Paper Key : IRJ************931
Author: Omkar Sunil Jadhav,Rutuja Patil,Kaustubh Pardeshi,Padma Iyer,Sagar Mane
Date Published: 09 Nov 2024
Abstract
This review paper examines the integration of artificial intelligence (AI) and Internet of Things (IoT) technologies in optimizing long-distance bike riding experiences, with a focus on routing, cost estimation, and crash detection. As AI and IoT innovations continue to shape transportation and mobility, they offer significant advancements in improving safety, efficiency, and rider experience. The paper explores key techniques such as AI-driven optimal routing algorithms, real-time cost estimation models, and IoT-enhanced crash detection systems, which contribute to the development of a comprehensive solution for long-distance bike riders. These models enable real-time traffic analysis, dynamic route planning, and predictive maintenance, enhancing the overall safety and cost-effectiveness of long-distance biking. Additionally, this review identifies future opportunities for AI and IoT to further personalize rider experiences, integrate with smart infrastructure, and address sustainability concerns in the biking ecosystem. The findings emphasize the potential of AI and IoT to revolutionize biking safety, navigation, and logistics, fostering a new era of connected and intelligent transportation for cyclists.
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