IoT-Based Smart Safety Analyzer for Women

IoT-Based Smart Safety Analyzer for Women

Copyright: © 2024 |Pages: 15
DOI: 10.4018/979-8-3693-2679-4.ch012
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Abstract

Despite significant technological advancements in modern times, the safety of women remains a persistent concern. It's important to develop IoT-based women's security systems with a user-centric approach, involving women in the design process to ensure the technology meets their needs effectively. An internet of things (IoT) based women's security system leverages connected devices and sensors to enhance the safety and well-being of women. These systems use technology to monitor, communicate, and respond to potential threats or emergencies. Artificial intelligence-based tools are employed to distinguish male individuals within designated women-only areas. The system assesses conditions by comparing specific attributes against its internal safety database. Upon detecting a potentially concerning scenario, the system promptly notifies the staff and triggers audible alarms for immediate attention. A “smart safety analyzer for women” could refer to a technological solution aimed at enhancing the safety and security of women in metro train.
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2. Literature Survey

This chapter aims to enhance the safety of women in public spaces by leveraging advancements in artificial intelligence, computer vision, and deep learning. To achieve this goal, we have conducted a literature survey to understand the relevant research in the fields of human behavior analysis, crowd monitoring, and gender detection, as outlined below.

Bhardwaj et al. (2022) discussed human behavior analysis using machine learning techniques. This paper provides insights into the state of the art in machine learning and object tracking, which are crucial components of our crowd monitoring system. It also highlights the need to assess the generalization of activity duration, a consideration that we will incorporate into system's design.

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