Intelligent control method for lighting equipment, intelligent control lighting equipment and electronic equipment

Abstract

The present invention provides a lighting equipment intelligent control method, intelligent control lighting equipment and electronic equipment, which relates to the field of lighting control, including: obtaining single environmental factor data of a lighting area; estimating the flow of people in the future time period of the lighting area based on the environmental data of the lighting area; determining the corresponding flow classification based on the flow of people in the future time period, and generating a lighting control strategy for the lighting equipment based on the flow classification corresponding to the flow of people in the future time period; controlling the lighting of the lighting equipment according to the lighting control strategy. The present invention not only improves the efficiency and reliability of the lighting system, but also effectively reduces energy consumption, providing users with a more comfortable and energy-saving lighting environment.

Description

Technical Field

[0001] The present invention relates to the field of lighting control technology, and in particular to an intelligent control method for lighting equipment, intelligent control lighting equipment and electronic equipment. Background Art

[0002] In modern urban construction, public places such as squares, parks, and parks are important places for citizens to relax, entertain, and carry out daily activities. Their nighttime lighting is not only related to public safety and convenience of passage, but also an important embodiment of the city's image and the concept of energy conservation and carbon reduction. These places usually have significant tidal changes in the user population, especially in the evening to early night (such as 18:00 to 22:00), when the flow of people is dense and the demand for lighting is high; while in the late night to the next morning (such as 22:00 to 6:00 the next day), the flow of people is greatly reduced, but basic lighting is still needed to ensure safety and nighttime passage.

[0003] Most traditional lawn lights use a simple time-sharing control strategy, that is, a few fixed time periods are preset and the lights are turned on and off by a timer. Although this control method is simple and easy to use, it lacks flexibility and cannot dynamically adjust the lighting brightness or the number of lights turned on according to the real-time changes in the flow of people, resulting in serious energy waste. In particular, the performance of solar lawn lights is limited by sunlight conditions. In continuous rainy weather, the battery energy storage is insufficient and it is difficult to meet the lighting needs during peak hours. In the late night when there is low traffic, the battery may be turned off prematurely due to excessive discharge, and it is unable to provide the necessary night lighting.

[0004] In addition, although existing intelligent lighting control systems can automatically adjust lighting according to ambient light or preset conditions to a certain extent, they often lack accurate perception and response mechanisms for dynamic changes in human traffic, resulting in a mismatch between lighting strategies and actual needs. For example, the system may make adjustments based on a fixed schedule or ambient brightness threshold, ignoring actual changes in human traffic, resulting in over-lighting when human traffic is sparse, or under-lighting when human traffic increases.

[0005] Therefore, an intelligent control method for lighting equipment, an intelligent control lighting equipment and an electronic device are proposed. Summary of the invention

[0006] This specification provides a lighting equipment intelligent control method, intelligent control lighting equipment and electronic equipment, which not only improves the efficiency and reliability of the lighting system, but also effectively reduces energy consumption, providing users with a more comfortable and energy-saving lighting environment.

[0007] This specification provides a lighting equipment intelligent control method, including:

[0008] Obtain single environmental factor data of lighting area;

[0009] estimating the flow of people in the lighting area in a future time period based on the lighting area environmental data;

[0010] Determine a corresponding human flow classification based on the human flow in the future time period, and generate a lighting control strategy for the lighting equipment based on the human flow classification corresponding to the human flow in the future time period;

[0011] The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

[0012] Optionally, also include:

[0013] Acquire multiple environmental factor data of the lighting area; wherein the multiple environmental factor data includes time factor data and weather factor data;

[0014] Evaluate based on the time factor data and the weather factor data respectively to obtain a first flow of people in a future time period and a second flow of people in a future time period;

[0015] Determine whether the first flow of people in the future time period is the same as the second flow of people in the future time period;

[0016] When the first human flow in the future time period is the same as the second human flow in the future time period, a corresponding human flow classification is determined based on the first human flow in the future time period / the second human flow in the future time period, and a lighting control strategy for the lighting equipment is generated based on the human flow classification corresponding to the first human flow in the future time period / the second human flow in the future time period;

[0017] The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

[0018] Optionally, also include:

[0019] When the first human flow in the future time period is different from the second human flow in the future time period, the average human flow in the future time period is determined based on the first human flow in the future time period and the second human flow in the future time period, the corresponding human flow grade is determined based on the average human flow in the future time period, and the lighting control strategy of the lighting equipment is generated based on the human flow grade corresponding to the average human flow in the future time period.

[0020] Optionally, also include:

[0021] The multiple environmental factor data also includes seasonal factor data;

[0022] Evaluate based on the time factor data, the weather factor data, and the season factor data respectively to obtain a first flow of people in a future time period, a second flow of people in a future time period, and a third flow of people in a future time period;

[0023] Determine whether the first person flow in the future time period, the second person flow in the future time period, and the third person flow in the future time period are the same;

[0024] When the first flow of people in the future time period, the second flow of people in the future time period, and the third flow of people in the future time period are different, taking the maximum value of the first flow of people in the future time period, the second flow of people in the future time period, and the third flow of people in the future time period as the predicted flow of people, determining the corresponding flow of people classification based on the predicted flow of people, and generating the lighting control strategy of the lighting equipment based on the flow of people classification corresponding to the predicted flow of people;

[0025] The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

[0026] Optionally, also include:

[0027] Obtain the current actual flow of people in the lighting area in real time;

[0028] Determine whether the deviation between the current actual flow of people and the estimated flow of people in the current time period meets the preset deviation value;

[0029] When the deviation between the current actual flow of people and the estimated flow of people in the current time period does not meet the preset deviation value, determining whether the current actual flow of people is greater than the estimated flow of people in the current time period;

[0030] When the current actual human flow is greater than the estimated human flow in the current time period, determining a human flow classification corresponding to the current actual human flow based on the current actual human flow, and generating a lighting control strategy for the lighting equipment based on the human flow classification corresponding to the current actual human flow;

[0031] The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

[0032] Optionally, also include:

[0033] When the current actual flow of people is less than the estimated flow of people in the current time period, the lighting components of the lighting device continue to be controlled to turn on and off according to the lighting control strategy.

[0034] This specification provides an intelligent control lighting device, comprising: a horizontal component and a vertical component, wherein the horizontal component is connected to one end of the vertical component, and the other end of the vertical component is connected to the ground;

[0035] A solar panel is provided on one side of the transverse component away from the longitudinal component, a lamp bead lighting area is provided on one side of the transverse component close to the longitudinal component, an infrared sensing sensor is provided on at least one end of the transverse component, and a light-storing light strip is provided on at least one side of the longitudinal component.

[0036] This specification also provides an electronic device, wherein the electronic device includes:

[0037] processor; and,

[0038] A memory storing computer executable instructions, which when executed cause the processor to perform any of the above methods.

[0039] The present specification also provides a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, any of the above methods is implemented.

[0040] In the present invention, multiple environmental factors such as time, weather, and season in the lighting area are comprehensively considered, and the flow of people in the future time period is accurately estimated through advanced prediction models, and the on and off status of the lighting equipment is dynamically adjusted accordingly. In addition, the method can also obtain the current actual flow of people in the lighting area in real time, and compare and analyze it with the estimated flow of people. When there is a significant deviation between the actual flow of people and the estimated value, it can quickly respond and adjust the lighting control strategy to ensure that the lighting equipment always matches the actual situation of the lighting area and user needs. This intelligent control method not only improves the efficiency and reliability of the lighting system, but also effectively reduces energy consumption, providing users with a more comfortable and energy-saving lighting environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0042] Figure 1 A schematic diagram of the principle of an intelligent control method for lighting equipment provided in an embodiment of this specification;

[0043] Figure 2 A schematic diagram of the structure of an intelligent control lighting device provided in an embodiment of this specification;

[0044] Figure 3 A schematic diagram of the structure of an electronic device provided in an embodiment of this specification;

[0045] Figure 4A schematic diagram of a computer-readable medium provided in accordance with an embodiment of the present specification.

[0046] The accompanying drawings illustrate: 10, horizontal component; 11, light-storing light strip; 21, vertical component; 22, solar panel; 23, infrared sensing sensor. DETAILED DESCRIPTION

[0047] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments described below are only examples, and those skilled in the art can think of other obvious variations. The basic principles of the present invention defined in the following description can be applied to other embodiments, variations, improvements, equivalents, and other technical solutions that do not deviate from the spirit and scope of the present invention.

[0048] The following is combined with Figure 1-4 The exemplary embodiments of the present invention are described more fully. However, the exemplary embodiments can be implemented in various forms, and it should not be understood that the present invention is limited to the embodiments set forth herein. On the contrary, providing these exemplary embodiments can make the present invention more comprehensive and complete, and it is more convenient to fully convey the inventive concept to those skilled in the art. The same reference numerals in the figures represent the same or similar elements, components or parts, and thus their repeated description will be omitted.

[0049] Under the premise of being consistent with the technical concept of the present invention, the features, structures, characteristics or other details described in a specific embodiment do not exclude that they can be combined in one or more other embodiments in a suitable manner.

[0050] In the description of specific embodiments, the features, structures, characteristics or other details described in the present invention are intended to enable those skilled in the art to fully understand the embodiments. However, it does not exclude that those skilled in the art can practice the technical solutions of the present invention without one or more of the specific features, structures, characteristics or other details.

[0051] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps can be decomposed, and some operations / steps can be combined or partially combined, so the actual execution order may change according to actual conditions.

[0052] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0053] The term "and / or" or "and / or" includes all combinations of any one or more of the associated listed items.

[0054] Figure 1 A schematic diagram of the principle of a lighting equipment intelligent control method provided in an embodiment of this specification, the method may include:

[0055] S110: Acquire single environmental factor data of the lighting area;

[0056] In a specific embodiment of the present specification, a variety of environmental sensing devices are installed at key locations in the lighting area, including but not limited to infrared human body sensors, Wi-Fi hotspot detectors, Bluetooth signal receivers, sound sensors, and light sensors. These devices can capture single environmental factor data such as the flow of people in the area, the number of device connections (indirectly reflecting the density of the crowd), the sound level, and the intensity of natural light in real time. The collected raw data is transmitted to the central control unit or cloud server through the Internet of Things (IoT) technology, and data cleaning and preprocessing technology are used to remove noise to ensure the accuracy and completeness of the data. At the same time, time series analysis methods are used to identify the periodicity, trend, and outliers of the data, providing a reliable basis for subsequent predictions.

[0057] S120: estimating the flow of people in the lighting area in a future time period based on the lighting area environment data;

[0058] In the specific implementation of this specification, a crowd flow prediction model is constructed using machine learning algorithms (such as support vector machines SVM, random forest RF, long short-term memory network LSTM, etc.). These models predict the flow of people in the future time period by learning the relationship between historical crowd flow data and environmental factors (such as weather, holidays, special events, etc.). During the model training process, environmental factor data (such as current weather forecast, holiday arrangements, social media popularity, etc.) and historical crowd flow data are combined, and feature selection and fusion technology are used to screen out the feature combination that contributes most to crowd flow prediction, thereby improving prediction accuracy.

[0059] S130: determining a corresponding human flow classification based on the human flow in the future time period, and generating a lighting control strategy for the lighting equipment based on the human flow classification corresponding to the human flow in the future time period;

[0060] In the specific implementation of this specification, multiple crowd flow classification standards (such as low, medium, high, and very high) are set according to the actual needs and operation strategies of the lighting area, and each classification corresponds to a different crowd density range. Based on the predicted crowd flow classification, differentiated lighting control strategies are formulated. For example, during peak crowd flow periods (high, very high), maintain or increase lighting brightness to ensure safety and visual comfort; during low crowd flow periods (low), reduce lighting brightness or turn off some lamps to save energy. At the same time, factors such as lighting uniformity and color temperature are considered to create a suitable night environment atmosphere.

[0061] S140: Controlling the lighting components of the lighting device to turn on and off according to the lighting control strategy.

[0062] In the specific implementation of this specification, the central control unit or cloud server sends control instructions to the lighting device through a wireless communication protocol (such as Zigbee, LoRa, NB-IoT, etc.) according to the generated lighting control strategy. After receiving the instructions, the intelligent controller built into the lighting device automatically adjusts the on and off state, brightness level or color temperature of the lighting component to achieve refined lighting control. At the same time, the device status information is fed back to the control system in real time to form a closed-loop control to ensure that the lighting effect is consistent with the expected strategy.

[0063] By collecting actual traffic data and energy consumption data in the lighting area and comparing them with the prediction results, the effectiveness of the lighting control strategy can be evaluated. Based on the evaluation results, the prediction model parameters are continuously adjusted, the traffic classification standards are optimized, and the lighting control strategy is improved to achieve continuous learning and optimization of the system.

[0064] Optionally, also include:

[0065] Acquire multiple environmental factor data of the lighting area; wherein the multiple environmental factor data includes time factor data and weather factor data;

[0066] Evaluate based on the time factor data and the weather factor data respectively to obtain a first flow of people in a future time period and a second flow of people in a future time period;

[0067] Determine whether the first flow of people in the future time period is the same as the second flow of people in the future time period;

[0068] When the first human flow in the future time period is the same as the second human flow in the future time period, a corresponding human flow classification is determined based on the first human flow in the future time period / the second human flow in the future time period, and a lighting control strategy for the lighting equipment is generated based on the human flow classification corresponding to the first human flow in the future time period / the second human flow in the future time period;

[0069] The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

[0070] In the specific implementation of this specification, the time factor data includes the current date, day of the week, holiday information, seasonal changes, etc. These factors usually affect people's daily activities and thus affect the flow of people in the lighting area. Weather factor data is obtained through the weather forecast API or the local weather station, including but not limited to temperature, humidity, precipitation, wind speed, wind direction, cloud cover, sunshine duration, etc. Weather conditions directly affect people's willingness to engage in outdoor activities and are an important reference for predicting the flow of people.

[0071] By using the correlation analysis between historical passenger flow data and time factor data (such as weekdays and weekends, holidays and non-holidays, seasonal changes, etc.), a time series prediction model or classification model is constructed to predict the first passenger flow in the future time period. Based on the statistical analysis of historical passenger flow data and weather factor data, the influence pattern of weather conditions on passenger flow is identified, such as the change pattern of passenger flow under sunny, rainy, high temperature, low temperature and other weather conditions. Using these rules, a flow prediction model under the influence of weather is constructed to predict the second passenger flow in the future time period. The first passenger flow predicted based on time factors is compared with the second passenger flow predicted based on weather factors. Since the two may be based on different assumptions and models, the prediction results may be different. According to the accuracy of historical data, the confidence of the model and the particularity of the current environment (such as sudden weather events, special event arrangements, etc.), different weights are assigned to the first passenger flow and the second passenger flow, and weighted average is performed to obtain the final predicted passenger flow.

[0072] According to the actual situation of the lighting area, different crowd flow classification standards are set, such as low, medium, high, and very high. Each classification corresponds to one or more specific crowd flow ranges. Based on the final predicted crowd flow classification, differentiated lighting control strategies are formulated. For example, when the crowd flow is low, the lighting brightness is reduced or some lighting equipment is turned off to save energy; when the crowd flow is high, the lighting brightness is maintained or increased to ensure safety and visual comfort. At the same time, the energy efficiency, maintenance cost and user experience of the lighting equipment are considered to comprehensively determine the lighting control plan.

[0073] Optionally, also include:

[0074] When the first human flow in the future time period is different from the second human flow in the future time period, the average human flow in the future time period is determined based on the first human flow in the future time period and the second human flow in the future time period, the corresponding human flow grade is determined based on the average human flow in the future time period, and the lighting control strategy of the lighting equipment is generated based on the human flow grade corresponding to the average human flow in the future time period.

[0075] In the specific implementation of this specification, the average value of the flow of people in the future time period is calculated, and this average value can be used as the basis for the subsequent lighting control strategy. When calculating the average value, the uncertainty of the prediction result should also be considered. This uncertainty can be quantified by calculating the confidence interval or standard deviation of the predicted value, providing additional reference information for the subsequent strategy formulation.

[0076] According to the actual situation of the lighting area, different crowd flow classification standards are set. Each classification corresponds to one or more specific crowd flow ranges and corresponding lighting needs. The calculated average crowd flow of the future time period is compared with the classification standard to determine the crowd flow classification to which it belongs. According to the determined crowd flow classification, differentiated lighting control strategies are formulated. This includes adjusting the lighting brightness, color temperature, turning on / off lighting equipment, etc. When formulating strategies, energy saving and optimization should be fully considered. For example, when the crowd flow is low, the lighting brightness can be reduced or some lighting equipment can be turned off to save energy; when the crowd flow is high, the lighting brightness should be maintained or increased to ensure safety and visual comfort. At the same time, you can also consider using energy-efficient lighting equipment and technologies, such as LED lighting, intelligent dimming systems, etc.

[0077] Optionally, also include:

[0078] The multiple environmental factor data also includes seasonal factor data;

[0079] Evaluate based on the time factor data, the weather factor data, and the season factor data respectively to obtain a first flow of people in a future time period, a second flow of people in a future time period, and a third flow of people in a future time period;

[0080] Determine whether the first person flow in the future time period, the second person flow in the future time period, and the third person flow in the future time period are the same;

[0081] When the first flow of people in the future time period, the second flow of people in the future time period, and the third flow of people in the future time period are different, taking the maximum value of the first flow of people in the future time period, the second flow of people in the future time period, and the third flow of people in the future time period as the predicted flow of people, determining the corresponding flow of people classification based on the predicted flow of people, and generating the lighting control strategy of the lighting equipment based on the flow of people classification corresponding to the predicted flow of people;

[0082] The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

[0083] In the specific implementation of this specification, on the basis of the original, the collection of seasonal factor data is added. Seasonal factor data includes information on the current season (spring, summer, autumn, winter), specific time periods within the season (such as the spring pollen peak, winter ski season, etc.), and seasonal activities (such as festivals, cultural exhibitions, etc.). The impact of these factors on the flow of people cannot be ignored, especially in tourist areas and areas with frequent seasonal activities.

[0084] Based on the correlation analysis between historical passenger flow data and time factors (date, week, holidays, etc.), the first passenger flow in the future time period is predicted. Using the weather forecast API or local weather station data, combined with the statistical analysis of historical passenger flow data and weather factors, the second passenger flow in the future time period is predicted. According to seasonal characteristics, seasonal activity arrangements and historical passenger flow data, a seasonal passenger flow prediction model is constructed to predict the third passenger flow in the future time period. This requires considering the impact of seasons on people's outdoor activity habits, travel preferences and special event arrangements. Compare and analyze the first, second and third passenger flows predicted based on time, weather and seasonal factors. Because different factors may affect passenger flow independently or intertwinedly, the prediction results may differ.

[0085] When the first, second, and third person flows are different, in order to ensure that the lighting equipment can meet the needs of peak hours, the maximum value among the first, second, and third person flows is used as the predicted person flow. This strategy is conservative, but it can effectively avoid insufficient lighting. While selecting the maximum value as the predicted person flow, the uncertainty of the prediction results should also be considered. This uncertainty can be quantified by calculating the confidence interval or standard deviation of each predicted value, and leaving room in the lighting control strategy to cope with possible fluctuations.

[0086] According to the actual situation of the lighting area, different crowd flow classification standards are set. Each classification corresponds to one or more specific crowd flow ranges and corresponding lighting needs. Based on the determined predicted crowd flow and crowd flow classification, differentiated lighting control strategies are formulated. This includes adjusting lighting brightness, color temperature, turning on / off lighting equipment, etc. to ensure that the lighting effect matches the predicted crowd flow.

[0087] Optionally, also include:

[0088] Obtain the current actual flow of people in the lighting area in real time;

[0089] Determine whether the deviation between the current actual flow of people and the estimated flow of people in the current time period meets the preset deviation value;

[0090] When the deviation between the current actual flow of people and the estimated flow of people in the current time period does not meet the preset deviation value, determining whether the current actual flow of people is greater than the estimated flow of people in the current time period;

[0091] When the current actual human flow is greater than the estimated human flow in the current time period, determining a human flow classification corresponding to the current actual human flow based on the current actual human flow, and generating a lighting control strategy for the lighting equipment based on the human flow classification corresponding to the current actual human flow;

[0092] The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

[0093] In the specific implementation of this specification, a crowd counter, camera (combined with image processing technology) or Wi-Fi / Bluetooth tracking device installed at the entrance, exit or key position of the lighting area is used to collect data on the number of people entering and leaving the lighting area in real time. The collected crowd data is processed in real time, including deduplication, verification and aggregation, to obtain the current actual crowd flow. According to the speed of change of crowd flow in the lighting area and the real-time requirements of lighting control, an appropriate data update frequency is set, such as updating once per second, once per minute or once per hour.

[0094] Based on historical data, time factors, weather factors, seasonal factors and other multi-dimensional information, use machine learning or statistical models to predict the estimated flow of people in the current time period. Calculate the difference between the current actual flow of people and the estimated flow of people to obtain the deviation value. According to the actual situation of the lighting area and the accuracy requirements of lighting control, set a reasonable preset deviation value. This value can be a fixed value or a percentage.

[0095] Determine whether the current actual flow of people is greater than the estimated flow of people: When the deviation value does not meet the preset deviation value, first determine whether the current actual flow of people is greater than the estimated flow of people. If the current actual flow of people is greater than the estimated flow of people, it means that the flow density of people in the lighting area is higher than expected, and dynamic adjustment needs to be prepared.

[0096] According to the actual situation and lighting needs of the lighting area, different crowd flow classification standards are set, such as low, medium, high, and very high. The current actual crowd flow is compared with the classification standards to determine the crowd flow classification it belongs to. Based on the determined crowd flow classification, the corresponding lighting control strategy is generated. This may include increasing the lighting brightness, turning on additional lighting equipment, adjusting the color temperature to provide a more comfortable visual environment, etc.

[0097] Optionally, also include:

[0098] When the current actual flow of people is less than the estimated flow of people in the current time period, the lighting components of the lighting device continue to be controlled to turn on and off according to the lighting control strategy.

[0099] In a specific implementation of the present specification, if the current actual flow of people is less than the estimated flow of people in the current time period, but the deviation is still within an acceptable range (i.e., less than the preset negative deviation threshold), the lighting components of the lighting equipment can continue to be controlled according to the currently executed lighting control strategy. If the current actual flow of people is significantly lower than the estimated flow of people, and the deviation exceeds the preset negative deviation threshold, further optimization of the lighting control strategy can be considered to reduce unnecessary energy consumption. This includes but is not limited to reducing the lighting brightness, turning off some lighting equipment, or adjusting the lighting mode to a more energy-saving state.

[0100] Evaluate the currently implemented lighting control strategy to determine if there is room for optimization. This can be achieved by analyzing historical data, the energy consumption of lighting equipment, and the lighting needs of users. Based on the evaluation results, develop one or more optimization plans. These plans should aim to reduce energy consumption while ensuring that the lighting effect meets basic requirements. For example, you can develop a plan to dynamically adjust the lighting brightness based on the flow of people, or automatically reduce the overall lighting brightness based on time periods (such as late at night). After selecting the best plan, convert it into specific control instructions and send it to the lighting equipment through the Internet of Things technology. After receiving the instructions, the lighting equipment adjusts the on and off status, brightness level or color temperature of its lighting components according to the content of the instructions. After implementing the optimization plan, continuously monitor the actual flow of people, lighting effects and energy consumption in the lighting area. Compare and analyze these data with the expected goals to evaluate the effectiveness of the optimization plan. If the effect is not ideal, you can make adjustments or try other optimization plans based on the feedback results.

[0101] If the deviation between the current actual flow of people and the estimated flow of people continues to exceed the preset negative deviation threshold and cannot be resolved by the optimization strategy, the anomaly detection mechanism is triggered. This may be due to external factors (such as emergencies, sudden weather changes, etc.). After the anomaly detection mechanism is triggered, the central control system sends an alarm message to the management personnel and recommends further measures. These measures may include increasing the flexibility of lighting equipment (such as enabling backup lighting solutions), adjusting the location or number of people flow monitoring equipment to improve accuracy, etc. Record the time, location, cause and other information of the anomaly and conduct in-depth analysis. This helps to identify potential sources of problems and develop preventive measures to avoid similar situations in the future.

[0102] In the present invention, multiple environmental factors such as time, weather, and season in the lighting area are comprehensively considered, and the flow of people in the future time period is accurately estimated through advanced prediction models, and the on and off status of the lighting equipment is dynamically adjusted accordingly. In addition, the method can also obtain the current actual flow of people in the lighting area in real time, and compare and analyze it with the estimated flow of people. When there is a significant deviation between the actual flow of people and the estimated value, it can quickly respond and adjust the lighting control strategy to ensure that the lighting equipment always matches the actual situation of the lighting area and user needs. This intelligent control method not only improves the efficiency and reliability of the lighting system, but also effectively reduces energy consumption, providing users with a more comfortable and energy-saving lighting environment.

[0103] Figure 2 A schematic diagram of the principle of an intelligent control lighting device provided in an embodiment of this specification, the device may include:

[0104] A transverse component and a longitudinal component, wherein the transverse component is connected to one end of the longitudinal component, and the other end of the longitudinal component is connected to the ground;

[0105] A solar panel is provided on one side of the transverse component away from the longitudinal component, a lamp bead lighting area is provided on one side of the transverse component close to the longitudinal component, an infrared sensing sensor is provided on at least one end of the transverse component, and a light-storing light strip is provided on at least one side of the longitudinal component.

[0106] In the specific implementation of this specification, the shell of the horizontal component is made of die-cast aluminum alloy to ensure the durability and corrosion resistance of the lamp. In terms of design, the overall lines of the horizontal component are smooth and distinctive, and the connection part with the lamp pole column (vertical component) achieves a smooth transition to enhance the overall aesthetics.

[0107] On the side of the horizontal component away from the vertical component, a high-efficiency solar panel is installed. The solar panel is responsible for collecting sunlight and converting it into electrical energy to provide green energy for the lamp. The design of the solar panel should take into account its angle and direction to ensure maximum absorption of sunlight.

[0108] On the side of the horizontal component close to the vertical component, there is a lamp bead lighting area. This area contains 7 LED lamp beads arranged in a straight line, each with a power of 1W. Among them, the central LED lamp bead is an independent circuit, powered by the battery inside the lamp head, realizing lighting in solar power supply mode. The other six LED lamp beads are another independent circuit, powered by the mains, ensuring sufficient lighting when solar energy is insufficient or at night.

[0109] At least one end (usually the front end) of the lateral component is equipped with an infrared sensor. The sensor can detect the movement of pedestrians or objects, thereby triggering the lighting system to switch on or off or adjusting the lighting brightness. The design of the infrared sensor should take into account its sensing range and sensitivity to ensure that it can accurately detect the approach of pedestrians.

[0110] The vertical component is a light pole column with a height of 700mm and a moderate width (i.e. the diameter or width of the light pole), which forms an overall coordinated appearance with the horizontal component. LED lights and light-storage luminescent materials are installed on the front facade of the light pole column. The LED lights are powered by the mains with a power of 10W / m (calculated according to the actual length) to provide additional lighting effects. Light-storage luminescent materials can store the energy of light and release it after the light source is cut off. Visible light can last for 6 hours in the dark. This material not only enhances the lighting effect, but also improves the energy saving and practicality of the lamp.

[0111] One end of the horizontal component is fixedly connected to the longitudinal component by a reliable connection method (such as bolt connection, welding, etc.). The other end of the longitudinal component is connected to the ground by embedded parts, expansion plugs or other fixing devices to ensure the stability and safety of the entire lamp.

[0112] During peak traffic hours (usually 18:00-22:00, adjustable), the six LED lamp beads under the lamp head provide uniform and soft ground lighting, powered by the mains. At the end of the peak period (such as 22:00-22:30, adjustable), the six lamp beads continue to illuminate, and the LED lights and light-storing materials on the lamp pole columns are also lit to provide atmosphere lighting and visual guidance. At this time, the light-storing materials begin to store energy. During the low traffic period (usually 22:30-6:00, adjustable), the lamp automatically cuts off the mains power supply and enters the energy-free mode. At this time, the LED light-storing lamps on the columns can still emit low-brightness lighting after power failure, ensuring the basic lighting needs of pedestrians late at night. If the infrared sensor detects that a pedestrian is approaching, it will start the central lamp bead powered by a solar battery to provide temporary road lighting for pedestrians, and automatically shut down after the pedestrian leaves, achieving intelligent energy saving.

[0113] Based on the same inventive concept, an embodiment of this specification also provides an electronic device.

[0114] The following describes an electronic device embodiment of the present invention, which can be regarded as a specific physical implementation of the method and device embodiments of the present invention. The details described in the electronic device embodiment of the present invention should be regarded as a supplement to the above method or device embodiments; details not disclosed in the electronic device embodiment of the present invention can be implemented with reference to the above method or device embodiments.

[0115] Figure 3This is a schematic diagram of the structure of an electronic device provided in an embodiment of this specification. Figure 3 The electronic device 300 according to the embodiment of the present invention is described. Figure 3 The electronic device 300 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0116] like Figure 3 As shown, the electronic device 300 is in the form of a general computing device. The components of the electronic device 300 may include, but are not limited to: at least one processing unit 310, at least one storage unit 320, a bus 330 connecting different system components (including the storage unit 320 and the processing unit 310), a display unit 340, etc.

[0117] The storage unit stores program codes, which can be executed by the processing unit 310, so that the processing unit 310 performs the steps according to various exemplary embodiments of the present invention described in the above processing method section of this specification. For example, the processing unit 310 can perform the following steps: Figure 1 Steps shown.

[0118] The storage unit 320 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 3201 and / or a cache memory unit 3202 , and may further include a read-only memory unit (ROM) 3203 .

[0119] The storage unit 320 may also include a program / utility 3204 having a set (at least one) of program modules 3205, such program modules 3205 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include the implementation of a network environment.

[0120] Bus 330 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0121] The electronic device 300 may also communicate with one or more external devices 400 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), one or more devices that enable viewers to interact with the electronic device 300, and / or any device that enables the electronic device 300 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed through an input / output (I / O) interface 350. Furthermore, the electronic device 300 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) through a network adapter 360. The network adapter 360 may communicate with other modules of the electronic device 300 through the bus 330. It should be understood that although Figure 3 Not shown, other hardware and / or software modules may be used in conjunction with the electronic device 300, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0122] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the exemplary embodiments described in the present invention can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation method of the present invention can be embodied in the form of a software product, which can be stored in a computer-readable storage medium (which can be a CD-ROM, USB flash drive, mobile hard disk, etc.) or on a network, including a number of instructions to enable a computing device (which can be a personal computer, server, or network device, etc.) to execute the above method according to the present invention. When the computer program is executed by a data processing device, the computer-readable medium can implement the above method of the present invention, that is: Figure 1 The method shown.

[0123] Figure 4 A schematic diagram of a computer-readable medium provided for an embodiment of this specification.

[0124] accomplish Figure 1The computer program of the method shown can be stored on one or more computer readable media. The computer readable medium can be a readable signal medium or a readable storage medium. The readable storage medium can be, for example, but not limited to, a system, device or device of electricity, magnetism, light, electromagnetic, infrared, or semiconductor, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0125] The computer readable storage medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by an instruction execution system, an apparatus, or a device or used in combination with it. The program code contained on the readable storage medium may be transmitted with any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0126] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the viewer computing device, partially on the viewer device, as a stand-alone software package, partially on the viewer computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving a remote computing device, the remote computing device may be connected to the viewer computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0127] In summary, the present invention can be implemented in hardware, or in a software module running on one or more processors, or in a combination thereof. It should be understood by those skilled in the art that general data processing devices such as microprocessors or digital signal processors (DSPs) can be used in practice to implement some or all of the functions of some or all of the components in the embodiments of the present invention. The present invention can also be implemented as a device or apparatus program (e.g., a computer program and a computer program product) for executing part or all of the methods described herein. Such a program implementing the present invention can be stored on a computer-readable medium, or can have the form of one or more signals. Such a signal can be downloaded from an Internet website, or provided on a carrier signal, or provided in any other form.

[0128] The specific embodiments described above further describe the purpose, technical solutions and beneficial effects of the present invention in detail. It should be understood that the present invention is not inherently related to any specific computer, virtual device or electronic device, and various general devices can also implement the present invention. The above description is only a specific embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

[0129] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0130] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A lighting equipment intelligent control method, characterized in that: include: Obtain single environmental factor data of lighting area; estimating the flow of people in the lighting area in a future time period based on the lighting area environmental data; Determine a corresponding human flow classification based on the human flow in the future time period, and generate a lighting control strategy for the lighting equipment based on the human flow classification corresponding to the human flow in the future time period; The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

2. The intelligent control method for lighting equipment according to claim 1, characterized in that: Also includes: Acquire multiple environmental factor data of the lighting area; wherein the multiple environmental factor data includes time factor data and weather factor data; Evaluate based on the time factor data and the weather factor data respectively to obtain a first flow of people in a future time period and a second flow of people in a future time period; Determine whether the first flow of people in the future time period is the same as the second flow of people in the future time period; When the first human flow in the future time period is the same as the second human flow in the future time period, a corresponding human flow classification is determined based on the first human flow in the future time period / the second human flow in the future time period, and a lighting control strategy for the lighting equipment is generated based on the human flow classification corresponding to the first human flow in the future time period / the second human flow in the future time period; The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

3. The intelligent control method for lighting equipment according to claim 2, characterized in that: Also includes: When the first human flow in the future time period is different from the second human flow in the future time period, the average human flow in the future time period is determined based on the first human flow in the future time period and the second human flow in the future time period, the corresponding human flow grade is determined based on the average human flow in the future time period, and the lighting control strategy of the lighting equipment is generated based on the human flow grade corresponding to the average human flow in the future time period.

4. The intelligent control method for lighting equipment according to claim 3, characterized in that: Also includes: The multiple environmental factor data also includes seasonal factor data; Evaluate based on the time factor data, the weather factor data, and the season factor data respectively to obtain a first flow of people in a future time period, a second flow of people in a future time period, and a third flow of people in a future time period; Determine whether the first person flow in the future time period, the second person flow in the future time period, and the third person flow in the future time period are the same; When the first flow of people in the future time period, the second flow of people in the future time period, and the third flow of people in the future time period are different, taking the maximum value of the first flow of people in the future time period, the second flow of people in the future time period, and the third flow of people in the future time period as the predicted flow of people, determining the corresponding flow of people classification based on the predicted flow of people, and generating the lighting control strategy of the lighting equipment based on the flow of people classification corresponding to the predicted flow of people; The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

5. The intelligent control method for lighting equipment according to claim 4, characterized in that: Also includes: Obtain the current actual flow of people in the lighting area in real time; Determine whether the deviation between the current actual flow of people and the estimated flow of people in the current time period meets the preset deviation value; When the deviation between the current actual flow of people and the estimated flow of people in the current time period does not meet the preset deviation value, determining whether the current actual flow of people is greater than the estimated flow of people in the current time period; When the current actual human flow is greater than the estimated human flow in the current time period, determining a human flow classification corresponding to the current actual human flow based on the current actual human flow, and generating a lighting control strategy for the lighting equipment based on the human flow classification corresponding to the current actual human flow; The lighting components of the lighting equipment are controlled to turn on and off according to the lighting control strategy.

6. The intelligent control method for lighting equipment according to claim 5, characterized in that: Also includes: When the current actual flow of people is less than the estimated flow of people in the current time period, the lighting components of the lighting device continue to be controlled to turn on and off according to the lighting control strategy.

7. An intelligent control lighting device, characterized in that: include: A transverse component and a longitudinal component, wherein the transverse component is connected to one end of the longitudinal component, and the other end of the longitudinal component is connected to the ground; A solar panel is provided on one side of the transverse component away from the longitudinal component, a lamp bead lighting area is provided on one side of the transverse component close to the longitudinal component, an infrared sensing sensor is provided on at least one end of the transverse component, and a light-storing light strip is provided on at least one side of the longitudinal component.

8. An electronic device, wherein: The electronic device includes: processor; and, A memory storing computer executable instructions which, when executed, cause the processor to perform the method according to any one of claims 1-6.

9. A computer-readable storage medium, wherein: The computer-readable storage medium stores one or more programs, and when the one or more programs are executed by a processor, the method of any one of claims 1 to 6 is implemented.

Images