Year: 2026
Type: article
Abstract: As rising crime rates and delayed emergency responses continue to pose serious threats to personal safety, especially in urban and semi-urban regions, the need for intelligent and reliable safety systems has become a major concern. Conventional personal safety solutions often depend on manual user interaction, stable network connectivity, and continuous location availability, which can reduce their effectiveness during real-world emergency situations. This project presents EcoShield, an AI-driven personal safety platform designed to enhance emergency responsiveness, situational awareness, and user protection. The proposed system integrates real-time location tracking, geospatial crime data visualization, and voice-based emergency detection to automatically trigger alerts during critical situations. By leveraging mobile sensing technologies and intelligent automation, EcoShield ensures timely communication with emergency contacts even when precise location data is partially unavailable. The system provides a secure and user-friendly interface that supports proactive risk awareness through danger-zone mapping and safe route guidance. Experimental testing and simulated evaluations demonstrate noticeable improvements in alert reliability, response time, and overall system effectiveness. This project contributes toward improving personal safety solutions and establishes a foundation for extending intelligent safety systems to broader smart-city and public security applications.
Institution: University of Mumbai
Language: English
Subfield: Automotive Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W7225315964