Ensuring Women's Safety Using Wearable Technology (AI and IoT): AI Tools and Applications for Women's Safety

Introduction

Women's safety is a huge global concern. Whether a woman is at home, on the job, or somewhere else, her safety is vital. While women continue to achieve greatness in many fields, they nevertheless face obstacles when it comes to social harassment. IoT, embedded systems, augmented reality, machine learning, artificial intelligence, and Android mobile apps are just a few of the innovative technologies that are relying on woman security systems. Women still face difficulties despite the rapid advancements in many areas of technology and the creation of numerous gadgets. This chapter suggests a safety measure to shield women from dangerous circumstances such as harassment, sexual assault, kidnappings, and sense less deaths. This chapter introduces an AI method that can increase safety and security. The integration of artificial intelligence (AI) technology aims to combat criminal activities, identify offenders, and give women and children with immediate support in times of emergency. The gadget is portable, so users can take it with them anywhere they perceive a threat. IoT is used to pinpoint the victim's precise location, allowing for quicker protection of the women. The voice is processed by voice recognition AI technology, which converts it into a digital signal that is displayed on the wristwatch. YOLOv6, a deep learning algorithm, can be used to recognize a victim's image. IoT has the capacity to satisfy all of our needs before we even realize what we will eventually need. Voice recognition uses an individual's tone, pitch, and accent to determine who they are. Additionally, among the individuals identified, the victim is identified using the deep learning model. Accurate victim data is provided by the deep learning model, shielding women from a variety of risks.In order to protect women, Safe-Guard is a ground-breaking wearable gadget that uses cutting-edge artificial intelligence (AI) and Internet of Things (IoT) technology. Safe-Guard monitors the user's whereabouts via geofencing and real-time location monitoring, sending out alarms whenever the wearer enters potentially dangerous regions. With a single touch, the SOS button acts as an instant lifeline, sending emergency notifications to pre-identified contacts or services. Additionally, Safe-Guard's voice-activated assistance feature makes it possible to subtly trigger distress signals by voice commands, guaranteeing that aid is always accessible, even when hands-free. The device's ability to capture both audio and video can be used to record situations and provide evidence for future investigations or legal processes. In order to identify risks, smart alert algorithms evaluate a variety of data sources and integrate with smart home appliances.

Figure 1.

Process to protect women from a danger

Although women's safety system with machine learning algorithms addresses some IoT network issues, significant research issues still need to be addressed through women's safety. The real-time-based training dataset is required to achieve high accuracy of machine learning models for making efficient women's safety systems. There is a risk that the device or system might go under the wrong prediction or may stop working due to technical reasons on time. The readings of sensors may change due to any reasons it can be due to bad health, weather or any technical issue. The proposed system is free of human interaction as compared to the existing systems but still, the proposed system needs a physical attachment to the human body. There are chances to lose the device by the victim. If the decision-making step goes wrong due to uneven readings of sensors it will give wrong information to the guardian.

Figure 2.

Taxonomy of IoT-based women’s safety devices