Methods and Systems for an Automated Design, Fulfillment, Deployment and Operation Platform for Lighting Installations

Abstract

A platform for design of a lighting installation generally includes an automated search engine for retrieving and storing a plurality of lighting objects in a lighting object library and a lighting design environment providing a visual representation of a lighting space containing lighting space objects and lighting objects. The visual representation is based on properties of the lighting space objects and lighting objects obtained from the lighting object library. A plurality of aesthetic filters is configured to permit a designer in a design environment to adjust parameters of the plurality of lighting objects handled in the design environment to provide a desired collective lighting effect using the plurality of lighting objects.

1 - 271 . (canceled) 
     
     
         272 . A method, comprising:
 recording biomarker data over a time frame, the biomarker data being indicative of at least one biological state of a user remaining in a lighting control environment over the time frame, the biomarker data being generated by providing at least one physiological sensor remaining with the user in the lighting control environment over the time frame;   recording light control settings data over the time frame for at least one light remaining in the lighting control environment with the user and with the at least one physiological sensor generating the biomarker data over the time frame; and   using machine learning for recording data correlations over the time frame between the at least one biological state of the user remaining in the lighting control environment over the time frame and lighting effects caused by the at least one light remaining in the lighting control environment with the user over the time frame, the data correlations being based on the recordings of the biomarker data and the recordings of the light control settings data, and utilizing the data correlations for controlling the at least one light.   
     
     
         273 - 427 . (canceled) 
     
     
         428 . The method of  claim 272 , wherein using the machine learning includes using a nearest neighbor interpolation or a Kaczmarz method. 
     
     
         429 . The method of  claim 272 , wherein utilizing the data correlations includes adapting the light control settings data for the at least one light in the lighting control environment based on the biomarker data generated by the at least one physiological sensor remaining with the user in the lighting control environment. 
     
     
         430 . The method of  claim 272 , wherein utilizing the data correlations includes adapting the light control settings data for the at least one light in the lighting control environment based on feedback on the lighting effects caused by the at least one light remaining in the lighting control environment over the time frame. 
     
     
         431 . The method of  claim 272 , wherein recording the data correlations includes classifying the lighting effects based on a measurable effect on the user. 
     
     
         432 . The method of  claim 272 , wherein recording the data correlations includes classifying the lighting effects based on a measurable productivity effect or health effect on the user. 
     
     
         433 . The method of  claim 432 , wherein classifying the lighting effects includes storing the light control settings data as being correlated with the lighting effects in a light fixture library. 
     
     
         434 . The method of  claim 272 , wherein recording the light control settings data includes causing the at least one light to generate light varying over the time frame through a range of color, intensity, spectrum, direction, shape, or distance. 
     
     
         435 . The method of  claim 272 , wherein providing the at least one physiological sensor includes providing a wearable sensor. 
     
     
         436 . The method of  claim 272 , wherein the biomarker data is generated by providing the at least one physiological sensor as including another physiological sensor. 
     
     
         437 . A non-transitory computer readable medium having stored thereon processor-executable software instructions that, when executed by a processor, cause the processor to generate control signals for recording data correlations between at least one biological state of a user and lighting effects caused by at least one light in a lighting control environment, by executing the steps comprising:
 recording biomarker data over a time frame, the biomarker data being indicative of at least one biological state of a user remaining in a lighting control environment over the time frame, the biomarker data being generated by providing at least one physiological sensor remaining with the user in the lighting control environment over the time frame;   recording light control settings data over the time frame for at least one light remaining in the lighting control environment with the user and with the at least one physiological sensor generating the biomarker data over the time frame; and   using machine learning for recording data correlations over the time frame between the at least one biological state of the user remaining in the lighting control environment over the time frame and lighting effects caused by the at least one light remaining in the lighting control environment with the user over the time frame, the data correlations being based on the recordings of the biomarker data and the recordings of the light control settings data, and utilizing the data correlations for controlling the at least one light.   
     
     
         438 . The non-transitory computer readable medium of  claim 437 , wherein using the machine learning includes using a nearest neighbor interpolation or a Kaczmarz method. 
     
     
         439 . The non-transitory computer readable medium of  claim 437 , wherein utilizing the data correlations includes adapting the light control settings data for the at least one light in the lighting control environment based on the biomarker data generated by the at least one physiological sensor remaining with the user in the lighting control environment. 
     
     
         440 . The non-transitory computer readable medium of  claim 437 , wherein utilizing the data correlations includes adapting the light control settings data for the at least one light in the lighting control environment based on feedback on the lighting effects caused by the at least one light remaining in the lighting control environment over the time frame. 
     
     
         441 . The non-transitory computer readable medium of  claim 437 , wherein recording the data correlations includes classifying the lighting effects based on a measurable effect on the user. 
     
     
         442 . The non-transitory computer readable medium of  claim 437 , wherein recording the data correlations includes classifying the lighting effects based on a measurable productivity effect or health effect on the user. 
     
     
         443 . The non-transitory computer readable medium of  claim 442 , wherein classifying the lighting effects includes storing the light control settings data as being correlated with the lighting effects in a light fixture library. 
     
     
         444 . The non-transitory computer readable medium of  claim 437 , wherein recording the light control settings data includes causing the at least one light to generate light varying over the time frame through a range of color, intensity, spectrum, direction, shape, or distance. 
     
     
         445 . The non-transitory computer readable medium of  claim 437 , wherein providing the at least one physiological sensor includes providing a wearable sensor. 
     
     
         446 . The non-transitory computer readable medium of  claim 437 , wherein the biomarker data is generated by providing the at least one physiological sensor as including another physiological sensor.