Donald Levi Tryon
This is a review of asset management systems and their implementations of sensor and artificial intelligence. There are many ways to implement management systems to help track the life cycle of assets within an organization. These systems can be upgraded with the use of sensors to collect live parameters of the asset’s current conditions to analyze their current state of operation. From here, the conditional state of operations should engage an action from the organization’s business model to cause an event. There are examples offered in this paper from alternative research that depicts the benefits of implementation of both sensors and artificial intelligence algorithms within the organizations. This is an overall review of how these interactions can be processed and implemented. Future studies will need to be conducted in the areas of methods and processes, in particular, in order to integrate a generic model for sensors and artificial intelligence into successful asset management systems.
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