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Framework for the Deployment of intelligent smart Cities (ISC) using Artificial Intelligence and Software Networking Technologies

Framework for the Deployment of Intelligent Smart Cities (IS...

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Advance computing and Innovative Technologies in Engineering (ICACITE), international conference on

作者： Nachaat Mohamed Ramakant Upadhyay Geethamanikanta Jakka P V Rambabu Badria Sulaiman Alfurhood Devesh Pratap Singh Rabdan Academy UAE Homeland Security Universiti Sains Malaysia Abu Dhabi UAE Department of CSE Sanskriti University Mathura Uttar Pradesh India Data Analytics Information Technology University of the Cumberlands USA Civil Engineering Department of Computer Sciences College of Computer and Information Sciences Princess Nourah Bint Abdulrahman University Saudi Arabia

This article’s goals include providing a framework for interpersonal and communication to safeguard welfare services and assess how well the innovation ecosystem is now understood. An essay starts with an overview or description of "urban area" This viewpoint includes neighborhood services, modern amenities, or smart infrastructure. Information and technology, digital operations use, monitoring, and interconnection, amongst other things. The section that follows examines various urban planning concerns, either administration or expansion. Utilizing diverse technologies effectively is made possible by innovative information about towns or an answer to a question concerning high-quality public infrastructure. An innovative method of managing networks is the Software Defined Network (SDN) architecture. Unlike switches in a conventional network computing environment, changes in SDN do not process inbound sachets in the similar means. If no inbound packets are identified after searching the linking tables, they are passed to the control system, the SDN’s operating system, for processing. A Spread Denial of Service (DoS) outbreak poses the biggest risk to the cyber security of an SDN *** system or application layers of the disease-ridden devices connected to the system will be the target of the attack. The approach for determining whether incoming packets are contaminated or not is clever machine learning-based, and it is proposed in this paper. In the context of smart cities, the deployment of artificial intelligence (AI) has newly drawn more and more attention. The purpose of this study is to perform a works assessment to examine the role of AI in the various parts of smart towns given the relevance of the topic. This study’s technique combines a thorough literature evaluation to find the most pertinent papers with reference system investigation to reveal the subtleties of the subject. The findings of this study highlight the significance of this technology, whi

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Towards Privacy-Preserving Deep Learning: Opportunities and Challenges

Towards Privacy-Preserving Deep Learning: Opportunities and ...

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international conference on data Science and Advanced analytics (DSAA)

作者： Sheraz Ali Muhammad Maaz Irfan Abubakar Bomai Chuan Zhao School of Information Science and Engineering University of Jinan Jinan China Shandong Provincial Key Laboratory of Network-based Intelligent Computing University of Jinan Jinan China Shandong Provincial Key Laboratory of Software Engineering Jinan China

ISBN: (数字)9781728182063

ISBN: (纸本)9781728182070

During the past decade, deep learning has achieved excellent results in many classic machine learning problems, such as face recognition, spam detection, and financial prediction, etc. The success of deep learning mainly benefits from training on a large amount of data gathered from different sources. However, the training data may include highly sensitive information that may lead to serious threats to personal privacy. In this paper, we review privacy threats in deep learning and present effective privacy-preserving techniques in the literature against these threats. We give a detailed comparison of different techniques and summarize the performance of the existing solutions. Furthermore, we discuss some open problems and challenges in this research area. In the end, we conclude this paper and point out possible research directions.

关键词： Deep learning data models data privacy Privacy Training Neural networks Training data

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Dynamic vulnerability detection approaches and tools: State of the Art

Dynamic vulnerability detection approaches and tools: State ...

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international conference on intelligent computing in data Sciences (ICDS)

作者： Oualid Zaazaa Hanan El Bakkali Smart Systems Laboratory Rabat-IT Center ENSIAS Mohammed V University Rabat Morocco

ISBN: (数字)9781728180847

ISBN: (纸本)9781728180854

Vulnerabilities are everywhere around us. Every device we use in our daily life include a software that may contain vulnerabilities. The growth use of software and devices to automate some of our daily life actions is making these programs more complex and more connected to the internet, which increase the risk of cyber-attacks. To reduce this risk, multiple programming companies are trying to use different approaches to find these vulnerabilities. Some are using static approaches during the software development life cycle while others are using dynamic analysis approaches to find vulnerabilities once the application is correctly working. Unfortunately, both approaches still suffer from multiple limitation and still need improvement. In this paper, we are discussing some of the most recent dynamic approaches and the efficient of the tools that use them.

关键词： Fuzzing Tools Performance analysis Grammar Servers Lakes Engines

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TL-AGRO: Transfer Learning-based Perilous Insect Detection Framework for smart Agriculture Underlying Edge computing

TL-AGRO: Transfer Learning-based Perilous Insect Detection F...

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intelligent Technologies (CONIT), international conference on

作者： Fenil Ramoliya Krisha Darji Riya Kakkar Rajesh Gupta Sudeep Tanwar Smita Agrawal Department of Comp. Sci. & Engg Institute of Technology Nirma University Ahmedabad India

ISBN: (数字)9798350349900

ISBN: (纸本)9798350349917

Remote sensing (RS) technology has revolutionized agriculture by harnessing advanced satellites with exceptional temporal and spatial resolution capabilities. These satellites capture Earth’s emitted energy and employ specialized sensors for data collection. Pre-processing techniques refine this data, which is seamlessly integrated into the Edge Device TL-AGRO AI system, transforming precision agriculture. Simultaneously, Unmanned Aerial Vehicles (UAVs) have become vital tools, capturing high-resolution data for plant ecology and Perilous farm insect detection. Our proposed framework TL-AGRO is an advanced agricultural analytics method that leverages meticulously preprocessed data to make precise predictions. It detects insects on agricultural properties and provides accurate classification using CNN Architectures, such as Visual Geometry Group 16 (VGG16), Xception Version 2 (XceptionV2), Residual Network 50 Version 2 (ResNet50V2), and Mobile Network Version 2 (MobileNetV2). Integration of coordinated alert system offers timely recommendations and warnings, empowering farmers to make informed decisions and mitigate insect-related risks. TL-AGRO can even identify individual insect infestations and recommend suitable pesticides, revolutionizing farming with an integrated framework that enhances productivity and sustainability. Performance evaluation of TL-AGRO includes various metrics such as accuracy and loss curves, confusion matrix, F1-score, recall and precision, demonstrating its effectiveness in advancing smart agriculture and ecological studies.

关键词： smart agriculture Visualization Accuracy Satellites Insects Transfer learning Computer architecture

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Towards Energy Efficiency in Microgrids for smart Sustainable Cities 2nd

Towards Energy Efficiency in Microgrids for Smart Sustaina...

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2nd international conference on Sustainable smart Cities and Territories, SSCT 2023

作者： Isanbaev, V. Baños, R. Gil, C. Gil, M.M. Martínez, F. Alcayde, A. Department Engineering University of Almería Carretera de Sacramento s/n La Cañada de San Urbano Almeía04120 Spain Department Informatics University of Almería Carretera de Sacramento s/n La Cañada de San Urbano Almeía04120 Spain

ISBN: (纸本)9783031369568

Microgrids are a critical component of smart and sustainable cities as they provide localized power generation and distribution that can be optimized for efficiency, cost, and environmental impact. Further, many microgrids are characterized for the presence of smart homes, which are an integral part of smart cities as they play a crucial role in improving the overall efficiency and sustainability of urban areas. One of the primary benefits of smart homes is the ability to reduce energy consumption and carbon emissions, for example, by automatically adjusting the temperature, lighting, and other settings to optimize energy usage based on the users’ needs and preferences. However, the efficient management of smart homes located in microgrids is still an open question. In particular, the efficient management of microgrids including smart homes requires measuring and processing a large amount of electrical data related to the energy generated by the power sources of the microgrid, the energy consumed by the loads (home appliances), the level of battery storage and the amount of transferred power flow between the microgrid and the main grid. This paper reflects on how to measure electrical variables at different points of the microgrids using low-cost smart meters with IoT capabilities and how to apply Non-Intrusive Load Monitoring (NILM) methods for energy efficiency purposes. The empirical study involving a real microgrid including a hybrid wind-solar generation system and a set of home appliances show that it is possible to collect data of different parts of the microgrid for efficient management purposes. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： smart meters

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A Free Placement Approach to Upper-Limb Tracking Using Inertial Sensors

A Free Placement Approach to Upper-Limb Tracking Using Inert...

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IEEE international conference on Green computing and Communications

作者： Xueyan Wu Qi Liu Mingxu Sun Xuqun Pei Haiping Mu Bin Ning Jingsu Coborive Innovion Cener of Aosheric Environen nd Equien Technoogy (CICAEET) Nnjing Universiy of Inforion Science TechnoogyShndong Beiing Medic Technoogy Co. Ld.Schoo of Eecric Engineering Universiy of Jinnde. Rehbiiion Jinn Cenr HosiThe Peoe's Hosi of Huiyinde. Sin surgery Jinn Cenr Hosi

ISBN: (数字)9781728176475

ISBN: (纸本)9781728176482

Currently, functional electrical stimulation is used as the most widely used rehabilitation therapy in intelligent medical treatment of stroke patients' limb rehabilitation. There are three methods for tracking optimization of FES rehabilitation therapy using MEMS inertial measurement units: based on Kalman filter algorithm, using quaternion fusion algorithm and establishing sensor information fusion algorithm, but there are existing, calibration needs to be performed in the early stage, inertial measurement unit Must be placed parallel to the arm, noise is prone to data drift and other issues. To solve the problem of the previous calibration of the sensor and the need to place the sensor according to the reference, and to improve the accuracy of the data, we propose a motion tracking model based on free placement to track the upper limb movement trajectory. The input data of the model is the sensor's triaxial acceleration data. The output data is angle change data, which avoids the process of pre-calibration and improves the accuracy of the data through the angle segmentation model. Four sets of comparative experiments show that this method effectively reduces the influence of the sensor position on the data, improves the data accuracy, and has higher accuracy and use value.

关键词： Task analysis Muscles Medical treatment Acceleration data models Robot sensing systems Iron data models Manipulator sensing systems task analysis MEDICAL TREATMENT data Accuracy acceleration inertia sensor muscles Sensors rehabilitation therapy Medicine Iron Measurement units sensor placement INERTIAL MEASUREMENT UNITS

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Efficient Network Administration for smart Grid data Center

Efficient Network Administration for Smart Grid Data Center

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international conference on Advanced Communication Technology (ICACT)

作者： Seonyong Jeong Seungwon Shin Graduate School of Information Security KAIST Daejeon South Korea School of Electrical Engineering KAIST Daejeon South Korea

ISBN: (数字)9791188428045

ISBN: (纸本)9781728149431

Nowadays, the smart grid systems, which are intelligent electrical grid systems, are being installed in the real world. According to the statistics, about 79 million Advanced Metering Infrastructure is deployed in the United States and these devices generate terabytes to petabyte levels of electricity data. As IT technology developed, the energy provider can get beneficial information by processing the data in the way such as Machine Learning or Deep Learning. So smart grid administrator utilizes a data center to store the energy data and to process them. The amount of power data is increasing rapidly and the type of power data becoming more and more diverse. In addition, as computing power improves, a lot of advantageous applications such as blackout prediction is developed. In the smart grid, the importance of the data center becomes higher and higher. However, the traditional data center is designed in strict. Because the traditional data centers are designed by vendors, the operations of each component of centers are ineffective on the smart grid system. So in this paper, we applied the Software-Defined data Center, which controls the data center in a virtualized and programmable manner, to operate the data in a more flexible and interoperable way.

关键词： data centers smart grids Access control Feature extraction Quality of service Software

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An intelligent Dimming Algorithm of Streetlight Based on Fuzzy Neural Network

An Intelligent Dimming Algorithm of Streetlight Based on Fuz...

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international Wireless Communications and Mobile computing conference, IWCMC

作者： Yunpeng Xue Yan Zhang Peng Shuxue School of Electronics Information Engineering Beihang University Beijing China

ISBN: (数字)9781728131290

ISBN: (纸本)9781728131306

In recent years, the IoT(Internet of things) industry has developed rapidly. As an important part of the IoT, smart streetlights have been widely used in cities around the world. More and more smart streetlights are being deployed with NB-IoT(Narrow Band Internet of Things) or Lora, which bring great convenience to streetlights management. The existing system is limited to reporting sensor data and error information of streetlight, but still adopts the traditional methods in brightness control, such as all- brightness or half-brightness in midnight, which has some shortcomings such as insufficient data utilization and less intelligent dimming algorithm, resulting in the street lamp failing to achieve the expected energy-saving effect. In this paper, an intelligent dimming algorithm of streetlight based on fuzzy neural network is designed. Combining advantages of fuzzy control and neural network, the algorithm can analyze the road information uploaded by the sensing layer and output the dimming signal. The simulation results show that, compared with the traditional method, the algorithm is more energy efficient and more consistent with human eye habits.

关键词： Brightness Roads Training Fuzzy neural networks Neural networks Lighting Industries

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A New Approach to Information Literacy in Higher Education in smart Learning Environment

A New Approach to Information Literacy in Higher Education i...

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international conference on Inventive Research in computing Applications (ICIRCA)

作者： B.Anjanee Kumar Rohit Kar K. K. Sunalini Kaneenika Jain Nitin Girdharwal Mohd Asif Shah Department of Electronics and Communication Engineering Dadi Institute of Engineering and Technology Anakapalle Andhra Pradesh India Department of Management St. Claret College Bangalore Karnataka India Department of English Koneru Lakshmaiah Education Foundation Guntur Andhrapradesh India S. S. Jain Subodh Management Institute Jaipur Rajasthan India Faculty of Management Prestige Institute of Management & Research (PIMR) Indore Madhya Pradesh India University School of Business Chandigarh University Gharuan Mohali Punjab India

In light of the current epidemic, it is crucial that children acquire better literary skills. That blended learning is considered as one of the most cutting-edge pedagogical strategies. The goal of blended learning is to develop a new learning environment that combines traditional learning with modern methods like e-learning, analytics, game-based learning, and open educational materials in order to improve learning effectiveness and enrich the learning experience. Meanwhile, the idea of smart learning environment has developed with a number of successful implementations as a significant and usable product of smart environments research. This research aims to show that the notion of mixed learning offers a positive outlook for the incorporation of emotional learning methodologies into the increasingly prevalent smart learning environments. Here, the first smart learning environment-based paradigm for enhancing students' information literacy. The outline the components of the intelligent learning environment for the development of students' information literacy based on reviews of the relevant literature and results from prior studies. Researchers found that blended learning increased students' engagement throughout the learning process, which led to better grades and deeper understanding. In addition, this approach could address the drawbacks of both online and in-person instruction, realize big data recording and representation of pedagogical, instructional, and curricular behavior, fully exploit instructors' potential in their various roles, and accurately reflect students' actual knowledge gain.

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Detecting SQL Injection Attacks in Cloud SaaS using Machine Learning

Detecting SQL Injection Attacks in Cloud SaaS using Machine ...

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IEEE international conference on Big data Security on Cloud (BigdataSecurity), High Performance and smart computing (HPSC) and intelligent data and Security (IDS)

作者： Dharitri Tripathy Rudrarajsinh Gohil Talal Halabi Applied Computer Science University Of Winnipeg Manitoba Canada

ISBN: (数字)9781728168739

ISBN: (纸本)9781728168746

Software as a Service (SaaS) has been adopted in a fast pace for applications and services to run on software cloud platform. However, the success of SaaS in cloud computing cannot obscure the security challenges faced by the web applications deployed on cloud SaaS. Like other web-based systems, cloud applications are prone to most of the common web attacks. The SQL injection attack is one of the most potential threat to a SaaS application. This may result in loss of sensitive and important data (e.g., financial, personal). Through this kind of attacks, the attacker can steal critical and confidential information to a business or an organization leading to high impact on tangible (e.g., data) and intangible (e.g., reputation) assets. The purpose of this research is to investigate the potential of using machine learning techniques for SQL injection detection on the application level. The algorithms to be tested are classifiers trained on different malicious and benign payloads. They take a payload as input and decide whether the input contains a malicious code or not. The results show that these algorithms can distinguish normal payloads from malicious payloads with a detection rate higher than 98%. The paper also compares the performance of different machine learning models in detecting SQL injection attacks.

关键词： SQL injection Cloud SaaS Cloud Security Machine Learning Deep Learning Tensortlow. Cloud computing Software as a service BUNDESAMT FUER STRAHLENSCHUTZ Machine Learning Artificial Intelligence Payload SQL Clouds Spyware Confidential Information application layer

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