A scientific instrument leasing analysis method and system based on big data

Abstract

The application is suitable for the field of computers, and provides a scientific instrument leasing analysis method and system based on big data, which comprises the following steps: acquiring position information of leasing equipment, wherein the leasing equipment comprises a first leasing equipment and a second leasing equipment; identifying a changed position relationship of the first leasing equipment and the second leasing equipment according to the position information of the leasing equipment; if it is identified that the first leasing equipment or the second leasing equipment to be used is within a mutual visual monitoring range, releasing use locking of a monitored leasing equipment; instructing at least one of the leasing equipment to monitor the monitored leasing equipment and generating monitoring information; and identifying and analyzing the monitoring information based on big data to determine whether there is a damaged use behavior in the monitoring information, wherein the application has the beneficial effects of reducing the labor intensity of operation and maintenance personnel, being capable of guaranteeing the integrity of the leasing equipment as much as possible, and reducing the risk of damage of the leasing equipment.

Description

Technical Field

[0001] This invention belongs to the field of computer science, and in particular relates to a scientific instrument rental analysis method and system based on big data. Background Technology

[0002] Instrument rental is essentially instrument sharing. Sellers rent instruments to intermediary platforms, which then rent them to users. The terms and conditions stipulate the time and fees, as well as the measures for breach of contract. Instrument sharing, especially of high-precision equipment, may sound unbelievable, but it is a real phenomenon and has been widely adopted abroad.

[0003] Instrument leasing can or is necessary when the following problems exist: lack of funds, lack of or unstable orders, temporary difficulties, mitigation of technical risks, reduction of investment pressure, and elimination of concerns. Instrument leasing, through methods such as rent-to-own and financial leasing, helps users to use relevant scientific analytical instruments and supporting equipment economically and conveniently, achieving a win-win situation. However, when the lessor leases scientific instruments to the lessee, considering the accuracy and cost of these instruments, such as mass spectrometers, maintenance personnel are often required to supervise the operation to prevent damage to these instruments, whether unintentional or intentional. This is especially true when multiple scientific instruments are leased to a single lessee at the same time, as the risk of instrument damage is greater, and relying solely on human supervision is quite difficult. Summary of the Invention

[0004] The purpose of this invention is to provide a scientific instrument rental analysis method and system based on big data, aiming to solve the problems mentioned in the background art.

[0005] The present invention is implemented as follows: On one hand, a method for analyzing the rental of scientific instruments based on big data, the method comprising the following steps:

[0006] Obtain the location information of the leased equipment, wherein the leased equipment includes a first leased equipment and a second leased equipment;

[0007] Identify the changing positional relationship between the first and second leased equipment based on the location information of the leased equipment;

[0008] If it is detected that the first or second leased device to be used is within the visual monitoring range of each other, the use lock of the monitored leased device is released;

[0009] Instruct at least one of the leased equipment to monitor the leased equipment being monitored and generate monitoring information;

[0010] Based on big data, the monitoring information is identified and analyzed to determine whether there is any destructive behavior in the monitoring information;

[0011] If it is determined that there is any unauthorized use in the monitoring information, the monitored leased equipment will be relocked and an early warning will be reported.

[0012] As a further aspect of the present invention, the step of identifying the changing positional relationship between the first rental equipment and the second rental equipment based on the location information of the rental equipment specifically includes:

[0013] Determine whether the first and second leased equipment are located within the same restricted area based on the information of the leased equipment;

[0014] When both the first leased equipment and the second leased equipment are within the same restricted area, the distance between the first leased equipment and the second leased equipment is identified.

[0015] As a further aspect of the present invention, the method further includes:

[0016] When the distance between the first leased device and the second leased device is not greater than the monitoring threshold distance, the first leased device and / or the second leased device are instructed to monitor and detect the leased device being monitored.

[0017] Determine whether the monitored leased equipment meets the conditions for unlocking. The conditions for unlocking include when the first leased equipment and / or the second leased equipment obtain the characteristic monitoring surface information of the monitored leased equipment.

[0018] As a further aspect of the present invention, after unlocking the monitored leased equipment, the method further includes:

[0019] Continue to monitor whether the first and second leased equipment remain within each other's visual monitoring range;

[0020] If so, then keep using the lock release function to continue to take effect;

[0021] Otherwise, the monitored rental equipment will be relocked until it is again within each other's visual monitoring range.

[0022] As a further aspect of the present invention, the step of identifying and analyzing monitoring information based on big data to determine whether there is any destructive usage behavior in the monitoring information includes:

[0023] The detection and monitoring information includes whether there are any changes in the movement of the monitored leased equipment, and the changes in movement include at least movement relative to a fixed point;

[0024] A request is sent to the monitored rental equipment to obtain the attitude data reported by the monitored rental equipment, wherein the attitude data includes at least one of angular velocity data and acceleration data;

[0025] When it is determined that the monitored rental equipment has moved, if it is further determined that at least one of the attitude data has changed beyond the corresponding set threshold, it is determined whether the time period corresponding to the movement change and the change exceeding the corresponding set threshold overlaps. The set threshold is set based on historical drop data.

[0026] If so, it is determined that the monitored rental equipment may have fallen;

[0027] If not, it is determined that the monitored leased equipment has been moved.

[0028] As a further aspect of the present invention, the method further includes:

[0029] When it is determined that the monitored rental equipment may fall, check whether any person who came into contact with the monitored rental equipment appears in the monitoring information;

[0030] If so, it is determined that the monitored rental equipment may have fallen due to human error;

[0031] Otherwise, it is determined that the monitored rental equipment may have fallen due to unexpected factors.

[0032] As a further aspect of the present invention, the method further includes:

[0033] If the monitored rental equipment cannot be identified based on the monitoring information, it is determined that the monitored rental equipment is obstructed.

[0034] The monitoring information includes residual footage of the monitored rental equipment, and the theoretical location of the monitored rental equipment is obtained based on the residual footage.

[0035] Instruct another rental device to send at least one infrared beam toward the theoretical location and detect whether feedback information is received. The feedback information is used to characterize that the monitored rental device has received the infrared beam and provided information feedback. When the housing of the monitored rental device is disassembled, the infrared receiver of the monitored rental device is disabled.

[0036] If not, it is determined that the monitored rental equipment may have been damaged and the monitored equipment is locked.

[0037] If so, it is determined that the monitored rental equipment is obstructed but is working normally.

[0038] As a further aspect of the present invention, another option is a scientific instrument rental and analysis system based on big data, the system comprising:

[0039] A location acquisition module is used to: acquire location information of rental equipment, wherein the rental equipment includes a first rental device and a second rental device;

[0040] The change-position recognition module is used to: identify the change-position relationship between the first rental equipment and the second rental equipment based on the location information of the rental equipment;

[0041] The lock release module is used to: release the lock of the monitored rental equipment when it is detected that the first or second rental equipment to be used is within the visual monitoring range of each other;

[0042] The monitoring module is used to: instruct at least one of the leased equipment to monitor the leased equipment being monitored and generate monitoring information;

[0043] The damage analysis module is used to: identify and analyze monitoring information based on big data to determine whether there is any damaging usage behavior in the monitoring information;

[0044] The locking and early warning module is used to: if it is determined that there is unauthorized use in the monitoring information, relock the monitored leased equipment and report the early warning information.

[0045] This invention provides a scientific instrument rental analysis method and system based on big data. By identifying the changing positional relationship between a first and second rental device based on the location information of the rental equipment, and if either the first or second rental device is identified as being within each other's visual monitoring range, the usage lock of the monitored rental device is released. Based on ensuring that at least two rental devices establish a mutual monitoring mechanism, the rental device can be unlocked for use. Furthermore, at least one of the rental devices is instructed to monitor the monitored rental device, generating monitoring information. Based on big data, the monitoring information is identified and analyzed to determine if any destructive usage behavior exists. If unauthorized usage behavior is detected, the monitored rental device is relocked and a warning is reported. This method takes into account the actual usage environment of the lessee and analyzes the monitoring data based on the established mutual monitoring mechanism. Therefore, in the actual usage environment, there is no need for additional monitoring equipment and maintenance personnel, or the workload of maintenance personnel can be reduced. This approach can maximize the integrity of the rental equipment and reduce the risk of damage. Attached Figure Description

[0046] Figure 1 This is the main flowchart of a scientific instrument rental analysis method based on big data.

[0047] Figure 2 This is a flowchart illustrating the changing positional relationship between the first and second leased equipment based on the location information of the leased equipment in a big data-based scientific instrument rental analysis method.

[0048] Figure 3 This is a flowchart for determining whether there is any damage or misuse behavior in the monitoring information of a scientific instrument rental analysis method based on big data.

[0049] Figure 4 This is a flowchart illustrating how to prevent the disassembly and damage of monitored rental equipment when it is obstructed, within a scientific instrument rental analysis method based on big data.

[0050] Figure 5 This is a main structure diagram of a scientific instrument rental and analysis system based on big data. Implementation

[0051] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0052] The specific implementation of the present invention will be described in detail below with reference to specific embodiments.

[0053] This invention provides a scientific instrument rental analysis method and system based on big data, which solves the technical problems in the background art.

[0054] The model and type of the rental equipment in this application embodiment are not limited. If necessary, for the convenience of testing and actual needs, functions in the prior art can be added to the rental equipment. These functions can be implemented by components or parts, such as positioning functions.

[0055] like Figure 1 The diagram shown is a main flowchart of a big data-based scientific instrument rental analysis method according to an embodiment of the present invention. The big data-based scientific instrument rental analysis method includes:

[0056] Step S10: Obtain the location information of the rental equipment, which includes a first rental device and a second rental device; there is at least one first rental device and one second rental device. In some cases, the first and second rental devices can be interchanged, and the first and second rental devices do not represent a limitation on the function of the rental equipment.

[0057] Step S11: Identify the changing positional relationship between the first and second rental devices based on the location information of the rental devices; the meaning of the changing positional relationship is that the location of the rental devices may change with use, but there should be some relationship between the two rental devices, and this relationship is the range of mutual visual monitoring described in the next step.

[0058] Step S12: If the first or second rental device to be used is identified as being within each other's visual monitoring range, the use lock of the monitored rental device is released; that is, when there are at least two rental devices that can monitor one of the (to be used) rental devices, the original use lock of the rental device is released; this use lock can be released by remotely issuing a command to unlock the rental device, or by remotely releasing the touch screen use lock or waking up the touch screen (when the rental device can only be used by using the touch screen).

[0059] Step S13: Instruct at least one of the leased equipment to monitor the leased equipment being monitored and generate monitoring information; such monitoring information may include video information;

[0060] Step S14: Based on big data, identify and analyze the monitoring information to determine whether there is any damaging behavior in the monitoring information; damaging behavior refers to behavior that causes damage to the normal use of the rental equipment or has the potential for damage, such as falling to the ground;

[0061] Step S15: If unauthorized use is detected in the monitoring information, the monitored leased equipment will be relocked and a warning message will be reported. Unlocking will only be restored after confirmation from the lessor.

[0062] In this embodiment, the changing positional relationship between the first and second rental devices is identified based on the location information of the rental devices. If the first or second rental device to be used is identified as being within each other's visual monitoring range, the use lock of the monitored rental device is released. Based on ensuring that at least two rental devices establish a mutual monitoring mechanism, the rental device can be unlocked for use. Furthermore, at least one of the rental devices is instructed to monitor the monitored rental device, generating monitoring information. Based on big data analysis, the monitoring information is identified to determine if there is any destructive usage behavior. If it is determined that there is any illegal usage behavior, the monitored rental device is relocked and a warning message is reported. This approach takes into account the actual usage environment of the lessee and analyzes the monitoring data based on the established mutual monitoring mechanism. Therefore, in the actual usage environment, there is no need for additional monitoring equipment and maintenance personnel, or the workload of maintenance personnel can be reduced. This approach can ensure the integrity of the rental equipment as much as possible and reduce the risk of damage to the rental equipment.

[0063] like Figure 2 As shown, in a preferred embodiment of the present invention, the step of identifying the changing positional relationship between the first rental device and the second rental device based on the location information of the rental device specifically includes:

[0064] Step S111: Determine whether the first leased equipment and the second leased equipment are located within the same restricted area based on the information of the leased equipment;

[0065] Step S112: When both the first leased equipment and the second leased equipment are within the same limited area of ​​use, identify the distance between the first leased equipment and the second leased equipment.

[0066] Understandably, the same restricted use area is generally the lessee's work area. The positioning device can be installed at the power socket inside the rental equipment. Positioning can be achieved through built-in GPS and rechargeable battery, making it easy to monitor the location changes of the rental equipment. The rental equipment can be equipped with 4G / 5G IoT, wireless, and Bluetooth. When the wireless network is interrupted, it will automatically switch to 4G / 5G signal to ensure smooth data transmission and alert the user to wireless network failure.

[0067] In a preferred embodiment of the present invention, the method further includes:

[0068] Step S20: When the distance between the first leased device and the second leased device is not greater than the monitoring threshold distance, instruct the first leased device and / or the second leased device to monitor and detect the leased device being monitored;

[0069] Step S21: Determine whether the monitored leased equipment meets the conditions for unlocking. The conditions for unlocking include when the first leased equipment and / or the second leased equipment obtain the characteristic monitoring surface information of the monitored leased equipment.

[0070] It is understandable that, considering the lessee's usage environment and the possibility of leasing more than one device, this embodiment can ensure that a visual monitoring mechanism is established between at least two leased devices to ensure that they can be used normally in a reasonable and compliant manner as much as possible.

[0071] In a preferred embodiment of the present invention, after unlocking the monitored leased equipment, the method further includes:

[0072] Step S121: Continue to detect whether the first leased equipment and the second leased equipment remain within each other's visual monitoring range;

[0073] Step S122: If yes, then keep using the lock release function in effect;

[0074] Step S123: Otherwise, relock the monitored rental equipment until it is again within each other's visual monitoring range.

[0075] It should be understood that, in conjunction with the previous embodiment, this embodiment provides a method to prevent the leased equipment from being taken out of the restricted use area or losing monitoring after unlocking and use, and can always ensure that if normal use is required, it must be within the range of mutual visual monitoring.

[0076] like Figure 3 As shown, in a preferred embodiment of the present invention, the step of identifying and analyzing monitoring information based on big data to determine whether there is any destructive behavior in the monitoring information includes:

[0077] Step S141: Detect whether there is any movement or change of the monitored rental equipment in the monitoring information. The movement or change includes at least movement relative to a fixed point. Here, the movement or change mainly refers to a change in position, including changes in vertical space.

[0078] Step S142: Send an acquisition command to the monitored rental equipment to acquire the attitude data reported by the monitored rental equipment, wherein the attitude data includes at least one of angular velocity data and acceleration data;

[0079] Step S143: When it is determined that the monitored rental equipment has moved, if it is determined that at least one of the attitude data has changed beyond the corresponding set threshold, proceed to the next step.

[0080] Step S144: Determine whether there is any overlap between the time periods corresponding to the movement changes and the changes exceeding the corresponding set thresholds. The set thresholds are set based on historical drop data. For example, based on historical drop data, it is determined that the angular velocity range of the monitored rental equipment falling from the designated placement platform is 5-15 rad / s. The acceleration is generally set based on the local gravitational acceleration. The set thresholds are generally selected from a large amount of historical drop data. The specific process is not described here.

[0081] Step S145: If yes, it is determined that the monitored rental equipment may have fallen;

[0082] Step S146: If not, it is determined that the monitored leased equipment has been moved.

[0083] In this embodiment, when it is determined that the monitored rental equipment has moved, if it is further determined that at least one of the attitude data has changed beyond the corresponding set threshold, it is determined whether the time period corresponding to the movement change and the change exceeding the corresponding set threshold overlaps. The purpose of determining whether the time period overlaps is to determine whether there is a correlation between the movement change and the change in attitude data. That is, a positional movement has occurred in vertical space, and this positional movement has caused the attitude parameters to change beyond the corresponding set threshold. It is highly unlikely that it is a human-caused movement, because the attitude parameters of a human-caused movement generally do not reach the attitude parameters corresponding to a fall, unless the person and the monitored rental equipment fall together.

[0084] In a preferred embodiment of the present invention, the method further includes:

[0085] Step S30: When it is determined that the monitored rental equipment may fall, check whether there are any people in contact with the monitored rental equipment in the monitoring information;

[0086] Step S31: If yes, it is determined that the monitored rental equipment may have fallen due to human factors;

[0087] Step S32: Otherwise, it is determined that the monitored rental equipment may have fallen due to unexpected factors.

[0088] It is understood that this embodiment can further determine the cause of the rental equipment falling, and combine the monitoring information to determine whether the person who came into contact with the monitored rental equipment is the cause or the cause of the fall. This makes it easier to determine the responsibility when the rental equipment is damaged.

[0089] like Figure 4 As shown, in a preferred embodiment of the present invention, the method further includes:

[0090] Step S40: If the monitored rental equipment cannot be identified based on the monitoring information, it is determined that the monitored rental equipment is obstructed;

[0091] Step S41: Obtain the residual footage of the monitored rental equipment contained in the monitoring information, and obtain the theoretical location of the monitored rental equipment based on the residual footage;

[0092] Step S42: Instruct another leased device to send at least one beam of infrared light toward the theoretical location;

[0093] Step S43: Detect whether feedback information is received. The feedback information is used to characterize the information feedback after the monitored rental equipment receives infrared light. When the housing of the monitored rental equipment is disassembled, the infrared receiver of the monitored rental equipment fails. The reason for sending at least one infrared beam is that the monitored rental equipment may move to a certain position, and the theoretical position may not be accurate enough. Therefore, multiple angles and multiple infrared beams can be emitted to try to find the infrared receiver in the theoretical position. When the housing of the monitored rental equipment is disassembled, the infrared receiver of the monitored rental equipment fails. The infrared receiver can form a logic circuit structure with the photosensitive element. When the housing is disassembled, light generally enters. At this time, the photosensitive element senses the light, causing the infrared receiver to stop working.

[0094] Step S44: If not, it is determined that the monitored rental equipment may have been damaged and the monitored equipment is locked; at this time, authorization from the lessor is required to unlock it.

[0095] Step S45: If yes, then it is determined that the monitored rental equipment is obstructed but is working normally.

[0096] It is understood that this embodiment provides a method to prevent the monitored rental equipment from being dismantled and damaged when the monitored rental equipment is obstructed. This is because the rental equipment may malfunction due to improper operation during use, and there is a risk that the lessee may dismantle the rental equipment without authorization. Through this embodiment, the integrity of the rental equipment can be guaranteed as much as possible, and the risk of the rental equipment being dismantled without authorization can be reduced.

[0097] like Figure 5 As shown, in another preferred embodiment of the present invention, a scientific instrument rental and analysis system based on big data is provided, the system comprising:

[0098] Location acquisition module 100 is used to: acquire location information of rental equipment, wherein the rental equipment includes a first rental equipment and a second rental equipment;

[0099] The change position recognition module 200 is used to: identify the change position relationship between the first rental equipment and the second rental equipment based on the location information of the rental equipment;

[0100] The lock release module 300 is used to: release the lock of the monitored rental equipment when it is detected that the first rental equipment or the second rental equipment to be used is within the visual monitoring range of each other;

[0101] Monitoring module 400 is used to: instruct at least one of the leased equipment to monitor the leased equipment being monitored and generate monitoring information;

[0102] Damage analysis module 500 is used to: identify and analyze monitoring information based on big data to determine whether there is any damaging usage behavior in the monitoring information;

[0103] The locking and early warning module 600 is used to: if it is determined that there is illegal use in the monitoring information, relock the monitored leased equipment and report the early warning information.

[0104] The above embodiments of the present invention provide a scientific instrument rental analysis method based on big data, and a scientific instrument rental analysis system based on big data. By identifying the changing positional relationship between a first and second rental device based on the location information of the rental equipment, if the first or second rental device to be used is identified as being within each other's visual monitoring range, the use lock of the monitored rental device is released. Based on ensuring that at least two rental devices establish a mutual monitoring mechanism, the rental device can be unlocked for use. Furthermore, at least one of the rental devices is instructed to monitor the monitored rental device, generating monitoring information. Based on big data, the monitoring information is identified and analyzed to determine whether there is any destructive usage behavior. If it is determined that there is any illegal usage behavior, the monitored rental device is relocked and a warning message is reported. This method takes into account the actual usage environment of the lessee, analyzes the monitoring data based on the established mutual monitoring mechanism, and eliminates the need for additional monitoring equipment and maintenance personnel in the actual usage environment, or reduces the workload of maintenance personnel, thus ensuring the integrity of the rental equipment as much as possible and reducing the risk of damage to the rental equipment.

[0105] In order for the above methods and systems to operate smoothly, the system may include more or fewer components than those described above, or combine certain components, or different components, in addition to the various modules mentioned above. For example, it may include input / output devices, network access devices, buses, processors, and memory.

[0106] The processor referred to can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor. This processor is the control center of the system, connecting various parts through various interfaces and lines.

[0107] The aforementioned memory can be used to store computer and system programs and / or modules. The aforementioned processor implements the various functions mentioned above by running or executing the computer programs and / or modules stored in the memory, and by calling the data stored in the memory. The memory may mainly include a program storage area and a data storage area. The program storage area may store the operating system, at least one application program required for a function (such as information collection template display function, product information publishing function, etc.). The data storage area may store data created based on the use of the berth status display system (such as product information collection templates corresponding to different product types, product information that different product providers need to publish, etc.). In addition, the memory may include high-speed random access memory, and may also include non-volatile memory, such as hard disk, memory, plug-in hard disk, smart media card (SMC), secure digital (SD) card, flash card, at least one disk storage device, flash memory device, or other volatile solid-state storage device.

[0108] It should be understood that although the steps in the flowcharts of the various embodiments of the present invention are shown sequentially according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless explicitly stated herein, there is no strict order restriction on the execution of these steps, and they can be executed in other orders. Moreover, at least some steps in the various embodiments may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily completed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be performed alternately or in turn with other steps or at least a portion of the sub-steps or stages of other steps.

[0109] 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.

[0110] The embodiments described above are merely illustrative of several implementations of the present invention, and while the descriptions are specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the present invention, and these modifications and improvements all fall within the scope of protection of the present invention. Therefore, the scope of protection of this patent should be determined by the appended claims.

[0111] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A scientific instrument rental analysis method based on big data, characterized in that, The method includes: Obtain the location information of the leased equipment, wherein the leased equipment includes a first leased equipment and a second leased equipment; Identify the changing positional relationship between the first and second leased equipment based on the location information of the leased equipment; If it is detected that the first or second leased device to be used is within the visual monitoring range of each other, the use lock of the monitored leased device is released; Instruct at least one of the leased equipment to monitor the leased equipment being monitored and generate monitoring information; Based on big data, the monitoring information is identified and analyzed to determine whether there is any destructive behavior in the monitoring information; If it is determined that there is any unauthorized use in the monitoring information, the monitored leased equipment will be relocked and a warning message will be reported. The process of identifying and analyzing monitoring information based on big data to determine whether there is any destructive behavior in the monitoring information includes: The detection and monitoring information includes whether there are any changes in the movement of the monitored leased equipment, and the changes in movement include at least movement relative to a fixed point; A request is sent to the monitored rental equipment to obtain the attitude data reported by the monitored rental equipment, wherein the attitude data includes at least one of angular velocity data and acceleration data; When it is determined that the monitored rental equipment has moved, if it is further determined that at least one of the attitude data has changed beyond the corresponding set threshold, it is determined whether the time period corresponding to the movement change and the change exceeding the corresponding set threshold overlaps. The set threshold is set based on historical drop data. If so, it is determined that the monitored rental equipment may have fallen; If not, it is determined that the monitored rental equipment has been moved; The method further includes: When it is determined that the monitored rental equipment may fall, check whether any person who came into contact with the monitored rental equipment appears in the monitoring information; If so, it is determined that the monitored rental equipment may have fallen due to human error; Otherwise, it is determined that the monitored rental equipment may have fallen due to unexpected factors.

2. The scientific instrument rental analysis method based on big data according to claim 1, characterized in that, The step of identifying the changing positional relationship between the first and second leased equipment based on the location information of the leased equipment specifically includes: Determine whether the first and second leased equipment are located within the same restricted area based on the information of the leased equipment; When both the first leased equipment and the second leased equipment are within the same restricted area, the distance between the first leased equipment and the second leased equipment is identified.

3. The scientific instrument rental analysis method based on big data according to claim 2, characterized in that, The method further includes: When the distance between the first leased device and the second leased device is not greater than the monitoring threshold distance, the first leased device and / or the second leased device are instructed to monitor and detect the leased device being monitored. Determine whether the monitored leased equipment meets the conditions for unlocking. The conditions for unlocking include when the first leased equipment and / or the second leased equipment obtain the characteristic monitoring surface information of the monitored leased equipment.

4. The scientific instrument rental analysis method based on big data according to claim 1, characterized in that, After unlocking the monitored leased equipment, the method further includes: Continue to monitor whether the first and second leased equipment remain within each other's visual monitoring range; If so, then keep using the lock release function to continue to take effect; Otherwise, the monitored rental equipment will be relocked until it is again within each other's visual monitoring range.

5. The scientific instrument rental analysis method based on big data according to any one of claims 1-4, characterized in that, The method further includes: If the monitored rental equipment cannot be identified based on the monitoring information, it is determined that the monitored rental equipment is obstructed. The monitoring information includes residual footage of the monitored rental equipment, and the theoretical location of the monitored rental equipment is obtained based on the residual footage. Instruct another rental device to send at least one infrared beam toward the theoretical location and detect whether feedback information is received. The feedback information is used to characterize that the monitored rental device has received the infrared beam and provided information feedback. When the housing of the monitored rental device is disassembled, the infrared receiver of the monitored rental device is disabled. If not, it is determined that the monitored rental equipment may have been damaged and the monitored equipment is locked. If so, it is determined that the monitored rental equipment is obstructed but is working normally.

6. A scientific instrument rental and analysis system based on big data, characterized in that, The system includes: A location acquisition module is used to: acquire location information of rental equipment, wherein the rental equipment includes a first rental device and a second rental device; The change-position recognition module is used to: identify the change-position relationship between the first rental equipment and the second rental equipment based on the location information of the rental equipment; The lock release module is used to: release the lock of the monitored rental equipment when it is detected that the first or second rental equipment to be used is within the visual monitoring range of each other; The monitoring module is used to: instruct at least one of the leased equipment to monitor the leased equipment being monitored and generate monitoring information; The damage analysis module is used to: identify and analyze monitoring information based on big data to determine whether there is any damaging usage behavior in the monitoring information; The locking and early warning module is used to: if it is determined that there is unauthorized use in the monitoring information, relock the monitored leased equipment and report the early warning information; The process of identifying and analyzing monitoring information based on big data to determine whether there is any destructive behavior in the monitoring information includes: The detection and monitoring information includes whether there are any changes in the movement of the monitored leased equipment, and the changes in movement include at least movement relative to a fixed point; A request is sent to the monitored rental equipment to obtain the attitude data reported by the monitored rental equipment, wherein the attitude data includes at least one of angular velocity data and acceleration data; When it is determined that the monitored rental equipment has moved, if it is further determined that at least one of the attitude data has changed beyond the corresponding set threshold, it is determined whether the time period corresponding to the movement change and the change exceeding the corresponding set threshold overlaps. The set threshold is set based on historical drop data. If so, it is determined that the monitored rental equipment may have fallen; If not, it is determined that the monitored rental equipment has been moved; Also includes: When it is determined that the monitored rental equipment may fall, check whether any person who came into contact with the monitored rental equipment appears in the monitoring information; If so, it is determined that the monitored rental equipment may have fallen due to human error; Otherwise, it is determined that the monitored rental equipment may have fallen due to unexpected factors.

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