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Design of intelligent Pension System Based on Zigbee Technology

Design of Intelligent Pension System Based on Zigbee Technol...

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data analytics, computing and Artificial Intelligence (ICDACAI), international conference on

作者： Yajuan Cao Kai Zhang Civil Administration Professional University Beijing China Everybody Insurance Group Beijing China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

In the context of the rapid development of information technology and network technology, the field of smart home is gaining widespread attention and is rapidly popularized in the world. intelligent home system through the integration of computer technology, a variety of family life related intelligent equipment interlinked to form an efficient residential facilities and family affairs management system. In our country, the problem of population aging is becoming more and more serious, and the need of elderly people's home care is more and more urgent. Therefore, the development of a smart pension system based on ZigBee technology is not only a necessary measure to respond to the national healthy China strategy, but also an important means to promote the combination of smart families and home care. This system aims to improve the quality of life and happiness of the elderly, which has important theoretical and practical significance. According to the living habits and room layout of ordinary families, this paper puts forward four intelligent solutions. The system integrates a wealth of ZigBee smart devices as well as emergency keys and Kinect devices to ensure the safety of everyday life for seniors. The system treats each home as an independent user and manages smart devices within the home through user accounts. The data communication of the system strictly follows the uniform protocol rules to ensure its stability and reliability. Users can interact with the system through web pages, smart speakers and mobile terminals to realize diversified operations and enhance the smart elderly care experience. After rigorous testing, the system meets the needs of users in terms of function and performance, has high feasibility and good interactivity, can receive and display environmental data in real time, and supports voice control intelligent devices, simplifies the operation process, and significantly improves the home care experience of the elderly.

关键词： Protocols Zigbee Web pages smart homes Stability analysis Pensions Safety Older adults smart devices Testing

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IoT, Heterogeneous data Processing, and AI Automation Synergy for Improved Efficiency and Maintenance: Revolutionizing Hospital Operations

IoT, Heterogeneous Data Processing, and AI Automation Synerg...

引用

2023 IEEE international conference on Signal Processing, Communications and computing, ICSPCC 2023

作者： Muqing, Niu Wenting, Liu Xiaole, Gao Zhiyuan, Zhao Jingjuan, Wang First Affiliated Hospital Henan University of Science and Technology Luoyang China Business School Henan University of Science and Technology Luoyang China

ISBN: (纸本)9798350316728

Modern healthcare is going through a big change because of the way that new tools are proposed. This paper works at how the Internet of Things (IoT), heterogeneous data transfer and processing, and Artificial Intelligence (AI) robotics could completely change how hospitals work. IoT technology has become a significant tool because it makes it possible to watch and collect data in realtime from hospital properties like medical equipment, wearables for patients, and smart sensors. This steady flow of different kinds of data brings both possibilities and problems. In our study, we talk about how significant it is to have strong data transmission and processing systems that can handle different data sources well. intelligent automation that is led by AI is at the heart of this change. AI systems can work with the huge amount of data created by IoT devices and use machine learning, predictive analytics, and cognitive computing to improve different parts of hospital management. This paper gives case studies and real-world examples of how IoT, diverse data processing, and AI automation have been used successfully in hospitals to show how these ideas can be used in the real world. IoT technology, diverse data processing, and AI automation are assembled to change the way hospitals work by making them more effective and easier to maintain. This study offers the significance of using these tools to keep up with the varying needs of current healthcare. As hospitals continue to change, this relationship will play an even bigger role in making sure that patients get superior care while making the best use of their resources. © 2023 IEEE.

关键词： Efficiency

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smart Grid data Traceability System based on Blockchain Technologies 8

Smart Grid Data Traceability System based on Blockchain Tech...

引用

8th Annual international conference on Network and Information Systems for Computers, ICNISC 2022

作者： Gao, Lingchao Pi, Zhixian Wang, Jiakai Sun, Jiasong State Grid Corporation of China Big Data Center Beijing China Tsinghua University E. E. Department Beijing China

ISBN: (纸本)9781665453516

The development of smart grid systems is based on the concept of integrating intelligence into all grid components for management, which contains a large amount of heterogeneous data such as various assets and equipment. Big data analytics is considered a practical technology to provide smart grid data management solutions. In order to overcome the problems of artificially introduced label confusion and storage duplication in smart grid data, this paper proposes a smart grid data traceability system based on the principle of blockchain. The experimental results of data traceability based on blockchain technology in the smart grid data traceability system show that by using blockchain technology-based data traceability in the smart grid procurement data platform, the data traceability capability of the smart grid data traceability system is improved. In addition, the tests conducted in the edge computing device scenario also obtained good usability and feasibility. © 2022 IEEE.

关键词： Information management

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Application of intelligent Techniques in smart Grid Automation

Application of Intelligent Techniques in Smart Grid Automati...

引用

Power, Control and computing Technologies (ICPC2T), conference on

作者： Manish Kumar Babu Papia Ray Anita Swain Department of EE VSSUT Burla India Department of ECE BCE Khordha India

ISBN: (数字)9798331530402

ISBN: (纸本)9798331530419

The smart grid is an advanced power system network that integrates cutting-edge technologies to enable efficient, reliable, and sustainable energy generation, distribution, and utilization. This paper provides a comprehensive survey of intelligent techniques, including machine learning for load forecasting and fault detection, optimization algorithms for demand-side management and renewable energy integration, and data analytics for real-time grid monitoring and decisionmaking. These approaches enhance grid performance by improving flexibility, operational efficiency, and resilience to disruptions. Specific examples, such as predictive maintenance using machine learning and optimization-based energy scheduling for microgrids, are discussed to illustrate their practical applications. The paper also explores challenges like cybersecurity and data quality, offering potential mitigation strategies. Additionally, successful implementations and their outcomes are highlighted, showcasing the transformative impact of intelligent techniques on smart grid automation. Finally, future research directions, such as leveraging blockchain for secure transactions and quantum computing for advanced optimizations, are identified to guide advancements in this field.

关键词： Renewable energy sources Automation Demand side management data analysis Machine learning Real-time systems smart grids Optimization Resilience Predictive maintenance

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Transwarp data Cloud: A Stable, Efficient, and intelligent data Application Cloud Platform 7

Transwarp Data Cloud: A Stable, Efficient, and Intelligent D...

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7th IEEE international conference on smart Cloud, smartCloud 2022

作者： Yang, Hongshan Liu, Wanggen Liu, Chenyun Wang, Tianqing Peng, Lei Transwarp Technology Co. Ltd Shanghai China Shanghai Big Data Center Shanghai China

ISBN: (数字)9781665451796

ISBN: (纸本)9781665451796

Large value hidden in Big data has motivated enterprises to transform from information technology magnates to data technology magnates. Cloud computing and artificial intelligence offer eligible solutions for extracting information in Big data, and integration of the above three renders the data cloud platform. In this paper, we specify Transwarp data Cloud (TDC), a stable, efficient, and intelligent data application cloud platform, which fuses data cloud, analytics cloud, and application cloud to manage all types of applications and services while sharing a well-maintained underlying infrastructure layer. In addition, we identify a general application framework based on TDC, by which various data-driven applications can be supported, and then we discuss some popular applied domains including Big data, Application Development and Management, and artificial intelligence. With powerful tools and flexible application support, TDC can help enterprises with the innovation and revolution of business in the era of Big data. © 2022 IEEE.

关键词： Big data

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Predictive analytics for Human Resource Management: Enhancing Talent Acquisition and Retention Using data analytics

Predictive Analytics for Human Resource Management: Enhancin...

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Innovative computing, intelligent Communication and smart Electrical Systems (ICSES), international conference on

作者： D. Radhasri Easwara Moorthy. R Vinothini. K Karthikeyan. S Aswini. L Department of Commerce Dr.SNS Rajalakshmi College of Arts and Science Tamilnadu India

ISBN: (数字)9798331543624

ISBN: (纸本)9798331543631

HRM depends on the output of predictive analytics by which the input achieves accurate data on employee hiring and retention. For enhancing the decision-making in the HR domain, this research proposes a novel multi-modal logistic regression, XGBoost, and deep learning-based designated hybrid prediction model. Due to the integration of several more common and uncommon HR datasets and richer feature engineering techniques, the mentioned model eliminates the limitations of previous studies. These enhance the chances of applicant selection and consequently the chances of the applicants' retention. The proposed hybrid model achieved 91.4% accuracy for applicant selection and 89.7% for employee retention; the accuracy of the models developed in the years 2021, 2022 & 2023, was 82.3%, 84.9%, and 87.4% respectively. Its implementation using IBM Watson and Kafka will afford HR managers practical real-time information from the model. Lastly, the benefits of applying the model to enhance the HR procedures are highlighted and recommendations for further work to increase the model's applicability in other areas are made.

关键词： Logistic regression Accuracy data analysis Decision making Reinforcement learning Predictive models Real-time systems data models Predictive analytics Human resource management

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Analyzing the Impact of Big data Technologies on Network Performance of smart Systems

Analyzing the Impact of Big Data Technologies on Network Per...

引用

international conference on computing and Networking Technology (ICCNT)

作者： Atul Kumar Pathak Meenakshi Dheer P S Raghavendra Rao Department of Law ARKA JAIN University Jamshedpur Jharkhand India Department of Agriculture Vivekananda Global University Jaipur India Department of Mechanical Engineering School of Engineering and Technology JAIN (Deemed to be University) Bangalore Karnataka India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

Large facts technology have revolutionized the manner smart systems, along with the net of things (IoT) and gadget-to-device (M2M) verbal exchange networks, operate. The accelerated availability of massive datasets, blended with excessive-overall performance computing and facts storage talents, has enabled the development of many powerful programs and network overall performance-enhancing answers. This paper analyzes the impact of huge statistics technology at the performance of smart structures. We study the use of huge statistics technologies which includes Hadoop, Apache Spark, and Apache Flink within the context of numerous smart applications, inclusive of predictive analytics, actual-time analytics, and facts lake optimization. The paper argues that the adoption of huge statistics technologies can enhance the scalability and overall performance of smart systems drastically. Specifically, the usage of huge statistics technologies can enhance the scalability and safety of records lakes and permit actual-time analytics in smart systems.

关键词： Machine-to-machine communications Scalability Lakes smart systems Routing Real-time systems Safety intelligent structures Predictive analytics Optimization

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Research on intelligent Manufacturing Production Lines for Automobile Wheel Hubs by Digital Twin Models

Research on Intelligent Manufacturing Production Lines for A...

引用

data analytics, computing and Artificial Intelligence (ICDACAI), international conference on

作者： Cao Zhuming Dong Huanbo Jia Jide Yi Shouhua The Higher Educational Key Laboratory for Flexible Manufacturing Equipment Integration of Fujian Province Xiamen Institute of Technology Xiamen China Metalworking Practice Center School of Advanced Engineering University of Science and Technology Beijing Beijing China Center of Modern Engineering Training Hunan University Changsha China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

Due to the complex geometric shapes, high precision design dimensions, and specific material characteristics of automobile wheel hubs, there are stringent requirements for processing procedures, efficiency, and stability. To meet these demands, enterprises commonly adopt intelligent manufacturing production lines. Key challenges include establishing adaptive intelligent capabilities for the "processing-measurement-compensation-processing" cycle, constructing digital twin models of wheel hub production lines for real-time synchronization in virtual reality production, optimizing equipment and process interfaces, and improving fixture systems. Integrating discrete CNC machining, inspection, and assembly organically is crucial for smart manufacturing engineers. This article provides targeted discussions on core technologies and development directions in this field.

关键词： Solid modeling Shape Wheels Production Virtual reality Stability analysis Digital twins Automobiles Synchronization smart manufacturing

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Reliability of MEMS Accelerometers Embedded in smart Mobile Devices for Robotics Applications 1

引用

international conference on computing, Intelligence and data analytics, ICCIDA 2022

作者： Bakirci, Murat Cetin, Mecit Faculty of Aeronautics and Astronautics Tarsus University Mersin33400 Turkey Transportation Research Institute Old Dominion University NorfolkVA23529 United States

ISBN: (数字)9783031270994

ISBN: (纸本)9783031270987

This study focuses on assessing the reliability of data from the accelerometer sensors embedded in smart mobile devices that may potentially be used for robotics and intelligent transportation systems (ITS) applications. It is shown how bias and noise elimination can be executed more consistently from acceleration profiles obtained from an accelerometer with a high amount of error. In cases where accurate acceleration information could not be detected through noise filtering, averaged acceleration values in specific time windows were computed and introduced as measurement values to the filtering algorithm. Thus, more consistent acceleration profiles were obtained through making better state estimations. As an alternative to one dimensional bias elimination process, bias errors were detected in six different orientations in three dimensions and subtracted from raw readings. Furthermore, ratiometricity analysis, which is important in applications that require long-term data collection, but is generally overlooked, was also performed through collecting continuous acceleration data for twelve hours. Ratiometric error was numerically quantified and completely subtracted from the raw data through computation of slopes between specific error regions with linear variation assumption between these regions. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Errors

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A Study on Surveillance System Using Deep Learning Methods 1

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2nd international conference on Ubiquitous computing and intelligent Information Systems (ICUIS)

作者： Vinothina, V. George, Augustine Prathap, G. Beulah, Jasmine Kristu Jayanti Coll Autonomous Bengaluru India

ISBN: (数字)9789811925412

ISBN: (纸本)9789811925412;9789811925405

Video Surveillance data is one of the varieties of Big data as it produces a huge amount of data required for further needs. Nowadays, the number of disruptive and aggressive activities that have been occuring are increased dramatically. Hence, securing individuals in public places like shopping malls, banks, public transportations, etc., has become significant. These public places are being equipped with CCTV (Closed Circuit Television) cameras to monitor the activity of the people. Monitoring also needs human's consistent focus to analyze the captured scenes and to react immediately if there is any suspicious activity such as theft, sabotage, bullying, etc. But constant focus on surveillance camera videos and identifying the unusual activities in the video is a challenging task as it needs time and manpower. Hence this paper analyzes various start-of-the-art video analytics methods to detect any aggression and unusual sign.

关键词： Big data Deep learning Suspicious activity Video surveillance

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