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8th international conference on smart and Sustainable Technologies, SpliTech 2023

作者： Fernández, Eduardo Illueca Kühne, Noel Gomariz Mulero, Nuria Bernabé Jara, Antonio J. University of Murcia Department of Informatics and Systems Spain Libelium Murcia Research and Development Department Spain

ISBN: (纸本)9789532901283

Low emissions zones (LEZs) have emerged as a key strategy in addressing urban air pollution and reducing greenhouse gas emissions. To effectively manage and enforce LEZs, optimization of mobility, intelligent transport systems, multi-modal mobility, and mobility as a service must be considered as objectives to be reached. In the same direction, public authorities have included in their strategic plans to make their city "more sustainable and smarter. In this sense, a comprehensive toot that integrates advanced technologies and data-driven approaches is essential. To overcome this limitation, Libelium proposes in this work a LEZ management software for smart decission making. It integrates various components such as real-time monitoring, data analytics, air quality modeling, and KPIs computation. Our solutions utilize a combination of sensors, cameras, and communication networks to collect real-time data on vehicle emissions, traffic patterns, and compliance levels within the designated low emissions zones. This paper shows promising results in this context validated in five European cities - Paris, Helsinki, Amsterdam, Stavanger, and Tallinn - obtaining a CO2eq emissions reduction up to 86 % in the best scenarios. In addition, the dispersion models can achieve a high resolution at a street level. For this reason, the tool for low emissions zone management presents a comprehensive and integrated approach to monitor, enforce, and evaluate LEZs effectively. The tool enables authorities to effectively combat urban air pollution and reduce emissions by leveraging real-time monitoring, data analytics, and sustainability impact assessment. Implementing such a tool has the potential to create cleaner and healthier urban environments, enhance transportation sustainability, and improve the overall quality of life for citizens. © 2023 University of Split, FESB.

关键词： data analytics

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A Semantic Analysis-Based Method for smart Contract Vulnerability 8

A Semantic Analysis-Based Method for Smart Contract Vulnerab...

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8th IEEE international conference on Big data Security on Cloud, 8th IEEE international conference on High Performance and smart computing, and 8th IEEE international conference on intelligent data and Security, BigdataSecurity/HPSC/IDS 2022

作者： Yan, Xingrun Wang, Shuo Gai, Keke Beijing Institute of Technology School of Computer Science and Technology Beijing100081 China Beijing Institute of Technology School of Cyberspace Science and Technology Beijing100081 China

ISBN: (纸本)9781665480697

smart contracts are distributed, self-executing programs on blockchain network and they have the potential to impact many industries. A large number of developers are optimistic about the development prospects of smart contracts. However, due to different levels of familiarity of developers with technology, the existence of serious vulnerabilities in code can result in huge property losses. The serious consequences of reentrancy vulnerabilities have attracted widespread attention from researchers, and researchers have proposed many approaches to detect them. Many experiments show that these approaches can only effectively detect certain types of vulnerabilities. Similar vulnerabilities still exist in some smart contracts. In this paper, we propose a semantic analysis-based detection method for reentrancy vulnerabilities. The method utilizes machine learning techniques to efficiently detect the vulnerabilities of the given code. And then, our method provides semantic analysis-based effective correction feedback of the code. Compared with the existing vulnerability detection tools Slither and Mythril, our method improves the work efficiency. Moreover, compared with the current Mythril method with the best vulnerability detection accuracy, our method improves the accuracy by 1.01%. © 2022 IEEE.

关键词： smart contract

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Advancements in smart Learning Techniques: A Comprehensive Review of Trends and Analytical Insights 6th

Advancements in Smart Learning Techniques: A Comprehensive R...

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6th international conference on smart computing and Informatics, SCI 2024

作者： Kaur, Ravinder Dogra, Ayush Department of Business Schools Chandigarh University Punjab Mohali India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India Rohin Institute MontclairNJ United States

ISBN: (纸本)9789819619801

smart learning techniques have gained significant attention in recent years due to advancements in technology and the increasing need for personalized and interactive learning experiences. These methods harness the potential of artificial intelligence, machine learning, data analytics, and augmented reality to elevate the process of learning. Major findings of this article present a thorough appraisal of the most current trends and analytical insights associated with the integration of smart learning techniques. The study casts a spotlight on several pivotal domains, encompassing personalized learning, adaptive learning, gamification, learning analytics, artificial intelligence (AI), natural language processing (NLP), augmented reality (AR), virtual reality (VR), mobile learning, social learning, and ethical considerations. The crux of personalized learning lies in its capability to tailor the learning experience in alignment with individual requisites. Meanwhile, adaptive learning takes the reins in customizing the learning journey, hinged upon learners’ advancement and proclivities. This research is completed using quantitative research methodology. Social learning thrives in a digitally connected era, fostering collaboration and shared knowledge acquisition. Amid these innovative strides, the discourse also delves into the ethical considerations intertwined with the deployment of intelligent technologies in learning contexts. In encapsulation, the paper navigates the expanse of smart learning techniques, elucidating their transformative effects, and potential for reshaping modern education review highlights key areas, such as personalized learning, adaptive learning, and gamification. It recommended the innovative learning with new learning system. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Supervised learning

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Sustainability in Development of Grant Applications 2nd

Sustainability in Development of Grant Applications

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2nd international conference on Ubiquitous computing and intelligent Information Systems (ICUIS)

作者： Encheva, Sylvia Western Norway Univ Appl Sci Inndalsveien 28Post Box 7030 N-5020 Bergen Norway

ISBN: (纸本)9789811925412;9789811925405

The aim of this work is to present a novel method for transitioning from competition to collaboration phase in the process of preparing applications for delivering an external support for research projects. Concept similarity is suggested to be employed to facilitate a search for semantic similarities among differently formulated grant applications and thereafter offer possibilities for incorporating a collaborative work to interested parties. During the entire process of similarity search and eventual suggestions for collaboration among competing teams, there will be no disclosure of proposals' contexts or ideas they are built upon. The presented approach may very and it will be used in other types of project applications cases, where both public and private organizations are involved.

关键词： Collaboration data analytics External grants

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Accelerating the Deployment of observant Energy Efficient Lighting System for smart Cities

Accelerating the Deployment of observant Energy Efficient Li...

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2022 international conference on data analytics for Business and Industry, ICDABI 2022

作者： Mishra, Vinay Kumar Singh, Mayank Tiwari, Raj Gaurang Kumar, Ajay Teerthanker Mahaveer University College of Computing Sciences and Information Technology Moradabad India Teerthanker Mahaveer University Uttar Pradesh Moradabad India Chitkara University Institute of Engineering and Technology Chitkara University Punjab India

ISBN: (纸本)9781665490580

It is no secret that street lighting costs a city a lot of money in terms of energy. An intelligent street lighting system can reduce municipal street lighting expenses by 50 percent to 70 percent. As the name implies, intelligent street lighting systems automatically modify their light output based on usage and occupancy, such as pedestrians, cyclists, cars and trucks being the primary users of the road. In order to reduce energy consumption, an intelligent street light management recommends installing a wireless-based system that can remotely track and control the real energy usage of the street lights. Using an IR transmitter and IR receiver combination, we present a technique for energy conservation. When the sensor detects movement, it sends the data to the microcontroller, which then turns the Light ON/OFF as needed. To reduce energy wasting and to save lives from accidents, this research's major goal is to prevent energy wastage. © 2022 IEEE.

关键词： Street lighting

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smart Children Management Using data analytics, Machine Learning and IoT 1st

Smart Children Management Using Data Analytics, Machine Lear...

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1st international conference on Artificial Intelligence for smart Community, AISC 2020

作者： Faruk, Md Jobair Hossain Adnan, Muhamad Hariz Muhamad College of Computing and Software Engineering Kennesaw State University Marietta United States Computing Department Faculty of Art Computing and Creative Industry Universiti Pendidikan Sultan Idris Tanjung Malim Malaysia

ISBN: (纸本)9789811621826

One of the biggest challenges faced by parents is managing the difficult or defiant behavior of children of the twenty-first century. Technology can help to provide support in managing children’s activities and helping parents to be in control. Recent advances in IoT have sparked the interest of researchers to develop a smart management system for children. This paper presents a review of the smart management of children using the internet of things (IoT), machine learning, and data analytics. The objective is to identify potential approaches regarding smart management for children based on IoT for future researchers. The reviews were conducted from secondary sources, where conference proceedings and journals have been analyzed from Scopus and other databases. The finding indicates that IoT-based smart system has robust accuracy and performance. Thus, exploiting IoT for the development of a smart management system for children will provide significant benefits to the future generation. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Internet of things

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IoT System Architecture for a smart City

IoT System Architecture for a Smart City

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Information, Control, and Communication Technologies (ICCT), international conference on

作者： Priyanka Nahar Avdhesh Ghuraiya Ilia Mikhailovich Voronkov Alexander Alexandrovich Kharlamov Department of Intelligent Information System and Technologies Moscow Institute of Physics and Technology Dolgoprudny Russia

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

Industry 5.0 has transformed manufacturing with smart factories as a key component. This report reviews the latest research on smart factories and industrial data management. Focusing on automation, AI, machine learning, big data and virtualization Technologies such as IoT and crowd sensing enable continuous data collection for real-time decision making and human-machine collaboration. We present a smart factory architecture that combines edge computing for local processing and cloud analytics with various communication technologies. To increase safety, efficiency, and connectivity in modern factories

关键词： Cloud computing Machine learning Computer architecture Real-time systems Production facilities Communications technology Fifth Industrial Revolution Virtualization smart manufacturing Edge computing

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Prediction of Diabetes at early stages using ANN & Outlier Exposure

Prediction of Diabetes at early stages using ANN & Outlier E...

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2022 international conference on Innovative computing, intelligent Communication and smart Electrical Systems, ICSES 2022

作者： Jagini, Ajay Gayatri, Nandam Nagaraju, Sangepu Rao, Vardhineni Saketh Rao, Kanjarla Sathish Sumanth, Boorla KITS Department of CSE Telangana Warangal India

ISBN: (数字)9781665474139

ISBN: (纸本)9781665474139

In the present scenario of medical field, Diabetes is a critical issue which do require a lot of attention and if predicted in early stages it can be cured easily. From past few decades many machine learning algorithms are being used for detection at early stages. In this research our principal attention is on prediction of diabetes for pregnant woman that can also be termed as Gestational Diabetes. This may also lead to affecting of Type 2 Diabetes. Several researchers worked hard to predict the results accurately. ANN has considerable edge over other classification algorithms. Machine Learning, Artificial Intelligence, data analytics, and other latest domains are being engaged in prediction of several categories of diseases in the health sector. ANNs (Artificial Neural Network) made a massive impact in medical department further egresses for various data driven applications in domain of health care. It starts with disease diagnosis, image processing of infected organs and finally predicting the disease accurately. Our primary focus is finding out the effect of parameters over dataset to forecast if a specific person is suffering from diabetes or not. PIMA dataset has been considered with 20 neurons for hidden layers and acquired accuracy of 86.2% when there are no outliers in dataset. This research depicts the accuracy &effectiveness of ANN model when compared to other classification algorithms. © 2022 IEEE.

关键词： data analytics

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A Robust Fault Detection and Location Prediction Module Using Support Vector Machine and Gaussian Process Regression for AC Microgrid

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2022年第1期58卷 930-939页

作者： Srivastava, Adhishree Parida, S. K. Birla Inst Technol Dept Elect & Elect Engn Patna 800014 Bihar India Indian Inst Technol Elect Engn Dept Patna 801106 Bihar India

Better reliability of power supply is assured with the inculcation of distributed generators (DGs) in a distribution network. smart sensors and latest grid communication protocols have played a crucial role in the development of intelligent microgrids (MGs). Conventional protection schemes do not provide reliable performance when implemented in MGs. This article proposes an approach which requires root mean square value of one cycle three -phase voltage and current measurements during fault. These data are treated as inputs for developing a fault isolation and locator module. This module is supposed to be available at central protection system, and is designed using machine learning (ML) based techniques viz. Gaussian process regression for fault location prediction and support vector machine for fault identification. Effectiveness of the proposed methodology is evaluated by considering practical grid scenarios with load variation and different DG penetration level. Furthermore, the robustness of the proposed model is assessed by performing sensitivity analysis with consideration of variation in line parameters and load as well as effect of DG correlation. A 7-bus meshed ac MG test system consisting of three DGs and two grid sources is modeled in SIMULINK platform, and is used to demonstrate the proposed module. data analytics tools of MATLAB 2020a has been explored to develop an ML-based fault isolation and location module for MGs. The proposed scheme has also been validated with real-time MG data obtained from OPAL Real time (OPAL-RT) real-time simulator OP-4510. The accuracy in predicted results proves that the proposed scheme is pertinent for real-time practical applications.

关键词： data models Support vector machines Microgrids Voltage measurement Training Fault location Circuit faults Distributed generator (DG) fault location Gaussian process regression machine learning (ML) microgrid (MG) relay support vector machine (SVM)

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Design of intelligent Pension System Based on Zigbee Technology

Design of Intelligent Pension System Based on Zigbee Technol...

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data analytics, computing and Artificial Intelligence (ICDACAI), international conference on

作者： Yajuan Cao Kai Zhang Civil Administration Professional University Beijing China Everybody Insurance Group Beijing China

ISBN: (数字)9798331519032

ISBN: (纸本)9798331519049

In the context of the rapid development of information technology and network technology, the field of smart home is gaining widespread attention and is rapidly popularized in the world. intelligent home system through the integration of computer technology, a variety of family life related intelligent equipment interlinked to form an efficient residential facilities and family affairs management system. In our country, the problem of population aging is becoming more and more serious, and the need of elderly people's home care is more and more urgent. Therefore, the development of a smart pension system based on ZigBee technology is not only a necessary measure to respond to the national healthy China strategy, but also an important means to promote the combination of smart families and home care. This system aims to improve the quality of life and happiness of the elderly, which has important theoretical and practical significance. According to the living habits and room layout of ordinary families, this paper puts forward four intelligent solutions. The system integrates a wealth of ZigBee smart devices as well as emergency keys and Kinect devices to ensure the safety of everyday life for seniors. The system treats each home as an independent user and manages smart devices within the home through user accounts. The data communication of the system strictly follows the uniform protocol rules to ensure its stability and reliability. Users can interact with the system through web pages, smart speakers and mobile terminals to realize diversified operations and enhance the smart elderly care experience. After rigorous testing, the system meets the needs of users in terms of function and performance, has high feasibility and good interactivity, can receive and display environmental data in real time, and supports voice control intelligent devices, simplifies the operation process, and significantly improves the home care experience of the elderly.

关键词： Protocols Zigbee Web pages smart homes Stability analysis Pensions Safety Older adults smart devices Testing

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