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Quality of Service (QoS)-Driven Edge Computing and Smart Hospitals: A Vision, Architectural Elements, and Future Directions 1

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NIELIT's International Conference on Communication, Electronics and Digital Technology, NICE-DT 2023

作者： Buyya, Rajkumar Srirama, Satish N. Mahmud, Redowan Goudarzi, Mohammad Ismail, Leila Kostakos, Vassilis Lab School of Computing and Information Systems The University of Melbourne Melbourne Australia School of Computer and Information Sciences The University of Hyderabad Hyderabad India School of Electrical Engineering Computing and Mathematical Sciences Curtin University Perth Australia Lab Department of Computer Science and Software Engineering National Water and Energy Center United Arab Emirates University Abu Dhabi United Arab Emirates

ISBN: (数字)9789819916993

ISBN: (纸本)9789819916986

The Internet of Things (IoT) paradigm is drastically changing our world by making everyday objects an integral part of the Internet. This transformation is increasingly being adopted in the healthcare sector, where Smart Hospitals are now relying on IoT technologies to track staff, patients, devices, and equipment, both within a hospital and beyond. This paradigm opens the door to new innovations for creating novel types of interactions among objects, services, and people in smarter ways to enhance the quality of patient services and the efficient utilisation of resources. However, the realisation of real-time IoT applications in health care and, ultimately, the development of Smart Hospitals are constrained by their current Cloud-based computing environment. Edge computing emerged as a new computing model that harnesses Edge-based resources alongside Clouds for real-time IoT applications. It helps to capitalise on the potential economic impact of the IoT paradigm of $11 trillion per year, with a trillion IoT devices deployed by 2025 to sense, manage, and monitor the hospital systems in real time. This vision paper proposes new algorithms and software systems to tackle important challenges in Edge computing-enabled Smart Hospitals, including how to manage and execute diverse real-time IoT applications and how to meet their diverse and strict Quality of Service (QoS) requirements in hospital settings. The vision we outline can help tackle timely challenges that hospitals increasingly face. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Quality of service

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Development of Microcontroller-Based Pure Sine Wave Inverter with Overload and Overheating Protection 17

Development of Microcontroller-Based Pure Sine Wave Inverter...

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17th IEEE International Conference on Advanced Trends in Radioelectronics, Telecommunications and computer engineering, TCSET 2024

作者： Holovatyy, Andriy Lobur, Mykhaylo Holovata, Sofia Lukaszewicz, Andrzej Nowakowski, Marek Kolesnyk, Kostyantyn Lviv Polytechnic National University Department of Computer-Aided Design Systems Lviv Ukraine Ukrainian National Forestry University Department of Software Engineering Lviv Ukraine Bialystok University of Technology Department of Machinery Design and Operation Bialystok Poland Military Institute of Armoured and Automotive Technology Development Department Sulejowek Poland Lviv Polytechnic National University Department of Computera-Aided Design Systems Lviv Ukraine

ISBN: (纸本)9798331520564

In the paper, hardware and software of the Arduino based pure sine wave inverter with overload and overheating protection have been developed. The inverter constantly monitors the consumption current, the battery voltage, the temperature of the power switches (radiator) and, if their parameters are normal, forms a sinusoidal voltage of 230 V, 50 Hz at the output of the inverter, similar to the network voltage. The inverter provides the display of information on the LCD screen about current and power consumption, battery voltage, temperature of the inverter power switches, as well as display of emergency icons when the permissible operating parameters are exceeded. The inverter generates sound and visual warning messages with LED indicators and buzzer. The inverter can be used as a lightweight low-power 100 W network inverter with sine-wave voltage for autonomous power supply of low-power electronics. © 2024 IEEE.

关键词： Microcontrollers

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Modeling and Real-Time Simulation of Microgrid Components Using Systemc-Ams

Modeling and Real-Time Simulation of Microgrid Components Us...

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2023 Winter Simulation Conference, WSC 2023

作者： Bhadani, Rahul Karsai, Gabor Tu, Hao Lukic, Srdjan Vanderbilt University Institute for Software Integrated Systems 1025 16th Ave S Suite 102 NashvilleTN37212 United States North Carolina State University Electrical and Computer Engineering 890 Oval Drive 3114 Engineering Building II RaleighNC27606 United States

ISBN: (纸本)9798350369663

Microgrids are localized power systems that can function independently or alongside the main grid. They consist of interconnected generators, energy storage, and loads that can be managed locally. Using SystemC-AMS, we demonstrate how microgrid components, including solar panels and converters, can be accurately modeled and simulated, along with their interactions. Real-time simulations are crucial for understanding microgrid behavior and optimizing components. This approach facilitates seamless integration with hardware prototypes and automation systems, supporting various development stages. Our study presents a best-case scenario for real-time simulation, assuming each loop takes less time than the simulation time step, with fallback to the previous value if data isn't received in time. This article introduces the first known real-time simulation strategy using SystemC-AMS, enabling the real-time simulation of microgrid components and integration with external devices. The implementation adopts a model-based design approach, creating increasingly complex systems with grid components and controllers. © 2023 IEEE.

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Drowsiness Detection Using CNN Architecture

Drowsiness Detection Using CNN Architecture

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International Conference on Futuristic Technologies (INCOFT)

作者： N.T. Renukadevi K. Kishore K. Saraswathi T. Roshan Nithish Department of Computer Technology-UG Kongu Engineering college Erode India B.Sc. (Software Systems) Kongu Engineering College Erode India B.Sc.(Computer Systems and Design) Kongu Engineering College Erode India

Nowadays, road accidents occur owing to the distractions of people who drives the vehicles by Internal or External factors. Using of Mobile phones and driving continuously for several hours are some of the reasons of driver distraction. Among these, the main distractions faced by drivers are drowsiness. Specifically, a driver turns to sleep while driving causes an accident. Latest studies reveal that approximately 20% of vehicle hits have caused by drowsy drivers. And now, these types of accidents can be detected by using modern software technologies. In that, Deep learning is a category of Artificial Intelligence (AI) concepts, which imitate the way humans, gain certain types of knowledge. Deep Learning plays a vital role in health care industry also. The main characteristic of deep learning is, it can built a model automatically by self-learning. In deep learning, Convolutional Neural Network (CNN) is a type of deep neural networks, which is applied to investigate visual imagery. In this research work, a CNN model will be built to identify the drowsiness of the driver by observing the driver's face reactions. The driver drowsiness dataset is downloaded from data-flair website and trained with CNN architecture. In this work, an image of driver's face will be captured through web camera and compared with trained images .If matches occur, an alarm will be given to make awareness to the driver and to avoid accidents.

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Intelligent Daycare: Enhancing Child Safety with IoT and Machine Learning Innovations

Intelligent Daycare: Enhancing Child Safety with IoT and Mac...

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International Conference on Communication and Electronics systems (ICCES)

作者： Amisha Prathyanga Pasindu Shyaminda Pasan Chamikara Sachin Lakshan Samantha Thelijjagoda Dharshana Kasthurirathna Department of Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka Department of Computer Systems Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (数字)9798350377972

ISBN: (纸本)9798350377989

Child safety and well-being in daycare settings are important, thus it is vital that the persons in charge be attentive to them. This research tries to solve the problem by introducing a smart and detailed monitoring system that utilizes new technology to enhance safety and support caretakers. The system has various innovative features, such as child missing detection, behavior and facial expression analysis, cry analysis and categorization, and fall detection. Using high-resolution cameras and on-device Edge AI capabilities, it ensures real-time surveillance of children's activities while protecting privacy. The approach integrates behavior and facial expression analysis to assess emotional states, cry recognition to discover childcare needs, as well as a useful fall detection system that can tell the difference between falls and other movements. All these parts synergize to hand over the necessary information to the caregivers on time and in a way that they can act upon. The quantitative experiments in real-time childcare centers show high accuracy through all the components, attesting to the system's reliability and durability. This research has important significance in improving the safety and the frequency response in daycare centers because it gives caregivers automated tools to quickly address the needs of children. While promising, the system has drawbacks, such as potential biases in data models and a reliance on ideal environmental circumstances. Future work intends to improve flexibility across varied daycare situations, improve accuracy through larger datasets, and investigate ethical frameworks for wider application.

关键词： Privacy Ethics Accuracy Surveillance Machine learning Edge AI Real-time systems Safety Time factors Fall detection

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SMATCH-M-LLM: Semantic Similarity in Metamodel Matching With Large Language Models

SMATCH-M-LLM: Semantic Similarity in Metamodel Matching With...

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International Mining software Repositories, MSR

作者： Nafisa Ahmed Hin Chi Kwok Mohammad Hamdaqa Wesley K. G. Assunção Department of Computer and Software Engineering Polytechnique Montréal Montréal Canada Department of Industrial and Systems Engineering Hong Kong Polytechnic University Hong Kong China Department of Computer Science North Carolina State University Raleigh USA

ISBN: (数字)9798331501839

ISBN: (纸本)9798331501846

Metamodel matching plays a crucial role in defining transformation rules in model-driven engineering by identifying correspondences between different metamodels, forming the foundation for effective transformations. Current techniques face significant challenges due to syntactical and structural heterogeneity. To address this, matching techniques often employ semantic similarity to identify correspondences. Traditional semantic matchers, however, rely on ontology matching tools or lexical databases, which often struggle when metamodels use different terminologies or hierarchical structures. Inspired by the contextual understanding capabilities of Large Language Models (LLMs), this paper explores the capability of GPT-4 potentials as a semantic matcher and alternative to existing methods for metamodel matching. However, metamodels can be large, which can overwhelm LLMs if provided in a single prompt, leading to reduced accuracy. Therefore, we propose prompting LLMs with fragments of the source and target metamodels, identifying correspondences through an iterative process. The fragments to be provided in the prompt are identified based on an initial mapping derived from their elements’ definitions. Through experiments with 10 metamodels, our results show that our LLMbased approach improves the accuracy of metamodel matching, achieving an average F-measure of $\approx 91 \%$, outperforming both the baseline and hybrid approaches, which have a maximum average F-measure of $\approx \mathbf{2 9 \%}$ and $\approx \mathbf{7 4 \%}$, respectively. Moreover, our approach surpasses single-prompt LLM-based matching, which has an average $\mathbf{F}$-measure of $\mathbf{8 0 \%}$, by approximately $\mathbf{1 1 \%}$.

关键词： Accuracy Costs Terminology Databases Large language models Semantics Ontologies Model driven engineering software Iterative methods

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Moving from the Developer Machine to IoT Devices: An Empirical Study

Moving from the Developer Machine to IoT Devices: An Empiric...

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IEEE Cybersecurity Development (SecDev)

作者： Md Rabbi Alam Jinpeng Wei Md Sajidul Islam Sajid Qingyang Wang Chenglong Fu Department of Software and Information Systems University of North Carolina at Charlotte USA Department of Computer and Information Sciences Towson University USA Department of Computer Science and Engineering Louisiana State University USA

ISBN: (数字)9798350391930

ISBN: (纸本)9798350391947

With the growing prevalence of Internet of Things (IoT) devices, IoT cloud platforms have become increasingly vital in the ecosystem that allows heterogeneous IoT devices to be accessed and managed by a wide range of IoT applications. IoT applications are typically hosted on dedicated application servers within the cloud platforms and offer intelligent automation, control, and management features for all connected IoT devices. However, we found that IoT devices can be attacked if the development environment is compromised. In this paper, we conduct the first systematic study on the security risks of IoT cloud platforms that are introduced by compromised development environments. We discover three novel attacks that can invoke commands on the IoT devices, initiate malicious IoT firmware update, and get access to the IoT devices through secure tunneling. We confirm the feasibility of these attacks on mainstream commercial IoT cloud platforms, including Azure IoT Hub, AWS IoT Core, Samsung SmartThings, IBM Watson IoT, and Google IoT, demonstrating their potential to impact a large number of devices. Our work leads to the creation of CVE-2023-38372 by IBM.

关键词： Resistance Intelligent automation Cloud computing Systematics Tunneling Internet of Things Security Servers Protection Microprogramming

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Not All Fabrics Are Created Equal: Exploring eFPGA Parameters for IP Redaction

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IEEE Transactions on Very Large Scale Integration (VLSI) systems 2023年第10期31卷 1459-1471页

作者： Bhandari, Jitendra Moosa, Abdul Khader Thalakkattu Tan, Benjamin Pilato, Christian Gore, Ganesh Tang, Xifan Temple, Scott Gaillardon, Pierre-Emmanuel Karri, Ramesh New York University Center for Cybersecurity New YorkNY11201 United States University of Calgary Department of Electrical and Software Engineering CalgaryT2N 1N4 Canada Politecnico di Milano Informazione e Bioingegneria Dipartimento di Elettronica Milan20133 Italy The University of Utah Laboratory for NanoIntegrated Systems Electrical and Computer Engineering Department Salt Lake CityUT84112 United States

Semiconductor design houses rely on third-party foundries to manufacture their integrated circuits (ICs). While this trend allows them to tackle fabrication costs, it introduces security concerns as external (and potentially malicious) parties can access critical parts of the designs and steal or modify the intellectual property (IP). Embedded field-programmable gate array (eFPGA) redaction is a promising technique to protect critical IPs of an ASIC by redacting (i.e., removing) critical parts and mapping them onto a custom reconfigurable fabric. Only trusted parties will receive the correct bitstream to restore the redacted functionality. While previous studies imply that using an eFPGA is a sufficient condition to provide security against IP threats like reverse-engineering, whether this truly holds for all eFPGA architectures is unclear, thus motivating the study in this article. We examine the security of eFPGA fabrics generated by varying different FPGA design parameters. We characterize the power, performance, and area (PPA) characteristics and evaluate each fabric's resistance to Boolean satisfiability (SAT)-based bitstream recovery. Our results encourage designers to work with custom eFPGA fabrics rather than off-The-shelf commercial FPGAs and reveals that only considering a redaction fabric's bitstream size is inadequate for gauging security. © 1993-2012 IEEE.

关键词： Fabrication

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Artificial Intelligence For Realtime Face Recognition Attendance Using College Classrooms and Buses

Artificial Intelligence For Realtime Face Recognition Attend...

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Electrical Electronics and Computing Technologies (ICEECT), International Conference on

作者： Ahila A Hosanna Princye P Poonguzhali A Kavivendhan M. Deepa A. Arthy R. Saravanakumar Department of Electronics and Communication Engineering Sri Sairam College of Engineering Anekal Bangalore India Department of Computer Science and Business Systems Francis Xavier Engineering College Tirunelveli Tamil Nadu India Software Analyst Iconix Software Solution Tirunelveli Tamil Nadu India

ISBN: (数字)9798350378092

ISBN: (纸本)9798350378108

Teachers take attendance by having pupils sign in or check-in classes and transportation. Student absences often result from individual mistakes. This article examines a technology that records data from classroom photographs of every student's face. This research uses an Adaptive Boost Classifier, Random Forest (RF), and Deep Convolutional Neural Networks (DCNNs). The model performs well on the DCNN model with 88 and 92% accuracy and on the ResNet50 pre-trained model with 97.21% accuracy. After detecting each student's face, they recorded their present status in an Excel document. It kept the best system implementation approach based on performance.

关键词： Adaptation models Accuracy Face recognition Transportation Forestry Convolutional neural networks Pupils System implementation Random forests Residual neural networks

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System to Improve the Quality of Water Resources in Sri Lanka Using Machine Learning and Image Processing 4

System to Improve the Quality of Water Resources in Sri Lank...

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4th International Conference on Advancements in Computing, ICAC 2022

作者： Liyanage, Samindi M.H. Gajanayake, G.M.B.S. Wijewickrama, Oshini Fernando, S.D.S.A. Wijendra, Dinuka Gamage, Aruna Ishara Department of Information Technology Sri Lanka Institute of Information Technology Malabe Sri Lanka Department Computer Systems & Software Engineering Sri Lanka Institute of Information Technology Malabe Sri Lanka

ISBN: (纸本)9798350398090

Water covers approximately 71% of the earth's surface, but only 1.2% of it can be used for drinking. However, due to the amount of waste water released into water resources, the presence of harmful microorganisms, and natural occurrences such as eutrophication, even that water cannot be used directly for drinking purposes without purification. One method of purifying water is chlorination. However, if the chlorine level exceeds the standard, it can cause both long-term and short-term illnesses. As a result, a system is imposed to solve four problems: predicting the pH value of chlorinated drinking water, determining the quantification value of active sludge in a wastewater plant, detecting microorganisms in drinking water, and predicting the percentage of eutrophication in a water resource. © 2022 IEEE.

关键词： Potable water

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