Systems and methods for aggregating classifications of predictive operations of a machine may include one or more sensors in communication with a processor. Such systems and methods may be implemented to receive on-board machine time series data, process the data, segment the processed data, resolve the segmented data, and characterize the segmented data. Additionally, such systems and methods may be implemented to determine profile percentage breakdowns of a machine, performance reports, and productivity reports, and inform composite work cycles.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system for aggregating classifications of predictive operations of a machine, the system comprising: a processor; one or more sensors in communication with the processor; a pre-processing module associated with the one or more sensors and executed by the processor, the pre-processing module receiving on-board machine time series data from the one or more sensors; an operation classifier module associated with the pre-processing module and executed by the processor, the operation classifier module receiving processed data from the pre-processing module; an application resolver module associated with the operation classifier module and executed by the processor, the application resolver module receiving machine operation predictions from the operation classifier module; a characterizer module associated with the operation classifier module and executed by the processor, the characterizer module receiving the machine operation predictions from the operation classifier module; an application profile module associated with the application resolver module and executed by the processor, the application profile module receiving one of cycle data and application data from the application resolver module; a reports module associated with the characterizer module and the application resolver module and executed by the processor, the reports module receiving severity and performance data from the characterizer module and receiving the one of cycle data and application data from the application resolver module; and a composite work cycle module associated with the characterizer module and executed by the processor, the composite work cycle module receiving the severity and performance data from the characterizer module. 2. The system of claim 1, wherein the pre-processing module includes at least one function for processing the on-board machine time series data, the at least one function processes the on-board machine time series data by one of filtering, performing pulse-width demodulation, computing window-based statistics, calculating integrals, calculating derivatives, performing map lookup, and computing physics-based calculations. 3. The system of claim 1, wherein the machine operation predictions are expressed as time series sequences. 4. The system of claim 1, wherein the machine operation predictions are expressed as series of operation-labeled time periods. 5. The system of claim 1, wherein the machine is an earth-moving, construction, or agricultural machine and the machine operation predictions represent one of dig, swing, dump, propel, idle, travel, load, carry, spread, push, and rip. 6. The system of claim 1, wherein the operation classifier module receives the on-board machine time series data from the one or more sensors. 7. The system of claim 1, wherein the characterizer module receives the on-board machine time series data from the one or more sensors and receives the processed data from the pre-processing module. 8. A method for aggregating classifications of predictive operations of a machine, the method comprising: receiving, from one or more sensors of the machine, on-board machine time series data using a computer processor; processing the on-board machine time series data into processed data using the computer processor; segmenting the processed data into machine operation predictions using the computer processor; resolving the machine operation predictions into one of cycle data and application data using the computer processor; characterizing the machine operation predictions into severity measures and performance measures using the computer processor; determining profile percentage breakdowns of what the machine was doing using the computer processor; determining performance reports and productivity reports using the computer processor; and informing a composite work cycle using the computer processor. 9. The method of claim 8, wherein the step of determining profile percentage breakdowns includes aggregating the one of cycle data and application data. 10. The method of claim 8, wherein the step of determining profile percentage breakdowns includes aggregating the machine operation predictions. 11. The method of claim 8, wherein the step of determining performance reports and productivity reports includes aggregating the one of cycle data and application data, the severity measures, and the performance measures. 12. The method of claim 8, wherein the step of informing a composite work cycle includes processing the severity measures and performance measures. 13. The method of claim 8, wherein the machine operation predictions are expressed as one of time series sequences and series of operation-labeled time periods. 14. The method of claim 8, wherein the step of processing the on-board machine time series data into processed data includes one of filtering, performing pulse-width demodulation, computing window-based statistics, computing sequential logic, computing combinatorial logic, calculating integrals, calculating derivatives, performing a map lookup, and computing physics-based calculations. 15. The method of claim 8, wherein the machine operation predictions represent one of dig, swing, dump, propel, idle, travel, load, carry, spread, push, and rip. 16. A non-transitory, computer readable medium having thereon computer-executable instructions for aggregating classifications of predictive operations of a machine, the instructions comprising: instructions for receiving, from one or more sensors of the machine, on-board machine time series data; instructions for processing the on-board machine time series data into processed data; instructions for segmenting the processed data into machine operation predictions; instructions for resolving the machine operation predictions into one of cycle data and application data; instructions for characterizing the machine operation predictions into severity measures and performance measures; instructions for determining profile percentage breakdowns of what the machine was doing; instructions for determining performance reports and productivity reports; and instructions for informing a composite work cycle. 17. The non-transitory, computer readable medium having thereon computer-executable instructions of claim 16, wherein the instructions for determining profile percentage breakdowns includes aggregating the one of cycle data and application data. 18. The non-transitory, computer readable medium having thereon computer-executable instructions of claim 16, wherein the instructions for determining profile percentage breakdowns includes aggregating the machine operation predictions. 19. The non-transitory, computer readable medium having thereon computer-executable instructions of claim 16, wherein the instructions for determining performance reports and productivity reports includes aggregating the one of cycle data and application data, the severity measures, and the performance measures. 20. The non-transitory, computer readable medium having thereon computer-executable instructions of claim 16, wherein the instructions for informing a composite work cycle includes processing the severity measures and the performance measures.