A method of utility pole integrity assessment by distributed fiber optic sensing/distributed acoustic sensing (DFOS/DAS) employing existing telecommunications fiber optic cable as a sensor. The fiber optic cable is suspended aerially from a plurality of utility poles and a machine learning model is developed during training by mechanically exciting the utility poles. Once developed, and in sharp contrast to the prior art, the machine learning model—in conjunction with DFOS/DAS operation—determines an integrity assessment for a plurality of the utility poles aerially suspending the fiber optic cable from a mechanical impact of a single pole.