Lighting equipment

Abstract

To provide a lighting device that can efficiently perform lighting control.SOLUTION: A lighting device includes a lighting unit, a camera, and a controller. The camera performs recognition to be used for lighting control based on a captured image. The controller outputs a recognition result obtained by the camera to a network.SELECTED DRAWING: Figure 2

Description

[Technical field]

[0001] SUMMARY OF THE DISCLOSURE The present invention relates to a lighting device. [Background technology]

[0002] 2. Description of the Related Art There is a conventional technique for acquiring an image captured by an imaging unit provided in a lighting device and controlling the lighting of the lighting device based on the image. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] JP 2019-120577 A Summary of the Invention [Problem to be solved by the invention]

[0004] However, the conventional technology has room for further improvement in terms of efficient lighting control.

[0005] An object of the present invention is to provide a lighting device capable of efficiently controlling lighting. [Means for solving the problem]

[0006] A lighting device according to an embodiment includes a lighting unit, a camera, and a control unit. The camera performs recognition based on a captured image for use in lighting control. The control unit outputs a recognition result obtained by the camera to a network. The network includes an Ethernet and a lighting control network. The control unit selects the network to output the recognition result from among the Ethernet and the lighting control network in accordance with the content of the recognition result. [Brief description of the drawings]

[0007] [Figure 1] FIG. 1 is a diagram illustrating an example of the configuration of a lighting system according to an embodiment. [Diagram 2] FIG. 2 is a block diagram illustrating an example of the configuration of the lighting device according to the embodiment. [Diagram 3]FIG. 3 is a diagram illustrating an example of the network information. [Figure 4] FIG. 4 is a flowchart showing a processing procedure of the processing executed in the lighting device according to the embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0008] The lighting device 1 described below includes a lighting unit 6, a camera 5, and a control unit 2. The camera 5 performs recognition based on a captured image for use in lighting control. The control unit 2 outputs the recognition result by the camera 5 to a network.

[0009] The networks described below include Ethernet (registered trademark) and a lighting control network. The control unit 2 outputs a part of the recognition result to the lighting control device 10 via the Ethernet, and outputs the other part to the lighting control device 10 via the lighting control network.

[0010] The control unit 2 described below selects the network to output from among the Ethernet and the lighting control network according to the contents of the recognition result.

[0011] The control unit 2 described below selects the lighting control network for the recognition result related to dimming of the lighting devices 1 and 11.

[0012] The control unit 2 described below selects a lighting control network for a recognition result that requires responsiveness of lighting control.

[0013] The control unit 2, which will be described below, selects Ethernet when the amount of data of the recognition result is equal to or greater than a threshold value.

[0014] Hereinafter, a lighting device according to an embodiment will be described with reference to the drawings. In the embodiments, the same components are denoted by the same reference numerals, and duplicated descriptions will be omitted.

[0015] Fig. 1 is a diagram showing a configuration example of a lighting system according to an embodiment. The lighting system S shown in Fig. 1 is arranged in a relatively large facility such as a factory where many people move around, and is suitable for individually and complexly controlling a plurality of lighting devices.

[0016] As shown in Fig. 1, a lighting system S includes lighting devices 1 and 11, a lighting control device 10, a hub 12, and a cloud 13. In the lighting system S shown in Fig. 1, the lighting devices 1 and 11 and the lighting control device 10 are connected by a lighting control network shown by a single line. Also, the lighting devices 1, the lighting control device 10, the hub 12, and the cloud 13 are connected by an Ethernet shown by a double line. Note that in the lighting system S, equipment installed in a facility may be connected to the lighting control network.

[0017] The lighting devices 1 and 11 are lighting devices that illuminate a predetermined space such as a facility. The lighting devices 1 and 11 are, for example, directly attached to a ceiling surface and illuminate a floor surface from the ceiling. Of the lighting devices 1 and 11, the lighting device 1 is equipped with a camera 5, and the lighting device 11 is an illumination device that does not have a camera 5. The lighting devices 1 and 11 use the camera 5 as a human presence sensor to switch illumination on and off depending on the presence of a person.

[0018] Furthermore, the lighting device 1 is disposed so that the imaging range of the camera 5 includes at least a part of all of the illumination ranges of the multiple lighting devices 11. The camera 5 is a camera with artificial intelligence, and analyzes an image captured by itself (hereinafter, a captured image) to perform recognition to be used for lighting control of the lighting devices 1 and 11.

[0019] For example, the camera 5 divides a given space (a captured image of the space) into a plurality of areas, and performs recognition for use in lighting control for each area. Each area is set so as to include the illumination range of each lighting device 11.

[0020] For example, the camera 5 recognizes the presence / absence of people in each area. Specifically, the camera 5 recognizes the number of people in each area. More specifically, the camera 5 generates a recognition result indicating whether the number of people present in the area is 1 or more, 5 or more, 7 or more, 10 or more, or 20 or more.

[0021] Furthermore, the camera 5 recognizes the luminance in each area. Specifically, the camera 5 recognizes a statistical value of the luminance in a plurality of pixels included in each area as the luminance. The statistical value is, for example, an average value, a median value, a mode value, etc. For example, the camera 5 generates as a recognition result whether the luminance is 1 lux or more, 200 lux or more, or 600 lux or more.

[0022] Furthermore, the camera 5 recognizes the density of people in each area. Specifically, the camera 5 recognizes the ratio of the area occupied by people to the surface area of ​​the area as the density. The camera 5 also recognizes the statistical value of the distance between multiple people recognized in the area as the density. The statistical value is, for example, the average value, the median value, the mode value, the minimum value, etc. For example, the camera 5 generates as a recognition result whether the density is normal (the above ratio is less than a predetermined value and the above distance statistical value is equal to or greater than a predetermined value), close (the above distance statistical value is less than a predetermined value), or dense (the above ratio is equal to or greater than a predetermined value).

[0023] The camera 5 also recognizes the orientation of people present in the area. For example, the camera 5 analyzes the captured images to detect the skeleton of a person, and recognizes the orientation of the person based on the orientation of the skeleton. The camera 5 also analyzes the movement direction of a person from multiple captured images that are consecutive in time series, and recognizes the orientation of the person based on the movement direction. For example, the camera 5 generates a recognition result indicating whether the person is facing north, northeast, east, southeast, south, southwest, west, or northwest.

[0024] For example, assuming that the vertically upward direction in the captured image is 0°, recognition results are generated using the following ranges: north from 346° to 15° (total 30°), northeast from 16° to 75° (total 60°), east from 76° to 105° (total 30°), southeast from 106° to 165° (total 60°), south from 166° to 195° (total 30°), southwest from 196° to 255° (total 60°), west from 256° to 285° (total 30°), and northwest from 286° to 345° (total 60°).

[0025] Then, the lighting device 1 outputs the recognition result of the camera 5 to the lighting control device 10 via a lighting control network or a network such as Ethernet.

[0026] The lighting control device 10 acquires the recognition result of the camera 5 of the lighting device 1, and performs lighting control of each of the lighting devices 1, 11 based on the recognition result. Specifically, the lighting control device 10 performs lighting control of each of the lighting devices 1, 11 via a lighting control network.

[0027] Specifically, the lighting control device 10 performs lighting control of the lighting devices 1, 11 corresponding to each area based on the recognition result for each area received from the lighting device 1. For example, the lighting control device 10 switches on / off the illumination of each lighting device 1, 11 depending on the presence / absence of a person in each area. Alternatively, the lighting control device 10 may control to increase the illumination intensity to a predetermined value when a person is present and decrease the illumination intensity to a predetermined value when a person is absent. Furthermore, the lighting control device 10 adjusts (dims) the illumination intensity of each lighting device 1, 11 depending on the luminance in each area.

[0028] Furthermore, the lighting control device 10 performs lighting control to improve people's comfort depending on the density and the direction of people. For example, when the density in a particular area becomes high, the lighting control device 10 increases the illumination intensity of the particular area as well as the surrounding areas. That is, the illumination intensity of the lighting devices 1, 11 in the surrounding areas is increased to assist in increasing the brightness of the high-density area. This makes it possible to maintain high brightness even in areas with high density.

[0029] Furthermore, the lighting control device 10 increases the illumination intensity of multiple areas located in the direction in which the person is facing, thereby making it possible to increase the luminance of the area in the direction in which the person is looking.

[0030] In this way, the lighting device 1 performs recognition for use in lighting control by itself and outputs the recognition results to the network, eliminating the need for the lighting control device 10, which is the output destination, to perform recognition processing when performing lighting control. In other words, the lighting device 1 (camera 5) performs the recognition processing instead of the lighting control device 10. In other words, since the recognition processing and lighting control processing are distributed to the lighting device 1 and the lighting control device 10, the processing load of the lighting control device 10 can be reduced and the responsiveness of lighting control can be improved. Therefore, the lighting device 1 according to the embodiment can perform efficient lighting control by outputting the recognition results to the network.

[0031] The hub 12 is a concentrator to which an Ethernet cable is connected. The hub 12 is connected to Ethernet communication cables connected to the lighting devices 1, the lighting control device 10, and the cloud 13, respectively.

[0032] The cloud 13 is an analysis server that acquires captured images and recognition results from the camera 5 of the lighting device 1 via Ethernet and performs various analyses. For example, the cloud 13 analyzes the flow of people in a given space based on the captured images and the above-mentioned recognition results. The cloud 13 transmits the analysis results to a terminal device of a manager of the given space.

[0033] Here, when the lighting device 1 transmits the recognition result of the camera 5 to the lighting control device 10, the lighting device 1 divides the recognition result and transmits the divided recognition result separately to the lighting control network and Ethernet.

[0034] Specifically, the lighting device 1 selects the network to output from among the lighting control network and Ethernet depending on the contents of the recognition result. For example, the lighting device 1 outputs information on the presence / absence of people and brightness to the lighting control network, and outputs the density and direction of people via Ethernet.

[0035] In other words, the lighting device 1 selects the lighting control network as the network to output the recognition result of the presence / absence of a person required for switching on and off the illumination, that is, the recognition result that requires the responsiveness of the lighting control. This makes it possible to improve the responsiveness of the lighting control, such as turning on / off the lighting device 1, 11, by outputting the recognition result that requires the responsiveness of the lighting control via a lighting control network suitable for lighting control such as DALI.

[0036] Furthermore, the lighting device 1 selects the lighting control network as the network to output the recognition result of the luminance required for adjusting the irradiation intensity, i.e., the recognition result related to the dimming of the lighting devices 1 and 11. This allows the lighting device 1 to output the recognition result related to the dimming via a lighting control network suitable for lighting control such as DALI, thereby improving the responsiveness of the lighting control related to the dimming of the lighting devices 1 and 11.

[0037] Furthermore, the lighting device 1 selects Ethernet as the network to output recognition results for which the amount of data, such as density and human orientation, is equal to or greater than a threshold. Recognition results such as density and human orientation are the result of further analysis using the presence / absence of people, so the amount of data is greater than the amount of data of the recognition result of the presence / absence of people. For this reason, recognition results with a large amount of data are output via Ethernet, which is suitable for transmitting large amounts of data. This makes it possible to avoid communication congestion in the lighting control network. Note that density and human orientation are not directly related to lighting control, in other words, the responsiveness of lighting control is low, so using Ethernet does not adversely affect the responsiveness of lighting control.

[0038] Next, a configuration example of the lighting device 1 will be described with reference to Fig. 2. Fig. 2 is a block diagram showing a configuration example of the lighting device 1 according to an embodiment. As shown in Fig. 2, the lighting device 1 is connected to an AC power source 100, and is supplied with driving power from the AC power source 100.

[0039] The lighting device 1 includes a control unit 2, a storage unit 3, a power supply unit 4, a camera 5, and a lighting unit 6. The storage unit 3 stores network information 31.

[0040] The storage unit 3 is realized by, for example, a semiconductor memory element such as a random access memory (RAM) or a flash memory, or a storage device such as a hard disk or an optical disk.

[0041] The network information 31 stored in the storage unit 3 is information related to the network to which the lighting device 1 is connected. Fig. 3 is a diagram showing an example of the network information 31. As shown in Fig. 3, the network information 31 has items such as "network ID", "type", and "transmission information".

[0042] "Network ID" is identification information for identifying a network. "Type" is information indicating the type of network. "Transmission information" is information that is output to the network.

[0043] For example, the network identified by the network ID "N1" is a lighting control network, and outputs information on the presence / absence of people and the brightness in the imaging range of the camera 5, which are the recognition results of the camera 5. The lighting control network is a network configured with transmission lines of a communication method using a communication standard related to lighting control, such as DALI (Digital Addressable Lighting Interface). Furthermore, the lighting device 1 is connected to the DALI standard transmission line via a serial interface such as RS485.

[0044] Moreover, the type of the network identified by the network ID "N2" is Ethernet, and information on the density and the direction of people, which are the recognition results of the camera 5, is output. The Ethernet is, for example, a LAN (Local Area Network).

[0045] The control unit 2 is a controller, and is realized, for example, by a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) using a RAM as a working area to execute various programs stored in a storage device inside the lighting device 1. The control unit 2 is also, for example, a controller, and is realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0046] The power supply unit 4 converts the driving power supplied from an AC power supply 100 from AC to DC, and supplies the same to the control unit 2, the camera 5, and the lighting unit 6.

[0047] The camera 5 is an imaging unit with artificial intelligence, and performs recognition for use in lighting control based on the captured image. Specifically, the camera 5 divides the area into a plurality of areas corresponding to the illumination ranges of the lighting devices 1 and 11, and performs recognition for each area. For example, as described above, the camera 5 recognizes the presence / absence of people, brightness, density, and direction of people.

[0048] The illumination unit 6 includes a light source such as an LED (Light Emitting Diode) and illuminates the surroundings. For example, the illumination unit 6 irradiates a range including the imaging range of the camera 5 as an illumination range.

[0049] Next, the processing contents of the control unit 2 will be specifically described.

[0050] The control unit 2 acquires the recognition result from the camera 5, and outputs the recognition result to the lighting control device 10 via a network selected by referring to the network information 31. Specifically, the control unit 2 outputs a part of the recognition result acquired from the camera 5 to the lighting control device 10 via Ethernet, and outputs the other part to the lighting control device 10 via the lighting control network.

[0051] More specifically, the control unit 2 selects a network to output from among the Ethernet and the lighting control network in accordance with the contents of the recognition result.

[0052] For example, when the recognition result is the presence / absence of a person or brightness, the control unit 2 selects the lighting control network as the output network. In other words, the control unit 2 selects the lighting control network for the recognition result that requires responsiveness of lighting control or the recognition result related to dimming of the lighting devices 1 and 11.

[0053] Specifically, the control unit 2 converts the recognition results of the presence / absence of a person and the brightness into a communication standard suitable for the lighting control network and outputs it to the lighting control network. More specifically, the control unit 2 converts the recognition results of the presence / absence of a person and the brightness into the DALI standard and outputs it.

[0054] Furthermore, when the recognition result is density or person orientation, the control unit 2 selects Ethernet as the output network. That is, when the amount of data of the recognition result is equal to or greater than a threshold, the control unit 2 selects Ethernet. The threshold is, for example, the amount of data of the recognition result of presence / absence of people.

[0055] When outputting to Ethernet, the control unit 2 does not need to convert the communication standard. In other words, the control unit 2 outputs the recognition result to Ethernet without converting the standard. The control unit 2 may instruct the camera 5 to output the density and the direction of people directly to Ethernet.

[0056] In this way, the control unit 2 can avoid communication congestion on the lighting control network by distributing and outputting the recognition results to the lighting control network and Ethernet. As a result, information output to the lighting control device 10 via the lighting control network can be transmitted without communication congestion, and lighting control control information output from the lighting control device 10 to the lighting devices 1 and 11 can be transmitted without communication congestion. In other words, the responsiveness of lighting control can be improved.

[0057] Furthermore, the control unit 2 acquires control information related to lighting control from the lighting control device 10 via the lighting control network, and controls the lighting mode of the lighting unit 6 based on the control information. Specifically, the control unit 2 turns the lighting unit 6 on / off and adjusts the illumination intensity.

[0058] Next, a processing procedure of the processing executed by the lighting device 1 according to the embodiment will be described with reference to Fig. 4. Fig. 4 is a flowchart showing the processing procedure of the processing executed by the lighting device 1 according to the embodiment.

[0059] 4, the lighting device 1 acquires a captured image by the camera 5 (step S101). Next, the camera 5 of the lighting device 1 performs recognition processing to be used for lighting control based on the captured image (step S102).

[0060] Next, the lighting device 1 selects a network to output to for each content of the recognition result (step S103). Next, the lighting device 1 outputs the content to be written to the selected network (step S104), and ends the process.

[0061] As described above, the lighting device 1 according to the embodiment includes the lighting unit 6, the camera 5, and the control unit 2. The camera 5 performs recognition based on a captured image for use in lighting control. The control unit 2 outputs the recognition result by the camera 5 to a network. This allows efficient lighting control.

[0062] Although an embodiment of the present invention has been described, this embodiment is presented as an example and is not intended to limit the scope of the invention. This embodiment can be implemented in various other forms, and various omissions, substitutions, and modifications can be made without departing from the gist of the invention. This embodiment and its modifications are included in the scope of the invention and its equivalents described in the claims, as well as in the scope and gist of the invention. [Explanation of symbols]

[0063] 1 Lighting equipment 2. Control section 3 Storage section 4 Power supply section 5. Camera 6. Lighting Section 10 Lighting control device 11 Lighting equipment 12. Hub 13. Cloud 31 Network Information 100 AC power supply S Lighting System

Claims

1. A lighting section; A camera that performs recognition for use in lighting control based on captured images; a control unit that outputs the recognition result by the camera to a network; Equipped with The network includes: Includes Ethernet and lighting control networks. The control unit is The network to be output is selected from the Ethernet and the lighting control network according to the contents of the recognition result, and the lighting control network is selected for the recognition result that requires responsiveness of lighting control. Lighting equipment.

2. The control unit is For the recognition result related to dimming of a lighting device, the lighting control network is selected.

10. The lighting device of claim 1.

3. The control unit is When the amount of data of the recognition result is equal to or greater than a threshold, the Ethernet is selected.

10. The lighting device of claim 1.

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