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A Cloud-Edge Server-Based Cypher Scheme for Secure data Sharing in IoT Environment

A Cloud-Edge Server-Based Cypher Scheme for Secure Data Shar...

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international conference on IoT, intelligent computing and Security, IICS 2021

作者： Kumar, Abhishek Singh, Vikram Department of Computer Science & Engineering Chaudhary Devi Lal University Haryana Sirsa India

ISBN: (纸本)9789811981357

As the technologies are growing, new challenges are emerging. The Internet is also one of these. IoT and cloud computing are considered a highly suitable combination in the field of information technology. This combination has generated the highest range of M2M and H2M interaction networks containing billions of gadgets operated remotely. Cloud computing provides computing and data storage utilities including service databases, software, networking and data analytics over the Internet to give faster deployment, economies of scale and flexible and optimal resource management. In edge computing, edge servers are placed close to the smart devices that reduce the communication overhead and security concerns. In this communication, a lightweight cryptographic approach has been proposed for searching and sharing the requested data by authorised end-users on edge server in cloud-assisted Internet of things. Results have shown a decrease in time duration for searching the data while not compromising with the security detail. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Information management

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Industrial Internet Architecture Design for intelligent Construction and Operation of Public Buildings Based on BP Algorithm

Industrial Internet Architecture Design for Intelligent Cons...

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2023 international conference on Networking, Informatics and computing, ICNETIC 2023

作者： Wen, Xiaohui Liu, Tao Qingdao University of Technology Qingdao273400 China

ISBN: (纸本)9798350313314

The feasible way to promote the transformation and upgrading of the construction industry is to vigorously develop the construction industry Internet to reduce capacity and cost. smart life has brought a lot of convenience to people, and the construction of smart city needs more and more technical and skilled management talents who master the installation, debugging, operation and maintenance of modern intelligent equipment. With the maturity and gradual application of cloud computing, Internet of Things and GIS technologies, building intelligent operation and maintenance based on data link and big data analysis will usher in huge development opportunities. The energy consumption prediction model of large public buildings is analyzed by using GA algorithm to optimize the weights and thresholds of BPNN, and the validity of the model is verified by an example. Therefore, it is a new development trend in the field of architecture to use data mining technology to mine relevant information and provide reference for the prediction of electricity consumption of large public buildings. In order to ensure the efficiency and quality of the system, more and more basic equipment and information systems of all kinds of production and operation need to be strengthened daily. Therefore, more and more operation and maintenance management software and platform construction are emerging in the market. © 2023 IEEE.

关键词： Construction industry

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Application of Big data in intelligent Government Affairs Management: An Example in Natural Resources Management 7

Application of Big Data in Intelligent Government Affairs Ma...

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7th international conference on Big data analytics, ICBDA 2022

作者： Meng, Fanrong Yao, Min Kong, Dengkui Wang, Xuefei Fan, Yanping Meng, Fanjun Information Center of Ministry of Natural Resources Beijing China Academy of the National Territorial Planning Heilongjiang China

ISBN: (纸本)9781665479387

China's government affairs service has been rapidly evolving from the stage of data-guided to data-driven in recent years. The effective utilization of big data is a critical step toward developing a smart government affairs management system. Using natural resources big data as an example, this paper discusses the data architecture, spatial data analysis techniques and their applicability to intelligent land management system on a broad scale, as well as several technical challenges that must be addressed, such as integrated computing of multi-source distributed data, the lack of intelligence in the present government affairs management system, and the need for real-Time collaboration between multi-level databases. This paper intends to broaden researchers' understanding of big data technology and application in the field of natural resources, and it serves as a reference point for big data in the pursuit of intelligent government affairs management. © 2022 IEEE.

关键词： Big data

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DEVELOPING USER- AND TECHNOLOGY-DRIVEN USE CASES FOR smart CITY APPLICATIONS 16

DEVELOPING USER- AND TECHNOLOGY-DRIVEN USE CASES FOR SMART C...

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16th international conference on Computer Graphics, Visualization, Computer Vision and Image Processing, CGVCVIP 2022, 8th international conference on Connected smart Cities, CSC 2022, 7th international conference on Big data analytics, data Mining and Computational Intelligence, BigDaCI 2022, and 11th international conference on Theory and Practice in Modern computing, TPMC 2022 - Held at the 16th Multi conference on Computer Science and Information Systems, MCCSIS 2022

作者： Otto, Robert Guedey, Myriam Uckelmann, Dieter University of Applied Sciences Stuttgart Schellingstraße 24 Stuttgart70174 Germany

ISBN: (纸本)9789898704429

Within the transformation and digitalization in the area of smart public buildings and infrastructures, finding, selecting and implementing the "right" use cases is an actual challenge for cities, public utilities, and other stakeholders. The question is where to start, what knowledge and capacities are available and what should be prioritized. This paper introduces a first concept for a methodology that supports the co-development of use cases with respect to current activities, existing infrastructures, and know-how on behalf of the public partners. As a preliminary result, three use cases were identified that represent the current priorities of the involved partner smart cities. © MCCSIS *** rights reserved.

关键词： Internet of things

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Internet of Energy (IoE): A Comprehensive Review of Design, Principles, and Architectural Frameworks 15th

Internet of Energy (IoE): A Comprehensive Review of Design, ...

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15th international conference on e Infrastructure and e Services for Developing Countries

作者： Abdalla, Rania Salih Ali, Elmustafa Sayed Mahbub, Sara A. Mokhtar, Rania A. Ahmed, Zeinab E. Taif Univ Dept Comp Engn Al Taif Saudi Arabia Red Sea Univ Dept Elect & Elect Engn Port Sudan Sudan Sudan Univ Sci & Technol Dept Elect Engn Khartoum Sudan Int Islamic Univ Malaysia Dept Elect & Comp Engn Kuala Lumpur Malaysia Univ Gezira Dept Comp Engn Wad Madani Sudan

ISBN: (纸本)9783031815690;9783031815706

Design of energy resources, transmission, distribution, and consumption in network architecture is becoming a challenging energy optimization issue. The demand for power analysis becomes a key pillar in sustainable renewable energy and adaptation to climate change. State-of-the-art technologies can play a vital role in realizing the new architectural design for smart grids and cities. The 4th generation mobile network is considered a critical technology and enabler. The 3GPP standard body is set to a target of 35% of the deployment of the 4G to be Low Power Wide Area (LPWA) network by 2020. LPWA is an Internet of Energy (IoE) structure that can provide a comprehensive stream of energy sector applications. The IoE with intelligent computing tools can dramatically enhance energy efficiency, improve and sustain renewable energy, and diminish energy contamination's ecological effects. This paper reviews the literature on the IoE design principles and architecture models comprehensively. it also explains IoE enabling technologies, including fog computing and various interoperability and data analysis standards.

关键词： Communications and measurement technology smart energy systems smart grid IoE Computational Tools IoE Design IoE Interoperability IoE Standards IoE Cyber Security

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Predicting the stock market index using GRU for the year 2020 4

Predicting the stock market index using GRU for the year 202...

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4th international conference on Emerging Systems and intelligent computing, ESIC 2024

作者： Narayana, S. Sri, Siddabathula Naga Divya Kumar, Seelam Rohith Ajay, Tappiti Vasiq, Shaik Sapa Sr Gudlavalleru Engineering College Dept. of Cse Andhra Pradesh Gudlavalleru521356 India

ISBN: (纸本)9798350349856

Predicting the behavior of the stock exchange is crucial, since it ranks as one of the foremost frequently studied fields nowadays. It is challenging to forecast the financial sector that requires a careful analysis of historical trends. The precision of conventional methods for predicting changes in stock prices was insufficient. In order to anticipate the values of stocks, deep learning becomes particularly popular technique. Deep Learning is a particularly popular method for anticipating stock prices because of the efficiency in patterns that are not linear. Recurrent neural networks were used to increase prediction accuracy since share price movements are dependent on sequence of time. Within Recurrent Neural Networks (RNNs), their pivotal strength lies in their adeptness at managing sequential data and grasping offered a distinct challenge as well as a chance to investigate sophisticated forecasting algorithms. Nonlinear stock price movements cannot be accurately predicted by traditional data analytics approaches. Owing to its effectiveness in capturing intricate, nonlinear patterns within time-series data, deep learning stands out as the predominant method employed for predicting stock prices. A 25% drop in global stock prices and a 30% reduction in G20 countries market prices were recorded in March 2020. Many businesses experience significant losses, and it may be very challenging for them to recover. While many stockholders suffered losses, several businesses managed to continue making money throughout this period. whether the Gated Recurrent Unit (GRU) model, exhibits superior predictive capabilities for significant fluctuations in stock prices during the year 2020 compared to the LSTM model. This research involves a comparative analysis between GRU and LSTM using diverse stock indices, with historical data sourced from the Yahoo Finance API. Notably, the Mean Absolute Percentage Error (MAPE) values demonstrate that GRU outperforms LSTM in forecasting accur

关键词： Forecasting

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CITIZEN SCIENCE PLATFORM FOR RADON POTENTIAL ASSESSMENT AND RADON RISK AWARENESS 16

CITIZEN SCIENCE PLATFORM FOR RADON POTENTIAL ASSESSMENT AND ...

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16th international conference on ICT, Society and Human Beings, ICT 2023, the 15th international conference on e-Health, EH 2023, the 9th international conference on Connected smart Cities, CSC 2023 and 8th international conference on Big data analytics, data Mining and Computational Intelligence, BigDaCI 2023

作者： Meneses, Paulo Lopes, Nuno Leite, Patrícia Teixeira, Paulo Silva, Joaquim P. School of Technology IPCA Barcelos Portugal LASI - Associate Laboratory of Intelligent Systems Guimarães Portugal

ISBN: (纸本)9789898704504

The WHO estimates that cancers caused by radon gas may account for 14% of all lung cancers. The concentration of indoor radon gas is a well-known public health threat and has been the subject of many scientific studies. The WHO has issued recommendations to encourage countries to act against radon exposure to reduce the associated cancer risks. However, despite the vast knowledge on this subject, the measures already taken and the information available, much of the population at risk remains unaware of what radon gas is and its impact on health. In this context, an approach has been designed to perform the pre-diagnosis of indoor radon potential based on the geographical location of the building, its construction characteristics, and its use profile. Recently, a model has been built that performs automatic classification of radon potential in indoor environments. This paper describes the development of a web platform integrating this model to enable citizens to obtain an assessment of the radon potential of the buildings where they work or live. The platform aims to promote radon measurements by the general population and raise awareness about radon risk. These measurements will generate new data that will be used to build more robust classification models. © ICT *** rights reserved.

关键词： Radon

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smart IoT-Integrated Weather analytics System

Smart IoT-Integrated Weather Analytics System

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international conference on Green Energy, computing and intelligent Technology 2024, GEn-CITy 2024

作者： Xun, Lim Shi Merugu, Suresh Maheshwari, Himani Department of Computer Science School of Computer Science University of Southampton Malaysia Johor Iskandar Puteri79100 Malaysia School of Computing Graphic Era Hill University Dehradun India

ISBN: (纸本)9781837242689

This paper proposes an IoT-based weather monitoring system utilizing Raspberry Pi 4 Model B as the core component to collect extensive weather data, including ambient temperature, humidity, atmospheric pressure, altitude, rainwater, ultraviolet rays, and ambient light intensity, utilizing appropriate sensors. A contemporary, user-friendly website serves as the interface, offering functionalities such as real-time data visualization and email notifications. The paper begins with an overview of the IoT and weather monitoring domains to underscore their importance and the necessity for advancements in these fields. A comprehensive literature review is conducted to identify trends, achievements, and existing gaps in previous IoT-based weather monitoring research. Following this, a detailed design strategy is outlined, covering all development phases from initial planning to final execution. This design framework is applied during the implementation phase, where the system's development and testing processes are meticulously recorded and analyzed. The results section provides an in-depth analysis of the collected data and evaluates the system's performance, demonstrating its effectiveness and reliability. The paper concludes with a summary of key findings, discussing the contributions to the field, identifying limitations, and proposing recommendations for future improvements and extensions to enhance the system's capabilities, thus addressing the gaps identified in the literature review. © The Institution of Engineering & Technology 2024.

关键词： Atmospheric humidity

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Double-Edged Agriculture 4.0: Hodiernal Expedient Technologies and Cyber-Security Challenges 6

Double-Edged Agriculture 4.0: Hodiernal Expedient Technologi...

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6th international conference on Contemporary computing and Informatics, IC3I 2023

作者： Arya, Swati Tripathi, Shubham Srivastava, Archana Aggarwal, Shruti Soni, Nupur Ansar, Syed Anas School of Computer Application Babu Banarasi das University Lucknow India Thapar Institute of Engineering and Technology Punjab India

ISBN: (纸本)9798350304480

Digitalization and intelligent systems have engulfed all dimensions and vicinity of existence. The intense fusion of hodiernal information technology and archaic agriculture has ushered in the epoch of agriculture 4.0, invariably reputed as smart agriculture. Variegated operational or forthcoming technologies reckon in agriculture 4.0, e.g., algae feedstock, automation, hydroponics, nanotechnology, genome editing, cognitive computing, blockchain, and machine learning, may have far-reaching implications for future agriculture and food systems and radical rudimentary potential. Although the profusion benefits of this Fourth Revolution abound, many unresolved issues and stumbling blocks must be conquered to make this paradigm shift feasible. Future solutions will coerce data availability and accuracy as vital factors to assist farmers, also security will become indispensable for constructing vigorous and efficacious systems. Security deals with difficulties like compatibility, scarce funds, and gargantuan data as smart agriculture incorporate a huge gamut and volume of resources. In this frame of reference, the authors opine that the inclusion and exclusion impact of Agriculture 4.0 technologies require ancillary scrutiny. This paper articulates the core technologies of agriculture 4.0 with an explicit focus on its applications in veritable contexts whilst delving into security issues (chiefly cyber-security). This research is envisaged to have a pragmatic influence on agriculture 4.0, emphasizing paradigms and security measures to aid farm stakeholders to navigate the firm's transition to digitization. © 2023 IEEE.

关键词： Agriculture 4.0 Cloud computing Cyber Security data analytics Internet of Things Sensor

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The smart Analysis of Performing Scalable Inference for Big data analytics

The Smart Analysis of Performing Scalable Inference for Big ...

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2023 international conference on Power Energy, Environment and intelligent Control, PEEIC 2023

作者： Bhandarkar, Vishakha D. Rongali, Aruna Sri Shamout, Mohamed Dawood Pund, Sachin Nama, Gigih Forda Patil, Shrishailappa Yeshwantrao Chavan College of Engineering Applied Mathematics and Humanities India University of the Cumberlands Graduate Doctoral Information Technology Information Technology Emphasis/Information Technology United States College of Business Administration University of Sharjah Department of Management Sharjah United Arab Emirates Shri Ramdeobaba College of Engineering and Management Department of Industrial Engineering Maharashtra Nagpur India Doctoral Program of Environtmental Science University of Lampung Department of Informatics Bandar Lampung Indonesia Vishwakarma Institute of Technology Computer Engineering Pune India

ISBN: (纸本)9798350357769

This paper examines the reproducibility of massive information analytics under particular factors. The paper proposes the 'performing Scalable Inference' technique to cope with scalability troubles and to exploit current big statistics platforms for efficient computing and statistics garage of the statistics. In particular, the paper describes how to perform leak-free, parallelizable visible analytics over massive datasets using present extensive records analytics frameworks such as Apache Flink. This method presents an automated manner to execute analytics that preserves reproducibility and the ability to make adjustments without re-running the entire technique. The paper also demonstrates how these analytics may help several real-world use instances, explore affected person cohorts for studies, and develop stratified patient cohorts for hospital therapy. In the end, the paper observes how the proposed method may be exercised within the real world. Actively scalable inference for massive information analytics is pivotal in optimizing decision-making and allocation of assets. Typically, such inferences are made based on information accumulated from numerous sources, databases, unstructured data, and different digital sources. So one can ensure scalability, a complete cloud-primarily based platform has to be hired. This solution will permit the ***, deploying the essential records series and evaluation algorithms are prime here. It could permit the platform to recognize the styles inside the statistics and discover any ability correlations or traits. Additionally, predictive analytics and system mastering strategies may be incorporated to provide insights into the results of the information. In the long run, by leveraging those techniques, the platform can draw efficient inferences and appropriately compare situations in an agile and green way.. © 2023 IEEE.

关键词： adjustments an a lytics automated preserves statistics

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