Integration of Cloud Computing and Big Data Technology for Smart Generation

Tomar, Dimpal; Tomar, Pradeep

doi:10.1109/confluence.2018.8443052

Cited by 10 publications

(5 citation statements)

References 5 publications

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“…[43] proposed a model that correctly and efficiently determined the customer population-based on service expectations, increases service requesters' satisfaction, prevents malicious intervention, and is effective and feasible. [44] categorized the big data, an understanding of Hadoop architecture, and a discussion of similar studies concerning big data and cloud platforms. Besides, they discussed the transparent problems of big data in the cloud domain.…”

Section: Discussion and Comparisonmentioning

confidence: 99%

Real Time Face-mask Detection with Arduino to Prevent COVID-19 Spreading

Almufti

Marqas

Nayef

et al. 2021

QAJ

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The rise of COVID-19 pandemic has had a lasting impact in many countries worldwide since 2019. Face-mask detection had been significant progress in the Image processing and deep learning fields studies. Many face detection models have been designed using different algorithms and techniques. The proposed approach in this paper developed to avoid mask-less people from entering to a desired places (i.e. Mall, University, Office, …etc.) by detecting face mask using deep learning, TensorFlow, Keras, and OpenCV and sending a signal to Arduino device that connected to the gate to be open. it detect a face in a real-time and identifies whether the person wear mask or not. The method attains accuracy up to 97.80%. The dataset provided in this paper, was collected from various sources.

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Section: Discussion and Comparisonmentioning

confidence: 99%

Real Time Face-mask Detection with Arduino to Prevent COVID-19 Spreading

Almufti

Marqas

Nayef

et al. 2021

QAJ

View full text Add to dashboard Cite

show abstract

“…Optimising both hardware and software components is crucial to improve the efficiency of embedded systems and support the transition towards a net-zero transportation industry [47]. Moreover, cloud computing must improve to cater for the high data management demands brought about by data-driven algorithms [48]. Cybersecurity protocols must also evolve to combat the cyber vulnerabilities of safety-critical ICPSs [49][50][51].…”

Section: Literature Gaps and Contributionsmentioning

confidence: 99%

Intelligent Embedded Systems Platform for Vehicular Cyber-Physical Systems

2023

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Intelligent vehicular cyber-physical systems (ICPSs) increase the reliability, efficiency and adaptability of urban mobility systems. Notably, ICPSs enable autonomous transportation in smart cities, exemplified by the emerging fields of self-driving cars and advanced air mobility. Nonetheless, the deployment of ICPSs raises legitimate concerns surrounding safety assurance, cybersecurity threats, communication reliability, and data management. Addressing these issues often necessitates specialised platforms to cater to the heterogeneity and complexity of ICPSs. To address this challenge, this paper presents a comprehensive CPS to explore, develop and test ICPSs and intelligent vehicular algorithms. A customisable embedded system is realised using a field programmable gate array, which is connected to a supervisory computer to enable networked operations and support advanced multi-agent algorithms. The platform remains compatible with multiple vehicular sensors, communication protocols and human–machine interfaces, essential for a vehicle to perceive its surroundings, communicate with collaborative systems, and interact with its occupants. The proposed CPS thereby offers a practical resource to advance ICPS development, comprehension, and experimentation in both educational and research settings. By bridging the gap between theory and practice, this tool empowers users to overcome the complexities of ICPSs and contribute to the emerging fields of autonomous transportation and intelligent vehicular systems.

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“…In 2018 Tomar, D., & Tomar, P. [44] addressed the main features and categorization of Big Data and Hadoop systems that govern the complexity about two case studies used in dealing with Big Data in the cloud. Focus on Cloud Techniques for Big Data and recognize a range of important open research challenges in this field.…”

Section: Literature Reviewmentioning

confidence: 99%

“…In terms of analytics and requirements, the computational parameters can be expanded. Tomar, D. et al [44] [45] 2018…”

mentioning

confidence: 99%

Comprehensive Survey of Big Data Mining Approaches in Cloud Systems

Ageed

Zeebaree

Sadeeq

et al. 2021

QAJ

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Cloud computing, data mining, and big online data are discussed in this paper as hybridization possibilities. The method of analyzing and visualizing vast volumes of data is known as the visualization of data mining. The effect of computing conventions and algorithms on detailed storage and data communication requirements has been studied. When researching these approaches to data storage in big data, the data analytical viewpoint is often explored. These terminology and aspects have been used to address methodological development as well as problem statements. This will assist in the investigation of computational capacity as well as new knowledge in this area. The patterns of using big data were compared in about fifteen articles. In this paper, we research Big Data Mining Approaches in Cloud Systems and address cloud-compatible problems and computing techniques to promote Big Data Mining in Cloud Systems.

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Integration of Cloud Computing and Big Data Technology for Smart Generation

Cited by 10 publications

References 5 publications

Real Time Face-mask Detection with Arduino to Prevent COVID-19 Spreading

Real Time Face-mask Detection with Arduino to Prevent COVID-19 Spreading

Intelligent Embedded Systems Platform for Vehicular Cyber-Physical Systems

Comprehensive Survey of Big Data Mining Approaches in Cloud Systems

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