https://www.prothomalo.com/bangladesh/62i23tdgc0
https://www.facebook.com/thedailycampusbd/videos/676134407671849
https://www.tbsnews.net/features/panorama/quest-affordable-dress-detects-sexual-harassment-654910
Sexual harassment remains a pressing issue worldwide, posing a threat to the safety and well-
being of women in various environments. In recent years, the advent of Internet of Things (IoT)
devices and machine learning (ML) techniques has opened up new possibilities for addressing
this problem. This paper proposes a novel ML-supported IoT device designed specifically for
women’s self-security system to reduce sexual harassment.
The designed device integrates advanced ML algorithms with IoT technology to provide women
with a reliable and effective means of enhancing their personal safety. The device incorporates
various sensors such FSR, GPS collect real-time data on the users movements, location. This
data is then processed by ML algorithms to detect and identify potential threats or instances of
sexual harassment. To improve accuracy and responsiveness, the ML algorithms are trained on
large datasets comprising diverse scenarios of sexual harassment incidents. By leveraging
techniques such as deep learning and pattern recognition, the device can analyze the collected
data and classify it into different categories, such as unwanted physical contact, verbal
harassment, or stalking. Upon detection of a potential threat, the device employs multiple
communication channels to alert the user, as well as trusted contacts or authorities and nearest
police station with live location.
These communication channels can include mobile notifications, SMS alerts, or even automated
emergency calls to nearest three police stations. Additionally, the device is equipped with a panic button that the user can
activate in critical situations to seek immediate help. The user can activate and deactivated the dress using mobile app. Beside this user can add multiple trusted contracts to this app for emergency help.
Furthermore, the designed device
incorporates a cloud-based backend system that facilitates data storage, analysis, and continuous
model updates. This enables the device to adapt and improve its detection capabilities over time,
enhancing its effectiveness in identifying and addressing sexual harassment incidents.