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3rd EAI International Conference on Cognitive Computing and Cyber Physical systems, IC4S 2022

作者： Sarkar, Argha Kundu, Mayuri Pareek, Prakash Gupta, Nishu Reis, Manuel J. Cabral S. School of Computer Science and Engineering REVA University Karnataka Bangalore560064 India Department of Electronics and Communication Engineering Vishnu Institute of Technology Andhra Pradesh Bhimavaram534202 India Department of Electronic Systems Faculty of Information Technology and Electrical Engineering Norwegian University of Science and Technology Gjøvik2815 Norway Engineering Department UTAD/IEETA Vila Real5001-801 Portugal

ISBN: (纸本)9783031289743

The present work researches driver drowsiness, which constitutes a huge problem, and can turn into fatal incidents potentially involving the losing of lives, being it while driving in a highway (car, bus, truck, etc.), in the railway, or any other transportation mean (ship, airplane, etc.). Recent technology has been involved in the study of the fatigue behaviour. The purpose of this work is to identify the in-driver’s drowsiness, contributing to get rid of the accidents, mainly during the night, and to ensure better safety in train and on the highways. A camera is used to capture images from the driver, and face detection is executed in real-time to find out the exact position of driver’s face. Here, the blinking of the driver’s eye is under consideration. The fundamental concept lies in the closing of the driver’s eye for a specific duration of time. If the closing time exceeds that certain duration, drowsiness is detected and an alarm is sounded for awareness. Python and OpenCV (using Haarcascade library) are the fundamental programming platforms for sensing the facial attributes. In this work, a cost-effective system for the driver’s drowsiness detection is aimed. Further, the result also indicates the reduction of response and processing time, which is ideal for real time detection. © 2023, ICST institute for computer sciences, Social Informatics and Telecommunications Engineering.

关键词： Python

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Stability Analysis and Performance Evaluation of Delayed Bilateral Telerobotic systems over a Lossy Communication Channel

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Journal of systems science & Complexity 2021年第1期34卷 157-179页

作者： BAKHSHI Ali ALFI Alireza TALEBI Heidar Ali SOURATGAR Amir Aboulfazl YOUSEFI Mahdi Faculty of Electrical and Robotic Engineering Shahrood University of TechnologyShahrood 36199-95161Iran Power Plants Control Systems Technology Development Plan Department of monitoring and ControlNiroo Research InstituteTehran 14665-517Iran Real-Time and Robotics system Laboratory Faculty of Electrical EngineeringAmirkabir University of TechnologyHafez AvenueTehran 15914Iran Electrical and Computer Engineering Department The University of British Columbia2385East MallVan couverBC V6T 1Z4Canada

The focus of this paper is to address a novel control technique for stability and transparency analysis of bilateral telerobotic systems in the presence of data loss and time delay in the communication channel. Different control strategies have been reported to compensate the effects of time delay in the communication channel;however, most of them result in poor performance under data loss. First, a model for data loss is proposed using a finite series representation of a set of periodic continuous *** improve the performance and data reconstruction, a holder circuits is also introduced. The passivity of the overall system is provided via the wave variable technique based on the proposed model for the data loss. The stability analysis of the system is then derived using the Lyapunov theorem under the time delay and the data loss. Finally, experimental results are given to illustrate the capability of the proposed control technique.

关键词： Lossy channel passivity stability telerobotic transparency

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Allocation and Migration of Virtual Machines Using Machine Learning

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computers, Materials & Continua 2022年第2期70卷 3349-3364页

作者： Suruchi Talwani Khaled Alhazmi Jimmy Singla Hasan JAlyamani Ali Kashif Bashir School of Computer Science&Engg. Lovely Professional UniversityPunjabIndia National Center for Robotics and Internet of Things Technology Communication and Information Technology Research InstituteKing Abdulaziz City for Science and Technology(KACST)Riyadh11442Saudi Arabia Department of Information Systems Faculty of Computing and Information Technology in RabighKing Abdulaziz UniversityRabigh21911Saudi Arabia Department of Computing and Mathematics ManchesterMetropolitan UniversityManchesterM156BHUK

Cloud computing promises the advent of a new era of service boosted by means of virtualization *** process of virtualization means creation of virtual infrastructure,devices,servers and computing resources needed to deploy an application *** extensively practiced technology involves selecting an efficient Virtual Machine(VM)to complete the task by transferring applications from Physical Machines(PM)to VM or from VM to *** whole process is very challenging not only in terms of computation but also in terms of energy and *** research paper presents an energy aware VM allocation and migration approach to meet the challenges faced by the growing number of cloud data *** Learning(ML)based Artificial Bee Colony(ABC)is used to rank the VM with respect to the load while considering the energy efficiency as a crucial *** most efficient virtual machines are further selected and thus depending on the dynamics of the load and energy,applications are migrated fromoneVMto *** simulation analysis is performed inMatlab and it shows that this research work results in more reduction in energy consumption as compared to existing studies.

关键词： Cloud computing VM allocation VM migration machine learning

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Exploring the Potential of LLM-based Chatbots for Task Scheduling in Robot Operations

Exploring the Potential of LLM-based Chatbots for Task Sched...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Catarina Rema Armando Sousa Heber Sobreira Pedro Costa Manuel F. Silva CRIIS - Centre for Robotics in Industry and Intelligent Systems INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal Faculty of Engineering University of Porto (FEUP) Porto Portugal ISEP Polytechnic of Porto rua Dr. António Bernardino de Almeida Porto Portugal

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

The rise of Industry 4.0 has revolutionized manufacturing by integrating real-time data analysis, artificial intelligence (AI), automation, and interconnected systems, enabling adaptive and resilient smart factories. Autonomous Mobile Robots (AMRs), with their advanced mobility and navigation capabilities, are a pillar of this transformation. However, their deployment in job shop environments adds complexity to the already challenging Job Shop Scheduling Problem (JSSP), expanding it to include task allocation, robot scheduling, and travel time optimization, creating a multi-faceted, non-deterministic polynomial-time hardness (NP-hard) problem. Traditional approaches such as heuristics, meta-heuristics, and mixed integer linear programming (MILP) are commonly used. Recent AI advancements, particularly large language models (LLM), have shown potential in addressing these scheduling challenges due to significant improvements in reasoning and decision-making from textual data. This paper examines the application of LLM to tackle scheduling complexities in smart job shops with mobile robots. Guided by tailored prompts inserted manually, LLM are employed to generate scheduling solutions, being these compared to an heuristic-based method. The results indicate that LLM currently have limitations in solving complex combinatorial problems, such as task scheduling with mobile robots. Due to issues with consistency and repeatability, they are not yet reliable enough for practical implementation in industrial environments. However, they offer a promising foundation for augmenting traditional approaches in the future.

关键词： Job shop scheduling Service robots Large language models Chatbots real-time systems Mobile robots Resource management Reliability Autonomous robots Smart manufacturing

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Human-centered AI and robotics

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AI Perspectives 2022年第1期4卷 1-14页

作者： Doncieux, Stephane Chatila, Raja Straube, Sirko Kirchner, Frank Institute of Intelligent Systems and Robotics (ISIR) Sorbonne Université CNRS Paris France Robotics Innovation Center DFKI GmbH (German Research Center for Artificial Intelligence) Bremen Germany Faculty of Mathematics and Computer Science Robotics Group University of Bremen Bremen Germany

robotics has a special place in AI as robots are connected to the real world and robots increasingly appear in humans everyday environment, from home to industry. Apart from cases were robots are expected to completely replace them, humans will largely benefit from real interactions with such robots. This is not only true for complex interaction scenarios like robots serving as guides, companions or members in a team, but also for more predefined functions like autonomous transport of people or goods. More and more, robots need suitable interfaces to interact with humans in a way that humans feel comfortable and that takes into account the need for a certain transparency about actions taken. The paper describes the requirements and state-of-the-art for a human-centered robotics research and development, including verbal and non-verbal interaction, understanding and learning from each other, as well as ethical questions that have to be dealt with if robots will be included in our everyday environment, influencing human life and societies.

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Photonic Crystal Design for Bloch Surface Wave Sensing 5

Photonic Crystal Design for Bloch Surface Wave Sensing

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5th International Conference on Applications of Optics and Photonics, AOP 2022

作者： Dias, Bernardo De Almeida, José M. M. M. Coelho, Luís C. C. INESC TEC-Institute for Systems and Computer Engineering Technology and Science Faculty of Sciences University of Porto Porto4169-007 Portugal Department of Physics and Astronomy Faculty of Sciences University of Porto Porto4169-007 Portugal Department of Physics School of Science and Technology University of Trás-os-Montes e Alto Douro Vila Real5001-801 Portugal

Bloch Surface Waves (BSW) consist of electromagnetic modes generated at the interface between a photonic crystal and an isotropic dielectric. This type of surface mode displays sharp resonances and high sensitivity to external refractive index variations, and thus appears to be an ideal candidate for usage in optical sensors. Nevertheless, design and optimization of photonic crystals is not a trivial task and constitutes an ongoing field of research. The sensitivity of BSW in both refractometric and adsorption sensing is calculated analytically using first-order perturbation theory for TE modes, allowing the understanding of how several physical parameters of the photonic crystal influence the sensitivity. Preliminary experimental results are presented, which aim to use the analytical calculations to allow for both refractometric and adsorption sensing in a single photonic crystal structure. © Published under licence by IOP Publishing Ltd.

关键词： Photonic crystals

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Creating Own AI Datasets from Different Language Sources Efficiently: Advantages, Disadvantages and Best Pracitces to Make Own Datasets 6

Creating Own AI Datasets from Different Language Sources Eff...

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6th IEEE International Conference and Workshop Obuda on Electrical and Power Engineering, CANDO-EPE 2023

作者： Molnar, Gyorgy Cserko, Jazsef Nagy, Eniko Balogh, Zoltan Óbuda University Kandó Kálmán Faculty of Electrical Engineering Budapest Hungary Széchenyi University János Csere Apáczai Faculty Győr Hungary John von Neumann University Gamf Faculty of Engineering and Computer Science Kecskemét Hungary Győr Hungary Institute of Cyberphysical Systems Óbuda University Antal Bejczy Center for Intelligent Robotics John von Neumann Faculty Budapest Hungary Constantine the Philosopher University in Nitra Faculty of Natural Sciences and Informatics Department of Informatics Nitra94901 Slovakia

ISBN: (纸本)9798350328752

Artificial Intelligence (AI) has become a ubiquitous technology that has the potential to revolutionize many industries. However, AI requires access to vast amounts of data to achieve its full potential. By understanding these data sources and the best practices for working with them, we can unlock the full potential of AI and create groundbreaking solutions that benefit society as a whole. Data sources can be utilized to train AI algorithms, including structured and unstructured data, but finding relevant datasets is challenging. The main problem is the international sources. Most of the datasets are available only in English or other common languages. However these are good sources, but translating them is expensive and time-consuming. This paper shows how to generate own datasets from open-source data with translation. © 2023 IEEE.

关键词： Artificial intelligence

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A Sentiment Analysis Study of Twitter Users' Reactions to the COVID-19 Vaccine

A Sentiment Analysis Study of Twitter Users' Reactions to th...

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International Conference on Information and Communication systems (ICICS)

作者： Suboh Alkhushayni Zakaria Alomari Du'a Al-Zaleq Dept. Information Systems Faculty of Information Technology and Computer Science Yarmouk University Irbid Jordan Dept. Computer Science New York Institute of Technology Vancouver BC Canada Dept. Robotics and Artificial Intelligence Engineering Al-Ahliyya Amman University Amman Jordan

This study investigates public attitudes towards the COVID-19 vaccine through Twitter data analysis. Using the Twitter API, tweets were collected, preprocessed, and labeled. Features were extracted using the Bag of Words representation, and sentiment analysis was conducted using Text Blob and Vader. Machine learning and deep learning models were trained and tested, revealing that deep learning models achieved the highest accuracy and F1 score. The research underscores the efficacy of machine learning and deep learning in analyzing COVID-19 vaccine-related tweets, shedding light on factors influencing vaccine resistance. These insights are crucial for pharmaceutical companies and public health officials, enabling them to address barriers to vaccine acceptance and enhance the societal benefits of widespread vaccination, contributing to the pandemic's resolution.

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Integrated RFID System for Intralogistics Operations with Industrial Mobile Robots

Integrated RFID System for Intralogistics Operations with In...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Fábio Daniel Pacheco Paulo M. Rebelo Ricardo B. Sousa Manuel F. Silva Hélio S. Mendonça INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal ISEP Polytechnic of Porto Porto Portugal University of Trás-os-Montes and Alto Douro (UTAD) Vila Real Portugal Faculty of Engineering University of Porto (FEUP) Porto Portugal

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

Radio-Frequency IDentification (RFID) technologies automate the identification of objects and persons, having several applications in retail, manufacturing, and intralogistics sectors. Several works explore the application of RFID systems in robotics and intralogistics, focusing on locating robots, tags, and inventory management. This paper addresses the challenge of intralogistics cargo trolleys communicating their characteristics to an autonomous mobile robot through an RFID system. The robot must know the trolley's relative pose to avoid collisions with the surroundings. As a result, the passive tag on the cargo communicates information to the robot, including the base footprint of the trolley. The proposed RFID system includes the development of a controller board to interact with the frontend integrated circuit of an external antenna onboard the industrial mobile robot. Experimental results assess the system's readability distance in two distinct environments and with two different antenna modules. All the code and documentation are available in a public repository.

关键词： Wireless communication Wireless sensor networks Service robots Robot sensing systems Sensors Mobile robots Object recognition Collision avoidance Radiofrequency identification Autonomous robots

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From Competition to Classroom: A Hands-on Approach to robotics Learning

From Competition to Classroom: A Hands-on Approach to Roboti...

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IEEE International Conference on Autonomous Robot systems and Competitions (ICARSC)

作者： Maria S. Lopes Jorge Diogo Ribeiro António Paulo Moreira Claudia D. Rocha João G. Martins José Maria Sarmento José Pedro Carvalho Paulo G. Costa Ricardo B. Sousa Faculty of Engineering University of Porto (FEUP) Porto Portugal INESC TEC - Institute for Systems and Computer Engineering Technology and Science Porto Portugal University of Tras-os-Montes and Alto Douro (UTAD) Vila Real Portugal SYSTEC-ARISE Research Center for System and Technologies Porto Portugal

ISBN: (数字)9798331538606

ISBN: (纸本)9798331538613

robotics education plays a crucial role in developing STEM skills. However, university-level courses often emphasize theoretical learning, which can lead to decreased student engagement and motivation. In this paper, we tackle the challenge of providing hands-on robotics experience in higher education by adapting a mobile robot originally designed for competitions to be used in laboratory classes. Our approach integrates real-world robot operation into coursework, bridging the gap between simulation and physical implementation while maintaining accessibility. The robot's software is developed using ROS, and its effectiveness is assessed through student surveys. The results indicate that the platform increases student engagement and interest in robotics topics. Furthermore, feedback from teachers is also collected and confirmed that the platform boosts students' confidence and understanding of robotics.

关键词： Surveys Education Software Mobile robots Robots Autonomous robots

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