Future smart cities: requirements, emerging technologies, applications, challenges, and future aspects

Javed, Abdul Rehman; Shahzad, Faisal; Rehman, Saif Ur; Zikria, Yousaf Bin; Razzak, Imran; Jalil, Zunera; Xu, Guandong

doi:10.1016/j.cities.2022.103794

Cited by 238 publications

(86 citation statements)

References 292 publications

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“…An in-depth study of the blockchain-based solution benefits: When applied to replace existing solutions [ 149 ], blockchain is a new technology that has the potential to destabilize the market, by introducing revolutionary ways that may transform society [ 150 ]. As a result, it is critical to establish whether a blockchain is truly required for a given application [ 151 ].…”

Section: Open Challengesmentioning

confidence: 99%

Blockchain for Modern Applications: A Survey

Krichen

Ammi

Mihoub

et al. 2022

Sensors

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Blockchain is a modern technology that has revolutionized the way society interacts and trades. It could be defined as a chain of blocks that stores information with digital signatures in a distributed and decentralized network. This technique was first adopted for the creation of digital cryptocurrencies, such as Bitcoin and Ethereum. However, research and industrial studies have recently focused on the opportunities that blockchain provides in various other application domains to take advantage of the main features of this technology, such as: decentralization, persistency, anonymity, and auditability. This paper reviews the use of blockchain in several interesting fields, namely: finance, healthcare, information systems, wireless networks, Internet of Things, smart grids, governmental services, and military/defense. In addition, our paper identifies the challenges to overcome, to guarantee better use of this technology.

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Section: Open Challengesmentioning

confidence: 99%

Blockchain for Modern Applications: A Survey

Krichen

Ammi

Mihoub

et al. 2022

Sensors

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“…Advances in information and communication technologies are fundamental to the future smart cities ( Javed et al, 2022 ). The current 4th Generation Mobile Communication Technology (4G) may not be able to satisfy the demands of users in terms of data rate, delay, and network capacity.…”

Section: Introductionmentioning

confidence: 99%

The effects of expectancies and patriotism on Chinese use intention of 5G network

Zhang

Jiayi²,

Chen³

2022

Front. Psychol.

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China leads the world in the development and rollout of 5G network, yet less research has been done on the drivers of Chinese people’s adoption of 5G network, especially the specific role of national sentiments, such as the influence of patriotism on their attitude toward 5G network. The study obtained 804 effective online questionnaires from the respondents of various ages, genders, areas, and educational levels. The results based on the structural equation modeling (SEM) analysis showed that patriotism was an antecedent to Chinese users’ cognition of the conditions provided by the government and telecom operators and the extent that users were influenced by media and surrounding people, which in turn increased users’ expectations of the performance of 5G network and their confidence in adapting to 5G network, and resulted in an increased willingness to use 5G network. This research helps to understand the role of patriotism, which is an emotional factor, in stimulating Chinese users’ attitudes toward 5G network at the time when 5G network is putting into large-scale commercial use in China.

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“…Robotics deep learning applications contribute to enormous issues that machine learning does not address (Koppu et al, 2020 ; Javed et al, 2022 ). Text classification can be done with super high accuracy using deep learning architectures since they require low-level engineering and computation.…”

Section: Introductionmentioning

confidence: 99%

An efficient approach for textual data classification using deep learning

Alqahtani

Khan

Alsubai

et al. 2022

Front. Comput. Neurosci.

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Text categorization is an effective activity that can be accomplished using a variety of classification algorithms. In machine learning, the classifier is built by learning the features of categories from a set of preset training data. Similarly, deep learning offers enormous benefits for text classification since they execute highly accurately with lower-level engineering and processing. This paper employs machine and deep learning techniques to classify textual data. Textual data contains much useless information that must be pre-processed. We clean the data, impute missing values, and eliminate the repeated columns. Next, we employ machine learning algorithms: logistic regression, random forest, K-nearest neighbors (KNN), and deep learning algorithms: long short-term memory (LSTM), artificial neural network (ANN), and gated recurrent unit (GRU) for classification. Results reveal that LSTM achieves 92% accuracy outperforming all other model and baseline studies.

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Future smart cities: requirements, emerging technologies, applications, challenges, and future aspects

Cited by 238 publications

References 292 publications

Blockchain for Modern Applications: A Survey

Blockchain for Modern Applications: A Survey

The effects of expectancies and patriotism on Chinese use intention of 5G network

An efficient approach for textual data classification using deep learning

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