Energy consumption monitoring and energy-saving control method and system of intelligent cabinet

Abstract

The invention relates to the field of energy consumption monitoring, in particular to an energy consumption monitoring and energy-saving control method and system for an intelligent cabinet. The method comprises the following steps: detecting that a user clicks a central control interaction interface based on an intelligent cabinet, performing illumination adjustment on the interaction interface, and outputting a real-time interaction interface; capturing a user click operation behavior based on the real-time interaction interface; performing interactive interface incremental loading processing on the user click operation behavior to complete real-time interactive energy-saving processing; performing interaction frequency statistics on the click operation behavior of the user to obtain interaction statistical information; judging that the intelligent cabinet enters a deep standby state based on the interaction statistical information; and performing energy consumption optimization and monitoring processing based on the deep standby state. The ineffective energy consumption of the goods storage intelligent cabinet is reduced, and the overall operation energy efficiency is improved.

Description

Technical Field

[0001] This invention relates to the field of energy consumption monitoring, and in particular to a method and system for energy consumption monitoring and energy-saving control of an intelligent cabinet. Background Technology

[0002] Smart lockers for cargo storage typically consist of a main control unit, display and interaction module, communication module, electronic lock control unit, environmental monitoring device, and power management system. In 24 / 7 operation, they require continuous network connectivity, status monitoring, and standby response. This long-term, uninterrupted operation leads to high overall energy consumption, especially during periods of low usage or idle time, where significant amounts of ineffective energy consumption still occur. Load variations under different usage scenarios, inadequate power management, and equipment aging further exacerbate energy waste, increasing operating costs and maintenance pressure. Existing energy management methods for smart lockers for cargo storage often rely on simple timed switches, zoned power supply, or manual inspections, lacking refined perception of equipment operating status and usage behavior. These methods typically only provide a rough estimate of overall energy consumption, failing to accurately analyze the energy consumption characteristics of individual functional modules and hindering the timely detection of abnormal energy consumption or energy efficiency degradation. Furthermore, traditional energy-saving control strategies are mostly statically configured, making dynamic adjustments based on actual usage and environmental changes difficult, resulting in limited energy-saving effects and low levels of intelligence. Summary of the Invention

[0003] To address the aforementioned technical problems, this invention proposes a method and system for energy consumption monitoring and energy-saving control of an intelligent cabinet, thereby resolving at least one of the aforementioned technical problems.

[0004] To achieve the above objectives, the present invention provides a method for energy consumption monitoring and energy-saving control of an intelligent cabinet, comprising the following steps: Based on the smart cabinet's detection of user clicks on the central control interface, the lighting of the interface is adjusted, and the real-time interactive interface is output. The user click behavior is captured based on the real-time interactive interface; the user click behavior is subjected to incremental loading of the interactive interface to complete the real-time interactive energy-saving processing. Analyze the frequency of user click actions to obtain interaction statistics. The smart cabinet is determined to be in deep standby mode based on interactive statistical information; energy consumption optimization and monitoring are then performed based on the deep standby mode.

[0005] This specification provides an energy consumption monitoring and energy-saving control system for an intelligent cabinet, used to execute the energy consumption monitoring and energy-saving control method for the intelligent cabinet as described above, including: The interface adjustment unit is used to adjust the lighting of the interactive interface based on the user's click on the central control interface of the smart cabinet, and output the real-time interactive interface. An incremental loading unit is used to capture user click behavior based on the real-time interactive interface; perform incremental loading of the interactive interface on the user click behavior to complete real-time interactive energy-saving processing. The interaction statistics unit is used to count the frequency of user click actions and obtain interaction statistics information. The state optimization unit is used to determine whether the smart cabinet has entered a deep standby state based on interactive statistical information; and to perform energy consumption optimization and monitoring processing based on the deep standby state.

[0006] The beneficial effects of this invention are as follows: By detecting user clicks on the central control interface, the brightness and backlight of the interface are activated only when the user is actually operating it, avoiding prolonged high-brightness display on the central control screen when there is no operation, thus reducing the basic energy consumption of the display module from the source. The interface brightness is dynamically adjusted according to the ambient light intensity and user operation status, ensuring visual clarity while reducing unnecessary brightness redundancy, achieving adaptive control of display energy consumption. Real-time output of the interactive interface allows the central control system to enter a high-power display mode only during interaction, improving the efficiency of screen resource utilization and extending the lifespan of display devices. Real-time capture of user click operations allows for interface refresh or function loading only for the user's current operating area, avoiding full-screen redrawing and full-function calls, significantly reducing CPU, GPU, and memory resource usage. An incremental loading method for the interactive interface loads only the functional modules currently needed by the user, reducing redundant background processes and lowering instantaneous power consumption peaks. By statistically analyzing the number of user clicks, operation intervals, and continuous interaction duration, accurate interaction frequency characteristics are formed, providing a quantitative basis for the smart cabinet to determine usage activity. By transforming user actions into interactive statistical information, energy management shifts from passive, timed control to dynamic decision-making based on actual usage behavior, improving the intelligence level of energy-saving control. When the interaction frequency is below a preset threshold, the intelligent cabinet can accurately identify non-usage periods and automatically enter deep standby mode, shutting down or reducing the frequency of the display module, interaction module, and some control units, significantly reducing the overall standby energy consumption. In deep standby mode, key energy-consuming units undergo tiered hibernation control, avoiding the hidden energy consumption problems still present in traditional standby modes, achieving a more thorough energy-saving effect. Continuous monitoring of energy consumption during deep standby allows for real-time evaluation of energy-saving effects, and timely wake-up or alarms are triggered when abnormal power consumption is detected, improving the safety and stability of system operation. Attached Figure Description

[0007] Figure 1 This is a flowchart illustrating the steps of an energy consumption monitoring and energy-saving control method for an intelligent cabinet according to the present invention. Figure 2 This is a detailed flowchart illustrating the implementation steps of step S1. Figure 3This is a flowchart illustrating the detailed implementation steps of step S2. Detailed Implementation

[0008] It should be understood that the specific embodiments described herein are for illustrative purposes only and are not intended to limit the scope of the invention.

[0009] This application provides a method and system for energy consumption monitoring and energy-saving control of an intelligent cabinet. The execution entities of the energy consumption monitoring and energy-saving control method and system for the intelligent cabinet include, but are not limited to, mechanical equipment, data processing platforms, cloud server nodes, network upload devices, etc., which can be considered as general computing nodes in this application. The data processing platform includes, but is not limited to, at least one of an audio-visual management system, an information management system, and a cloud data management system.

[0010] Please see Figures 1 to 3 This invention provides a method for energy consumption monitoring and energy-saving control of intelligent cabinets, comprising the following steps: Based on the smart cabinet's detection of user clicks on the central control interface, the lighting of the interface is adjusted, and the real-time interactive interface is output. The user click behavior is captured based on the real-time interactive interface; the user click behavior is subjected to incremental loading of the interactive interface to complete the real-time interactive energy-saving processing. Analyze the frequency of user click actions to obtain interaction statistics. The smart cabinet is determined to be in deep standby mode based on interactive statistical information; energy consumption optimization and monitoring are then performed based on the deep standby mode.

[0011] In the embodiments of the present invention, see Figure 1 The diagram below illustrates the steps of an energy consumption monitoring and energy-saving control method for an intelligent cabinet according to the present invention. In this example, the steps of the energy consumption monitoring and energy-saving control method for the intelligent cabinet include: Based on the smart cabinet's detection of user clicks on the central control interface, the lighting of the interface is adjusted, and the real-time interactive interface is output. In this embodiment, when a user clicks or touches the central control interface, the touch sensing unit identifies the touch location, duration, and area to confirm a valid human-computer interaction need. After confirming the user's operation, the interface brightness and display parameters are dynamically adjusted based on the current ambient light conditions and the initial display state of the interface. The lighting adjustment process uses the range of ambient light intensity changes as a reference. For example, in low-light environments, the display brightness is controlled at a lower level, while in strong light environments, the brightness is moderately increased to ensure readability and avoid excessive energy consumption. During the adjustment process, the display brightness changes gradually in a smooth transition manner to avoid additional power consumption fluctuations caused by instantaneous brightness changes. By coordinating the adjustment of backlight intensity, display contrast, and color display parameters, a real-time interactive interface matching the current usage scenario is output, ensuring that the central control display maintains display energy consumption within a reasonable range while meeting user operation needs.

[0012] The user click behavior is captured based on the real-time interactive interface; the user click behavior is subjected to incremental loading of the interactive interface to complete the real-time interactive energy-saving processing. In this embodiment, after the real-time interactive interface is output, the user's clicks, swipes, or confirmation operations on the interface are continuously captured. User click behavior data is generated by recording the time of touch occurrence, touch area, and operation sequence. Based on the captured operation behavior, the interactive interface adopts an incremental loading process. That is, only the interface areas and functional elements directly related to the current operation are loaded and refreshed, while other interface content not involved in the current operation remains statically displayed. When the user performs a pickup operation, only the input area, confirmation prompt area, and other relevant elements are updated, without re-rendering the background area or other functional modules. During the incremental loading process, different loading priorities are set for interface elements according to the continuity and urgency of the operation behavior, avoiding the increase in display processing power consumption caused by loading a large amount of irrelevant content at once. In this way, the refresh behavior of the interactive interface is highly matched with the user's actual operation, significantly reducing the number of display refreshes and graphics processing load while ensuring smooth operation.

[0013] Analyze the frequency of user click actions to obtain interaction statistics. In this embodiment, after capturing and incrementally loading user click behavior, the distribution of the behavior over time is statistically analyzed to obtain interaction statistics reflecting usage intensity. By setting a fixed statistical period, the number of touchscreen activations, consecutive clicks, operation intervals, and interface dwell time per unit time are summarized and calculated to describe the activity level of user operations at the current stage. Multiple consecutive clicks and frequent interface switching within a short period are considered a high interaction frequency; conversely, prolonged inactivity or only a single wake-up action is considered a low interaction frequency. The interaction statistics comprehensively reflect user operation density and interface usage through multiple indicators. The smart cabinet is determined to be in deep standby mode based on interactive statistical information; energy consumption optimization and monitoring are then performed based on the deep standby mode.

[0014] In this embodiment, after obtaining interaction statistics, the current usage status of the smart locker is analyzed according to a preset interaction frequency judgment rule. When the interaction frequency remains at a low level for several consecutive statistical periods, such as a significant decrease in touchscreen activations, a significant increase in interface dwell time, and no effective operation, the smart locker is determined to have entered a low-frequency usage state. In this state, continuing to maintain a complete display and high-frequency detection would cause unnecessary energy waste, thus triggering a deep standby judgment. To avoid frequent switching of operating states, a continuous periodic confirmation mechanism is introduced during the judgment process. Only when the low-frequency state persists for a set duration is it considered to have entered the deep standby condition. After determining that the smart locker has entered the deep standby state, corresponding energy consumption optimization and monitoring measures are implemented to reduce overall operating energy consumption. In the deep standby state, the central control interface display is turned off or reduced to the lowest brightness, the sampling interval for touch scanning behavior is extended to reduce the power consumption caused by continuous detection, and unnecessary interface refreshes and background processing activities are suspended. During the energy consumption optimization process, the minimum operating capacity of key basic functions is maintained to ensure that normal operation can be restored in a timely manner when a new user operation is detected. Energy consumption data during deep standby is recorded and monitored, and statistical displays of energy consumption, touch detection energy consumption, and other basic energy consumption indicators are generated to analyze energy-saving effects and operational stability. Through continuous energy consumption monitoring and optimization, the smart locker for goods storage maintains low power consumption operation in low-frequency usage scenarios.

[0015] In this embodiment, see Figure 2 The specific steps for detecting user clicks on the central control interface based on the smart cabinet, adjusting the lighting of the interface, and outputting the real-time interactive interface are as follows: Based on the intelligent cabinet, user clicks on the central control interface are detected, and ambient light sensing parameters are collected based on the light sensor. Based on the analysis of ambient light sensor parameters, the incident angle of light, the distribution of light intensity and the color temperature shift are analyzed to obtain the characteristics of ambient light. Calculate the optimal display brightness value and ambient contrast compensation coefficient based on ambient light characteristics; The interactive interface lighting is adjusted based on the optimal display brightness value and the ambient contrast compensation coefficient, and a real-time interactive interface is output; the interactive interface lighting adjustment includes backlight intensity, pixel brightness rate and color saturation.

[0016] In this embodiment, during the operation of the smart locker, the central control interface identifies user actions through a touch detection mechanism to avoid unnecessary display power consumption when no one is operating it. When a user clicks or swipes on the central control interface, the capacitance distribution of the touch layer changes. The touch detection unit identifies this change and confirms the existence of valid human-computer interaction. After confirming that the click duration and touch area meet preset conditions, the ambient light acquisition process is triggered. Subsequently, the light sensor located on the outside of the smart locker or near the central control panel begins to perceive the surrounding environment, collecting the light intensity parameters and light response values ​​corresponding to different spectral channels. To improve the stability of the collected data, the light sensor continuously outputs multiple sets of light data at a fixed sampling frequency within a short period of time, and filters out instantaneous abnormal values ​​caused by factors such as personnel movement and locker reflection. By comparing the values ​​of light response channels in different directions, the main incident direction of light relative to the central control interface is calculated, thereby distinguishing light types such as frontal illumination, side illumination, or ambient diffuse reflection. Statistical processing is performed on the light intensity data within the sampling period to analyze the average level and variation of light intensity, in order to determine whether the current lighting environment is in a relatively stable state. Furthermore, the color characteristics of ambient light are analyzed using multi-channel spectral response parameters. The color temperature shift of ambient light is calculated based on the energy distribution ratio of the red, green, and blue channels, which is used to characterize whether the ambient light is biased towards warm or cool colors.

[0017] By matching the current illumination intensity characteristics with a preset brightness response relationship, the required display brightness level for clear information display under this lighting environment is determined. The brightness value is then corrected based on the light incidence angle characteristics. When light shines directly on the interface at a large angle, the brightness compensation ratio is appropriately increased, while the brightness increase is reduced under diffused light conditions, thus obtaining the optimal display brightness value. An environmental contrast compensation coefficient is calculated based on the illumination intensity distribution and color temperature shift characteristics. By adjusting the contrast relationship between bright and dark areas of the interface, the recognizability of key information such as text and icons under different lighting conditions is improved, avoiding increased display energy consumption due to simply increasing brightness. The backlight drive parameters are adjusted to gradually change the backlight intensity to the target brightness level, avoiding sudden brightness changes that could affect the user's vision. Furthermore, the pixel illumination rate of different areas of the interface is adjusted according to the environmental contrast compensation coefficient. The pixel emission ratio is appropriately reduced in background areas and non-critical information areas, while maintaining a high display intensity for key interactive content such as pickup information and operation buttons, thereby reducing overall light consumption while ensuring readability. Finally, the interface color saturation is adapted and adjusted based on the ambient light color temperature characteristics to reduce unnecessary color light consumption.

[0018] In this embodiment, see Figure 3 The specific steps for capturing user click behavior based on the real-time interactive interface and performing incremental loading of the interactive interface on the user click behavior to complete the real-time interactive energy-saving processing are as follows: Capture user click behavior based on a real-time interactive interface; Perform semantic analysis on the user's click behavior to generate semantic features; Based on the semantic features of the operation, the interactive content and the interactive interface are identified, and related interactive content is generated. Identify and tag related elements based on associated interaction content; Incremental loading of the interactive interface for related elements is performed to achieve real-time interactive energy saving.

[0019] In this embodiment, during the operation of the central control interface of the smart locker, the touch feedback information of the real-time interactive interface is continuously monitored to capture user actions such as clicks, long presses, or continuous touches. The central control interface typically uses a capacitive touch structure. When a user's finger touches the interface, the charge distribution of the touch layer changes. The touch detection module converts this change into corresponding touch coordinates, touch duration, and touch intensity parameters, and records them in chronological order to form operation behavior data. To reduce energy consumption caused by invalid processing, a valid click operation is only recognized when the touch duration exceeds a preset threshold (e.g., more than 30ms) and the touch area is within the effective interaction range, thereby avoiding meaningless responses caused by accidental touches or environmental interference. During the capture process, the time interval of continuous clicks is statistically analyzed. When the interval between adjacent clicks is less than a certain value (e.g., 300ms), it is considered as a continuous operation sequence. After acquiring the user's click operation behavior data, the semantic analysis of the interaction intent implied by the operation behavior is performed to distinguish different types of user operation needs. By comprehensively judging parameters such as click location, click order, click frequency, and operation duration, semantic features reflecting the user's operation purpose are extracted. When a user clicks multiple times in a short period of time on functional areas such as "save" or "retrieve," it can be determined as a clear function access operation; while when a user makes a single click on the edge of the interface or a non-core area, it may be an interface wake-up or accidental operation. During the operation semantic analysis process, the operation behavior is mapped to a preset semantic category, such as function selection, information confirmation, or return browsing, and corresponding semantic label parameters are generated for each category. To reduce processing complexity, operation semantic features are usually expressed in a simplified feature set form, such as by combining operation type identifiers, target area numbers, and operation urgency levels, thereby reducing the computing resources required for subsequent interaction processing.

[0020] The system matches operational semantic features with preset interactive content mapping relationships to identify the core interface modules and information elements required for the current operation. For example, in the semantics of a pickup operation, only the pickup code input area, confirmation button, and prompt information area are associated, without loading advertisements or auxiliary instructions. During the identification process, interactive content is graded according to importance and frequency of use, with high-frequency and key content prioritized as associated interactive content, while other content is either not rendered or kept in a low refresh state. The interactive interface layout structure is analyzed, dividing the interface into several display element units, such as text areas, icon areas, input box areas, and background areas, and determining the associated elements that need to participate in the current interaction based on the associated interactive content. In the confirmation operation phase, only the confirmation button, status prompt text, and necessary input display elements are marked as associated elements, while background decorative elements and unnecessary graphic elements remain inactive. During element identification, each associated element is assigned a corresponding display priority and refresh flag to control its subsequent display update strategy. During incremental loading, only marked associated elements are activated, updated in content, or animated. Unmarked elements retain their current display state or enter a low refresh mode, thus avoiding increased energy consumption from repeated rendering of the entire interface. While the user is entering the pickup code, only the input box content and related prompts are updated; other interface elements are not refreshed. To ensure smooth interaction, incremental loading uses a step-by-step update approach, prioritizing high-priority elements and delaying or merging the loading of low-priority elements to reduce instantaneous power consumption peaks.

[0021] In this embodiment, the incremental loading process of the interactive interface is specifically as follows: Non-critical background elements are identified based on associated elements; low-priority elements are statically cached and reused. Calculate the number of GPU calls and adaptively reduce the frequency. Identify the frame buffer refresh frequency and reduce the frame buffer refresh frequency.

[0022] In this embodiment, by analyzing the interface layout structure and element display attributes, decorative backgrounds, fixed prompts, static icons, and other content that do not directly affect the current operation flow are identified as non-critical background elements and marked as low-priority display objects. For these low-priority elements, a static caching and reuse approach is adopted. That is, the rendering result is stored in the display cache area upon initial loading, and is not repeatedly triggered for drawing or rearrangement during subsequent interactions; it is only reloaded when the interface undergoes structural changes. This avoids repeated rendering of the background area during frequent user clicks or input operations, thereby reducing the continuous call requirements of the graphics processing unit. The number of graphics processing requests triggered by operations such as interface element refresh, animation response, and text update is recorded and accumulated within a preset time window, for example, calculating the GPU call frequency at a period of 500ms or 1s. When the number of calls exceeds a preset threshold (e.g., more than 20 times within a unit period), it is determined that the current display processing has redundancy or room for optimization. Based on this, the graphics processing behavior is adaptively reduced, for example, by merging multiple drawing requests in a short period of time, delaying low-priority graphics updates, or canceling drawing calls for invisible areas, thereby reducing the number of times the GPU actually participates in the computation.

[0023] By identifying the refresh requirements of the current interactive interface during operation, the refresh rate of the frame buffer is dynamically evaluated. When the interface is in a static display state or only local elements change, the overall frame buffer refresh rate is reduced. During user input or while waiting for feedback, the changes in interface content are usually concentrated in local areas. In this case, the refresh rate can be reduced from the usual 60Hz to 30Hz or lower, thereby reducing the repeated output of frame data by the display control unit. While reducing the refresh rate, the display stability of key interactive areas is maintained, avoiding interface flickering or operation delays due to insufficient refresh.

[0024] In this embodiment, the specific steps for performing interaction frequency statistics on user click operations to obtain interaction statistics information are as follows: Define the touch scan sampling period; The user's click behavior is used to identify the interaction type and obtain different types of interaction behavior data; the different types of interaction behavior data include the number of touch screen activations, button response latency, operation completion time and interface dwell time. Based on the touch scanning sampling period, the interaction frequency of different types of interactive behavior data is statistically analyzed to obtain interaction statistics information.

[0025] In this embodiment, the touch scanning sampling period is used to limit the time interval for the touch detection module to poll and sample the touchscreen state. Its setting needs to strike a balance between response speed and power consumption. A sampling period that is too short will cause frequent touch scanning triggers, increasing processing load and power consumption; a sampling period that is too long may cause click response lag, affecting user experience. Based on the actual usage characteristics of the central control interface, the touch scanning sampling period is set within a reasonable range. For example, in standby or low-interaction states, the sampling period is extended to 80ms–120ms to reduce invalid scans; after detecting continuous operation behavior, the sampling period is dynamically shortened to 20ms–40ms to ensure the accuracy and timeliness of click recognition. By comprehensively judging the touch trigger time, touch duration, touch position changes, and the comparison relationship between the interface state before and after the operation, the interaction type of the user operation is identified. The process of waking the touchscreen from a off or low-brightness state is identified as touchscreen activation behavior, and the number of touchscreen activations is recorded. The time difference between the user clicking a button and the interface responding is recorded as button response latency. The time span from when the user initiates a function operation to when the interface indicates that the operation is completed is identified as operation completion duration. The length of time the user stays on a certain interface without taking further action is statistically analyzed as interface dwell time. These different types of interactive behavior data are recorded separately during the identification process and organized in chronological order to reflect the user's actual operating habits during the use of the smart cabinet.

[0026] By mapping touchscreen activation counts, button response latency, operation completion time, and interface dwell time to corresponding sampling periods, statistical analysis is performed on the interaction frequency, operation density, and interface usage intensity per unit time. When the number of touchscreen activations is low and the interface dwell time is long over several consecutive sampling periods, it can be determined that the current state is one of low interaction activity; conversely, multiple activations and short operation completion times within a short period indicate concentrated user operations and high interaction frequency. By statistically analyzing the distribution of different interactive behaviors across sampling periods, interaction statistics are generated to describe the changing trends in interaction intensity at different stages of user interaction with the smart locker.

[0027] In this embodiment, the specific steps for determining whether the smart cabinet has entered a deep standby state based on interactive statistical information are as follows: The activity level of the smart cabinet is evaluated by analyzing the interactive statistics, resulting in a periodic activity index. Set a low-frequency silence threshold; compare and analyze the periodic activity index based on the low-frequency silence threshold; when the low-frequency silence threshold is greater than the periodic activity index, determine that the current smart cabinet is in low-frequency use mode. Entering deep standby mode based on low-frequency usage mode.

[0028] In this embodiment, a weighted analysis of multi-dimensional interactive statistics, such as touchscreen activation count, button response latency, operation completion time, and interface dwell time, is used to construct an activity evaluation method reflecting the intensity of interaction. Touchscreen activation count reflects the frequency with which the user wakes up the interface within a unit period; interface dwell time reflects whether the user is in a prolonged browsing or waiting state; and operation completion time measures the continuity and smoothness of the interaction process. By normalizing these indicators and combining them according to preset weights, a periodic activity index is obtained for the corresponding time period. Within a 60-second statistical period, when the touchscreen activation count is high, the operation completion time is short, and the interface dwell time is dispersed, the periodic activity index is relatively high; conversely, when the activation count is low, the interface dwells for a long time, and there is no obvious operation, the periodic activity index decreases significantly. After obtaining the periodic activity index, a low-frequency silence threshold is pre-set to determine the usage state; this threshold distinguishes between normal interaction states and low-frequency usage states. The setting of the low-frequency silent threshold comprehensively considers the deployment environment, usage time, and historical interaction patterns of the smart cabinet. For example, the threshold can be set lower at night or in areas with sparse traffic, while it can be appropriately increased in high-frequency usage areas during the day. By comparing and analyzing the periodic activity index within the current statistical period with the low-frequency silent threshold, the smart cabinet is determined to be in low-frequency usage mode when the periodic activity index remains below the low-frequency silent threshold for several consecutive statistical periods. This determination process avoids triggering state switching based solely on a single periodic fluctuation, thereby reducing the control overhead caused by frequent entry and exit from energy-saving states.

[0029] When entering deep standby mode, the display output, touch scanning frequency, and background operating modules of the central control interface are subject to tiered power reduction. For example, the display is switched to a low-brightness or off state, the touch scanning sampling cycle is extended to a larger interval to reduce the power consumption caused by continuous polling, and unnecessary interface refresh and data processing are suspended. In deep standby mode, only basic wake-up detection capabilities are retained. When a new touch activation or external event trigger condition is detected, the system gradually restores to normal interaction mode. In this way, the smart cabinet maintains the lowest energy consumption level in scenarios where it is unused for a long time or used infrequently, ensuring a rapid response when a user arrives.

[0030] In this embodiment, the specific steps for identifying the real-time occupancy status of the cabinet based on the deep standby state and generating a cabinet energy consumption report are as follows: Based on the deep standby state, the real-time cabinet occupancy status is identified, and idle and occupied cabinets are marked. Turn off the temperature control module of the vacant cabinet; The occupied cabinets are subjected to constant temperature control; the real-time occupancy status information of the cabinets is statistically analyzed, and a cabinet energy consumption report is generated.

[0031] In this embodiment, when the smart locker is in deep standby mode, the real-time occupancy status of each compartment is continuously identified and categorized to monitor resource usage within the locker under low-power operation. The locker is distinguished as occupied by jointly judging the locker door's open / closed state, lock status, and retrieval records. When the locker door is closed, the lock is engaged, and there are incomplete retrieval records, the locker is marked as occupied; when the locker door is closed but there are no corresponding retrieval records, it is marked as idle. To avoid introducing additional energy consumption during the status identification process, a low-frequency polling method is used for occupancy detection, with a detection cycle set between 3 and 10 minutes, ensuring minimal power consumption during deep standby. After marking the locker occupancy status, the temperature control components of the identified idle lockers are shut down to avoid continuous unnecessary energy consumption. Since there are no items stored in the vacant cabinets, their internal temperature does not need to be maintained within a specific range. Therefore, by stopping the operation of the vacant cabinet temperature control module, the temperature control drive unit enters a sleep or power-off state, retaining only the necessary safety detection capabilities. During implementation, it is first confirmed that the cabinet status remains vacant for multiple consecutive detection cycles to prevent frequent start-ups and shutdowns of the temperature control module due to brief status changes, thus introducing additional power consumption. Subsequently, the power supply to the corresponding cabinet's temperature control is cut off, and the shutdown time is recorded for subsequent energy consumption statistics and analysis. By shutting down the vacant cabinet temperature control module, the base energy consumption level in deep standby mode can be significantly reduced, especially in application scenarios with a large number of cabinets and a high vacancy rate. For cabinets marked as occupied, constant temperature control is implemented to ensure the safety and stability of the stored items. Constant temperature control does not maintain high-precision temperature regulation, but rather maintains the internal temperature of the cabinet within a reasonable range, such as between 15°C and 25°C, based on the general needs of the stored items, to avoid affecting the items due to excessive cold or heat. During constant temperature control, the internal temperature change trend of the cabinet is periodically detected. The temperature control module is only triggered when the temperature deviates from the set range, avoiding energy waste caused by continuous operation. By extending the temperature control detection interval and reducing the temperature control response frequency, the temperature control behavior minimizes energy output while meeting basic requirements. After completing cabinet status identification and differentiated temperature control processing, real-time cabinet occupancy information is summarized and statistically analyzed to form a complete cabinet energy consumption report. By unifying information such as the number of idle cabinets, the number of occupied cabinets, the duration of temperature control on, and the duration of temperature control off, and recording various energy consumption-related parameters by cabinet dimension, the energy consumption situation becomes traceable and analyzable. The cabinet energy consumption report not only reflects the energy consumption distribution during the current deep standby phase but also shows the energy consumption differences between occupied and idle states of different cabinets.

[0032] In this embodiment, an energy consumption monitoring and energy-saving control system for an intelligent cabinet is provided, used to execute the energy consumption monitoring and energy-saving control method for the intelligent cabinet as described above, including: The interface adjustment unit is used to adjust the lighting of the interactive interface based on the user's click on the central control interface of the smart cabinet, and output the real-time interactive interface. An incremental loading unit is used to capture user click behavior based on the real-time interactive interface; perform incremental loading of the interactive interface on the user click behavior to complete real-time interactive energy-saving processing. The interaction statistics unit is used to count the frequency of user click actions and obtain interaction statistics information. The state optimization unit is used to determine whether the smart cabinet has entered a deep standby state based on interactive statistical information; and to perform energy consumption optimization and monitoring processing based on the deep standby state.

[0033] In all respects, the embodiments should be regarded as exemplary and non-limiting, and the scope of the invention is defined by the appended claims rather than the foregoing description. Therefore, it is intended that all variations falling within the meaning and scope of the equivalents of the application be included within the present invention.

[0034] The above description is merely a specific embodiment of the present invention, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein are implemented in other embodiments without departing from the spirit or scope of the invention. The present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features of the invention herein.

Claims

1. A method for energy consumption monitoring and energy-saving control of an intelligent cabinet, characterized in that, Includes the following steps: Based on the smart cabinet's detection of user clicks on the central control interface, the lighting of the interface is adjusted, and the real-time interactive interface is output. Capture user click behavior based on a real-time interactive interface; The user click operation behavior is processed by incremental loading of the interactive interface to complete real-time interactive energy saving. Analyze the frequency of user click actions to obtain interaction statistics. Based on interactive statistical information, the smart cabinet is determined to have entered a deep standby state; Energy consumption optimization and monitoring are performed based on the deep standby state.

2. The energy consumption monitoring and energy-saving control method for intelligent cabinets according to claim 1, characterized in that, The specific steps for detecting user clicks on the central control interface based on the smart cabinet, adjusting the interface lighting, and outputting the real-time interactive interface are as follows: Based on the intelligent cabinet, user clicks on the central control interface are detected, and ambient light sensing parameters are collected based on the light sensor. Based on the analysis of ambient light sensor parameters, the incident angle of light, the distribution of light intensity and the color temperature shift are analyzed to obtain the characteristics of ambient light. Calculate the optimal display brightness value and ambient contrast compensation coefficient based on ambient light characteristics; The interactive interface lighting is adjusted based on the optimal display brightness value and the ambient contrast compensation coefficient, and a real-time interactive interface is output; the interactive interface lighting adjustment includes backlight intensity, pixel brightness rate and color saturation.

3. The energy consumption monitoring and energy-saving control method for the intelligent cabinet according to claim 1, characterized in that, The specific steps for capturing user click behavior based on a real-time interactive interface and performing incremental loading of the interactive interface to complete real-time interactive energy-saving processing are as follows: Capture user click behavior based on a real-time interactive interface; Perform semantic analysis on the user's click behavior to generate semantic features; Based on the semantic features of the operation, the interactive content and the interactive interface are identified, and related interactive content is generated. Identify and tag related elements based on associated interaction content; Incremental loading of the interactive interface for related elements is performed to achieve real-time interactive energy saving.

4. The energy consumption monitoring and energy-saving control method for the intelligent cabinet according to claim 3, characterized in that, The incremental loading process for the interactive interface is specifically as follows: Non-critical background elements are identified based on associated elements; low-priority elements are statically cached and reused. Calculate the number of GPU calls and adaptively reduce the frequency. Identify the frame buffer refresh frequency and reduce the frame buffer refresh frequency.

5. The energy consumption monitoring and energy-saving control method for the intelligent cabinet according to claim 1, characterized in that, The specific steps for statistically analyzing the frequency of user click actions to obtain interaction statistics are as follows: Define the touch scan sampling period; The user's click behavior is used to identify the interaction type and obtain different types of interaction behavior data; the different types of interaction behavior data include the number of touch screen activations, button response latency, operation completion time and interface dwell time. Based on the touch scanning sampling period, the interaction frequency of different types of interactive behavior data is statistically analyzed to obtain interaction statistics information.

6. The energy consumption monitoring and energy-saving control method for intelligent cabinets according to claim 1, characterized in that, The specific steps for determining whether the smart cabinet has entered a deep standby state based on interactive statistical information are as follows: The activity level of the smart cabinet is evaluated by analyzing the interactive statistics, resulting in a periodic activity index. Set a low-frequency silence threshold; compare and analyze the periodic activity index based on the low-frequency silence threshold; when the low-frequency silence threshold is greater than the periodic activity index, determine that the current smart cabinet is in low-frequency use mode. Entering deep standby mode based on low-frequency usage mode.

7. The energy consumption monitoring and energy-saving control method for the intelligent cabinet according to claim 6, characterized in that, The deep standby state specifically refers to: The display driver chip will be switched to sleep mode. Identify the operating power of the wireless communication module; adjust the operating power to the minimum sustaining power; The real-time reporting mode of the wireless communication module is adjusted to a timed batch reporting mode. Adjust the touch scanning frequency of the central control interface to ultra-low frequency polling; Collect interaction information in deep standby mode and generate a deep standby power consumption log.

8. The energy consumption monitoring and energy-saving control method for the intelligent cabinet according to claim 1, characterized in that, The specific steps for energy consumption optimization and monitoring based on the deep standby state are as follows: Based on the deep standby state, the real-time cabinet occupancy status is identified, and a cabinet energy consumption report is generated; Energy consumption optimization and monitoring are performed based on deep standby power consumption logs and cabinet power consumption reports.

9. The energy consumption monitoring and energy-saving control method for intelligent cabinets according to claim 8, characterized in that, The specific steps for identifying the real-time occupancy status of the cabinet based on the deep standby state and generating a cabinet energy consumption report are as follows: Based on the deep standby state, the real-time cabinet occupancy status is identified, and idle and occupied cabinets are marked. Turn off the temperature control module of the vacant cabinet; The occupied cabinets are subjected to constant temperature control; the real-time occupancy status information of the cabinets is statistically analyzed, and a cabinet energy consumption report is generated.

10. An energy consumption monitoring and energy-saving control system for an intelligent cabinet, characterized in that, The method for energy consumption monitoring and energy-saving control of the intelligent cabinet as described in claim 1 includes: The interface adjustment unit is used to adjust the lighting of the interactive interface based on the user's click on the central control interface of the smart cabinet, and output the real-time interactive interface. An incremental loading unit is used to capture user click behavior based on the real-time interactive interface; perform incremental loading of the interactive interface on the user click behavior to complete real-time interactive energy-saving processing. The interaction statistics unit is used to count the frequency of user click actions and obtain interaction statistics information. The state optimization unit is used to determine whether the smart cabinet has entered a deep standby state based on interactive statistical information; and to perform energy consumption optimization and monitoring processing based on the deep standby state.

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