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IoT for Sustainable Hospitality: A Systematic Review of Opportunities and Challenges for the Hospitality Industry Revolution 19

IoT for Sustainable Hospitality: A Systematic Review of Oppo...

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19th Annual International Conference on Distributed computing in Smart Systems and the Internet of Things, DCOSS-IoT 2023

作者： Poullas, Marios S. Kakoulli, Elena Neapolis University Pafos Intelligent Systems Laboratory Department of Computer Science Pafos Cyprus Cell and Developmental Biology University College London London United Kingdom Cyprus University of Technology Electrical Engineering and Computer Engineering and Informatics Limassol Cyprus

ISBN: (纸本)9798350346497

Technology has influenced the hospitality industry, and the Internet of Things (IoT) has become a focus for sustainability, revenue growth, and problem-solving. This systematic review examined the opportunities and challenges of implementing IoT technology for a sustainable hospitality. Through a thorough analysis of 28 studies, we found that IoT technology has great potential to address sustainability issues in the hospitality industry. However, there are still significant challenges that need to be addressed for the successful implementation of IoT technology in the hospitality industry. Overall, this study highlights the potential of IoT technology to revolutionize the hospitality industry and make it more sustainable. Further research is needed to address the challenges of IoT implementation in the hospitality industry and to evaluate the effectiveness of IoT technology in achieving sustainability goals. © 2023 IEEE.

关键词： Energy efficiency

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A 32 Gb/s PAM-4 Optical Transceiver with Active Back Termination in 40 nm CMOS Technology

IEEE Open Journal of Circuits and Systems

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IEEE Open Journal of Circuits and Systems 2021年 2卷 56-64页

作者： Ho, Wei-Hsiang Hsieh, Yi-Hsun Murmann, Boris Chen, Wei-Zen Department of Electronics Engineering and the Institute of Electronics College of Electrical and Computer Engineering National Chiao Tung University Hsinchu Taiwan Department of Electrical Engineering Stanford University StanfordCA United States

This article describes the design of a 32 Gb/s four-level pulse amplitude modulation (PAM- 4) optical transceiver in a 40 nm CMOS technology. At the transmitter side, the laser driver is composed of an asymmetric waveform equalizer, a 3-tap feed-forward equalizer (FFE), and a novel active-back termination (ABT) circuit. The ABT circuit provides a self-tracking, tunable source impedance to match the characteristic impedance of different laser diodes. At the receiver side, the fully integrated optical receiver consists of a transimpedance amplifier (TIA), a variable gain amplifier (VGA), an automatic threshold tracking circuit (ATC), and a quarter-rate decision feedback equalizer (DFE). By using the adaptive ATC, it reduces the BER induced by the harmonic distortion along the signal path by more than 27X under a THD of -20dB. Both the ATC and DFE are automatically adapted by an on-chip sign-sign LMS (SSLMS) engine. Fabricated in TSMC 40 nm CMOS process, the chip area for the transmitter and receiver are about 0.029 mm2 and 0.23 mm2. The power consumptions are about 146.8 mW and 128.8 mW respectively for the PAM-4 transmitter and receiver. © 2020 IEEE.

关键词： Electronic circuit tracking

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Deep Learning based ROI Segmentation using Convolution Neural Network 2

Deep Learning based ROI Segmentation using Convolution Neura...

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2nd International Conference on Applied Artificial Intelligence and computing, ICAAIC 2023

作者： Arunadevi, R. Sudha, S. Karthi, V. Saranya, M.D. Raaj, Thurai V B Kumar K, Kavin Karpagam Academy of Higher Education Department of Biomedical Engineering Coimbatore India Velalar College of Engineering and Technology Department of Biomedical Engineering Erode India K S R Institute for Engineering and Technology Department of Computer Science and Engineering Tiruchengode India Kpr Institute of Engineering and Technology Department of Electronics and Communication Engineering Coimbatore India Madanapalle Institute of Technology & Science Department of Electrical and Electronics Engineering India Kongu Engineering College Department of Electronics and Communication Engineering Erode638060 India

ISBN: (纸本)9781665456302

Atherosclerosis is a chronic degenerative disease that results in cardiovascular diseases (CVDs) and is detected either by cardiac arrest or stroke. Early diagnosis of CVDs is made possible by identifying Intima Media Thickness (IMT) and elasticity. B-mode ultrasound imaging has on no account ionizing radiation and is economical and non-invasive to assess CVDs. This paper proposes an effective automatic image segmentation method using deep learning CNN for segmenting the region containing intima media of far wall carotid artery. The proposed approach is compared with SVM classifier and RBF neural network and is proven to be robust with improved accuracy and F1 score. © 2023 IEEE.

关键词： Ionizing radiation

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Machine Learning for Caching Placement in Edge computing Networks

Machine Learning for Caching Placement in Edge Computing Net...

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International Conference on computing, Networking and Communications (ICNC)

作者： Liang Zhang Bijan Jabbari Department of Electrical and Computer Engineering George Mason University Fairfax VA USA Department of Electrical and Computing Engineering Communications and Networks Laboratory George Mason University Fairfax VA USA

ISBN: (数字)9798350370997

ISBN: (纸本)9798350371000

Internet of Things devices (IoTDs) that deployed for various applications have limited size, power, storage, and computing capabilities, and many of them are used for low-latency applications. Mobile edge computing (MEC) can be leveraged to reduce the latency of IoTDs, and judicious caching placement can help further to improve the quality of service. In this paper, we study multi-content placement (MCP) in the MEC networks for IoTDs by considering the background data caching in the edge nodes and the data collection of IoTDs. The MCP problem is formulated by considering the caching, the IoTD assignment, and the communication and computing resources allocation to minimize the average latency of all IoTDs. As the MCP problem is NP-hard, we propose a deep reinforcement machine learning algorithm to obtain the caching placement and IoTD assignment jointly to solve the MCP problem. We use an optimal joint resource-scheduling algorithm to assign the resources. Our results demonstrate that considerable latency improvement can be achieved through the proposed deep reinforcement machine learning algorithm as compared to baseline algorithms.

关键词： Machine learning algorithms Multi-access edge computing Scheduling algorithms Simulation Quality of service Data collection Deep reinforcement learning

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Task Allocation in Extreme Edge computing for Complex IoT Services

Task Allocation in Extreme Edge Computing for Complex IoT Se...

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Canadian Conference on electrical and computer engineering (CCECE)

作者： Rawan F. El-Khatib Sara A. Elsayed Nizar Zorba Hossam S. Hassanein Department of Electrical and Computer Engineering Queen’s University Kingston Canada School of Computing Queen’s University Kingston Canada Electrical Engineering Department Qatar University Doha Qatar

ISBN: (数字)9798350371628

ISBN: (纸本)9798350371635

The rise of 6G technology will enable various innovative applications to deliver transformative experiences and services with unprecedented speed, reliability, and interactivity. On one hand, the realization of such innovative applications relies on the processing of large volumes of data generated at the Extreme Edge of the network, requiring time-critical and resource-intensive processing. On the other hand, these applications require handling multi-modal data or inputs from several sensing data sources, and as a result, the resulting computing tasks encompass multiple subtasks that are crucial to service delivery. Conventional offloading schemes overlook the complexity of these applications, jeopardizing the task success rate and application QoS. In this work, we highlight the dire need for a computational offloading scheme that addresses the intricate nature of such applications and their computing tasks, and present a preliminary problem formulation to tackle these needs.

关键词： 6G mobile communication Soft sensors computer network reliability Quality of service Complexity theory Time factors Resource management

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Artificial Intelligence assisted Electric Vehicles Fast Charging Station Design using Grid Distribution Network Model 4

Artificial Intelligence assisted Electric Vehicles Fast Char...

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4th International Conference on Intelligent Technologies, CONIT 2024

作者： Anitha, C. Chitra, K. Vijayalakshmi, G. Kumaran, G. Vijetha, T. Ormila, K. Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Computer Science and Engineering Tamil Nadu Chennai India Cmr Institute of Technology Department of Electrical and Electronics Engineering Karnataka Bengaluru India Prince Shri Venkateshwara Padmavathy Engineering College Department of Electronics and Communication Engineering Tamil Nadu Chennai India Saveetha Institute of Medical and Technical Sciences Saveetha University Saveetha School of Engineering Department of Cse Tamilnadu Chennai India Mlr Institute of Technology Department of Ece Hyderabad Dundigal India A.M.K. Technological Polytechnic College Department of Electrical and Electronics Engineering Tamil Nadu Chennai India

ISBN: (纸本)9798350349900

The electric vehicle charging station is a game-changer that supplants the older kind of charging stations. Our futuristic electric vehicle charging station may be installed virtually anywhere, takes minimal space, and operates independently of the government's power source, in contrast to the current practice of reserving these stations for major urban areas. Among the many global industries that rely on fossil fuels, transportation ranks high. The development of electric vehicles (EVs) and other forms of transportation electrification are thus essential in the fight against carbon-dioxide emissions and the over-reliance on traditional energy sources that are harmful to the environment. At the same time, electricity distribution, use, and supply have been accompanied by massive amounts of data due to the fast digitization of electrical networks and EVs. These datasets may be used to inform choices and insights by using artificial intelligence (AI) algorithms. Despite a number of recent studies in this area, no one has explicitly examined the usefulness of AI for charge-demand profiling, data augmentation, demand forecasting, explainability of demand, and charge optimization of the EVI. For the purpose of efficiently delivering the fast charging function, this study suggested a novel logic called Grid Distributed Fast EV Charging (GDFEVC). To evaluate the proposed model's efficiency, it was cross-validated with the standard Fast EV Charging Model (FEVCM). This AI framework has been empirically tested on a real-world EVI case study, and the results show that it helps with the new problems with dispersed energy supplies that are coming up with EV adoption. © 2024 IEEE.

关键词： Charging stations

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An Intensive Review on Propagative Antagonistic N/W which is used in Health Care System 4

An Intensive Review on Propagative Antagonistic N/W which is...

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4th IEEE International Conference on Advance computing and Innovative Technologies in engineering, ICACITE 2024

作者： Badhoutiya, Arti Sivaiah, Borra Almusawi, Muntather Verma, Rajan Singh, Rajesh Angadi, Sanjeevkumar Gla University Department of Electrical Engineering Mathura India Cmr College of Engineering & Technology Department of Cse India The Islamic University Najaf Iraq Chitkara University Chitkara Center for Research and Development Himachal Pradesh 174103 India Uttaranchal University Uttaranchal Institute of Technology Department of Electronics & Communication Engineering Dehradun248007 India Nutan College of Engineering and Research Computer Science and Engineering Pune Maharashtra Talegaon Dabhade India

ISBN: (纸本)9798350360165

This article introduces a Generative Adversarial Network tailored for medical imaging, in particular designed to synthesize retinal images alongside side their segmented mask. This innovation addresses the challenge of obtaining big datasets for deep getting to know, in particular in scientific fields wherein expert annotations are high priced and time-ingesting. It not satisfactory generates fantastic synthetic scientific pics for supervised analysis but moreover achieves cutting-edge day overall performance with dice coefficients of 0.837 on the STARE dataset and 0.832 on the dataset, surpassing present techniques. This development highlights the capability of GANs in scientific imaging, deep gaining knowledge of, and style transfer applications. © 2024 IEEE.

关键词： Gallium nitride

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Role and Application of Ribs in Solar Air Heater 6

Role and Application of Ribs in Solar Air Heater

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6th International Conference on Contemporary computing and Informatics, IC3I 2023

作者： Singh, Amandeep Joshi, Sanjeev Kumar Kumar, Dharmendra Kumar, Rajiv Pandey, Shiv Dayal Thapliyal, Madhur Uttaranchal Institute of Technology Uttaranchal University Uttarakhand Dehradun India Uttaranchal School of Computing Sciences Uttaranchal University Uttarakhand Dehradun India Shivalik College of Engineering Computer Science and Engineering Department Uttarakhand Dehradun India Graphic Era Hill University Department of Computer Application Uttarakhand Dehradun India

ISBN: (纸本)9798350304480

Maintaining the clean environment and reducing the usage of fossil fuels requires switching to renewable sources of energy, because of limited resources of fossil fuels and having insufficient fossil fuel storage. The world is facing from shortage of fossil fuel and its cost is going too high and its smoke is very harmful to the environment. In this crisis, the world is starting the use of renewable energy. Renewable energies are easily available, and it reduces air pollution and fuel cost. non-conventional energy sources, like solar energy, atomic energy, hydroelectric power, wind energy etc. are a substitute for conventional energy. Solar energy is the best one, is used in various utilization, like solar air heaters, solar water heaters, solar power generation, solar pumps, solar cooking etc. Solar air heater that absorbs heat from the sun's radiations to heat air and it is collected by the collector & converted into kinetic energy and also restored in the form of potential energy. In this review, we will discuss the role of ribs in solar air heating systems to enhance the heat transfer rate, types of rib, and the purpose of ribs arrangement in solar air heating systems. Ribs are used to transfer maximum heat and increase the pressure inside of the cabin and it located on the absorber plate surface and it help to increase the solar air heaters performance. This study emphasizes exploring the effects of ribs and the behaviour of fluid after impacting on the ribs. For drying crops, heating buildings, and other uses, solar air heaters are extremely important in the agriculture sector, small-scale industries, in urban and villages for heating and drying purposes, etc. The use of ribs can enhance the effectiveness of a solar air heating system and this technology can be used for heat transmission enhancement, power generation & can fulfil the world's energy requirements. The primary objectives of this review article are to assist and summaries the research work carried

关键词： Energy Heat transfer Power generation Renewable energy Ribs Solar air heater Solar energy

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Near-field metasurface sensor for an early-stage breast cancer detection

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Sensors International 2025年第1期6卷 100305-100305页

作者： Aldhaeebi, Maged A. Almoneef, Thamer Bamatraf, Saeed Aldhaibain, A.O. Bakhalah, Osamah Alhdad, Saleh Bakhalah, Sumaia Saleem, M. Kamran Electrical Engineering Department College of Engineering Prince Sattam Bin Abdulaziz University Al-Kharj11942 Saudi Arabia Department of Computer Science College of Applied Sciences Seiyun University Hadhramout Seiyun Yemen Department of Electronic and Communication College of Engineering Hadhramout University Hadhramout Mukalla Yemen Department of Electrical Engineering College of Engineering University of Central Punjab Lahore Pakistan

In this paper, a novel and highly sensitive metasurface sensor for microwave breast tumor detection is proposed. The proposed sensor array comprises 8 × 8 small-size sensor elements that are capable of reacting to changes in both electric and magnetic fields. This allows the sensor to detect even minor variations in the surrounding medium, resulting in improved sensitivity. Additionally, designing a sensor array improves sensitivity by covering all areas of the breast tissues with multiple small sensor elements. Numerical studies have been conducted to assess the sensor sensitivity using realistic healthy and non-healthy breast models with diagnosed tumors placed at different locations within healthy breast models in the CST simulation environment at varying stand-off distances. An experiment was conducted to validate the sensor's concept. It involved testing a metasurface sensor with phantoms resembling both healthy female breast tissues and those with a 10 mm tumor. The results from simulations and experiments demonstrate that the metasurface sensor is capable of detecting breast tumors at different distances. For safety compliance, specific absorption rate (SAR) values were obtained through both simulation and experimentation. The simulated SAR values were calculated to be 0.357 W/kg and 0.216 W/kg at 1 g and 10 g, respectively, using 17 dBm for safety. The measured SAR values were 0.101 W/kg and 0.1 W/kg at 1 g and 10 g, respectively. © 2024 The Authors

关键词： Microwave sensors

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An Emperical Way to Diagnose the Cancer Stages Using Algorithm in AI System 5

An Emperical Way to Diagnose the Cancer Stages Using Algorit...

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5th IEEE International Conference on computing, Power, and Communication Technologies, IC2PCT 2024

作者： Muniandi, Balakumar Yennapusa, Haritha Ramakrishnan, Rakesh Gupta, Ketan Logeshwaran, J. Lawrence Technological University Department of Electrical and Computer Engineering SouthfieldMI United States University of Central Missouri Department of Computer Science AustinTX United States University of the Cumberlands Department of Information Technology Union CityCA United States University of the Cumberlands Department of Information Technology WilliamsburgKY United States Sri Eshwar College of Engineering Department of Electronics and Communication Engineering Tamil Nadu Coimbatore India

ISBN: (纸本)9798350383522

This paper gives a unique technique for automated cancer detection the use of AI-based totally prediction algorithms. Cancer often gives as a complicated and heterogeneous set of traits, making prognosis hard. In this novel method, an AI-primarily based set of rules is used to come across most cancers from visible and scientific information. The set of rules utilizes supervised studying to categorize scientific information and photograph features, after which practice a supervised type version to be expecting the presence of most cancers. The set of rules is optimized for accuracy and can discover multiple types of cancer with excessive accuracy. The results demonstrate that this novel approach can stumble on most cancers with an accuracy of up to ninety%, making it an effective device for automatic most cancers prognosis. Additionally, the set of rules might be similarly applied to other scientific diagnosis tasks, in which AI-based totally prediction can be a treasured device. © 2024 IEEE.

关键词： Accuracy Heterogeneous Prediction Supervised learning Valuable tool

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