System and method for optimizing utility pipe sensors placement using artificial intelligence technology

A computer-implemented method and system for determining placement of a sensor component on a utility pipe. Data relating to the utility pipe is inputted which is processed to generate one or more variables. One or more models are trained, via the one or more variables, to produce an output indicative of a likelihood of failure variable associated with the utility pipe from each model. The outputs from all models are preferably combined into an ensemble output indicative of a likelihood of failure associated with the utility pipe. A consequence of failure variable associated with the utility pipe is determined preferably utilizing a plurality of weighted variables. A sensor placement determinative variable is then determined contingent upon the ensemble output and the consequence of failure variable associated with the utility pipe. Feedback data is then provided indicative of physical placement of one or more sensor components associated with the utility pipe based at least in part on the sensor placement determinative variable.