Disaster survey method, disaster survey device, and computer-readable storage medium

Abstract

The application discloses a disaster survey method, a disaster survey device and a computer readable storage medium, and the method comprises the following steps: when a disaster survey instruction is received, controlling a survey robot and / or a drone to travel based on a preset survey route; receiving survey temperature and survey humidity sent by the survey robot and / or the drone, and determining a survey temperature and survey humidity receiving time point; determining a survey point corresponding to the survey temperature and the survey humidity according to the preset survey route and the receiving time point; determining an expected temperature interval and an expected humidity interval corresponding to the survey point according to weather information of a current warehouse location; and outputting an alarm prompt when the survey temperature is not in the expected temperature interval and the survey humidity is not in the expected humidity interval. The application predicts the disaster of the survey point through the disaster survey device and the current weather, thereby guaranteeing the safety of warehouse goods.

Description

Technical Field

[0001] This invention relates to the field of warehouse disaster management, and more particularly to disaster surveying methods, disaster surveying devices, and computer-readable storage media. Background Technology

[0002] Warehouse management, also known as storage management, refers to the effective control of activities such as receiving, issuing, and storing stored goods. Its purpose is to ensure the integrity of stored goods and guarantee the normal operation of production and business activities for enterprises. Among the necessary measures to ensure the integrity of stored goods, fire prevention is crucial.

[0003] In the relevant warehouse safety management solutions, Chinese patent application number CN201920169596.6 discloses a warehouse fire safety monitoring system, which mainly discloses the determination of fire occurrence through video open flame images and smoke alarms.

[0004] However, this type of warehouse fire safety monitoring system can only issue an alarm when a fire occurs. By the time the alarm is triggered, the fire has often already spread significantly, resulting in substantial damage to warehouse goods. Therefore, current warehouse fire safety monitoring systems have the drawback of being unable to predict the extent of a fire.

[0005] The above content is only used to help understand the technical solution of the present invention and does not represent an admission that the above content is prior art. Summary of the Invention

[0006] The main objective of this invention is to provide a disaster assessment method, a disaster assessment device, and a computer-readable storage medium to solve the problem that current warehouse fire safety monitoring systems cannot predict disasters.

[0007] To achieve the above objectives, the present invention provides a disaster assessment method, which includes the following steps:

[0008] Upon receiving a disaster survey instruction, control the survey robot and / or drone to travel along a preset survey route;

[0009] Receive survey temperature and survey humidity sent by the survey robot and / or the drone, and determine the time point at which the survey temperature and survey humidity are received;

[0010] Based on the preset survey route and the receiving time point, determine the survey points corresponding to the survey temperature and the survey humidity;

[0011] Based on the weather information of the current warehouse location, determine the expected temperature range and expected humidity range corresponding to the survey point;

[0012] output an alarm prompt when the survey temperature is not within the expected temperature range and the survey humidity is not within the expected humidity range.

[0013] Optionally, after the step of determining the expected temperature range and the expected humidity range corresponding to the survey point according to weather information of a current warehouse location, the method further comprises:

[0014] obtaining a temperature change curve or a humidity change curve of the survey point in a preset time period when the survey temperature is not within the expected temperature range or the survey humidity is not within the expected humidity range;

[0015] outputting an alarm prompt when the temperature change curve is a continuously increasing curve or the humidity change curve is a continuously decreasing curve; or

[0016] controlling the survey robot and / or the unmanned aerial vehicle to continue to travel based on the preset survey route when the temperature change curve is not the continuously increasing curve and the humidity change curve is not the continuously decreasing curve.

[0017] Optionally, the step of outputting an alarm prompt when the survey temperature is not within the expected temperature range and the survey humidity is not within the expected humidity range comprises:

[0018] determining a warning index as a first index and outputting a first-level alarm prompt when the survey temperature is greater than a maximum value of the expected temperature and the survey humidity is less than a minimum value of the expected humidity curve; or

[0019] determining the warning index as a second index and outputting a second-level alarm prompt when the survey temperature is less than a minimum value of the expected temperature and the survey humidity is greater than a maximum value of the expected temperature.

[0020] Optionally, before the step of determining the expected temperature range and the expected humidity range corresponding to the survey point according to weather information of a current warehouse location, the method further comprises:

[0021] obtaining network address information of the current warehouse and determining the weather information based on the network address information;

[0022] receiving first category information of goods in the survey point sent by the survey robot and / or the unmanned aerial vehicle;

[0023] when the first category information is flammable goods, the step of determining the expected temperature range and the expected humidity range corresponding to the survey point according to weather information of a current warehouse location comprises:

[0024] If the weather information indicates rain, the maximum value of the desired temperature range is determined to be a first degree Celsius, and the minimum value is determined to be a second degree Celsius; the minimum value of the desired humidity range is determined to be a first humidity value, and the maximum value is determined to be a second humidity value; or

[0025] If the weather information is sunny, the maximum value of the desired temperature range is determined to be the third degree Celsius, and the minimum value is determined to be the fourth degree Celsius. The minimum value of the desired humidity range is the third humidity value, and the maximum value is the fourth humidity value. The third degree Celsius is greater than the first degree Celsius, the fourth degree Celsius is greater than the second degree Celsius, the third humidity value is less than the first humidity value, and the fourth humidity value is less than the second humidity value.

[0026] Optionally, after determining the desired temperature range and desired humidity range corresponding to the survey point based on the weather information of the current warehouse location, the method further includes:

[0027] When the surveyed temperature is within the desired temperature range and the surveyed humidity is within the desired humidity range, the surveying robot and / or the drone are controlled to continue traveling based on the preset survey route.

[0028] Optionally, after the step of controlling the survey robot and / or drone to travel based on a preset survey route upon receiving a disaster survey instruction, the method further includes:

[0029] Receive the second type information of goods at the survey point and the spatial information of the survey point sent by the survey robot and / or the drone;

[0030] When the type of goods is flammable and explosive, the space utilization rate of the goods is determined based on the space information;

[0031] When the space utilization rate exceeds the preset space utilization rate associated with flammable and explosive materials, an alarm prompt will be output.

[0032] Optionally, before the step of controlling the survey robot and / or drone to travel based on a preset survey route upon receiving a disaster survey instruction, the method further includes:

[0033] Control the surveying robot and / or the drone to clean the historical inventory data of the goods in the current warehouse to obtain valid inventory data;

[0034] The GPT4.0 model is trained using the effective inventory data, and the storage quantity and storage area of ​​each item in the current warehouse are determined based on the effective inventory data.

[0035] The storage quantity and storage area of ​​each item are input into the trained GPT4.0 model to obtain the preset survey route.

[0036] Optionally, after the step of controlling the surveying robot and / or the drone to clean and process the historical inventory data of the goods in the current warehouse to obtain valid inventory data, the method further includes:

[0037] The GPT4.0 model is trained using the effective inventory data, and the unsold value of each item is determined based on the effective inventory data.

[0038] The unsold inventory value is input into the trained GPT4.0 model to obtain the expected purchase value and replenishment time for each item.

[0039] The inventory management information for all goods in the warehouse is updated based on the expected purchase value and the replenishment time.

[0040] After the replenishment time is reached and the replenishment of each item is completed, the disaster assessment instruction is generated; or

[0041] The disaster survey command is generated based on a preset survey period.

[0042] In addition, to achieve the above objectives, the present invention also provides a disaster surveying device, which includes a memory, a processor, and a disaster surveying program stored in the memory and executable on the processor. When the disaster surveying program is executed by the processor, it implements the steps of the disaster surveying method described above.

[0043] In addition, to achieve the above objectives, the present invention also provides a computer-readable storage medium storing a disaster assessment program, which, when executed by a processor, implements the steps of the disaster assessment method described above.

[0044] This invention provides a disaster assessment method, a disaster assessment device, and a computer-readable storage medium. Upon receiving a disaster assessment command, the method controls a survey robot and / or a drone to travel along a preset survey route. It then receives survey temperature and humidity data sent by the survey robot and / or the drone, determines the time point at which the survey temperature and humidity data are received, and determines the corresponding survey points based on the preset survey route and the time point. Next, based on the weather information of the current warehouse location, it determines the expected temperature range and expected humidity range corresponding to the survey points. When the survey temperature is not within the expected temperature range, or the survey humidity is not within the expected humidity range, an alarm is output. It can be seen that by using a disaster assessment device such as a survey robot and / or a drone to survey various locations of stored goods in the current warehouse, and combining this with current weather information to predict the probability of fire in the current area, the method can inform the current survey points of potential danger, thus achieving fire prediction. Attached Figure Description

[0045] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present invention and, together with the description, serve to explain the principles of the invention. To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without any creative effort.

[0046] Figure 1 This is a flowchart illustrating the first embodiment of the disaster assessment method of the present invention;

[0047] Figure 2 This is a flowchart illustrating the second embodiment of the disaster assessment method of the present invention;

[0048] Figure 3 This is a flowchart illustrating the third embodiment of the disaster assessment method of the present invention;

[0049] Figure 4 This is a flowchart illustrating the fourth embodiment of the disaster assessment method of the present invention;

[0050] Figure 5 This is a flowchart illustrating the fifth embodiment of the disaster assessment method of the present invention;

[0051] Figure 6 These are schematic diagrams of the terminal hardware structure of various embodiments of the disaster assessment method of the present invention.

[0052] The realization of the objective, functional features and advantages of the present invention will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0053] It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

[0054] Among relevant warehouse safety management solutions, Chinese patent application number CN201920169596.6 discloses a warehouse fire safety monitoring system, which mainly discloses the use of video images of open flames and smoke detectors to determine the occurrence of a fire. However, this type of warehouse fire safety monitoring system can only issue an alarm when a fire occurs. By the time the warning is triggered, the fire has often already spread significantly, resulting in serious damage to warehouse goods. Therefore, current warehouse fire safety monitoring systems have the deficiency of being unable to predict the extent of a fire.

[0055] To address the aforementioned shortcomings, this invention proposes a disaster assessment method, the main solution of which includes the following steps:

[0056] Upon receiving a disaster survey instruction, control the survey robot and / or drone to travel along a preset survey route;

[0057] Receive survey temperature and survey humidity sent by the survey robot and / or the drone, and determine the time point at which the survey temperature and the survey humidity are received;

[0058] Based on the preset survey route and the receiving time, determine the survey points corresponding to the survey temperature and the survey humidity;

[0059] Based on the weather information of the current warehouse location, determine the expected temperature range and expected humidity range corresponding to the survey point;

[0060] An alarm is output when the measured temperature is not within the expected temperature range and the measured humidity is not within the expected humidity range.

[0061] This invention uses disaster detection devices, such as detection robots and / or drones, to survey various locations of stored goods in a warehouse. At the same time, it combines current weather information to predict the probability of fire in the current area, thereby informing the current survey location of the danger and achieving fire prediction.

[0062] To better understand the above technical solutions, exemplary embodiments of this disclosure will be described in more detail below with reference to the accompanying drawings. While exemplary embodiments of this disclosure are shown in the drawings, it should be understood that this disclosure can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of this disclosure to those skilled in the art.

[0063] First Embodiment

[0064] The solution in this embodiment is applied to a disaster survey device. This device can be an operable device such as a computer, mobile phone, or tablet that has an operating system and can control robots, drones, forklifts, robotic arms, and cameras to perform corresponding actions and collect corresponding information.

[0065] Please refer to Figure 1 In the first embodiment, the steps of the disaster assessment method include:

[0066] Step S10: Upon receiving a disaster survey instruction, control the survey robot and / or drone to travel along a preset survey route;

[0067] In this embodiment, fire detection can be performed using survey robots and / or drones, as well as to detect whether items have fallen from heights. Disaster detection commands can be set based on preset time periods, such as automatically triggering a disaster detection command every 2 or 4 hours, or they can be manually input, such as being triggered by a warehouse manager clicking the corresponding disaster trigger control. Upon receiving the disaster detection command, the survey device, such as a computer, sends the corresponding survey route to the survey robot and / or drone, and further controls the robot and / or drone to travel along the survey route, performing fire detection at each survey point along the route.

[0068] Optionally, to prevent goods from falling from heights due to improper operation by warehouse management personnel or machines after large-scale outbound or inbound processing, after a large-scale outbound or inbound process, the management personnel can click the corresponding disaster survey button. The computer will then receive the disaster survey instruction, send a survey route to the survey robot and / or drone, and control the survey robot and / or drone to travel along the survey route. The robot and / or drone will then detect the probability of goods falling from heights at each survey point along the survey route, and can also perform fire surveys at the same time.

[0069] The preset route can be a survey route set manually, or a relatively accurate route generated by an intelligent language model such as the GPT model. When a survey is required or when a preset survey time is reached, the disaster survey device receives the corresponding disaster survey instruction. Subsequently, the disaster survey device, such as a computer, sends the preset survey route to the survey robot and / or drone, and controls the survey robot and / or drone to travel based on the preset survey route.

[0070] For example, in a small warehouse, such as one with a height of only two meters, drones may have difficulty conducting surveys at that height. In this case, a surveying robot can be directly controlled to travel along a preset survey route. In a medium-sized warehouse, where a drone can independently survey the goods, it can also be directly controlled to travel along a preset survey route. In a large warehouse, a surveying robot and a drone can be combined, meaning both can perform surveying work together. The surveying robot can be responsible for surveying lower areas (e.g., below 2 meters), while the drone can survey higher areas (i.e., compensating for the limitations of the surveying robot by surveying areas above 2 meters). It should be noted that when the surveying robot and drone perform surveying actions simultaneously, their survey routes are completely different. The surveying robot can complete the survey of lower areas based on a preset route, while the drone can complete the survey of higher areas based on a preset route. The survey areas of the two are complementary and do not affect each other. The above data is for illustrative purposes only and is not intended to limit the invention.

[0071] Optionally, to ensure survey accuracy, when drones and survey robots perform survey tasks together, they can both survey the same location. For example, when a survey robot surveys goods at a low position, a drone can survey the same location from a higher position, thus avoiding false alarms caused by malfunctions in the survey robot's modules, such as temperature or humidity sensors. Similarly, a survey robot can also survey goods at higher positions to compensate for the malfunction.

[0072] Step S20: Receive the survey temperature and survey humidity sent by the survey robot and / or the drone, and determine the time point at which the survey temperature and the survey humidity are received;

[0073] In this embodiment, after the survey robot and / or drone arrives at the survey point on the preset survey route, it can obtain the survey temperature and humidity of the survey point through temperature and humidity sensors, and record the collection time corresponding to the survey temperature and humidity. Subsequently, the survey robot and / or drone can send the survey temperature, the survey humidity, and the collection time to the disaster assessment device. Based on this, the disaster assessment device can receive the survey temperature and humidity sent by the survey robot and / or the drone, and determine the receiving time of the survey temperature and humidity. Therefore, the survey temperature refers to the temperature corresponding to the area where the survey point is located, and the survey humidity refers to the humidity corresponding to the area where the survey point is located. The survey point can be a point corresponding to a single shelf, or a point corresponding to the same batch of goods.

[0074] Step S30: Determine the survey points corresponding to the survey temperature and the survey humidity based on the preset survey route and the receiving time point;

[0075] In this embodiment, the survey robot and / or drone travel at a constant speed. After receiving the receiving time point, the travel distance of the survey robot and / or drone can be calculated based on the receiving time point, and then the survey point can be determined based on the corresponding position on the survey route according to the travel distance.

[0076] Optionally, the survey points corresponding to the surveyed temperature and humidity can be determined according to the order of the received time points. For example, if there are 10 survey points set on the preset survey route, and the computer receives 10 sets of time points corresponding to the surveyed temperature and humidity, it can determine the surveyed temperature and humidity corresponding to each survey point according to the order of the received time points.

[0077] Step S40: Based on the weather information of the current warehouse location, determine the expected temperature range and expected humidity range corresponding to the survey point;

[0078] In this embodiment, before obtaining weather information, it is necessary to determine the address information of the current warehouse, and then obtain the current weather information based on the address information. The process of obtaining address information may include: obtaining the network address information of the current warehouse, and determining the weather information based on the network address information. The computer can determine the location of the current warehouse through the current network communication address, i.e., IP (Internet Protocol Address). For example, if the current location is in City B of Province A, Province B can be used as a search keyword to obtain the weather information corresponding to City B, and then the weather information of City B can be used as the weather information of the current warehouse. Since the types of goods in the warehouse are different, their corresponding expected temperature ranges and expected humidity ranges will also be different. Therefore, after determining the weather information, it is also necessary to receive the first type information of goods at the survey point sent by the survey robot and / or the drone.

[0079] Optionally, the current address of the warehouse can be obtained through a satellite positioning module, and then the corresponding weather information can be obtained based on that address.

[0080] After obtaining the weather information, it is also necessary to determine the current date. That is, based on the climate of the area where the warehouse is located, the current date, the type of goods at the survey point, and the most suitable temperature and humidity range at the current survey point at the corresponding time, the desired temperature range and the desired humidity range are obtained.

[0081] For example, in the current weather information, the weather is rainy, such as a heavy rainstorm; the nearest solar term to the current date is the summer solstice; and the type of goods is flammable, which is prone to combustion above 35℃. Therefore, the expected temperature range cannot exceed 30℃. Based on the current heavy rain information and the climate corresponding to the solar term, the expected temperature range for the survey point can be calculated as 0℃-20℃, meaning the first maximum temperature is 20 degrees Celsius and the second is 0 degrees Celsius. The expected humidity range is 40%-80%, where the first humidity value is 40% and the second is 80%. If the current weather is sunny, since sunny days correspond to higher temperatures and lower humidity, the calculated expected temperature range for the survey point is 10℃-30℃, meaning the third maximum temperature is 30 degrees Celsius and the fourth is 5 degrees Celsius; and the expected humidity range is 30%-70%, meaning the third humidity value is 30% and the fourth is 70%. It is understandable that the third and fourth degrees Celsius corresponding to sunny days are greater than the first and second degrees Celsius corresponding to rainy days, respectively, and the third and fourth humidity values ​​are less than the first and second humidity values ​​corresponding to rainy days, respectively.

[0082] Optionally, the desired temperature range and desired humidity range can be further optimized under other weather scenarios. For example, the maximum value of the desired temperature range for cloudy days is greater than the maximum value of the desired temperature range for rainy days.

[0083] Optionally, the desired temperature range and the desired humidity range can be further optimized based on the current geographical location of the warehouse. For example, if the current solar term is the summer solstice and the weather is cloudy, and the desired temperature range is 5℃-25℃, then if the current geographical location is in the Pearl River Basin, the desired temperature range can be optimized to 8℃-28℃.

[0084] It should be noted that the above parameters are for illustrative purposes only and are not intended to limit the scope of the invention.

[0085] Step S50: When the measured temperature is not within the expected temperature range and the measured humidity is not within the expected humidity range, an alarm prompt is output.

[0086] In this embodiment, the desired temperature range and the desired humidity range are the most suitable judgment ranges for determining whether a fire has occurred. If the measured temperature and the measured humidity are not within the corresponding ranges, it indicates that the probability of a fire occurring at the measurement point is relatively high. Therefore, the disaster measurement device can output alarm prompts for the corresponding area through the display, or it can output voice prompts.

[0087] In addition to fire alarms, other abnormal alerts can also be issued. Specifically, when the measured temperature exceeds the maximum value of the desired temperature and the measured humidity is less than the minimum value of the desired humidity curve, a warning index is determined as the first index, and a first-level alarm is issued.

[0088] For example, the first-level alarm prompt refers to a fire alarm prompt. When the measured temperature is 45℃, the maximum value of the expected temperature range is 35℃, the measured humidity is 25%, and the minimum value of the expected humidity range is 35%, it can be considered that the probability of a fire at the measured point is relatively high. Based on this, the warning index corresponding to the measured point is the first index, and at this time, the computer needs to output a voice or screen prompt indicating that there is a fire hazard at the measured point.

[0089] When the measured temperature is less than the minimum value of the expected temperature, and the measured humidity is greater than the maximum value of the expected temperature, the warning index is determined to be the second index, and a second-level alarm prompt is output.

[0090] For example, a second-level alarm could be an anomaly other than a fire. In this case, the measured temperature is 15°C, with a minimum expected temperature range of 20°C, while the measured humidity is 90%, with a maximum expected humidity range of 75%. This could indicate an anomaly at the measured location, such as a leaking beverage. In this scenario, the warning index can be set as the second index, and the computer can then output an alarm indicating an anomaly at that location.

[0091] Optionally, when the measured temperature and the measured humidity are within the desired range, the survey robot and / or the drone are controlled to continue traveling along the preset survey route. When both the measured temperature and humidity are within their respective desired ranges, the survey point is considered normal, and other survey points can continue to be surveyed according to the survey route.

[0092] In the technical solution disclosed in this embodiment, a surveying robot and / or drone are controlled by a computer or other surveying device to alternately or cooperate in performing corresponding disaster surveying tasks in different warehouse environments. The temperature and humidity information of the survey points are sent to the surveying device in real time. After comparing the information, the computer calculates the most suitable temperature and humidity range for the goods at the survey point based on the current weather, date, goods category, and geographical location. Then, it judges the current survey temperature and humidity. When the survey temperature and humidity are not within the expected temperature and humidity ranges, it indicates that there is a fire risk or other risks at the current survey point. At this time, the computer needs to output an alarm prompt to prevent the occurrence of fire or other disasters in advance and avoid damage to the warehouse goods.

[0093] Second Embodiment

[0094] Please refer to Figure 2 In the second embodiment, based on the first embodiment, after step S40, the method further includes:

[0095] Step S60: When the measured temperature is not within the desired temperature range, or the measured humidity is not within the desired humidity range, obtain the temperature change curve or humidity change curve of the measured point over a preset period.

[0096] In this embodiment, when one of the parameters, temperature and humidity, is not within the corresponding range, the survey point can be considered to be in an observation state. At this time, it is necessary to continuously observe the temperature change curve and humidity change curve of the survey point over a preset period of time, and determine whether the survey point is in an abnormal condition based on this.

[0097] For example, the current expected temperature range is 10 to 20 degrees Celsius, and the expected humidity range is 30% to 60%. At this time, the measured humidity is 40%, and the expected temperature is 40 degrees Celsius. Based on this, it can be considered that there is a potential anomaly in the current temperature. At this time, the surveying device controls the surveying robot and / or drone to continuously record the temperature of the surveyed points within 10 minutes and obtain the corresponding temperature change curve, and then make further judgments based on the temperature change curve.

[0098] Optionally, if the measured humidity is not within the desired humidity range, the humidity value is continuously recorded to obtain a humidity change curve.

[0099] It should be noted that the above parameters are for illustrative purposes only and are not intended to limit the scope of the invention.

[0100] Step S70: When the temperature change curve is a continuously increasing curve or the humidity change curve is a continuously decreasing curve, an alarm prompt is output.

[0101] In this embodiment, the temperature change curve is a continuously increasing curve, that is, the temperature corresponding to the current survey point is continuously increasing. At this time, it can be considered that the probability of a fire occurring at the current survey point is high, and the computer will directly output a fire alarm prompt. On the other hand, the humidity change curve is a continuously decreasing curve, which can be considered that there is a leak of goods at the current survey point, causing the humidity in the area to decrease. The computer can output a corresponding abnormal alarm prompt.

[0102] Optionally, when the temperature change curve is not a continuously increasing curve and the humidity change curve is not a continuously decreasing curve, the survey robot and / or the drone are controlled to continue traveling along the preset survey route. That is, when both the temperature change curve and the humidity change curve are in a flat state, it can be considered that there is no abnormality at the current survey point, and then the survey robot and / or the drone can be controlled to continue traveling according to the survey route.

[0103] In the technical solution disclosed in this embodiment, when one of the current measured temperature or measured humidity values ​​is not within the corresponding expected range, the temperature or humidity of the measured point is continuously monitored, and when the temperature is detected to be continuously increasing or the humidity is detected to be continuously decreasing, the corresponding type of alarm prompt is output to further prevent the occurrence of disasters and ensure the safety of goods in the warehouse.

[0104] Third Embodiment

[0105] Please refer to Figure 3 In the third embodiment, based on the first embodiment, after step S10, the method further includes:

[0106] Step S80: Receive the second type information of the goods at the survey point and the spatial information of the survey point sent by the survey robot and / or the drone;

[0107] In this embodiment, the presence or absence of any goods at the current survey point can be determined based on the type of goods and their stacking density. The survey robot and / or the drone are equipped with 3D sensing radar, enabling them to perceive the space occupied by the goods within the survey area.

[0108] Step S90: When the type of goods is flammable and explosive, determine the space utilization rate of the goods based on the space information;

[0109] In this embodiment, for flammable and explosive products such as glass bottled beverages, it is necessary to determine whether their stacking is normal, that is, whether the space occupied is normal. In other words, it is necessary to calculate the space utilization rate of glass bottled beverages based on space information, and then send the space utilization rate to the computer so that the computer can calculate whether the space utilization rate is normal.

[0110] Step S100: When the space utilization rate is greater than the preset space utilization rate associated with flammable and explosive materials, an alarm prompt is output.

[0111] In this embodiment, all flammable and explosive materials are associated with corresponding space utilization rates, such as the number of stackable layers. When the computer determines that the space utilization rate of flammable and explosive materials at the current survey point is greater than the preset space utilization rate, it can be considered that the flammable and explosive materials are placed too high or too densely, which may easily cause a disaster. The computer will then output corresponding alarm information.

[0112] In the technical solution disclosed in this embodiment, the type of goods at the survey point and the space utilization rate corresponding to the goods are used to determine whether the goods at the current survey point are in a dangerous state. When it is determined that they are in a dangerous state, a corresponding alarm prompt is output to improve the safety of goods in the warehouse.

[0113] Fourth embodiment

[0114] Please refer to Figure 4 In the fourth embodiment, based on the first embodiment, before step S10, the following steps are further included:

[0115] Step S110: Control the surveying robot and / or the drone to clean the historical inventory data of the goods in the current warehouse to obtain valid inventory data;

[0116] In this embodiment, when the computer-controlled survey robot and / or the drone travels along a preset survey route, the survey route needs to be generated. This survey route can be generated using a natural language processing model such as GPT4.0.

[0117] Before generating the survey route, the GPT4.0 model needs to be trained. The training set can be the valid inventory data corresponding to the historical inventory data of each item in the current warehouse. The historical inventory data includes the item category or region of each item, as well as the shipment and receipt data, shipment and receipt time, purchase location, order number, and production location of each item. The valid inventory data is the filtered historical inventory data. The filtered data is irrelevant to training the GPT4.0 model, such as the order number, production location, and purchase location of the item.

[0118] Step S120: Train the GPT4.0 model using the effective inventory data, and determine the storage quantity and storage area of ​​each item in the current warehouse based on the effective inventory data;

[0119] In this embodiment, after filtering and obtaining the valid product data of the warehouse, the model can be trained using the product data, and the overall layout of the current warehouse is also input into the model as a training set. Then, based on the valid inventory data, the remaining storage amount of each product in the current warehouse and the corresponding storage area are calculated, so that the trained GPT4.0 model can obtain the survey route based on the storage amount, storage area and corresponding semantics.

[0120] Step S130: Input the storage quantity and storage area of ​​each item into the trained GPT4.0 model to obtain the preset survey route.

[0121] In this embodiment, the storage quantity, storage area, and corresponding instructions such as "generate a survey route based on the storage quantity and storage area" of each item need to be input into the trained GPT4.0 model to obtain the corresponding survey route.

[0122] Specifically, if drones are needed to survey various locations in the warehouse, the storage quantity and storage area of ​​each item, as well as the "survey route suitable for drone flight survey based on the storage quantity and storage area of ​​each item" are input into the GPT4.0 model, the corresponding survey route for the drone can be obtained.

[0123] Optionally, in warehouses of different scenarios, preset survey routes corresponding to survey robots or survey routes corresponding to survey robots and drones when conducting joint surveys can be generated by modifying semantic instructions.

[0124] In the scheme disclosed in this embodiment, the GPT4.0 model is trained by using the effective data of each item in the current warehouse and the layout of the warehouse as the training set. Then, the remaining inventory information of the warehouse is used as the input instruction for the trained model to generate the most time-saving or most efficient survey route, thereby improving the survey efficiency of survey robots and / or drones.

[0125] The fifth embodiment is described in detail below. Figure 5 In the fifth embodiment, based on the fourth embodiment, after step S110, the method further includes:

[0126] Step S140: Train the GPT4.0 model using the effective inventory data, and determine the unsold value of each item based on the effective inventory data;

[0127] In this embodiment, the slow-moving value can be determined based on the ratio of the average purchase volume to the average sales volume of goods within a preset time period. That is, when the purchase volume is higher than the sales volume, the slow-moving value is greater than 1, and vice versa. The slow-moving value is used to measure the popularity of each item in the current warehouse. The smaller the slow-moving value, the higher the sales rate of the goods and the higher their popularity.

[0128] Step S150: Input the unsold value into the trained GPT4.0 model to obtain the expected purchase value and replenishment time for each item;

[0129] In this embodiment, the unsold inventory value can be used as the input parameter of the trained GPT4.0 model to obtain the expected purchase value and replenishment time for each product. That is, the purchase quantity and replenishment time of each product can be adjusted according to the current popularity of the product, thereby optimizing warehouse management and making the purchase quantity of each product tend to be within a normal range, which can avoid the dangerous situation of excessive or dense stacking of goods.

[0130] Step S160: Update the inventory management information of all goods in the warehouse based on the purchase expectation and the replenishment time;

[0131] Step S170: After the replenishment time is reached and the replenishment of each item is completed, the disaster survey instruction is generated.

[0132] In this embodiment, after detecting that all goods in the current warehouse have been replenished, in order to ensure the safety of the current goods, the disaster survey command can be directly generated, thereby controlling the survey robot and / or drone to perform the survey task based on the preset survey route.

[0133] Optionally, the disaster survey command can be generated based on a preset survey period.

[0134] In the technical solution disclosed in this embodiment, the unsold value of each item in the current warehouse is used as the input parameter of the trained GPT4.0 model. Then, the warehouse inventory management information is updated based on the data generated by the model, thereby improving the management efficiency of each item in the warehouse. After the warehouse completes the replenishment of the goods, a disaster survey command is generated, and the survey robot and / or drone are controlled to perform the survey task based on the preset survey route, so as to ensure the safety of each item after the warehouse is replenished.

[0135] Reference Figure 6 , Figure 6 This is a schematic diagram of the terminal structure of the hardware operating environment involved in the embodiments of the present invention.

[0136] like Figure 6As shown, the terminal may include: a processor 1001, such as a CPU; a network interface 1004; a user interface 1003; a memory 1005; and a communication bus 1002. The communication bus 1002 is used to enable communication between these components. The user interface 1003 may include a display screen and an input unit such as a keyboard. Optionally, the user interface 1003 may also include a standard wired interface or a wireless interface. The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface). The memory 1005 may be high-speed RAM or non-volatile memory, such as a disk drive. Optionally, the memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0137] Those skilled in the art will understand that Figure 6 The terminal structure shown does not constitute a limitation on the terminal and may include more or fewer components than shown, or combine certain components, or have different component arrangements.

[0138] like Figure 6 As shown, the memory 1004, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and a disaster assessment program.

[0139] exist Figure 6 In the terminal shown, network interface 1003 is mainly used to connect to the backend server and communicate with it; processor 1001 can call the disaster assessment program stored in memory 1005 and perform the following operations:

[0140] Upon receiving a disaster survey instruction, control the survey robot and / or drone to travel along a preset survey route;

[0141] Receive survey temperature and survey humidity sent by the survey robot and / or the drone, and determine the time point at which the survey temperature and the survey humidity are received;

[0142] Based on the preset survey route and the receiving time, determine the survey points corresponding to the survey temperature and the survey humidity;

[0143] Based on the weather information of the current warehouse location, determine the expected temperature range and expected humidity range corresponding to the survey point;

[0144] An alarm is output when the measured temperature is not within the expected temperature range and the measured humidity is not within the expected humidity range.

[0145] Furthermore, the processor 1001 can call the disaster assessment program stored in the memory 1005 and also perform the following operations:

[0146] When the measured temperature is not within the desired temperature range, or the measured humidity is not within the desired humidity range, obtain the temperature change curve or humidity change curve of the measured point over a preset period.

[0147] An alarm will be output when the temperature change curve is a continuously increasing curve or the humidity change curve is a continuously decreasing curve; or

[0148] When the temperature change curve is not the continuously increasing curve and the humidity change curve is not the continuously decreasing curve, the survey robot and / or the drone are controlled to continue traveling based on the preset survey route.

[0149] Furthermore, the processor 1001 can call the disaster assessment program stored in the memory 1005 and also perform the following operations:

[0150] When the measured temperature exceeds the maximum value of the desired temperature and the measured humidity is less than the minimum value of the desired humidity curve, the warning index is determined as the first index, and a first-level alarm is output; or

[0151] When the measured temperature is less than the minimum value of the expected temperature, and the measured humidity is greater than the maximum value of the expected temperature, the warning index is determined to be the second index, and a second-level alarm prompt is output.

[0152] Furthermore, the processor 1001 can call the disaster assessment program stored in the memory 1005 and also perform the following operations:

[0153] Obtain the network address information of the current warehouse, and determine the weather information based on the network address information;

[0154] Receive information on the first type of goods at the survey point sent by the survey robot and / or the drone;

[0155] When the first type of information is flammable, the step of determining the desired temperature range and desired humidity range corresponding to the survey point based on the weather information of the current warehouse location includes:

[0156] If the weather information indicates rain, the maximum value of the desired temperature range is determined to be a first degree Celsius, and the minimum value is determined to be a second degree Celsius; the minimum value of the desired humidity range is determined to be a first humidity value, and the maximum value is determined to be a second humidity value; or

[0157] If the weather information is sunny, the maximum value of the desired temperature range is determined to be the third degree Celsius, and the minimum value is determined to be the fourth degree Celsius. The minimum value of the desired humidity range is the third humidity value, and the maximum value is the fourth humidity value. The third degree Celsius is greater than the first degree Celsius, the fourth degree Celsius is greater than the second degree Celsius, the third humidity value is less than the first humidity value, and the fourth humidity value is less than the second humidity value.

[0158] Furthermore, the processor 1001 can call the disaster assessment program stored in the memory 1005 and also perform the following operations:

[0159] When the surveyed temperature is within the desired temperature range and the surveyed humidity is within the desired humidity range, the surveying robot and / or the drone are controlled to continue traveling based on the preset survey route.

[0160] Furthermore, the processor 1001 can call the disaster assessment program stored in the memory 1005 and also perform the following operations:

[0161] Receive the second type information of goods at the survey point and the spatial information of the survey point sent by the survey robot and / or the drone;

[0162] When the type of goods is flammable and explosive, the space utilization rate of the goods is determined based on the space information;

[0163] When the space utilization rate exceeds the preset space utilization rate associated with flammable and explosive materials, an alarm prompt will be output.

[0164] Furthermore, the processor 1001 can call the disaster assessment program stored in the memory 1005 and also perform the following operations:

[0165] Control the surveying robot and / or the drone to clean the historical inventory data of the goods in the current warehouse to obtain valid inventory data;

[0166] The GPT4.0 model is trained using the effective inventory data, and the storage quantity and storage area of ​​each item in the current warehouse are determined based on the effective inventory data.

[0167] The storage quantity and storage area of ​​each item are input into the trained GPT4.0 model to obtain the preset survey route.

[0168] Furthermore, the processor 1001 can call the disaster assessment program stored in the memory 1005 and also perform the following operations:

[0169] The GPT4.0 model is trained using the effective inventory data, and the unsold value of each item is determined based on the effective inventory data.

[0170] The unsold inventory value is input into the trained GPT4.0 model to obtain the expected purchase value and replenishment time for each item.

[0171] The inventory management information for all goods in the warehouse is updated based on the expected purchase value and the replenishment time.

[0172] After the replenishment time is reached and the replenishment of each item is completed, the disaster assessment instruction is generated; or

[0173] The disaster survey command is generated based on a preset survey period.

[0174] Furthermore, those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program includes program instructions and can be stored in a storage medium, which is a computer-readable storage medium. The program instructions are executed by at least one processor in the control terminal to implement the process steps of the embodiments of the above methods.

[0175] Therefore, the present invention also provides a computer-readable storage medium storing a disaster assessment program, which, when executed by a processor, implements the various steps of the disaster assessment method described in the above embodiments.

[0176] It should be noted that, since the storage medium provided in the embodiments of this application is the storage medium used to implement the methods of the embodiments of this application, those skilled in the art can understand the specific structure and variations of the storage medium based on the methods described in the embodiments of this application, and therefore will not be repeated here. All storage media used in the methods of the embodiments of this application fall within the scope of protection of this application.

[0177] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0178] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, as well as combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0179] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0180] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0181] It should be noted that any reference signs placed between parentheses in the claims should not be construed as limiting the claims. The word "comprising" does not exclude the presence of components or steps not listed in the claims. The word "a" or "an" preceding a component does not exclude the presence of a plurality of such components. The invention can be implemented by means of hardware comprising several different components and by means of a suitably programmed computer. In a unit claim enumerating several means, several of these means may be embodied by the same item of hardware. The use of the words first, second, and third, etc., does not indicate any order. These words can be interpreted as names.

[0182] Although preferred embodiments of the invention have been described, those skilled in the art, upon learning the basic inventive concept, can make other changes and modifications to these embodiments. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments as well as all changes and modifications falling within the scope of the invention.

[0183] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

[0184] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural or procedural transformations made based on the description and drawings of the present invention, or direct or indirect applications in other related technical fields, are similarly included within the scope of patent protection of the present invention.

Claims

1. A disaster assessment method, characterized in that, The disaster surveying method, applied to a disaster surveying device, includes: Upon receiving a disaster survey instruction, the system controls the survey robot and / or drone to travel along a preset survey route and conduct fire surveys at each survey point along the route. The system receives second-type information of goods at the survey point and spatial information of the survey point from the survey robot and / or the drone, wherein the survey robot and / or the drone is equipped with a three-dimensional sensing radar to perceive the space occupied by the goods in the survey area. When the type of goods is flammable and explosive, the space utilization rate of the goods is determined based on the space information; When the space utilization rate is greater than the preset space utilization rate associated with flammable and explosive materials, an alarm prompt will be output; Receive survey temperature and survey humidity sent by the survey robot and / or the drone, and determine the time point at which the survey temperature and the survey humidity are received; Based on the preset survey route and the receiving time, determine the survey points corresponding to the survey temperature and the survey humidity; The current address of the warehouse is obtained through a satellite positioning module, and the corresponding weather information is obtained based on the address; Based on the climate of the warehouse's current location, the current date, the types of goods at the survey points, and the most suitable temperature and humidity range at the corresponding time points, the desired temperature range and desired humidity range are obtained. When the measured temperature is less than the minimum value of the expected temperature and the measured humidity is greater than the maximum value of the expected temperature, the warning index is determined as the second index, and a second-level alarm prompt is output.

2. The disaster assessment method as described in claim 1, characterized in that, After the step of determining the desired temperature and humidity ranges based on the climate of the warehouse's current location, the current date, the type of goods at the survey points, and the most suitable temperature and humidity ranges at the corresponding time points, the method further includes: When the measured temperature is not within the desired temperature range, or the measured humidity is not within the desired humidity range, obtain the temperature change curve or humidity change curve of the measured point over a preset period. An alarm will be output when the temperature change curve is a continuously increasing curve or the humidity change curve is a continuously decreasing curve; or When the temperature change curve is not the continuously increasing curve and the humidity change curve is not the continuously decreasing curve, the survey robot and / or the drone are controlled to continue traveling based on the preset survey route.

3. The disaster assessment method as described in claim 1, characterized in that, After the step of determining the desired temperature and humidity ranges based on the climate of the warehouse's current location, the current date, the type of goods at the survey points, and the most suitable temperature and humidity ranges at the corresponding time points, the method further includes: When the measured temperature exceeds the maximum value of the desired temperature and the measured humidity is less than the minimum value of the desired humidity curve, the warning index is determined as the first index, and a first-level alarm is output; or When the measured temperature is less than the minimum value of the expected temperature, and the measured humidity is greater than the maximum value of the expected temperature, the warning index is determined to be the second index, and a second-level alarm prompt is output.

4. The disaster assessment method as described in claim 1, characterized in that, Before the step of obtaining the current warehouse address via satellite positioning module and obtaining the corresponding weather information based on the address, the method further includes: Obtain the network address information of the current warehouse, and determine the weather information based on the network address information; Receive information on the first type of goods at the survey point sent by the survey robot and / or the drone; When the first type of information is flammable, the step of determining the desired temperature range and desired humidity range corresponding to the survey point based on the weather information of the current warehouse location includes: If the weather information indicates rain, the maximum value of the desired temperature range is determined to be a first degree Celsius, and the minimum value is determined to be a second degree Celsius; the minimum value of the desired humidity range is determined to be a first humidity value, and the maximum value is determined to be a second humidity value; or If the weather information is sunny, the maximum value of the desired temperature range is determined to be the third degree Celsius, and the minimum value is determined to be the fourth degree Celsius. The minimum value of the desired humidity range is the third humidity value, and the maximum value is the fourth humidity value. The third degree Celsius is greater than the first degree Celsius, the fourth degree Celsius is greater than the second degree Celsius, the third humidity value is less than the first humidity value, and the fourth humidity value is less than the second humidity value.

5. The disaster assessment method as described in claim 1, characterized in that, After the step of determining the desired temperature and humidity ranges based on the climate of the warehouse's current location, the current date, the type of goods at the survey points, and the most suitable temperature and humidity ranges at the corresponding time points, the method further includes: When the surveyed temperature is within the desired temperature range and the surveyed humidity is within the desired humidity range, the surveying robot and / or the drone are controlled to continue traveling based on the preset survey route.

6. The disaster assessment method as described in claim 1, characterized in that, Before the step of controlling the survey robot and / or drone to travel based on a preset survey route upon receiving a disaster survey instruction, the method further includes: Control the surveying robot and / or the drone to clean the historical inventory data of the goods in the current warehouse to obtain valid inventory data; The GPT4.0 model is trained using the effective inventory data, and the storage quantity and storage area of ​​each item in the current warehouse are determined based on the effective inventory data. The storage quantity and storage area of ​​each item are input into the trained GPT4.0 model to obtain the preset survey route.

7. The disaster assessment method as described in claim 6, characterized in that, After the step of controlling the surveying robot and / or the drone to clean and process the historical inventory data of the goods in the current warehouse to obtain valid inventory data, the method further includes: The GPT4.0 model is trained using the effective inventory data, and the unsold value of each item is determined based on the effective inventory data. The unsold inventory value is input into the trained GPT4.0 model to obtain the expected purchase value and replenishment time for each item. The inventory management information for all goods in the warehouse is updated based on the expected purchase value and the replenishment time. After the replenishment time is reached and the replenishment of each item is completed, the disaster assessment instruction is generated; or The disaster survey command is generated based on a preset survey period.

8. A disaster assessment device, characterized in that, The disaster assessment device includes: a memory, a processor, and a disaster assessment program stored in the memory and executable on the processor. When the disaster assessment program is executed by the processor, it implements the steps of any one of the disaster assessment methods as claimed in claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a disaster assessment program, which, when executed by a processor, implements the steps of the disaster assessment method as described in any one of claims 1 to 7.

Images