Intelligent lighting system with predictive maintenance scheduling and method of operation thereof

1. A lighting system, comprising:

at least one controller 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;

determine a lighting system failure trend using the logging data;

derive, using the lighting system failure tread; at least one complex feature 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 predicted component failure;

model predicted component failure in accordance with the at least one complex feature;

store the model in a memory; and

wherein the lighting system further comprises a plurality of lamps, 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, wherein the controller is further configured to form a cluster of at least two of the predicted lamp failures in accordance with geophysical location and predicted failure times of corresponding lamps, and wherein 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.

2. The system of claim 1 , wherein the controller is further configured to render the modeled predicted component failures on a display of the lighting system.

3. The system of claim 1 , wherein the controller is further configured to obtain the lighting logging data from at least one of a lamp electrical portion, a system operating information portion, sensors, an installation configuration portion, a weather information portion, a traffic portion, and a crime portion.

4. The lighting system of claim 1 , wherein the at least one controller which is further configured to derive at least one informative data feature, using the at least one complex feature, to predict operating performance of the lighting system, wherein the at least one informative data feature includes a polynomial having a degree of 2 and the at least one complex feature includes at least one of a quadratic voltage trend of the lamp at specific points in time, a quadratic trend of the number of times the lamp attempts to ignite before another ignite instruction is given, and quadratic trend of the number of times the lamp spontaneously extinguishes.

5. A method of determining performance of a lighting system, the method performed by at least one controller of the lighting system and comprising acts of:

obtaining lighting logging data comprising feature information related to features of the lighting system and obtained from a plurality of information sources;

determining lighting system failure trend using the logging data;

deriving, using the lighting system failure trend, at least one complex feature to predict at least one component failure in the lighting system at a future time;

selecting logging data from the plurality of information sources to calculate the predicted component failure;

modeling predicted component failures in accordance with the at least one complex feature;

storing the model in a memory; and

wherein the lighting system further comprises a plurality of lamps, 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, the method further comprising acts of:

clustering at least two of the predicted lamp failures into a cluster in accordance with geophysical locations and predicted failure times of corresponding lamps; and

scheduling maintenance to replace the lamps of the cluster at a determined time that is determined to be optimal with respect to the cluster in accordance with the model.

6. The method of claim 5 , further comprising an act of rendering the predicted component failures on a display of the lighting system.

7. The method of claim 5 , further comprising an act of obtaining the lighting logging data from at least one of a lamp electrical portion, a system operating information portion, sensors, an installation configuration portion, a weather information portion a traffic portion, and a crime portion.

8. The method of claim 5 , wherein the modeling step includes deriving at least one informative data feature, using the at least one complex feature, to predict operating performance of the lighting system, wherein the at least one informative data feature includes a polynomial has a degree of 2 and the at least one complex feature includes at least one of a quadratic voltage trend of the lamp at specific points in time, a quadratic trend of the number of times the lamp attempts to ignite before another ignite instruction is given, and quadratic trend of the number of times the lamp spontaneously extinguishes.

9. The computer program of claim 8 , wherein the model includes deriving at least one informative data feature, using the at least one complex feature, to predict operating performance of the lighting system, wherein the at least one informative data feature includes a polynomial has a degree of 2 and the at least one complex feature includes at least one of a quadratic voltage trend of the lamp at specific points in time, a quadratic trend of the number of times the lamp attempts to ignite before another ignite instruction is given, and quadratic trend of the number of times the lamp spontaneously extinguishes.

10. A computer program stored on a computer readable memory medium, the computer program configured to determine performance of a lighting system, the computer program comprising:

a program portion configured to:

obtain lighting logging data comprising feature information related to features of the lighting system and obtained from a plurality of information sources;

determine a lighting system failure trend using the logging data;

derive, using the lighting system failure tread; at least one complex feature 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;

store the model in a memory; and

wherein the lighting system further comprises a plurality of lamps, 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, wherein the program portion is further configured to cluster at least two of the predicted lamps failures to form a cluster in accordance with geophysical locations and predicted failure times of corresponding lamps, wherein the program portion 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 in accordance with the model.

11. The computer program of claim 10 , wherein the program portion is further configured to render the predicted component failures on a display of the lighting system.

12. The computer program of claim 10 , wherein the program portion is further configured to obtain the lighting logging data from at least one of a lamp electrical portion, a system operating information portion, sensors, an installation configuration portion, a weather information portion, a traffic portion, and a crime portion.