Method and device for intelligently adjusting projection brightness, computer equipment and storage medium

Abstract

The invention relates to the technical field of projectors, and discloses a method and device for intelligently adjusting projection brightness, computer equipment and a storage medium. The method comprises the following steps: acquiring current ambient light intensity data and distance data between a projector and a projection curtain to form a data set; preprocessing the data set to obtain preprocessed data; calculating to obtain a brightness adjustment factor according to the preprocessed data; calculating a new projection brightness value according to the brightness adjustment factor; and applying the new projection brightness value to the projector to complete projection brightness adjustment. By implementing the method provided by the invention, automatic adjustment of the projection brightness according to the actual brightness of the projection environment and the projection distance is realized, manual intervention of a user is not needed, and the problem of improper brightness caused by improper operation or inaccurate judgment of the user is avoided.

Description

Technical Field

[0001] The present invention relates to projector technology, and more particularly to a method, device, computer device, and storage medium for intelligently adjusting projection brightness. Background Art

[0002] In the current projector product market, the brightness adjustment function, as one of the key factors affecting the quality of the projection image and the user's visual experience, is mainly realized by the user's manual operation. Traditional projectors usually provide a limited number of fixed brightness levels, and users need to select the most suitable brightness setting from these levels according to the actual projection environment and personal needs.

[0003] However, the actual projection environment is extremely complex and variable. Indoor lighting conditions, usage scenarios, and the specific needs of users may all pose different requirements for projection brightness. For example, in a relatively bright meeting room or classroom, in order to ensure the clarity and visibility of the projection image, users usually need to select a higher brightness level; while in a relatively dark home theater or bedroom environment, too high a brightness may not only cause eye fatigue for users, but also lead to color distortion of the image, affecting the overall viewing experience.

[0004] Currently, the method of manually adjusting brightness has many inconveniences. On the one hand, users need to frequently manually adjust the brightness according to environmental changes, and the operation process is cumbersome and error-prone; on the other hand, since users often have difficulty accurately judging the optimal brightness value in the current environment, it is easy to have the situation of over-adjusting or under-adjusting the brightness. This inaccurate brightness adjustment not only fails to fully meet the user's expectations for image quality, but may also have a negative impact on the lifespan and performance of the projector. Summary of the Invention

[0005] The purpose of the present invention is to overcome the deficiencies of the prior art and provide a method, device, equipment, and medium for intelligently adjusting projection brightness.

[0006] To solve the above technical problems, the present invention adopts the following technical solutions:

[0007] In a first aspect, a method for intelligently adjusting projection brightness is provided, including:

[0008] Obtaining current ambient light intensity data and the distance data between the projector and the projection screen to form a data set;

[0009] Preprocessing the data set to obtain preprocessed data;

[0010] Calculating a brightness adjustment factor according to the preprocessed data;

[0011] Calculating a new projection brightness value according to the brightness adjustment factor;

[0012] Apply the new projection brightness value to the projector to complete the adjustment of the projection brightness.

[0013] In a second aspect, a device for intelligently adjusting the projection brightness is provided, including:

[0014] An acquisition unit, configured to acquire the current ambient light intensity data and the distance data between the projector and the projection screen to form a data set;

[0015] A preprocessing unit, configured to preprocess the data set to obtain preprocessed data;

[0016] A first calculation unit, configured to calculate a brightness adjustment factor according to the preprocessed data;

[0017] A second calculation unit, configured to calculate a new projection brightness value according to the brightness adjustment factor;

[0018] An application unit, configured to apply the new projection brightness value to the projector to complete the adjustment of the projection brightness.

[0019] In a third aspect, a computer device is provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for intelligently adjusting the projection brightness as described above are implemented.

[0020] In a fourth aspect, a computer-readable storage medium is provided. The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for intelligently adjusting the projection brightness as described above are implemented.

[0021] In the above method for intelligently adjusting the projection brightness, by acquiring the current ambient light intensity data and the distance data between the projector and the projection screen, a comprehensive data set is formed, and the data set is preprocessed to obtain more accurate and reliable preprocessed data. Based on these preprocessed data, a brightness adjustment factor is calculated, and then a new projection brightness value is calculated according to this factor. This process realizes the automatic adjustment of the projection brightness according to the actual brightness of the projection environment and the projection distance, without manual intervention by the user, avoiding the problem of inappropriate brightness caused by improper operation or inaccurate judgment of the user; in addition, by accurately calculating the brightness adjustment factor and the new projection brightness value, it can ensure that the projection screen maintains the best brightness state under different ambient light and projection distances, effectively improving the quality and clarity of the projection screen; in addition, the automated brightness adjustment process simplifies the user operation, enabling the user to avoid frequently manually adjusting the brightness, thus bringing a more comfortable and natural visual experience to the user. Whether in a brightly lit conference room or a dimly lit home theater, the user can enjoy the most suitable projection brightness.

[0022] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments. Description of the Drawings

[0023] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings.

[0024] Figure 1 It is a flowchart of the method for intelligently adjusting the projection brightness provided by an embodiment of the present invention;

[0025] Figure 2 It is a schematic block diagram of the device for intelligently adjusting the projection brightness provided by an embodiment of the present invention;

[0026] Figure 3 It is a schematic structural diagram of a computer device in an embodiment of the present invention. Detailed Embodiments

[0027] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the protection scope of the present invention.

[0028] It should be understood that when used in this specification and the appended claims, the terms "comprises" and "comprising" indicate the presence of the described features, wholes, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, wholes, steps, operations, elements, components, and / or their combinations.

[0029] It should also be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in this specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an", and "the" are intended to include the plural forms.

[0030] It should be further understood that the term " / and / " used in this specification of the present invention and the appended claims refers to any combination and all possible combinations of one or more of the related listed items, and includes these combinations.

[0031] The prerequisite for applying the method for intelligently adjusting the projection brightness is that it needs to be applied to a projector equipped with a light sensor, a distance sensor, and a brightness adjustment controller.

[0032] Among them, the light sensor includes:

[0033] light_sensor_id: The unique identifier of the light sensor.

[0034] ambient_light_intensity: The ambient light intensity value, with the unit of lux.

[0035] light_timestamp: The timestamp of the light data acquisition.

[0036] The distance sensor includes:

[0037] distance_sensor_id: The unique identifier of the distance sensor.

[0038] projection_distance: The distance between the projector and the projection screen or the viewer, with the unit of meter (m).

[0039] distance_timestamp: The timestamp of the distance data acquisition.

[0040] The brightness adjustment controller includes:

[0041] record_id: The unique identifier of the record.

[0042] projector_id: The associated projector identifier.

[0043] brightness_value: The adjusted brightness value.

[0044] adjustment_time: The timestamp of the brightness adjustment.

[0045] light_intensity: The ambient light intensity value during adjustment.

[0046] projection_distance: The projection distance during adjustment.

[0047] Please refer to Figure 1 In the specific embodiments shown, the present invention discloses a method for intelligently adjusting the projection brightness, including the following steps:

[0048] S110, obtaining the current ambient light intensity data and the distance data between the projector and the projection screen to form a data set;

[0049] In one embodiment, before step S110, it further includes: when the projector system starts up, initializing the light sensor, distance sensor, and brightness adjustment controller, including setting parameters such as the acquisition frequency, for example, collecting data every 1 second, initializing relevant weight parameters such as the light intensity weight being 0.6 and the distance weight being 0.4, and establishing a connection with the projector, etc.

[0050] Specifically, for the initialization of the light sensor: Ensure that the light sensor is correctly connected to the main control board of the projector, usually communicating through I2C, SPI, or analog signal interfaces. Configure the acquisition frequency of the light sensor, for example: set to collect light intensity data every 1 second, and set a weight for the light intensity data, such as 0.6, indicating that in the subsequent environmental adaptation algorithm, the light intensity will account for 60% of the decision-making proportion. That is to say, by monitoring the change of ambient light in real time, it provides a basis for automatic brightness adjustment, avoiding the picture being too bright or too dark and enhancing the viewing experience.

[0051] For the initialization of the distance sensor: Ensure that the distance sensor (such as an infrared sensor) is correctly installed on the projector and connected to the main control board. Also set to collect distance data every 1 second to monitor the distance between the projector and the projection surface, and set a weight for the distance data, such as 0.4, indicating that when adjusting the projection size or focal length, the distance factor will account for 40% of the decision-making proportion. That is to say, automatically adjust the size and clarity of the projection screen to adapt to different projection distances, ensuring that the screen ratio is correct and clear.

[0052] For the initialization of the brightness adjustment controller: Ensure that the communication interface (such as a PWM signal) between the brightness adjustment controller and the main control board is working properly. Set the initial brightness value of the brightness adjustment controller, which may be based on a preset default setting or the record from the last use. Prepare the brightness adjustment algorithm according to the data of the light sensor and distance sensor, and calculate in combination with the set weights. That is to say, subsequently, automatically adjust the projection brightness according to the ambient light and projection distance to achieve a comfortable viewing effect.

[0053] Establishing a connection with the projector: Communication protocol configuration: Ensure that the communication protocol (such as HDMI-CEC, RS-232, or network protocol) between the projector and the main control board is correctly configured, identify and connect to the projector through the communication protocol, and obtain parameters such as its model, resolution, and supported color space. That is to say, ensure the compatibility and correct communication between the projector and the control system, providing basic information for subsequent projection settings and optimizations.

[0054] Specifically, the system triggers the sensor to start data acquisition work at set time intervals (for example, every 1 second). It obtains ambient light intensity data from the light sensor (including the light sensor identifier, light intensity value, and light acquisition timestamp), and stores it in the data structure of the corresponding light sensor. It obtains the distance data between the projector and the projection screen or the viewer from the distance sensor (including the distance sensor identifier, distance value, and distance acquisition timestamp), and stores it in the data structure of the corresponding distance sensor.

[0055] More specifically, set the time interval for data acquisition in the system configuration file, for example, acquire data every 1 second. When the system starts, it reads the time interval setting in the configuration file and initializes the timer or scheduler to trigger data acquisition according to this time interval. That is to say, by ensuring a consistent data acquisition frequency, a stable time reference is provided for subsequent data analysis and processing.

[0056] In addition, when the timer or scheduler reaches the set time interval, it sends data acquisition instructions to the light sensor and the distance sensor. After receiving the instructions, the sensors start to acquire the current ambient light intensity or distance data. That is to say, it realizes timed and automatic data acquisition, reduces manual intervention, and improves the efficiency and accuracy of data acquisition.

[0057] In addition, after the light sensor acquires the light intensity data, it packs it together with the sensor identifier and the acquisition timestamp into a data structure. The system reads the data of the light sensor through the communication interface (such as I2C, SPI, etc.) and stores it in the predefined data structure of the light sensor. That is to say, by obtaining accurate ambient light intensity data, it provides a basis for adjusting the brightness of the projector to ensure that the projection image remains clearly visible in different light environments.

[0058] In addition, after the distance sensor acquires the distance data, it also packs it together with the sensor identifier and the acquisition timestamp into a data structure. The system reads the data of the distance sensor through the communication interface and stores it in the predefined data structure of the distance sensor. That is to say, by obtaining accurate distance data between the projector and the projection screen or the viewer, it provides a basis for adjusting the focal length and the size of the projection image, etc., to ensure that the projection image has the correct proportion and is clear.

[0059] In addition, the system establishes independent data storage structures for the light sensor and the distance sensor respectively, such as arrays, linked lists, or database tables. Each time the acquired data is appended to the corresponding data storage structure for subsequent data analysis and processing. That is to say, by realizing the orderly storage and management of data, it is convenient for subsequent data query, analysis, and mining, providing data support for the intelligent control and adjustment of the projector.

[0060] S120, preprocess the dataset to obtain preprocessed data;

[0061] Specifically, the preprocessing of the dataset includes:

[0062] Data cleaning:

[0063] Missing value handling: Check whether there are missing values in the dataset (such as data not collected due to sensor failures or communication problems). For missing values, interpolation methods (such as linear interpolation, filling with neighboring values) or prediction filling based on historical data trends can be used.

[0064] Outlier detection and handling: Use statistical methods (such as the 3σ principle) or machine learning algorithms (such as Isolation Forest) to detect outliers in the dataset. For the detected outliers, options include deletion, replacement with the mean / median, or other appropriate handling.

[0065] Data standardization / normalization:

[0066] Since the light intensity values and distance values may have different dimensions and distribution ranges, to eliminate this difference, the data can be standardized (such as Z-score standardization) or normalized (such as scaling the data to the range of 0 - 1). This helps with subsequent data analysis and model training, making the algorithm more stable and efficient.

[0067] Timestamp alignment and synchronization:

[0068] Ensure that the timestamps of the light intensity data and distance data are aligned, that is, both are collected at the same time point. If there is a timestamp deviation, time synchronization processing is required. This is crucial for analyzing the correlation between light intensity and distance changes.

[0069] Data aggregation and dimensionality reduction:

[0070] If the dataset is too large or contains redundant information, the data can be aggregated (such as calculating the average, maximum, minimum, etc. over a certain period of time) or dimensionality reduction processing (such as Principal Component Analysis - PCA) can be performed. This helps reduce the complexity of data processing and improve the running efficiency of the algorithm.

[0071] Feature extraction and construction:

[0072] Extract meaningful features from the original data, such as the change trend of light intensity, the change rate of distance, etc. According to business requirements, construct new feature variables to better describe the patterns and rules behind the data.

[0073] That is to say, by implementing the above preprocessing of the dataset to obtain preprocessed data, the following technical effects are brought about by this technical feature:

[0074] Improve data quality: By cleaning the data and handling outliers, noise and errors in the data are removed, improving the accuracy and reliability of the data.

[0075] Enhance algorithm performance: Data standardization / normalization makes the algorithm more stable and efficient, avoiding algorithm biases caused by dimensional differences. Timestamp alignment and synchronization ensure data consistency and relevance, facilitating accurate analysis of the interactions between data.

[0076] Reduce processing complexity: Data aggregation and dimensionality reduction reduce the dimensionality and quantity of data, lowering the complexity and computational cost of data processing.

[0077] Improve model performance: Feature extraction and construction enable the model to capture more information and patterns in the data, enhancing the model's prediction accuracy and generalization ability.

[0078] In one embodiment, preprocessing the dataset to obtain preprocessed data includes:

[0079] Check the legality of the dataset;

[0080] If the dataset is all legal and valid, directly preprocess the dataset to obtain preprocessed data;

[0081] If the dataset is not all legal and valid, discard or correct the abnormal data in the dataset, then combine the legal and valid data to form a complete dataset, and then preprocess the complete dataset to obtain preprocessed data.

[0082] Specifically, after the sensor data acquisition is completed, the system transfers this data to the brightness adjustment controller. First, data preprocessing is performed, including checking the legal validity of the data in the dataset:

[0083] Light intensity value check: For each collected light intensity value I, determine whether I < 0 Lux or I > 100000 Lux holds. If it holds, then this light intensity value is abnormal data; if it does not hold, then it is legal and valid data.

[0084] Distance value check: For each collected distance value d, determine whether d < 0.5 m or d > 10 m holds. If it holds, then this distance value is abnormal data; if it does not hold, then it is legal and valid data.

[0085] If the data in the dataset is all legal and valid after inspection, directly preprocess the dataset to obtain preprocessed data.

[0086] If there is abnormal data in the dataset, operate according to the set processing method:

[0087] Discard abnormal data: When abnormal data is detected in the light intensity value or distance value, directly delete the data point from the dataset. For example, if there is a light intensity value I = -100 lux, since it is less than 0 and belongs to abnormal data, then in the array or list storing the data, delete the element corresponding to this data. After discarding the abnormal data, the remaining legal and valid data is used for subsequent regular data analysis and processing tasks, such as preprocessing the dataset to obtain preprocessed data or establishing a mathematical model for the relationship between light intensity and distance.

[0088] Correct abnormal data: Determine a window size w (for example, w = 5). For the detected abnormal light intensity value Iabnormal, find its position i in the data sequence. Take w / 2 data points before and after position i (if they exist), and calculate the mean I of these w data points (including Iabnormal itself. If it is valid data, it participates in the calculation; if it is abnormal data, it is replaced by surrounding valid data). Then replace the original abnormal data Iabnormal with the calculated mean I. The corrected abnormal data and the original legal and valid data together form a complete dataset, which is used in application scenarios that require a complete data sequence, such as preprocessing the dataset to obtain preprocessed data or continuously updating the system state estimation in a real-time monitoring system to adjust the projector parameters.

[0089] That is to say, through the legality check, effectively identify and process abnormal data to improve the accuracy and reliability of the dataset. In addition, two methods for processing abnormal data, namely discarding and correcting, are provided to meet the requirements of different application scenarios. Discarding abnormal data is suitable for scenarios where extremely high data accuracy is required and data loss can be tolerated. Correcting abnormal data is suitable for scenarios that require a complete data sequence and have a certain tolerance for abnormal data. In addition, the preprocessed data is cleaner and more accurate, which helps to improve the accuracy and efficiency of subsequent data analysis and processing. For example, when establishing a mathematical model for the relationship between light intensity and distance, more accurate data will result in a more accurate and reliable model.

[0090] S130, Calculate the brightness adjustment factor based on the preprocessed data;

[0091] Specifically, according to specific application requirements, define the calculation rules for the brightness adjustment factor. This rule may be based on a certain relationship between light intensity and distance, such as a linear relationship, a logarithmic relationship, or a more complex non-linear relationship. The rule may also include some thresholds or limiting conditions to ensure that the brightness adjustment factor varies within a reasonable range. Using the preprocessed data, calculate the brightness adjustment factor corresponding to each data point one by one according to the defined calculation rules. For example, if the brightness adjustment factor is inversely proportional to the light intensity and directly proportional to the square of the distance, then a formula can be defined as: Brightness adjustment factor = k * (1 / light intensity) * distance^ 2 , where k is a constant coefficient. The calculated brightness adjustment factors may need to be verified to ensure that they meet the expected effects. If it is found that the brightness adjustment factors do not meet the expectations in some cases, it may be necessary to adjust the calculation rules or the coefficient k and recalculate.

[0092] That is to say, by implementing the above technical feature of calculating the brightness adjustment factor based on the preprocessed data, the following technical effects are brought:

[0093] Improve the accuracy of brightness adjustment: By calculating the brightness adjustment factor based on the preprocessed data, the brightness can be adjusted more accurately according to the ambient light intensity and distance, thus improving the accuracy of brightness adjustment.

[0094] Enhance the adaptability of the system: The calculation rules of the brightness adjustment factor can be defined and adjusted according to actual needs, enabling the system to adapt to different environments and application scenarios.

[0095] Enhance the user experience: Accurate brightness adjustment can ensure the clarity and visibility of images or display content, thus enhancing the user's viewing experience.

[0096] Optimize energy utilization: By reasonably adjusting the brightness, unnecessary energy waste can be avoided, thus optimizing energy utilization and reducing operating costs.

[0097] Support intelligent control: The calculation of the brightness adjustment factor can be integrated into an intelligent control system to achieve automatic and real-time brightness adjustment and improve the intelligent level of the system.

[0098] In one embodiment, the calculating the brightness adjustment factor based on the preprocessed data includes:

[0099] Set the influence weight of light intensity on brightness and the influence weight of distance on brightness;

[0100] Perform normalization processing on the preprocessed data to obtain a normalized value;

[0101] Calculate the brightness adjustment factor based on the influence weight of light intensity on brightness, the influence weight of distance on brightness, and the normalization value.

[0102] Specifically, read two parameters from the preprocessed data: light_intensity (ambient light intensity value) and projection_distance (distance value between the projector and the projection screen or the viewer). Then define the weights:

[0103] Set the influence weight of light intensity on brightness to 0.6, denoted as light_weight.

[0104] Set the influence weight of distance on brightness to 0.4, denoted as distance_weight.

[0105] Normalize the light intensity value:

[0106] Assume that the appropriate viewing light intensity range is 300 - 700 lux. First, calculate the normalized value of light intensity, normalized_light_intensity, using the formula:

[0107] normalized_light_intensity = (light_intensity - 300) / (700 - 300). The function of this formula is to map the actual light intensity value to the range of 0 - 1, where 300 lux corresponds to 0 and 700 lux corresponds to 1. To ensure that the normalized light intensity value is within the legal range of 0 - 1, use max(0, min(1, normalized_light_intensity)) for limitation. That is, if the calculated normalized value is less than 0, set it to 0; if it is greater than 1, set it to 1.

[0108] Normalize the distance value:

[0109] Assume that the appropriate viewing distance range is 1 - 5 meters. Calculate the normalized value of distance, normalized_distance_value, using the formula:

[0110] normalized_distance_value = (projection_distance - 1) / (5 - 1). This formula maps the actual projection distance to the range of 0 - 1, where 1 meter corresponds to 0 and 5 meters corresponds to 1. Similarly, to ensure that the normalized distance value is within the legal range of 0 - 1, use max(0, min(1, normalized_distance_value)) for limitation.

[0111] Calculate the brightness adjustment factor:

[0112] Calculate the brightness adjustment factor adjustment_factor based on the normalized values of the light intensity value and the distance value and the set weights. The calculation formula is as follows:

[0113] adjustment_factor = light_weight * (1 - normalized_light_intensity) + distance_weight * (1 - normalized_distance_value). This formula comprehensively considers the effects of light intensity and distance on brightness. Among them, (1 - normalized_light_intensity) represents the contribution of the degree of deviation of light intensity from the appropriate range to brightness adjustment, and (1 - normalized_distance_value) represents the contribution of the degree of deviation of distance from the appropriate range to brightness adjustment.

[0114] That is to say, by setting the influence weights of light intensity and distance and calculating the brightness adjustment factor based on the normalized data, the brightness can be adjusted more accurately according to the ambient light and viewing distance. In addition, the normalization process ensures that data in different ranges have a consistent benchmark during calculation, improving the accuracy and reliability of the calculation. In addition, the weight setting and normalization process enable the system to flexibly adapt to different viewing environments and requirements. By adjusting the weights, the influence degrees of light intensity and distance on brightness adjustment can be easily changed to meet different application scenarios and requirements. In addition, accurate brightness adjustment can ensure the clarity and visibility of images or display contents. Especially under different light intensities and viewing distances, it can provide the best viewing experience. Users do not need to manually adjust the brightness, and the system can automatically adapt according to the environment, improving the convenience and comfort of use.

[0115] S140, calculate the new projection brightness value according to the brightness adjustment factor;

[0116] Specifically, set a reference brightness value (base_brightness), which is the brightness setting of the projector under standard viewing conditions (such as appropriate light intensity and viewing distance). Use the brightness adjustment factor to adjust the reference brightness value to obtain the new projection brightness value (new_brightness). The calculation formula can be expressed as: new_brightness = base_brightness * adjustment_factor. Here, adjustment_factor is used as a multiplier to adjust the reference brightness according to the changes in environmental conditions. If adjustment_factor is greater than 1, the brightness will increase; if it is less than 1, the brightness will decrease.

[0117] That is to say, by implementing the above-mentioned method of calculating a new projection brightness value according to the brightness adjustment factor, the following technical effects are brought:

[0118] Adaptive brightness adjustment: By calculating a new projection brightness value according to the brightness adjustment factor, the projector can automatically adapt to different viewing environments and conditions, such as changing light intensity and viewing distance. This adaptive adjustment ensures that the image or display content can maintain the best brightness and clarity in various environments.

[0119] Improve the viewing experience: Accurate brightness adjustment can reduce eye fatigue and improve the viewing comfort. Whether in a bright or dim environment, or at different viewing distances, users can enjoy a consistent and high-quality visual experience.

[0120] In one embodiment, calculating a new projection brightness value according to the brightness adjustment factor includes:

[0121] Obtain the minimum brightness value and the maximum brightness value of the projector;

[0122] Calculate a new projection brightness value according to the minimum brightness value, the maximum brightness value and the brightness adjustment factor.

[0123] Specifically, obtain current_brightness (the current brightness value of the projector) from the light sensor, and obtain projector_params (a data structure containing projector parameters, where there are at least two key-value pairs, min_brightness and max_brightness, representing the minimum brightness value and the maximum brightness value supported by the projector respectively) from the projector.

[0124] Calculate the new projected brightness value new_brightness according to the brightness adjustment factor. The calculation formula is: new_brightness = current_brightness + (adjustment_factor * (max_brightness - min_brightness)). The function of this formula is to increase or decrease a certain brightness value based on the brightness adjustment factor on the basis of the current brightness value, where (max_brightness - min_brightness) represents the adjustable range of the projector brightness. To ensure that the new projected brightness value is within the legal range supported by the projector (i.e., between min_brightness and max_brightness), use max(min_brightness, min(max_brightness, new_brightness)) for limitation. That is, if the calculated new projected brightness value is less than the minimum brightness value, set it to the minimum brightness value; if it is greater than the maximum brightness value, set it to the maximum brightness value.

[0125] That is to say, by combining the current brightness value, the adjustable range of the projector brightness, and the brightness adjustment factor, the new projected brightness value can be accurately calculated and controlled. This precise control ensures that the brightness adjustment not only meets the environmental requirements but also does not exceed the physical limitations of the projector. In addition, the brightness adjustment factor is dynamically calculated based on factors such as the ambient light intensity and the viewing distance. Therefore, the new projected brightness value can adapt to the changes in the environment, which enables the projector to provide the best brightness performance under different viewing conditions and improves the viewing experience.

[0126] S150, Apply the new projected brightness value to the projector to complete the projection brightness adjustment.

[0127] Specifically, the brightness adjustment controller transmits the calculated new projected brightness value to the projection brightness control system. The projection brightness control system compares the new projected brightness value with the current brightness value in the projection device parameter data structure. If the brightness value changes, the new projected brightness value is sent to the projector through the corresponding interface or driver to adjust the actual brightness of the projector.

[0128] That is to say, by applying the new projected brightness value to the projector, the automatic adjustment of the projection brightness is realized without manual intervention by the user. This improves the intelligent level of the projection system and enables the projection brightness to be automatically adjusted according to the environmental changes. In addition, the automatic brightness adjustment ensures that the projection image can maintain the best brightness performance under different light conditions, improving the viewing comfort and clarity. The user does not need to manually adjust the brightness in different environments and enjoys a more convenient and pleasant viewing experience.

[0129] In one embodiment, relevant information for brightness adjustment (such as the adjusted brightness value, adjustment time, ambient light intensity value, projection distance, etc.) is recorded into a brightness adjustment record data structure for subsequent query and analysis.

[0130] Specifically, first, a data structure is defined to store relevant information for brightness adjustment. This data structure can be a class, a structure, or a database table, containing fields such as: the adjusted brightness value, adjustment time, ambient light intensity value, projection distance, etc. Each time brightness adjustment is performed, the system obtains the necessary information from relevant sensors or devices. For example, the ambient light intensity value is obtained from a light sensor, the adjusted brightness value is obtained from a projector or a control system, the adjustment time is obtained from the system clock, and (if applicable) the projection distance is obtained from a distance sensor or user input. Additionally, the collected brightness adjustment information is filled into a predefined brightness adjustment record data structure. This can be achieved by creating an instance of the data structure and setting its field values, or by inserting the information into a database table. Moreover, the filled brightness adjustment record data structure is stored in a persistent storage medium, such as a hard disk, a database, or cloud storage. This ensures that the recorded information is still available after the system restarts or shuts down. Additionally, query and analysis interfaces are developed to allow users or system administrators to query brightness adjustment records as needed. This can include functions such as filtering and sorting according to conditions such as time range, brightness value range, ambient light intensity, or projection distance. Data analysis tools or APIs are provided to perform statistical analysis on brightness adjustment records, such as calculating the average brightness value, analyzing the brightness adjustment trend, or identifying abnormal adjustment events.

[0131] That is to say, by recording relevant information for brightness adjustment, the system provides a complete history of brightness adjustment, enhancing the traceability of the system. Additionally, the brightness adjustment records provide a valuable data basis for subsequent data analysis and system optimization. By analyzing the adjustment records, patterns and trends of brightness adjustment can be identified, providing guidance for further system optimization. Additionally, users can query the brightness adjustment records to understand the performance of the system in different environments, thereby better understanding and controlling the projection brightness, which helps to improve user satisfaction and trust. Additionally, by accumulating and analyzing brightness adjustment records, the system can gradually learn users' preferences and behavior patterns, providing data support for future intelligent upgrades. For example, the system can automatically adjust the brightness according to users' habits without manual intervention by users.

[0132] In one embodiment, relevant information for brightness adjustment of each user is uploaded to the manufacturer's server. The server is built with a big data model that can learn the usage habits and optimal brightness settings of a large number of users, and then continuously optimize the brightness adjustment algorithm to make the brightness adjustment more intelligent and accurate, adapting to the needs of different users and scenarios, and improving the overall performance and reliability of the projector.

[0133] Specifically, on the projector device side, a data collection module is designed and implemented to be responsible for collecting in real time or periodically the information related to brightness adjustment of each user, such as the adjusted brightness value, adjustment time, ambient light intensity value, projection distance, and user identification (such as user ID), etc. Through a network connection (such as Wi-Fi, wired network, or mobile network), the collected data is encrypted and uploaded to the manufacturer's server to ensure the security and privacy protection during the data transmission process. On the manufacturer's server, a large-scale data storage system is established to store the data from various projector devices. This system can be a distributed database or a data lake to support efficient data storage and query. Additionally, a data cleaning and preprocessing process is designed to deduplicate, verify, and format the uploaded data to ensure the accuracy and consistency of the data. A big data model is built on the server. This model is based on machine learning or deep learning technologies and can process and analyze the usage data of a large number of users. The model is initially trained using historical data so that it can identify the usage habits and optimal brightness setting patterns of users. As new data is continuously uploaded, the model is continuously incrementally trained or retrained to continuously optimize and update the parameters and rules of the model. Based on the output results of the big data model, the brightness adjustment algorithm of the projector is continuously optimized. For example, according to the user's historical preferences and the current ambient light intensity, the brightness is automatically adjusted to the most appropriate value. The optimized algorithm is pushed to each projector device side through software updates or remote configuration to achieve intelligent and precise brightness adjustment.

[0134] That is to say, through the learning and optimization of the big data model, the projector can automatically adjust the brightness according to the user's usage habits and the current environment, realizing intelligent brightness adjustment, which greatly improves the user's usage experience and satisfaction. Additionally, the big data model can analyze the data of a large number of users, find out the optimal brightness setting pattern, and make the brightness adjustment of the projector more precise, which helps to reduce the frequency of users manually adjusting the brightness, saving time and energy. Moreover, since the big data model can learn the usage habits and preferences of different users, the projector can adapt to the needs of different users and scenarios. Whether in the home, office, or public places, it can provide appropriate brightness settings. Additionally, the application of the big data model provides new ideas and directions for the innovation and development of projector products. Through continuous learning and optimization, more intelligent and personalized functions can be developed to meet the growing needs of users.

[0135] The present invention forms a comprehensive data set by obtaining the current ambient light intensity data and the distance data between the projector and the projection screen, and preprocesses this data set to obtain more accurate and reliable preprocessed data. Based on this preprocessed data, a brightness adjustment factor is calculated, and then a new projection brightness value is calculated according to this factor. This process realizes the automatic adjustment of the projection brightness according to the actual brightness of the projection environment and the projection distance, without manual intervention by the user, avoiding the problem of inappropriate brightness caused by improper operation or inaccurate judgment of the user. In addition, by accurately calculating the brightness adjustment factor and the new projection brightness value, it is possible to ensure that the projection screen maintains the best brightness state under different ambient light and projection distances, effectively improving the quality and clarity of the projection screen. In addition, the automated brightness adjustment process simplifies the user operation, enabling the user to avoid frequent manual brightness adjustment, thus bringing a more comfortable and natural visual experience to the user. Whether in a brightly lit conference room or a dimly lit home theater, the user can enjoy the most suitable projection brightness.

[0136] Figure 2 It is a schematic block diagram of a device 300 for intelligently adjusting the projection brightness provided by an embodiment of the present invention. As Figure 2 shown, corresponding to the above method for intelligently adjusting the projection brightness, the present invention also provides a device 300 for intelligently adjusting the projection brightness. The device 300 for intelligently adjusting the projection brightness includes units for executing the above method for intelligently adjusting the projection brightness, and this device can be configured in a server. Specifically, please refer to Figure 2 . The device 300 for intelligently adjusting the projection brightness includes an acquisition unit 301, a preprocessing unit 302, a first calculation unit 303, a second calculation unit 304, and an application unit 305;

[0137] The acquisition unit 301 is used to acquire the current ambient light intensity data and the distance data between the projector and the projection screen to form a data set;

[0138] The preprocessing unit 302 is used to preprocess the data set to obtain preprocessed data;

[0139] The first calculation unit 303 is used to calculate a brightness adjustment factor according to the preprocessed data;

[0140] The second calculation unit 304 is used to calculate a new projection brightness value according to the brightness adjustment factor;

[0141] The application unit 305 is used to apply the new projection brightness value to the projector to complete the projection brightness adjustment.

[0142] In one embodiment, the preprocessing unit 302 includes:

[0143] A checking module for checking the legality of a data set;

[0144] A preprocessing module for directly preprocessing the data set to obtain preprocessed data if the data set is all legal and valid;

[0145] A correction and combination preprocessing module for discarding or correcting abnormal data in the data set if the data set is not all legal and valid, then combining the legal and valid data to form a complete data set, and then preprocessing the complete data set to obtain preprocessed data.

[0146] In one embodiment, the first calculation unit 303 includes:

[0147] A setting module for setting the influence weight of light intensity on brightness and the influence weight of distance on brightness;

[0148] A normalization module for normalizing the preprocessed data to obtain a normalized value;

[0149] A first calculation module for calculating a brightness adjustment factor according to the influence weight of light intensity on brightness, the influence weight of distance on brightness, and the normalized value.

[0150] In one embodiment, the second calculation unit 304 includes:

[0151] An acquisition module for acquiring the minimum brightness value and the maximum brightness value of the projector;

[0152] A second calculation module for calculating a new projection brightness value according to the minimum brightness value, the maximum brightness value, and the brightness adjustment factor.

[0153] It should be noted that those skilled in the art can clearly understand that the specific implementation processes of the above-mentioned device 300 for intelligently adjusting projection brightness and each unit can refer to the corresponding descriptions in the foregoing method embodiments. For the sake of convenience and brevity of description, they will not be elaborated here.

[0154] In one embodiment, a computer device is provided. This computer device can be a server, and its internal structure diagram can be as Figure 3As shown in the figure. The computer device includes a processor, a memory, a network interface, and a database connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile and / or volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external client through a network connection. When the computer program is executed by the processor, it realizes the functions or steps on the server side of a method for intelligently adjusting projection brightness.

[0155] In one embodiment, a computer device is provided, including a memory, a processor, and a computer program stored on the memory and executable on the processor. When the processor executes the computer program, the following steps are implemented:

[0156] Obtain the current ambient light intensity data and the distance data between the projector and the projection screen to form a data set; preprocess the data set to obtain preprocessed data; calculate a brightness adjustment factor based on the preprocessed data; calculate a new projection brightness value based on the brightness adjustment factor; apply the new projection brightness value to the projector to complete the projection brightness adjustment.

[0157] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by the processor, the following steps are implemented:

[0158] Obtain the current ambient light intensity data and the distance data between the projector and the projection screen to form a data set; preprocess the data set to obtain preprocessed data; calculate a brightness adjustment factor based on the preprocessed data; calculate a new projection brightness value based on the brightness adjustment factor; apply the new projection brightness value to the projector to complete the projection brightness adjustment.

[0159] It should be noted that for the functions or steps that the above computer-readable storage medium or computer device can achieve, reference can be made to the relevant descriptions on the server side and the client side in the foregoing method embodiments. To avoid repetition, they will not be described in detail here.

[0160] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include non-volatile and / or volatile memories. Non-volatile memories can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memories can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDR SDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and Rambus dynamic RAM (RDRAM), etc.

[0161] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the above division of each functional unit and module is used as an example. In actual applications, the above functions can be allocated to different functional units and modules according to needs, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0162] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions recorded in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included in the protection scope of the present invention.

Claims

1. A method for intelligently adjusting projection brightness, characterized in that: include: Acquire current ambient light intensity data and distance data between the projector and the projection screen to form a data set; Preprocessing the data set to obtain preprocessed data; According to the preprocessed data, the brightness adjustment factor is calculated; According to the brightness adjustment factor, a new projection brightness value is calculated; Apply the new projection brightness value to the projector to complete the projection brightness adjustment.

2. The method for intelligently adjusting projection brightness according to claim 1, characterized in that: The preprocessing of the data set to obtain preprocessed data includes: Check the legality of the dataset; If the data set is all legal and valid, the data set is directly preprocessed to obtain preprocessed data; If the data set is not completely legal and valid, the abnormal data in the data set is discarded or corrected and combined with the legal and valid data to form a complete data set, and then the complete data set is preprocessed to obtain preprocessed data.

3. The method for intelligently adjusting projection brightness according to claim 1, characterized in that: The step of calculating the brightness adjustment factor according to the preprocessed data includes: Set the weight of the light intensity on the brightness and the weight of the distance on the brightness; Normalizing the preprocessed data to obtain normalized values; The brightness adjustment factor is calculated according to the influence weight of light intensity on brightness, the influence weight of distance on brightness and the normalized value.

4. The method for intelligently adjusting projection brightness according to claim 1, characterized in that: The step of calculating a new projection brightness value according to the brightness adjustment factor includes: Get the minimum and maximum brightness values ​​of the projector; A new projection brightness value is calculated based on the minimum brightness value, the maximum brightness value and the brightness adjustment factor.

5. A device for intelligently adjusting projection brightness, characterized in that: include: An acquisition unit, used to acquire current ambient light intensity data and distance data between the projector and the projection screen to form a data set; A preprocessing unit, used for preprocessing the data set to obtain preprocessed data; A first calculation unit, used for calculating a brightness adjustment factor according to preprocessed data; A second calculation unit, used to calculate a new projection brightness value according to the brightness adjustment factor; The application unit is used to apply the new projection brightness value to the projector to complete the projection brightness adjustment.

6. The device for intelligently adjusting projection brightness according to claim 5, characterized in that: The pre-processing unit comprises: Check module, used to check the legitimacy of the data set; The preprocessing module is used to directly preprocess the data set to obtain preprocessed data if the data set is all legal and valid; The correction and preprocessing module is used to discard or correct the abnormal data in the data set if the data set is not completely legal and valid, and then combine the legal and valid data to form a complete data set, and then preprocess the complete data set to obtain preprocessed data.

7. The device for intelligently adjusting projection brightness according to claim 5, characterized in that: The first computing unit comprises: A setting module, used to set the influence weight of light intensity on brightness and the influence weight of distance on brightness; A normalization module, used for normalizing the preprocessed data to obtain a normalized value; The first calculation module is used to calculate the brightness adjustment factor according to the influence weight of the light intensity on the brightness, the influence weight of the distance on the brightness and the normalized value.

8. The device for intelligently adjusting projection brightness according to claim 5, characterized in that: The second computing unit comprises: An acquisition module is used to obtain the minimum brightness value and the maximum brightness value of the projector; The second calculation module is used to calculate a new projection brightness value according to the minimum brightness value, the maximum brightness value and the brightness adjustment factor.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for intelligently adjusting projection brightness as described in any one of claims 1 to 4 are implemented.

10. A storage medium, wherein the computer-readable storage medium stores a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for intelligently adjusting projection brightness as claimed in any one of claims 1 to 4 are implemented.

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