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Real-time camera analytics for enhancing traffic intersection safety 22

Real-time camera analytics for enhancing traffic intersectio...

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20th ACM international conference on Mobile Systems, Applications and Services, MobiSys 2022

作者： Ghasemi, Mahshid Kleisarchaki, Sofia Calmant, Thomas Gürgen, Levent Ghaderi, Javad Kostic, Zoran Zussman, Gil Columbia University Electrical Engineering United States Kentyou Grenoble France

ISBN: (纸本)9781450391856

Crowded metropolises present unique challenges to the potential deployment of autonomous vehicles. Safety of pedestrians cannot be compromised and personal privacy must be preserved. smart city intersections will be at the core of Artificial Intelligence (AI)-powered citizen-friendly traffic management systems for such metropolises. Hence, the main objective of this work is to develop an experimentation framework for designing applications in support of secure and efficient traffic intersections in urban areas. We integrated a camera and a programmable edge computing node, deployed within the COSMOS testbed in New York City, with an Eclipse sensiNact data platform provided by Kentyou. We use this pipeline to collect and analyze video streams in real-time to support smart city applications. In this demo, we present a video analytics pipeline that analyzes the video stream from a COSMOS' street-level camera to extract traffic/crowd-related information and sends it to a dedicated dashboard for real-time visualization and further assessment. This is done without sending the raw video, in order to avoid violating pedestrians' privacy. © 2022 Owner/Author.

关键词： Object detection

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Research on intelligent Teaching Spatial Model Based on Cloud-side data Co-operation 5

Research on Intelligent Teaching Spatial Model Based on Clou...

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5th Annual international conference on data Science and Business analytics, ICDSBA 2021

作者： Sun, Yanbo Chongqing Police College Chongqing China

ISBN: (纸本)9781665445900

In the era of big data, the construction of intelligent teaching space model based on cloud edge data collaboration is the focus of current education innovation exploration. On the basis of understanding the construction model and based on the secure storage system of cloud edge data collaboration, this paper deeply discusses how to realize the technology and finally obtain the results. © 2021 IEEE.

关键词： Digital storage

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Design and Implementation of Adaptive Scheduling Management for User-Mode Thread Pool

Design and Implementation of Adaptive Scheduling Management ...

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2022 international conference on Computer Graphics, Artificial Intelligence, and data Processing, ICCAID 2022

作者： Cai, Bin Qiu, Bingcheng Yao, Jian Xiao, Xiaohong Liu, Lei Xie, Jiangang Zhang, Xu Wu, Ruilong Guangdong Guangzhou China Wuhan University Hubei Wuhan China Blue Dot Power Data Technology Co. Ltd. Beijing China China Hi-Tech Group Co. Ltd. Guangdong Guangzhou China

ISBN: (纸本)9781510663350

Progress in network and storage technology enables data center services to provide high-concurrency and low-latency processing responses. The user-mode thread pool is one of the technologies that can be used to improve the overall concurrent responsiveness of the service system while ensuring its stability of the system. In the system of multicore processor architecture, the scheduling management of the user-mode thread pool is much more complicated than that of the thread pool. First, the existing method cannot fully utilize the advantage of parallel execution of multicore processor architecture, and it is difficult to implement unified resource provisioning management among multiple user-mode thread pools. Second, the existing user-mode thread scheduling method cannot distinguish the performance requirements of different data processing tasks but treat all user-mode thread tasks in the same way. Last, the existing user-mode thread scheduling method controls the execution of all kernel threads, which is difficult to isolate host threads and other kernel threads in the system. It fails to reflect the performance requirements of different user-mode thread tasks, or to provide finer-grained execution timing control of the user-mode thread. This paper provides a two-level scheduling management method for user-mode thread pool, which can effectively integrate OS scheduling mechanism and user-mode thread scheduling mechanism, with a view to distinguishing the needs of different data processing tasks, enabling more targeted and fine-grained scheduling and execution control of user-mode threads, achieving isolation of host threads from non-host threads and differentiated scheduling control without affecting the scheduling mechanism of the OS itself, and enabling the global unified resource provisioning management of multi-user thread pools for multicore processor architecture. Generally, the new method can greatly improve the efficiency and performance of user thread pools

关键词： Network architecture

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Application of internet of things in the construction of smart city

Application of internet of things in the construction of sma...

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international conference on Application of intelligent Systems in Multi-modal Information analytics, MMIA 2020

作者： Guo, Ge Pang, Liang School of Management Wuhan Donghu University Wuhan China School of Economics and Management Hubei University of Science and Technology Xianning China

ISBN: (纸本)9783030515553

Advances in science and technology have promoted the development of traditional cities to smart cities. In the process of urban development, there will inevitably be some problems, such as information security, traffic congestion, single education mode, unreasonable use of medical resources, etc., which all need the support of Internet core technology to reduce the occurrence rate of these problems. The Internet of things technology is through data collection, comparison and analysis, it improves the speed of information processing, shares urban dynamic data, provides more efficient, diverse and flexible urban services, and realizes the most basic goal of smart city construction. Starting from the background of the development of smart city, this paper analyzes the factors influencing the development of smart city and the application of relevant models by scholars at home and abroad, finds out the problems existing in the development process of smart city, puts forward corresponding solutions, and discusses the application strategies of Internet of things technology in the construction of smart city, I hope this research can contribute to he development and construction of smart cities. © Springer Nature Switzerland AG 2021.

关键词： Internet of things

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Design and Implementation of a smart DC Microgrid System for Renewable Energy Integration using IoT and Real-Time data analytics

Design and Implementation of a Smart DC Microgrid System for...

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Self Sustainable Artificial Intelligence Systems (ICSSAS), international conference on

作者： Sakib Hossain Saiful Islam Tuhin Md Al Araf Md. Sahadat Hossain Sani Md. Arif Hasan Masum Md. Sabbir Hasan Sohag Dept. of Electrical and Electronic Engineering (EEE) Bangladesh University of Business and Technology (BUBT) Dhaka Bangladesh

ISBN: (数字)9798350368413

ISBN: (纸本)9798350368420

This research discusses about the design and execution of a direct current (DC) microgrid system that leverages Internet of Things (IoT) technology. The microgrid combines various green energy sources, including solar panels, a wind turbine, and a DC generator, along with a battery storage unit. A microcontroller serves as the core control unit, controlling and regulating power flow. The system gives real-time data collection for performance study through IoT integration. The collected data reveals the effectiveness of the DC microgrid system, with solar energy presenting as the most reliable renewable source. The application of IoT-based control indicates the promise for intelligent and sustainable energy management. This study paves the way for advancements in microgrid technology, merging artificial intelligence, wireless energy harvesting for improved performance and peer-to-peer energy sharing.

关键词： Wireless communication Decentralized control Microgrids Solar energy Real-time systems Wind turbines Peer-to-peer computing Internet of Things Energy harvesting Artificial intelligence

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data Management Platform for smart Orchestration of Decentralized and Heterogeneous Vehicular Edge Networks 22

Data Management Platform for Smart Orchestration of Decentra...

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2nd ACM conference on Information Technology for Social Good, GoodIT 2022

作者： Ayaz, Berk Slamnik-Kriještorac, Nina Marquez-Barja, Johann University of Antwerp Faculty of Applied Engineering Antwerp Belgium University of Antwerp-Imec IDLab Faculty of Applied Engineering Antwerp Belgium

ISBN: (纸本)9781450392846

intelligent edge orchestration has become a vital component within next generation communication networks, such as 5G. They offer optimal resource allocation and service distribution, hence allow for full utilization of the opportunities provided by those networks. Orchestrators make use of Machine Learning (ML) techniques to determine the most optimal operational decisions, such as deployment and scaling of services, ensuring the quality of the service performance. The training and validation of these models require significant amount of data. However, in such environments we deal with heterogeneous and distributed data sources, in which the data needs to be collected and pre-processed efficiently, and as such, made ready-to-use for these ML models. Hence, in this paper several state-of-the-art data management technologies suitable for edge computing and orchestration are investigated and compared. After investigating the theoretical features of these technologies, they are deployed and tested on the smart Highway testbed. The strengths and shortcomings of these systems are presented and compared based on the Quality of Service (QoS) requirements for various vehicular services dealing with highly mobile users, i.e., vehicles, which are considered as quite stringent. This hybrid platform, combining several data management technologies, will be used to assist and enrich the research on smart edge orchestration at IDLab and serve as a reference for other interested parties. © 2022 ACM.

关键词： Information management

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Big data in smart Infrastructure

Big Data in Smart Infrastructure

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intelligent Systems conference, IntelliSys 2020

作者： Serrano, Will Alumni Imperial College London South Kensington LondonSW7 2AZ United Kingdom

ISBN: (纸本)9783030551865

Infrastructure is becoming smarter due to technical advances such as the Internet of Things (IoT) that enables a greater interconnectivity between assets and Artificial Intelligence (AI) to enhance the decision making task;this paper proposes a Big data Framework in smart Infrastructure such as Airports, Stations intelligent Transport Systems and Buildings. The interconnection of infrastructure systems using Local Area Networks, Wi-Fi, Radio or Mobile Networks is not enough to optimize and expand Infrastructure services and functionality;Big data integration, management and analytics will play a key role in the next smart Infrastructure stages when Infrastructure will learn and adapt to users. However, the inconvenient truth behind the Big data hosted in the cloud is the intrinsically associated Cybersecurity threat and risk. This paper provides the practical application of Digital as a Service (DaaS) with considerations and recommendations that cover the implementation of Big data in smart Infrastructure with some practical examples of real Infrastructure projects: Buildings, Airport, Stations and intelligent Transport Systems. In addition, flagship projects have also to be delivered on time, budget and quality within a Health and Safety environment in order to be successful where the understanding of requirements and solutions is key and an Agile approach has some benefits to the traditional project management delivery. © 2021, Springer Nature Switzerland AG.

关键词： Big data

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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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international conference on Power Energy, Environment and intelligent Control (PEEIC)

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

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..

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Research on edge computing technology of Internet of Things based on intelligent and environmental protection

Research on edge computing technology of Internet of Things ...

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IEEE international conference on Consumer Electronics and Computer Engineering (ICCECE)

作者： Cheng, Yunli Meng, Hainie Yuan, Lina Lei, Yaohua Inst GuangZhou Software Engn Guangzhou 510990 Guangdong Peoples R China

ISBN: (纸本)9781728183190

With the rapid developoment of Internet of Things technology, in the filed intelligent envieronmental protection, a large number. of ens iron menial protection equipment access, Ill us will produce hundreds of millions of enivironmental data. The traditional data processing mode of cloud computing is difficult to meet the demand of intelligent analysis, and a new kind of Internet of things technology - edge computing is gradually concerned by people. The proposal of edge computing is mainly to relive to the data processing pressure generated by hundreds of millions of iot devices. Edge computing technology has been applied in many fields. The application of edge computing technology in the field of environmental protection can accelerate the landing applications in the intelligent environmental protection industry und holier promote the intelligent environmental protection. This paper mainly studies the edge computing technology is applied in environmental wisdom, through a comprehensive study reference architecture model, and calculate the edge of the architectural model in practical application, design a kind of wisdom were calculated based ion edge iot framework of environmental and on this basis, combining With century oasis software and systems engineering technology I projects, design a kind of wisdom environmental oriented iot gateway software architecture, and finally reality the edge (of. the Internet if things intelligent gateway for wisdom of environmental protection. The research focuses ion the problems of intelligent access toen;environmental protection devices, safe transmission of environmental protection data, quick connection of en;iron mental protection platform und so on. Finally, it is tested in a practical project to verify. the stability and reliability of intelligent;listen ay on the edge of smart environmental protection. System evaluation results shim that the wisdom green edge intelligent galena, support for multiple ty(pes of environmenta

关键词： smart environmental protection The Internet of things Edge calculation Application research on

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data Fusion for smart Agriculture Applied to an IoT-based Use-Case for Arable Crops

Data Fusion for Smart Agriculture Applied to an IoT-based Us...

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Omni-layer intelligent Systems (COINS), international conference on

作者： Ioannis A. Vetsikas Ioanna Roussaki Institute of Communication and Computer Systems Athens Greece

The H2020 DEMETER project uses advanced AI and IoT technologies in order to promote the sustainability of the agricultural sector, to decrease the costs and the environmental impact, while maintaining yields at the same time. To achieve this it developed a service-oriented architecture where various interoperable enablers (i.e., services) can be combined in order to create apps that optimize the usage of resources and yield at the same time. This paper first presents a specific use-case that optimizes rice and maize irrigation and fertilization management processes. Then, it focuses its main part in the development of a data fusion enabler that, combined with appropriate sensor, data analytics, decision support and actuation enablers was combined into the development of DEMETER apps for this use case, that achieved reductions of the used resources (water and fertilizer) while maintaining the crop yields. For the development of this fusion enabler, several preexisting fusion techniques were examined, and the most appropriate of these were used and combined to form the fusion enabler.

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