English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Action detection and public traffic safety are crucial aspects of a safecommunity and a better society. Monitoring traffic flows in a smart city usingdifferent surveillance cameras can play a significant role in recognizingaccidents and alerting first responders. The utilization of action recognition(AR) in computer vision tasks has contributed towards high-precisionapplications in video surveillance, medical imaging, and digital signalprocessing. This paper presents an intensive review focusing on actionrecognition in accident detection and autonomous transportation systems for asmart city. In this paper, we focused on AR systems that used diverse sourcesof traffic video capturing, such as static surveillance cameras on trafficintersections, highway monitoring cameras, drone cameras, and dash-cams.Through this review, we identified the primary techniques, taxonomies, andalgorithms used in AR for autonomous transportation and accident detection. Wealso examined data sets utilized in the AR tasks, identifying the main sourcesof datasets and features of the datasets. This paper provides potentialresearch direction to develop and integrate accident detection systems forautonomous cars and public traffic safety systems by alerting emergencypersonnel and law enforcement in the event of road accidents to minimize humanerror in accident reporting and provide a spontaneous response to victims

Review on Action Recognition for Accident Detection in Smart City Transportation Systems