A computer-implemented method, comprising: collecting, via one or more sensors (112, 114, 116, 118) associated with a vehicle and/or at least one tire of a plurality of tires supporting the vehicle, first data (136, 138, 310, 910) corresponding to real-time kinetics of the vehicle and/or the at least one tire associated with the vehicle; locally processing the first data (136, 138; 310; 910) to generate second data (320, 330, 930) as a reduced subset of the first data (136, 138; 310; 910), said second data (320, 330; 930) representative of the first data (136, 138; 310; 910) and comprising any one or more predetermined features extracted therefrom; processing the second data (320, 330; 930) to estimate a current tire wear characteristic in real-time for the at least one tire; and selectively providing real-time feedback based on the estimated current tire wear characteristic, wherein the first data (136, 138; 310; 910) is processed via a computing system onboard the vehicle, the method further comprising: selectively transmitting the second data (320, 330; 930) to a remote computing system (130, 140) via a communications network; and via the remote computing system (130, 140), processing the second data (320, 330; 930) to estimate the wear characteristic for the at least one tire characterized in that the second data (320, 330; 930) comprises a plurality of sequential data frames, each data frame comprising a multidimensional histogram of forces (F x, F y, F z) associated with the vehicle and/or the at least one tire. collecting, via one or more sensors (112, 114, 116, 118) associated with a vehicle and/or at least one tire of a plurality of tires supporting the vehicle, first data (136, 138, 310, 910) corresponding to real-time kinetics of the vehicle and/or the at least one tire associated with the vehicle; locally processing the first data (136, 138; 310; 910) to generate second data (320, 330, 930) as a reduced subset of the first data (136, 138; 310; 910), said second data (320, 330; 930) representative of the first data (136, 138; 310; 910) and comprising any one or more predetermined features extracted therefrom; processing the second data (320, 330; 930) to estimate a current tire wear characteristic in real-time for the at least one tire; and selectively providing real-time feedback based on the estimated current tire wear characteristic, wherein the first data (136, 138; 310; 910) is processed via a computing system onboard the vehicle, the method further comprising: selectively transmitting the second data (320, 330; 930) to a remote computing system (130, 140) via a communications network; and via the remote computing system (130, 140), processing the second data (320, 330; 930) to estimate the wear characteristic for the at least one tire characterized in that the second data (320, 330; 930) comprises a plurality of sequential data frames, each data frame comprising a multidimensional histogram of forces (F x, F y, F z) associated with the vehicle and/or the at least one tire. selectively transmitting the second data (320, 330; 930) to a remote computing system (130, 140) via a communications network; and via the remote computing system (130, 140), processing the second data (320, 330; 930) to estimate the wear characteristic for the at least one tire characterized in that the second data (320, 330; 930) comprises a plurality of sequential data frames, each data frame comprising a multidimensional histogram of forces (F x, F y, F z) associated with the vehicle and/or the at least one tire.