The emergence and growing adoption of Machine Learning (ML) and Artificial Intelligence (AI) across domains is driving new and innovative approaches toward improving system performance and efficiency. The off-highway segment is no exception and is already leveraging a range of AI/ML tools and models.
The paper talks about implementing virtual sensors in Off-Highway machines covering unique limitations & challenges of virtual sensors, advantages of implementing virtual sensors, and enhanced features and greater flexibility compared to traditional physical sensors. Implementing virtual sensors requires careful consideration of the algorithms used to train the data and the data used to train the model. Despite these challenges, the benefits of virtual sensors, including scalability and adaptability, make it a valuable tool in improving the efficiency of the system.