Control method and system of solar camera monitoring equipment

Abstract

The invention discloses a control method of solar camera monitoring equipment. The control method comprises the following steps: S1, acquiring energy storage data and environment data of the solar camera monitoring equipment; s2, according to the energy storage data and the environmental data, determining a predicted electric quantity proportion of the device in a preset time period, the predicted electric quantity proportion being a proportion of a residual electric quantity and a rated capacity of the device in the preset time period; s3, generating an equipment adjustment instruction according to the predicted electric quantity proportion; and S4, adjusting load parameters of the equipment according to the equipment adjusting instruction. According to the control method of the solar camera monitoring equipment, the predicted electric quantity proportion of the preset time period is determined by obtaining the energy storage data and the environment data, the equipment adjusting instruction is generated and executed to adjust the load parameters, and the purpose of dynamically balancing the equipment energy consumption control and monitoring function stability is achieved.

Description

Technical Field

[0001] This invention belongs to the field of intelligent device control technology, and relates to a control method and system for a solar-powered video surveillance device. Background Technology

[0002] Solar-powered video surveillance equipment is a crucial facility in the outdoor security field, and its operational stability and battery life directly impact monitoring effectiveness. Since these devices typically rely on solar panels in conjunction with energy storage batteries for power, environmental factors such as sunlight intensity and weather changes cause fluctuations in battery power. Simultaneously, the power consumption of the device's own components, such as supplementary lighting, video modules, and zoom motors, varies significantly under different operating states (e.g., alarm triggering, daily monitoring). Current technologies often employ fixed power thresholds to trigger simple load switching operations (e.g., directly shutting off supplementary lighting when the battery is low), or adjustments based solely on single-dimensional data (e.g., monitoring only the current battery level). This fails to comprehensively consider the real-time discharge rate of the energy storage battery, the predicted power generation trend under ambient light, and the functional priority requirements under alarm states. Consequently, the device may prematurely shut down when power is low due to a crude adjustment strategy, or waste energy when power is sufficient due to a lack of optimized load power consumption. Ultimately, a dynamic balance between energy consumption control and monitoring function stability cannot be achieved. Summary of the Invention

[0003] This invention provides a control method for a solar-powered video surveillance device. By acquiring energy storage data and environmental data, the method determines the predicted power ratio for a preset time period, generates and executes device adjustment commands to adjust load parameters, thereby achieving the goal of dynamically balancing the stability of the device's energy consumption control and monitoring functions.

[0004] To achieve the above objectives, the present invention adopts the following technical solution: A control method for a solar-powered video surveillance device includes the following steps: S1. Acquire energy storage data and environmental data from solar-powered video surveillance equipment; S2. Based on the energy storage data and the environmental data, determine the predicted power ratio of the device during a preset period, wherein the predicted power ratio is the ratio of the remaining power of the device to its rated capacity during the preset period; S3. Generate device adjustment instructions based on the predicted power ratio; S4. Adjust the load parameters of the device according to the device adjustment instruction.

[0005] Furthermore, the energy storage data includes the device's current power percentage and battery discharge rate, and the environmental data includes light intensity and weather conditions. Determining the predicted power percentage of the device within a preset time period based on the energy storage data and the environmental data includes the following steps: S21. Preprocess the light intensity and the weather condition respectively to obtain the average light intensity and the weather correction coefficient; S22. Based on the average light intensity and the weather correction coefficient, determine the predicted power generation of the device during the preset time period; S23. Based on the current power ratio, the battery discharge rate, and the predicted power generation, determine the predicted power ratio of the device during the preset time period.

[0006] Furthermore, after determining the predicted power ratio of the device during the preset time period based on the current power ratio, the battery discharge rate, and the predicted power generation, the process includes: S24. Acquire device status data, wherein the device status data includes the device's detection alarm status and the real-time power consumption of the load in the device; When the detection alarm state of the device is triggered and the real-time power consumption of the load in the device increases, the battery discharge rate is corrected.

[0007] Furthermore, generating device adjustment instructions based on the predicted power ratio includes the following steps: S31. Generate a corresponding basic adjustment instruction based on the threshold range to which the predicted power ratio belongs; S32. Based on the detection alarm status of the device, the basic adjustment command is adjusted for the first time to generate a first adjustment command; S33. Based on the predicted power generation trend, the first adjustment instruction is adjusted a second time to generate a second adjustment instruction; S34. Generate the device adjustment instruction based on the second adjustment instruction.

[0008] Furthermore, generating the device adjustment instruction based on the second adjustment instruction includes the following steps: S341. Obtain the load type, adjustment method, adjustment time node, and adjustment magnitude of the device corresponding to the second adjustment instruction; S342. Based on the load type, adjustment method, adjustment time node, and adjustment magnitude, generate the device adjustment command that can be executed by the device.

[0009] Furthermore, the adjustment instructions include maintenance instructions, power reduction instructions, load limiting instructions, and alarm priority instructions; The step of adjusting the load parameters of the device according to the device adjustment command includes: When the adjustment command is the maintenance command, the device's fill light is controlled to maintain the original high-brightness constant-on mode, the video module maintains high-quality operating parameters, and the zoom motor maintains high-frequency automatic adjustment parameters. When the adjustment command is the power reduction command, the device's fill light is controlled to reduce its brightness to the basic lighting level, the video module is switched to medium quality operating parameters, and the zoom motor extends the automatic adjustment interval. When the adjustment command is a load limiting command, the supplementary light of the device is adjusted to only be triggered by the detection alarm, the video module is switched to low quality operating parameters, and the zoom motor's automatic adjustment function is turned off. When the adjustment command is an alarm priority command, the device's fill light is forced to turn on high brightness mode, the video module maintains basic high-quality operating parameters, and the zoom motor resumes intermediate frequency automatic adjustment parameters.

[0010] A control system for a solar-powered video surveillance device, and a control method for the solar-powered video surveillance device, comprising: The data acquisition module is used to acquire energy storage data and environmental data from the solar-powered video surveillance equipment. The power prediction module is used to determine the predicted power ratio of the device in a preset period based on the energy storage data and the environmental data. The predicted power ratio is the ratio of the remaining power of the device in the preset period to its rated capacity. The instruction generation module is used to generate device adjustment instructions based on the predicted power ratio; The load adjustment module is used to adjust the load parameters of the device according to the device adjustment command.

[0011] The beneficial effects of this invention are as follows: By acquiring energy storage data and environmental data from solar-powered video surveillance equipment, this invention determines the predicted power ratio for a preset time period, and then generates and executes equipment adjustment commands based on this predicted ratio, thereby achieving dynamic control of equipment load parameters. This method comprehensively considers the real-time status of the energy storage battery and the environmental power generation potential, avoiding the limitations of traditional methods that rely solely on current power or fixed threshold adjustments. It effectively balances the stability of equipment energy consumption control and monitoring functions, reducing the risk of monitoring interruptions due to insufficient power and avoiding energy waste when power is sufficient, significantly improving the endurance and operational reliability of solar-powered video surveillance equipment. Attached Figure Description

[0012] Figure 1 This is a schematic diagram of the overall method steps of the present invention.

[0013] Figure 2 This is a schematic diagram illustrating the steps of the method for determining the predicted power ratio in this invention.

[0014] Figure 3 This is a schematic diagram of the steps of the method for generating device adjustment instructions according to the present invention. Detailed Implementation

[0015] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains; the terminology used herein in the specification is for the purpose of describing particular embodiments only and is not intended to limit the invention; the terms "comprising" and "having," and any variations thereof, in the specification, claims, and foregoing drawings are intended to cover non-exclusive inclusion. The terms "first," "second," etc., in the specification, claims, or foregoing drawings are used to distinguish different objects and not to describe a particular order.

[0016] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of the invention. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0017] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0018] A control method for a solar-powered video surveillance device includes the following steps: S1. Acquire energy storage data and environmental data from solar-powered video surveillance equipment; The energy storage data includes the device's current power percentage and battery discharge rate; Among them, the current power ratio refers to the ratio of the battery's current remaining power to its rated capacity (e.g., "remaining power is 65% of the rated capacity"), reflecting the current energy storage level of the device. It can be collected in real time by the relevant battery management equipment or system built into the device. By monitoring the battery terminal voltage, current integration, etc., the remaining power is calculated and compared with the rated capacity to output the current power ratio. The battery discharge rate refers to the proportion of the battery's released power per unit time to its rated capacity (e.g., "discharge per hour is 8% of the rated capacity"), reflecting the battery's power consumption rate. The relevant battery management equipment or system monitors the total load current (e.g., "current total load current is 2.5A") and combines it with the battery voltage (e.g., "12V") to calculate the total power consumption (total power consumption = current × voltage). Then, the hourly discharge ratio is obtained by using the formula "discharge rate = total power consumption / (battery voltage × rated capacity)".

[0019] The environmental data includes light intensity and weather conditions; Among them, light intensity refers to the intensity of light radiation received by the solar panel (e.g., "current light intensity is 8000 lux"), which directly affects the efficiency of solar power generation. The light intensity data can be collected in real time by the light sensor on the top of the device. The sensor then converts the light signal into an electrical signal, and outputs the light intensity value after analog-to-digital conversion. Weather status refers to the weather conditions within a preset time period (e.g., "cloudy to sunny in the next 2 hours"), which is used to correct the solar power generation forecast. The weather status data can be accessed through the device's built-in network module (e.g., 4G / 5G communication module) to obtain weather status information for the next preset time period (e.g., "2 hours").

[0020] The device status data includes the device's detection alarm status and the real-time power consumption of the load in the device. Among them, the alarm detection status refers to whether the device has triggered an alarm (e.g., "alarm triggered"). It reflects whether the device is in a high-priority working mode (e.g., enhanced monitoring is required). The alarm detection status can be determined by the device's built-in alarm detection system or by devices (e.g., motion sensors, sound sensors). For example, if the sensor detects an anomaly (e.g., a moving object or a high-decibel sound), it will output an "alarm triggered" status signal. The real-time power consumption of the fill light, video module, and zoom motor refers to the current power consumption of each load (e.g., "fill light power consumption 15W, video module power consumption 20W, zoom motor power consumption 0W"). It reflects the real-time energy consumption distribution of the device. The power consumption is calculated by collecting the current value through the independent current monitoring module of each load and combining it with the battery voltage (e.g., "12V") (power consumption = current × voltage).

[0021] The three types of data mentioned above together constitute a complete picture of the equipment's operating status. Energy storage data (current power ratio, discharge rate) reflects the battery's power storage and consumption capacity; environmental data (sunlight intensity, weather conditions) reflects the power generation potential of the solar panels; and equipment status data (detection alarm status, load power consumption) reflects the priority of the equipment's power demand (e.g., prioritizing the power consumption of the video module when an alarm is triggered). By synchronously collecting and analyzing this data, the power supply and demand relationship of the equipment can be accurately assessed, providing a core basis for subsequent prediction of power ratio and generation of adjustment instructions.

[0022] S2. Based on the energy storage data and the environmental data, determine the predicted power ratio of the device during a preset period, wherein the predicted power ratio is the ratio of the remaining power of the device to its rated capacity during the preset period; Specifically, using a "preset period" (e.g., 10:00 PM to 6:00 AM the next day) covering the main monitoring time period as a time window, the predicted power consumption ratio is calculated. The preset period is a defined future time interval. The total future power generation is predicted by combining the solar panel's power output (e.g., no power generation at night), and the total future power consumption is predicted by combining the current power consumption of each module of the equipment (e.g., high-definition video mode, constant supplementary lighting). Based on the current remaining power, predicted power generation, and predicted power consumption, the remaining power at the end of the historical period is calculated. Finally, the predicted power consumption ratio corresponding to the preset period is obtained by dividing the remaining power by the rated capacity. The core of this step is to quantitatively assess the future energy safety level of the equipment—for example, if the predicted power consumption ratio is only 15% (below the equipment shutdown protection threshold of 20%), it is clear that the equipment faces the risk of "monitoring interruption due to power depletion" within the preset period.

[0023] Specifically, step S2 also includes the following steps: S21. Preprocess the light intensity and the weather condition respectively to obtain the average light intensity and the weather correction coefficient; Specifically, environmental data includes two types of raw data: real-time light intensity and future weather data. Preprocessing unifies and corrects these two types of raw data to obtain two key parameters: the average light intensity and the weather correction coefficient. The average light intensity reflects the average light radiation intensity received by the solar panels within a preset time period and is used to calculate the basic power generation efficiency. The weather correction coefficient reflects the impact of weather conditions on power generation efficiency (e.g., cloudy weather will reduce the actual power generation capacity) and is used to adjust the basic power generation efficiency.

[0024] The calculation process for the average light intensity is as follows: The light sensor collects light intensity data every 5 minutes, collecting 12 sets of data per hour (time points: 0min, 5min, 10min…55min). If a set of data deviates significantly from other data (e.g., a value of 10000 lux is collected, while the values ​​before and after it are 5000-6000 lux), it is determined to be a sensor error and the outlier is discarded. Assuming 11 sets of valid data are collected per hour, with specific values ​​of 5200 lux, 5500 lux, 5800 lux, 5300 lux, 5600 lux, 5400 lux, 5700 lux, 5100 lux, 5900 lux, 5500 lux, and 5400 lux, the average light intensity is calculated using the formula "average light intensity = (5200 + 5500 + … + 5400) / 11", resulting in an average value of approximately 5500 lux.

[0025] The process for determining the weather correction factor is as follows: The network module obtains the weather status for the next one or several hours as "partly cloudy, 70% cloud cover" (the higher the cloud cover, the more severe the sunlight obstruction). It then uses a built-in "Weather Type - Correction Coefficient" lookup table (based on historical power generation data statistics; for example: sunny <30% cloud cover corresponds to 1.0, partly cloudy 30%-50% cloud cover corresponds to 0.8, partly cloudy 50%-80% cloud cover corresponds to 0.6, and overcast / rainy ≥80% cloud cover corresponds to 0.3). The correction coefficient for "partly cloudy, 70% cloud cover" is matched to 0.6. The correction coefficient in the lookup table can be adaptively modified according to actual needs or other requirements.

[0026] S22. Based on the average light intensity and the weather correction coefficient, determine the predicted power generation of the device during the preset time period; Base power generation is the theoretical power generation capacity of a solar panel under current sunlight conditions. It can be determined as follows: The system of the equipment can pre-calibrate the mapping relationship between "illuminance and base power generation" (such as the baseline value under standard sunlight conditions and the proportional relationship corresponding to different sunlight intensities). Based on the pre-processed average sunlight intensity, the base power generation without weather correction is calculated through this mapping relationship (such as linear interpolation, piecewise functions, or lookup tables). This step avoids the random errors of single sampling (such as low sunlight values ​​caused by instantaneous cloud cover) by statistically averaging the sunlight intensity, making the base power generation closer to the theoretical power generation capacity under actual sunlight conditions.

[0027] The weather correction factor reflects the impact of actual weather on the effective solar radiation received by solar panels (e.g., cloudy weather reduces the utilization rate of sunlight). The base power generation is multiplied by the weather correction factor to obtain the predicted power generation within a preset time. This adjustment process dynamically corrects the impact of future weather changes on power generation capacity, which cannot be reflected by relying solely on sunlight intensity, by combining weather state information.

[0028] S23. Based on the current power ratio, the battery discharge rate, and the predicted power generation, determine the predicted power ratio of the device during the preset time period.

[0029] In this step, the discharge consumption within a preset time period is first calculated. Discharge consumption refers to the proportion of electricity consumed by the battery due to load operation without any power generation replenishment. The calculation formula is as follows: Discharge consumption = Battery discharge rate × Preset time; Example: If the battery discharge rate is 12% / hour and the preset time is 2 hours, then: Discharge consumption = 12% / hour × 2 hours = 24%; Secondly, calculate the supplementary power generation within the preset time period. Supplementary power generation refers to the proportion of electricity generated by the solar panels and stored in the batteries within the preset time period. This requires first converting the predicted power generation into actual supplementary electricity (Wh), and then converting it into a percentage of the rated capacity (%). The calculation formula is as follows: Power generation supplement = (predicted power generation × preset time) / battery rated capacity × 100%; Example: If the predicted power generation is 48W, the preset time is 2 hours, and the battery's rated capacity is 2400Wh, then: Supplemental power generation = (48W × 2 hours) / 2400Wh × 100% = 4%; Finally, calculate the predicted battery capacity percentage after a preset time. The predicted battery capacity percentage is the current battery capacity percentage minus the discharge consumption, plus the power generation replenishment (if the power generation replenishment is greater than the discharge consumption, the battery capacity increases; otherwise, it decreases). The calculation formula is: Predicted power ratio = Current power ratio - Discharge consumption + Power generation replenishment; Example: Current battery percentage is 65%, discharge consumption is 24%, and power generation replenishment is 4%, then: Predicted electricity consumption percentage = 65% - 24% + 4% = 45%.

[0030] More specifically, to improve the accuracy of the predicted power ratio, this control method can optimize the traditional linear calculation (S21-S23) by combining a large artificial intelligence model. Specifically, it trains a large time series model (such as LSTM or Transformer) by collecting historical energy storage data (current power ratio, battery discharge rate, and aging degradation coefficient), environmental data (minute-level light intensity, weather conditions), equipment status data (alarm trigger status, real-time load power consumption), and time features (seasonal, time period, lunar phase, and other periodic information). The model uses "multi-dimensional data from the previous 24 hours" as input and "predicted power ratio for a future preset time period" as output label for supervised learning (the optimizer uses Adam, dynamically adjusting the learning rate to minimize MSE). When the equipment is running, the traditional linear calculation and the large model prediction are executed simultaneously. The results are output through a weighted fusion formula (final predicted ratio = α × large model prediction value + (1-α) × traditional prediction value, where α is dynamically adjusted according to recent errors). This effectively captures the influence of nonlinear factors such as light fluctuations and battery aging, solving the problem of large errors in traditional methods under complex scenarios. S24. Obtain device status data, wherein the device status data includes the device's detection alarm status and the real-time power consumption of the load in the device.

[0031] Specifically, the system determines whether an alarm state is triggered by multi-sensor fusion (e.g., the sensor detects an abnormal target and video analysis confirms it is not natural interference). Once triggered, it outputs an "alarm triggered" signal. At the same time, it needs to dynamically collect load power consumption, including the basic operating power consumption of the device when there is no alarm (e.g., low brightness of the supplementary light, normal frame rate of the video module, and normal power consumption of the zoom motor in standby mode), the real-time power consumption increase caused by the increase in brightness of the supplementary light, the increase in frame rate of the video module, the start of the zoom motor, etc. after the alarm is triggered (alarm state power consumption), and the total energy storage capacity of the energy storage battery (battery rated capacity) used to convert power consumption into energy ratio.

[0032] The correction process is as follows: The control system reads the alarm status signal in real time. If it is "yes" (alarm triggered), the correction process begins. If it is "no" (normal state), the original discharge rate based on normal power consumption statistics is maintained. Then, the increase in the total power consumption of the device under alarm state due to the increase in load power consumption is calculated (i.e., the difference between the total power consumption under alarm state and the total power consumption under normal state). Since the battery discharge rate is essentially "the proportion of electricity consumed per unit time to the rated capacity of the battery" and is proportional to the total power consumption of the device, it is calculated based on normal power consumption under normal state, and needs to be corrected in conjunction with the power consumption increment under alarm state (the higher the total power consumption, the greater the discharge rate). Finally, in step S23, the predicted power ratio originally calculated based on the normal discharge rate is replaced with a recalculation using the corrected discharge rate (the greater the discharge rate, the more electricity is consumed within the preset time).

[0033] S3. Generate device adjustment instructions based on the predicted power ratio; The device control chip has a preset "power ratio - adjustment strategy" mapping rule (e.g., ≥30% is high security level, 10%-30% is medium security level, <10% is low security level). Based on the predicted power ratio obtained in S2 (e.g., 15% is medium security level), corresponding adjustment instructions are generated: at the high security level, the current parameters are maintained (e.g., high video quality, constant supplementary light) to ensure monitoring effect; at the medium security level, the power consumption of non-critical loads is reduced (e.g., video is switched to medium quality, supplementary light is adjusted to low brightness) to balance energy consumption and monitoring; at the low security level, core loads are limited and unnecessary loads are turned off (e.g., video is switched to low quality, supplementary light is only turned on when alarm is triggered, zoom motor automatic adjustment is turned off) to maximize battery life. For example, in this embodiment, since the predicted power ratio is 15% (medium security level), the instruction "video is switched to medium quality, supplementary light is adjusted to low brightness" is generated, which reduces energy consumption while ensuring basic monitoring capabilities.

[0034] In this embodiment, step S3 further includes the following steps: S31. Generate a corresponding basic adjustment instruction based on the threshold range to which the predicted power ratio belongs; Specifically, the system pre-sets three threshold intervals: high battery level area, medium battery level area, and low battery level area. The basis for the division includes the energy storage characteristics of the device (such as the rated battery capacity), the power consumption characteristics of the load (such as the power consumption ratio of critical loads to non-critical loads), and the monitoring requirements of the application scenario (such as whether 24-hour uninterrupted monitoring is required). The specific definitions are as follows: The high battery level area is defined as the predicted battery level ratio B ≥ B_high (such as 70%). The setting basis is that the remaining battery power is sufficient to meet the long-term operation of the device under normal load (such as ≥ 8 hours) without restricting power consumption. The medium battery level area is defined as B_low ≤ B < B_high (such as 40% ≤ B < 70%). The setting basis is that the remaining battery power is medium, and it is necessary to optimize the power consumption of non-essential loads to extend the battery life, but the basic functions of critical loads need to be retained. The low battery level area is defined as B < B_low (such as B < 40%). The setting basis is that the remaining battery power is tight, and it is necessary to forcibly turn off non-critical loads to prioritize the short-term operation of critical monitoring functions (such as ≤ 4 hours). Among them, the specific values of B_high (the lower threshold of the high battery level area) and B_low (the lower threshold of the medium battery level area) can be dynamically adjusted according to the device type and scenario requirements. For example, devices used for forest fire monitoring have higher requirements for battery life, and B_low can be set to 50%; devices used for general park monitoring can be set to 40%.

[0035] Furthermore, the basic adjustment instructions corresponding to each threshold interval are as follows: 1. High battery level area (B ≥ B_high) Goal: Maintain the full-function operation of the device and ensure the monitoring quality.

[0036] Basic adjustment instruction: All loads maintain the normal working mode without additional power consumption restrictions.

[0037] Supplementary light: Turn on the automatic dimming mode (automatically adjust the brightness according to the ambient light); Video module: Collect at high resolution (such as 4K) and high frame rate (such as 25fps); Zoom motor: Support free adjustment (adjust the focal length according to the monitoring target in real time).

[0038] 2. Medium battery level area (B_low ≤ B < B_high) Goal: Optimize the power consumption of non-essential loads and balance battery life and monitoring quality.

[0039] Basic adjustment instruction: Reduce the power consumption of non-essential loads and retain the basic functions of critical loads.

[0040] Supplementary light: Turn off the automatic strong light mode (only turn on low-brightness supplementary light when the ambient light is lower than the threshold); Video module: Reduce frame rate (e.g., from 25fps to 20fps) or resolution (e.g., from 4K to 1080P). Zoom motor: Limit adjustment frequency (e.g., adjust once every 5 minutes at most to avoid power consumption from frequent operation).

[0041] 3. Low battery area (B) <B_low) Objective: Force power rationing to prioritize the short-term operation of critical monitoring functions.

[0042] Basic adjustment command: Shut down non-critical workloads and retain only the minimum functionality of critical workloads.

[0043] Fill lights: All off (for non-critical loads, nighttime monitoring relies on infrared mode); Video module: Reduce to the lowest resolution (e.g., 720P) and frame rate (e.g., 15fps). Zoom motor: Stop active adjustment (only supports manual triggering or single adjustment in emergency situations).

[0044] S32. Based on the detection alarm status of the device, the basic adjustment command is adjusted for the first time to generate a first adjustment command; This step is a dynamic correction step in the generation of equipment adjustment instructions. The core objective is to make the first correction to the instructions within the framework of the basic adjustment instructions, taking into account whether the equipment is currently in a critical monitoring stage (i.e., detection alarm state), so as to ensure the effectiveness of critical monitoring functions is prioritized when power is limited.

[0045] The adjustment logic in this step is based on the "critical task priority" principle: when the device is in an alarm state, restrictions on critical loads should be relaxed to ensure monitoring quality; when there is no alarm, basic instructions should be strictly executed to save power. The specific adjustment rules are as follows: 1. Alarm status trigger ("Yes" state): Critical loads take priority; When an alarm state is detected (such as tracking illegally parked vehicles), the system needs to identify the "critical loads" (modules that directly affect the effectiveness of monitoring) and "non-critical loads" (auxiliary function modules) in the device, and relax the restrictions on basic instructions for critical loads, while non-critical loads still execute according to basic instructions.

[0046] Critical loads typically include video modules (which determine image clarity) and zoom motors (which determine target tracking capabilities); non-critical loads typically include fill lights (for auxiliary lighting, which can be replaced by infrared mode) and status indicator lights (used only for displaying device status).

[0047] Example: The basic adjustment command is "medium power zone strategy" (video module reduced to 1080P@20fps, fill light turned off automatic high beam). If an alarm is detected at this time (such as tracking an illegally parked vehicle), the adjustment rules are as follows: Critical load (video module): relax restrictions, maintain the original resolution (4K) and frame rate (25fps) to ensure clear recording of vehicle information; Non-critical load (fill light): still turn off automatic high beam mode according to the basic command (to avoid extra power consumption).

[0048] 2. Alarm status not triggered (“No” status): Strictly execute basic instructions; When the device is in normal monitoring mode (no abnormal events), the system does not need to provide additional protection for the high-performance operation of critical loads. At this time, the power consumption of each load is strictly controlled in accordance with the basic adjustment instructions in order to maximize the device's battery life.

[0049] Example: The basic adjustment command is "medium power zone strategy" (video module 1080P@20fps, fill light off automatic high beam). If no alarm state is detected (such as only recording road images normally), each load will strictly follow the basic command without any additional relaxation.

[0050] S33. Based on the predicted power generation trend, the first adjustment instruction is adjusted a second time to generate a second adjustment instruction; This step is the final dynamic correction stage of the equipment adjustment command generation. The core objective is to further adjust the load control strategy based on the first adjustment command (which already incorporates power thresholds and alarm status) and the future power generation trend (i.e., changes in the power generation capacity of the solar panels), so as to balance the current power consumption with the future power replenishment capacity and avoid excessive or insufficient power curtailment caused by changes in power generation capacity.

[0051] The predicted power generation trend includes an upward trend (future power generation will increase significantly), a stable trend (future power generation will remain basically stable), and a downward trend (future power generation will decrease significantly or will soon enter a period of no sunlight at night). The adjustment logic in this step is based on the principle of dynamically adapting to future power supply capacity: if future power generation capacity increases (upward trend), the current load limit can be appropriately relaxed to improve monitoring quality; if future power generation capacity decreases (downward trend), the current load needs to be further limited to reserve power; if power generation capacity is stable (stable trend), the first adjustment instruction is maintained. The specific adjustment rules are as follows: 1. Rising power generation trend: Relax load restrictions and improve monitoring quality; When the predicted power generation shows an upward trend, the future power generation of solar panels will increase, and the battery's replenishment capacity will be enhanced. At this time, the system can appropriately restore the power consumption of some loads to improve monitoring quality and avoid functional redundancy caused by excessive power curtailment.

[0052] Adjustment targets: Prioritize the restoration of critical loads that have a significant impact on monitoring quality (such as video module frame rate and zoom motor adjustment frequency). Adjustment range: dynamically set according to the increase in power generation (e.g., for every 10% increase in power generation, 1-2 fps of video frame rate can be restored).

[0053] Example: The first adjustment instruction is "video module 1080P@20fps (medium power range + no alarm status)". If the predicted power generation trend is "rising" (e.g., with enhanced light, the power generation will increase by 20% in the next 3 hours), then the adjustment rule is: restore the video module frame rate to 22fps to improve the smoothness of the picture; maintain the basic strategy of "off automatic high light" for the supplementary lights (non-critical loads do not need to be restored).

[0054] 2. Power generation trend is "stable": The first adjustment order will be maintained, with no additional adjustments. When the predicted power generation is stable, the future battery replenishment capacity is basically stable. The current load control strategy has already balanced power generation and monitoring needs, and no additional adjustments are required.

[0055] Example: The first adjustment instruction is "video module 1080P@20fps, fill light off automatic high beam". If the predicted power generation trend is "stable" (e.g., stable light, power generation fluctuation ≤5% in the next 3 hours), then the second adjustment instruction is the same as the first adjustment instruction, and each load is strictly executed according to the original strategy.

[0056] 3. Power generation trend "declining": Strengthen load constraints and reserve power; When the predicted power generation trend is downward, the future power generation of solar panels will decrease, and the battery's ability to replenish power will weaken. At this time, the system needs to further limit load power consumption to reserve sufficient power to ensure the continuous operation of critical monitoring functions.

[0057] Adjustment targets: Prioritize limiting non-critical loads that have a minor impact on monitoring quality (such as supplementary lights and status indicators); if this is still insufficient, moderately limit critical loads. Adjustment range: dynamically set according to the rate of decrease in power generation (e.g., for every 10% decrease in power generation, the video frame rate decreases by 1-2 fps).

[0058] Example: The first adjustment instruction is "video module 1080P@20fps (medium power range + no alarm status)". If the predicted power generation trend is "decreasing" (e.g., the power generation will decrease by 30% in the next 3 hours due to upcoming cloudy weather), then the adjustment rule is: reduce the video module frame rate to 18fps and turn off the status indicator (non-critical load) to further reduce power consumption.

[0059] S34. Generate the device adjustment instruction based on the second adjustment instruction.

[0060] Specifically, step S34 includes: S341. Obtain the load type, adjustment method, adjustment time node, and adjustment magnitude of the device corresponding to the second adjustment instruction; The second adjustment instruction is the final optimization strategy that integrates the current power threshold, alarm status, and future power generation trends (e.g., "reduce the video module frame rate to 18fps and keep the fill light in low brightness mode"). The core task of this step is to extract specific control parameters from this strategy to provide data support for subsequent hardware template matching.

[0061] The specific steps are as follows: Identify the adjustment target: Identify the load modules that need adjustment (such as video capture modules, fill lights, zoom motors, etc.); Parameter analysis: Extract the specific control requirements of each module, including quantitative parameters (such as video resolution "1080P", frame rate "18fps") and qualitative parameters (such as fill light "low brightness fill light only", zoom motor "adjust once every 10 minutes"). Clearly define constraints: Identify implicit priority rules (such as "critical load (video module) parameters must not be lower than the safety threshold" and "non-critical load (status indicator) can be downgraded").

[0062] Through this step, the abstract strategy description is transformed into a structured set of parameters (such as "video module: 1080P@18fps, critical load; fill light: low brightness mode, non-critical load"), providing a clear input basis for subsequent steps.

[0063] S342. Based on the load type, adjustment method, adjustment time node, and adjustment magnitude, generate the device adjustment instruction that can be executed by the device; To ensure compatibility between the strategy parameters and the device hardware, the extracted parameters must be matched with a pre-designed "instruction parameter template." The template is predefined based on device hardware characteristics (such as the resolution range supported by the video module and the dimming capability of the supplementary lighting) and application scenarios (such as outdoor monitoring needing to cope with day-night temperature differences), and includes the following four categories of rules: Load type rules: Define the priority of each module (e.g., the video module is a "critical load" and should be prioritized; the fill light is a "non-critical load" and can be appropriately restricted). Adjustment method rules: Specify the operation type for parameter adjustment (e.g., "direct setting" is suitable for fixed parameters such as video resolution; "phased adjustment" is suitable for parameters that require gradual transition, such as extending the zoom motor adjustment interval from 5 minutes to 10 minutes). Time-based rules: Clearly define when to adjust (e.g., critical load parameters need to be adjusted in real time to ensure monitoring quality; non-critical load parameters can be adjusted later, after the current task is completed). Adjustment amplitude rules: Limit the magnitude of parameter changes (e.g., video frame rate adjustment should not exceed ±2fps each time to avoid hardware overload).

[0064] By matching templates, parameters are translated into hardware-understandable "adjustment action" descriptions (such as "Video module (critical load): direct setting, real-time execution, frame rate reduction of 2fps"), ensuring that the strategy is consistent with the hardware capabilities.

[0065] This step is the final stage of strategy implementation, requiring the "adjustment actions" determined in the first two steps to be translated into instructions that the device hardware can directly execute. The specific process is as follows: Instruction content design: Based on the hardware communication protocol (such as the device's internal control bus), the adjustment elements (load type, adjustment method, time node, amplitude) are converted into instruction content that the device can recognize. For example, the video module's "1080P@18fps" needs to be converted into a "resolution setting + frame rate setting" combination instruction that the hardware can receive; the fill light's "low brightness mode" needs to be converted into a "dimming mode switching" instruction.

[0066] Command Verification: After command generation, its reliability must be ensured through double verification. Hardware compatibility check: Check whether the parameters are within the range supported by the device (e.g., whether the video module supports 18fps frame rate). Logical consistency check: Confirm that there are no conflicts between the instructions of different modules (such as whether the video frame rate adjustment and the zoom motor adjustment interval are compatible to avoid blurry images).

[0067] The adjustment instructions include maintenance instructions, power reduction instructions, load limiting instructions, and alarm priority instructions; S4. Adjust the load parameters of the equipment according to the equipment adjustment instructions.

[0068] The adjustment instructions include maintenance instructions, power reduction instructions, load limiting instructions, and alarm priority instructions; The step of adjusting the load parameters of the device according to the device adjustment command includes: When the adjustment command is the maintenance command, the device's fill light is controlled to maintain the original high-brightness constant-on mode, the video module maintains high-quality operating parameters, and the zoom motor maintains high-frequency automatic adjustment parameters. When the adjustment command is the power reduction command, the device's fill light is controlled to reduce its brightness to the basic lighting level, the video module is switched to medium quality operating parameters, and the zoom motor extends the automatic adjustment interval. When the adjustment command is a load limiting command, the supplementary light of the device is adjusted to only be triggered by the detection alarm, the video module is switched to low quality operating parameters, and the zoom motor's automatic adjustment function is turned off. When the adjustment command is an alarm priority command, the device's fill light is forced to turn on high brightness mode, the video module maintains basic high-quality operating parameters, and the zoom motor resumes intermediate frequency automatic adjustment parameters.

[0069] This embodiment focuses on the load parameter adjustment logic of a solar-powered video surveillance device (hereinafter referred to as "the device"). Through the dynamic execution of the following four types of adjustment commands, it achieves an intelligent balance between monitoring capability and energy consumption. The device's preset parameters include: power threshold (corresponding to the power threshold range in step S31), alarm detection status (non-emergency alarm, emergency alarm), load type (fill light, video module, zoom motor), adjustment methods (brightness adjustment, image quality switching, interval extension, etc.), adjustment time points (continuous / current moment / next cycle / real-time / immediate), and adjustment amplitude (preset level parameters, such as high brightness, medium image quality, extension factor, etc.). The specific implementation steps are as follows: 1. Maintain the implementation of instructions; Triggering conditions: The predicted power consumption ratio monitored by the device in real time is in the high power consumption range, and no detection alarm is triggered (no moving object or intrusion event).

[0070] Adjustment operation: Fill light: Maintain high brightness constant light mode according to preset adjustment method (adjustment time point is continuous, adjustment amplitude is high brightness parameter); Video module: Maintain high-quality operating parameters according to preset adjustment method (adjustment time node is continuous, adjustment amplitude is high quality level); Zoom motor: Maintains high-frequency automatic adjustment parameters according to preset adjustment mode (adjustment time node is continuous, adjustment amplitude is a multiple of high-frequency interval). Implementation results: The equipment operates at full capacity, the supplementary lighting provides sufficient illumination, the video module outputs high-definition images, and the zoom motor responds to dynamic scenes in real time, meeting the all-weather high-definition monitoring needs under high power conditions, with energy consumption at a normal level.

[0071] 2. Implementation of power reduction instructions; Triggering conditions: The device's predicted battery level is in the medium range, or a non-emergency detection alarm is triggered (such as a moving object that is not marked as an intrusion).

[0072] Adjustment operation: Fill light: Reduce brightness to basic lighting level according to preset adjustment method (adjustment time point is the current moment, adjustment amplitude is the basic amplitude); Video module: Switch to medium quality operating parameters according to the preset adjustment method (adjustment time point is the next cycle, adjustment amplitude is medium quality level); Variable zoom motor: Extend the automatic adjustment interval according to the preset adjustment method (the adjustment time node is after the current operation ends, and the adjustment amplitude is the preset extension multiple). Implementation results: The equipment load intensity is reduced, the supplementary lights only provide basic lighting, the video module reduces data transmission, and the zoom motor reduces frequent adjustments. While ensuring basic monitoring capabilities, energy consumption is reduced, achieving balanced control under moderate power consumption conditions.

[0073] 3. Restrict the execution of load commands; Triggering conditions: The device's predicted battery percentage is in the low battery range, and no emergency detection alarm has been triggered (only environmental disturbances or non-intrusion events).

[0074] Adjustment operation: Supplemental lighting: It is turned on only when an alarm is triggered according to the preset adjustment mode (the adjustment time is off during non-alarm periods / on during alarm periods, and the adjustment value is completely off). Video module: Switch to low quality operating parameters according to the preset adjustment method (adjustment time point is real time, adjustment amplitude is low quality level). Zoom motor: Turn off the automatic adjustment function according to the preset adjustment mode (adjustment time point is immediate, adjustment amplitude is locked fixed angle). Implementation results: The device load enters a low-power mode, the fill light is only used briefly when necessary, the video module significantly reduces image quality to reduce computing and storage consumption, the zoom motor stops unnecessary adjustments, minimizing energy consumption and extending the device's battery life under low power conditions.

[0075] 4. Implementation of alarm priority commands: Triggering conditions: The device's predicted battery percentage is in the low battery range, but an emergency detection alarm is triggered (such as human intrusion, abnormal entry, or other events that need to be recorded).

[0076] Adjustment operation: Fill light: Force high brightness mode to be turned on according to preset adjustment method (adjustment time point is immediate, adjustment amplitude is high brightness parameter); Video module: Maintain basic high-quality operating parameters according to preset adjustment methods (adjustment time point is real-time, adjustment amplitude is basic high-quality level); Variable zoom motor: Restore the intermediate frequency automatic adjustment parameters according to the preset adjustment method (the adjustment time node is after the current operation ends, and the adjustment amplitude is the intermediate frequency interval multiple); Implementation results: When the device is in low power condition, it prioritizes monitoring of emergency events. The supplementary light provides sufficient illumination to clearly record the target. The video module maintains key image quality parameters. The zoom motor dynamically tracks the target to ensure complete and clear recording of emergency events. After the alarm is cleared, it automatically switches back to the load limiting mode.

[0077] A control system for a solar-powered video surveillance device, comprising executing a control method for the solar-powered video surveillance device, including: The data acquisition module is used to acquire energy storage data and environmental data from the solar-powered video surveillance equipment. The power prediction module is used to determine the predicted power ratio of the device in a preset period based on the energy storage data and the environmental data. The predicted power ratio is the ratio of the remaining power of the device in the preset period to its rated capacity. The instruction generation module is used to generate device adjustment instructions based on the predicted power ratio; The load adjustment module is used to adjust the load parameters of the device according to the device adjustment command.

[0078] This invention can be used in a wide range of general-purpose or special-purpose computer system environments or configurations.

[0079] Examples include: personal computers, server computers, handheld or portable devices, tablet devices, multiprocessor systems, microprocessor-based systems, set-top boxes, programmable consumer electronics, network PCs, minicomputers, mainframe computers, and distributed computing environments that include any of the above systems or devices.

[0080] This invention can be described in the general context of computer-executable instructions that are executed by a computer, such as program modules.

[0081] Generally, program modules include routines, programs, objects, components, data structures, etc., that perform specific tasks or implement specific abstract data types. This invention can also be practiced in distributed computing environments where tasks are performed by remote processing devices connected via communication networks.

[0082] In a distributed computing environment, program modules can reside on local and remote computer storage media, including storage devices.

[0083] Specifically, those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by instructing related hardware through computer-readable instructions. These computer-readable instructions can be stored in a computer-readable storage medium. When the program is executed, it can include the processes of the embodiments of the above methods. The aforementioned storage medium can be a non-volatile storage medium such as a magnetic disk, optical disk, or read-only memory (ROM), or random access memory (RAM).

[0084] It should be understood that although the steps in the flowcharts in the accompanying drawings are shown sequentially as indicated by the arrows, these steps are not necessarily performed in the order indicated by the arrows. Unless otherwise expressly stated herein, there is no strict order in which these steps are performed, and they may be performed in other orders.

[0085] Moreover, at least some steps in the flowchart of the attached figure may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. Their execution order is not necessarily sequential, but can be executed in turn or alternately with other steps or at least some of the sub-steps or stages of other steps.

[0086] Obviously, the embodiments described above are only some embodiments of the present invention, and not all embodiments. The accompanying drawings show preferred embodiments of the present invention, but do not limit the scope of the invention. The present invention can be implemented in many different forms; rather, these embodiments are provided to provide a thorough and complete understanding of the disclosure of the present invention.

[0087] Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing specific embodiments or make equivalent substitutions for some of the technical features. Any equivalent structures made using the content of this specification and drawings, whether directly or indirectly applied to other related technical fields, are similarly within the scope of protection of this patent.

Claims

1. A control method for a solar-powered video surveillance device, characterized in that, Includes the following steps: S1. Acquire energy storage data and environmental data from solar-powered video surveillance equipment; S2. Based on the energy storage data and the environmental data, determine the predicted power ratio of the device during a preset period, wherein the predicted power ratio is the ratio of the remaining power of the device to its rated capacity during the preset period; S3. Generate device adjustment instructions based on the predicted power ratio; S4. Adjust the load parameters of the device according to the device adjustment instruction.

2. The control method for a solar-powered video surveillance device according to claim 1, characterized in that, The energy storage data includes the device's current battery percentage and battery discharge rate, and the environmental data includes light intensity and weather conditions. Determining the predicted battery percentage of the device within a preset time period based on the energy storage data and the environmental data includes the following steps: S21. Preprocess the light intensity and the weather condition respectively to obtain the average light intensity and the weather correction coefficient; S22. Based on the average light intensity and the weather correction coefficient, determine the predicted power generation of the device during the preset time period; S23. Based on the current power ratio, the battery discharge rate, and the predicted power generation, determine the predicted power ratio of the device during the preset time period.

3. The control method for a solar-powered video surveillance device according to claim 2, characterized in that, After determining the predicted power ratio of the device during the preset time period based on the current power ratio, the battery discharge rate, and the predicted power generation, the process includes: S24. Acquire device status data, wherein the device status data includes the device's detection alarm status and the real-time power consumption of the load in the device; When the detection alarm state of the device is triggered and the real-time power consumption of the load in the device increases, the battery discharge rate is corrected.

4. The control method for a solar-powered video surveillance device according to claim 2, characterized in that, The step of generating device adjustment instructions based on the predicted power ratio includes the following steps: S31. Generate a corresponding basic adjustment instruction based on the threshold range to which the predicted power ratio belongs; S32. Based on the detection alarm status of the device, the basic adjustment command is adjusted for the first time to generate a first adjustment command; S33. Based on the predicted power generation trend, the first adjustment instruction is adjusted a second time to generate a second adjustment instruction; S34. Generate the device adjustment instruction based on the second adjustment instruction.

5. The control method for a solar-powered video surveillance device according to claim 4, characterized in that, The step of generating the device adjustment instruction based on the second adjustment instruction includes the following steps: S341. Obtain the load type, adjustment method, adjustment time node, and adjustment magnitude of the device corresponding to the second adjustment instruction; S342. Based on the load type, adjustment method, adjustment time node, and adjustment magnitude, generate the device adjustment command that can be executed by the device.

6. The control method for a solar-powered video surveillance device according to claim 1, characterized in that, The adjustment instructions include maintenance instructions, power reduction instructions, load limiting instructions, and alarm priority instructions; The step of adjusting the load parameters of the device according to the device adjustment command includes: When the adjustment command is the maintenance command, the device's fill light is controlled to maintain the original high-brightness constant-on mode, the video module maintains high-quality operating parameters, and the zoom motor maintains high-frequency automatic adjustment parameters. When the adjustment command is the power reduction command, the device's fill light is controlled to reduce its brightness to the basic lighting level, the video module is switched to medium quality operating parameters, and the zoom motor extends the automatic adjustment interval. When the adjustment command is a load limiting command, the supplementary light of the device is adjusted to only be triggered by the detection alarm, the video module is switched to low quality operating parameters, and the zoom motor's automatic adjustment function is turned off. When the adjustment command is an alarm priority command, the device's fill light is forced to turn on high brightness mode, the video module maintains basic high-quality operating parameters, and the zoom motor resumes intermediate frequency automatic adjustment parameters.

7. A control system for a solar-powered video surveillance device, used to execute the control method for the solar-powered video surveillance device according to any one of claims 1 to 6, characterized in that, include: The data acquisition module is used to acquire energy storage data and environmental data from the solar-powered video surveillance equipment. The power prediction module is used to determine the predicted power ratio of the device in a preset period based on the energy storage data and the environmental data. The predicted power ratio is the ratio of the remaining power of the device in the preset period to its rated capacity. The instruction generation module is used to generate device adjustment instructions based on the predicted power ratio; The load adjustment module is used to adjust the load parameters of the device according to the device adjustment command.

Images