Intelligent control of the light characteristic

1. A method comprising:

controlling a lighting device ( 111 - 113 ) for lighting at least one scene ( 151 - 158 ) in an area ( 150 ) with a first light characteristic ( 201 , 202 );

receiving measurement data indicative of the behavior of a flow of people ( 180 ) in the area ( 150 ) during the lighting of the at least one scene ( 151 - 158 ) with the first light characteristic ( 201 , 202 );

determining a second light characteristic ( 201 , 202 ) on the basis of the measurement data;

controlling the lighting device ( 111 - 113 ) for lighting the at least one scene ( 151 - 158 ) with the second light characteristic ( 201 , 202 );

implementing a control loop having a target behavior of the flow of people ( 180 ) as a reference variable, the measurement data as a process variable, and the second light characteristic ( 201 , 202 ) of the lighting device ( 111 - 113 ) as a control variable.

2. The method according to claim 1 wherein the second light characteristic ( 201 , 202 ) is additionally determined on the basis of a model ( 250 ) of the behavior of the flow of people ( 180 ) as a function of the second light characteristic ( 201 , 202 ).

3. The method according to claim 2 , further comprising:

monitoring of the measurement data over a period of at least 10 minutes; and

training the model ( 250 ) on the basis of the monitoring of the measurement data.

4. The method according to claim 2 , further comprising:

receiving reference measurement data indicative of the behavior of at least one further flow of people ( 180 ) in at least one further area ( 150 ); and

training the model ( 250 ) on the basis of the reference measurement data.

5. The method according to claim 2 , wherein the model ( 250 ) describes different behaviors of the flow of people ( 180 ) as a function of the second light characteristic ( 201 , 202 ) for different geometric arrangements of the at least one scene ( 151 - 158 ) in the area ( 150 ).

6. The method according to claim 2 , wherein the model ( 250 ) describes different behaviors of the flow of people ( 180 ) as a function of the second light characteristic ( 201 , 202 ) for different types of the at least one scene ( 151 - 158 ).

7. The method according to claim 2 , wherein the model ( 250 ) describes different behaviors of the flow of people ( 180 ) as a function of the second light characteristic ( 201 , 202 ) for different values of at least one environmental parameter of the at least one scene ( 151 - 158 ) and/or the area ( 150 ).

8. The method according to claim 7 , wherein the at least one environmental parameter is selected from the following group: time of day; weather; day of the week; daylight brightness; outside temperature and inside temperature.

9. The method according to claim 2 , further comprising:

monitoring of the measurement data over a period of at least 30 minutes; and

training the model ( 250 ) on the basis of the monitoring of the measurement data.

10. The method according to claim 2 , further comprising:

monitoring of the measurement data over a period of at least 120 minutes; and

training the model ( 250 ) on the basis of the monitoring of the measurement data.

11. The method according to claim 1 , further comprising:

receiving control data which is indicative for at least one environmental parameter of the at least one scene ( 151 - 158 ) and/or the area ( 150 );

wherein the determination of the second light characteristic ( 201 , 202 ) is additionally based on the control data.

12. The method according to claim 11 , wherein the at least environmental parameter is selected from the following group: time of day; weather; day of the week; daylight brightness; outside temperature and inside temperature.

13. The method according to claim 1 ,

wherein the second light characteristic ( 201 , 202 ) is additionally determined on the basis of a predetermined rate of change based upon the first light characteristic ( 201 , 202 ), and

wherein the rate of change optionally corresponds to a time period that is greater than an average length of stay of participants in the flow of people ( 180 ) in the at least one scene ( 151 - 158 ).

14. The method according to claim 1 , wherein the measurement data is indicative for elements selected from the following group: a speed ( 162 ) of the flow of people ( 180 ); at least one compaction of the flow of people ( 180 ); a branching factor for the flow of people ( 180 ); and an attractiveness factor for the at least one scene ( 151 - 158 ) for the flow of people.

15. The method according to claim 1 , further comprising:

controlling at least one measuring device ( 121 ) for acquiring the measurement data, wherein the at least one measuring device ( 121 ) measures one or more of the following observables: the current speed of the flow of people ( 180 ) at the least one scene ( 151 - 158 ); the average speed of the flow of people ( 180 ) at the least one scene ( 151 - 158 ); and the position of participants in the flow of people ( 180 ) with respect to the at least one scene ( 151 - 158 ).

16. The method according to claim 1 , wherein the first light characteristic ( 201 , 202 ) and/or the second light characteristic ( 201 , 202 ) comprise one or more elements of the following group: light intensity; light contrast; light pressure; light color; and local light distribution.