Post Pandemic World and Challenges for E-Governance Framework

2021 ◽  
Vol 10 (3) ◽  
pp. 2630-2636
Keyword(s):  
Cloud Computing ◽  
Smart Cities ◽  
Rapid Development ◽  
Smart Devices ◽  
Economic Modelling ◽  
Intelligent Robots ◽  
Autonomous Cars ◽  
Autonomous Machines ◽  
Almost All ◽  
Digital Or

Emergence of cloud computing and rapid development of automation in terms of Internet of Things (IoT), it was evident in the wake of 2019 that world is gradually moving towards a complete digital system from individual to business and ultimately government level. Technology advancements start expanding from smart devices to smart cities, autonomous machines to autonomous cars and expert systems to intelligent robots. These advancements are supported by the swiftly growing communication and networking domain where 5G is introducing new range of expansion and more freedom to creativity and novelty. This new regime of advanced technologies has made the foundation on live digital or internet based structures that transformed into cloud computing with swiftly growing facilities and innovative competitors. Cloud computing penetrates in almost all digital domains from individuals to corporates and to governments as well due to its versatile services, economic modelling and ease of accessibility.

Edge Cloud

2019 ◽  
pp. 107-131
Author(s):  
Lucia Agnes Beena Thomas
Keyword(s):  
Cloud Computing ◽  
Virtual Reality ◽  
Cost Saving ◽  
New Technologies ◽  
Smart Cities ◽  
Low Latency ◽  
Battery Life ◽  
Real Time Processing ◽  
Time Processing ◽  
Autonomous Cars

With the proliferation of new technologies such as augmented and virtual reality, autonomous cars, 5G networks, drones, and IOT with smart cities, consumers of cloud computing are becoming the producers of data. Large volume of data is being produced at the edge of the network. This scenario insists the need for efficient real-time processing and communication at the network edge. Cloud capabilities must be distributed across the network to form an edge cloud, which places computing resources where the traffic is at the edge of the network. Edge cloud along with 5G services could also glint the next generation of robotic manufacturing. The anticipated low latency requirement, battery life constraint, bandwidth cost saving, as well as data safety and privacy are also inscribed by edge cloud. A number of giants like Nokia, AT&T, and Microsoft have emerged in the market to support edge cloud. This chapter wraps the features of edge cloud, the driving industries that are providing solutions, the use cases, benefits, and the challenges of edge cloud.

scholarly journals The role of elements of the Economics of Quality in mathematical modelling of socio-economic processes

2019 ◽  
Vol 138 ◽  
pp. 02008 ◽  
Author(s):  
Vladimir Okrepilov ◽  
Natalia Chetyrkina ◽  
Mikhail Krylov
Keyword(s):  
Quality Management ◽  
Information Quality ◽  
Smart Cities ◽  
Management Systems ◽  
Economic Modelling ◽  
Quality Management Systems ◽  
Development Models ◽  
Managerial Decisions ◽  
Almost All

Nowadays, when making managerial decisions, specialists are faced with the need to process ever-increasing volumes of information in an increasingly shorter time. The need for the development of a methodology for social forecasting on the basis of detailed development models is growing. Since the basis of the activity of the socio-economic system of any level is an anthropogenic factor, this increases the degree of probability of the implementation of various scenarios. To develop more accurate forecasts, it is necessary to use the tools of the economics of quality standardization, metrology, quality management. Standardization determines the ability to normalize and assess sustainability indicators of development, as well as management methods. Metrology provides uniform methods for measuring these indicators. Based on the received information, quality management systems allow making reliable managerial decisions. The use of tools of the economics of quality is possible at almost all stages of socio-economic modelling. The role of elements of the economics of quality, in particular standardization, is especially growing in the development of the digital economy and “smart cities”, where a complete unification of the formats for accumulating and transmitting information to all users is required.

scholarly journals ARTIFICIAL INTELLIGENCE AS A SERVICE IN DISTRIBUTED MULTI ACCESS EDGE COMPUTING ON 5G EXTRACTING DATA USING IOT AND INCLUDING AR/VR FOR REAL-TIME REPORTING

2021 ◽  
Vol 9 (1) ◽  
pp. 912-931
Author(s):  
Pavan Madduru
Keyword(s):  
Cloud Computing ◽  
Internet Of Things ◽  
Virtual Machines ◽  
Smart Cities ◽  
Assistive Technologies ◽  
Edge Computing ◽  
Smart Devices ◽  
The Internet ◽  
Iot Applications ◽  
The Internet Of Things

To meet the growing demand for mobile data traffic and the stringent requirements for Internet of Things (IoT) applications in emerging cities such as smart cities, healthcare, augmented / virtual reality (AR / VR), fifth-generation assistive technologies generation (5G) Suggest and use on the web. As a major emerging 5G technology and a major driver of the Internet of Things, Multiple Access Edge Computing (MEC), which integrates telecommunications and IT services, provides cloud computing capabilities at the edge of an access network. wireless (RAN). By providing maximum compute and storage resources, MEC can reduce end-user latency. Therefore, in this article we will take a closer look at 5G MEC and the Internet of Things. Analyze the main functions of MEC in 5G and IoT environments. It offers several core technologies that enable the use of MEC in 5G and IoT, such as cloud computing, SDN / NFV, information-oriented networks, virtual machines (VMs) and containers, smart devices, shared networks and computing offload. This article also provides an overview of MEC's ​​role in 5G and IoT, a detailed introduction to MEC-enabled 5G and IoT applications, and future perspectives for MEC integration with 5G and IoT. Additionally, this article will take a closer look at the MEC research challenges and unresolved issues around 5G and the Internet of Things. Finally, we propose a use case that MEC uses to obtain advanced intelligence in IoT scenarios.

Waste Management System for Smart City Using IoT

2019 ◽  
pp. 1-15
Author(s):  
Golden Julie E.
Keyword(s):  
Cloud Computing ◽  
Big Data ◽  
Internet Of Things ◽  
Waste Management ◽  
Smart City ◽  
Management System ◽  
Smart Cities ◽  
Smart Devices ◽  
Construction Technology ◽  
Waste Management System

In the present scenario, sensors place a major role for implementing smart devices. Internet of Things (IoT) is an advancement of sensors which can communicate with non-communicate things (devices). Many of the developed counties are using smartness in creating and communicating devices using IoT. In India, major challenges focus on how and where to implement smartness. Hence, authors found some different areas like healthcare, education, transport, water, energy, communication, security & safety, citizen services, and so on. All these areas are covered by a smart way using recent technology (IoT) in smart cities concepts. Various technologies like IoT, Big Data, and cloud computing are used for constructing smartness in the form of devices. In this Chapter, authors focus on a smart waste management system using IoT. They provide various smart bin construction technology, advantages, standards and challenges in detail. It is very useful to the reader to understand the various method of waste management in smart cities development using IoT.

scholarly journals Image-Based Automatic Watermeter Reading under Challenging Environments

Sensors ◽  
2021 ◽  
Vol 21 (2) ◽  
pp. 434
Author(s):  
Qingqi Hong ◽  
Yiwei Ding ◽  
Jinpeng Lin ◽  
Meihong Wang ◽  
Qingyang Wei ◽  
...  
Keyword(s):  
Smart Cities ◽  
Rapid Development ◽  
Mobile Network ◽  
Spatial Layout ◽  
Single Image ◽  
Automatic Instrument ◽  
Intelligent Sensors ◽  
Fifth Generation ◽  
Instrument Reading ◽  
Network Technologies

With the rapid development of artificial intelligence and fifth-generation mobile network technologies, automatic instrument reading has become an increasingly important topic for intelligent sensors in smart cities. We propose a full pipeline to automatically read watermeters based on a single image, using deep learning methods to provide new technical support for an intelligent water meter reading. To handle the various challenging environments where watermeters reside, our pipeline disentangled the task into individual subtasks based on the structures of typical watermeters. These subtasks include component localization, orientation alignment, spatial layout guidance reading, and regression-based pointer reading. The devised algorithms for orientation alignment and spatial layout guidance are tailored to improve the robustness of our neural network. We also collect images of watermeters in real scenes and build a dataset for training and evaluation. Experimental results demonstrate the effectiveness of the proposed method even under challenging environments with varying lighting, occlusions, and different orientations. Thanks to the lightweight algorithms adopted in our pipeline, the system can be easily deployed and fully automated.

scholarly journals Past, present, and future of smart learning: a topic-based bibliometric analysis

2021 ◽  
Vol 18 (1) ◽  
Author(s):  
Xieling Chen ◽  
Di Zou ◽  
Haoran Xie ◽  
Fu Lee Wang
Keyword(s):  
Cloud Computing ◽  
Blended Learning ◽  
Information And Communication Technologies ◽  
Content Management ◽  
Research Field ◽  
Smart Devices ◽  
Major Research ◽  
Research Issues ◽  
Course Content ◽  
Smart Learning

AbstractInnovative information and communication technologies have reformed higher education from the traditional way to smart learning. Smart learning applies technological and social developments and facilitates effective personalized learning with innovative technologies, especially smart devices and online technologies. Smart learning has attracted increasing research interest from the academia. This study aims to comprehensively review the research field of smart learning by conducting a topic modeling analysis of 555 smart learning publications collected from the Scopus database. In particular, it seeks answers to (1) what the major research topics concerning smart learning were, and (2) how these topics evolved. Results demonstrate several major research issues, for example, Interactive and multimedia learning, STEM (science, technology, engineering, and mathematics) education, Attendance and attention recognition, Blended learning for smart learning, and Affective and biometric computing. Furthermore, several emerging topics were identified, for example, Smart learning analytics, Software engineering for e-learning systems, IoT (Internet of things) and cloud computing, and STEM education. Additionally, potential inter-topic directions were highlighted, for instance, Attendance and attention recognition and IoT and cloud computing, Semantics and ontology and Mobile learning, Feedback and assessment and MOOCs (massive open online courses) and course content management, as well as Blended learning for smart learning and Ecosystem and ambient intelligence.

scholarly journals Mobile Networks and Internet of Things Infrastructures to Characterize Smart Human Mobility

Smart Cities ◽  
2021 ◽  
Vol 4 (2) ◽  
pp. 894-918
Author(s):  
Luís Rosa ◽  
Fábio Silva ◽  
Cesar Analide
Keyword(s):  
Internet Of Things ◽  
Mobile Networks ◽  
Smart Cities ◽  
Human Mobility ◽  
Rapid Development ◽  
Disruptive Technology ◽  
New Paradigm ◽  
Design And Optimization ◽  
High Level

The evolution of Mobile Networks and Internet of Things (IoT) architectures allows one to rethink the way smart cities infrastructures are designed and managed, and solve a number of problems in terms of human mobility. The territories that adopt the sensoring era can take advantage of this disruptive technology to improve the quality of mobility of their citizens and the rationalization of their resources. However, with this rapid development of smart terminals and infrastructures, as well as the proliferation of diversified applications, even current networks may not be able to completely meet quickly rising human mobility demands. Thus, they are facing many challenges and to cope with these challenges, different standards and projects have been proposed so far. Accordingly, Artificial Intelligence (AI) has been utilized as a new paradigm for the design and optimization of mobile networks with a high level of intelligence. The objective of this work is to identify and discuss the challenges of mobile networks, alongside IoT and AI, to characterize smart human mobility and to discuss some workable solutions to these challenges. Finally, based on this discussion, we propose paths for future smart human mobility researches.

Research and application of new media urban landscape design method based on 5G virtual reality

2021 ◽  
pp. 1-9
Author(s):  
Guangchao Zhang ◽  
Xinyue Kou
Keyword(s):  
Virtual Reality ◽  
New Media ◽  
Urban Landscape ◽  
Design Method ◽  
Smart Cities ◽  
Rapid Development ◽  
Environmental Design ◽  
Landscape Design ◽  
Living Environment ◽  
The City

In recent years, with the rapid development of VR technology, its application range gradually involves the field of urban landscape design. VR technology can simulate complex environments, breaking through the limitations of traditional environmental design on large amounts of information processing and rendering of renderings. It can display complex and abstract urban environmental design through visualization. With the support of high-speed information transmission in the 5G era, VR technology can simulate the overall urban landscape design by generating VR panoramas, and it can also bring the experiencer into an immersive and interactive virtual reality world through VR video Experience. Based on this, this article uses the 5G virtual reality method in the new media urban landscape design to conduct research, aiming to provide an urban landscape design method with strong authenticity, good user experience and vividness. This paper studies the urban landscape design method in the new media environment; in addition, how to realize the VR panorama in the 5G environment, and also explores the image design of each node in the city in detail; and uses the park design in the city As an example, the realization process of the entire virtual reality is described in detail. The research in this article shows that the new media urban landscape design method based on 5G virtual reality, specifically to the design of urban roads, water divisions, street landscapes, and people’s living environment, makes the realization of smart cities possible.

scholarly journals Object Detection, Distributed Cloud Computing and Parallelization Techniques for Autonomous Driving Systems

2021 ◽  
Vol 11 (7) ◽  
pp. 2925
Author(s):  
Edgar Cortés Gallardo Medina ◽  
Victor Miguel Velazquez Espitia ◽  
Daniela Chípuli Silva ◽  
Sebastián Fernández Ruiz de las Cuevas ◽  
Marco Palacios Hirata ◽  
...  
Keyword(s):  
Neural Networks ◽  
Cloud Computing ◽  
Path Planning ◽  
Object Detection ◽  
Short Term Memory ◽  
Smart Cities ◽  
Autonomous Vehicle ◽  
Computational Time ◽  
End To End ◽  
On The Road

Autonomous vehicles are increasingly becoming a necessary trend towards building the smart cities of the future. Numerous proposals have been presented in recent years to tackle particular aspects of the working pipeline towards creating a functional end-to-end system, such as object detection, tracking, path planning, sentiment or intent detection, amongst others. Nevertheless, few efforts have been made to systematically compile all of these systems into a single proposal that also considers the real challenges these systems will have on the road, such as real-time computation, hardware capabilities, etc. This paper reviews the latest techniques towards creating our own end-to-end autonomous vehicle system, considering the state-of-the-art methods on object detection, and the possible incorporation of distributed systems and parallelization to deploy these methods. Our findings show that while techniques such as convolutional neural networks, recurrent neural networks, and long short-term memory can effectively handle the initial detection and path planning tasks, more efforts are required to implement cloud computing to reduce the computational time that these methods demand. Additionally, we have mapped different strategies to handle the parallelization task, both within and between the networks.

scholarly journals Cloud-based intelligent self-diagnosis and department recommendation service using Chinese medical BERT

2021 ◽  
Vol 10 (1) ◽  
Author(s):  
Junshu Wang ◽  
Guoming Zhang ◽  
Wei Wang ◽  
Ka Zhang ◽  
Yehua Sheng
Keyword(s):  
Cloud Computing ◽  
Large Scale ◽  
Medical Service ◽  
Rapid Development ◽  
Medical Knowledge ◽  
Language Models ◽  
Computing Environment ◽  
Computing Power ◽  
Cloud Computing Environment ◽  
Proposed Model

AbstractWith the rapid development of hospital informatization and Internet medical service in recent years, most hospitals have launched online hospital appointment registration systems to remove patient queues and improve the efficiency of medical services. However, most of the patients lack professional medical knowledge and have no idea of how to choose department when registering. To instruct the patients to seek medical care and register effectively, we proposed CIDRS, an intelligent self-diagnosis and department recommendation framework based on Chinese medical Bidirectional Encoder Representations from Transformers (BERT) in the cloud computing environment. We also established a Chinese BERT model (CHMBERT) trained on a large-scale Chinese medical text corpus. This model was used to optimize self-diagnosis and department recommendation tasks. To solve the limited computing power of terminals, we deployed the proposed framework in a cloud computing environment based on container and micro-service technologies. Real-world medical datasets from hospitals were used in the experiments, and results showed that the proposed model was superior to the traditional deep learning models and other pre-trained language models in terms of performance.

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