Personalized and Safe Route Planning for Asthma Patients Using Real-Time Environmental Data
Journal:
arXiv
Published Date:
Dec 13, 2024
Abstract
Asthmatic patients are very frequently affected by the quality of air,
climatic conditions, and traffic density during outdoor activities. Most of the
conventional routing algorithms, such as Dijkstra's algorithm, usually fail to
consider these health dimensions, hence resulting in suboptimal or risky
recommendations. Here, the health-aware heuristic framework is presented that
shall utilize real-time data provided by the Microsoft Weather API. The
advanced A* algorithm provides dynamic changes in routes depending on air
quality indices, temperature, traffic density, and other patient-related health
data. The power of the model is realized by running simulations in city
environments and outperforming the state-of-the-art methodology in terms of
recommendation accuracy at low computational overhead. It provides
health-sensitive route recommendations, keeping in mind the avoidance of
high-risk areas and ensuring safer and more suitable travel options for
asthmatic patients.
