Enhancing pedestrian mobility in Smart Cities using Big Data

Carter, Ebony B.; Adam, P.J.; Tsakis, Deon; Shaw, Stephen B.; Watson, Richard; Ryan, Peter

doi:10.1080/23270012.2020.1741039

Cited by 52 publications

(37 citation statements)

References 20 publications

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“…tactile internet, flying networks and holographic calls for future networks in 2030. In [24] and [25], future trends and applications enabling 6G technology have been summarized. Blockchain technology, human centric services and key performance indicators of 6g are investigated in these studies.…”

Section: G and 6g -1000 Times Reductionmentioning

confidence: 99%

6G: Envisioning the Key Technologies, Applications and Challenges

Mohsan¹,

Mazinani²,

Malik³

et al. 2020

IJACSA

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In 2030, 6G is going to bring remarkable revolution in communication technologies as it will enable Internet of Everything. Still many countries are working over 5G and B5G has yet to be developed, while some research groups have already initiated projects on 6G. 6G will provide high and sophisticated QoS e.g. virtual reality and holographic communication. At this stage, it is impossible to speculate every detail of 6G and which key technologies will mark 6G. The wide applications of ICT, such as IoT, AI, blockchain technology, XR (Extended Reality) and VR (Virtual Reality), has created the emergence of 6G technology. On the basis of 5G technique, 6G will put profound impact over ubiquitous connectivity, holographic connectivity, deep connectivity and intelligent connectivity. Notably, research fraternity should focus on challenges and issues of 6G. They need to explore various alternatives to meet desired parameters of 6G. Thus, there are many potential challenges to be envisioned. This review study outlines some future challenges and issues which can hamper deployment of 6G. We subsequently define key potential features of 6G to provide the state of the art of 6G technology for future research. We have provided a review of extant research on 6G. In this review, technology prospects, challenges, key areas and related issues are briefly discussed. In addition, we have provided technologies breakdown and framework of 6G. We have shed light over future directions, applications and practical considerations of 6G to help researchers for possible breakthroughs. Our aim is to aggregate the efforts and eliminate the technical uncertainties towards breakthrough innovations for 6G.

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Section: G and 6g -1000 Times Reductionmentioning

confidence: 99%

6G: Envisioning the Key Technologies, Applications and Challenges

Mohsan¹,

Mazinani²,

Malik³

et al. 2020

IJACSA

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“…The Victorian datasets are all published on data.gov.au, which includes a link to the COM's open data portal (https://data.melbourne.vic.gov.au/). [27], which is a trend which can be expected to increase in the future. Many of these datasets can be visualized using built-in mapping tools.…”

Section: Australian Government Open Datamentioning

confidence: 99%

“…As an example of local council initiatives, analysis of pedestrian traffic in the COM was reported by Carter at al. [27]. While COM is not a suburban council, it is still the local council for the inner-city Central Business District (CBD).…”

Section: City Of Melbourne Pedestrian Traffic Analysismentioning

confidence: 99%

Big Data Analytics in Australian Local Government

Watson¹,

Ryan

2020

Smart Cities

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Australian governments at all three levels—local (council), state, and federal—are beginning to exploit the massive amounts of data they collect through sensors and recording systems. Their aim is to enable Australian communities to benefit from “smart city” initiatives by providing greater efficiencies in their operations and strategic planning. Increasing numbers of datasets are being made freely available to the public. These so-called big data are amenable to data science analysis techniques including machine learning. While there are many cases of data use at the federal and state level, local councils are not taking full advantage of their data for a variety of reasons. This paper reviews the status of open datasets of Australian local governments and reports progress being made in several student and other projects to develop open data web services using machine learning for smart cities.

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“…Its application touches a variety of urban infrastructures, such as a smart grid allowing decentralized energy distribution, waste management for detecting and separating trash, monitoring of waste and stormwater, and traffic control for automated vehicles [ 1 ]. At the core of the idea are the Internet of Things (IoT) sensors that collect a large quantity of user data for the control of Information and Communication Technology (ICT) devices [ 2 ]. This implies at least two crucial opportunities for the industry: massive demand for sensing hardware, and the availability of big data on how people use urban amenities.…”

Section: Introductionmentioning

confidence: 99%

“…Despite some small successes, the idea of smart city seems largely unsubstantiated [ 2 ]. This is entirely attributable to the ability of the sensors to surveil people’s behavior.…”

Section: Introductionmentioning

confidence: 99%

Developing Sidewalk Inventory Data Using Street View Images

Kang

Lee

Zou

2021

Sensors

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(1) Background: Public sidewalk GIS data are essential for smart city development. We developed an automated street-level sidewalk detection method with image-processing Google Street View data. (2) Methods: Street view images were processed to produce graph-based segmentations. Image segment regions were manually labeled and a random forest classifier was established. We used multiple aggregation steps to determine street-level sidewalk presence. (3) Results: In total, 2438 GSV street images and 78,255 segmented image regions were examined. The image-level sidewalk classifier had an 87% accuracy rate. The street-level sidewalk classifier performed with nearly 95% accuracy in most streets in the study area. (4) Conclusions: Highly accurate street-level sidewalk GIS data can be successfully developed using street view images.

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Enhancing pedestrian mobility in Smart Cities using Big Data

Cited by 52 publications

References 20 publications

6G: Envisioning the Key Technologies, Applications and Challenges

6G: Envisioning the Key Technologies, Applications and Challenges

Big Data Analytics in Australian Local Government

Developing Sidewalk Inventory Data Using Street View Images

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