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3rd International Conference on intelligent Communication Technologies and Virtual Mobile Networks, ICICV 2021

作者： Kumar, K. Kranthi Ramaraj, E. Indira, D.N.V.S.L.S. Alagappa University Department of Computer Science Karaikudi India Gudlavalleru Engineering College Department of Information Technology Gudlavalleru India

ISBN: (纸本)9780738111834

Internet of things is the advanced technological enhancement to make every city as smart. Recent days everywhere across the world IoT became one of the leading technologies. The popularity behind this technology is lies in its diverse nature as it integrates various heterogenous systems to work together. This heterogeneous nature lead to many challenging tasks. Apart from all these aspects data fusion is one the peak improvement in any autonomous systems, it improves the systems functionality by applying fusion algorithms. This paper is going to discuss the challenging things of data fusion and will propose specific fusion algorithm to make any autonomous system as perfectly autonomous. Lastly, it is going to present how data Fusion is achieved in IoT. Managing heterogeneous Bigdata and timely data and sensor fusion in IoT is a challenging task meanwhile data analysis, accuracy, reliability and decision-making is also vital role, these aspects are all presented in this paper. It has taken connected car as an example to discuss the above said. © 2021 ieee.

关键词： Internet of things

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Research on Design of advanced Marine Scientific Survey Vessel Based on Computer data Engineering and intelligent Information System

Research on Design of Advanced Marine Scientific Survey Vess...

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Power Electronics, Computer Applications (ICPECA), ieee International Conference on

作者： Ning Wang Xiaojun Hou Liang Ma Haoran Zhang Zhiqiang Zhang Yellow Sea Fisheries Research Institute Qingdao China China Ship Scientific Research Center Qingdao China

This paper studies the integrated fishery environmental scientific survey vessel system, which has the topology and data flow model of the scientific survey vessel information system with the time series database. The performance testing technology of big computer data in scientific survey ship information topology system has established a comprehensive fishery scientific survey system in ocean waters. The scientific research ship information topology system can meet the requirements of the information management algorithm for scientific research ship operation. In this paper, the topological structure of the information system is used to build the data flow model of the scientific research ship. series database. This paper designs a set of ship systems suitable for research and found that the system can meet the needs of comprehensive investigation and research tasks of fishery science in distant waters. The system provides computer platform support for fishery resource protection, environmental restoration, responsible exploration and fishing, and satellite remote sensing applications.

关键词： databases Computational modeling Time series analysis data models Topology Marine vehicles Computer security

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Enhancing IoT-Driven Smart Home Security and Automation with a GCN Model

Enhancing IoT-Driven Smart Home Security and Automation with...

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Integrated Circuits and Communication systems (ICICACS), ieee International Conference on

作者： Sreelakshmi Ganti Ravi Kumar Vankayalapati P. Krishnamoorthy Pallavi S Thakare Ullal Akshatha Nayak P Vignesh Department of Electronics and Communication Engineering Geethanjali College of Engineering and Technology Medchal India Equinix Texas USA Department of Computer Science and Engineering Sasi Institute of Technology & Engineering West Godavari India Department of Information Technology Dr D. Y. Patil Institute of Technology Pimpri India Department of Information Science and Engineering Nitte Meenakshi Institute of Technology Bangalore India Department of Mathematics KCG College of Technology Chennai India

ISBN: (数字)9798331508456

ISBN: (纸本)9798331508463

A network of computing devices and sensors, the Internet of Things (IoT) rapidly exchanges data to assess circumstances and propose new services. intelligent home technologies rely on IoT. Contemporary smart home systems offer automatic lighting control, smoke detectors, temperature sensors, and smart lock installations. But these technologies raise serious privacy and security concerns. Security flaws let hackers access sensitive data, sendoff false alarms, and take control monitoring systems. Smart home technology is vulnerable to many threats because consumers are wary of it. Recommended steps are preprocessing, sensing, and model training. Preparing raw, unstructured data for analysis. DHT11 humidity and temperature sensors and HC-SR501 PIR motion detectors collect data. It trained the model using Multiscale DGCN data. Better than GCN and BiLSTM, Multiscale DGCN performs. It uses Internet of Things-based smart home security data well, with an average accuracy rate of 93.87%. Identifying outliers in sensor data solves major smart home security challenges. Increasing smart home system accuracy reduces security concerns and boosts user trust, which may drive adoption.

关键词： Temperature sensors Accuracy Bidirectional long short term memory Smart homes DH-HEMTs Safety Security Internet of Things Integrated circuit modeling intelligent sensors

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iAMEC, an intelligent Autonomous Mover for Navigation in Indoor People Rich Environments

iAMEC, an Intelligent Autonomous Mover for Navigation in Ind...

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

作者： Hwang, Yin-Tsung Chen, Kuan-Hong Fan, Chih-Peng Lai, Yong-Kang Wu, Chung-Bin Tsai, Hsiao-Ping Lin, Wei-Liang Lin, Kuang-Hao Natl Chung Hsing Univ Dept Elect Engn Taichung Taiwan Feng Chia Univ Dept Elect Engn Taichung Taiwan Natl Formosa Univ Dept Elect Engn Huwei Township Yunlin Taiwan

ISBN: (纸本)9781665419130

This paper presents the key sensing, navigation techniques, and edge AI computing chip design for an autonomous mover, iAMEC, tailored to indoor and people rich environments such as shopping centers. iAMEC aims at serving as a platform for service robots and features swift maneuverability and collision avoidance in navigation. It is equipped with a smart sensing module consisting of a Lidar, a camera and an ultrasonic array radar. Camera images are analyzed on the fly by using 2-stage CNN models for not only object recognition but also pedestrian behavior prediction. The ultrasonic array radar can detect both the distance and the direction of the surrounding objects in short distance. The low cost 1-ray Lidar performs SLAM as well as scanning for a wider range. data fusion results of these three sensing techniques are passed to the navigation/control module, which determines the optimal path and also steers iAMEC to the destination. Navigation is based on a reinforcement learning model, which is trained in a virtual environment by using a simulation engine, UNITY. DLA (deep learning architecture) acceleration chip design and the associated model-to-DLA mapping tool are also developed to facilitate real time edge computing of CNN based image analysis. A 4-wheeled autonomous mover prototype has been built and mounted with developed sensing, navigation and control modules. The evaluation results indicate preliminary success of iAMEC in navigating under a controlled environment.

关键词： autonomous mover CNN based image analysis data fusion navigation deep learning architecture

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Design of a Physiologically Based Feedback Loop Using Biosensors for Interactive XR and Spatial computing Environments

Design of a Physiologically Based Feedback Loop Using Biosen...

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intelligent Reality (ICIR), ieee International Conference on

作者： Eoghan Ó Riain Joseph G. McVeigh Brona M. Fullen Denis Martin David Murphy School of Computer Science & Information Technology School of Clinical Therapies University College Cork Cork Ireland Discipline of Physiotherapy School of Clinical Therapies University College Cork Cork Ireland UCD School of Public Health Physiotherapy and Sports Science UCD Centre for Translational Pain Research University College Dublin Dublin Ireland Centre for Rehabilitation Teesside University Middlesbrough United Kingdom School of Computer Science & Information Technology University College Cork Cork Ireland

ISBN: (数字)9798331534424

ISBN: (纸本)9798331534431

This work investigates the signal characteristics of a physiological response (acute stress) and determines the viability of developing a Virtual Reality (VR) integrated physiologically based real-time feedback loop. This work has possible applications in physiotherapy and patient rehabilitation for long-term conditions including long COVID, persistent pain, and chronic fatigue. Using real-time physiological data, this approach can offer an individualised and immersive therapeutic experience. By synchronizing VR experiences with physiological responses, clinicians can optimise treatment efficacy and facilitate targeted rehabilitation efforts. A design and early prototype were developed to include a feedback loop driven by an ensemble of biosignal signatures, correlating with stress responses, that adjusts dynamic components in the environment. The prototype shows the feasibility of developing a physiologically based XR environment suitable for virtual physiotherapy interventions.

关键词： Feedback loop Prototypes Virtual reality Patient rehabilitation Sensor fusion Physiology Real-time systems Spatial computing Biosensors Stress

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Realization of intelligent Cleaning Control System for Photovoltaic Modules 3

Realization of Intelligent Cleaning Control System for Photo...

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3rd International Conference on Artificial Intelligence and advanced Manufacture, AIAM 2021

作者： Jiang, Xiaojing Nantong Institute of Technology Nantong226002 China

ISBN: (纸本)9781665417327

With the gradual decrease of primary energy sources and the increasing demand for power resources in society, the development of solar energy has attracted worldwide attention. Photovoltaic power generation technology has developed rapidly, and more and more photovoltaic power plants have been built in various countries around the world. Long-term exposure of photovoltaic modules to the outdoors can cause serious ash deposit, and affect the efficiency of photovoltaic power generation, which is why the photovoltaic modules need to be cleaned. This paper designs and implements an intelligent cleaning control system for photovoltaic modules, which is divided into a server system and a Web system. The software and hardware interaction uses Socket communication technology. The server system realizes the one-to-many communication function with the Web system and the cleaning robot, the intelligent cleaning control strategy function, the cleaning robot data storage and the forwarding function of control commands. The Web system mainly realizes information management and intelligent cleaning control functions. The system realizes the information management and intelligent control of the cleaning robot, improves the power generation efficiency of photovoltaic modules, and thereby enhances the economic benefits of photovoltaic power plants. © 2021 ieee.

关键词： Control systems

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A Brief Review of Unsupervised Learning Algorithms for Zero-Day Attacks in Intrusion Detection systems

A Brief Review of Unsupervised Learning Algorithms for Zero-...

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computing and Machine Intelligence (ICMI), International Conference on

作者： Sunkanmi Oluwadare Zag ElSayed Oluwaseun Adekoya Department of Information Technology University of Cincinnati Ohio United States of America Department of Mechanical Engineering University of Cincinnati Ohio United States of America

ISBN: (数字)9798350372977

ISBN: (纸本)9798350372984

This research paper presents a brief review of ten popular unsupervised algorithms widely utilized in pattern recognition publications. The algorithms are assessed based on their popularity, strengths, limitations, and resource require-ments. Considering these factors, we propose two most-preferred algorithms suitable for adoption in IDS (Intrusion Detection systems) to address the problems associated with Zero Day exploits or attacks. Our review of the surveyed algorithms facilitated the recommendation of specific algorithms that can enhance IDS capabilities in detecting and mitigating Zero-Day attacks and anomalous intrusion attempts. These algorithms leverage unsupervised learning techniques to overcome the limitations of traditional signature-based approaches. By incorporating these algorithms, IDS can better handle sophisticated and evolving attacks that often evade detection. In conclusion, this research provides valuable insights into the strengths, limitations, and resource requirements of popular unsupervised algorithms used in pattern recognition. It highlights the potential of adopting these algorithms in IDS systems to bolster their ability to detect and respond to Zero-Day attacks. By recommending the integration of these algorithms, we contribute to the development of intelligent IDS solutions that can adapt to dynamic threat landscapes.

关键词： Surveys Performance evaluation Reviews Heuristic algorithms Intrusion detection Training data Real-time systems

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An IoT Cloud Based Health Monitoring System for Remote Area Using Node MCU: E Health Checker

An IoT Cloud Based Health Monitoring System for Remote Area ...

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

作者： B. Venkataramanaiah Sravan Kumar Chittimalla V Raveendra Reddy A. Vani Malokhat Saidmuratova Surayyo Khasanova P Vinayagam Department of ECE Vel Tech Rangarajan Dr.sagunthala R&D Institute of science and technology Chennai India Enliven Technologies Inc Texas United States Department of EEE Ramireddy Subbaramireddy Engineering College SPSR Nellore India Department of ECE Chaitanya Bharathi Institute of Technology Hyderabad India Department of Pedagogy and Psychology Urgench State University Urgench Uzbekistan Department of Psychology and Medicine Mamun University Khiva Uzbekistan Department of ECE Saveetha Engineering College Chennai India

ISBN: (数字)9798331527549

ISBN: (纸本)9798331527556

This research work introduces a real-time health monitoring system using IOT sensors and cloud integration for human health monitoring. The system leverages the Node MCU micro controller for its Wi-Fi capabilities., interfacing with sensors like DHT11 (for temperature and humidity)., HBR (for heart rate)., and SpO2 (for oxygen saturation). These sensors continuously gather health-related data., which is transmitted to the Thing Speak cloud platform for storage and analysis. The hardware setup involves connecting the Node MCU to the sensors for accurate data collection., while the firmware is programmed to handle real-time data acquisition and cloud communication. ThingSpeak is configured to receive and store the data, organizing it into custom channels for further analysis. Basic data processing algorithms are applied to filter out noise and detect trends in the collected health metrics. The system enables real-time visualization of health data and employs machine learning models to offer personalized healthcare insights. This framework facilitates proactive healthcare interventions., enhancing patient care and supporting chronic condition management. With continuous monitoring and cloud-based analysis, it provides a foundation for personalized treatment plans, improving the overall healthcare experience and people lives in rural areas will benefit.

关键词： Temperature sensors Cloud computing Machine learning algorithms Clouds Medical services Market research Real-time systems Sensor systems Sensors Monitoring

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Convergence of intelligent data acquisition and advanced computing systems

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SENSORS 2021年第7期21卷 2262页

作者： Stamatescu, Grigore Sachenko, Anatoliy Popescu, Dan Univ Politehn Bucuresti Dept Automat & Ind Informat 313 Splaiul Independentei Bucharest 060042 Romania Kazimierz Pulaski Univ Technol & Humanities Radom Dept Informat Ul Malczewskiego 29 PL-26600 Radom Poland West Ukrainian Natl Univ Res Inst Intelligent Comp Syst 3 Peremoga Sq UA-46020 Ternopol Ukraine

The special issue welcomed submissions as extended versions of conference articles published in the proceedings of the “10th ieee International Conference on intelligent data acquisition and advanced computing systems: Technology and Applications (IDAACS’2019)” allowing the authors to expand on their theoretical and experimental contributions. Potential topics of the special issue that were initially defined were mapped onto the core areas and special streams of the IDAACS’2019 conference, and included but were not limited to: advanced instrumentation and data acquisition systems, advanced mathematical methods for data acquisition and computing systems, computational intelligence for instrumentation and data acquisition systems, data analysis and modeling, intelligent distributed systems and remote control, intelligent information systems, data mining, and ontology, Internet of Things, pattern recognition, digital image, and signal processing, intelligent instrumentation and data acquisition systems in advanced manufacturing for Industry 4, intelligent robotics and sensors, machine learning, application for smart buildings and smart cities. [2] presents a system that combines scalar, ground level measurements, from sensor networks with aerial robotic platforms (UAVs) as data collection and communication relay infrastructure. data are colected through existing building automation system (BAS) infrastructure with wireless components for sensing, room temperature sensors, and control, motor valves for the heating elements.

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information transmission protection using linguistic steganography with arithmetic encoding and decoding approach 3

information transmission protection using linguistic stegano...

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3rd ieee International Conference on advanced Trends in Information Theory, ATIT 2021

作者： ivasenko, Maksym Suprun, Olha Suprun, Oleh Software Systems and Technology Department Taras Shevchenko National University of Kyiv Kyiv Ukraine Department of Cybersecurity National Academy of the Security Service of Ukraine Kyiv Ukraine Department of intelligent Software Systems Taras Shevchenko National University of Kyiv Kyiv Ukraine

ISBN: (纸本)9781665438452

Security of internet of Things and internet space in general is one of the main areas of research in the field of information technology today and steganography - one of the best methods of message encryption and transmission. Steganography algorithms are used to hide data in cover media, such as text, images, videos, etc., as cover media and change the structure and features of a text message so that it is not identified by human eyes and machines. However, the use of text media as accompanying text is relatively difficult compared to other methods of information coverage due to the lack of available redundant information in the text data. At the same time, text data is being transmitted the fastest and most frequently, so it is ideal for quickly transmitting short important messagesю in this research, an overview of existing approaches to textual steganography and our approaches to steganography methods are presented. New approaches to text steganography, which easily hide the text-coverage and also take less time to encrypt, are presented. A new method of steganography is shown and tested;a software implementation of this method is created. The advantages of using a new method of steganography are substantiated. it is confirmed that this algorithm is faster when working with large amounts of data, comparing to existing algorithms. At the same time, it allows to choose different parameters and settings, increasing its protective potential. © 2021 ieee.

关键词： Steganography

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