Page 96 - 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
 The backend will leverage a cloud infrastructure (e.g., real-time tracking. Machine learning algorithms will optimize
AWS or Google Cloud) to manage real-time tracking, ride matching and predict potential safety risks based on
user data, and ride analytics. A secure database system historical data. Testing will be conducted using user
will be implemented to store sensitive user and driver feedback to fine-tune the app's performance.
information, ensuring compliance with privacy 3. Evaluation Phase:
regulations such as GDPR.
Once the app is deployed, the evaluation phase will involve
 Machine learning algorithms will be integrated to gathering quantitative and qualitative data. Key performance
optimize ride matching and safety features, such as indicators (KPIs) such as user adoption rates, app usage
predicting peak hours or ensuring driver-passenger frequency, and user ratings for safety features will be
compatibility. analyzed. Surveys and interviews will be conducted with
users (women and parents) to assess their satisfaction,
Research Goals: perceived safety, and overall experience. Statistical analyses
 Evaluating Safety Impact: Assess the effectiveness of will be applied to identify any correlations between app
the integrated safety features in reducing the perceived features and user satisfaction.
risk for women and parents.
4. Optimization Phase:
 User Adoption & Satisfaction: Measure user Based on the evaluation results, the optimization phase will
satisfaction levels regarding the app's convenience, involve refining the app’s features, improving security
security, and usability.
protocols, and enhancing user interfaces. Feedback
 Operational Feasibility: Analyze the operational regarding ride scheduling, driver communication, and child
efficiency of a women-only service, including driver seat functionality will guide adjustments. The goal is to
recruitment, service scalability, and geographical continuously enhance the system’s usability, safety
coverage. measures, and scalability.
Through this work, we aim to provide a comprehensive Components of the Research Model:
transport solution that prioritizes the safety and convenience 1. User-Centered Design:
of women and parents. By integrating cutting-edge  Goal: To ensure that the app meets the real needs of
technology and user-centered design principles, the women and parents, ensuring safety, convenience, and
proposed system will contribute to the development of a ease of use.
more secure, inclusive, and trustworthy transportation
 Methods: Surveys, user interviews, focus groups to
ecosystem.
gather insights on the most critical features such as
IV. PROPOSED RESEARCH MODEL emergency response times, trust in drivers, and the need
The proposed research model aims to evaluate the for child-friendly vehicles.
effectiveness and feasibility of a women-only cab app 2. Safety and Security Features:
designed with enhanced safety features tailored for parents.  Goal: To validate the effectiveness of the enhanced
This model is based on a combination of technical safety features such as GPS tracking, verified drivers,
innovation, user-centered design, and empirical analysis. It panic buttons, and emergency contact sharing.
explores key components including safety, user experience,
system efficiency, and social impact, structured into four  Methods: Analysis of safety incident rates before and
main phases: design, implementation, evaluation, and after implementing the app and user feedback regarding
optimization. their perceived security during rides.
1. Design Phase: 3. System Performance and Efficiency:
The design phase focuses on identifying the user needs,  Goal: To measure the app’s operational efficiency,
defining core features, and conceptualizing the app’s focusing on real-time ride tracking, ride matching, and
architecture. User research through surveys, focus groups, scalability.
and interviews will be conducted to gather insights from  Methods: System logs, backend data, and machine
women and parents regarding their safety concerns and learning outcomes will be evaluated to optimize the
transportation requirements. Based on these insights, the
key features such as verified female drivers, real-time GPS ride-matching algorithm and predict potential delays or
tracking, child seat options, and emergency alert systems will safety concerns.
be incorporated into the app. 4. Impact on User Experience:
 Goal: To assess the overall user satisfaction and
2. Implementation Phase: adoption of the women-only cab service.
The implementation phase focuses on the development and
deployment of the women-only cab app. A hybrid mobile  Methods: User satisfaction surveys, NPS (Net Promoter
application will be created using technologies like React Score), app usage data, and social media monitoring will
Native, enabling cross-platform compatibility. The backend be employed to evaluate how well the app addresses the
will be developed using cloud computing services (e.g., AWS, needs of women and parents.
Google Cloud) to manage user data, ride information, and

IJTSRD | Special Issue on Emerging Trends and Innovations in Web-Based Applications and Technologies Page 86