firstly, we estimate the energy ratio of tasks using a Fuzzy Logic Energy Management (FL-EM) algorithm and distribute resources according to different layers. Subsequently, the task-offloading parallel squirrel (TO-PS) method is used to effectively extend the task with better energy consumption and computational efficiency. Finally, it is decided to protect the work data using the Provable Energy-Aware Cryptographic Security (PE-ACS) algorithm. The proposed algorithm achieves a 96.7% success rate in protecting high-level data from cybercrime. Additionally, it enhances security and task performance while reducing energy consumption in multi-tier edge cloud computing systems. © 2025 IEEE.

关键词： Cloud security

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Simulation of rotating three bucket loading method 4

Simulation of rotating three bucket loading method

引用

4th international conference on computer Vision, Application, and Algorithm, CVAA 2024

作者： Xiao, Yajing Xi, Qiming Wu, Hui Liu, Jie China Coal Technology & Engineering Group Intelligent Storage & Loading Technology Co. Ltd. Beijing100013 China Huaneng Coal Technology Research Co. Ltd. Beijing100070 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

A rapid quantitative loading process using a rotating three bucket is proposed and software simulation of the loading process is conducted. Through software simulation, the feeding and unloading of three buckets and buffer buckets during the loading process, as well as the feeding situation of the carriage are studied. Simulations were conducted on the loading process with different vehicle models and loading parameters, and there were no incidents of material scattering or insufficient loading during the entire train loading process. This verifies that the rotating three bucket loading process can adapt to different loading conditions, theoretically verifying the feasibility of the three bucket time-sharing feeding and continuous loading process. © 2025 SPIE.

关键词： control systems Miniaturization Systems modeling

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Adaptive Video Bitrate Allocation for Remotely Operated Vehicles (ROV) 8th

Adaptive Video Bitrate Allocation for Remotely Operated Vehi...

引用

8th international conference on intelligent Transport Systems, INTSYS 2024

作者： Afi, Eman Sarah Triqui, Ons Sayahi, Sofiane Besbes, Hichem Tlili, Fethi Mediterranean Institute of Technology South Mediterranean University Tunis Tunisia Higher School of Communication of Tunis University of Carthage Ariana Tunisia Innovation Department ACTIA Engineering Services Ariana Tunisia COSIM Lab Higher School of Communication of Tunis University of Carthage Ariana Tunisia GRESCOM Lab Higher School of Communication of Tunis University of Carthage Ariana Tunisia

ISBN: (纸本)9783031863691

Establishing a stable and efficient connection between operators and remotely operated vehicles (ROVs) is essential for successful missions in challenging environments. Real-time video transmission is particularly critical, providing operators with visual feedback to navigate and control the vehicle effectively. This study aims to improve video transmission quality in a multi-camera ROV equipped with six cameras and various sensors. Our focus is to enhance the Quality-Aware Dynamic Rate Allocation (QADRA) system, which optimizes video quality by dynamically adjusting codec parameters like resolution and quantization parameters (QPs) based on expected peak signal-to-noise ratio (XPSNR) predictions. This enhancement addresses the unique challenges of achieving balanced video quality across multiple video streams. The method involves developing a system that dynamically adapts codec parameters for each camera based on predefined bitrates, influenced by an assigned weight to each camera to control bitrate distribution and resulting video quality. By prioritizing certain video streams, this weighted system aims to optimize visual representation and thus improve the operator’s situational awareness. Results from theoretical exploration and analysis indicate that this approach can enhance the internal distribution of video quality across multiple camera feeds, contributing to more effective decision-making during teleoperated vehicle operations. In conclusion, this research advances the multi-camera video transmission capabilities for teleoperated vehicles, addressing limitations in video quality management and improving operational effectiveness in remote vehicle control. © ICST Institute for computer Sciences, Social Informatics and Telecommunications engineering 2025.

关键词： Remotely operated vehicles

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A privacy protection strategy based on homomorphic encryption and neural networks 24

A privacy protection strategy based on homomorphic encryptio...

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8th international conference on Electronic Information Technology and computer engineering, EITCE 2024

作者： Liu, Lingli Du, Xiongxiong Ma, Mingcheng Wang, Dong Henan International Joint Laboratory of Intelligent Network Theory and Key Technology Henan University Henan Kaifeng China

ISBN: (纸本)9798400710094

In recent years, incidents of data abuse and privacy leakage remind people that improper use of big data technology can bring disastrous consequences. To realize the true value of data, data sharing is needed. This paper adopts a training method for a privacy-protecting neural network model based on homomorphic encryption in a cloud computing environment. It designs a piecewise linear activation function considering the role of the activation function for homomorphic computing. A ciphertext update strategy is proposed to control weight ciphertext noise growth. Combined with cloud computing, complex neural network computing tasks are entrusted to the cloud. Applied to data privacy protection, it is observed that AlexNet’s PPNN takes 293.5 seconds for inference on CIFAR-10 or MNIST. The lightweight architecture SqueezeNet generated by EVA amplifies AlexNet’s layers and adds rescaling. Although homomorphic encryption in SqueezeNet is slower, it reduces the delay to 72.7 seconds and ensures data security. © 2024 Copyright held by the owner/author(s).

关键词： Differential privacy

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