A Comprehensive Review of SHIELD: Smart Handler for Incident Event and Location Detection

In today’s world, women face safety challenges everywhere, whether it is on the street, at home or in unfamiliar places. Laws and social programs are there to protect them, but these measures are not always helpful to prevent women in dangerous situations, especially when the women is alone or in new environment. Traditional safety tools often reacts when something has already happened which is not enough. Now with the rise of smartphones, we have various powerful tools that can help us. Modern phones come with cameras, microphones, sensors and also fast processing power. These features help to create an application that can act quickly in emergency, giving the women support when needed. SHIELD is designed to help women in panic situations. It quietly works in a background, track user’s location, records both audio and video, and sends the alert to the trusted contacts simultaneously. The idea is to help women in stressful situations, without complicating the process. The main goal of the SHIELD is to save time in emergencies because even a few seconds can make a big difference. By automatically gathering evidences and sending alerts the application increases the chances of getting help quickly. Unlike other applications which offers only one feature, SHIELD combines multiple functions like live location tracking, audio-video recording, and notifications into a single, easy-to-use platform. The application also works when there is no internet and is designed to minimize battery usage. Due to which it can function reliably in different situations. SHIELD gives women a dependable tool to feel safer in their everyday lives.

LITERATURE REVIEW

In recent years, research on mobile and wearable technologies has increasingly focused on enhancing personal safety, particularly for women. Usability and effectiveness have been identified as critical factors in the adoption of such application. For instance, Sharma et al. [1] conducted a study on mobile safety applications, showing that simple interfaces, quick access to emergency functions, and minimal time response load are essential for real-life emergency scenarios. Building on this, Agarwal and Kumar [2] proposed a shake- based safety application that triggers emergency alerts through intuitive gestures, allowing users to discreetly request help during urgent situations. This paper explored the motion and sensor’s-based techniques used in women safety application. Patel et al. [3] evaluated the performance of motion sensors in women’s safety applications, demonstrating their ability to detect sudden movements indicative of distress. Similarly, Singh et al. [4] this paper gives overview of how voice command is recognised. It also highlights the importance of voice activated response in emergency situation. Expanding on automated detection, Das and Mohapatra [5] developed a keyword-based alert system using natural language processing (NLP), allowing the application to recognize distress words in spoken input and initiate alerts automatically. Accurate location tracking remains a cornerstone of safety solutions. M. Pathak, V. Sinha et al. [6] developed a real-time location- sharing framework to ensure that trusted contacts receive timely and precise information. Misra and Rajput [7] addressed the challenges of GPS accuracy in urban environments, suggesting the need for hybrid or advanced localization techniques to improve reliability. Additional research emphasizes geofencing and safe-zone alerts, which proactively notify guardians if users enter potentially unsafe areas. Wearable devices integrated with GSM and IoT technologies provide a discreet and continuous layer of protection. Roy and Ghosh [8] proposed a GSM-based wearable capable of sending immediate alerts even without internet access. while Jain and Srivastava [9] demonstrated IoT-enabled wearables that monitor safety parameters in real-time. R. Tripathi, S. Gupta et al. [10] further enhanced wearable functionality by integrating heart-rate monitoring to trigger automatic alerts during abnormal readings, highlighting the potential of physiological monitoring in emergency scenarios. Recent advances also include AI-based predictive analytics, which analyse patterns in movement, voice stress, and physiological signals to anticipate potential threats before they escalate. Multi-modal integration of audio, video, GPS, and biometric data is increasingly being adopted to provide more reliable and actionable safety information. Cloud-based platforms and real-time data processing enable emergency contacts or authorities to respond quickly, significantly improving response effectiveness. Emerging approach also focus on encouraging proactive safety behaviour through gamification and behavioural nudges. Regular reminders, safety tips, or incentives for check-ins help users maintain vigilance, while social integration features enable trusted networks and community reporting, creating collective awareness and faster response during emergencies. Overall, the reviewed studies indicate a clear trend towards multi- functional, intelligent safety solutions that combine sensors, location tracking, automated alerts, predictive analytics, and social integration. While existing application address specific safety aspects, integrating these diverse features into a cohesive, user-friendly platform remains a critical area for future research and development, exemplified by systems like SHIELD.

METHODOLOGY

The development of SHIELD follows structured approach designed to ensure the application integration with the real- world safety requirements while maintaining the usability and reliability. The methodology has requirement analysis, System design, implementation strategy and validation procedure.

Fig. 3.1 System Architecture