A system for the determination of an output characteristic of a light source, the system comprising: a) a light collector; b) a non-spectral light detector configured to produce a signal from light collected by the light collector, wherein the non-spectral light detector measures the integrated intensity at all wavelengths of light; and c) a computer programmed with a neural network trained with the spectral profiles of a plurality of light sources having a spectrum independent of output intensity and including the light source to provide the output characteristic of the light source from the signal produced by the non-spectral light detector, wherein the neural network comprises a plurality of input nodes, wherein each input node is configured to contain at least one data point; a plurality of hidden nodes grouped in a plurality of layers, wherein each of the plurality of hidden nodes received as input all of the at least one data points from the plurality of input nodes; and an output node, wherein the plurality of hidden nodes and output node are trained with the spectral profiles of a plurality of light sources including the light source, wherein the output characteristic is output power, output energy, output flux, a calculated spectrum, irradiance, calculated light source age, or calculated exposure time. a) a light collector; b) a non-spectral light detector configured to produce a signal from light collected by the light collector, wherein the non-spectral light detector measures the integrated intensity at all wavelengths of light; and c) a computer programmed with a neural network trained with the spectral profiles of a plurality of light sources having a spectrum independent of output intensity and including the light source to provide the output characteristic of the light source from the signal produced by the non-spectral light detector, wherein the neural network comprises a plurality of input nodes, wherein each input node is configured to contain at least one data point; a plurality of hidden nodes grouped in a plurality of layers, wherein each of the plurality of hidden nodes received as input all of the at least one data points from the plurality of input nodes; and an output node, wherein the plurality of hidden nodes and output node are trained with the spectral profiles of a plurality of light sources including the light source, wherein the output characteristic is output power, output energy, output flux, a calculated spectrum, irradiance, calculated light source age, or calculated exposure time. wherein the neural network comprises a plurality of input nodes, wherein each input node is configured to contain at least one data point; a plurality of hidden nodes grouped in a plurality of layers, wherein each of the plurality of hidden nodes received as input all of the at least one data points from the plurality of input nodes; and an output node, wherein the plurality of hidden nodes and output node are trained with the spectral profiles of a plurality of light sources including the light source, wherein the output characteristic is output power, output energy, output flux, a calculated spectrum, irradiance, calculated light source age, or calculated exposure time.