Data Science and Intelligent Computing Techniques
Predictive Maintenance Strategies for Internet of Things (IoT) Systems in Transportation
Authors: Satendra Ch. Pandey and Vasanthi Kumari P
Publishing Date: 22-10-2023
ISBN: 978-81-955020-2-8
Abstract
The rapid integration of Internet of Things (IoT) technologies into transportation systems has paved the way for transformative advancements in efficiency, safety, and operational management. In this context, Predictive Maintenance (PdM) strategies have emerged as a crucial paradigm, offering the potential to revolutionize maintenance practices in the transportation sector.Predictive maintenance strategies for IoT systems in transportation offer a promising solution to improve operational efficiency, reduce costs, enhance safety, and prolong the life of assets. As IoT technology continues to advance, the transportation industry is poised to benefit from increasingly accurate and reliable predictive maintenance solutions. Predictive maintenance in IoT-enabled transportation systems represents a transformative approach to maintenance management, leveraging data and analytics to ensure the continued reliability and safety of vehicles and infrastructure while optimizing operational costs. One critical application is predictive maintenance, which leverages IoT data to preemptively identify and address maintenance needs in vehicles and infrastructure.
Keywords
PdM, IoT
Cite as
Satendra Ch. Pandey and Vasanthi Kumari P, "Predictive Maintenance Strategies for Internet of Things (IoT) Systems in Transportation", In: Satyasai Jagannath Nanda and Rajendra Prasad Yadav (eds), Data Science and Intelligent Computing Techniques, SCRS, India, 2023, pp. 525-532. https://doi.org/10.56155/978-81-955020-2-8-49