A remaining power-based end-side intelligent analysis degradation method and system, electronic device and storage medium

Abstract

The application discloses an end-side intelligent analysis degradation method and system based on residual power, electronic equipment and a storage medium, and relates to the technical field of energy consumption management. The method comprises the following steps: S10, collecting the residual power proportion, charging current and current weather information of an end-side device; S20, calculating the residual power, weather energy supplement expectation and power tension degree of the end-side device; S30, determining a candidate degradation gear through a preset mapping rule; S40, adjusting the current actual gear according to a preset rule based on the comparison result of the candidate degradation gear and the current actual gear; S50, configuring the energy consumption parameters of the end-side device according to the adjusted current actual gear, and determining the data back transmission mode based on whether a key event occurs in the intelligent analysis task currently executed by the end-side device; and S60, judging whether the residual power of the end-side device is lower than a protection threshold value, and if yes, executing hardware protection power-off, and if not, returning to S10. The application has the beneficial effect of guaranteeing the effective endurance time of a key task.

Description

Technical Field

[0001] This invention relates to the field of energy management technology, and more specifically, to an edge-side intelligent analysis and degradation method, system, electronic device, and storage medium based on remaining power. Background Technology

[0002] Currently, edge devices powered by solar energy and / or batteries are widely used in outdoor monitoring scenarios. These devices typically need to run multiple intelligent analysis tasks in parallel. However, existing technologies have the following drawbacks in terms of power management: The current approach to power degradation decisions relies on a single criterion and fails to consider weather-related factors: When making degradation decisions, existing solutions typically rely solely on the remaining power percentage, neglecting the impact of current weather conditions on anticipated future power replenishment. For example, during cloudy or rainy weather, equipment struggles to effectively replenish its power via solar energy, but existing solutions cannot anticipate this situation and implement more proactive energy-saving measures, leading to premature power depletion during subsequent periods of darkness.

[0003] The downgrade strategy lacks a dynamic adjustment mechanism: existing solutions usually adopt a fixed downgrade mode or a simple threshold judgment. They cannot dynamically determine the candidate downgrade level through mapping rules based on multi-dimensional information such as remaining power, expected weather-based power replenishment, and power shortage. They also cannot flexibly adjust the actual level according to preset rules based on the comparison results between the candidate downgrade level and the current actual level, resulting in poor adaptability of the downgrade strategy.

[0004] Energy consumption parameters and data transmission methods are disconnected and not optimized in tandem: When adjusting energy consumption parameters (such as resolution, computing power, and reporting cycle), the existing solution does not coordinate with the data transmission method for critical events. For example, it continues to transmit large amounts of data in the conventional way when the battery is low, resulting in unnecessary energy waste and failing to maximize device battery life while ensuring priority transmission of critical events.

[0005] To address this, the present invention provides an edge-side intelligent analysis degradation method, system, electronic device, and storage medium based on remaining power, which can solve the technical problems existing in the prior art, such as a single degradation decision basis, a lack of dynamic adjustment mechanism for degradation strategies, and a disconnect between energy consumption parameters and data feedback methods, thereby ensuring the effective battery life for critical tasks. Summary of the Invention

[0006] To overcome the shortcomings of existing technologies, this invention provides an edge-side intelligent analysis degradation method, system, electronic device, and storage medium based on remaining power. This invention can solve the technical problems existing in the prior art, such as the single degradation decision basis, the lack of dynamic adjustment mechanism for degradation strategies, and the separation of energy consumption parameters and data feedback methods, thereby ensuring the effective battery life of critical tasks.

[0007] The technical solution adopted by this invention to solve its technical problem is: an end-side intelligent analysis and degradation method based on remaining power, applied to end-side devices powered by solar energy and / or batteries, wherein the end-side devices run multiple intelligent analysis tasks in parallel, and the improvement is that the end-side intelligent analysis and degradation method based on remaining power includes the following steps: S10 collects the remaining battery percentage, charging current, and current weather information of the terminal device; S20, calculate the remaining power of the terminal device, weather-based power replenishment expectations, and power shortage level based on the remaining power ratio and current weather information; wherein, the expression for calculating the remaining power is: ; In the formula, Indicates the remaining power of the terminal device; Indicates the nominal battery capacity of the end-side device; Indicates the battery discharge coefficient of the end-side device; The calculation expression for the expected weather-based energy replenishment is as follows: ; In the formula, This indicates an expectation of weather-related energy replenishment. Indicates the photovoltaic conversion efficiency; This indicates the reduction factor corresponding to the current weather information; Indicates the current photovoltaic power; This indicates the predicted time window for photovoltaic power replenishment; The formula for calculating the electricity shortage level is: ; In the formula, This represents the average power consumption when operating at full load. Indicates the target battery life; This represents a small positive number to avoid division by zero; S30, based on the remaining battery power, current weather information, and battery availability, determine candidate downgrade levels using a preset mapping rule; wherein, the specific method for determining candidate downgrade levels using the preset mapping rule is as follows: The current relegation score is calculated using a relegation score function, and then mapped to the relegation level based on this score. The expression for the relegation score function is as follows: In the formula, Indicates the current relegation score; This represents the quantified severity value of the current score; , as well as All represent the weighting coefficients for the downgrade; Alternatively, you can obtain the number of candidate downgrade levels by querying the preset power consumption-weather mapping table; S40, based on the comparison results between the candidate downgrade gear and the current actual gear, adjust the current actual gear according to preset rules; S50 configures the energy consumption parameters of the end-side device according to the adjusted current actual gear position, and determines the data feedback method based on whether a critical event occurs in the intelligent analysis task currently being executed by the end-side device. S60: Determine whether the remaining power of the terminal device is lower than the protection threshold. If yes, execute hardware protection power-down. If no, return to S10.

[0008] Furthermore, in step S40, the specific method for adjusting the current actual gear according to preset rules based on the comparison result between the candidate downgrade gear and the current actual gear is as follows: If the value of the candidate downgrade is greater than the current actual gear, then the downgrade operation is performed, and the current actual gear is updated to the candidate downgrade. If the value of the candidate downgrade gear is less than the current actual gear, it is determined whether a preset upgrade condition is met. If met, an upgrade operation is performed, raising the current actual gear by one gear. If not met, the current actual gear is maintained. The preset upgrade condition includes: The charging current is not less than the preset minimum charging current threshold; The remaining power is not less than the upper threshold value corresponding to the current actual gear level; And the duration of the above two conditions remaining stable reaches the preset hysteresis stability duration; If the value of the candidate downgrade is equal to the current actual gear, then the current actual gear will be maintained.

[0009] Furthermore, in step S50, the specific method for determining the data feedback method based on whether a critical event has occurred in the intelligent analysis task currently being executed by the end-side device is as follows: When a critical event occurs, the critical event will be encapsulated into a short video and sent back with priority. When no critical events occur, local caching is performed or heartbeat reporting is executed according to the reporting cycle corresponding to the current actual gear position.

[0010] An end-side intelligent analysis and degradation system based on remaining power capacity, characterized by the following improvements: The sensing unit is used to collect data on the remaining battery percentage, charging current, and current weather information of the terminal device. The energy calculation unit is used to calculate the remaining power of the terminal device, the expected weather-based power replenishment, and the power shortage based on the remaining power ratio and current weather information. The mapping engine is used to determine candidate downgrade levels based on the remaining battery power, current weather information, and battery availability, according to preset mapping rules. The gear adjustment unit is used to adjust the current actual gear according to preset rules based on the comparison results between the candidate downgraded gear and the current actual gear. The execution unit is used to configure the energy consumption parameters of the end-side device according to the adjusted current actual gear, and to determine the data feedback method based on whether a critical event has occurred in the intelligent analysis task currently being executed by the end-side device. The protection unit is used to determine whether the remaining power of the terminal device is lower than the protection threshold. If so, it performs hardware protection power-down; otherwise, it triggers the sensing unit to re-collect data.

[0011] An electronic device, improved in that it includes at least one processor and at least one memory, wherein, The memory stores computer-readable instructions; The computer-readable instructions are executed by one or more processors, enabling the electronic device to implement the edge-side intelligent analysis and degradation method based on remaining power as described above.

[0012] An improvement of a storage medium having computer-readable instructions stored thereon, wherein the computer-readable instructions are executed by one or more processors to implement the end-side intelligent analysis degradation method based on remaining power as described above.

[0013] The beneficial effects of this invention are as follows: First, by collecting the remaining battery percentage, charging current, and current weather information, and calculating weather-based energy replenishment expectations and battery tension based on the remaining battery percentage and current weather information, this invention incorporates weather-based energy replenishment factors into the downgrade decision-making process, solving the problem of a single basis for downgrade decision-making. Second, based on the remaining battery, current weather information, and battery tension, candidate downgrade levels are dynamically determined through preset mapping rules, and the actual downgrade level is adjusted according to preset rules based on the comparison results between the candidate downgrade levels and the current actual level, realizing multi-dimensional information-driven dynamic downgrade adjustment and solving the problem of a lack of dynamic adjustment mechanism in downgrade strategies. Finally, by configuring energy consumption parameters and determining the data feedback method based on the occurrence of critical events, this invention coordinates the configuration of energy consumption parameter adjustments and data feedback strategies, prioritizing the effective feedback of critical events in low battery conditions, thus solving the problem of the separation between energy consumption parameters and data feedback methods. Therefore, this invention can solve the technical problems of single downgrade decision-making basis, lack of dynamic adjustment mechanism in downgrade strategies, and separation between energy consumption parameters and data feedback methods in the prior art, thereby ensuring the effective endurance time for critical tasks. Attached Figure Description

[0014] Figure 1 This is an overall flowchart of an end-side intelligent analysis and degradation method based on remaining power according to the present invention. Figure 2This is a block diagram of an end-side intelligent analysis and degradation system based on remaining power according to the present invention. Figure 3 This is a hardware structure diagram of an electronic device as an example embodiment; Figure 4 This is a block diagram illustrating an electronic device as an example embodiment. Detailed Implementation

[0015] The present invention will be further described below with reference to the accompanying drawings and embodiments.

[0016] The following will clearly and completely describe the concept, specific structure, and technical effects of the present invention in conjunction with embodiments and accompanying drawings, so as to fully understand the purpose, features, and effects of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, not all of them. Other embodiments obtained by those skilled in the art based on the embodiments of the present invention without creative effort are all within the scope of protection of the present invention. Furthermore, all connections / linkages involved in the patent do not simply refer to direct contact between components, but rather to the ability to form a better connection structure by adding or reducing connecting accessories according to specific implementation conditions. The various technical features in this invention can be combined interactively without contradicting each other.

[0017] Reference Figure 1 As shown, this invention discloses an end-side intelligent analysis degradation method based on remaining power, applied to end-side devices powered by solar energy and / or batteries. The end-side device runs multiple intelligent analysis tasks in parallel, wherein the intelligent analysis tasks are divided into three priority levels according to importance and urgency: T0 (Critical Alarm Class): Highest priority, including tasks involving security or emergency alarms such as perimeter intrusion detection, personnel fall detection, and smoke / fire detection. These tasks must remain enabled in all priority levels and must not be disabled due to downgrading.

[0018] T1 (General Events): Medium priority, including non-urgent but valuable monitoring tasks such as vehicle parking violation detection, crowd gathering warnings, and item abandonment detection. Can be selectively disabled in mild downgrade and above.

[0019] T2 (Non-critical): Lowest priority, including auxiliary or non-real-time tasks such as passenger flow statistics, license plate recognition, gimbal patrol, and full-time video recording. It is first disabled in slightly downgraded and higher priority levels to save power.

[0020] The end-side intelligent analysis and degradation method based on remaining power includes the following steps: S10 collects the remaining battery percentage, charging current, and current weather information of the terminal device; It should be noted that in this embodiment, the end-side device is a device powered by solar energy and / or a battery, such as an outdoor green power pan-tilt unit, a temporary battery-powered device, or a forest battery-powered sphere device. The remaining power percentage is read in real time by the Battery Management System (BMS), and the unit is percentage (0~1). The charging current is collected by a current sensor, and the unit is milliampere (mA). The current weather information is obtained through photovoltaic power sampling or a network weather API and quantified into three levels: W0 (sunny, energy can be replenished), W1 (cloudy, weak energy replenishment), and W2 (overcast or continuous no sunlight), with corresponding severity quantification values ​​w of 0, 1, and 2, respectively. The system performs a data collection operation at a fixed period (e.g., every 30 seconds) to ensure the timeliness of the data.

[0021] S20 calculates the remaining power of the terminal device, weather-based power replenishment expectations, and power shortage based on the remaining power ratio and current weather information; It should be noted that, in this embodiment, the expression for calculating the remaining power is: ; In the formula, Indicates the remaining power of the terminal device; Indicates the nominal battery capacity of the end-side device; This represents the battery discharge coefficient of the end-side device, with a value ranging from 0.85 to 0.95. It is used to characterize the proportion of energy that the battery of the end-side device can actually release.

[0022] The calculation expression for the expected weather-based energy replenishment is as follows: ; In the formula, This indicates an expectation of weather-related energy replenishment. Indicates the photovoltaic conversion efficiency; This indicates the reduction factor corresponding to the current weather information; Indicates the current photovoltaic power; This indicates the predicted time window for photovoltaic power replenishment, with a value ranging from 4 to 12 hours. Furthermore, the expression for calculating the power shortage is as follows: ; In the formula, This represents the average power consumption when operating at full load. Indicates the target battery life; This represents a small positive number to avoid division by zero (e.g., 0.01). When When this occurs, it indicates that the system cannot operate at full capacity for the target duration and needs to be downgraded.

[0023] S30 determines candidate downgrade levels based on remaining battery power, current weather information, and battery availability using preset mapping rules; It should be noted that, in this embodiment, the determination of candidate downgrade profiles through preset mapping rules includes two implementation methods, and one can be chosen for use in actual applications: Method 1: Calculate the current relegation score using the relegation score function, and then map it to the relegation level. The expression for the relegation score function is: In the formula, Indicates the current relegation score; This represents the quantified severity value of the current score (W0 corresponds to 0, W1 corresponds to 1, and W2 corresponds to 2). , as well as All represent the downgrade weighting coefficients. In this embodiment, , as well as The values ​​are: 1.6, 0.5, 0.7; the calculation expression for the candidate downgrade level is: The value is rounded to the nearest whole number and is limited to 0-3. The larger the value, the deeper the downgrade. These values ​​correspond to four different levels: L0, L1, L2, and L3. L0 represents the full load level, L1 represents the slight downgrade level, L2 represents the severe downgrade level, and L3 represents the minimum downgrade level.

[0024] Method 2: Obtain candidate downgrade levels by querying a preset power consumption-weather mapping table. An example mapping table is shown below:

[0025] In W2 weather conditions, even if the SOC is still above 60%, it should at least enter L1, prematurely closing T2 to reserve energy for potentially longer periods of darkness later; in W2 weather conditions, if the SOC falls to 8%~15%, it should enter L3 to ensure the T0 channel is maintained. Optionally, if Exceeding the preset high tension threshold (If the value is 1.2-1.8), then add one level to the above mapping result, but not exceeding the highest level L3.

[0026] S40, based on the comparison results between the candidate downgrade gear and the current actual gear, adjust the current actual gear according to preset rules; It should be noted that in this embodiment, the current actual gear L is also one of the four levels from L0 to L3, consistent with the value range of the candidate downgrade gear. The preset rule is as follows: if the value of the candidate downgrade gear is greater than the current actual gear, a downgrade operation is immediately performed, updating the current actual gear to the candidate downgrade gear; if the value of the candidate downgrade gear is less than the current actual gear, it is determined whether the preset upgrade condition is met. If it is met, an upgrade operation is performed, raising the current actual gear by one gear; if it is not met, the current actual gear is maintained; if the value of the candidate downgrade gear is equal to the current actual gear, the current actual gear is maintained.

[0027] Downshifting takes effect immediately, without waiting for any additional conditions, ensuring that the device can quickly enter low-power mode when the battery is rapidly depleting or the weather suddenly worsens, preventing the battery from running out due to lag. Upshifting, on the other hand, requires the following three conditions to be met simultaneously, and can only be performed one level at a time; skipping levels is not allowed: Condition 1: The charging current is not less than the preset minimum charging current threshold.

[0028] This condition is used to confirm that the device is currently in a true charging state, rather than a misjudgment caused by SOC sampling fluctuations. When the photovoltaic panel is shaded, briefly obscured by clouds, or the device is in shadow, the charging current may momentarily drop to zero or negative. In this case, even if the SOC reading recovers, the charging speed should not be increased.

[0029] Condition 2: The remaining battery power is not less than the upper threshold value corresponding to the current actual power level.

[0030] This condition is used to prevent frequent upgrades and downgrades when the SOC fluctuates slightly around the threshold. There is a hysteresis bandwidth between the upper threshold for recovery and the lower threshold for entering this level. The value of the hysteresis bandwidth can be adjusted according to the ambient light fluctuations and the power consumption characteristics of the device. The larger the hysteresis bandwidth, the stronger the anti-jitter capability, but the longer the recovery time. Conversely, the smaller the hysteresis bandwidth, the more sensitive the recovery, but the more prone it is to oscillations when the lighting is unstable.

[0031] Condition 3: The duration of the above two conditions remaining stable reaches the preset hysteresis stability duration.

[0032] This condition is used to exclude instantaneous SOC spikes caused by brief periods of sunlight (such as light filtering through clouds or intermittent sunlight due to swaying leaves). On cloudy or overcast days, photovoltaic power output may fluctuate frequently, and the SOC may rise briefly before quickly falling back. If an upgrade is performed based solely on this instantaneous condition, the device may repeatedly upgrade and downgrade within minutes, not only increasing power consumption but also causing alarm fluctuations and impacting user experience.

[0033] By combining the above three conditions, a hysteresis control strategy is achieved that enables immediate downshifting, slow upshifting, and gradual gear recovery, effectively avoiding repeated upshifting and downshifting caused by weather fluctuations.

[0034] S50 configures the energy consumption parameters of the end-side device according to the adjusted current actual gear position, and determines the data feedback method based on whether a critical event occurs in the intelligent analysis task currently being executed by the end-side device. It should be noted that, in this embodiment, the energy consumption parameters include at least one of resolution, computing frequency, and reporting cycle.

[0035] The specific method for determining the data feedback method based on whether a critical event has occurred in the intelligent analysis task currently being executed by the edge device is as follows: When a critical event (T0 event) occurs in the intelligent analysis task currently being executed by the edge device, the system executes a differentiated feedback strategy based on the current actual gear position: If the current actual threshold reaches or exceeds the preset short video trigger threshold (e.g., L≥2): the device is in a moderate or deep degradation state, with bandwidth and power consumption strictly limited. The system will encapsulate key events as short videos for priority transmission back, rather than uploading complete long-duration recordings or high-definition streams.

[0036] If the current actual power level has not reached the short video trigger level (i.e., L<2, in L0 or L1 state): At this time, the device has sufficient power or is slightly downgraded, and the bandwidth and power consumption are relatively sufficient. The system uploads the key event in the normal bitstream mode, that is, uploads the complete high-definition alarm recording, so that the backend platform can perform detailed analysis and evidence collection.

[0037] When a general event (T1 event) occurs in the intelligent analysis task currently being executed by the edge device, the system also executes a differentiated processing strategy based on the current actual gear position: If the current actual power level reaches or exceeds the preset local cache trigger level (e.g., L≥2): the device is in a moderate or deep degradation state and should not consume additional power for real-time uploading. The system will temporarily store the relevant data of the T1 event (such as captured images and event logs) in the local storage medium, and will re-upload it after the device upgrades or the photovoltaic power replenishment returns to normal.

[0038] If the current actual gear position has not reached the locally cached trigger gear position: the system will upload the T1 event to the cloud in real time in the usual way.

[0039] When no critical or general events occur during the intelligent analysis task currently being performed by the edge device, the system performs heartbeat reporting according to the reporting cycle corresponding to the current actual gear level. This means periodically sending device status information (such as SOC, current gear level, temperature, etc.) to the cloud to maintain the device's online status. The amount of data reported by the heartbeat is extremely small, and the power consumption is negligible.

[0040] By employing the aforementioned differentiated data backhaul strategy, the effective backhaul of critical alarm events is prioritized under low power conditions, while the transmission of non-urgent data is delayed, thereby minimizing communication and encoding power consumption and extending the effective battery life of the device.

[0041] S60: Determine whether the remaining power of the terminal device is lower than the protection threshold. If yes, execute hardware protection power-down. If no, return to S10.

[0042] It should be noted that, in this embodiment, the protection threshold is a hardware protection power-off threshold. When the remaining battery power is lower than this threshold, hardware protection power-off is executed to avoid permanent damage caused by over-discharge of the battery. When the remaining battery power is not lower than this threshold, the process returns to S10 to continue the next round of loop detection.

[0043] Reference Figure 2 As shown, the present invention also discloses an end-side intelligent analysis and degradation system 600 based on remaining power, comprising: The sensing unit 601 is used to collect the remaining power percentage, charging current and current weather information of the end-side device; The energy calculation unit 602 is used to calculate the remaining power of the terminal device, the expected weather-based power replenishment, and the power shortage based on the remaining power ratio and current weather information. The mapping engine 603 is used to determine candidate downgrade levels based on the remaining battery power, current weather information, and battery availability, using preset mapping rules. The gear adjustment unit 604 is used to adjust the current actual gear according to preset rules based on the comparison results between the candidate downgraded gear and the current actual gear. The execution unit 605 is used to configure the energy consumption parameters of the end-side device according to the adjusted current actual gear, and to determine the data feedback method based on whether a critical event occurs in the intelligent analysis task currently being executed by the end-side device. The protection unit 606 is used to determine whether the remaining power of the terminal device is lower than the protection threshold. If so, it performs hardware protection power-off; otherwise, it triggers the sensing unit to re-collect data.

[0044] It should be noted that the end-side intelligent analysis and degradation strategy based on remaining power provided in the above embodiments is only an example of the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed. That is, the internal structure of the end-side intelligent analysis and degradation system 600 based on remaining power will be divided into different functional modules to complete all or part of the functions described above. Furthermore, the end-side intelligent analysis and degradation system 600 based on remaining power provided in the above embodiments and the embodiment of the end-side intelligent analysis and degradation method based on remaining power belong to the same concept. The specific way each module performs its operation has been described in detail in the method embodiment, and will not be repeated here.

[0045] Figure 3 A schematic diagram of the structure of an electronic device according to an exemplary embodiment is shown.

[0046] It should be noted that this electronic device is merely an example adapted to the present invention and should not be construed as providing any limitation on the scope of use of the present invention. Furthermore, this electronic device should not be interpreted as requiring or depending on having... Figure 3 One or more components of the exemplary electronic device 2000 shown.

[0047] The hardware structure of electronic devices 2000 can vary significantly due to differences in configuration or performance, such as... Figure 3 As shown, the electronic device 2000 includes: a power supply 210, an interface 230, at least one memory 250, and at least one central processing unit (CPU) 270.

[0048] Specifically, power supply 210 is used to provide operating voltage for various hardware devices on electronic device 2000.

[0049] Interface 230 includes at least one wired or wireless network interface 231 for interacting with external devices. Of course, in other examples adapted to this invention, interface 230 may further include at least one serial-to-parallel conversion interface 233, at least one input / output interface 235, and at least one USB interface 237, etc. Figure 3 As shown, this does not constitute a specific limitation.

[0050] The memory 250 serves as a carrier for resource storage and can be a read-only memory, random access memory, disk, or optical disk, etc. The resources stored on it include the operating system 251, application programs 253, and data 255, etc., and the storage method can be temporary storage or permanent storage.

[0051] The operating system 251 is used to manage and control the various hardware devices and application programs 253 on the electronic device 2000, so as to enable the central processing unit 270 to perform calculations and processing on the massive data 255 in the memory 250. It can be Windows Server™, Mac OS X™, Unix™, Linux™, FreeBSD™, etc.

[0052] Application 253 is a computer-readable instruction based on operating system 251 that performs at least one specific task, and may include at least one module ( Figure 3 (Not shown), each module may contain computer-readable instructions for the electronic device 2000. For example, an end-side intelligent analysis degradation device based on remaining power can be considered as application 253 deployed on the electronic device 2000.

[0053] Data 255 may be signal information, etc., and is stored in memory 250.

[0054] The central processing unit 270 may include one or more processors and is configured to communicate with the memory 250 via at least one communication bus to read computer-readable instructions stored in the memory 250, thereby enabling the computation and processing of massive amounts of data 255 in the memory 250. For example, the edge-side intelligent analysis and degradation method based on remaining power can be implemented by the central processing unit 270 reading a series of computer-readable instructions stored in the memory 250.

[0055] Furthermore, the present invention can also be implemented through hardware circuits or a combination of hardware circuits and software. Therefore, the implementation of the present invention is not limited to any specific hardware circuit, software, or combination thereof.

[0056] Please see Figure 4 This invention provides an electronic device 4000, which may include: a desktop computer, a laptop computer, a server, etc., with sensor recognition capabilities.

[0057] exist Figure 4 In this context, the electronic device 4000 includes at least one processor 4001 and at least one memory 4003.

[0058] The data interaction between the processor 4001 and the memory 4003 can be achieved through at least one communication bus 4002. This communication bus 4002 may include a path for transmitting data between the processor 4001 and the memory 4003. The communication bus 4002 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The communication bus 4002 can be divided into an address bus, a data bus, a control bus, etc. For ease of representation, Figure 4 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0059] Optionally, the electronic device 4000 may further include a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as sending and / or receiving data. It should be noted that in practical applications, the transceiver 4004 is not limited to one type, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present invention.

[0060] Processor 4001 may be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this invention. Processor 4001 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of a DSP and a microprocessor, etc.

[0061] The memory 4003 may be a ROM (Read Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or an EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program instructions or code in the form of instructions or data structures and accessible by the electronic device 4000, but not limited thereto.

[0062] The memory 4003 stores computer-readable instructions, and the processor 4001 can read the computer-readable instructions stored in the memory 4003 through the communication bus 4002.

[0063] The computer-readable instructions are executed by one or more processors 4001 to implement the end-side intelligent analysis and degradation method based on remaining power in the above embodiments.

[0064] Furthermore, this embodiment of the invention provides a storage medium storing computer-readable instructions, which are executed by one or more processors to implement the end-side intelligent analysis and degradation method based on remaining power as described above.

[0065] Compared with existing technologies, the beneficial effects of this invention are as follows: First, by collecting the remaining power ratio, charging current, and current weather information, and calculating weather-based energy replenishment expectations and power shortage based on the remaining power ratio and current weather information, weather-based energy replenishment factors are incorporated into the downgrade decision, solving the problem of a single basis for downgrade decision. Second, based on the remaining power, current weather information, and power shortage, candidate downgrade levels are dynamically determined through preset mapping rules, and the actual downgrade level is adjusted according to preset rules based on the comparison results between the candidate downgrade levels and the current actual level, realizing dynamic downgrade adjustment driven by multi-dimensional information, solving the problem of a lack of dynamic adjustment mechanism for downgrade strategies. Finally, by configuring energy consumption parameters and determining the data feedback method based on the occurrence of critical events, the energy consumption parameter adjustment and data feedback strategy are configured in a coordinated manner, prioritizing the effective feedback of critical events in low power conditions, solving the problem of the separation between energy consumption parameters and data feedback methods. Therefore, this invention can solve the technical problems of single downgrade decision basis, lack of dynamic adjustment mechanism for downgrade strategies, and separation between energy consumption parameters and data feedback methods in existing technologies, thereby ensuring the effective endurance of critical tasks.

[0066] The above is a detailed description of the preferred embodiments of the present invention. However, the present invention is not limited to the embodiments described. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of the present invention. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A method for intelligent analysis and degradation based on remaining power on the end side, applied to an end-side device powered by solar energy and / or a battery, wherein the end-side device runs multiple intelligent analysis tasks in parallel, characterized in that, The end-side intelligent analysis and degradation method based on remaining power includes the following steps: S10 collects the remaining battery percentage, charging current, and current weather information of the terminal device; S20, calculate the remaining power of the terminal device, weather-based power replenishment expectations, and power shortage level based on the remaining power ratio and current weather information; wherein, the expression for calculating the remaining power is: ; In the formula, Indicates the remaining power of the terminal device; Indicates the nominal battery capacity of the end-side device; Indicates the battery discharge coefficient of the end-side device; The calculation expression for the expected weather-based energy replenishment is as follows: ； In the formula, This indicates an expectation of weather-related energy replenishment. Indicates the photovoltaic conversion efficiency; This indicates the reduction factor corresponding to the current weather information; Indicates the current photovoltaic power; This indicates the predicted time window for photovoltaic power replenishment; The formula for calculating the electricity shortage level is: ； In the formula, This represents the average power consumption when operating at full load. Indicates the target battery life; This represents a small positive number to avoid division by zero; S30, based on the remaining battery power, current weather information, and battery availability, determine candidate downgrade levels using a preset mapping rule; wherein, the specific method for determining candidate downgrade levels using the preset mapping rule is as follows: The current relegation score is calculated using a relegation score function, and then mapped to the relegation level based on this score. The expression for the relegation score function is as follows: In the formula, Indicates the current relegation score; This represents the quantified severity value of the current score; , as well as All represent the weighting coefficients for the downgrade; Alternatively, you can obtain the number of candidate downgrade levels by querying the preset power consumption-weather mapping table; S40, based on the comparison results between the candidate downgrade gear and the current actual gear, adjust the current actual gear according to preset rules; S50 configures the energy consumption parameters of the end-side device according to the adjusted current actual gear position, and determines the data feedback method based on whether a critical event occurs in the intelligent analysis task currently being executed by the end-side device. S60: Determine whether the remaining power of the terminal device is lower than the protection threshold. If yes, execute hardware protection power-down. If no, return to S10.

2. The end-side intelligent analysis and degradation method based on remaining power as described in claim 1, characterized in that, In step S40, the specific method for adjusting the current actual gear according to preset rules based on the comparison result between the candidate downgrade gear and the current actual gear is as follows: If the value of the candidate downgrade is greater than the current actual gear, then the downgrade operation is performed, and the current actual gear is updated to the candidate downgrade. If the value of the candidate downgrade gear is less than the current actual gear, it is determined whether a preset upgrade condition is met. If met, an upgrade operation is performed, raising the current actual gear by one gear. If not met, the current actual gear is maintained. The preset upgrade condition includes: The charging current is not less than the preset minimum charging current threshold; The remaining power is not less than the upper threshold value corresponding to the current actual gear level; And the duration of the above two conditions remaining stable reaches the preset hysteresis stability duration; If the value of the candidate downgrade is equal to the current actual gear, then the current actual gear will be maintained.

3. The end-side intelligent analysis and degradation method based on remaining power as described in claim 1, characterized in that, In step S50, the specific method for determining the data feedback method based on whether a critical event has occurred in the intelligent analysis task currently being executed by the end device is as follows: When a critical event occurs, the critical event will be encapsulated into a short video and sent back with priority. When no critical events occur, local caching is performed or heartbeat reporting is executed according to the reporting cycle corresponding to the current actual gear position.

4. An end-side intelligent analysis and degradation system based on remaining power capacity, characterized in that, include: The sensing unit is used to collect data on the remaining battery percentage, charging current, and current weather information of the terminal device. The energy calculation unit is used to calculate the remaining power of the terminal device, the expected weather-based power replenishment, and the power shortage based on the remaining power ratio and current weather information. The mapping engine is used to determine candidate downgrade levels based on the remaining battery power, current weather information, and battery availability, according to preset mapping rules. The gear adjustment unit is used to adjust the current actual gear according to preset rules based on the comparison results between the candidate downgraded gear and the current actual gear. The execution unit is used to configure the energy consumption parameters of the end-side device according to the adjusted current actual gear, and to determine the data feedback method based on whether a critical event has occurred in the intelligent analysis task currently being executed by the end-side device. The protection unit is used to determine whether the remaining power of the terminal device is lower than the protection threshold. If so, it performs hardware protection power-down; otherwise, it triggers the sensing unit to re-collect data.

5. An electronic device, characterized in that, Includes at least one processor and at least one memory, wherein, The memory stores computer-readable instructions; The computer-readable instructions are executed by one or more processors, causing the electronic device to implement the end-side intelligent analysis and degradation method based on remaining power as described in any one of claims 1-3.

6. A storage medium having computer-readable instructions stored thereon, characterized in that, The computer-readable instructions are executed by one or more processors to implement the end-side intelligent analysis and degradation method based on remaining power as described in any one of claims 1-3.

Images