Multimodal Women Safety and Analytics Using OpenCV and OpenVINO

Safety is a basic human right, but the safety of women is still a challenge that the whole world is concerned about, and urgent effective solutions are required. This paper presents an intelligent safety tool based on artificial intelligence, to be deployed in two stages: smart surveillance and user-side applications, including mobile apps and websites. The system will make use of technologies such as the Intel OpenVINO<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TM</sup> Toolkit and OpenCV for real-time gender detection, crowd density analysis, and gesture recognition. The system can send an SOS through gesture recognition in an emergency, which can enable services like Geocoder and Nominiatim to share the user's location in multiple emergency contacts along with a loud alarm. It also contains a multilingual SOS trigger button within the mobile application and website, community and support of the clients, a resource and information repository. The solution is developed to be deployed using the existing CCTV cameras and smartphones in a cost-effective and scalable way. Regarding benchmark performance, the proposed AI model is almost negligible; detection tasks get completed within milliseconds.

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Publication Details

Published
2025-04-04
DOI
https://doi.org/10.1109/iccsai64074.2025.11063727
Primary Topic
IoT and GPS-based Vehicle Safety Systems
Type
article
Field-Weighted Citation Impact
0.00
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article

Multimodal Women Safety and Analytics Using OpenCV and OpenVINO

Ravinder Pal Singh, S Rajesh, S. Vats, Shashi Kant Mahajan et al.
IoT and GPS-based Vehicle Safety Systems
article

Multimodal Women Safety and Analytics Using OpenCV and OpenVINO

Ravinder Pal Singh, S Rajesh, S. Vats, Shashi Kant Mahajan, H. C. Malik, Manvi Chhiller
article en

Abstract

Safety is a basic human right, but the safety of women is still a challenge that the whole world is concerned about, and urgent effective solutions are required. This paper presents an intelligent safety tool based on artificial intelligence, to be deployed in two stages: smart surveillance and user-side applications, including mobile apps and websites. The system will make use of technologies such as the Intel OpenVINO<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">TM</sup> Toolkit and OpenCV for real-time gender detection, crowd density analysis, and gesture recognition. The system can send an SOS through gesture recognition in an emergency, which can enable services like Geocoder and Nominiatim to share the user's location in multiple emergency contacts along with a loud alarm. It also contains a multilingual SOS trigger button within the mobile application and website, community and support of the clients, a resource and information repository. The solution is developed to be deployed using the existing CCTV cameras and smartphones in a cost-effective and scalable way. Regarding benchmark performance, the proposed AI model is almost negligible; detection tasks get completed within milliseconds.

Amity University (IN), Amity University (AE)
Gender equality
Openalex Percentile: Top 83%
IoT and GPS-based Vehicle Safety Systems
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Multimodal Women Safety and Analytics Using OpenCV and OpenVINO — Ravinder Pal Singh, S Rajesh, et al. · (2025) | TGRS Research Map | TGRS