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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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Risk-Sensitive Filtering under False Data Injection Attacks

Risk-Sensitive Filtering under False Data Injection Attacks

引用

international conference on Multisensor Fusion and Integration for intelligent systems (MFI)

作者： Kundan Kumar Muhammad Iqbal Simo Särkkä Department of Electrical Engineering and Automation Aalto University Finland

ISBN: (数字)9798350368031

ISBN: (纸本)9798350368048

This paper addresses a risk-sensitive remote estimation problem for cyber-physical systems (CPSs) where the accurate model of a dynamic system is not completely known or may differ from the assumed model. In CPSs, sensors and the monitoring control center are remotely located. Sensors transmit the measurements via unreliable wireless communication channels that are vulnerable to cyber-attacks. Specifically, attackers can inject false data to alter the measurements in the communication channel or attack sensors. To tackle this, we design a risk-sensitive filtering algorithm to operate under false data injection attacks. The proposed estimator aims to minimize the risk-sensitive error criterion, defined as the expectation of the accumulated exponential quadratic error. Simulation results demonstrate the effectiveness of the proposed algorithm.

关键词： Wireless communication Estimation error Filtering Simulation Linear regression Filtering algorithms Approximation algorithms Sensors intelligent systems Monitoring

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intelligent Home Speech Recognition control System Based on Single Chip Microcomputer

Intelligent Home Speech Recognition Control System Based on ...

引用

2023 ieee international conference on Sensors, Electronics and Computer Engineering, ICSECE 2023

作者： Zhimeng, Liu Tong, Fu Yuxia, Zhang Dalian University of Technology City Institute Liaoning Dalian China

ISBN: (纸本)9798350313734

This design is based on single chip microcomputer intelligent home speech recognition control system, the system is composed of software and hardware parts. The hardware part basically includes the voice recognition part, the key setting part and the prompt display part. Through voice commands to control the switching and running functions of various home systems. With STM32 single chip microcomputer as the core, the design of TFT color screen, intelligent voice recognition module, temperature and humidity detection module, light acquisition module, lighting and dark adjustment, fan driver module, relay driver module and key module. The device has three operating modes: automatic mode, voice-activated mode and manual mode. Among them, the voice control mode realizes intelligent dialogue through intelligent voice recognition module, and controls the switch, level setting and mode switching of all devices. Automatic mode Automatically controls the device by setting the expected temperature, humidity, etc. Manual mode is used as a backup when both voice and automatic modes fail. After the system is powered, each detection module can work normally. The results show that the design has practical application value. © 2023 ieee.

关键词： Real time control

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Containerized Computer Vision Applications on Edge Devices 7

Containerized Computer Vision Applications on Edge Devices

引用

7th ieee international conference on Edge Computing and Communications (ieee EDGE) / ieee World Congress on Services (SERVICES)

作者： Alqaisi, Osamah I. Tosun, Ali Saman Korkmaz, Turgay Univ Texas San Antonio Dept Comp Sci San Antonio TX 78249 USA Univ North Carolina Pembroke Dept Math & Comp Sci Pembroke NC 28372 USA

ISBN: (纸本)9798350304831

The proliferation of IoT devices has led to various computer vision applications, where addressing bandwidth and latency challenges through edge nodes presents significant benefits. However, there are still existing gaps and a need for improvements to optimize IoT applications, especially in the field of computer vision, by overcoming limited resources and enhancing device performance. Addressing these challenges is essential to unlock the full potential of IoT applications in real-world scenarios. This paper evaluates the use of lightweight container technology for computer vision applications which using different algorithms, such as Haar Cascades, HOG and CNN with YOLO algorithm, on edge devices and provides a comprehensive comparison and analysis of different versions of computer vision applications in containers in terms of processing ability, and performance. It focuses on containerizing computer vision applications using Docker to achieve safe execution of multiple applications on these devices without interference and to enable flexibility, efficiency, portability, scalability, and isolation. The study also examines the resource usage, execution time, and receiving time of containerized computer vision applications. The research findings significantly advance our understanding of computer vision processing in IoT and edge computing, thereby opening up new avenues for real-time computing scenarios. These insights have the potential to drive transformative advancements in the field, enabling more efficient and accurate computer vision applications in IoT and paving the way for enhanced real-time decision-making, automation, and intelligent systems.

关键词： Edge Computing Embedded Vision Container technology OpenCV Container Docker IoT

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Dream to Drive: Learning Conditional Driving Policies in Imagination 27

Dream to Drive: Learning Conditional Driving Policies in Ima...

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27th ieee international conference on intelligent Transportation systems, ITSC 2024

作者： Joseph, Tim Fechner, Marcus Abouelazm, Ahmed Zollner, Marius J. Fzi Research Center for Information Technology Karlsruhe Germany Karlsruhe Institute of Technology Karlsruhe Germany

ISBN: (纸本)9798331505929

Learning driving policies to control autonomous vehicles via reinforcement learning (RL) offers a solution to learn optimal driving behavior directly from sensor data. However, designing a reward function that leads to a driving policy that works in any situation has not yet been achieved. Instead, one has to use different reward functions for different situation. While possible with model predictive control (MPC), approaches based on RL must be re-trained any time the reward function changes. We suggest a different direction: we propose a model-based RL agent that learns a conditional driving policy by simulating behavior for many different reward functions in imagination using a world model. We do so by randomly sampling parameters that shape the reward function and optimizing an actor-critic policy that is conditioned on these parameters. We evaluate our approach in CARLA and demonstrate that our approach combines the flexibility of MPC with the long-term capabilities and execution speed of RL. © 2024 ieee.

关键词： Adversarial machine learning

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Deep Learning-Based Classification of Lung and Colon Cancer using a Proposed CNN Architecture 5

Deep Learning-Based Classification of Lung and Colon Cancer ...

引用

5th international conference on IoT Based control Networks and intelligent systems, ICICNIS 2024

作者： Verma, Goldy Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9798331518097

Among the main causes of cancer-related death worldwide are lung and colon cancers. Early malignant tumour discovery and precise classification of them define both appropriate treatment and better patient outcomes. This paper provides a convolutional neural network (CNN) model aimed in classifying lung and colon cancer subtypes including colon benign tissue, lung adenocarcinoma, lung benign tissue, and lung squamous cell carcinoma. With 500 images in every class, the model was developed on a 2,500-histology image Kaggle dataset. Since every class gains almost perfect values in accuracy, recall, and F1 scores, our results show a remarkable 99% classification accuracy. To give perfect separation between benign and malignant tissues, the proposed CNN design successfully finds complex patterns in the photos. The study exceeds conventional diagnostic methods since it reveals the great promise of CNNs as a fast, highly accurate non-invasive tool for cancer diagnosis. © 2024 ieee.

关键词： Lung cancer

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Glass Container Fill Level Measurement via Vibration on a Low-Power Embedded System

Glass Container Fill Level Measurement via Vibration on a Lo...

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2023 ieee international conference on Omni-Layer intelligent systems, COINS 2023

作者： Raza, Ali Markovic, Nikola Wolf, Thomas Romahn, Pascal Zinn, Arndt-Hendrik Kolossa, Dorothea Zolitron-Internet of Things Company GmbH Germany Institute of Energy and Automation Technology TU Berlin Germany

ISBN: (纸本)9798350346473

In many European countries, up to 90% of glass is recycled. The glass is often collected in large, open, publicly placed metallic or plastic containers. In order to optimize the collection process, reliable information on the fill levels of these containers is of prime importance. Ideally, containers should be emptied once they are filled up to their capacity. Demand-based route optimization for glass collection is only possible if fill levels of containers are available. This paper introduces a novel method to measure the fill level of glass containers via passive vibration analysis on a smart, solar-powered, Narrow-Band-IoT (NB-IoT) enabled sensor attached to one of the walls of the container. Deep neural networks are used in a resource-constrained environment to reliably estimate the fill level. Considerable reductions in NB-IoT network traffic volume and sensor energy consumption were achieved by employing the principles of edge computing without compromising the quality of the algorithm in comparison to a cloud deployment. © 2023 ieee.

关键词： Edge computing

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Combining Steganography and Cryptography Simultaneously to Safely Mask Data in Graphics 5

Combining Steganography and Cryptography Simultaneously to S...

引用

5th international conference on IoT Based control Networks and intelligent systems, ICICNIS 2024

作者： Mukhopadhyaya, Keka Anushree, M. Bhargav, M. Anusha, E. Vikas, M.R. CMR Institute of Technology Electronics and Communications Engineering AECS Layout Bengaluru India

ISBN: (纸本)9798331518097

This research study proposes a novel approach to secure communication that blends RSA cryptography and steganography. Using Java, Python, and JavaScript, the authors describe a full framework for secretly sending and encrypting sensitive data while hiding it in cover media. Use of public and private key pairs in RSA cryptography to securely encrypt and decrypt messages while safeguarding data integrity. The least significant bit (LSB) approach is used in this study to conceal encrypted data without appreciably altering the appearance or audio quality of the cover media. Cross-platform interoperability, RSA key generation, message encryption and decryption, and steganographic embedding and extraction are important aspects of the work's implementation. After extensive testing and evaluation, we've drawn the conclusion that the work is effective in securely sending and receiving digitally encrypted messages while protecting the privacy and reliability of the data. Users can find the program more usable and accessible across a range of platforms and settings because to its user-friendly interface and seamless integration of steganographic and cryptographic features. © 2024 ieee.

关键词： cybersecurity

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A New Island Genetic Algorithm for Path Planning Problems *

A New Island Genetic Algorithm for Path Planning Problems *

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2023 ieee international conference on Real-Time Computing and Robotics, RCAR 2023

作者： Zhang, Jinghao Chen, Zhe Li, Ning Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Tsinghua University Department of Automation Beijing100084 China

ISBN: (纸本)9798350327182

Genetic algorithm (GA) is an effective method for path planning problems. As a powerful variant of GA, island genetic algorithm (IGA) has considerable improvement in performance. In this paper, a new island model of GA is proposed to avoid the premature phenomenon and achieve better efficiency. First, a new method of creating subpopulations is presented based on K-means to expand the searching area for the optima. Meanwhile, recombining subpopulations is proposed as a new strategy to improve the diversity of populations and save computational time. Moreover, a method is designed based on Monte Carlo sampling to handle the uncertainty of maps. Comparative experiments are presented to verify the efficiency of the proposed algorithm. Then, a proper number of samples is found by simulation to balance the accuracy and the time cost of Monte Carlo sampling. © 2023 ieee.

关键词： Genetic algorithms

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Robust Cooperative control of a Team of UAVs Carrying a Slung Payload

Robust Cooperative Control of a Team of UAVs Carrying a Slun...

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2023 ieee international conference on systems, Man, and cybernetics, SMC 2023

作者： Samarasinghe, Sudarshan Mark Alqumsan, Ahmad Abu Arogbonlo, Adetokunbo Rokonuzzaman, Mohammad Nahavandi, Saeid Institute for Intelligent Systems Research and Innovation Deakin University VIC3216 Australia Swinburne University of Technology Hawthorn Australia

ISBN: (纸本)9798350337020

The increased use of commercial Unmanned Aerial Vehicles (UAVs) has generated a great interest in their potential to be used for transporting loads and other equipment. However, as the attraction of a UAV is its versatility and cost effectiveness, constraints are placed on the size and capability of a single UAV. Therefore, using multiple UAVs in flight formation has become an elegant solution to these limitations. The formation control of a team of load bearing UAVs is far from trivial. The UAV itself is an underactuated nonlinear system posing significant control challenges. Recent research on this topic has shown promising results and interesting modelling methods such as the Udwadia-Kalaba method has been proposed, to model the loaded system. This research will explore this problem using this method while seeking to bring in robust control techniques for low-level UAV stabilization by designing a sliding mode control system. The proposed low level controller will be combined with the formation controller and the stability demonstrated through simulations. © 2023 ieee.

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