Data processing apparatus, data processing method, and data processing program

Abstract

To provide a data processing apparatus, a method for processing data, and program capable of reducing the power consumption of lighting equipment installed in a public space.SOLUTION: The data processing apparatus includes: an acquisition unit for acquiring sensor data detected by a sensor installed in a public space; and a control unit for controlling lighting equipment installed in the public space on the basis of the sensor data acquired by the acquisition unit.SELECTED DRAWING: Figure 4

Description

[Technical Field]

[0001] The technology of the present disclosure relates to a data processing device, a data processing method, and a data processing program. [Background technology]

[0002] Patent document 1 discloses a persona chatbot control method performed by at least one processor, the method including the steps of receiving a user utterance, adding the user utterance to a prompt including an instruction sentence related to a description of the chatbot character, encoding the prompt, and inputting the encoded prompt into a language model to generate a chatbot utterance in response to the user utterance. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Publication No. 2022-180282 Summary of the Invention [Problem to be solved by the invention]

[0004] Incidentally, when controlling lighting equipment installed in public spaces, the lighting of the lighting equipment is often controlled based on a preset schedule. For example, lighting equipment installed in public spaces may be controlled to turn on the lights at night (e.g., from 5 PM to 5 AM) and turn off the lights during the day (e.g., from 5 AM to 5 PM).

[0005] However, there is room for improvement in the conventional technology. For example, even at night, if there are few people or vehicles passing by, it may not be a problem to turn off lighting equipment installed in public spaces. Therefore, when using conventional technology that controls the turning off of lighting equipment according to the time of day, there is a problem in that the lights are turned on even when there are no people or vehicles passing by, resulting in unnecessary power consumption. [Means for solving the problem]

[0006] A first aspect of the technology of the present disclosure is a data processing device comprising an acquisition unit that acquires sensor data detected by a sensor installed in a public space, and a control unit that controls lighting equipment installed in the public space based on the sensor data acquired by the acquisition unit.

[0007] A second aspect of the technology of the present disclosure is a data processing method that includes acquiring sensor data detected by a sensor installed in a public space, and controlling lighting equipment installed in the public space based on the acquired sensor data.

[0008] A third aspect of the technology of the present disclosure is a program for causing a computer to execute a process including acquiring sensor data detected by a sensor installed in a public space, and controlling lighting equipment installed in the public space based on the acquired sensor data. [Brief explanation of the drawings]

[0009] [Figure 1] FIG. 1 is a conceptual diagram illustrating an example of a configuration of a data processing system. [Figure 2] FIG. 1 is a conceptual diagram showing an example of main functions of a data processing device and a smart device. [Figure 3] FIG. 10 is a diagram for explaining an outline of a specification process. [Figure 4] 2 shows a schematic functional configuration of a specific processing unit of the data processing device. [Figure 5] FIG. 1 is a diagram illustrating an example of a trained model. [Figure 6] 10 is a diagram illustrating an example of an operational flow of specific processing by a data processing device. DETAILED DESCRIPTION OF THE INVENTION

[0010] Hereinafter, an example of an embodiment of a data processing device, a data processing method, and a program according to the technology of the present disclosure will be described with reference to the accompanying drawings.

[0011] First, the terms used in the following description will be explained.

[0012] In the following embodiments, a coded processor (hereinafter simply referred to as a "processor") may be a single arithmetic device or a combination of multiple arithmetic devices. Furthermore, the processor may be a single type of arithmetic device or a combination of multiple types of arithmetic devices. Examples of arithmetic devices include a CPU (Central Processing Unit), a GPU (Graphics Processing Unit), a GPGPU (General-Purpose computing on Graphics Processing Units), an APU (Accelerated Processing Unit), or a TPU (Tensor Processing Unit).

[0013] In the following embodiments, a coded RAM (Random Access Memory) is a memory in which information is temporarily stored and is used as a working memory by a processor.

[0014] In the following embodiments, the coded storage is one or more non-volatile storage devices that store various programs, various parameters, etc. Examples of non-volatile storage devices include flash memory (SSD (Solid State Drive)), magnetic disks (e.g., hard disks), and magnetic tapes.

[0015] In the following embodiments, a communication I / F (Interface) with a symbol is an interface including a communication processor, an antenna, etc. The communication I / F controls communication between multiple computers. Examples of communication standards applied to the communication I / F include wireless communication standards including 5G (5th Generation Mobile Communication System), Wi-Fi (registered trademark), Bluetooth (registered trademark), etc.

[0016] In the following embodiments, "A and / or B" is synonymous with "at least one of A and B." In other words, "A and / or B" means that it may be only A, only B, or a combination of A and B. Furthermore, in this specification, the same concept as "A and / or B" is also applied when three or more things are expressed connected by "and / or."

[0017] FIG. 1 shows an example of the configuration of a data processing system 10 according to the embodiment.

[0018] As shown in FIG. 1, a data processing system 10 includes a data processing device 12 and a lighting facility 14. An example of the data processing device 12 is a server. In this embodiment, the data processing device 12 is an example of a "data processing device" according to the technology of the present disclosure, and the smart device 14 is an example of a "lighting facility" according to the technology of the present disclosure. Note that hereinafter, the smart device 14 will be simply referred to as the lighting facility 14.

[0019] The data processing device 12 includes a computer 22, a database 24, and a communication I / F 26. The computer 22 is an example of a "computer" according to the technology of the present disclosure. The computer 22 includes a processor 28, a RAM 30, and a storage 32. The processor 28, the RAM 30, and the storage 32 are connected to a bus 34. The database 24 and the communication I / F 26 are also connected to the bus 34. The communication I / F 26 is connected to a network 54. Examples of the network 54 include a WAN (Wide Area Network) and / or a LAN (Local Area Network).

[0020] The lighting fixture 14 includes a computer 36, lamps 40, a camera 42, and a communication I / F 44. The computer 36 includes a processor 46, a RAM 48, and a storage 50. The processor 46, the RAM 48, and the storage 50 are connected to a bus 52. The lamps 40 and the camera 42 are also connected to the bus 52. The camera 42 is an example of a sensor of the present disclosure.

[0021] Lamp 40 is configured to be able to light up and adjust its brightness in response to control signals output from computer 36. Camera 42 is a small digital camera equipped with an optical system including a lens, aperture, and shutter, and an imaging element such as a CMOS (Complementary Metal-Oxide-Semiconductor) image sensor or a CCD (Charge Coupled Device) image sensor.

[0022] The communication I / F 44 is connected to a network 54. The communication I / Fs 44 and 26 control the exchange of various information between the processor 46 and the processor 28 via the network 54.

[0023] FIG. 2 shows an example of the main functions of the data processing device 12 and the lighting equipment 14.

[0024] 2, in the data processing device 12, a specific process is performed by the processor 28. A specific processing program 56 is stored in the storage 32. The specific processing program 56 is an example of a "program" according to the technology of the present disclosure. The processor 28 reads the specific processing program 56 from the storage 32 and executes the read specific processing program 56 on the RAM 30. The specific process is realized by the processor 28 operating as a specific processing unit 290 in accordance with the specific processing program 56 executed on the RAM 30.

[0025] The storage 32 stores a trained model 58. The trained model 58 is used by the specification processing unit 290.

[0026] In the lighting equipment 14, the reception output processing is performed by the processor 46. A reception output program 60 is stored in the storage 50. The reception output program 60 is used in conjunction with the specific processing program 56 by the data processing system 10. The processor 46 reads the reception output program 60 from the storage 50 and executes the read reception output program 60 on the RAM 48. The reception output processing is realized by the processor 46 operating as the lighting control unit 46A in accordance with the reception output program 60 executed on the RAM 48.

[0027] Next, the processing of the specific processing unit 290 when the data processing device 12 performs specific processing to control the lighting fixtures 14 will be described.

[0028] In the identification process of this embodiment, as shown in Fig. 3, lighting equipment 14 installed in a public space P is controlled. Specifically, the lighting equipment 14 is turned on and dimmed based on information about the surrounding environment of the lighting equipment 14 obtained from images or videos captured by a camera 42 provided in the lighting equipment 14. The public space P may be either outdoors or indoors. For example, the public space P may be a road or the like.

[0029] As shown in FIG. 4, the specific processing unit 290 includes an acquisition unit 292 and a control unit 294.

[0030] The acquisition unit 292 acquires image or video data captured by the camera 42 of the lighting equipment 14. Specifically, the lighting control unit 46A of the lighting equipment 14 transmits the image or video data captured by the camera 42 to the data processing device 12. Then, the acquisition unit 292 of the data processing device 12 acquires the image or video data transmitted from the lighting equipment 14.

[0031] The control unit 294 controls at least one of turning on and dimming the lighting equipment 14 based on information about the surrounding environment of the lighting equipment 14 obtained from the image or video captured by the camera 42. Specifically, the control unit 294 inputs the image or video data captured by the camera 42 into the trained model 58 to obtain control data for controlling the turning on and dimming of the lighting equipment 14.

[0032] The control unit 294 then transmits the control data to the lighting fixture 14. In the lighting fixture 14, the lighting control unit 46A controls the lighting and dimming of the lamp 40 in accordance with the control data transmitted from the data processing device 12. Specifically, the control unit 294 transmits a signal corresponding to the control data to the lighting fixture 14. The lighting control unit 46A of the lighting fixture 14 then controls the lighting and dimming of the lamp 40 in accordance with the signal transmitted from the data processing device 12.

[0033] The trained model 58 is what is called AI (Artificial Intelligence). For example, the trained model 58 is obtained by performing deep learning on a neural network. When image or video data captured by the camera 42 is input to the trained model 58, control data for controlling the lighting and dimming of the lighting equipment 14 is output.

[0034] FIG. 5 is a diagram illustrating an example of a trained model 58 according to this embodiment. As illustrated in FIG. 5, for example, when image or video data of the surroundings of the lighting equipment 14 is input to the trained model 58, control data for controlling the lighting and dimming of the lighting equipment 14 is output. This control data includes, for example, data on the probability that the lamp 40 included in the lighting equipment 14 will be turned on and data on the degree of dimming. For example, when the probability that the lamp 40 will be turned on is greater than 0.5, the lamp 40 is controlled to be turned on. On the other hand, when the probability that the lamp 40 will be turned on is 0.5 or less, the lamp 40 is controlled to be turned off. Furthermore, for example, the dimming of the lamp 40 is controlled according to the data on the degree of dimming. For example, when the data on the degree of dimming is 0.6, dimming control is performed so that the lamp 40 outputs light at 60% of the maximum output of the light output from the lamp 40.

[0035] The trained model 58 is generated in advance based on training data in which, for example, previously collected training image or video data of the surroundings of the lighting equipment is associated with correct control data for the training image or video data. The correct control data is, for example, manually created in advance. Alternatively, for example, the training data is created in advance based on performance data of actual lighting equipment.

[0036] In this case, trained model 58 is trained so that, for example, the more people or vehicles appearing in the training image or video data and the darker the background appearing in the training image or video data, the closer the probability that the lamp will light up approaches 1 and the greater the light output of the lamp represented by the dimming degree. On the other hand, trained model 58 is trained so that, for example, the fewer people or vehicles appearing in the training image or video data and the brighter the background appearing in the training image or video data, the closer the probability that the lamp will light up approaches 0 and the smaller the light output of the lamp represented by the dimming degree.

[0037] As a result, for example, when controlling the lamp 40 of the actual lighting equipment 14, the lighting control and dimming control are performed so that the lamp 40 is turned on and the light output from the lamp 40 is stronger the more people or vehicles appear in the image or video data around the lighting equipment 14 and the darker the background appears in the learning image or video data. Also, for example, when controlling the lamp 40 of the actual lighting equipment 14, the lighting control and dimming control are performed so that the lamp 40 is turned off and the light output from the lamp 40 is weaker the more people or vehicles appear in the image or video data around the lighting equipment 14 and the brighter the background appears in the learning image or video data.

[0038] Next, the operation of the data processing system 10 will be described.

[0039] An example of the flow of the identification process will be described with reference to Fig. 6. The flow of the identification process shown in Fig. 6 is an example of a "data processing method" according to the technique of the present disclosure.

[0040] The camera 42 of the lighting equipment 14 captures an image or video of the surroundings of the lighting equipment 14, and the image or video data is transmitted to the data processing device 12. For example, the lighting control unit 46A of the lighting equipment 14 transmits the image or video data of the surroundings of the lighting equipment 14 to the data processing device 12 every time a predetermined time elapses.

[0041] In step S300, the acquisition unit 292 acquires image or video data of the surroundings of the lighting equipment 14.

[0042] In step S301, the control unit 294 reads the trained model 58 from the storage 32.

[0043] In step S303, the control unit 294 acquires control data for controlling the lighting equipment 14 by inputting the image or video data of the surroundings of the lighting equipment 14 acquired in step S300 into the trained model 58 acquired in step S301.

[0044] In step S304, the control unit 294 outputs a signal corresponding to the control data acquired in step S303 to the lighting equipment 14, thereby controlling the lighting and dimming of the lighting equipment 14.

[0045] The lighting control unit 46A of the lighting equipment 14 controls the lighting and dimming of the lamps 40 in response to the signal transmitted from the data processing device 12.

[0046] As described above, the data processing device 12 acquires image or video data captured by a camera, which is an example of a sensor installed in a public space, and controls the lighting equipment installed in the public space based on the image or video data. This reduces the power consumption of the lighting equipment installed in the public space. Specifically, by controlling the lighting equipment according to the surrounding conditions of the lighting equipment captured by the camera (e.g., the number of people or the number and brightness of vehicles), it is possible to prevent the lighting equipment from being turned on even when there are no people or vehicles in the public space.

[0047] Furthermore, global electricity consumption is on the rise. This has led to a demand for more efficient urban lighting, which consumes a large amount of electricity. For example, as disclosed in Reference 1 below, global electricity consumption is on the rise.

[0048] Reference 1: Ministry of Economy, Trade and Industry Energy White Paper 2019 "Part 2 Energy Trends / Chapter 2 International Energy Trends", No. 223-1-1

[0049] For this reason, energy management has been attracting attention in recent years, and the market size is on the rise. The energy management market is expected to continue expanding in the future, and has great potential for the future.

[0050] Therefore, in this embodiment, as described above, lighting (specifically, electric lights, etc.) in public spaces, including roads, is controlled more efficiently. Conventional lighting is controlled, for example, by turning on and off lights at specific times according to a preset schedule. In contrast, smart street lighting, implemented by the data processing device 12 of this embodiment, automatically adjusts lighting using AI, which is a trained model 58, and sensor technology. Specifically, as described above, the data processing device 12 of this embodiment monitors the surrounding environment, traffic volume, weather, etc., of the lighting equipment using a camera, which is an example of a sensor that detects the environment, traffic volume, weather, etc., and optimizes the brightness of lighting and the timing of turning on or off lights in real time. This provides bright lighting in areas with heavy traffic and many pedestrians at night, and conversely, reduces energy waste by reducing lighting in areas with light traffic and bright daytime hours. Therefore, this embodiment contributes to improving energy efficiency and reducing costs, while also contributing to improving urban safety and aesthetics.

[0051] In addition, sensor technology and remote monitoring enable early detection of malfunctions and abnormalities in lighting fixtures, enabling maintenance to be carried out.

[0052] For example, the control unit 294 of the data processing device 12 may acquire image or video data, which is an example of sensor data when the lamp 40 of the lighting equipment 14 is turned on or dimmed, and determine whether an abnormality has occurred in the lighting equipment 14 based on the acquired image or video data. For example, if the background shown in the image or video data does not become brighter despite an instruction to turn on the lamp 40 of the lighting equipment 14, it is considered that some abnormality has occurred in the lighting equipment 14. Similarly, if the background shown in the image or video data does not become brighter (or darker) in response to the dimming despite an instruction to dim the lamp 40 of the lighting equipment 14, it is considered that some abnormality has occurred in the lighting equipment 14. Therefore, when the control unit 294 outputs an alert indicating an abnormality in the lighting equipment 14, it is possible to take measures such as performing maintenance on the lighting equipment 14.

[0053] The data processing device 12 may also control the lighting equipment 14 based on weather data for the location where the lighting equipment 14 is installed. The weather data for the location where the lighting equipment 14 is installed may be, for example, data provided by a predetermined organization (e.g., the Japan Meteorological Agency) or data obtained by a sensor installed in the vicinity of the lighting equipment 14. In this case, the acquisition unit 292 of the data processing device 12 further acquires weather data for the location where the lighting equipment 14 is installed, and the control unit 294 of the data processing device 12 controls the lighting equipment 14 based on the image or video data captured by the camera 42 and the weather data. For example, if the weather data indicates cloudy or rainy weather, lighting control and dimming control are performed so that the lamps 40 of the lighting equipment 14 are turned on and the light output from the lamps 40 is increased. On the other hand, if the weather data indicates clear skies, lighting control and dimming control are performed so that the lamps 40 of the lighting equipment 14 are turned off and the light output from the lamps 40 is decreased.

[0054] Furthermore, in the above embodiment, a camera 42 is used as an example of a sensor, but this is not limiting. Any sensor capable of acquiring information about the surrounding environment of the lighting equipment 14 may be used. For example, a sensor capable of detecting people or vehicles in a public space may be realized without being a camera. Also, for example, traffic volume information for a certain road may be acquired based on road traffic information. In this case, the acquisition unit 292 of the data processing device 12 acquires sensor data detected by a sensor installed in the public space. Then, the control unit 294 of the data processing device 12 controls the lighting equipment 14 installed in the public space based on the sensor data.

[0055] Furthermore, in the above embodiment, the case where control data for the lighting equipment 14 is generated using the trained model 58 has been described as an example, but the present invention is not limited to this. For example, the control data may be generated according to preset table data. For example, the control unit 294 of the data processing device 12 may control the lighting and dimming of the lamps 40 by referring to table data in which the number of people or vehicles (or weather data, etc.) present around the lighting equipment 14 is associated with data indicating whether the lamps are on or off and the degree of dimming.

[0056] Furthermore, in the above embodiment, the trained model 58 is stored in the storage 32 of the data processing device 12, and the control unit 294 of the data processing device 12 inputs image or video data of the surroundings of the lighting equipment 14 to the trained model 58 stored in the storage 32. However, the present invention is not limited to this. For example, the trained model 58 may be stored in the storage 50 of the lighting equipment 14. In this case, the lighting control unit 46A of the lighting equipment 14 obtains control data by inputting image or video data of the surroundings of the lighting equipment 14 to the trained model 58 stored in the storage 50, and controls the lighting and dimming of the lamp 40 according to the control data.

[0057] The smart street lighting executed by the data processing device 12 of this embodiment is expected to be used by the following entities.

[0058] (Local government) Smart street lighting can be used by cities or municipalities to improve public infrastructure, thereby improving urban energy efficiency, promoting environmentally friendly urban planning, and increasing convenience and safety for citizens.

[0059] (Energy company) The use of smart street lighting will improve energy efficiency and reduce peak power demand, making it possible to improve the efficiency of power supply.

[0060] (Real Estate Developer) Smart street lighting is also an attractive addition to real estate development projects, as it can improve the aesthetics and safety of cities, making residential or commercial areas more attractive.

[0061] (Environmental protection organization) Environmental protection organizations that promote improved energy efficiency or the use of renewable energy may also be interested in smart street lighting, which is attracting attention as a technology that contributes to the creation of sustainable cities.

[0062] (Technology company) The development and implementation of smart street lighting requires the use of advanced technologies such as sensor technology, AI, and IoT, and companies or startups that provide these technologies are likely to be interested in this field.

[0063] Furthermore, by using the smart street lighting of this embodiment, the following effects can be obtained.

[0064] (Energy Efficiency and Environmental Protection) The use of smart street lighting can promote efficient energy use and reduce power waste, thereby reducing global warming and the burden on the environment and contributing to the creation of sustainable cities.

[0065] (Safety and public peace of mind) Smart street lighting enables real-time lighting control using sensors and AI, making it possible to adjust lighting according to traffic volume and pedestrian density in public spaces. Brighter lighting reduces the risk of traffic accidents and crime, and increases citizens' sense of safety and security.

[0066] (Cost reduction and efficient operation) The introduction of smart street lighting will enable reductions in energy costs and more efficient maintenance of lighting equipment, thereby reducing city operating costs and enabling more effective budget allocation.

[0067] (Dissemination of advanced technologies and innovation) Smart street lighting is an initiative that utilizes advanced technologies such as sensor technology, AI, and IoT. Therefore, the introduction of smart street lighting can promote industrial development and innovation, contributing to the creation of a competitive society.

[0068] The system according to the present disclosure has been described above mainly with respect to the functions of the data processing device 12, but the system according to the present disclosure is not necessarily implemented on a server. The system according to the present disclosure may be implemented as a general information processing system. The present disclosure may be implemented, for example, as a software program running on a personal computer or an application running on a smartphone, etc. The method according to the present disclosure may be provided to users in the form of SaaS (Software as a Service).

[0069] In the above embodiment, an example was given in which a specific process is performed by one computer 22, but the technology disclosed herein is not limited to this, and distributed processing of the specific process may be performed by multiple computers including computer 22.

[0070] In the above embodiment, an example in which the specific processing program 56 is stored in the storage 32 has been described, but the technology of the present disclosure is not limited to this. For example, the specific processing program 56 may be stored in a portable, computer-readable, non-transitory storage medium such as a USB (Universal Serial Bus) memory. The specific processing program 56 stored in the non-transitory storage medium is installed in the computer 22 of the data processing device 12. The processor 28 executes the specific processing in accordance with the specific processing program 56.

[0071] Alternatively, the specific processing program 56 may be stored in a storage device such as a server connected to the data processing device 12 via the network 54, and the specific processing program 56 may be downloaded and installed on the computer 22 in response to a request from the data processing device 12.

[0072] It is not necessary to store all of the specific processing program 56 in a storage device such as a server connected to the data processing device 12 via the network 54, or to store all of the specific processing program 56 in the storage 32; only a portion of the specific processing program 56 may be stored.

[0073] The hardware resource for executing a specific process can be any of the following processors: An example of a processor is a CPU, which is a general-purpose processor that functions as a hardware resource for executing a specific process by executing software, i.e., a program. Another example of a processor is a dedicated electrical circuit, such as an FPGA (Field-Programmable Gate Array), a PLD (Programmable Logic Device), or an ASIC (Application Specific Integrated Circuit), which is a processor with a circuit configuration designed specifically for executing a specific process. Each processor has built-in or connected memory, and each processor uses the memory to execute the specific process.

[0074] The hardware resource that executes the specific processing may be configured with one of these various processors, or may be configured with a combination of two or more processors of the same or different types (for example, a combination of multiple FPGAs, or a combination of a CPU and an FPGA). Also, the hardware resource that executes the specific processing may be a single processor.

[0075] As an example of a system configured with a single processor, first, one processor is configured by combining one or more CPUs and software, and this processor functions as a hardware resource that executes a specific process. Second, there is a system that uses a processor that realizes the functions of an entire system including multiple hardware resources that execute a specific process on a single IC chip, as typified by SoC (System-on-a-chip). In this way, a specific process is realized using one or more of the above-mentioned various processors as hardware resources.

[0076] Furthermore, the hardware structure of these various processors can be, more specifically, an electric circuit that combines circuit elements such as semiconductor devices. The specific processing described above is merely an example. Therefore, it goes without saying that unnecessary steps may be deleted, new steps may be added, or the processing order may be rearranged, without departing from the spirit of the invention.

[0077] The above-described description and illustrations are a detailed explanation of the parts related to the technology of the present disclosure and are merely an example of the technology of the present disclosure. For example, the above description of the configuration, functions, actions, and effects is an explanation of an example of the configuration, functions, actions, and effects of the parts related to the technology of the present disclosure. Therefore, it goes without saying that unnecessary parts may be deleted, new elements may be added, or replacements may be made to the above-described description and illustrations within the scope of the gist of the technology of the present disclosure. Furthermore, to avoid confusion and facilitate understanding of the parts related to the technology of the present disclosure, the above-described description and illustrations omit explanations of common technical knowledge that do not require particular explanation to enable the implementation of the technology of the present disclosure.

[0078] All publications, patent applications, and technical standards mentioned in this specification are herein incorporated by reference to the same extent as if each individual publication, patent application, or technical standard was specifically and individually indicated to be incorporated by reference. [Explanation of symbols]

[0079] 10 Data Processing System 12 Data Processing Device 14 Lighting equipment 290 Special Processing Department 292 Acquisition Department 294 Control Unit

Claims

1. an acquisition unit that acquires sensor data detected by sensors installed in public spaces; a control unit that controls lighting equipment installed in the public space based on the sensor data acquired by the acquisition unit; and 2. A data processing device comprising:

2. the sensor is a camera; the sensor data is an image or video captured by the camera, the control unit controls at least one of turning on and dimming the lighting equipment based on surrounding environment information of the lighting equipment obtained from the image or video captured by the camera.

2. The data processing device according to claim 1.

3. The control unit By inputting the sensor data into a trained model that outputs control data for controlling lighting and dimming of the lighting equipment when the sensor data is input, the control data output from the trained model is acquired, and at least one of lighting and dimming of the lighting equipment is controlled according to the acquired control data.

3. The data processing device according to claim 1.

4. The acquisition unit further acquires weather data for a location where the lighting equipment is installed, The control unit controls the lighting equipment based on the sensor data and the weather data.

3. The data processing device according to claim 1.

5. the control unit acquires the sensor data when the lighting equipment is turned on or dimmed, and determines whether or not an abnormality has occurred in the lighting equipment based on the acquired sensor data.

3. The data processing device according to claim 1.

6. Acquire sensor data detected by sensors installed in public spaces, controlling lighting equipment installed in the public space based on the acquired sensor data; A data processing method in which processing is performed by a computer.

7. Acquire sensor data detected by sensors installed in public spaces, controlling lighting equipment installed in the public space based on the acquired sensor data; A program that causes a computer to execute a process.

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