Project Raksha is a conceptual algorithm designed to enhance women's safety in various environments. This README outlines the proposed features and considerations for potential future development, focusing on the algorithmic aspects rather than mobile application implementation.
- Secret Code Recognition: Develop an algorithm to recognize a pre-set secret code from voice input.
- Emergency Alert Generation: Create an algorithm to generate SOS messages with current and live location data.
- Continuous Location Tracking: Design an algorithm for efficient, continuous location tracking until a safety confirmation is received.
- Point-Based System: Develop an algorithm to evaluate routes based on safety landmarks:
- Police Station: +10 points
- Mid-Traffic Area: +8 points
- Well-Lit Streets: +7 points
- Route Optimization: Create an algorithm to select the route with the highest safety score while minimizing distance.
- Dynamic Route Adjustment: Design an algorithm to update route recommendations based on real-time safety data.
- Data Aggregation: Develop an algorithm to collect and process user-reported safety information.
- Safety Score Calculation: Create an algorithm to dynamically adjust safety scores based on incidents, time of day, and other factors.
- Proximity Calculation: Design an algorithm to efficiently determine nearby users for targeted alerts.
- Alert Priority System: Develop an algorithm to prioritize and distribute emergency alerts effectively.
- Voice Recognition Accuracy: Develop algorithms robust enough to handle various accents and dialects.
- Efficient Background Processing: Design algorithms that can run efficiently with minimal resource consumption.
- Data Integration: Create algorithms to effectively integrate and process data from multiple sources for safety scoring.
- Scalability: Develop algorithms capable of handling large volumes of concurrent users and data points.
- Data Anonymization: Design algorithms to process and store data in an anonymized format.
- False Positive Reduction: Develop algorithms to minimize false SOS triggers while maintaining sensitivity.
- Machine Learning Integration: Consider incorporating machine learning algorithms for improved route suggestion and safety scoring over time.
- Graph Theory Application: Utilize graph theory algorithms for efficient route calculation and optimization.
- Predictive Safety Analysis: Develop algorithms to predict potentially unsafe areas based on historical and real-time data.
- User Behavior Learning: Create algorithms to learn and adapt to individual user patterns for more personalized safety recommendations.
Please Note: Project Raksha is currently in the conceptual stage, focusing on algorithm development. No actual implementation or mobile application development has begun. This README serves as an outline of the proposed algorithmic features and considerations for potential future development.