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检索条件"任意字段=3rd IEEE Intelligent Data Acquisition and Advanced Computing Systems"

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Integration and Implementation of intelligent Circuit System in Internet of Things Equipment

Integration and Implementation of Intelligent Circuit System...

引用

data Analytics, computing and Artificial Intelligence (ICDACAI), International Conference on

作者： Yike Sang Xintong Han Songling Zhao Mingsheng Chang Weifang Engineering Vocational College Qingzhou China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

The integration and implementation of intelligent circuit system in Internet of Things (IoT) devices is one of the key technologies in the current digital era. With the continuous improvement of the intelligence of IoT equipment, intelligent circuit system, as its core component, undertakes the heavy responsibility of data acquisition, processing and transmission, and gives the equipment the ability of independent learning and decision-making. However, there are still many challenges to effectively integrate the intelligent circuit system into IoT devices and achieve efficient and stable operation. In this paper, the integration method and implementation technology of intelligent circuit system in IoT equipment are deeply discussed. In the aspect of hardware integration, the research emphasizes the importance of standardization and universal interface design, and how to reduce energy consumption through intelligent sleep technology and energy management strategy. Software integration involves selecting the appropriate operating system, communication protocol and data processing strategy to ensure that the intelligent circuit system can seamlessly interface with IoT devices and realize efficient data processing. In addition, the paper also discusses the selection and application of embedded system and microcontroller, as well as the selection and optimization of communication technology to meet the needs of different IoT devices. Through case analysis, this paper shows the integration and realization process of intelligent circuit system in smart home system, including hardware selection, software development, application of communication technology and application of data analysis and processing technology. The analysis of performance, stability and security shows that the smart home system performs well in real-time control, data processing and personalized experience. At the same time, it also points out the potential risks of the system in extreme cases and puts

关键词： Performance evaluation Embedded systems Standardization Smart homes Hardware Software Stability analysis Real-time systems Internet of Things Energy management

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data Security Protection System in Human-Machine-Object Fusion intelligent Demand Engineering System 3

Data Security Protection System in Human-Machine-Object Fusi...

引用

3rd International Conference on Integrated Circuits and Communication systems, ICICACS 2025

作者： Qi, Yongjun Li, Chenggao Tang, Hailin Shen, Junxuan Guangdong Baiyun University Faculty of Megadata and Computing Guangdong Guangzhou China School of Information and Communication Technology Mongolian University of Science and Technology Ulaanbaatar Mongolia

ISBN: (纸本)9798331508456

In the engineering system of human-machine physical intelligence requirements, the multi-source and high complexity of data pose significant security risks. Therefore, this article designs a comprehensive data security protection system. Firstly, this article chooses a dynamic encryption strategy based on role-based access control. Then, this article combines differential privacy algorithm to construct a privacy protection model to ensure the privacy of data during sharing and processing. Subsequently, this article proposes a trusted data transmission protocol. Finally, this article introduces federated learning techniques to further improve the security and robustness of data in distributed scenarios. The experimental results show that the system performs well in terms of data security, privacy protection, and processing efficiency. Especially under high-intensity attacks, the system successfully detected and prevented approximately 98% of tampering. In the above data conclusions, the research method has significant advantages in encryption performance, achieving a better balance between privacy protection and data accuracy, demonstrating strong application prospects. © 2025 ieee.

关键词： Requirements engineering

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data Augmentation for Entity Resolution: A Comparative Evaluation

Data Augmentation for Entity Resolution: A Comparative Evalu...

引用

computing and Machine Intelligence (ICMI), International Conference on

作者： Tobias Rettenmeier Alexander Jesser Institute for Intelligent Cyber-Physical Systems Heilbronn University of Applied Sciences Künzelsau Germany

ISBN: (数字)9798350372977

ISBN: (纸本)9798350372984

data augmentation is an important technique to enhance the performance of models in different fields, such as computer vision and natural language processing. In entity resolution, few papers have applied general or task-specific data augmentation techniques, and systematic knowledge is sparse. This study evaluates eight rule-based, model-based, and sample interpolation by comparing them systematically across 10 datasets and two transformer-based models or entity resolution matching systems: BERT and Ditto, leveraging DistiIBERT. The results show the potential of data augmentation to increase per-formance, although the influence of the technique used depends heavily on the model and dataset. Here, MixDA and random word insertion performed best, so they are most suitable for recommendation to practitioners dealing with entity resolution tasks.

关键词： Systematics Computational modeling data augmentation Transformers data models Reproducibility of results Natural language processing

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Leveraging IoT and Machine Learning for intelligent Water Quality Monitoring systems

Leveraging IoT and Machine Learning for Intelligent Water Qu...

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2025 International Conference on intelligent Control, computing and Communications, IC3 2025

作者： Baranwal, Gaurav Singh, Kaushtubh Gupta, Ayush Tiwari, Harsh N. Gupta, Tukur Ajay Kumar Garg Enginnering College Department of Electronics and communication Engineering Ghaziabad India

ISBN: (纸本)9798331527495

Water quality monitoring is a crucial aspect of public health, particularly in mitigating the risks associated with waterborne diseases and ensuring safe drinking water. Traditional monitoring methods are often labor-intensive, costly, and lack real-time capabilities, making them unsuitable for widespread and rural deployment. This paper examines the integration of advanced technologies, specifically the Internet of Things (IoT) and Machine Learning (ML), to design a sophisticated, low-cost water quality monitoring system. Leveraging an array of sensors, including pH, turbidity, temperature, total dissolved solids (TDS), and dissolved oxygen (DO), combined with the advanced embedded processor, the system ensures seamless data acquisition and processing. IoT enables continuous remote monitoring, while ML algorithms provide predictive analytics and intelligent anomaly detection to identify potential contaminants and trends. These value-driven solutions underscore the transformative potential of advanced technologies in revolutionizing water quality assessment. This review article carefully reviews the available literature on water quality assessment in order to lay out an assortment of conclusions on the concerns, problems, challenges, and research gaps that have emerged during the last few years. Research gaps are identified by thoroughly examining the previously suggested methodologies. The study presented in this article primarily identified the problems with the accuracy of the models, the generation of data collection mechanisms, and the types of data that were used in the suggested frameworks. Subsequently, research avenues towards smart water quality monitoring are offered by examining key concepts crucial to the expansion of this field of research. © 2025 ieee.

关键词： Damage detection

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Practical Network Guiding of Higher Vocational Logistics Management Major with Video Processing and GIS systems 3

Practical Network Guiding of Higher Vocational Logistics Man...

引用

3rd International Conference on Inventive Research in computing Applications, ICIRCA 2021

作者： Zhang, Zhuoyuan Collage of Business Administration Heilongjiang Polytechnic Heilongjiang Haerbin150080 China

ISBN: (纸本)9780738146270

Practical network guiding of the higher vocational logistics management major with video processing and the GIS systems is studied in this paper. In the actual modern logistics management, the information platform module mainly realizes the collection and storage, processing and transmission of the logistics information, etc. The challenges of the traditional ways are the efficiency of processing the data. To deal with this this paper firstly use the video processing framework to collect the multi-dimensional data as the basis for validating the model. Then, the GIS system is combined for the comprehensive modelling. The application scenario is selected as the guiding. The simulation has shown the satisfactory performance. © 2021 ieee.

关键词： intelligent systems

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uPIM: Performance-aware Online Learning Capable Processing-in-Memory 3

uPIM: Performance-aware Online Learning Capable Processing-i...

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ieee 3rd International Conference on Artificial Intelligence Circuits and systems (AICAS)

作者： Bavikadi, Sathwika Sutradhar, Purab Ranjan Ganguly, Amlan Dinakarrao, Sai Manoj Pudukotai George Mason Univ Dept Elect & Comp Engn Fairfax VA 22030 USA Rochester Inst Technol Dept Comp Engn Rochester NY 14623 USA

ISBN: (纸本)9781665419130

Machine learning and AI-based automated systems are gaining increasing attention for real-time intelligent applications by virtue of a superior co-ordination between the software and the hardware within these systems. Although the majority of the automated systems are implementing Convolutional neural networks (CNNs), and Deep Neural Networks (DNNs) on the hardware with impressive accuracy, a significant amount of cost is associated with data movement in these platforms. Recent advancements in processing-in-memory (PIM), a non-von Neumann computing paradigm, have proven to be very effective in minimizing data communication overheads by performing computations within the memory chip. However, these devices are primarily designed as inference engines and therefore have not been adequately investigated for real-time learning capabilities for applications in changing environments. In this work, we introduce uPIM, a PIM architecture that supports a Generative Adversarial Network (GAN)-based performance-aware online learning model for updating the weights with minimal overheads. Our hardware-software co-design approach exhibits superior performance and efficiency in real-time applications like Autonomous Navigation systems (ANS) by leveraging massive data-level parallelism and ultra-low data movement latency. The evaluations are performed on multiple state-of-the-art deep learning networks like LeNet, AlexNet, ResNet18, 34, 50 on the German Traffic Sign Recognition Benchmark (GTSRB) dataset and the Belgium Traffic Sign dataset (BTSD) with several data-precisions. The proposed performance-aware, quantization-friendly online learning based PIM architecture achieves an average accuracy of 72% for GTSRB and 83.4% for BTSD dataset under varying environment for CNNs implemented for Traffic Sign Recognition (TSR) with 8-bit fixed point data-precision.

关键词： Performance evaluation Neural networks Computer architecture Parallel processing Generative adversarial networks Real-time systems Hardware

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Design and Simulation of an intelligent Traffic Management System Using Vehicular Networks

Design and Simulation of an Intelligent Traffic Management S...

引用

intelligent data Communication Technologies and Internet of Things (IDCIoT), International Conference on

作者： P. Tapan Datta D.Lalith Kumar S. Tanoj Shinu M Rajagopal Department of Computer Science and Engineering Amrita School of Computing Amrita Vishwa Vidyapeetham Bengaluru India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

In this study , the reasearch is focused on the simulation of vehicular communication networks, especially intelligent traffic systems, to enhance dependability, safety, and optimality in communication. The simulation is performed using the OMNeT++ simulator and is integrated with the Veins framework that uses the ieee 802.11p protocol for V2V and V2I communications. Importing real-world traffic scenarios into the framework is obtained via the use of SUMO through TraCIScenarioManager. Other features of the framework include the definition of mobility models, dynamic obstacles, and detailed radio propagation modeling. TraCIDemo11p is used for mobility and communication by both RSUs and vehicles with applications in beaconing and channel switching. The whole framework analyzes smart traffic management solutions, providing as much insight into their performance based upon the communication reliability and overall efficiency in vehicular networks.

关键词： Protocols Vehicle-to-infrastructure Simulation Vehicular ad hoc networks Switches Radio propagation Safety Security Reliability Vehicle dynamics

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A Hidden Markov Model Based intelligent Platform for Characterizing Behaviors 3

A Hidden Markov Model Based Intelligent Platform for Charact...

引用

3rd ieee International Conference on Human-Machine systems, ICHMS 2022

作者： Li, Yang Lei, Geoff Bui, Linh Lei, Chengwei New York University College of Art and Science New York City United States St. Michael's University School Victoria Canada California State University Bakersfield Public Health Program Bakersfield United States California State University Bakersfield Computer Science Department Bakersfield United States

ISBN: (数字)9781665452380

ISBN: (纸本)9781665452380

With the development of advanced data science oriented technology utilized in recent clinical psychology, the diagnosis of behavioral disorders can be deduced using several key behavioral abnormalities. Despite this, diagnosing these disorders can prove to be a challenge and may require large amounts of time and personalized testing for each individual. As a potential aid, we present a novel computer intelligence platform for clinical and counseling psychologists as well as mental health professionals. By using a Hidden Markov Model based algorithm, the platform will build up a personalized behavior pattern mathematical profile for each user. This profile could be used as an auxiliary analyzing tool for psychologists to quickly preset a high dimension personality properties prognosis. With more accurate clinical trial data, this platform could also apply specific treatment approaches geared towards the individual based on the computational analysis. © 2022 ieee.

关键词： Hidden Markov models

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Distributed computing and data Processing Technology under the Power data Middleware Architecture

Distributed Computing and Data Processing Technology under t...

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data Science and Computer Application (ICDSCA), ieee International Conference on

作者： Yuelin Zou Jia Shen Rui Yin Jiangtao Guo Yi Guo State Grid Xinjiang Electric Power Co. Ltd. Information and Communication Company Urumqi China State Grid Xinjiang Electric Power Co. Ltd. Urumqi China State Grid Info-Telecom Great Power Science and Technology Co. Ltd Fuzhou China

With the establishment and development of integrated monitoring platforms and communication information platforms for intelligent substations, the data volume of the power system is showing explosive growth. However, existing data centers have poor processing capabilities for massive amounts of data, making it difficult to meet the multiple service quality requirements of users. How to effectively manage massive and complex data, fully utilize the value of data, improve service quality, reduce operational costs, and achieve rapid response to users is an urgent problem to be solved. Therefore, based on the actual needs of power enterprises, this article proposed a cloud computing power data middleware architecture based on distributed technology, which effectively managed, cleaned, converted, and evaluated power data sources through cloud computing platforms. This article mainly analyzed the shortcomings of traditional power data processing platforms and the feasibility of cloud computing based power data platforms. Finally, through load balancing bias comparison and pressure testing experiments under different task numbers, it was proven that cloud computing systems outperformed traditional power data processing systems in terms of utility value, completion time, and load balancing. Moreover, in the pressure testing experiment, under the condition of 10 concurrent users and 673 system request transactions, 91.3% of the interface response time in the cloud computing system was within 50ms. Therefore, cloud computing systems have certain advantages in processing power data.

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intelligent Management System for Micro-Grids using Internet-of-Things 3

Intelligent Management System for Micro-Grids using Internet...

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3rd Mexican Humanitarian Technology Conference (ieee MHTC)

作者： Gutierrez, Sebastian Medina, Guillermo Ponce, Hiram Espinosa, Ricardo Univ Panamer Fac Ingn Aguascalientes Aguascalientes Mexico Univ Panamer Fac Ingn Ciudad De Mexico Mexico

ISBN: (纸本)9781665419475

The current research work proposes the design of an intelligent platform for managing the generation, distribution, transmission, commercialization and consumption of electricity, allowing the decision-making process aimed at reducing costs and maximizing the use of energy resources. The technological proposal is a system of information made of integrated sensors. This creates an electrical real-time network that share energy in the cloud through LPWAN networks. Later, the data from the sensors are received in an intelligent platform (Max4 IoT) that employs super-computing systems and artificial intelligence for the analysis of individual and aggregated data. The system is able to learn about the electrical network, knowing the consumers' behavior and energy trends, allowing to generate responses based on specific situations by sending SMS alerts and emails about abnormal situations or programmed tasks. In addition, the system allows the generation of reports on the network status in real-time and commands control signals on the switching on-and-off of equipment in response to consumption peaks and/or power supply outages. The platform allows interaction with distributed generation systems and micro-grids, through its mobile or web interface, increasing user interaction with the electrical system and the inclusion of renewable energy sources, thus influencing a better quality of service provided to the end user.

关键词： artificial intelligence energy consumption distributed generation internet-of-thing micro-grids

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