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Automated Biological Analysis System: Integration of Chatbots and Edge computing 26

Automated Biological Analysis System: Integration of Chatbot...

引用

2024 IEEE international conference on automation/26th Congress of the Chilean Association of Automatic control, ICA-ACCA 2024

作者： Reveco-Toledo, Florencia Soto, Ismael Garcia, Veronica University of Santiago of Chile C.I.M.T.T. Department of Electrical Engineering Santiago Chile University of Santiago of Chile C.E.C.T.A. Department of Food Science and Technology Santiago Chile

ISBN: (纸本)9798350378115

This article presents an automated system for counting and analyzing biological samples, integrating edge computing, computer vision, and Natural Language Processing (NLP) through a chatbot interface. The system processes biological samples locally using advanced image processing techniques, reducing latency and improving the accuracy of results. Additionally, the system allows for remote user interaction via a natural language interface and stores spatiotemporal data in the cloud for enhanced management. The system achieves a 6 5 % success rate in Colony-forming unit (CFU) detection and 85% in RFID/QR label recognition, with identified areas for improvement in image quality and standardization. © 2024 IEEE.

关键词： Natural language processing systems

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An Autoencoder-Driven FDIA Detection Method for Virtual Coupling Systems of Heavy-Haul Trains 21

An Autoencoder-Driven FDIA Detection Method for Virtual Coup...

引用

21st IEEE international Symposium on Parallel and Distributed Processing with Applications, 13th IEEE international conference on Big Data and Cloud computing, 16th IEEE international conference on Social computing and Networking and 13th international conference on Sustainable computing and communications, ISPA/BDCloud/SocialCom/SustainCom 2023

作者： Ren, Wanwan Peng, Jun Zhang, Rui Rong, Jieqi Shu, Boyu Liu, Yongting Yang, Yingze Central South University School of Computer Science and Engineering Changsha China Central South University School of Electronic Information Changsha China Changsha University School of Electronic Information and Electrical Engineering Changsha China Central South University School of Automation Changsha China

ISBN: (纸本)9798350329223

The virtual coupling system provides a solution for improving the transport capacity of heavy-haul trains, and its implementation relies on reliable train-to-train communication. However, communications are vulnerable to cyberattacks. Among them, false data injection attacks (FDIAs) are a common and highly concealed form of attack. They interfere with train information interaction by destroying the authenticity of data, disrupting the cooperative control objectives of the virtual coupling system, and thus affecting the stable operation of the train. In order to ensure the safe, reliable, and efficient operation of heavy-haul trains, an autoencoder-driven FDIA detection method for virtual coupling systems of heavy-haul trains is proposed. First, the virtual coupling system of heavy-haul trains is modeled. Next, the collaborative control law of the virtual coupling system is designed, and the potential impact of false data injection on the system is analyzed. Afterward, a stacked autoencoder model is developed. Using the unsupervised idea, the model is trained to learn to reconstruct normal operating data, and the reconstruction error of the trained model is used as an attack detection indicator. Finally, the effectiveness of the proposed scheme is evaluated against several attack scenarios. © 2023 IEEE.

关键词： Learning systems

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A Novel User Authentication and Access control Model in Enhancing Cloud Security 15

A Novel User Authentication and Access Control Model in Enha...

引用

15th international conference on computing communication and Networking Technologies, ICCCNT 2024

作者： Krishna, R. Satya Mohan, V. Murali Koneru Lakshmaiah Education Foundation Department of Computer Science & Engineering Green Fileds A.P. Vaddeswaram522302 India

ISBN: (纸本)9798350370249

The ever-increasing use of cloud computing has made data and resource security a major issue. Unauthorized access to data and cloud services puts many people and organizations in danger. This paper aims to improve cloud security by addressing this difficulty by presenting a novel approach for user authentication and access control. The suggested architecture offers a complete solution for avoiding unwanted access in cloud environments by combining cutting-edge user authentication techniques with strong access control mechanisms. The goal of the research is to create a framework that is user-centric and gives security and user experience equal priority. It makes use of cutting-edge techniques and technologies, including Secure Socket Layer (SSL), Encryption, Adaptive Authentication, and Multi-Factor Authentication (MFA), to guarantee quick and easy user authentication and, ultimately, that only authorized users can access cloud services. Through a rigorous evaluation and testing procedure, this technique shows how effective it is in avoiding disruptions to user convenience while preventing unlawful access. © 2024 IEEE.

关键词： Access control Cloud Security Data Privacy User Authentication

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Deep Learning for Medical Image Segmentation: Applications in Disease Detection and Diagnosis 3

Deep Learning for Medical Image Segmentation: Applications i...

引用

3rd international conference on automation, computing and Renewable Systems, ICACRS 2024

作者： Kannan, R. Jestus, J. Madesh, P. Department of Electronics and Communication Engineering Saveetha Engineering College Chennai India

ISBN: (数字)9798331532420

ISBN: (纸本)9798331532420

The accurate diagnosis of disorders is contingent upon the accurate segmentation of medical images. It enables physicians to isolate specific regions of the body for further investigation. This study introduces a novel deep learning-based segmentation technique that employs a dynamic region-based model in conjunction with convolutional neural networks (CNNs) to enhance the precision of borders and the accuracy of segmentation. To overcome the obstacles associated with segmenting intricate medical images and guarantee precise edge identification, a novel adaptive boundary loss function is suggested. The attention mechanism of the model enables it to fine-tune both small and complicated regions of interest, and it is compatible with a variety of imaging modalities, such as MRI, CT, and ultrasound. The proposed method outperforms existing models on Dice coefficient and Intersection over Union (IoU) metrics, as evidenced by comprehensive evaluations on benchmark datasets, including skin lesion and brain tumor segmentation. The findings indicate that the model has the potential to enhance clinical decision-making by offering more precise disease detection segmentation. © 2024 IEEE.

关键词： Convolutional neural networks

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Voice controlling Industrial automation system 4

Voice Controlling Industrial Automation system

引用

4th IEEE international conference on Advance computing and Innovative Technologies in Engineering, ICACITE 2024

作者： Kumar, Anubhav Aslam, Atif Maheswari, Naman Singh, Jay G L Bajaj Institute of Technology and Management U.P Greater Noida India G L Bajaj Institute of Technology and Management Dept. of Eee U.P Greater Noida India

ISBN: (纸本)9798350360165

The Internet of Things, or IoT, is still gaining popularity across a wide range of sectors and uses. One such sector that has witnessed a significant rise in IoT usage is industrial automation. This article uses PLC, Wifi, and smart switch controller to control domestic appliances and industrial equipment. The proposed approach can be successfully applied in systems where wired connections are either preferred or required because it makes use of wireless control. Using wireless technology, it transmits the signal, where these signals are received at receiver end and further microcontroller decodes same. According to the code, it will switch on and off at the output. Relays that are electromechanical and solid state are employed. In addition to it this system which incorporates capabilities with hand free operations. Where signals are decoded by microcontroller at reciver ends fascinating the ON/OFF of the device, hence this integration device fuctionally represents a edge solution for enchancing in various other enivorments. © 2024 IEEE.

关键词： Domestic appliances

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Edge computing for Microgrid via MATLAB Embedded Coder and Low-Cost Smart Meters 8

Edge Computing for Microgrid via MATLAB Embedded Coder and L...

引用

8th international conference on Smart Grid and Smart Cities, ICSGSC 2024

作者： Xu, Linna Huang, Jian Yang, Shan Zhu, Yongli School of System Science and Engineering Sun-Yat Sen University Guangzhou China

ISBN: (纸本)9798350377408

In this paper, an edge computing-based machine-learning study is conducted for solar inverter power forecasting and droop control in a remote microgrid. The machine learning models and control algorithms are directly deployed on an edge-computing device (a smart meter-concentrator) in the microgrid rather than on a cloud server at the far-end control center, reducing the communication time the inverters need to wait. Experimental results on an ARM-based smart meter board demonstrate the feasibility and correctness of the proposed approach by comparing against the results on the desktop PC. © 2024 IEEE.

关键词： MATLAB

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Shortest Job First with Gateway-based Resource Management Strategy for Fog Enabled Cloud computing 4

Shortest Job First with Gateway-based Resource Management St...

引用

4th IEEE international conference on Data Engineering and communication Systems, ICDECS 2024

作者： Anbazhagan, K. Kumar, Rotash Thilagavathy, R. Anuradha, D. Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Department of Computer Science and Engineering Chennai India Government Engineering College Department of Electronics and Communication Engineering Rajasthan Jhalawar India College of Engineering and Technology Srm Institute of Science and Technology Kattankulathur Department of Computing Technologies Chennai India Panimalar Engineering College Department of Computer Science and Business Systems Chennai India

ISBN: (纸本)9798350393354

In recent years, fog computing has extended cloud services to the network edge, lowering network latency and congestion and overcoming cloud computing restrictions. Many hurdles, however, must be overcome before the benefits of the fog-IoT paradigm for low-latency applications can be completely realized. The most challenging difficulty in IoT applications is developing efficient resource management strategies that maximize throughput while minimizing delay. IoT and fog computing, rather than simply utilizing cloud computing technology, have brought intriguing new data management solutions. Fog computing makes real-time analytics applications conceivable. After combining fog computing technologies with Internet of Things (IoT) applications, the system can reply in milliseconds. Existing fog resource managers focus on a subset of fog resource management parameters such as system response time, network bandwidth, energy consumption, and latency. No Fog resource management takes multiple factors into account at the same time for decision-making, which will become increasingly crucial in intelligent homes. Gateway-based Fog computing pioneered the introduction of the shortest job (SJFGFC) to address these difficulties. The technique is validated in an IoT-based imaginative house automation scenario before being evaluated in a small-scale bright home experiment using the iFogSim toolbox and empirical models. © 2024 IEEE.

关键词： Fog computing

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Computation Offloading for Industrial Internet of Things: A Cooperative Approach 19

Computation Offloading for Industrial Internet of Things: A ...

引用

19th IEEE international Wireless communications and Mobile computing (IEEE IWCMC)

作者： Chouikhi, Samira Esseghir, Moez Merghem-Boulahia, Leila Univ Technol Troyes Comp Sci & Digital Soc LIST3N Lab Troyes France

ISBN: (纸本)9798350333398

The term "Industrial Internet of Things" (IIoT) was created to describe a specific area of the Internet of Things (IoT) that integrates Information and communication Technologies (ICT) like cloud/edge computing, wireless sensor/actuator networks, connected objects, etc. to enable and accelerate the development of industry 4.0. Industry standards for IoT device connectivity and operation set it apart. A few of the properties of Industrial IoT include its high levels of resilience, communication availability, enormous data collecting, security, accuracy, automation, and interoperability. IIoT is also used for complicated task delegation, data-driven decision-making, and remote control of equipment. The IIoT applications also have various levels of criticality and quality of service requirements. Hence, it is very challenging to respect the specificity of each application and guarantee the required QoS. In this paper, we offload computationally demanding tasks to edge and cloud servers with stronger computational capabilities. Our suggested model tries to maximize the number of tasks completed before their tolerant deadlines while minimizing each IIoT device's energy consumption. Furthermore, we introduce a distributed cooperative game that enables each device to choose whether to offload its tasks or locally execute them based on task completion and energy consumption. We demonstrate the existence of the Nash equilibrium by demonstrating that the proposed game is a weighted potential game. We also propose a practical implementation of the game using a distributed mechanism. Finally, we evaluate the proposal using simulation to show the benefits of computation offloading in terms of latency and energy consumption.

关键词： Computation offloading cloud-edge computing Industrial Internet of Things game theory cooperative game

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Digital Twins for Sophisticated Laboratory automation for Energy Management and Security

Digital Twins for Sophisticated Laboratory Automation for En...

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2025 international conference on Computer, Electrical and communication Engineering, ICCECE 2025

作者： Madur, Parameshwar Bureti, Nischitha Rajeshkumar, Sutaria Jay Mangalraj, P. Gitam Dept of Cse Bengaluru India

ISBN: (纸本)9798331513894

The recent advancements in Digital Twin technologies and their transformative applications across various sectors bring in a new dimension to the Human Computer Interface Domain. Due to the immersive and interactive nature of the Digital Twin applications, we are emphasizing to utilize the advancement for laboratory automation and rehabilitation. The democratization of virtual reality, enabled by cost-effective headgear and the integration of Unity AR technology with the Internet of Things (IoT), has revolutionized the control of home appliances, making it an intuitive and immersive experience. We are proposing a model to control sophisticated laboratories' power supplies using digital twin technologies integrated with IoT. The Model encompasses a 2D system-based interaction, a Mixed Reality-based interaction, and a Hand Gesture-based interaction, all developed using the Unity Engine and the Leap Motion-SDK. The integration of IoT devices is achieved through NODEMCU, which toggles the status (ON/OFF) of the appliances upon receiving an HTTP request. This comprehensive exploration of the latest VR and AR technologies and their applications provides valuable insights for future research and development in the field. We have evaluated our proposed work quantitatively and qualitatively (through user experiences) and modernized. © 2025 IEEE.

关键词： Virtualization

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Smart Health Band for Epilepsy and Seizure, Fits Detection with Alert System and Live Location using IoT and Cloud computing 2

Smart Health Band for Epilepsy and Seizure, Fits Detection w...

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2nd IEEE international conference on IoT, communication and automation Technology, ICICAT 2024

作者： Bind, Vishal Sharma, Aditya Kirti Mishra, Kavita Pandey, Prashant Jayprakash Tiwari, Amreesh Rajkiya Engineering College Department of Electronics Engineering Sonbhadra231206 India Madan Mohan Malviya University of Technology Department of Electronics Engineering Gorakhpur273010 India

ISBN: (纸本)9798350368109

Millions of people worldwide suffer from the neurological condition known as epilepsy. The health of patients depends on the prompt identification of epileptic seizures, and technology can be very helpful in this respect. We present a smart health band in this conference article that interfaces with an ESP8266 Node MCU, uses a number of sensors (BMP280, MAX30102, IR, DHT11, LDR, and an OLED display), and interacts with MATLAB for data processing and *** is a neurological condition that impacts millions globally, making the prompt identification of seizures essential for patient care. In this conference paper, we introduce an innovative health band designed to continuously monitor vital parameters, including heart rate, oxygen levels, temperature, humidity, and ambient light through a range of sensors. The data collected in real-time is analyzed using MATLAB algorithms to detect patterns that may indicate an impending seizure. Upon detection, the health band activates an alert system that notifies caregivers or healthcare professionals, providing them with the patient's current location. The alert system of the smart health band is crafted to ensure efficiency and effectiveness, delivering timely notifications through multiple communication methods. The patient's location is determined using GPS or Wi-Fi positioning, facilitating rapid response and intervention during seizure events. Furthermore, the health band leverages cloud computing for data storage and analysis, allowing for remote health monitoring and access. This proposed system presents a holistic approach to epilepsy management and seizure detection, featuring an integrated alert mechanism and real-time location tracking through IoT and cloud technologies. By employing various sensors connected to an ESP8266 Node MCU and utilizing MATLAB for data processing, this system offers a reliable and precise method for seizure detection. The smart health band has the potential to greatly enhance the q

关键词： Electronic health record

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