Page 87 - Emerging Trends and Innovations in Web-Based Applications and Technologies

International Journal of Trend in Scientific Research and Development (IJTSRD) @ www.ijtsrd.com eISSN: 2456-6470
To increase the reach and accessibility of the app, it will be developed for both Android and iOS platforms, with multi-language
support to cater to diverse user groups. Partnerships with local law enforcement agencies and women’s organizations will also
be established to provide additional layers of support and assistance.
Overall, the proposed women-only cab application aims to create a safer, more empowering transportation solution by
combining cutting-edge technology, community engagement, and strategic safety features. This initiative seeks to foster a sense
of independence and confidence among women while addressing the challenges associated with personal safety during travel.
IV. PROPOSED RESEARCH MODEL
The proposed research model for the development of a women-only cab application with real-time tracking and parental
monitoring is structured to address the critical safety challenges faced by women in public and private transportation. The
model follows a systematic approach, integrating technological, social, and operational components to ensure a secure, reliable,
and user-friendly commuting experience for women.
The research model is based on three key pillars: User Safety, Technological Integration, and Operational Efficiency. These
pillars work together to form a holistic solution that not only provides real-time monitoring but also empowers women with
enhanced mobility options.

1. User Safety Features
 Real-Time Tracking: The core component of the model, allowing continuous GPS tracking of rides, which can be shared
with parental figures or trusted contacts for real-time monitoring.
 Parental Monitoring System: A dedicated module that provides live notifications, trip updates, and safety alerts to
guardians, ensuring peace of mind during the ride.
 Emergency Response Mechanisms: Integration of SOS buttons, automated alerts to emergency contacts, and instant
communication with local authorities to provide immediate assistance in distress situations.
 Driver Verification: Strict screening processes, including background checks, driving history analysis, and biometric
authentication, to ensure only verified female drivers are onboarded.
2. Technological Integration
 AI-Powered Risk Assessment: Machine learning algorithms analyze ride patterns, traffic conditions, and location-based
risk factors to suggest safer routes and predict potential risks.
 Geofencing and Route Deviation Alerts: The model includes geofencing capabilities to trigger alerts when a vehicle
deviates from a designated safe zone, ensuring swift action in case of any anomalies.
 Data Encryption and Privacy Protection: Ensuring user data confidentiality through end-to-end encryption, protecting
personal and location information from unauthorized access.
 Cloud-Based Infrastructure: A scalable backend to handle real-time data processing, ride history storage, and secure
access to user preferences.
3. Operational Efficiency
 User-Friendly Mobile Application: A seamless and intuitive interface for booking rides, selecting preferred drivers,
scheduling trips, and accessing safety features effortlessly.
 Automated Ride Matching: An AI-based system to match passengers with the nearest available female drivers while
considering user preferences and past ride history.
 Feedback and Rating System: Continuous improvement through user feedback, allowing riders to report concerns and
rate their experience to maintain service quality.
 Multi-Language Support: The app will cater to a diverse user base by providing multiple language options, enhancing
accessibility and usability.
4. Stakeholder Collaboration
 Partnerships with Law Enforcement: Collaborations with police and emergency services to respond swiftly to distress
signals.

IJTSRD | Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies Page 77