Intelligent System-Based Stun Gloves for Women's Protection

Subham Kumar Verma*, Khadim Moin Siddiqui**, Udai Raj Tiwari***, Sandhya Shrivastava****, Utkarsh Rai*****, Jayati Vaish******
*-****** Department of Electrical Engineering, Shri Ramswaroop Memorial College of Engineering and Management, Lucknow, India.
Periodicity:January - June'2023
DOI : https://doi.org/10.26634/jaim.1.1.19167

Abstract

In recent times, the security of women and girls has become a major concern in urban areas in many countries. To assist with settling this issue, this paper proposes a Global Positioning System (GPS)-based Stun Gloves for women with many safety techniques. The basic operation of this prototype design is that whenever women detect danger, they can simply press the gadget's ON button. When the gadget becomes active, it will track the online position of women using GPS and send an emergency message using the Global System for Mobile Communications (GSM) to the currently enlisted portable number and the police control room. These security Stun Gloves have both an alarm and a shock provider circuit. The heartbeat rate and temperature are also shown on a connected Liquid Crystal Display (LCD). The heartbeat sensor can detect any unusual heart rate patterns and send the woman's current location via GPS to the rescue team or pre-registered mobile number in the form of a Short Message Service (SMS). Likewise, in the case of self-protection, this gadget is incorporated with a shock generator. This safety precaution can be taken by women in case of any emergency crisis, which a female can use against a person. The main benefit of the design of Stun Gloves is that this gadget is compact and easy to use by any woman.

Keywords

Women Protection System, Emergency Pushbutton, GPS Tracker, Self-Defense, Stun-Gloves, Buzzer, Temperature Sensor, Heart Rate Sensor.

How to Cite this Article?

Verma, S. K., Siddiqui, K. M., Tiwari, U. R., Shrivastava, S., Rai, U., and Vaish, J. (2023). Intelligent System-Based Stun Gloves for Women's Protection. i-manager’s Journal on Artificial Intelligence & Machine Learning, 1(1), 28-33. https://doi.org/10.26634/jaim.1.1.19167

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