V-Safe-Anywhere: Empowering Women's Safety With Wearable AI and IoT Technology

Literature Survey

In Recent literature survey, (Bhardwaj and Aggarwal, 2014) presents Suraksha as an independent device activated through voice, switch, or shock/force. The voice trigger identifies the victim's voice, sending distress messages automatically. The switch functions as a straightforward on/off trigger. In the case of shock/force, when thrown, the device utilizes a force sensor to relay the victim's location to family and friends. (Akram et al., 2019) proposed an IoT safety device which employs fingerprint-based connectivity for women's security, activating alerts to nearby contacts and police when unsafe conditions are detected. It incorporates a self-defense shockwave generator and features like group messaging and audio recording. Additionally, a dedicated mobile app aids in locating safe places from the victim's current position, facilitating quick access to secure areas.

(Vijaylashmi et al., 2015) proposed a women's self-defense system which get triggered by a switch, instantly sending the victim's location and playing a prerecorded alert message through a speech circuit. (Monisha et al.,2016) propose the FEMME device which was equipped with an android application. It sends SOS messages, records audio and video as incident evidence, and includes a module detecting hidden cameras via a radio frequency receiver, identifying electromagnetic waves emitted by spy cameras. (Kumar et al., 2017) introduced a wristwatch device based on the GEOFENCE concept, activating the application within specific areas. It enables two-way communication for the victim to reach out to family or friends. Additionally, the device allows the woman to activate a loud buzzer on the recipient's end, even if their device is in silent mode. (Sogi et al., 2018) had introduced SMARISA, a portable women's safety device with hardware including Raspberry Pi Zero, a camera, buzzer, and an activation button. Initiated by the victim, it retrieves the current location and captures the attacker's image, sending both to the police or predefined emergency contacts through the victim's smartphone.