Insight into the Impact of COVID-19 on Australian Transportation Sector: An Economic and Community-Based Perspective

Munawar, Hafiz Suliman; Khan, Sara Imran; Qadir, Zakria; Kouzani, Abbas Z.; Mahmud, Arafat

doi:10.3390/su13031276

Cited by 81 publications

(96 citation statements)

References 65 publications

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“…Before COVID-19, the proportion of household trips by private cars was stable, with 70% of the people travelling by car, while during COVID-19, the usage of private cars was comparatively higher than the rest. Active transport of household trips increased from 14 to 20% but, however, was lower in absolute terms [36,37].…”

Section: Change In the Mode Of Transportmentioning

confidence: 99%

Insights into the Mobility Pattern of Australians during COVID-19

et al. 2021

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Coronavirus disease 2019 (COVID-19) is an infectious disease characterised by symptoms that are like the common cold. The current pandemic situation in anticipation of a vaccine has posed serious threats to the health and economic sectors of countries worldwide. To overcome the quick transmission of the virus, the government of Australia has also taken drastic measures to prevent its spread. These policies include an international and interstate travel ban, social distancing rules, lockdown, shutdown of educational institutes and work-from-home policies. Such rules have affected people on both behavioural and psychological levels. This study aims to analyse the effect of COVID-19 on Australian citizens, and therefore, the changed behaviour of citizens concerning their mobility patterns, transport preferences and shopping methods under the pandemic have been studied. A detailed literature search was adopted for gathering data related to the study theme, along with real-time evidence of changes in the behaviour of people following the pandemic. The socioeconomic impact of the pandemic on social inequality and thereby the effect on the vulnerable people of the population are also studied. Authentic surveys and statistical data are consulted to figure out how the new lifestyle choices of people will linger in the post-pandemic era. It was found that people in Australia have adopted the work-from-home regime, and new habits suiting the nationwide restrictions have become routine for many people.

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Section: Change In the Mode Of Transportmentioning

confidence: 99%

Insights into the Mobility Pattern of Australians during COVID-19

et al. 2021

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“…COVID-19 has had a huge impact on the transportation industry. With the adoption of COVID prevention methods, a reduced demand for transport has been noticed [42], which has also affected other areas, such as agricultural supply chains [43]. IoT applications such as the toll and reservation ticketing system, navigation tracking and GIS mapping, control and guidance systems, supply chain management solution systems, and smart vehicle applications can tackle some problems during the pandemic to limit crowded areas and help the process of importing and exporting goods.…”

Section: Iot In the Transportation Sectormentioning

confidence: 99%

IoT Technologies during and Beyond COVID-19: A Comprehensive Review

2021

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The COVID-19 pandemic provided a much-needed sanity check for IoT-inspired frameworks and solutions. IoT solutions such as remote health monitoring and contact tracing provided support for authorities to successfully manage the spread of the coronavirus. This article provides the first comprehensive review of key IoT solutions that have had an impact on COVID-19 in healthcare, contact tracing, and transportation during the pandemic. Each sector is investigated in depth; and potential applications, social and economic impact, and barriers for mass adaptation are discussed in detail. Furthermore, it elaborates on the challenges and opportunities for IoT framework solutions in the immediate post-COVID-19 era. To this end, privacy and security concerns of IoT applications are analyzed in depth and emerging standards and code of practices for mass adaptation are also discussed. The main contribution of this review paper is the in-depth analysis and categorization of sector-wise IoT technologies, which have the potential to be prominent applications in the new normal. IoT applications in each selected sector are rated for their potential economic and social impact, timeline for mass adaptation, and Technology Readiness Level (TRL). In addition, this article outlines potential research directions for next-generation IoT applications that would facilitate improved performance with preserved privacy and security, as well as wider adaptation by the population at large.

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“…The Figure 6. Shows the building area detection using Gabor filter results on a sample satellite images, in a binary image two pixels are connected to each other if the value of the pixel is one or are connected by a path [11].…”

Section: Gabor Local Feature Point Extractionmentioning

confidence: 99%

“…Shen et al [11] assessed the building extraction method based on remote sensing image via Gabor filter and multi-orientation π local binary pattern (LBP) operator. This method was aimed to achieve better visualisation and improved urban planning.…”

Section: Introductionmentioning

confidence: 99%

A Gabor Filter-Based Protocol for Automated Image-Based Building Detection

et al. 2021

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Detecting buildings from high-resolution satellite imagery is beneficial in mapping, environmental preparation, disaster management, military planning, urban planning and research purposes. Differentiating buildings from the images is possible however, it may be a time-consuming or complicated process. Therefore, the high-resolution imagery from satellites needs to be automated to detect the buildings. Additionally, buildings exhibit several different characteristics, and their appearance in these images is unplanned. Moreover, buildings in the metropolitan environment are typically crowded and complicated. Therefore, it is challenging to identify the building and hard to locate them. To resolve this situation, a novel probabilistic method has been suggested using local features and probabilistic approaches. A local feature extraction technique was implemented, which was used to calculate the probability density function. The locations in the image were represented as joint probability distributions and were used to estimate their probability distribution function (pdf). The density of building locations in the image was extracted. Kernel density distribution was also used to find the density flow for different metropolitan cities such as Sydney (Australia), Tokyo (Japan), and Mumbai (India), which is useful for distribution intensity and pattern of facility point f interest (POI). The purpose system can detect buildings/rooftops and to test our system, we choose some crops with panchromatic high-resolution satellite images from Australia and our results looks promising with high efficiency and minimal computational time for feature extraction. We were able to detect buildings with shadows and building without shadows in 0.4468 (seconds) and 0.5126 (seconds) respectively.

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Insight into the Impact of COVID-19 on Australian Transportation Sector: An Economic and Community-Based Perspective

Cited by 81 publications

References 65 publications

Insights into the Mobility Pattern of Australians during COVID-19

Insights into the Mobility Pattern of Australians during COVID-19

IoT Technologies during and Beyond COVID-19: A Comprehensive Review

A Gabor Filter-Based Protocol for Automated Image-Based Building Detection

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