The present provides a method for condition monitoring a vehicle and for alerting of irregularities/defects.
The method comprises the steps of: monitoring sensory data from multiple sensors; collecting data continuously from said sensors; processing said data; applying machine learning algorithms at an online remote server configured to incorporate all the acquired sensory data and providing an output sending/receiving a notification of a malfunction event; wherein applying said machine learning algorithms comprising applying at least one of the following models: (d) model I—trained to learn the behavior of said acquired sensory data and to identify malfunction(s) based on said sensory data; (e) model II—trained to learn the behavior of said acquired sensory data and to identify an exceptional event based on said sensory data and optionally based on human feedback; and (f) model III—trained to learn the behavior of said acquired sensory data and to identify upcoming malfunctions based on said sensory data.