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 Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The safety of railways, the nation's main transportation network, is currently drawing attention. This is mainly because of recent terrorist attacks aimed at private multipurpose facilities in a number of foreign countries. This article proposes a system for real-time monitoring of railway facilities and secure areas. Access control will be obtained using Raspberry Pi, an inexpensive micro-controller connected to the cloud via Amazon Web Service. Real-time surveillance is demonstrated by implementing computer vision and deep learning, and Twilio API. Intruders in restricted areas (such as tracks and electrical installations) can be detected with high precision and notifications can be sent to the safety and security managers in real time via short message service through cloud applications. The proposed system will assist the safety and security managers in responding swiftly and effectively to prevent or minimize risks that arise due to intruders.

Development of a real-time security management system for restricted access areas using computer vision and deep learning