Object Tracking in Vary Lighting Conditions for Fog Based Intelligent Surveillance of Public Spaces

Liu, Gaocheng; Liu, Shuai; Muhammad, Khan; Sangaiah, Arun Kumar; Doctor, Faiyaz

doi:10.1109/access.2018.2834916

Cited by 74 publications

(32 citation statements)

References 54 publications

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“…AI paradigms Machine learning [26]; [63]; [67][68][69][70]; Probabilistic methods [70]; [73][74][75]; [77]; [80][81][82]; [87]; [90]; [93,94]; [96][97][98][99][100][101]; [112][113][114]; [134]; [136][137][138] Knowledge-based [26]; [63]; [67][68][69][70][71]; [73]; [77,78]; [82]; [92]; [98]; [100]; [112]; [136]; [139][140][141][142]…”

Section: Category Element Referencementioning

confidence: 99%

“…Advanced AI surveillance technologies, enabled by motion detection, predictive analytics, drones, and other autonomous devices, can be used to monitor urban areas, recognize threats, such as crime [72,93,100,148], fraud [109], accidents, and fire [101,123,160]. On a broader scale, AI can be used to monitor communication networks and recognize potential terrorist threats, trafficking, crime syndicates, and other illegal behavior [100].…”

Section: Ai In the Governance Dimension Of Smart Citiesmentioning

confidence: 99%

“…On a broader scale, AI can be used to monitor communication networks and recognize potential terrorist threats, trafficking, crime syndicates, and other illegal behavior [100]. Once targets are identified, intelligent surveillance systems can evaluate and track targets [93], and collect forensic evidence-such as video recording [138]. AI can also be used to better predict future crime incidents and ensure the optimal allocation of crime law enforcement [144].…”

Section: Ai In the Governance Dimension Of Smart Citiesmentioning

confidence: 99%

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Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature

et al. 2020

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Artificial intelligence (AI) is one of the most disruptive technologies of our time. Interest in the use of AI for urban innovation continues to grow. Particularly, the rise of smart cities—urban locations that are enabled by community, technology, and policy to deliver productivity, innovation, livability, wellbeing, sustainability, accessibility, good governance, and good planning—has increased the demand for AI-enabled innovations. There is, nevertheless, no scholarly work that provides a comprehensive review on the topic. This paper generates insights into how AI can contribute to the development of smarter cities. A systematic review of the literature is selected as the methodologic approach. Results are categorized under the main smart city development dimensions, i.e., economy, society, environment, and governance. The findings of the systematic review containing 93 articles disclose that: (a) AI in the context of smart cities is an emerging field of research and practice. (b) The central focus of the literature is on AI technologies, algorithms, and their current and prospective applications. (c) AI applications in the context of smart cities mainly concentrate on business efficiency, data analytics, education, energy, environmental sustainability, health, land use, security, transport, and urban management areas. (d) There is limited scholarly research investigating the risks of wider AI utilization. (e) Upcoming disruptions of AI in cities and societies have not been adequately examined. Current and potential contributions of AI to the development of smarter cities are outlined in this paper to inform scholars of prospective areas for further research.

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Section: Category Element Referencementioning

confidence: 99%

Section: Ai In the Governance Dimension Of Smart Citiesmentioning

confidence: 99%

Section: Ai In the Governance Dimension Of Smart Citiesmentioning

confidence: 99%

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Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature

et al. 2020

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“…8,9 Based on the analytic hierarchy process (AHP) method, the database access path prediction method based on circulant neural network is constructed using a hierarchical structure to construct a multi-attribute decision-making problem. 8,9 Based on the analytic hierarchy process (AHP) method, the database access path prediction method based on circulant neural network is constructed using a hierarchical structure to construct a multi-attribute decision-making problem.…”

Section: Alternate Transit Data Centersmentioning

confidence: 99%

“…When considering the selection of data transmission paths between data centers under multi-attribute information, an important problem is that there are certain mutual constraints between multiple attributes. 8,9 Based on the analytic hierarchy process (AHP) method, the database access path prediction method based on circulant neural network is constructed using a hierarchical structure to construct a multi-attribute decision-making problem. The database usually has an efficient monitoring and management tool, and key attribute values can be obtained by monitoring and quantifying.…”

Section: Alternate Transit Data Centersmentioning

confidence: 99%

Analysis of distributed database access path prediction based on recurrent neural network in internet of things

2019

Concurrency and Computation

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For avoiding the phenomenon of congestion, delay, and jitter in thedatabase access path, it is necessary to study the prediction method of database access path. Predicted database access path has high delay and jitter when using existing database access path prediction method to predict the path. Therefore, a prediction method of database access path is proposed based on the recurrent neural network. A decision matrix is constructed and normalized based on the analytic hierarchy process. The evaluation value of the alternative transit data center is calculated by the arithmetic weighted average operator, and the transit data center is selected according to the evaluation result. The matter-element analysis model is used to establish the mapping relationship between the user experience quality and the network service quality parameters. Moreover, the user experience quality evaluation level objective function of the database access path prediction method is constructed. Through the objective function to obtain the optimal database access path, the database access path prediction is completed. The experimental results show that the delay of the database access path predicted by the proposed method is much lower than other methods. The jitter is less than 30 ms and the jitter is small, which verifies the effectiveness of the path prediction method. KEYWORDSaccess path, alternative transit data center, database, decision matrix, prediction method, recurrent neural network INTRODUCTIONLarge-scale databases copy user data to multiple databases to improve user service quality. 1 A large amount of data needs to be transmitted between these distributed databases. Measurement studies have shown that the traffic between databases already accounts for nearly half of the database export bandwidth. 2,3 To meet the peak bandwidth requirement of the application, the access path of the database needs to be predicted. The existing database access path prediction method predicts the optimal path with high delay and large jitter. It is necessary to analyze and study the database access path prediction method. 4Wang et al proposed a database access path prediction method based on the number limit and data transmission delay. 5 This method uses the distributed shortest path tree algorithm to collect the relevant information and sensing data of sensor nodes in the k + 1 hop communication range. The virtual force theory is used to calculate the virtual force of the sensor node and the resultant force of all virtual forces. Based on the current dwell time of the grid center and the next dwell grid center based on the number of stays, the size and direction of the resultant force are calculated; then, according to the location of the sensor node, the remaining energy and other information to find a better path to complete the database access path prediction. The delay of the path predicted by this method is higher.Luo and Liu proposed a database access path prediction method based on traffic gravitational field. 6 This method combines the...

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Virtual and Augmented Reality in Surgery

Halabi

Balakrishnan

Dakua

et al. 2020

Lecture Notes in Electrical Engineering

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Object Tracking in Vary Lighting Conditions for Fog Based Intelligent Surveillance of Public Spaces

Cited by 74 publications

References 54 publications

Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature

Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature

Analysis of distributed database access path prediction based on recurrent neural network in internet of things

Virtual and Augmented Reality in Surgery

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