Multi-sensor temperature data sampling method and device, electronic equipment and medium

Abstract

The invention relates to the technical field of multi-sensor temperature data sampling, and discloses a multi-sensor temperature data sampling method and device, electronic equipment and a medium, and the method comprises the steps: obtaining a first sampling strategy, and sampling the first temperature data of each temperature sensor through the first sampling strategy; detecting whether each first temperature data is greater than a temperature threshold set by the corresponding temperature sensor in real time; marking the temperature sensor of which the first temperature data is greater than a corresponding temperature threshold as a target temperature sensor; setting a corresponding second sampling frequency according to the first temperature data of the target temperature sensor; updating the first sampling strategy based on the target temperature sensor and the corresponding second sampling frequency to obtain a second sampling strategy; and continuously sampling second temperature data of each temperature sensor through a second sampling strategy. The beneficial effects of the invention are that unification of resource optimization and monitoring precision is realized, and reliable guarantee is provided for accurate temperature control in the food processing process.

Description

Technical Field

[0001] This invention relates to the field of multi-sensor temperature data sampling technology, and in particular to a multi-sensor temperature data sampling method, apparatus, electronic device, and medium. Background Technology

[0002] In the food processing process, real-time and accurate multi-point temperature monitoring is crucial to ensuring production safety, product quality, and stable equipment operation. Currently, a bus-based multi-sensor temperature acquisition system has been integrated to synthesize temperature data measured by various temperature sensors.

[0003] However, existing technologies generally employ a fixed-frequency polling sampling strategy. This uniform approach collects all data at a fixed cycle regardless of temperature changes at each monitoring point, resulting in a large amount of redundant data during the temperature stabilization phase. This leads to a significant waste of communication bandwidth, main control unit computing resources, and system power consumption. Furthermore, this approach cannot provide more refined data when local temperatures exceed thresholds, making it difficult to balance monitoring efficiency with resource consumption. Therefore, improving system resource utilization and achieving rapid response to abnormal temperatures has become a pressing technical problem in this field. Summary of the Invention

[0004] Based on this, it is necessary to address the existing problem of multi-sensor temperature data sampling and propose a multi-sensor temperature data sampling method, device, electronic equipment, and medium.

[0005] A multi-sensor temperature data sampling method is implemented through a sensor sampling system, the sensor sampling system including a bus and temperature sensors connected to the bus, the method comprising: A first sampling strategy is obtained, and first temperature data of each temperature sensor is sampled using the first sampling strategy; wherein, the first sampling strategy includes a first sampling frequency corresponding to each temperature sensor; Real-time detection of whether each of the first temperature data is greater than the temperature threshold set by the corresponding temperature sensor; The temperature sensor whose first temperature data is greater than the corresponding temperature threshold is marked as the target temperature sensor; A second sampling frequency is set according to the first temperature data from the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency; The first sampling strategy is updated based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy; The second sampling strategy is used to continue sampling the second temperature data of each temperature sensor.

[0006] Furthermore, after the step of continuing to sample the second temperature data of each temperature sensor using the second sampling strategy, the method further includes: The temperature change is obtained by performing a differential calculation on the first temperature data sampled by the first sampling strategy and the second temperature data sampled by the second sampling strategy. The temperature change, the first temperature data, and the second temperature data are aggregated to obtain an aggregated data package; The data packet is sent to a designated terminal via a preset wireless communication device.

[0007] Further, the step of continuing to sample the second temperature data of each temperature sensor using the second sampling strategy includes: Obtain the target sampling frequency with the highest frequency among all temperature sensors in the second sampling strategy, and set the total communication cycle according to the target frequency; The total communication cycle is divided into a corresponding number of communication time periods according to the number of temperature sensors; The communication time period is allocated to the corresponding temperature sensor as an exclusive communication window between the temperature sensor and the bus. Second temperature data from each temperature sensor is sampled during each total communication cycle.

[0008] Furthermore, prior to the step of sampling the second temperature data of each temperature sensor within each total communication cycle, the method further includes: Calculate the difference between the first temperature data of the target temperature sensor and the corresponding temperature threshold; The priority of the target temperature sensor is calculated based on the difference. The sampling order of each temperature sensor within the total communication cycle is adjusted according to the priority.

[0009] Furthermore, before the step of setting the corresponding second sampling frequency based on the first temperature data from the target temperature sensor, the method further includes: The sensor sampling system acquires multiple first datasets and multiple second datasets; wherein the first datasets do not contain temperature data greater than the corresponding temperature threshold, and the second datasets contain temperature data greater than the corresponding temperature threshold. The index data for each temperature sensor is determined based on multiple first datasets, thus obtaining the index dataset; Calculate the difference between each temperature data in each second dataset and the corresponding index data in the index dataset to obtain the third dataset corresponding to each second dataset; Calculate the correlation coefficients between any two data points in the third dataset; Data pairs with a correlation coefficient greater than a preset correlation coefficient are marked as collaborative data; Based on the labeling results, all temperature sensors are clustered to obtain multiple temperature sensor clusters; wherein, the sampling frequency is the same in each temperature sensor cluster.

[0010] Further, the step of updating the first sampling strategy based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy includes: Obtain the target temperature sensor cluster in which the target temperature sensor is located; Set the sampling frequency of all temperature sensors in the target temperature sensor cluster to the second sampling frequency; The first sampling strategy is updated by updating the temperature sensors in the target temperature sensor cluster and their corresponding second sampling frequencies to obtain the second sampling strategy.

[0011] Further, the step of continuing to sample the second temperature data of each temperature sensor using the second sampling strategy includes: Real-time monitoring of the voltage levels of the bus's data and clock lines during the sampling process; When the level of the data line and / or the clock line is detected to be lower than the preset abnormal low level value and the duration exceeds the preset time threshold, the currently sampled second temperature data is recorded as the target second temperature data, and the number of abnormalities of the target second temperature data is recorded. A retransmission delay time is set for the target second temperature data based on the number of anomalies, and the time point for resampling the target second temperature data is set according to the retransmission delay time.

[0012] A multi-sensor temperature data sampling device is implemented through a sensor sampling system, the sensor sampling system including a bus and a temperature sensor connected to the bus, the device comprising: An acquisition module is used to acquire a first sampling strategy and sample the first temperature data of each temperature sensor using the first sampling strategy; wherein, the first sampling strategy includes a first sampling frequency corresponding to each temperature sensor; The detection module is used to detect in real time whether each of the first temperature data is greater than the temperature threshold set by the corresponding temperature sensor; A marking module is used to mark a temperature sensor whose first temperature data is greater than the corresponding temperature threshold as a target temperature sensor. The setting module is used to set a corresponding second sampling frequency based on the first temperature data from the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency. The update module is used to update the first sampling strategy based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy; The sampling module is used to continue sampling the second temperature data of each temperature sensor through the second sampling strategy.

[0013] An electronic device includes a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the following steps: A first sampling strategy is obtained, and first temperature data of each temperature sensor is sampled using the first sampling strategy; wherein, the first sampling strategy includes a first sampling frequency corresponding to each temperature sensor; Real-time detection of whether each of the first temperature data is greater than the temperature threshold set by the corresponding temperature sensor; The temperature sensor whose first temperature data is greater than the corresponding temperature threshold is marked as the target temperature sensor; A second sampling frequency is set according to the first temperature data from the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency; The first sampling strategy is updated based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy; The second sampling strategy is used to continue sampling the second temperature data of each temperature sensor.

[0014] A computer-readable storage medium storing a computer program, which, when executed by a processor, causes the processor to perform the following steps: A first sampling strategy is obtained, and first temperature data of each temperature sensor is sampled using the first sampling strategy; wherein, the first sampling strategy includes a first sampling frequency corresponding to each temperature sensor; Real-time detection of whether each of the first temperature data is greater than the temperature threshold set by the corresponding temperature sensor; The temperature sensor whose first temperature data is greater than the corresponding temperature threshold is marked as the target temperature sensor; A second sampling frequency is set according to the first temperature data from the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency; The first sampling strategy is updated based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy; The second sampling strategy is used to continue sampling the second temperature data of each temperature sensor.

[0015] The beneficial effects of this invention are as follows: Under normal conditions, it operates at a lower first sampling frequency, which significantly reduces data redundancy in the stable temperature range, and significantly reduces the bus communication load, main control unit computing overhead, and overall system power consumption. Once a local temperature exceeds the threshold, the corresponding sensor is immediately marked as the target device, and its sampling frequency is dynamically increased to a higher second sampling frequency. This temperature-based differentiated sampling mechanism ensures resource conservation under normal operating conditions and ensures that more detailed and continuous temperature change data can be obtained under abnormal conditions, thereby achieving a balance between resource optimization and monitoring accuracy, and providing a reliable guarantee for precise temperature control in food processing. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] in: Figure 1 This is an application environment diagram of a multi-sensor temperature data sampling method in one embodiment; Figure 2 This is a flowchart of a multi-sensor temperature data sampling method in one embodiment; Figure 3 This is a structural block diagram of a multi-sensor temperature data sampling device in one embodiment; Figure 4 This is a structural block diagram of an electronic device in one embodiment. Detailed Implementation

[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0019] Figure 1 This is a diagram illustrating a multi-sensor temperature data sampling application environment in one embodiment. (Refer to...) Figure 1This multi-sensor temperature data sampling method is applied to a multi-sensor temperature data sampling system. The system includes a terminal 110 and a server 120. The terminal 110 and server 120 are connected via a network. The terminal 110 can be a desktop terminal or a mobile terminal; a mobile terminal can be at least one of a mobile phone, tablet, or laptop. The server 120 can be a standalone server or a server cluster consisting of multiple servers. The terminal 110 is used to sample temperature data, and the server 120 is used to generate sampling strategies.

[0020] like Figure 2 As shown, in one embodiment, a multi-sensor temperature data sampling method is provided. This method can be applied to both terminals and servers, and is implemented through a sensor sampling system. The sensor sampling system includes a bus and temperature sensors connected to the bus. This embodiment illustrates its application to a terminal. The multi-sensor temperature data sampling method specifically includes the following steps: S1: Obtain a first sampling strategy, and sample the first temperature data of each temperature sensor using the first sampling strategy; wherein, the first sampling strategy includes the first sampling frequency corresponding to each temperature sensor; S2: Real-time detection of whether each of the first temperature data is greater than the temperature threshold set by the corresponding temperature sensor; S3: Mark the temperature sensor whose first temperature data is greater than the corresponding temperature threshold as the target temperature sensor; S4: Set a corresponding second sampling frequency based on the first temperature data from the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency; S5: Update the first sampling strategy based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy; S6: Continue to sample the second temperature data of each temperature sensor using the second sampling strategy.

[0021] The system employs a typical bus architecture, where multiple temperature sensors are connected to the master control unit via shared physical lines (data lines and clock lines). The bus typically consists of two main signal lines: a data line (SDA) and a clock line (SCL). The data line transmits temperature data, while the clock line synchronizes data transmission between different devices. All temperature sensors are connected to the SDA and SCL signal lines of the bus via pull-up resistors. Each sensor has a unique address on the bus, allowing the master control unit to distinguish between them. In this shared bus architecture, all sensors are connected in parallel, requiring minimal wiring and simplifying the cabling process. Each temperature sensor integrates the necessary address encoding internally, allowing the master control unit to selectively communicate with a particular sensor by sending specific address commands, thereby enabling the reading or writing of temperature data. Data acquisition and transmission are based on a master / slave model. The master control unit acts as the "master device," responsible for generating clock signals and controlling the start and end of data transmission, while each temperature sensor acts as a "slave device," executing operations according to the master device's commands. Through this master-slave relationship, the bus can efficiently coordinate the operation of multiple sensors, ensuring orderly data exchange. When the main control unit needs to read the temperature data of a specific sensor, it will first send the address of the sensor to activate the sensor, and then perform read and write operations according to the preset timing control signals. After receiving the command, the temperature sensor will return its current temperature value to the main control unit through the data line for further processing.

[0022] The bus design allows multiple temperature sensors to share the same data and clock lines, reducing wiring complexity and cost. However, this sharing mechanism also requires robust load management capabilities to handle potential signal interference, conflicts, and delays during processing. To ensure data transmission efficiency, the main control unit coordinates communication between temperature sensors using appropriate signal control and waiting mechanisms, ensuring that no multiple sensors compete for the bus simultaneously. When a temperature sensor detects an anomaly and is flagged as a target sensor, the system prioritizes accessing that sensor within a specified time window to acquire high-frequency temperature change data, further improving monitoring accuracy and timeliness.

[0023] As described in step S1 above, a first sampling strategy is obtained, and the first temperature data of each temperature sensor is sampled using the first sampling strategy. The first sampling strategy includes a first sampling frequency corresponding to each temperature sensor. The core of the first sampling strategy is to assign a "first sampling frequency" to each sensor, which is usually a relatively low value. The purpose is to achieve temperature data acquisition from each sensor without burdening the system. Specifically, the system accesses all connected temperature sensors in turn according to the set frequency, obtains their current temperature readings, and collectively forms the first temperature data.

[0024] As described in step S2 above, it is necessary to detect in real time whether each of the first temperature data points exceeds the temperature threshold set by the corresponding temperature sensor. Real-time detection is performed on the continuously collected "first temperature data" within a sampling period. Specifically, the working principle involves comparing each sensor reading with its preset "temperature threshold." This temperature threshold is typically set based on the sensor environment, product characteristics, and safety requirements. For example, in some food storage environments, the temperature threshold may be set to a refrigeration temperature (e.g., 4°C), while in specific food processing or sterilization stages, the threshold may be a higher value. This allows for precise identification of which target sensor temperature readings have exceeded safety limits, thereby initiating subsequent control and response strategies.

[0025] As described in step S3 above, the temperature sensor whose first temperature data is greater than the corresponding temperature threshold is marked as the target temperature sensor. Temperature sensors whose temperature data exceeds a set threshold are marked as target temperature sensors. The specific marking method is not limited; for example, they can be marked with a symbol. The purpose is to extract temperature sensors whose first temperature data is greater than the corresponding temperature threshold, so as to facilitate the subsequent setting of the second sampling frequency.

[0026] As described in step S4 above, a corresponding second sampling frequency is set based on the first temperature data from the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency. The higher second sampling frequency reflects the urgency of the target sensor, indicating a significant change in its value that requires timely acquisition. When the temperature of the target sensor exceeds its set normal operating range, its sampling frequency is dynamically increased to obtain updated data more frequently, making monitoring more flexible and significantly improving the response speed to abnormal situations. For example, if the temperature of a sensor exceeds a threshold for the first time, its sampling frequency can be set to two samples per second instead of one sample per 10 seconds. This flexibility ensures that the system can capture thermal fluctuations in real time and promptly grasp the trend of temperature changes, enabling more accurate control and adjustment.

[0027] As described in step S5 above, the first sampling strategy is updated based on the target temperature sensor and its corresponding second sampling frequency to obtain the second sampling strategy. According to the set target sensor and its corresponding second sampling frequency, the first sampling strategy is systematically updated to the second sampling strategy. The updated second sampling strategy will certainly respond to real-time changing monitoring needs with greater flexibility. Through this flexible sampling strategy, the system can effectively manage resources, ensuring that in the event of temperature anomalies, limited computing and transmission resources can be concentrated on important sensors.

[0028] As described in step S6 above, the second temperature data from each temperature sensor continues to be sampled using the second sampling strategy. Compared to the low sampling frequency of the previous cycle, this new strategy sets specific target sensors as high-frequency sampling carriers, while the remaining unmarked sensors maintain their original low-frequency, low-power state. This ensures effective monitoring under different temperature changes, achieving "priority sampling." Even when dealing with multi-point temperature monitoring over a large area, the dual-track sampling mechanism ensures that core data can be fed back in real time with new stability, comprehensively enhancing the response flexibility and accuracy of the temperature monitoring system. Through the dynamic sampling strategy, bus load and power consumption are significantly reduced, improving the accuracy of food temperature control.

[0029] In one embodiment, after step S6 of continuing to sample the second temperature data of each temperature sensor using the second sampling strategy, the method further includes: S701: Perform differential calculation on the first temperature data sampled by the first sampling strategy and the second temperature data sampled by the second sampling strategy to obtain the temperature change. S702: Aggregate the temperature change, the first temperature data, and the second temperature data to obtain an aggregated data package; S703: The data packet is sent to the designated terminal via a preset wireless communication device.

[0030] As described in step S701 above, the temperature change is obtained by performing a differential calculation on the first temperature data sampled by the first sampling strategy and the second temperature data sampled by the second sampling strategy. The core idea of ​​differential calculation is to quickly determine the temperature change trend by comparing the temperature values ​​at two time points. Specifically, the first temperature data is collected using the first sampling strategy, and the second temperature data is collected again using the second sampling strategy. These are then combined into a temperature dataset in chronological order. The temperature change between two adjacent temperature data points in this dataset is then calculated, i.e., ΔT = T. k - T k-1This temperature change not only reflects the degree of temperature increase or decrease, but also provides important information for subsequent monitoring and decision-making. For example, in the food processing industry, a significant temperature change may indicate an abnormal situation that requires immediate countermeasures.

[0031] As described in step S702 above, the temperature change, the first temperature data, and the second temperature data are aggregated to obtain an aggregated data packet. The temperature change, the first temperature data, and the second temperature data are integrated into a unified structure to form the aggregated data packet. The structure design of this data packet needs to consider the effectiveness and integrity of its transmission. It typically includes the numerical value of the temperature change, the corresponding first and second temperature data, the sampling timestamp, the sensor ID, and other information. When forming the aggregated data packet, the system will use a specific protocol format to ensure that the data can be accurately interpreted and processed during wireless transmission.

[0032] As described in step S703 above, the data packet is sent to the designated terminal via a preset wireless communication device. The bus can rely on this preset wireless communication device to complete the wireless data transmission. This device can be Bluetooth, Wi-Fi, Zigbee, or other wireless protocols suitable for short- or medium-range transmission. During data transmission, the system first encodes the aggregated data packet into a format suitable for wireless transmission and transmits it via radio frequency signals, ensuring that the data can be accurately delivered to the destination terminal or processing platform. This enables remote access and real-time feedback of temperature monitoring data, allowing staff or the system to instantly obtain the latest temperature status information from different locations. This wireless transmission method not only improves the timeliness of monitoring data but also creates conditions for subsequent data analysis and decision-making.

[0033] In one embodiment, step S6, which involves continuing to sample the second temperature data from each temperature sensor using the second sampling strategy, includes: S601: Obtain the target sampling frequency with the highest frequency among all temperature sensors in the second sampling strategy, and set the total communication cycle according to the target frequency; S602: Divide the total communication cycle into a corresponding number of communication time periods according to the number of temperature sensors; S603: Allocate the communication time period to the corresponding temperature sensor as an exclusive communication window between the temperature sensor and the bus; S604: Samples the second temperature data of each temperature sensor during each total communication cycle.

[0034] As described in step S601 above, the highest target sampling frequency among all temperature sensors in the second sampling strategy is obtained, and the total communication period is set according to the target frequency. A "total communication period" is determined, which is the time interval for data communication between different sensors. This total period is set based on the sampling frequency specified for each temperature sensor in the second sampling strategy. Specifically, the system will select a suitable time window to ensure that all necessary communication tasks are completed within this time period. For each temperature sensor marked as a target, its operating frequency may be different. Therefore, the system needs to comprehensively consider this when setting the total period. For example, suppose there are three sensors in the system: Sensor A (high priority): second sampling frequency = 4Hz, sampling interval ≤ 250 ms; Sensor B (high priority): second sampling frequency = 2Hz, sampling interval ≤ 500ms; Sensor C (normal priority): first sampling frequency = 0.2Hz, sampling interval ≤ 5000ms; among which, the most stringent requirement comes from Sensor A's 250 ms. Therefore, the total communication period of the system must be set to ≤ 250 ms (for example, it can be set to 200ms or 250ms). Within a total cycle of 250ms, the system will: first access sensor A, then sensor B, and (because there is ample time) may also access sensor C. Alternatively, the system can choose to access sensor C only once every 20 cycles (5 seconds), as long as its minimum frequency requirement is met.

[0035] As described in step S602 above, the total communication cycle is divided into a corresponding number of communication time segments according to the number of temperature sensors. This division process ensures that each temperature sensor has an independent and fixed time segment for data exchange within the cycle. Assuming the total cycle is confirmed to be 6 seconds, and the system is connected to 6 temperature sensors, the system will evenly divide this 6-second total communication cycle into 6 time segments, each lasting 1 second. This segmentation method ensures that each sensor has its own dedicated communication window, thereby avoiding data conflicts and collisions. When one sensor exchanges data within its dedicated time segment, other sensors will remain silent, which can significantly improve the stability and effectiveness of communication.

[0036] As described in step S603 above, the communication time period is allocated to the corresponding temperature sensor as an exclusive communication window between the temperature sensor and the bus. Within each set communication time period, only the corresponding temperature sensor can actively exchange data with the main control unit. For example, assuming the communication cycle is divided into six 1-second time periods, the system will allocate the first time period to the first temperature sensor, the second time period to the second sensor, and so on, based on the previous markings. This effectively avoids data conflicts and broadcast flickering problems caused by multiple sensors requesting data simultaneously.

[0037] As described in step S604 above, the second temperature data of each temperature sensor is sampled within each total communication cycle. Within the previously set communication time period, the "second temperature data" of each temperature sensor is sampled one by one according to the preset second sampling strategy. This means that within the exclusive time period assigned to each temperature sensor, the system will actively send a data read command, instructing the sensor to return its current temperature value, ensuring efficient collection of key temperature data and minimizing omissions or delays.

[0038] In one embodiment, prior to step S604 of sampling the second temperature data of each temperature sensor within each total communication cycle, the method further includes: S5041: Calculate the difference between the first temperature data of the target temperature sensor and the corresponding temperature threshold; S5042: Calculate the priority of the target temperature sensor based on the difference; S5043: Adjust the sampling order of each temperature sensor within the total communication cycle according to the priority.

[0039] As described in step S5041 above, the difference between the first temperature data of the target temperature sensor and the corresponding temperature threshold is calculated. This difference can be expressed as: difference = first temperature data - temperature threshold. The significance of this difference is that it reflects the degree of deviation of the current temperature of the target temperature sensor from its set safety threshold.

[0040] As described in step S5042 above, the priority of the target temperature sensor is calculated based on the difference. The priority setting directly affects the sampling order and resource allocation of each sensor within the sampling period. The larger the difference, the higher the priority of the target temperature sensor. This priority division logic reflects the system's dynamic response capability and aligns with the target-oriented temperature monitoring approach. For example, if the temperature of a sensor significantly exceeds the limit, with a difference of 5°C, the system will set the priority of that sensor to the highest level to ensure rapid data sampling and subsequent analysis. Conversely, for sensors with relatively stable temperatures and smaller differences (such as 1°C), their priority will be correspondingly reduced.

[0041] As described in step S5043 above, the sampling order of each temperature sensor within the total communication cycle is adjusted according to the priority. Based on the previously calculated priority of the target temperature sensor, the sampling order of each temperature sensor within this round of communication cycle is dynamically adjusted. The sampling order of the sensors is arranged one by one according to the priority from high to low, so that the high-priority sensor enters its exclusive communication time period first for data exchange, which greatly reduces the resources spent on other sensors with normal temperatures. For example, in the same 6-second total communication cycle, the first-priority sensor will undoubtedly get the first 2 seconds of exclusive communication window, while the sampling order will allocate the subsequent time period to the lower-priority sensors.

[0042] In one embodiment, before step S4 of setting the corresponding second sampling frequency based on the first temperature data from the target temperature sensor, the method further includes: S301: Obtain multiple first datasets and multiple second datasets sampled by the sensor sampling system; wherein, the first datasets do not contain temperature data greater than the corresponding temperature threshold, and the second datasets contain temperature data greater than the corresponding temperature threshold; S302: Determine the index data of each temperature sensor based on multiple first datasets to obtain the index dataset; S303: Calculate the difference between each temperature data in each second dataset and the corresponding index data in the index dataset to obtain the third dataset corresponding to each second dataset; S304: Calculate the correlation coefficients between pairs of data in the third dataset; S305: Mark the pairwise data with a correlation coefficient greater than a preset correlation coefficient as collaborative data; S306: Based on the labeling results, all temperature sensors are clustered to obtain multiple temperature sensor clusters; wherein, the sampling frequency is the same in each temperature sensor cluster.

[0043] As described in step S301 above, multiple first datasets and multiple second datasets sampled by the sensor sampling system are acquired. In this stage, the system acquires multiple datasets recorded by the sensor sampling system. The first dataset consists of temperature data collected by each temperature sensor during routine monitoring. These data do not exceed specific temperature thresholds and are therefore within the normal range, indicating that the system is operating normally. The second dataset contains temperature data exceeding the temperature thresholds collected during abnormal or critical situations; in other words, these data indicate that certain sensors are experiencing temperature events requiring attention. Both the first and second datasets represent historical data collected by the system for that sensor, representing data collected within one sampling period.

[0044] As described in step S302 above, the index data of each temperature sensor is determined based on multiple first datasets, resulting in an index dataset. The previously acquired multiple first datasets are analyzed to determine the key index data for each temperature sensor. Typically, this index data may include the mean temperature, standard deviation, and fluctuation range, depending on the specific application scenario and requirements. For example, the system can calculate the average temperature of each sensor over multiple sampling periods as its baseline index, or calculate the standard deviation of the temperature to assess its stability under normal operating conditions.

[0045] As described in step S303 above, the difference between each temperature data point in each second dataset and the corresponding indicator data in the indicator dataset is calculated to obtain a third dataset corresponding to each second dataset. Each data point exceeding a temperature threshold is extracted from the second dataset and compared with the corresponding indicator data to calculate their difference, i.e., temperature data - indicator data. This difference not only reflects the degree of deviation of the current temperature from the normal state but also reveals deeper information, such as the relationship between the amplitude of temperature fluctuations and the degree of stability. These differences will be organized into a new dataset, i.e., the third dataset.

[0046] As described in step S304 above, the correlation coefficients of each pair of data points in the third dataset are calculated. The correlation coefficient quantifies the strength of the relationship between temperature changes among different sensors. The Pearson correlation coefficient is typically used to calculate the correlation coefficient. By comparing all temperature data pairwise, the system can identify sensors with significant correlations. This correlation analysis can not only promptly detect connections between sensors, such as whether both are simultaneously affected by environmental changes, but also identify potential faults or data anomalies. A high correlation coefficient indicates a strong linear relationship, while a low correlation coefficient indicates the absence of a strong linear relationship.

[0047] As described in step S305 above, pairs of data with a correlation coefficient greater than a preset correlation coefficient are marked as collaborative data. This identifies data pairs with correlation coefficients greater than the preset correlation coefficient as collaborative data. The preset correlation coefficient is set based on actual application scenarios, historical data, and business needs; for example, the preset correlation coefficient is set to 0.7. By marking collaborative data, the system can effectively focus on sensor data that can influence each other or be driven by the same external conditions, aiding subsequent data analysis and decision-making.

[0048] As described in step S306 above, all temperature sensors are clustered according to the labeling results, resulting in multiple temperature sensor clusters. Based on the labeling results, the system divides all temperature sensors into several "sensor clusters" according to their correlation coefficients. In this process, the system groups sensors with high correlation and labeled as cooperative data into the same group, forming a "temperature sensor cluster". All sensors within this cluster will be assigned the same sampling frequency. The advantage of this organization method is that it can significantly improve the management and operation efficiency of the system. By grouping interconnected sensors together, the system can execute a unified sampling frequency within their exclusive windows. This not only helps to improve the symmetry and consistency of the data, but also reduces competition on the channel, while prioritizing the effectiveness of multi-point temperature monitoring. Based on the clustering results, when processing and analyzing data, the system can more accurately perform cross-cluster data aggregation and comparison, enabling the entire temperature monitoring system to quickly allocate resources, adaptively sample, and optimize processing across different sensor clusters when facing complex environmental changes.

[0049] It should be noted that clustering is used to set the sampling frequency, while priority adjustment is used to optimize the sampling order within the total communication cycle; the two can be executed in parallel.

[0050] In one embodiment, step S5, which updates the first sampling strategy based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy, includes: S501: Obtain the target temperature sensor cluster where the target temperature sensor is located; S502: Set the sampling frequency of all temperature sensors in the target temperature sensor cluster to the second sampling frequency; S503: Update the first sampling strategy by updating the temperature sensors in the target temperature sensor cluster and their corresponding second sampling frequencies to obtain the second sampling strategy.

[0051] As described in step S501 above, the target temperature sensor cluster to which the target temperature sensor belongs is obtained. The sensor cluster to which the target temperature sensor belongs is identified and obtained; that is, after clustering, each sensor cluster is stored in an internal data structure. Then, the clustering results storing different sensor information are retrieved from the internal data structure to quickly locate the group to which the target sensor belongs.

[0052] As described in step S502 above, the sampling frequency of all temperature sensors in the target temperature sensor cluster is set to the second sampling frequency. In this process, the system uniformly sets all sensors belonging to the target temperature sensor cluster to the same "second sampling frequency." This adjustment means that all these sensors will share an increased, dynamic sampling frequency in subsequent sampling cycles, enabling more precise and real-time monitoring of temperature changes. Unifying all sensors to the same high-frequency sampling strategy helps improve data consistency and synchronization, ensuring that sensors within the same cluster can work in coordination. For example, assuming the temperature sensors in the target cluster were previously assigned a lower first sampling frequency (e.g., checking once every 10 seconds), through dynamic adjustment, the system can increase this frequency to twice per second based on their respective temperature states. This adjustment not only increases the frequency of key data acquisition but also provides more accurate real-time data for subsequent processing, thereby effectively improving the overall system's responsiveness.

[0053] As described in step S503 above, the first sampling strategy is updated by updating the temperature sensors in the target temperature sensor cluster and their corresponding second sampling frequencies to obtain the second sampling strategy. Based on the acquired target temperature sensor cluster and its set second sampling frequency, the system will modify and replace the corresponding items in the original sampling strategy in real time. This involves adjusting all sensors in the target sensor cluster and their newly set sampling frequencies to ensure that future data acquisition follows the new frequency strategy. This update not only improves the system's flexibility and ensures real-time response and adjustment to the actual environmental conditions during temperature monitoring, but also reduces system power consumption caused by unnecessary resource waste.

[0054] In one embodiment, step S6, which involves continuing to sample the second temperature data from each temperature sensor using the second sampling strategy, includes: S611: Real-time monitoring of the level values ​​of the data lines and clock lines of the bus during the sampling process; S612: When the level value of the data line and / or the clock line is detected to be lower than the preset abnormal low level value and the duration exceeds the preset time threshold, the currently sampled second temperature data is recorded as the target second temperature data, and the number of abnormalities of the target second temperature data is recorded. S613: Set a retransmission delay time for the target second temperature data based on the number of anomalies, so as to set the time point for resampling the target second temperature data based on the retransmission delay time.

[0055] As described in step S611 above, the level values ​​of the data line and clock line of the bus are monitored in real time during the sampling process. Normally, when the bus is idle, the data line (SDA) and clock line (SCL) should be kept at a high level (logic 1); however, during data transmission, the signals will switch according to the communication protocol rules. The system uses a dedicated hardware pin (GPIO) configured as an input mode and connected to these two signal lines for real-time level monitoring.

[0056] As described in step S612 above, when the level value of the data line and / or the clock line is detected to be lower than a preset abnormal low level value, and the duration exceeds a preset time threshold, the currently sampled second temperature data is recorded as the target second temperature data, and the number of abnormalities of the target second temperature data is recorded. When the level value of the data line (SDA) or clock line (SCL) is detected to be lower than the set "abnormal low level value", and the duration of this low level state exceeds a preset time threshold, the system will record the second temperature data collected at this moment as "target second temperature data". This indicates that there is a problem with the transmission of the temperature data. If the second temperature data of a certain sensor shows communication line abnormalities in multiple sampling periods, it indicates that there are unstable factors in its connection with the system, and a specific retransmission strategy may be needed to ensure that the data is not lost and ultimately ensure the accuracy of monitoring.

[0057] As described in step S613 above, a retransmission delay time is set for the target second temperature data based on the number of anomalies, so as to set the time point for resampling the target second temperature data according to the retransmission delay time. The retransmission delay time is intelligently adjusted based on the recorded number of anomalies to set the time point for resampling the target second temperature data. When the system detects multiple anomalies, i.e., a certain target second temperature data value is frequently affected by abnormal levels within a short period, this indicates that the sensor's stability is poor or there is a problem with the communication environment. Therefore, the system will increase the retransmission delay time according to the number of anomalies, typically using an exponential backoff algorithm. For example, the retransmission delay might be 10 milliseconds after the first anomaly, while it could be set to 20 milliseconds after the second anomaly, and so on. This dynamic adjustment mechanism aims to enhance the ability to respond to faults, so as to avoid exacerbating the communication burden or causing more conflicts due to excessively frequent retransmissions.

[0058] Reference Figure 3 The present invention also provides a multi-sensor temperature data sampling device, implemented through a sensor sampling system, the sensor sampling system including a bus and a temperature sensor connected to the bus, the device comprising: The acquisition module 902 is used to acquire a first sampling strategy and sample the first temperature data of each temperature sensor through the first sampling strategy; wherein, the first sampling strategy includes a first sampling frequency corresponding to each temperature sensor; The detection module 904 is used to detect in real time whether each of the first temperature data is greater than the temperature threshold set by the corresponding temperature sensor. The marking module 906 is used to mark a temperature sensor whose first temperature data is greater than the corresponding temperature threshold as a target temperature sensor. Setting module 908 is used to set a corresponding second sampling frequency based on the first temperature data of the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency; The update module 910 is used to update the first sampling strategy based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy; The sampling module 912 is used to continue sampling the second temperature data of each temperature sensor through the second sampling strategy.

[0059] In one embodiment, a multi-sensor temperature data sampling device further includes: The differential calculation module is used to perform differential calculation on the first temperature data sampled by the first sampling strategy and the second temperature data sampled by the second sampling strategy to obtain the temperature change. The data aggregation module is used to aggregate the temperature change, the first temperature data, and the second temperature data to obtain an aggregated data package; The sending module is used to send the data packet to a designated terminal via a preset wireless communication device.

[0060] In one embodiment, the sampling module 912 includes: The total communication cycle setting submodule is used to obtain the target sampling frequency with the highest frequency among the temperature sensors of the second sampling strategy, and set the total communication cycle according to the target frequency; A sub-module is used to divide the total communication cycle into a corresponding number of communication time periods according to the number of temperature sensors; The allocation submodule is used to allocate the communication time period to the corresponding temperature sensor as an exclusive communication window between the temperature sensor and the bus. The sampling submodule is used to sample the second temperature data of each temperature sensor during each total communication cycle.

[0061] In one embodiment, the sampling module 912 further includes: The difference calculation submodule is used to calculate the difference between the first temperature data of the target temperature sensor and the corresponding temperature threshold. A priority calculation submodule is used to calculate the priority of the target temperature sensor based on the difference. The sampling order adjustment submodule is used to adjust the sampling order of each temperature sensor within the total communication cycle according to the priority.

[0062] In one embodiment, a multi-sensor temperature data sampling device further includes: The first dataset acquisition module is used to acquire multiple first datasets and multiple second datasets sampled by the sensor sampling system; wherein, the first dataset does not contain temperature data greater than the corresponding temperature threshold, and the second dataset contains temperature data greater than the corresponding temperature threshold. The indicator data determination module is used to determine the indicator data of each temperature sensor based on multiple first datasets, thereby obtaining the indicator dataset; The third dataset acquisition module is used to calculate the difference between each temperature data in each second dataset and the corresponding index data in the index dataset, thereby obtaining the third dataset corresponding to each second dataset. The correlation coefficient calculation module is used to calculate the correlation coefficient between any two data points in the third dataset; A collaborative data labeling module is used to label pairwise data with a correlation coefficient greater than a preset correlation coefficient as collaborative data. The clustering module is used to cluster all temperature sensors according to the labeling results to obtain multiple temperature sensor clusters; wherein, the sampling frequency is the same in each temperature sensor cluster.

[0063] In one embodiment, the update module 910 includes: The target temperature sensor cluster acquisition submodule is used to acquire the target temperature sensor cluster to which the target temperature sensor is located. The sampling frequency setting submodule is used to set the sampling frequency of all temperature sensors in the target temperature sensor cluster to the second sampling frequency. The second sampling strategy acquisition submodule is used to update the first sampling strategy by updating the temperature sensors in the target temperature sensor cluster and their corresponding second sampling frequencies to obtain the second sampling strategy.

[0064] In one embodiment, the sampling module 912 includes: The level detection submodule is used to monitor the level values ​​of the data lines and clock lines of the bus in real time during the sampling process. An anomaly count recording submodule is used to record the currently sampled second temperature data as the target second temperature data and record the number of anomalies of the target second temperature data when the level value of the data line and / or the clock line is detected to be lower than a preset abnormal low level value and the duration exceeds a preset time threshold. The time-point sampling submodule is used to set a retransmission delay time for the target second temperature data based on the number of anomalies, so as to set the time point for resampling the target second temperature data based on the retransmission delay time.

[0065] Figure 4 An internal structural diagram of an electronic device in one embodiment is shown. This electronic device can specifically be a terminal or a server, and more specifically, a computer device. Figure 4 As shown, the electronic device includes a processor, a memory, and a network interface connected via a system bus. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores an operating system and may also store a computer program. When executed by the processor, this computer program enables the processor to implement a multi-sensor temperature data sampling method. The internal memory may also store a computer program, which, when executed by the processor, enables the processor to implement the multi-sensor temperature data sampling method. Those skilled in the art will understand that... Figure 4 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the electronic device to which the present application is applied. The specific electronic device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0066] In one embodiment, an electronic device is provided, including a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the following steps: A first sampling strategy is obtained, and first temperature data of each temperature sensor is sampled using the first sampling strategy; wherein, the first sampling strategy includes a first sampling frequency corresponding to each temperature sensor; Real-time detection of whether each of the first temperature data is greater than the temperature threshold set by the corresponding temperature sensor; The temperature sensor whose first temperature data is greater than the corresponding temperature threshold is marked as the target temperature sensor; A second sampling frequency is set according to the first temperature data from the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency; The first sampling strategy is updated based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy; The second sampling strategy is used to continue sampling the second temperature data of each temperature sensor.

[0067] Under normal conditions, it operates at a lower first sampling frequency, which significantly reduces data redundancy in the stable temperature range, and significantly reduces bus communication load, main control unit computing overhead, and overall system power consumption. Once a local temperature exceeds the threshold, the corresponding sensor is immediately marked as the target device, and its sampling frequency is dynamically increased to a higher second sampling frequency. This temperature-based differentiated sampling mechanism ensures resource conservation under normal operating conditions and ensures that more detailed and continuous temperature change data can be obtained under abnormal conditions, thereby achieving a balance between resource optimization and monitoring accuracy, and providing a reliable guarantee for precise temperature control in food processing.

[0068] In one embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, causes the processor to perform the following steps: A first sampling strategy is obtained, and first temperature data of each temperature sensor is sampled using the first sampling strategy; wherein, the first sampling strategy includes a first sampling frequency corresponding to each temperature sensor; Real-time detection of whether each of the first temperature data is greater than the temperature threshold set by the corresponding temperature sensor; The temperature sensor whose first temperature data is greater than the corresponding temperature threshold is marked as the target temperature sensor; A second sampling frequency is set according to the first temperature data from the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency; The first sampling strategy is updated based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy; The second sampling strategy is used to continue sampling the second temperature data of each temperature sensor.

[0069] Under normal conditions, it operates at a lower first sampling frequency, which significantly reduces data redundancy in the stable temperature range, and significantly reduces bus communication load, main control unit computing overhead, and overall system power consumption. Once a local temperature exceeds the threshold, the corresponding sensor is immediately marked as the target device, and its sampling frequency is dynamically increased to a higher second sampling frequency. This temperature-based differentiated sampling mechanism ensures resource conservation under normal operating conditions and ensures that more detailed and continuous temperature change data can be obtained under abnormal conditions, thereby achieving a balance between resource optimization and monitoring accuracy, and providing a reliable guarantee for precise temperature control in food processing.

[0070] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments described above. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), RAMbus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and RAMbus dynamic RAM (RDRAM), etc.

[0071] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0072] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of this patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A multi-sensor temperature data sampling method, implemented through a sensor sampling system, the sensor sampling system comprising a bus and temperature sensors connected to the bus, characterized in that, The method includes: A first sampling strategy is obtained, and first temperature data of each temperature sensor is sampled using the first sampling strategy; wherein, the first sampling strategy includes a first sampling frequency corresponding to each temperature sensor; Real-time detection of whether each of the first temperature data is greater than the temperature threshold set by the corresponding temperature sensor; The temperature sensor whose first temperature data is greater than the corresponding temperature threshold is marked as the target temperature sensor; A second sampling frequency is set according to the first temperature data from the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency; The first sampling strategy is updated based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy; The second sampling strategy is used to continue sampling the second temperature data of each temperature sensor.

2. The multi-sensor temperature data sampling method according to claim 1, characterized in that, After the step of continuing to sample the second temperature data of each temperature sensor using the second sampling strategy, the method further includes: The temperature change is obtained by performing a differential calculation on the first temperature data sampled by the first sampling strategy and the second temperature data sampled by the second sampling strategy. The temperature change, the first temperature data, and the second temperature data are aggregated to obtain an aggregated data package; The data packet is sent to a designated terminal via a preset wireless communication device.

3. The multi-sensor temperature data sampling method according to claim 1, characterized in that, The step of continuing to sample the second temperature data of each temperature sensor using the second sampling strategy includes: Obtain the target sampling frequency with the highest frequency among all temperature sensors in the second sampling strategy, and set the total communication cycle according to the target frequency; The total communication cycle is divided into a corresponding number of communication time periods according to the number of temperature sensors; The communication time period is allocated to the corresponding temperature sensor as an exclusive communication window between the temperature sensor and the bus. Second temperature data from each temperature sensor is sampled during each total communication cycle.

4. The multi-sensor temperature data sampling method according to claim 3, characterized in that, Before the step of sampling the second temperature data of each temperature sensor in each total communication cycle, the method further includes: Calculate the difference between the first temperature data of the target temperature sensor and the corresponding temperature threshold; The priority of the target temperature sensor is calculated based on the difference. The sampling order of each temperature sensor within the total communication cycle is adjusted according to the priority.

5. The multi-sensor temperature data sampling method according to claim 1, characterized in that, Before the step of setting the corresponding second sampling frequency based on the first temperature data from the target temperature sensor, the method further includes: The sensor sampling system acquires multiple first datasets and multiple second datasets; wherein the first datasets do not contain temperature data greater than the corresponding temperature threshold, and the second datasets contain temperature data greater than the corresponding temperature threshold. The index data for each temperature sensor is determined based on multiple first datasets, thus obtaining the index dataset; Calculate the difference between each temperature data in each second dataset and the corresponding index data in the index dataset to obtain the third dataset corresponding to each second dataset; Calculate the correlation coefficients between any two data points in the third dataset; Data pairs with a correlation coefficient greater than a preset correlation coefficient are marked as collaborative data; Based on the labeling results, all temperature sensors are clustered to obtain multiple temperature sensor clusters; wherein, the sampling frequency is the same in each temperature sensor cluster.

6. The multi-sensor temperature data sampling method according to claim 5, characterized in that, The step of updating the first sampling strategy based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy includes: Obtain the target temperature sensor cluster in which the target temperature sensor is located; Set the sampling frequency of all temperature sensors in the target temperature sensor cluster to the second sampling frequency; The first sampling strategy is updated by updating the temperature sensors in the target temperature sensor cluster and their corresponding second sampling frequencies to obtain the second sampling strategy.

7. The multi-sensor temperature data sampling method according to claim 1, characterized in that, The step of continuing to sample the second temperature data of each temperature sensor using the second sampling strategy includes: Real-time monitoring of the voltage levels of the bus's data and clock lines during the sampling process; When the level of the data line and / or the clock line is detected to be lower than the preset abnormal low level value and the duration exceeds the preset time threshold, the currently sampled second temperature data is recorded as the target second temperature data, and the number of abnormalities of the target second temperature data is recorded. A retransmission delay time is set for the target second temperature data based on the number of anomalies, and the time point for resampling the target second temperature data is set according to the retransmission delay time.

8. A multi-sensor temperature data sampling device, implemented through a sensor sampling system, the sensor sampling system comprising a bus and a temperature sensor connected to the bus, characterized in that, The device includes: An acquisition module is used to acquire a first sampling strategy and sample the first temperature data of each temperature sensor using the first sampling strategy; wherein, the first sampling strategy includes a first sampling frequency corresponding to each temperature sensor; The detection module is used to detect in real time whether each of the first temperature data is greater than the temperature threshold set by the corresponding temperature sensor; A marking module is used to mark a temperature sensor whose first temperature data is greater than the corresponding temperature threshold as a target temperature sensor. The setting module is used to set a corresponding second sampling frequency based on the first temperature data from the target temperature sensor; wherein the second sampling frequency is greater than the first sampling frequency. The update module is used to update the first sampling strategy based on the target temperature sensor and the corresponding second sampling frequency to obtain the second sampling strategy; The sampling module is used to continue sampling the second temperature data of each temperature sensor through the second sampling strategy.

9. A computer-readable storage medium, characterized in that, The device contains a computer program that, when executed by a processor, causes the processor to perform the steps of the multi-sensor temperature data sampling method as described in any one of claims 1 to 7.

10. An electronic device, characterized in that, The device includes a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the steps of the multi-sensor temperature data sampling method as described in any one of claims 1 to 7.

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