Observational analysis reveals improved safety through IoT technologies in women, suggesting wider applications.
The present paper concerns the improvement of women's safety and accessibility to people with disabilities via IoT-enabled assistance and self-protection technologies. The system suggested uses an ESP32-CAM module for real-time image capture and surveillance, in combination with an ultrasonic sensor for detecting obstacles and closeness awareness. Equipped with AI/ML algorithms for gesture recognition and wireless connectivity via Wi-Fi, the system supports rapid response and remote monitoring using a mobile app. The software uses real-time notifications, image streaming, and auto-decision-making to enhance users' mobility and safety, especially that of the blind and visually impaired.
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Tahreem et al. (2025) studied this question.
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