A lighting system, comprising: at least one controller (102, 610) which is configured to: obtain lighting logging data comprising feature information related to features of the lighting system and obtained from a plurality of information sources; derive, by performing a complex feature extraction process, at least one complex feature from the lighting logging data to predict at least one component failure in the lighting system at a future time; select logging data from the plurality of information sources to calculate the predicted component failure; model predicted component failure in accordance with the at least one complex feature; and store the model in a memory (112, 620), wherein the lighting system further comprises a plurality of lamps (106-x), and the modeled predicted component failures comprise predicted lamp failures of two or more lamps of the plurality of lamps and corresponding predicted failure times, characterized in that the controller is further configured to form a cluster of at least two of the predicted lamp failures in accordance with geophysical locations and predicted failure times of corresponding lamps, and in that the controller is further configured to schedule maintenance to replace the lamps of the cluster at a determined time that is determined to be optimal with respect to the cluster. at least one controller (102, 610) which is configured to: obtain lighting logging data comprising feature information related to features of the lighting system and obtained from a plurality of information sources; derive, by performing a complex feature extraction process, at least one complex feature from the lighting logging data to predict at least one component failure in the lighting system at a future time; select logging data from the plurality of information sources to calculate the predicted component failure; model predicted component failure in accordance with the at least one complex feature; and store the model in a memory (112, 620), obtain lighting logging data comprising feature information related to features of the lighting system and obtained from a plurality of information sources; derive, by performing a complex feature extraction process, at least one complex feature from the lighting logging data to predict at least one component failure in the lighting system at a future time; select logging data from the plurality of information sources to calculate the predicted component failure; model predicted component failure in accordance with the at least one complex feature; and store the model in a memory (112, 620), wherein the lighting system further comprises a plurality of lamps (106-x), and the modeled predicted component failures comprise predicted lamp failures of two or more lamps of the plurality of lamps and corresponding predicted failure times, characterized in that the controller is further configured to form a cluster of at least two of the predicted lamp failures in accordance with geophysical locations and predicted failure times of corresponding lamps, and in that the controller is further configured to schedule maintenance to replace the lamps of the cluster at a determined time that is determined to be optimal with respect to the cluster.