Lamp color temperature control method and system, storage medium and intelligent terminal

Abstract

The invention relates to a lamp color temperature control method and system, a storage medium and an intelligent terminal, and relates to the field of intelligent illumination, and the method comprises the steps: obtaining an area video in a preset illumination area; analyzing the regional video based on preset influence characteristics to obtain a regional condition, wherein the influence characteristics comprise people flow characteristics and traffic flow characteristics; converting the region condition according to a preset conversion rule to obtain a color temperature index; searching a corresponding color temperature control condition from a preset temperature control database based on the color temperature index; according to the color temperature control method and device, the lamps corresponding to the lighting areas are controlled according to the color temperature control conditions, the targeted color temperature is adopted for lighting according to the conditions in the lighting areas where the lighting lamps can light, control is flexible, and complex and changeable environmental conditions such as special weather events or sudden people flow and traffic flow changes are dealt with; and the flexibility of color temperature control of the lamp is improved.

Description

Technical Field

[0001] The present application relates to the field of intelligent lighting, and in particular to a lamp color temperature control method, system, storage medium and intelligent terminal. Background Art

[0002] Smart lighting technology is connected to the control system through the network, and uses the smart client to control the light, change the light brightness, color, color temperature and mode to create a more comfortable, safe, energy-saving and healthy light environment. From the development trend, smart lighting will be an important part of the future smart home and smart city, and will be gradually promoted with the development of smart home, tunnel lighting, smart city and the progress of intelligent control technology.

[0003] The following problems exist in the prior art. The current intelligent control system still uses relatively simple control logic, such as manual control, which is not flexible enough to cope with complex and changeable environmental conditions, special weather events or sudden changes in pedestrian and vehicle traffic, which may lead to insufficient lighting. There is still room for improvement. Summary of the invention

[0004] In order to improve the problem of insufficient lighting caused by the lack of flexibility of manual control and its difficulty in coping with complex and changing environmental conditions, special weather events or sudden changes in pedestrian and vehicle traffic, the present application provides a lamp color temperature control method, system, storage medium and intelligent terminal.

[0005] In a first aspect, the present application provides a method for controlling the color temperature of a lamp, which adopts the following technical solution: A method for controlling the color temperature of a lamp, comprising: Get the area video within the preset lighting area; Analyze the regional video based on preset influencing features to obtain regional conditions, wherein the influencing features include pedestrian flow features and vehicle flow features; The regional conditions are converted according to the preset conversion rules to obtain the color temperature index; Based on the color temperature index, the corresponding color temperature control situation is found from the preset temperature control database; The lamps corresponding to the lighting area are controlled according to the color temperature control situation.

[0006] By adopting the above technical solution, the situation in the area that the lighting fixture can illuminate is analyzed, and then targeted color temperature is used for lighting. For example, when there is a lot of traffic, cold colors and high color temperature are used, and when there is a little pedestrian traffic, warm colors and low color temperature are used. The control is more flexible and can cope with complex and changeable environmental conditions such as special weather events or sudden changes in pedestrian and vehicle traffic, thereby improving the flexibility of the lamp color temperature control.

[0007] Optionally, the method of analyzing the regional video based on the impact feature to obtain the regional situation includes: Determine video clarity based on regional video and impact features; When the video clarity falls within the preset clarity range, the regional video is directly analyzed based on the influencing features to obtain the regional situation; When the video clarity falls within a preset blur level range, the regional video is defined as a blurry regional video; Control the lamps corresponding to the lighting area according to the preset high color temperature and reacquire the area video, and define the reacquired area video as a clear area video; The clear area video is analyzed based on the impact features to obtain the regional situation.

[0008] By adopting the above technical solution, when the lighting image is not clear and the vision may be blurred due to rainy and foggy weather, a high color temperature can be used to make the image clear, which is convenient for obtaining the actual situation in the lighting area, and then the corresponding color temperature is provided according to the actual situation, thereby improving the accuracy of regional situation analysis in the color temperature control of lamps.

[0009] Optionally, the method of controlling the lamps corresponding to the lighting area according to the high color temperature condition and obtaining a clear area video includes: Determine whether there is a human flow feature in the blurred area video based on the impact feature; When there are crowd features in the blurred area video, the lamps corresponding to the lighting area are controlled according to the high color temperature and continue for the preset safety impact time; Reacquire the regional video within the safety impact duration, and define the reacquired regional video as a clear regional video; When there is no crowd feature, the lamps corresponding to the lighting area are controlled according to the high color temperature condition and the instantaneous area video whose video clarity falls within the clarity range is obtained; When there is no crowd feature in the instantaneous area video, the instantaneous area video is directly output as a clear area video; When there are crowd features in the instantaneous area video, the lamps corresponding to the lighting area will continue to have a safety impact duration and a clear area video will be obtained within the safety impact duration.

[0010] By adopting the above technical solution, if a person is found in the image after the image is made clear by using cool colors and high color temperature, the clarity time is shortened to a shorter time, for example: 0.5 seconds, so as to avoid visual impact on the flow of people. While ensuring clarity, it will not cause discomfort to pedestrians, thereby improving the humanization and intelligence of the color temperature control of the lamps.

[0011] Optionally, the method further includes controlling the lamps corresponding to the lighting area according to the high color temperature condition after the interval time and continuing to obtain the clear area video. The method for determining the interval time includes: The cumulative number of acquisitions of blurred area videos; When the acquisition number is the preset first number, the preset standard interval duration is output as the interval duration, and the corresponding clear area video acquired is defined as the first clear area video; When the number of acquisitions is not the preset first number of times, the blurred area video is acquired again after the interval time and the clear area video is acquired again, and the corresponding acquired clear area video is defined as the second clear area video, and the clear area video acquired last time is defined as the third clear area video, and the third clear area video is the video adjacent to the second clear area video; Analyze the first clear area video based on the influencing feature to obtain a first pedestrian flow feature quantity, a first vehicle flow feature quantity, and a first vehicle flow feature speed; Analyze the second clear area video based on the impact feature to obtain a second pedestrian feature quantity, a second vehicle feature quantity, and a second vehicle feature speed; Analyze the third clear area video based on the impact feature to obtain a third pedestrian flow feature quantity, a third vehicle flow feature quantity, and a third vehicle flow feature speed; Determine a first crowd flow change trend based on the first crowd flow feature quantity and the second crowd flow feature quantity; Determine a first traffic flow change trend based on the first traffic flow feature quantity, the second traffic flow feature quantity, the first traffic flow feature speed, and the second traffic flow feature speed; Determine a second flow of people change trend based on the third flow of people feature quantity and the second flow of people feature quantity; Determine a first traffic flow change trend based on the third traffic flow feature quantity, the second traffic flow feature quantity, the third traffic flow feature speed, and the first traffic flow feature speed; When the acquisition number is the preset second number, based on the first pedestrian flow change trend, the first vehicle flow change trend and the interval duration, a corresponding first change interval duration is searched from a preset change database, and outputted as the interval duration; When the number of acquisitions is neither the first number nor the second number, the corresponding second change interval duration is searched from a preset change database based on the second pedestrian flow change trend, the second vehicle flow change trend and the interval duration, and is output as the interval duration.

[0012] By adopting the above technical solution, the time difference of color temperature change is controlled by the change of pedestrian flow and vehicle flow. On the one hand, it is no longer necessary to calculate and control the color temperature change, which reduces the calculation cost. On the other hand, if there are more people, the longer the interval time is, the number of sudden high color temperature changes is reduced, avoiding frequent flashing that affects the walking conditions of pedestrians, and further improving the humanization of the color temperature control of the lamps.

[0013] Optionally, the conversion rule is to first obtain a traffic speed parameter according to the traffic characteristic speed multiplied by a preset traffic speed ratio, to obtain a traffic quantity parameter according to the traffic characteristic quantity multiplied by a preset traffic quantity ratio, and to obtain a traffic quantity parameter according to the pedestrian characteristic quantity multiplied by a preset pedestrian quantity ratio, wherein the traffic characteristic speed is the speed of the successfully matched traffic characteristic, the traffic characteristic quantity is the number of successfully matched traffic characteristics, and the pedestrian characteristic quantity is the number of successfully matched pedestrian characteristics. The method for converting the regional situation according to the preset conversion rule to obtain the color temperature index includes: Get the lighting area status; The lighting area itself is disassembled to obtain the standard pedestrian flow characteristic range and the standard vehicle flow characteristic range; Disassemble the regional situation to obtain the actual pedestrian flow characteristics and actual vehicle flow characteristics; When the actual pedestrian flow characteristics fall within the standard pedestrian flow characteristics range, and the actual vehicle flow characteristics fall within the standard vehicle flow characteristics range, the color temperature index is calculated according to the preset vehicle flow speed ratio, vehicle flow quantity ratio, pedestrian quantity ratio, actual pedestrian flow characteristics and actual vehicle flow characteristics; When the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range, the degree of difference in the pedestrian flow characteristics is determined based on the actual pedestrian flow characteristics and the standard pedestrian flow characteristics range; Determine the degree of difference in traffic flow characteristics based on actual traffic flow characteristics and the range of standard traffic flow characteristics; Based on the difference in crowd flow characteristics, the corresponding corrected crowd flow ratio is found from a preset crowd flow correction database; Based on the degree of difference in traffic flow characteristics, the corresponding corrected traffic flow quantity ratio and corrected traffic flow speed ratio are found from a preset traffic flow correction database; The color temperature index is calculated based on the corrected pedestrian flow ratio, corrected vehicle flow ratio, corrected pedestrian flow ratio, actual pedestrian flow characteristics and actual vehicle flow characteristics.

[0014] By adopting the above technical solution, it is determined according to the actual situation whether there are abnormal situations. For example, there are many more people in the fast lane where there should be fewer people, there are fewer cars in the area where there should be a large traffic flow, and the speed of cars is very slow in the position where the speed is fast. If there are abnormal situations, the corresponding conversion rules need to be changed, so that the color temperature index is more accurate, and then the color temperature control is more accurate.

[0015] Optionally, the method for calculating the color temperature index according to the corrected pedestrian flow ratio, the corrected vehicle flow ratio, the corrected pedestrian flow ratio, the actual pedestrian flow characteristics, and the actual vehicle flow characteristics includes: When the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range, an abnormal situation inquiry signal is issued; When a preset normal situation response option is received or no response option is received, the color temperature index is calculated according to the corrected pedestrian flow ratio, the corrected vehicle flow ratio, the corrected pedestrian flow ratio, the actual pedestrian flow characteristics and the actual vehicle flow characteristics; When receiving a preset special situation response option, searching the preset special correction database for the corresponding special correction pedestrian flow ratio, special correction vehicle flow ratio and / or special correction vehicle flow speed ratio based on the special situation response option; The found special corrected pedestrian flow ratio, special corrected vehicle flow ratio and / or special corrected vehicle flow speed ratio are replaced with the corresponding corrected pedestrian flow ratio, corrected vehicle flow ratio and / or corrected pedestrian flow ratio, and then the color temperature index is calculated based on the actual pedestrian flow characteristics and the actual vehicle flow characteristics.

[0016] By adopting the above technical solution, when an abnormal situation really occurs, people will be consulted about what happened, and the correction coefficient can be determined according to the feedback, so that the color temperature index is more accurate, and the color temperature control is further accurate.

[0017] Optionally, when the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range, the method of sending an abnormal situation inquiry signal includes: Analyze the regional video based on the preset staff characteristics to obtain the information of the staff on site; When the on-site staff information exists, searching for the corresponding on-site staff mobile device from a preset staff database based on the on-site staff information, and sending an abnormal situation inquiry signal to the on-site staff mobile device; Obtaining on-duty staff information when on-site staff information does not exist; Find the corresponding mobile device of the on-duty staff from the staff database based on the on-duty staff information, and send an abnormal situation inquiry signal to the mobile device of the on-duty staff; When no normal situation response option or special situation response option is received within the preset response time, the regional video is analyzed based on the impact characteristics to obtain the successfully matched non-staff information on site; sorting the on-site non-staff information based on a preset informed judgment rule to obtain an on-site non-staff group, and defining the on-site non-staff information at the first position as designated on-site non-staff information; Based on the designated on-site non-staff information, a corresponding on-site non-staff mobile device is searched from a preset non-staff database, and an abnormal situation inquiry signal is sent to the on-site non-staff mobile device until a normal situation response option or a special situation response option is generated or the response time is exceeded; When no normal situation reply option or special situation reply option is received within the response time, the designated on-site non-staff information is removed from the on-site non-staff group, and the designated on-site non-staff information is updated, and the on-site non-staff mobile device is updated until the normal situation reply option or special situation reply option is received, or the on-site non-staff group does not exist; Outputs normal response options when there is no non-staff group present.

[0018] By adopting the above technical solution, the person being questioned gives priority to the staff present on the scene. If they are not present, the staff on the other end who can be viewed through the video is selected, and finally the non-staff present on the scene is selected. The non-staff present on the scene are also selected in the order in which they can be informed of the situation, thereby improving the accuracy of abnormal situation confirmation.

[0019] In a second aspect, the present application provides a lamp color temperature control system, which adopts the following technical solution: A lamp color temperature control system, comprising: The acquisition module is used to obtain the regional video, the lighting area itself and the on-duty staff information; A memory, used to store a program of a control method of any of the above-mentioned lamp color temperature control methods; The program in the memory can be loaded and executed by the processor to implement any of the above-mentioned lamp color temperature control methods.

[0020] By adopting the above technical solution, the situation in the area that the lighting fixture can illuminate is analyzed, and then targeted color temperature is used for lighting. For example, when there is a lot of traffic, cold colors and high color temperature are used, and when there is a little pedestrian traffic, warm colors and low color temperature are used. The control is more flexible and can cope with complex and changeable environmental conditions such as special weather events or sudden changes in pedestrian and vehicle traffic, thereby improving the flexibility of the lamp color temperature control.

[0021] In the third aspect, the present application provides a smart terminal, which adopts the following technical solution: The intelligent terminal comprises a memory and a processor, wherein the memory stores a computer program which can be loaded by the processor and execute any one of the above-mentioned lamp color temperature control methods.

[0022] By adopting the above technical solution, the situation in the area that the lighting fixture can illuminate is analyzed, and then targeted color temperature is used for lighting. For example, when there is a lot of traffic, cold colors and high color temperature are used, and when there is a little pedestrian traffic, warm colors and low color temperature are used. The control is more flexible and can cope with complex and changeable environmental conditions such as special weather events or sudden changes in pedestrian and vehicle traffic, thereby improving the flexibility of the lamp color temperature control.

[0023] Fourthly, the present application provides a computer storage medium that can store corresponding programs and has the characteristics of fast interaction with memory big data.

[0024] Computer readable storage medium, using the following technical solution: A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above-mentioned lamp color temperature control methods.

[0025] By adopting the above technical solution, the situation in the area that the lighting fixture can illuminate is analyzed, and then targeted color temperature is used for lighting. For example, when there is a lot of traffic, cold colors and high color temperature are used, and when there is a little pedestrian traffic, warm colors and low color temperature are used. The control is more flexible and can cope with complex and changeable environmental conditions such as special weather events or sudden changes in pedestrian and vehicle traffic, thereby improving the flexibility of the lamp color temperature control.

[0026] In summary, the present application includes at least the following beneficial technical effects: 1. Analyze the situation in the area that the lighting fixture can illuminate, and then use targeted color temperature for lighting. The control is more flexible and can cope with complex and changeable environmental conditions such as special weather events or sudden changes in pedestrian and vehicle traffic, which improves the flexibility of lighting color temperature control; 2. When the lighting image is not clear, high color temperature is used to make the image clear, which is convenient for obtaining the real situation in the lighting area and improves the accuracy of regional situation analysis in the color temperature control of lamps; 3. Consult when in abnormal situation, and determine the correction coefficient according to the feedback, so that the color temperature index is more accurate, and then the color temperature control is more accurate. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 It is a flow chart of a lamp color temperature control method in an embodiment of the present application.

[0028] Figure 2 It is a flowchart of a method for analyzing regional videos based on impact features to obtain regional conditions in an embodiment of the present application.

[0029] Figure 3 It is a flow chart of a method for controlling lamps corresponding to a lighting area according to a high color temperature condition and obtaining a clear area video in an embodiment of the present application.

[0030] Figure 4 It is a flowchart of a method for determining an interval duration in an embodiment of the present application, in which the lamps corresponding to the lighting area are controlled according to a high color temperature condition after an interval duration and clear area video continues to be acquired.

[0031] Figure 5 It is a flow chart of a method for converting regional conditions according to preset conversion rules to obtain a color temperature index in an embodiment of the present application.

[0032] Figure 6 It is a flow chart of a method for calculating a color temperature index according to a corrected pedestrian flow ratio, a corrected vehicle flow ratio, a corrected pedestrian flow ratio, actual pedestrian flow characteristics, and actual vehicle flow characteristics in an embodiment of the present application.

[0033] Figure 7 It is a flow chart of a method for sending an abnormal situation inquiry signal when the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range in an embodiment of the present application.

[0034] Figure 8 It is a system module diagram of a lamp color temperature control method in an embodiment of the present application. DETAILED DESCRIPTION

[0035] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-Figure 8 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0036] The present application embodiment discloses a method for controlling the color temperature of a lamp. Figure 1 , a lamp color temperature control method includes: Step 100: Acquire a regional video within a preset lighting area.

[0037] The lighting area is the area illuminated by the street lamp. The regional video is the video captured by the camera in the lighting area. The acquisition method is to capture it with a camera, that is, a wide-angle camera that can cover the entire lighting area is also installed on the street lamp. If a single camera cannot cover the entire lighting area, multiple cameras with different angles are installed.

[0038] Step 101: Analyze the regional video based on preset impact features to obtain regional conditions.

[0039] The influencing features are features that are sufficient to affect the color temperature. The influencing features include the characteristics of people flow and vehicle flow. Here, people and vehicles are the main focus, and other conditions such as animals and plants are not analyzed for the time being. The regional situation is the situation in the area, including the number of people, the number of vehicles, and the speed of the vehicles. Since the speed of the vehicle is involved here, the analysis here cannot be based solely on photos, but requires video to judge the speed.

[0040] The analysis method is a matching method, that is, the features of the person and the vehicle are compared with each frame of the video.

[0041] Step 102: converting the regional conditions according to a preset conversion rule to obtain a color temperature index.

[0042] The conversion rule is to first obtain the traffic speed parameter by multiplying the traffic characteristic speed by the traffic speed ratio, obtain the traffic quantity parameter by multiplying the traffic characteristic number by the traffic quantity ratio, and obtain the traffic quantity parameter by multiplying the pedestrian characteristic number by the pedestrian quantity ratio. Then, the traffic quantity parameter, the pedestrian quantity parameter, and the traffic speed parameter are added to obtain the color temperature index. The traffic characteristic speed is the speed of the successfully matched traffic characteristic, and the traffic speed ratio is the ratio of the traffic speed in the color temperature index. The traffic characteristic number is the number of successfully matched traffic characteristics, and the traffic quantity ratio is the ratio of the traffic quantity in the color temperature index. The pedestrian characteristic number is the number of successfully matched pedestrian characteristics, and the pedestrian quantity ratio is the ratio of the pedestrian quantity in the color temperature index. If there are other regional situations, they can also be added according to the corresponding ratios. It should be noted here that the speed of the pedestrian flow is not used as a reference because the deviation is extremely large.

[0043] The color temperature index is an index that can represent the required color temperature, which can be a numerical value. The conversion process is to extract the regional situation and then convert it according to the conversion rules.

[0044] Step 103: searching for corresponding color temperature control conditions from a preset temperature control database based on the color temperature index.

[0045] The color temperature control situation is how to control the color temperature. Here it mainly refers to the color temperature. The database stores the mapping relationship between the color temperature index and the color temperature control situation, which is obtained by the staff in this field based on the actual situation and their own experience, that is, when the actual regional situation is within a certain range, at what color temperature the traffic is smoother and the human body feels more comfortable, the corresponding regional situation is recorded, and then converted into the range of the color temperature index. When the system receives the corresponding color temperature index, it automatically finds the corresponding color temperature control situation from the database and outputs it.

[0046] Step 104: Control the lamps corresponding to the lighting area according to the color temperature control condition.

[0047] Reference Figure 2,The method of analyzing the regional video based on the ,impact features to obtain the regional situation includes: Step 200: Determine video clarity based on regional video and impact features.

[0048] The video clarity is the clarity of the image and the matching of the influencing features. Here, the overlap between the traffic features in the influencing features and the successfully matched traffic features in the regional video can be compared, or the edge detection method can be used for detection.

[0049] Step 201: When the video definition falls within a preset definition range, the regional video is directly analyzed based on the influencing features to obtain the regional situation.

[0050] The clarity range is the range of clarity within which the video is clear. If it is within the clarity range, it means that the video is clear, and there is no interference such as rain or fog, and all influencing features can be directly analyzed. Therefore, the regional video can be directly analyzed based on the influencing features to obtain the regional situation.

[0051] Step 202: When the video clarity falls within a preset blur level range, define the region video as a blur region video.

[0052] The blur level range is the range of clarity within which the video is blurry. If it falls within the blur level range, the video may be incorrectly identified, may be incorrectly identified, or may not be identified, so it needs to be processed.

[0053] Step 203: Control the lamps corresponding to the lighting area according to the preset high color temperature and reacquire the area video, and define the reacquired area video as a clear area video.

[0054] The high color temperature situation refers to the situation where the color temperature is high. Here, the high color temperature is a fixed range, rather than a relatively high color temperature compared to a certain color temperature. The lamps corresponding to the lighting area are controlled according to the high color temperature situation, so that the street lamps have strong penetration in rainy and foggy weather, provide brighter and clearer lighting, enhance contrast, and help improve the visibility of objects.

[0055] Step 204: Analyze the clear area video based on the impact features to obtain the area situation.

[0056] Reference Figure 3 The method of controlling the lamps corresponding to the lighting area according to the high color temperature and obtaining a clear area video includes: Step 300: Determine whether there is a human flow feature in the blurred area video based on the impact feature.

[0057] The judgment method is consistent with step 101, that is, directly matching with the blurred area video.

[0058] Step 301: When there are crowd features in the blurred area video, the lamps corresponding to the lighting area are controlled according to the high color temperature condition and continue for a preset safety impact time.

[0059] The safety impact duration is the length of time that the light has a high color temperature but is too short to easily cause eye damage. This length is obtained by the staff in this field based on tests. When there are human flow features in the blurred area video, it means that there must be people regardless of whether the video is clear or not. Once the high color temperature is turned on for a long time, it is easy to cause harm. Therefore, although the lamps corresponding to the lighting area are controlled according to the preset high color temperature, it only lasts for the safety impact duration.

[0060] It should be noted that in the present application, once the lamps corresponding to the lighting area are controlled according to the high color temperature and the safety impact time lasts, the original color temperature will be restored immediately after the safety impact time.

[0061] Step 302: Reacquire the regional video within the safety impact time, and define the reacquired regional video as a clear regional video.

[0062] During the safety impact time, the light is clearer than the video in the fuzzy area, so a video with a duration less than or equal to the safety impact time can be obtained during this time.

[0063] Step 303: When there is no crowd feature, the lamps corresponding to the lighting area are controlled according to the high color temperature condition and the instantaneous area video whose video clarity falls within the clarity range is obtained.

[0064] The instantaneous region video is the video at the instant when the video definition falls within the definition range.

[0065] When it does not exist, it can be controlled for a long time to get a completely clear video. There are two steps here, first record the video, then intercept the clear part of the video, both can be done at the same time, once the cleaned part is intercepted, stop recording and delete the unclear part.

[0066] Step 304: When there is no crowd feature in the instantaneous area video, directly output the instantaneous area video as a clear area video.

[0067] If it does not exist, the instantaneous area video is directly output as the clear area video.

[0068] Step 305: When there are crowd features in the instantaneous area video, the lamps corresponding to the lighting area are continuously illuminated for the safety impact time and a clear area video is obtained within the safety impact time.

[0069] When there are crowd flow features in the instantaneous area video, it means that the person has been identified after being clearly found at this time, so the harm to the person can be stopped in time, so the safety impact time only lasts and the clear area video is obtained within the safety impact time.

[0070] Reference Figure 4 , and further comprising controlling the lamps corresponding to the lighting area according to the high color temperature after the interval time and continuing to obtain the clear area video, the method for determining the interval time, the method comprising: Step 400: accumulating the number of acquisitions of blurred area videos.

[0071] The acquisition times are the times of acquiring blur area videos. Here, each time a blur area video is acquired, the lamps corresponding to the lighting area will be suddenly controlled according to the high color temperature. At this time, a clear area video will be acquired in the following time. At this time, the blur area video is interrupted, and the new blur area video will be restarted when the lamps are turned off or controlled according to the cold color temperature.

[0072] Step 401: when the acquisition times are the preset first times, the preset standard interval duration is output as the interval duration, and the corresponding acquired clear area video is defined as the first clear area video.

[0073] The first time is the number of times the blurred area video appears for the first time. The standard interval is a standard interval set by humans. Since there is no reference before, an interval is set by humans as a basis for control, so that although the blurred area video is restored immediately after the safety impact time, the high color temperature is not used immediately because the area video is blurred, making the detection process less frequent.

[0074] Step 402: When the number of acquisitions is not the preset first number, the blurred area video is acquired again after an interval and the clear area video is acquired again, and the corresponding acquired clear area video is defined as the second clear area video, and the clear area video acquired last time is defined as the third clear area video.

[0075] The third clear area video is a video taken before the second clear area video when the lamps corresponding to the lighting area are controlled according to the high color temperature situation and the safety impact lasts for a long time.

[0076] Step 403: Analyze the first clear area video based on the influencing features to obtain the first pedestrian feature quantity, the first vehicle feature quantity and the first vehicle feature speed.

[0077] The first number of pedestrian features is the number of pedestrian features that are successfully matched in the first clear area video. The first number of vehicle features is the number of vehicle features that are successfully matched in the first clear area video. The first vehicle feature speed is the speed of the vehicle features that are successfully matched in the first clear area video. The first two analysis methods are image comparison and then statistics, while the third analysis method is to calculate the displacement distance of the position of the vehicle features after image comparison in two images with fixed time intervals.

[0078] Step 404: Analyze the second clear area video based on the influencing features to obtain the second pedestrian feature quantity, the second vehicle feature quantity and the second vehicle feature speed.

[0079] The second number of pedestrian features is the number of pedestrian features that are successfully matched in the second clear area video. The second number of vehicle features is the number of vehicle features that are successfully matched in the second clear area video. The second vehicle feature speed is the speed of the vehicle features that are successfully matched in the second clear area video. The analysis method is similar to step 403 and will not be repeated here.

[0080] Step 405: Analyze the third clear area video based on the influencing features to obtain a third pedestrian feature quantity, a third vehicle feature quantity, and a third vehicle feature speed.

[0081] The third number of pedestrian features is the number of pedestrian features that are successfully matched in the third clear area video. The third number of vehicle features is the number of vehicle features that are successfully matched in the third clear area video. The third vehicle feature speed is the speed of the vehicle features that are successfully matched in the third clear area video. The analysis method is similar to step 403 and will not be repeated here.

[0082] Step 406: Determine the first crowd flow change trend based on the first crowd flow feature quantity and the second crowd flow feature quantity.

[0083] The first crowd change trend is the change trend of the number of crowds from the first clear area video to the second clear area video, which is determined by subtracting the two and dividing by the interval time.

[0084] Step 407: Determine the first traffic flow change trend based on the first traffic flow feature quantity, the second traffic flow feature quantity, the first traffic flow feature speed, and the second traffic flow feature speed.

[0085] The first traffic flow change trend is a change trend of the traffic flow quantity and the traffic flow speed from the first clear area video to the second clear area video, and is determined by subtracting the quantity and the speed from each other and dividing by the interval time.

[0086] Step 408: Determine a second crowd flow change trend based on the third crowd flow feature quantity and the second crowd flow feature quantity.

[0087] The second crowd flow change trend is the change trend of the number of people from the third clear area video to the second clear area video, which is determined by subtracting the two and dividing by the interval time.

[0088] Step 409: Determine the first traffic flow change trend based on the third traffic flow feature quantity, the second traffic flow feature quantity, the third traffic flow feature speed and the first traffic flow feature speed.

[0089] The second traffic flow change trend is a change trend of the traffic flow quantity and traffic flow speed from the third clear area video to the second clear area video, which is determined by subtracting the quantity and speed from each other and dividing by the interval time.

[0090] Step 410: When the acquisition number is the preset second number, the corresponding first change interval duration is searched from the preset change database based on the first pedestrian flow change trend, the first vehicle flow change trend and the interval duration, and outputted as the interval duration.

[0091] The second number is the number of times the blurred area video appears for the second time. The first change interval duration is the interval duration in which the situation in the area will change in theory under the first pedestrian change trend and the first vehicle change trend, and the change trend of both occurs within the interval duration. The database stores the mapping relationship between the first pedestrian change trend, the first vehicle change trend, the interval duration and the first change interval duration. After a large number of on-site observations and records by the staff in this field, the interval duration in which the situation in the area will change is obtained when the first pedestrian change trend, the first vehicle change trend and the interval duration are consistent, and then the average value of the test data is taken and special cases are removed to obtain. When the system receives the corresponding first pedestrian change trend, the first vehicle change trend and the interval duration, the corresponding first change interval duration is automatically found from the database for output. If there is no identical data here, a set of most similar mapping relationships will be automatically found from the database for output.

[0092] When the number of acquisitions is the second number, it means that the first clear area video and the second clear area video are acquired. Therefore, based on the first pedestrian flow change trend, the first vehicle flow change trend and the interval duration, the corresponding first change interval duration is found from the preset change database and output as the interval duration.

[0093] Step 411: When the number of acquisitions is neither the first number nor the second number, the corresponding second change interval duration is searched from a preset change database based on the second pedestrian flow change trend, the second vehicle flow change trend and the interval duration, and outputted as the interval duration.

[0094] The second change interval duration is the interval duration during which the situation in the area will theoretically change under the second pedestrian flow change trend and the second vehicle flow change trend, and the change trends of the two occur within the interval duration. The establishment of the database was introduced in step 410 and will not be repeated here. When the system receives the corresponding second pedestrian flow change trend, the second vehicle flow change trend and the interval duration, it automatically searches for the corresponding second change interval duration from the database for output. If there is no identical data here, a set of the most similar mapping relationships will be automatically searched for output from the database.

[0095] When the acquisition times are neither the first time nor the second time, it means that the acquired videos are the second clear area videos and the third clear area videos.

[0096] Reference Figure 5 , the method of converting the regional conditions according to the preset conversion rules to obtain the color temperature index includes: Step 500: Obtain the lighting area status.

[0097] The lighting area itself is a situation where there is no actual scene, that is, only the geographical location of the lighting area (for example, intersections, unmanned lanes, and car-free passages), actual layout (for example, whether there are zebra crossings, whether there are people passing by), etc. are analyzed. The data obtained here can be manually input, that is, the corresponding environmental values ​​are input by the staff in advance when installing the lamps in the system.

[0098] Step 501: Decompose the lighting area to obtain a standard pedestrian flow feature range and a standard vehicle flow feature range.

[0099] The standard pedestrian flow feature range is the range of the number of pedestrian flow features under normal circumstances in the lighting area. The standard vehicle flow feature range is the range of the number and speed of vehicle flow features under normal circumstances in the lighting area. The analysis process is that the standard pedestrian flow feature range and the standard vehicle flow feature range are part of the lighting area itself, and can be directly extracted.

[0100] Step 502: Decompose the regional situation to obtain actual pedestrian flow characteristics and actual vehicle flow characteristics.

[0101] The actual pedestrian flow feature is the number of pedestrian flow features in the lighting area under actual conditions. The actual vehicle flow feature is the number and speed of vehicle flow features in the lighting area under actual conditions. The disassembly steps can be introduced in step 102, which will not be repeated here.

[0102] Step 503: When the actual pedestrian flow characteristics fall within the standard pedestrian flow characteristics range, and the actual vehicle flow characteristics fall within the standard vehicle flow characteristics range, the color temperature index is calculated according to the preset vehicle flow speed ratio, vehicle flow quantity ratio, pedestrian quantity ratio, actual pedestrian flow characteristics and actual vehicle flow characteristics.

[0103] The vehicle speed ratio, vehicle quantity ratio, and pedestrian quantity ratio have all been introduced in step 102, so they will not be described in detail here.

[0104] When the actual pedestrian flow characteristics fall within the range of standard pedestrian flow characteristics, and the actual vehicle flow characteristics fall within the range of standard vehicle flow characteristics, it indicates that this is a normal situation. Then the color temperature index is directly calculated according to the vehicle flow speed ratio, vehicle flow number ratio, pedestrian flow number ratio, actual pedestrian flow characteristics and actual vehicle flow characteristics.

[0105] Step 504: when the actual crowd flow feature does not fall within the standard crowd flow feature range, or the actual vehicle flow feature does not fall within the standard vehicle flow feature range, the crowd flow feature difference degree is determined based on the actual crowd flow feature and the standard crowd flow feature range.

[0106] The difference degree of crowd flow characteristics is the difference degree between the actual crowd flow characteristics and the standard crowd flow characteristics range. The method of determination here is to subtract the median value of the standard crowd flow characteristics range from the actual crowd flow characteristics, and then divide it by the median value of the standard crowd flow characteristics range. If it does not fall into the range, it means that the situation is not normal at this time, so different values ​​need to be used for the vehicle speed ratio, vehicle quantity ratio, and passenger quantity ratio at this time.

[0107] Step 505: Determine the degree of difference in traffic flow characteristics based on the actual traffic flow characteristics and the standard traffic flow characteristic range.

[0108] The degree of difference in traffic flow characteristics is the degree of difference between the actual traffic flow characteristics and the standard traffic flow characteristics range. The determination method here is to subtract the median of the standard traffic flow characteristics range from the number and speed in the actual traffic flow characteristics, and then divide it by the median of the standard traffic flow characteristics range.

[0109] Step 506: based on the difference degree of the crowd flow characteristics, the corresponding corrected crowd flow quantity ratio is searched from the preset crowd flow correction database.

[0110] The corrected proportion of the number of people is the proportion after the proportion of the number of people changes due to the difference in the characteristics of the people. The database stores the mapping relationship between the difference in the characteristics of the people and the corrected proportion of the number of people. The staff in this field calculates the difference in the characteristics of the people according to the actual characteristics of the people exceeding the range of the characteristics of the people, and then calculates the value of the color temperature index converted by the difference in the degree of color temperature demand of the characteristics of the people based on their own experience when everything else is the same except the characteristics of the people. When the system receives the corresponding difference in the characteristics of the people, it automatically finds the corresponding corrected proportion of the number of people from the database and outputs it.

[0111] Step 507: Based on the degree of difference in traffic flow characteristics, the corresponding corrected traffic flow quantity ratio and corrected traffic flow speed ratio are searched from a preset traffic flow correction database.

[0112] The corrected traffic volume ratio is the ratio after the traffic volume ratio changes due to the difference in traffic volume characteristics. The corrected traffic speed ratio is the ratio after the traffic speed ratio changes due to the difference in traffic volume characteristics. The database stores the mapping relationship between the difference in traffic volume characteristics, the corrected traffic volume ratio and the corrected traffic speed ratio. The staff in this field calculates the difference in traffic volume characteristics based on the actual traffic volume characteristics exceeding the traffic volume characteristics range, and then calculates the value of the color temperature index converted by the different degree of color temperature requirements of the traffic volume characteristics when everything else is the same except the traffic volume characteristics through their own experience. When the system receives the corresponding difference in traffic volume characteristics, it automatically finds the corresponding corrected traffic volume ratio and corrected traffic speed ratio from the database for output.

[0113] Step 508: Calculate the color temperature index according to the corrected pedestrian flow ratio, the corrected vehicle flow ratio, the corrected pedestrian flow ratio, the actual pedestrian flow characteristics, and the actual vehicle flow characteristics.

[0114] When the proportion changes, it can be calculated directly according to the changed proportion.

[0115] Reference Figure 6 The method for calculating the color temperature index according to the corrected proportion of pedestrian flow, the corrected proportion of vehicle flow, the corrected proportion of pedestrian flow, the actual characteristics of pedestrian flow and the actual characteristics of vehicle flow includes: Step 600: When the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range, an abnormal situation inquiry signal is issued.

[0116] The abnormal situation inquiry signal is a signal automatically sent by the system to inquire why the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range. The sending method here can be text.

[0117] Step 601: When a preset normal situation response option is received or no response option is received, a color temperature index is calculated according to the corrected pedestrian flow ratio, the corrected vehicle flow ratio, the corrected pedestrian flow ratio, the actual pedestrian flow characteristics and the actual vehicle flow characteristics.

[0118] The normal situation reply option is an option for a normal situation, although the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range. When an abnormal situation inquiry signal is sent here, a reply option will be provided. The corresponding receiving personnel only need to enter the corresponding option of the motor, without text input, so as to make the reply uniform and convenient for processing. If it is a normal situation, the color temperature index is calculated according to the corrected pedestrian flow ratio, the corrected vehicle flow ratio, the corrected pedestrian flow ratio, the actual pedestrian flow characteristics and the actual vehicle flow characteristics.

[0119] Step 602: When receiving a preset special situation response option, the corresponding special correction pedestrian flow ratio, special correction vehicle flow ratio and / or special correction vehicle flow speed ratio are searched from a preset special correction database based on the special situation response option.

[0120] The special situation reply option is an option for a special situation in which the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range, such as: traffic accidents, traffic jams, construction, etc. The special correction of the proportion of the number of people is the proportion of the number of people under special circumstances. The special correction of the number of vehicles is the proportion of the number of vehicles under special circumstances. The special correction of the vehicle speed is the proportion of the vehicle speed under special circumstances. The database stores the mapping relationship between the special situation reply option, the special correction of the proportion of the number of people, the special correction of the proportion of the number of vehicles and / or the special correction of the proportion of vehicle speed. The staff in this field observes the color temperature index actually required under the special situation corresponding to the special situation reply option, and then determines through their own experience that when all other conditions except the pedestrian flow characteristics or vehicle flow characteristics are the same, the value of the color temperature index converted by the different degree of demand for color temperature of the pedestrian flow characteristics or vehicle flow characteristics is calculated. When the system receives the special situation reply option, the special correction of the proportion of the number of people, the special correction of the proportion of the number of vehicles and / or the special correction of the proportion of vehicle speed is automatically output.

[0121] It should be noted here that the special situation response options are different. It may output one of the special corrected pedestrian flow ratio, the special corrected vehicle flow ratio and the special corrected vehicle flow speed ratio, or it may output two or even all of them.

[0122] Step 603: Replace the corresponding corrected pedestrian quantity ratio, corrected vehicle quantity ratio and / or corrected pedestrian quantity ratio with the found special corrected pedestrian quantity ratio, special corrected vehicle quantity ratio and / or special corrected vehicle speed ratio, and then calculate the color temperature index in combination with the actual pedestrian flow characteristics and the actual vehicle flow characteristics.

[0123] Reference Figure 7 The method of sending an abnormal situation inquiry signal when the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range includes: Step 700: Analyze the regional video based on preset staff characteristics to obtain information about the staff present.

[0124] The staff characteristics are the staff of the street light management system, or the staff of the corresponding traffic area or the characteristics of the traffic police. The on-site staff information is the personnel in the lighting area that match the staff characteristics. The analysis method here can be directly through face recognition or through special clothing recognition, that is, work clothes, and the work clothes are numbered.

[0125] Step 701: When the on-site staff information exists, the corresponding on-site staff mobile device is searched from a preset staff database based on the on-site staff information, and an abnormal situation inquiry signal is sent to the on-site staff mobile device.

[0126] The on-site staff mobile device is a mobile device carried by the on-site staff, such as a mobile phone. The database stores the mapping relationship between the on-site staff information and the on-site staff mobile device. The staff registers their own mobile devices and records them. When the system receives the corresponding on-site staff information, it automatically finds the corresponding on-site staff mobile device from the database for output.

[0127] When the on-site staff information exists, it means that there are staff on the scene, so he can clearly understand the cause of the abnormal situation at this time, so these personnel are preferably selected as insiders and send out abnormal situation inquiry signals.

[0128] Step 702: Obtain on-duty staff information when on-duty staff information does not exist.

[0129] The on-duty staff information is the person watching the video at the other end of the video. Here, since the entire system still needs to be monitored by the equipment monitoring personnel, the monitoring personnel can also be a witness to know the cause of the abnormal situation.

[0130] Step 703: Based on the on-duty staff information, the corresponding on-duty staff mobile device is searched from the staff database, and an abnormal situation inquiry signal is sent to the on-duty staff mobile device.

[0131] The on-duty staff mobile device is a mobile device carried by the on-duty staff. The establishment of the database is not described in detail here. When the system receives the corresponding on-duty staff information, it automatically searches for the corresponding on-duty staff mobile device from the database.

[0132] When there is no information about the on-site staff, the second choice is the on-duty staff who can watch the video, and send him an abnormal situation inquiry signal.

[0133] Step 704: When no normal situation response option or special situation response option is received within the preset response time, the regional video is analyzed based on the impact characteristics to obtain the successfully matched on-site non-staff information.

[0134] The response time is a manually set time, that is, the longest time a person takes to respond after receiving an inquiry signal, for example, 1 minute. The on-site non-staff information is the information of people who are on site but not the corresponding staff. The matching method is face recognition.

[0135] Step 705: sorting the on-site non-staff information based on a preset informed judgment rule to obtain an on-site non-staff group, and defining the on-site non-staff information at the first position as designated on-site non-staff information.

[0136] The informed judgment rule is a principle for judging the ability of the non-staff members on the scene to know the current situation, such as age and education level. The non-staff members on the scene in the non-staff group are sorted according to the informed judgment rule, and the more informed the members are, the higher the ranking.

[0137] Step 706: Based on the designated on-site non-staff information, the corresponding on-site non-staff mobile device is searched from the preset non-staff database, and an abnormal situation inquiry signal is sent to the on-site non-staff mobile device until a normal situation response option or a special situation response option is generated or the response time is exceeded.

[0138] The mobile device of the non-staff present is a mobile device associated with the designated non-staff present information. The mapping relationship between the designated non-staff present information and the mobile device of the non-staff present is stored in the database. It can be obtained by searching the database. When the system receives the corresponding designated non-staff present information, it automatically searches the database for the corresponding mobile device of the non-staff present and outputs it.

[0139] Step 707: When the normal situation reply option or the special situation reply option is not received within the response time, the designated on-site non-staff information is removed from the on-site non-staff group and the designated on-site non-staff information is updated, and the on-site non-staff mobile device is updated until the normal situation reply option or the special situation reply option is received, or the on-site non-staff group does not exist.

[0140] If no normal response option or special response option is received within the response time, it means that the designated non-staff information on site has not responded, or the mobile phone number is incorrect. Therefore, in order to reduce unnecessary time, directly skip this designated non-staff information on site and search for the next one until someone can provide feedback.

[0141] Step 708: Output a normal situation reply option when there is no on-site non-staff group.

[0142] When there is no non-staff group present, it means that there is no one at this time, so the system can respond according to the normal situation, that is, output the normal situation response option.

[0143] Based on the same inventive concept, an embodiment of the present invention provides a lamp color temperature control system.

[0144] Reference Figure 8 , a lamp color temperature control system, comprising: The acquisition module is used to obtain the regional video, the lighting area itself and the on-duty staff information; A memory, used for storing a program of a control method of a lamp color temperature control method; The program in the memory can be loaded and executed by the processor to implement a control method for controlling the color temperature of a lamp.

[0145] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0146] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that can be loaded and executed by a processor and a method for controlling the color temperature of a lamp.

[0147] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0148] Based on the same inventive concept, an embodiment of the present invention provides an intelligent terminal, including a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executed by a method for controlling the color temperature of a lamp.

[0149] The above are all preferred embodiments of the present application, and are not intended to limit the protection scope of the present application. Any feature disclosed in this specification (including the abstract and drawings), unless otherwise stated, can be replaced by other equivalent or alternative features with similar purposes. That is, unless otherwise stated, each feature is only an example of a series of equivalent or similar features.

Claims

1. A method for controlling the color temperature of a lamp, characterized in that: include: Get the area video within the preset lighting area; Analyze the regional video based on preset influencing features to obtain regional conditions, wherein the influencing features include pedestrian flow features and vehicle flow features; The regional conditions are converted according to the preset conversion rules to obtain the color temperature index; Based on the color temperature index, the corresponding color temperature control situation is found from the preset temperature control database; The lamps corresponding to the lighting area are controlled according to the color temperature control situation.

2. A lamp color temperature control method according to claim 1, characterized in that: Methods for analyzing regional videos based on impact features to obtain regional conditions include: Determine video clarity based on regional video and impact features; When the video clarity falls within the preset clarity range, the regional video is directly analyzed based on the influencing features to obtain the regional situation; When the video clarity falls within a preset blur level range, the regional video is defined as a blurry regional video; Control the lamps corresponding to the lighting area according to the preset high color temperature and reacquire the area video, and define the reacquired area video as a clear area video; The clear area video is analyzed based on the impact features to obtain the regional situation.

3. A lamp color temperature control method according to claim 2, characterized in that: The method of controlling the lamps corresponding to the lighting area according to the high color temperature and obtaining a clear area video includes: Determine whether there is a human flow feature in the blurred area video based on the impact feature; When there are crowd features in the blurred area video, the lamps corresponding to the lighting area are controlled according to the high color temperature and continue for the preset safety impact time; Reacquire the regional video within the safety impact duration, and define the reacquired regional video as a clear regional video; When there is no crowd feature, the lamps corresponding to the lighting area are controlled according to the high color temperature condition and the instantaneous area video whose video clarity falls within the clarity range is obtained; When there is no crowd feature in the instantaneous area video, the instantaneous area video is directly output as a clear area video; When there are crowd features in the instantaneous area video, the lamps corresponding to the lighting area will continue to have a safety impact duration and a clear area video will be obtained within the safety impact duration.

4. A lamp color temperature control method according to claim 3, characterized in that: The method also includes controlling the lamps corresponding to the lighting area according to the high color temperature after the interval time and continuing to obtain the clear area video. The method for determining the interval time includes: The cumulative number of acquisitions of blurred area videos; When the acquisition number is the preset first number, the preset standard interval duration is output as the interval duration, and the corresponding clear area video acquired is defined as the first clear area video; When the number of acquisitions is not the preset first number of times, the blurred area video is acquired again after the interval time and the clear area video is acquired again, and the corresponding acquired clear area video is defined as the second clear area video, and the clear area video acquired last time is defined as the third clear area video, and the third clear area video is the video adjacent to the second clear area video; Analyze the first clear area video based on the influencing feature to obtain a first pedestrian flow feature quantity, a first vehicle flow feature quantity, and a first vehicle flow feature speed; Analyze the second clear area video based on the impact feature to obtain a second pedestrian feature quantity, a second vehicle feature quantity, and a second vehicle feature speed; Analyze the third clear area video based on the impact feature to obtain a third pedestrian flow feature quantity, a third vehicle flow feature quantity, and a third vehicle flow feature speed; Determine a first crowd flow change trend based on the first crowd flow feature quantity and the second crowd flow feature quantity; Determine a first traffic flow change trend based on the first traffic flow feature quantity, the second traffic flow feature quantity, the first traffic flow feature speed, and the second traffic flow feature speed; Determine a second flow of people change trend based on the third flow of people feature quantity and the second flow of people feature quantity; Determine a first traffic flow change trend based on the third traffic flow feature quantity, the second traffic flow feature quantity, the third traffic flow feature speed, and the first traffic flow feature speed; When the acquisition number is the preset second number, based on the first pedestrian flow change trend, the first vehicle flow change trend and the interval duration, a corresponding first change interval duration is searched from a preset change database, and outputted as the interval duration; When the number of acquisitions is neither the first number nor the second number, the corresponding second change interval duration is searched from a preset change database based on the second pedestrian flow change trend, the second vehicle flow change trend and the interval duration, and is output as the interval duration.

5. The method for controlling the color temperature of a lamp according to claim 1, characterized in that: The conversion rule is to first obtain a traffic speed parameter by multiplying a traffic characteristic speed by a preset traffic speed ratio, to obtain a traffic quantity parameter by multiplying a traffic characteristic quantity by a preset traffic quantity ratio, and to obtain a traffic quantity parameter by multiplying a pedestrian characteristic quantity by a preset pedestrian quantity ratio, wherein the traffic characteristic speed is the speed of a successfully matched traffic characteristic, the traffic characteristic quantity is the quantity of successfully matched traffic characteristics, and the pedestrian characteristic quantity is the quantity of successfully matched pedestrian characteristics. The method for converting the regional situation according to the preset conversion rule to obtain a color temperature index includes: Get the lighting area status; The lighting area itself is disassembled to obtain the standard pedestrian flow characteristic range and the standard vehicle flow characteristic range; Disassemble the regional situation to obtain the actual pedestrian flow characteristics and actual vehicle flow characteristics; When the actual pedestrian flow characteristics fall within the standard pedestrian flow characteristics range, and the actual vehicle flow characteristics fall within the standard vehicle flow characteristics range, the color temperature index is calculated according to the preset vehicle flow speed ratio, vehicle flow quantity ratio, pedestrian quantity ratio, actual pedestrian flow characteristics and actual vehicle flow characteristics; When the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range, the degree of difference in the pedestrian flow characteristics is determined based on the actual pedestrian flow characteristics and the standard pedestrian flow characteristics range; Determine the degree of difference in traffic flow characteristics based on actual traffic flow characteristics and the range of standard traffic flow characteristics; Based on the difference in crowd flow characteristics, the corresponding corrected crowd flow ratio is found from a preset crowd flow correction database; Based on the degree of difference in traffic flow characteristics, the corresponding corrected traffic flow quantity ratio and corrected traffic flow speed ratio are found from a preset traffic flow correction database; The color temperature index is calculated based on the corrected pedestrian flow ratio, corrected vehicle flow ratio, corrected pedestrian flow ratio, actual pedestrian flow characteristics and actual vehicle flow characteristics.

6. A lamp color temperature control method according to claim 5, characterized in that: Methods for calculating the color temperature index according to the corrected proportion of pedestrian flow, the corrected proportion of vehicle flow, the corrected proportion of pedestrian flow, the actual characteristics of pedestrian flow and the actual characteristics of vehicle flow include: When the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range, an abnormal situation inquiry signal is issued; When a preset normal situation response option is received or no response option is received, the color temperature index is calculated according to the corrected pedestrian flow ratio, the corrected vehicle flow ratio, the corrected pedestrian flow ratio, the actual pedestrian flow characteristics and the actual vehicle flow characteristics; When receiving a preset special situation response option, searching the preset special correction database for the corresponding special correction pedestrian flow ratio, special correction vehicle flow ratio and / or special correction vehicle flow speed ratio based on the special situation response option; The found special corrected pedestrian flow ratio, special corrected vehicle flow ratio and / or special corrected vehicle flow speed ratio are replaced with the corresponding corrected pedestrian flow ratio, corrected vehicle flow ratio and / or corrected pedestrian flow ratio, and then the color temperature index is calculated based on the actual pedestrian flow characteristics and the actual vehicle flow characteristics.

7. A lamp color temperature control method according to claim 6, characterized in that: The method of sending an abnormal situation inquiry signal when the actual pedestrian flow characteristics do not fall within the standard pedestrian flow characteristics range, or the actual vehicle flow characteristics do not fall within the standard vehicle flow characteristics range includes: Analyze the regional video based on the preset staff characteristics to obtain the information of the staff on site; When the on-site staff information exists, searching for the corresponding on-site staff mobile device from a preset staff database based on the on-site staff information, and sending an abnormal situation inquiry signal to the on-site staff mobile device; Obtaining on-duty staff information when on-site staff information does not exist; Find the corresponding mobile device of the on-duty staff from the staff database based on the on-duty staff information, and send an abnormal situation inquiry signal to the mobile device of the on-duty staff; When no normal situation response option or special situation response option is received within the preset response time, the regional video is analyzed based on the impact characteristics to obtain the successfully matched non-staff information on site; sorting the on-site non-staff information based on a preset informed judgment rule to obtain an on-site non-staff group, and defining the on-site non-staff information at the first position as designated on-site non-staff information; Based on the designated on-site non-staff information, a corresponding on-site non-staff mobile device is searched from a preset non-staff database, and an abnormal situation inquiry signal is sent to the on-site non-staff mobile device until a normal situation response option or a special situation response option is generated or the response time is exceeded; When no normal situation reply option or special situation reply option is received within the response time, the designated on-site non-staff information is removed from the on-site non-staff group, and the designated on-site non-staff information is updated, and the on-site non-staff mobile device is updated until the normal situation reply option or special situation reply option is received, or the on-site non-staff group does not exist; Outputs normal response options when there is no non-staff group present.

8. A lamp color temperature control system, characterized in that: include: The acquisition module is used to obtain the regional video, the lighting area itself and the on-duty staff information; A memory, used to store a program of a control method of a lamp color temperature control method according to any one of claims 1 to 7; The program in the memory can be loaded and executed by the processor to implement a control method for controlling the color temperature of a lamp as described in any one of claims 1 to 7.

9. Intelligent terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a computer program that can be loaded by the processor and executes a method for controlling the color temperature of a lamp as claimed in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that A computer program is stored which can be loaded by a processor and executes a lamp color temperature control method according to any one of claims 1 to 7.

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