Navigation-aid light risk assessment method and system based on multi-level heterogeneous data

Abstract

The embodiment of the invention provides a navigation-aid light risk assessment method and system based on multi-level heterogeneous data, and belongs to the technical field of risk early warning. The method comprises the following steps: determining a target hierarchy corresponding to a target object and an association index corresponding to each sub-hierarchy in the target hierarchy; obtaining an index score corresponding to the associated index of each sub-hierarchy in the target hierarchy; performing information fusion on the index scores to obtain a hierarchy score value corresponding to each sub-hierarchy in the target hierarchy; determining an initial risk assessment result corresponding to each sub-hierarchy in the target hierarchy according to the hierarchy score; and determining a target risk assessment result of the target object according to the initial risk assessment result. According to the risk assessment method and device, the problem that the risk assessment accuracy is low due to the fact that the assessment result depends on the personal experience of deep employees and lacks scientific argumentation and objective judgment when risk assessment is carried out in the prior art is solved, the risk assessment accuracy in the navigational light is improved, and the effectiveness of risk management measures is further improved.

Description

Technical Field

[0001] The present invention relates to the technical field of risk warning, and in particular to a method and system for risk assessment of navigation lighting based on multi-level heterogeneous data. Background Art

[0002] The airport navigation lighting system is a key component to ensure aviation safety, and it involves many areas and equipment. The normal operation of these equipment and areas is crucial to ensure the take-off and landing of aircraft and ground taxiing. However, if the airport navigation lighting system is abnormal, it will have a serious impact on the normal operation of the airport. The current operation guarantee system of airport navigation lighting mainly focuses on emergency repair, that is, emergency repair when equipment or areas fail. Although this method can quickly restore the normal operation of the equipment to a certain extent, it lacks the prediction and early intervention mechanism for potential risks, resulting in frequent emergency events. What is more serious is that in emergency situations, there is often a shortage of spare parts, which further aggravates the severity of the problem. In order to solve this problem, it is necessary to conduct a comprehensive risk assessment of the airport navigation lighting system. However, the current risk assessment method relies too much on the personal experience of senior employees and lacks scientific quantitative analysis methods. This subjective risk assessment method makes the risk assessment largely remain at the subjective level, lacking scientific argumentation and objective judgment methods. This not only affects the accuracy of risk assessment, but also limits the effectiveness of risk management measures. Summary of the invention

[0003] The main purpose of the embodiments of the present invention is to provide a method and system for risk assessment of navigation lights based on multi-level heterogeneous data, aiming to solve the problem in related technologies that when conducting risk assessment, the assessment results rely on the personal experience of senior employees and lack scientific argumentation and objective judgment, which leads to low accuracy of risk assessment.

[0004] In a first aspect, an embodiment of the present invention provides a method for risk assessment of navigation lights based on multi-level heterogeneous data, comprising:

[0005] Determine a target level corresponding to the target object and an associated indicator corresponding to each sub-level in the target level;

[0006] Obtaining an indicator score corresponding to the associated indicator corresponding to each of the sub-levels in the target level;

[0007] Performing information fusion on the indicator scores to obtain the hierarchical score corresponding to each sub-level in the target level;

[0008] Determine the initial risk assessment result corresponding to each sub-level in the target level according to the level scoring score;

[0009] A target risk assessment result corresponding to the target object is determined according to the initial risk assessment result.

[0010] In a second aspect, an embodiment of the present invention provides a navigation lighting risk assessment system based on multi-level heterogeneous data, including:

[0011] An indicator determination module, used to determine a target level corresponding to a target object and an associated indicator corresponding to each sub-level in the target level;

[0012] A score obtaining module, used for obtaining an indicator score corresponding to the associated indicator corresponding to each of the sub-levels in the target level;

[0013] A score calculation module, used for performing information fusion on the indicator score to obtain a level score corresponding to each sub-level in the target level;

[0014] An initial assessment module, used to determine an initial risk assessment result corresponding to each sub-level in the target level according to the level scoring score;

[0015] The target assessment module is used to determine the target risk assessment result corresponding to the target object according to the initial risk assessment result.

[0016] In a third aspect, an embodiment of the present invention further provides a terminal device, comprising a processor, a memory, a computer program stored in the memory and executable by the processor, and a data bus for realizing connection and communication between the processor and the memory, wherein when the computer program is executed by the processor, the steps of any one of the methods for risk assessment of navigation lights based on multi-level heterogeneous data provided in the specification of the present invention are implemented.

[0017] In a fourth aspect, an embodiment of the present invention further provides a storage medium for computer-readable storage, characterized in that the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement any step of the method for risk assessment of navigation lights based on multi-level heterogeneous data as provided in the specification of the present invention.

[0018] The embodiment of the present invention provides a method and system for assessing the risk of navigation lights based on multi-level heterogeneous data, the method comprising: determining the target level corresponding to the target object and the associated indicators corresponding to each sub-level in the target level, so as to systematically analyze and understand the structure of the target object, and ensure that each sub-level can be paid attention to and managed; then obtaining the indicator score corresponding to the associated indicators corresponding to each sub-level in the target level; performing information fusion on the indicator score to obtain the level score corresponding to each sub-level in the target level, so that the current information of each sub-level of the target object can be quantified, so as to more objectively analyze the performance of each sub-level; then determining the initial risk assessment result corresponding to each sub-level in the target level according to the level score, so as to timely identify potential risks, provide suggestions for subsequent risk management, and reduce the blindness of decision-making; finally determining the target risk assessment result corresponding to the target object according to the initial risk assessment result. The method solves the problem in the related art that the assessment result depends on the personal experience of senior employees when conducting risk assessment, lacks scientific argumentation and objective judgment, and thus leads to low accuracy of risk assessment, improves the accuracy of risk assessment in navigation lights, and further improves the effectiveness of risk management measures. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0020] Figure 1 A flowchart of a method for risk assessment of navigation lights based on multi-level heterogeneous data provided by an embodiment of the present invention;

[0021] Figure 2 A schematic diagram of the dependency relationship between various sub-levels in a target level provided by an embodiment of the present invention;

[0022] Figure 3 A schematic diagram of the module structure of a navigation lighting risk assessment system based on multi-level heterogeneous data provided by an embodiment of the present invention;

[0023] Figure 4 A schematic block diagram of the structure of a terminal device provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] The flowcharts shown in the accompanying drawings are only examples and do not necessarily include all the contents and operations / steps, nor must they be executed in the order described. For example, some operations / steps may also be decomposed, combined or partially merged, so the actual execution order may change according to actual conditions.

[0026] It should be understood that the terms used in this specification of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. As used in the specification of the present invention and the appended claims, unless the context clearly indicates otherwise, the singular forms "a", "an" and "the" are intended to include plural forms.

[0027] The embodiment of the present invention provides a method and system for risk assessment of navigation lights based on multi-level heterogeneous data. The method for risk assessment of navigation lights based on multi-level heterogeneous data can be applied to a terminal device, which can be an electronic device such as a tablet computer, a laptop computer, a desktop computer, a personal digital assistant, and a wearable device. The terminal device can be a server or a server cluster.

[0028] Some embodiments of the present invention are described in detail below in conjunction with the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments can be combined with each other.

[0029] Please refer to Figure 1 , Figure 1 A flowchart of a method for risk assessment of navigation lights based on multi-level heterogeneous data is provided in an embodiment of the present invention.

[0030] like Figure 1 As shown, the risk assessment method for navigation lighting based on multi-level heterogeneous data includes steps S101 to S105.

[0031] Step S101: Determine a target level corresponding to a target object and an associated index corresponding to each sub-level in the target level.

[0032] For example, the target object is a navigation lighting system. To ensure that abnormal objects in the navigation lighting system can be found in time, the navigation lighting system is hierarchically divided to obtain a corresponding target level. The target level can be obtained by region or by device type.

[0033] For example, the target level contains multiple sub-levels, and each sub-level involves corresponding associated indicators when making risk judgments. When the target level is obtained by regional division, the associated indicators corresponding to each sub-level in the target level include risk indicators of equipment involved in the region.

[0034] In some embodiments, determining the target level corresponding to the target object and the associated index corresponding to each sub-level in the target level includes: obtaining the corresponding target level according to the scene distribution corresponding to the target object, the target level including multiple sub-levels; and obtaining the associated index corresponding to each sub-level according to the dependency relationship between two adjacent sub-levels.

[0035] For example, if the target object is a navigation lighting system, the corresponding target level is obtained by dividing it according to the lighting requirements in different scenarios in the navigation lighting system. For example, there are many areas and equipment involved in the navigation lighting system, including multiple scenarios such as runways, taxiways, aprons, and various lighting equipment such as approach lights, runway lights, taxiway lights, etc. in different scenarios. The normal operation in these scenarios is crucial to ensure the take-off and landing of aircraft and ground taxiing. Therefore, the navigation lighting system is divided according to the different scenarios involved to obtain the corresponding target level.

[0036] Exemplarily, the target level includes at least two sub-levels, namely a first sub-level and a second sub-level. The first sub-level and the second sub-level are adjacent to each other. Then, the association indicator corresponding to the first sub-level depends on the association indicator of the second sub-level, or the association indicator corresponding to the second sub-level depends on the association indicator of the first sub-level.

[0037] For example, if the associated indicator corresponding to the first sub-level depends on the associated indicator of the second sub-level, then the associated indicator of the second sub-level includes the first risk indicator of the first device indicator and the first risk indicator of the second device indicator, and then the associated indicator of the first sub-level includes the first device indicator and the second device indicator. That is, in this application, when determining the target level corresponding to the target object, it is obtained by splitting it in sequence according to the scene, so that when obtaining the associated indicator corresponding to each sub-level in the target level, the determination of the associated indicator of the current sub-level depends on the associated indicator of the adjacent sub-level.

[0038] In some embodiments, the sub-level is any one of the first level, the second level, the third level, the fourth level and the fifth level, and the obtaining of the association index corresponding to each sub-level according to the dependency relationship between two adjacent sub-levels includes: obtaining the association index corresponding to the first level including an interior field index and an exterior field index according to the interior and exterior scene division of the first level; performing regional scene division on the basis of the first level according to the second level, and obtaining the association index of the second level including a first regional index corresponding to the interior field index and a second regional index corresponding to the exterior field index; performing regional scene division on the basis of the second level according to the third level, and obtaining the association index of the second level including a first regional index corresponding to the interior field index and a second regional index corresponding to the exterior field index. According to the method, the associated indicators of the third level are divided into zones, including a first zone indicator corresponding to the first zone indicator and a second zone indicator corresponding to the second zone indicator; according to the method, the associated indicators of the fourth level are divided based on the third level using lighting circuits and equipment information, including a first device indicator corresponding to the first zone indicator and a second device indicator corresponding to the second zone indicator; according to the method, the associated indicators of the fifth level are divided based on the fourth level using risk factors, including a first risk indicator corresponding to the first device indicator and a second risk indicator corresponding to the second device indicator.

[0039] Exemplarily, the sub-level is any one of the first level, the second level, the third level, the fourth level and the fifth level, that is, the target level includes the first level, the second level, the third level, the fourth level and the fifth level.

[0040] For example, the first level is obtained by dividing the target object into internal and external scenes, and the associated indicators corresponding to the first level include internal field indicators and external field indicators. The first level can comprehensively grasp the risk status of the internal and external fields in the navigation lighting system.

[0041] Exemplarily, the second level is obtained by further dividing the regional scenes on the basis of the first level, and the associated indicators of the second level include the first regional indicators corresponding to the indoor indicators and the second regional indicators corresponding to the outdoor indicators.

[0042] For example, the associated indicators corresponding to the first level include indoor field indicators and outdoor field indicators, and the second level is obtained by further dividing the regional scenes on the basis of the first level. If the first level is divided according to the north-south direction, the associated indicators of the second level include the first regional indicators corresponding to the indoor field indicators, which are the indoor field south area indicators and the indoor field north area indicators, and the associated indicators of the second level also include the second regional indicators corresponding to the outdoor field indicators, which are the outdoor field south area indicators and the outdoor field north area indicators.

[0043] Exemplarily, the third level is obtained by performing regional partitioning on the basis of the second level, and the associated indicators of the third level include a first partition indicator corresponding to the first regional indicator and a second partition indicator corresponding to the second regional indicator.

[0044] For example, the associated indicators corresponding to the second level include the first area indicator corresponding to the inner field indicator and the second area indicator corresponding to the outer field indicator, the first area indicator includes the inner field south area indicator and the inner field north area indicator, and the second area indicator includes the outer field south area indicator and the outer field north area indicator. Then, the associated indicators of the third level include the first sub-area indicator corresponding to the first area indicator, including the first inner field area indicator corresponding to the inner field south area indicator and the second inner field area indicator corresponding to the inner field north area indicator. For example, the first inner field area indicator includes the tower, station 3, and station 4, and the second inner field area indicator includes station 1, station 2, and the operation control center. The associated indicators of the third level also include the second sub-area indicator corresponding to the second area indicator, including the first outer field area indicator corresponding to the outer field south area indicator and the second outer field area indicator corresponding to the outer field north area indicator. For example, the first outer field area indicator includes the south runway, the south taxiway, and the approaches to the directions 09 and 27; the second outer field area indicator includes the north runway, the north taxiway, and the approaches to the directions 10 and 28.

[0045] Exemplarily, the fourth level is obtained by dividing the third level using lighting circuits and device information, and the associated index of the fourth level includes a first device index corresponding to the first partition index and a second device index corresponding to the second partition index.

[0046] For example, the associated indicators corresponding to the third level include the first partition indicator corresponding to the first area indicator and the second partition indicator corresponding to the second area indicator. The total equipment score of Station 1, Station 2, Station 3 and Station 4 in the first partition indicator is composed of five equipment indicators: high and low voltage system, diesel generator, UPS, navigation light monitoring system and dimmer. The corresponding first equipment indicator in the first partition indicator includes but is not limited to high and low voltage system, diesel generator, UPS, navigation light monitoring system and dimmer. In the second partition indicator, each partition is composed of multiple lighting circuit indicators. Taking the 09 direction approach partition as an example, it is composed of 12 lighting circuit indicators, of which the first nine are controlled by the 09 approach light group control, and the last three are controlled by the 09 slope warning light group control.

[0047] Exemplarily, according to the fifth level, risk factors are used to divide the fourth level, and the associated indicators of the fifth level include a first risk indicator corresponding to the first equipment indicator and a second risk indicator corresponding to the second equipment indicator.

[0048] For example, in the fifth level of risk factor classification, the high and low voltage systems of the first equipment indicator are composed of two risk factor project indicator scores: service life and number of failures; the diesel generator is composed of four indicator scores: service life, number of failures, oil storage and battery; the navigation lighting monitoring system is composed of two indicator scores: service life and number of system paralysis; the dimmer is composed of four indicator scores: service life, number of failures, standby machine status and spare parts status. The first risk indicator corresponding to the first equipment indicator includes standby machine status, number of failures, service life, spare parts status, etc. The lighting circuit of the second equipment indicator is composed of eight risk factor indicators: total resistance, single-segment resistance, cable, lamp, cast iron box waterproof, isolation transformer, connector and number of failures. The second risk indicator corresponding to the second equipment indicator includes total resistance, cable, lamp, single-segment resistance, etc.

[0049] For example, according to Figure 2 The correlation between the corresponding correlation indicators of each level in the first level, second level, third level, fourth level and fifth level is shown.

[0050] Step S102: Obtain an indicator score corresponding to the associated indicator corresponding to each of the sub-levels in the target level.

[0051] Exemplarily, the scoring criteria for the associated indicators corresponding to each sub-level in the target level are determined according to historical experience or expert experience, and then the indicator scores corresponding to the associated indicators are determined according to the scoring criteria.

[0052] In some embodiments, obtaining the indicator score corresponding to the associated indicator corresponding to each of the sub-levels in the target level includes: obtaining a first usage parameter corresponding to the first risk indicator of the first device indicator in the fifth level and a second usage parameter corresponding to the second risk indicator of the second device indicator; determining a first indicator score corresponding to the first risk indicator using a first preset rule according to the first usage parameter and determining a second indicator score corresponding to the second risk indicator using a second preset rule according to the second usage parameter; determining a third indicator score corresponding to the first device indicator of the fourth level by performing information fusion based on the first indicator score and the first risk indicator and determining a fourth indicator score corresponding to the second device indicator of the fourth level by performing information fusion based on the second indicator score and the second risk indicator; determining a fourth indicator score corresponding to the second device indicator of the fourth level by performing information fusion based on the third indicator score The fifth indicator score corresponding to the first partition indicator of the third level is determined by information fusion based on the fourth indicator score and the second equipment indicator, and the sixth indicator score corresponding to the second partition indicator of the third level is determined by information fusion based on the fourth indicator score and the second equipment indicator; the seventh indicator score corresponding to the first area indicator of the second level is determined by information fusion based on the fifth indicator score and the first partition indicator, and the eighth indicator score corresponding to the second area indicator of the second level is determined by information fusion based on the sixth indicator score and the second partition indicator; the ninth indicator score corresponding to the inner field indicator of the first level is obtained by information fusion based on the seventh indicator score and the first area indicator, and the tenth indicator score corresponding to the outer field indicator of the first level is obtained by information fusion based on the eighth indicator score and the second area indicator.

[0053] For example, according to Figure 2 It is known that the correlation between each associated indicator in the first level, the second level, the third level, the fourth level and the fifth level, and the indicator score of each level is calculated by weighted calculation of the indicator score of the corresponding next level. For example, when calculating the indicator score corresponding to each associated indicator in each sub-level, the indicator score corresponding to each associated indicator in the fifth level can be calculated first, and then the indicator score corresponding to each associated indicator in the fourth level can be calculated based on the indicator score corresponding to each associated indicator in the fifth level, and so on.

[0054] Exemplarily, a first usage parameter corresponding to a first risk indicator of a first device indicator and a second usage parameter corresponding to a second risk indicator of a second device indicator in the fifth level are obtained.

[0055] For example, the first risk index of the high and low voltage system in the first equipment index is composed of two risk factors: service life and number of failures. Then, the first use parameter corresponding to the first risk index includes service life I51 and the number of failures I 52 The first risk index of the diesel generator is composed of four risk factors: service life, number of failures, oil storage and battery. The first use parameter corresponding to the first risk index includes service life I 51 、Number of failures I 52 、Oil storage capacity I 53 With battery I 54 The first risk index of the navigation light monitoring system is composed of two risk factors: service life and system failure times. The first use parameter corresponding to the first risk index includes service life I 51 System crash times I 55 The first risk index of the dimmer is composed of four risk factors: service life, number of failures, standby machine status and spare parts status. The first use parameter corresponding to the first risk index includes service life I 51 , number of failures I 52 , standby situation I 56 Spare parts situation 57 .

[0056] For example, by substituting the service life y and the number of failures t into the following formula, the corresponding usage parameters can be obtained.

[0057]

[0058] Among them, I 51 It represents the usage parameters corresponding to the service life of the high and low voltage system, y represents the service life, t represents the number of failures, I 52 Indicates the usage parameters corresponding to the number of faults in the high and low voltage systems.

[0059] Exemplarily, the first usage parameter is scored and quantified according to a first preset rule to determine a first indicator score corresponding to the first risk indicator.

[0060] For example, taking the risk index corresponding to the high and low voltage system as an example, assuming that the index weight ω51 corresponding to the service life y is equal to 60%, and the index weight ω52 corresponding to the number of failures t is equal to 40%, then according to the first preset rule, the first index score corresponding to the first risk index can be obtained as follows:

[0061] I 4g =I 51 *ω 51 +I 52 *ω 52

[0062] Among them, I 51 Indicates the usage parameters corresponding to the service life of the high and low voltage systems, I 52represents the usage parameter corresponding to the number of faults in the high and low voltage systems, ω51 represents the indicator weight corresponding to the service life y, ω52 represents the indicator weight corresponding to the number of faults t, I 4g Indicates the first indicator score corresponding to the high and low pressure systems.

[0063] For example, the above formula shows that the service life of the high and low voltage systems of Station 3 in the third level is 1 year, and the number of failures is 0. Then the index score corresponding to the high and low voltage systems of Station 3 in the third level is I4g=98.8.

[0064] Exemplarily, the second usage parameter is scored and quantified according to the second preset rule, so as to determine the second indicator score corresponding to the second risk indicator.

[0065] For example, the lighting circuit in the second equipment index is composed of eight risk factors: total resistance, single-segment resistance, cable, lamp, cast iron box waterproof, isolation transformer, connector and number of failures. The second use parameter corresponding to the second risk index includes total resistance. 51 , single section resistance O 52 、Cable O 53 、Lighting O 54 , Cast iron box waterproof O 55 , Isolation transformer O 56 、Connector O 57 and the number of failures O 58 .

[0066] For example, the total resistance O is obtained according to the following formula 51 , single section resistance O 52 、Cable O 53 、Lighting O 54 , Cast iron box waterproof O 55 , Isolation transformer O 56 、Connector O 57 and the number of failures O 58 .

[0067]

[0068]

[0069] Among them, O 51 Indicates the second usage parameter corresponding to the total resistance value t1, O 52 Indicates the second usage parameter corresponding to the single-ended resistance value of t2. 53 Indicates the second usage parameter corresponding to the cable t3, O 54 Indicates the second usage parameter corresponding to the lamp at t4, O 55 Indicates the second usage parameter corresponding to the waterproofness of the cast iron box t5, O 56Indicates the second usage parameter corresponding to the isolation transformer t6, O 57 Indicates the second usage parameter corresponding to the connector t7 and O 58 Indicates the second usage parameter corresponding to the fault number t8.

[0070] The result is calculated based on the index score corresponding to the grounding zone 1 in the fourth level. 41 Take the total resistance value O as an example, according to the above formula 51 , single section resistance O 52 、Cable O 53 、Lighting O 54 , Cast iron box waterproof O 55 , Isolation transformer O 56 、Connector O 57 and the number of failures O 58 , and set the weight corresponding to the total resistance value to 0.35, the weight corresponding to the single-segment resistance value to 0.2, the weight corresponding to the cable to 0.1, the weight corresponding to the lamp to 0.05, the weight corresponding to the cast iron box waterproof to 0.05, the weight corresponding to the isolation transformer to 0.05, the weight corresponding to the connector to 0.05, and the weight corresponding to the number of faults to 0.15, then the first indicator score corresponding to 09 grounding belt is 0 41 It is the weighted summation result between each second usage parameter and the corresponding indicator weight.

[0071] For example, according to the above analysis combined with Figure 2 It can be seen that the present application obtains the first usage parameter corresponding to the first risk indicator of the first device indicator in the fifth level and obtains the second usage parameter corresponding to the second risk indicator of the second device indicator in the second level, and then uses the first preset rule to convert the first usage parameter to obtain the first indicator score corresponding to the first risk indicator, and uses the second preset rule to convert the second usage parameter to obtain the second indicator score corresponding to the second risk indicator.

[0072] Exemplarily, the lighting circuit and device information involved in the fourth level is obtained, and then the risk information corresponding to the first device indicator and the risk information corresponding to the second device indicator in the fourth level are obtained from the first risk indicator, and then the indicator score corresponding to each risk information in the first device indicator is obtained from the first indicator score, and then the weighted sum of each indicator score is performed to obtain the third indicator score corresponding to the first device indicator in the fourth level. Similarly, the fourth indicator score corresponding to the second device indicator in the fourth level is obtained.

[0073] Exemplarily, the regional partition information involved in the third level is obtained, the regional information involved in the first partition index is obtained, and then the index score involved in the regional information is obtained from the third index score, and then the weighted sum of each index score is performed to obtain the fifth index score corresponding to the first partition index. Similarly, the sixth index score corresponding to the second partition index of the third level is obtained.

[0074] Exemplarily, the regional scene information involved in the second level is obtained, and then the regional scene information involved in the first regional indicator is obtained, and then the indicator score involved in the regional scene information is obtained from the fifth indicator score, and then the weighted sum of each indicator score is performed to obtain the seventh indicator score corresponding to the first regional indicator. Similarly, the eighth indicator score corresponding to the second regional indicator of the second level is obtained.

[0075] Exemplarily, the indoor and outdoor scenes involved in the first level are obtained, and then the indoor and outdoor scene information involved in the indoor field indicator is obtained from the first area indicator, and then the indicator score involved in the indoor and outdoor scene information is obtained from the seventh indicator score, and then the weighted sum of each indicator score is performed to obtain the ninth indicator score corresponding to the indoor field indicator. Similarly, the tenth indicator score corresponding to the outdoor field indicator of the first level is obtained.

[0076] For example, according to the above analysis, the present application Figure 2 As shown, the target level is split from left to right into the first level, the second level, the third level, the fourth level and the fifth level. When calculating the indicator scores corresponding to the associated indicators in each level, the indicator scores corresponding to the associated indicators in each level are obtained from right to left according to the dependency relationship of the associated indicators.

[0077] Step S103: perform information fusion on the indicator scores to obtain a level score corresponding to each sub-level in the target level.

[0078] Exemplarily, after obtaining the indicator scores corresponding to each level, the indicator scores can be fused according to the machine learning model to obtain the level score corresponding to each sub-level in the target level.

[0079] In some embodiments, the information fusion of the indicator scores to obtain the level score corresponding to each of the sub-levels in the target level includes: setting the associated weights corresponding to the associated indicators; and weighted processing of the indicator scores according to the associated weights to obtain the level score corresponding to each of the sub-levels in the target level.

[0080] Exemplarily, the association weight corresponding to each associated indicator in different levels is set according to expert experience or historical experience, and then the indicator score is weighted according to the association weight to obtain the level score corresponding to each sub-level in the target level.

[0081] For example, the target objects are divided into five levels from top to bottom, namely the first level (inside and outside field layer), the second level (regional layer), the third level (division layer), the fourth level (lighting circuit / equipment layer) and the fifth level (risk factor project layer). The indicator score of each level is calculated by weighting the indicator score of the corresponding next level. At the same time, the scores of all indicators at each level are 0-100. The higher the score, the lower the risk of the indicator, and vice versa. For example, the associated weights corresponding to each associated indicator in the first level are obtained, and the sum of all associated weights in this level is equal to 1, then the weighted sum is performed according to the associated weights and the indicator scores corresponding to each associated indicator, so as to obtain the level score corresponding to this level.

[0082] Step S104: determining an initial risk assessment result corresponding to each of the sub-levels in the target level according to the level scoring score.

[0083] Exemplarily, the target threshold is determined, and the absolute value of the difference between the target threshold and the hierarchical score is calculated. When the absolute value of the difference is less than a preset value, the initial risk assessment result of the sub-level corresponding to the hierarchical score is determined to be a low risk; when the absolute value of the difference is greater than or equal to the preset value, the initial risk assessment result of the sub-level corresponding to the hierarchical score is determined to be a high risk.

[0084] In some embodiments, determining the initial risk assessment result corresponding to each of the sub-levels in the target level according to the level score includes: setting a risk threshold, and comparing the level score with the risk threshold to obtain a comparison result; and determining the initial risk assessment result corresponding to each of the sub-levels in the target level according to the comparison result.

[0085] Exemplarily, a risk threshold is set based on historical experience or expert experience, and then the hierarchical score is compared with the risk threshold to obtain a comparison result. When the comparison result is that the hierarchical score is less than or equal to the risk threshold, the initial risk assessment result of the sub-level corresponding to the hierarchical score is determined to be a lower risk; when the comparison result is that the hierarchical score is greater than the risk threshold, the initial risk assessment result of the sub-level corresponding to the hierarchical score is determined to be a higher risk.

[0086] Step S105: Determine a target risk assessment result corresponding to the target object according to the initial risk assessment result.

[0087] Exemplarily, an initial risk assessment result corresponding to each sub-level in the target level is obtained, and then the initial risk assessment results are summarized to obtain a target risk assessment result corresponding to the target object.

[0088] In some embodiments, after obtaining the target risk assessment result, the method further includes: determining an abnormal object corresponding to the target object based on the target risk assessment result; determining an abnormality handling strategy corresponding to the abnormal object, and performing abnormal repair on the abnormal object according to the abnormality handling strategy to obtain an abnormality handling result.

[0089] Exemplarily, according to the target risk assessment result, the corresponding object when the risk among the target objects is higher is determined as an abnormal object, and then the exception handling strategy that can be taken when the abnormal object is abnormal is obtained from the database, so that the abnormal object is repaired according to the exception handling strategy, and then the exception handling result is obtained, thereby ensuring the normal operation of the target object.

[0090] See also Figure 3 , Figure 3 An aid to navigation lighting risk assessment system 200 based on multi-level heterogeneous data is provided in an embodiment of the present application. The aid to navigation lighting risk assessment system 200 based on multi-level heterogeneous data includes an indicator determination module 201, a score acquisition module 202, a score calculation module 203, an initial assessment module 204, and a target assessment module 205, wherein the indicator determination module 201 is used to determine the target level corresponding to the target object and the associated indicator corresponding to each sub-level in the target level; the score acquisition module 202 is used to obtain the indicator score corresponding to the associated indicator corresponding to each sub-level in the target level; the score calculation module 203 is used to perform information fusion on the indicator score to obtain the level score corresponding to each sub-level in the target level; the initial assessment module 204 is used to determine the initial risk assessment result corresponding to each sub-level in the target level according to the level score; the target assessment module 205 is used to determine the target risk assessment result corresponding to the target object according to the initial risk assessment result.

[0091] In some implementations, the indicator determination module 201, during the process of determining the target level corresponding to the target object and the associated indicator corresponding to each sub-level in the target level, performs:

[0092] Obtaining the corresponding target level according to the scene distribution corresponding to the target object, wherein the target level includes a plurality of sub-levels;

[0093] The association index corresponding to each of the sub-levels is obtained according to the dependency relationship between two adjacent sub-levels.

[0094] In some implementations, the sub-level is any one of the first level, the second level, the third level, the fourth level, and the fifth level, and the indicator determination module 201, in the process of obtaining the associated indicator corresponding to each sub-level according to the dependency relationship between two adjacent sub-levels, performs:

[0095] The correlation index corresponding to the first level obtained according to the first level of internal and external scene division includes an internal field index and an external field index;

[0096] Performing regional scene division based on the first level according to the second level, obtaining the associated index of the second level including a first regional index corresponding to the indoor index and a second regional index corresponding to the outdoor index;

[0097] Performing regional partitioning on the basis of the second level according to the third level, obtaining the associated index of the third level including a first partition index corresponding to the first regional index and a second partition index corresponding to the second regional index;

[0098] According to the fourth level, based on the third level, the light circuit and device information are divided to obtain the fourth level association index, including a first device index corresponding to the first partition index and a second device index corresponding to the second partition index;

[0099] According to the fifth level, based on the fourth level, the risk factors are used to divide the associated indicators of the fifth level, so that the associated indicators of the fifth level include a first risk indicator corresponding to the first equipment indicator and a second risk indicator corresponding to the second equipment indicator.

[0100] In some implementations, the score obtaining module 202 performs, during the process of obtaining the indicator score corresponding to the associated indicator corresponding to each of the sub-levels in the target level:

[0101] Obtaining a first usage parameter corresponding to the first risk indicator of the first device indicator and a second usage parameter corresponding to the second risk indicator of the second device indicator in the fifth level;

[0102] Determine a first indicator score corresponding to the first risk indicator using a first preset rule according to the first usage parameter and determine a second indicator score corresponding to the second risk indicator using a second preset rule according to the second usage parameter;

[0103] Performing information fusion based on the first indicator score and the first risk indicator to determine a third indicator score corresponding to the first device indicator of the fourth level, and performing information fusion based on the second indicator score and the second risk indicator to determine a fourth indicator score corresponding to the second device indicator of the fourth level;

[0104] Performing information fusion based on the third indicator score and the first device indicator to determine a fifth indicator score corresponding to the first partition indicator of the third level, and performing information fusion based on the fourth indicator score and the second device indicator to determine a sixth indicator score corresponding to the second partition indicator of the third level;

[0105] Performing information fusion based on the fifth indicator score and the first sub-area indicator to determine a seventh indicator score corresponding to the first regional indicator of the second level, and performing information fusion based on the sixth indicator score and the second sub-area indicator to determine an eighth indicator score corresponding to the second regional indicator of the second level;

[0106] Information fusion is performed based on the seventh indicator score and the first area indicator to obtain a ninth indicator score corresponding to the inner field indicator of the first level, and information fusion is performed based on the eighth indicator score and the second area indicator to obtain a tenth indicator score corresponding to the outer field indicator of the first level.

[0107] In some implementations, the score calculation module 203 performs, during the process of performing information fusion on the indicator score to obtain the level score corresponding to each of the sub-levels in the target level:

[0108] Setting the association weight corresponding to the association indicator;

[0109] The indicator score is weighted according to the associated weight to obtain the level score corresponding to each sub-level in the target level.

[0110] In some implementations, during the process of determining the initial risk assessment result corresponding to each of the sub-levels in the target level according to the level scoring score, the initial assessment module 204 performs:

[0111] Setting a risk threshold, and comparing the level score with the risk threshold to obtain a comparison result;

[0112] The initial risk assessment result corresponding to each of the sub-levels in the target level is determined according to the comparison result.

[0113] In some implementations, after obtaining the target risk assessment result, the navigation lighting risk assessment system 200 based on multi-level heterogeneous data further performs:

[0114] Determine the abnormal object corresponding to the target object according to the target risk assessment result;

[0115] Determine the exception handling strategy corresponding to the exception object, and perform exception repair on the exception object according to the exception handling strategy to obtain the exception handling result.

[0116] In some implementations, the navigation lighting risk assessment system 200 based on multi-level heterogeneous data may be applied to a terminal device.

[0117] It should be noted that, those skilled in the art can clearly understand that, for the sake of convenience and brevity of description, the specific working process of the navigation lighting risk assessment system 200 based on multi-level heterogeneous data described above can refer to the corresponding process in the aforementioned embodiment of the navigation lighting risk assessment method based on multi-level heterogeneous data, and will not be repeated here.

[0118] See also Figure 4 , Figure 4 A schematic block diagram of the structure of a terminal device provided in an embodiment of the present invention.

[0119] like Figure 4 As shown, the terminal device 300 includes a processor 301 and a memory 302, and the processor 301 and the memory 302 are connected via a bus 303, such as an I2C (Inter-integrated Circuit) bus.

[0120] Specifically, the processor 301 is used to provide computing and control capabilities to support the operation of the entire terminal device. The processor 301 can be a central processing unit (CPU), and the processor 301 can also be other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. Among them, the general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc.

[0121] Specifically, the memory 302 may be a Flash chip, a read-only memory (ROM) disk, an optical disk, a USB flash drive, or a mobile hard disk.

[0122] Those skilled in the art will understand that Figure 4 The structure shown in the figure is only a block diagram of a partial structure related to the embodiment of the present invention, and does not constitute a limitation on the terminal device to which the embodiment of the present invention is applied. The specific server may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0123] The processor is used to run a computer program stored in the memory, and implement any one of the methods for risk assessment of navigation lights based on multi-level heterogeneous data provided by the embodiments of the present invention when executing the computer program.

[0124] In one embodiment, the processor is used to run a computer program stored in the memory, and implements the following steps when executing the computer program:

[0125] Determine a target level corresponding to the target object and an associated indicator corresponding to each sub-level in the target level;

[0126] Obtaining an indicator score corresponding to the associated indicator corresponding to each of the sub-levels in the target level;

[0127] Performing information fusion on the indicator scores to obtain the hierarchical score corresponding to each sub-level in the target level;

[0128] Determine the initial risk assessment result corresponding to each sub-level in the target level according to the level scoring score;

[0129] A target risk assessment result corresponding to the target object is determined according to the initial risk assessment result.

[0130] In some implementations, during the process of determining the target level corresponding to the target object and the associated index corresponding to each sub-level in the target level, the processor 301 executes:

[0131] Obtaining the corresponding target level according to the scene distribution corresponding to the target object, wherein the target level includes a plurality of sub-levels;

[0132] The association index corresponding to each of the sub-levels is obtained according to the dependency relationship between two adjacent sub-levels.

[0133] In some implementations, the sub-level is any one of the first level, the second level, the third level, the fourth level, and the fifth level, and the processor 301, in the process of obtaining the association index corresponding to each of the sub-levels according to the dependency relationship between two adjacent sub-levels, executes:

[0134] The correlation index corresponding to the first level obtained according to the first level of internal and external scene division includes an internal field index and an external field index;

[0135] Performing regional scene division based on the first level according to the second level, obtaining the associated index of the second level including a first regional index corresponding to the indoor index and a second regional index corresponding to the outdoor index;

[0136] Performing regional partitioning on the basis of the second level according to the third level, obtaining the associated index of the third level including a first partition index corresponding to the first regional index and a second partition index corresponding to the second regional index;

[0137] According to the fourth level, based on the third level, the light circuit and device information are divided to obtain the fourth level association index, including a first device index corresponding to the first partition index and a second device index corresponding to the second partition index;

[0138] According to the fifth level, based on the fourth level, the risk factors are used to divide the associated indicators of the fifth level, so that the associated indicators of the fifth level include a first risk indicator corresponding to the first equipment indicator and a second risk indicator corresponding to the second equipment indicator.

[0139] In some implementations, the processor 301, in the process of obtaining the indicator score corresponding to the associated indicator corresponding to each of the sub-levels in the target level, executes:

[0140] Obtaining a first usage parameter corresponding to the first risk indicator of the first device indicator and a second usage parameter corresponding to the second risk indicator of the second device indicator in the fifth level;

[0141] Determine a first indicator score corresponding to the first risk indicator using a first preset rule according to the first usage parameter and determine a second indicator score corresponding to the second risk indicator using a second preset rule according to the second usage parameter;

[0142] Performing information fusion based on the first indicator score and the first risk indicator to determine a third indicator score corresponding to the first device indicator of the fourth level, and performing information fusion based on the second indicator score and the second risk indicator to determine a fourth indicator score corresponding to the second device indicator of the fourth level;

[0143] Performing information fusion based on the third indicator score and the first device indicator to determine a fifth indicator score corresponding to the first partition indicator of the third level, and performing information fusion based on the fourth indicator score and the second device indicator to determine a sixth indicator score corresponding to the second partition indicator of the third level;

[0144] Performing information fusion based on the fifth indicator score and the first sub-area indicator to determine a seventh indicator score corresponding to the first regional indicator of the second level, and performing information fusion based on the sixth indicator score and the second sub-area indicator to determine an eighth indicator score corresponding to the second regional indicator of the second level;

[0145] Information fusion is performed based on the seventh indicator score and the first area indicator to obtain a ninth indicator score corresponding to the inner field indicator of the first level, and information fusion is performed based on the eighth indicator score and the second area indicator to obtain a tenth indicator score corresponding to the outer field indicator of the first level.

[0146] In some implementations, the processor 301, in the process of performing information fusion on the indicator score to obtain the level score corresponding to each of the sub-levels in the target level, executes:

[0147] Setting the association weight corresponding to the association indicator;

[0148] The indicator score is weighted according to the associated weight to obtain the level score corresponding to each sub-level in the target level.

[0149] In some implementations, during the process of determining the initial risk assessment result corresponding to each of the sub-levels in the target level according to the level scoring score, the processor 301 executes:

[0150] Setting a risk threshold, and comparing the level score with the risk threshold to obtain a comparison result;

[0151] The initial risk assessment result corresponding to each of the sub-levels in the target level is determined according to the comparison result.

[0152] In some implementations, after obtaining the target risk assessment result, the processor 301 further executes:

[0153] Determine the abnormal object corresponding to the target object according to the target risk assessment result;

[0154] Determine the exception handling strategy corresponding to the exception object, and perform exception repair on the exception object according to the exception handling strategy to obtain the exception handling result.

[0155] It should be noted that, technical personnel in the relevant field can clearly understand that, for the convenience and conciseness of description, the specific working process of the terminal device described above can refer to the corresponding process in the aforementioned embodiment of the navigation lighting risk assessment method based on multi-level heterogeneous data, and will not be repeated here.

[0156] An embodiment of the present invention further provides a storage medium for computer-readable storage, wherein the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement any step of the method for risk assessment of navigation lights based on multi-level heterogeneous data as provided in the description of the embodiment of the present invention.

[0157] The storage medium may be an internal storage unit of the terminal device described in the foregoing embodiment, such as a hard disk or memory of the terminal device. The storage medium may also be an external storage device of the terminal device, such as a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), etc., equipped on the terminal device.

[0158] It will be appreciated by those skilled in the art that all or some of the steps, systems, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, and appropriate combinations thereof. In a hardware embodiment, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. Such software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As known to those skilled in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to store the desired information and can be accessed by a computer. In addition, it is well known to those of ordinary skill in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

[0159] It should be understood that the term "and / or" used in the present specification and the appended claims refers to any combination of one or more of the associated listed items and all possible combinations, including these combinations. It should be noted that, in this article, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or system including a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to such process, method, article or system. In the absence of further restrictions, an element defined by the sentence "including a..." does not exclude the presence of other identical elements in the process, method, article or system including the element.

[0160] The serial numbers of the embodiments of the present invention are only for description and do not represent the advantages and disadvantages of the embodiments. The above description is only a specific embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any technician familiar with the technical field can easily think of various equivalent modifications or replacements within the technical scope disclosed by the present invention, and these modifications or replacements should be included in the protection scope of the present invention. Therefore, the protection scope of the present invention shall be based on the protection scope of the claims.

Claims

1. A method for risk assessment of navigation lights based on multi-level heterogeneous data, characterized in that: The method comprises: Determine a target level corresponding to the target object and an associated indicator corresponding to each sub-level in the target level; Obtaining an indicator score corresponding to the associated indicator corresponding to each of the sub-levels in the target level; Performing information fusion on the indicator scores to obtain the hierarchical score corresponding to each sub-level in the target level; Determine the initial risk assessment result corresponding to each sub-level in the target level according to the level scoring score; A target risk assessment result corresponding to the target object is determined according to the initial risk assessment result.

2. The method according to claim 1, characterized in that The determining of the target level corresponding to the target object and the associated index corresponding to each sub-level in the target level includes: Obtaining the corresponding target level according to the scene distribution corresponding to the target object, wherein the target level includes a plurality of sub-levels; The association index corresponding to each of the sub-levels is obtained according to the dependency relationship between two adjacent sub-levels.

3. The method according to claim 2, characterized in that The sub-level is any one of the first level, the second level, the third level, the fourth level and the fifth level, and obtaining the association index corresponding to each sub-level according to the dependency relationship between two adjacent sub-levels includes: The correlation index corresponding to the first level obtained according to the first level of internal and external scene division includes an internal field index and an external field index; Performing regional scene division based on the first level according to the second level, obtaining the associated index of the second level including a first regional index corresponding to the indoor index and a second regional index corresponding to the outdoor index; Performing regional partitioning on the basis of the second level according to the third level, obtaining the associated index of the third level including a first partition index corresponding to the first regional index and a second partition index corresponding to the second regional index; According to the fourth level, based on the third level, the light circuit and device information are divided to obtain the fourth level association index, including a first device index corresponding to the first partition index and a second device index corresponding to the second partition index; According to the fifth level, based on the fourth level, the risk factors are used to divide the associated indicators of the fifth level, so that the associated indicators of the fifth level include a first risk indicator corresponding to the first equipment indicator and a second risk indicator corresponding to the second equipment indicator.

4. The method according to claim 3, characterized in that The obtaining of the indicator score corresponding to the associated indicator corresponding to each of the sub-levels in the target level includes: Obtaining a first usage parameter corresponding to the first risk indicator of the first device indicator and a second usage parameter corresponding to the second risk indicator of the second device indicator in the fifth level; Determine a first indicator score corresponding to the first risk indicator using a first preset rule according to the first usage parameter and determine a second indicator score corresponding to the second risk indicator using a second preset rule according to the second usage parameter; Performing information fusion based on the first indicator score and the first risk indicator to determine a third indicator score corresponding to the first device indicator of the fourth level, and performing information fusion based on the second indicator score and the second risk indicator to determine a fourth indicator score corresponding to the second device indicator of the fourth level; Performing information fusion based on the third indicator score and the first device indicator to determine a fifth indicator score corresponding to the first partition indicator of the third level, and performing information fusion based on the fourth indicator score and the second device indicator to determine a sixth indicator score corresponding to the second partition indicator of the third level; Performing information fusion based on the fifth indicator score and the first sub-area indicator to determine a seventh indicator score corresponding to the first regional indicator of the second level, and performing information fusion based on the sixth indicator score and the second sub-area indicator to determine an eighth indicator score corresponding to the second regional indicator of the second level; Information fusion is performed based on the seventh indicator score and the first area indicator to obtain a ninth indicator score corresponding to the inner field indicator of the first level, and information fusion is performed based on the eighth indicator score and the second area indicator to obtain a tenth indicator score corresponding to the outer field indicator of the first level.

5. The method according to claim 1, characterized in that The step of fusing the indicator scores to obtain a hierarchical score corresponding to each sub-level in the target level includes: Setting the association weight corresponding to the association indicator; The indicator score is weighted according to the associated weight to obtain the level score corresponding to each sub-level in the target level.

6. The method according to claim 1, characterized in that The determining, according to the hierarchical scoring value, an initial risk assessment result corresponding to each sub-level in the target level includes: Setting a risk threshold, and comparing the level score with the risk threshold to obtain a comparison result; The initial risk assessment result corresponding to each of the sub-levels in the target level is determined according to the comparison result.

7. The method according to any one of claims 1 to 6, characterized in that After obtaining the target risk assessment result, the method further includes: Determine the abnormal object corresponding to the target object according to the target risk assessment result; Determine the exception handling strategy corresponding to the exception object, and perform exception repair on the exception object according to the exception handling strategy to obtain the exception handling result.

8. A navigation lighting risk assessment system based on multi-level heterogeneous data, characterized in that: include: An indicator determination module, used to determine a target level corresponding to a target object and an associated indicator corresponding to each sub-level in the target level; A score obtaining module, used for obtaining an indicator score corresponding to the associated indicator corresponding to each of the sub-levels in the target level; A score calculation module, used for performing information fusion on the indicator score to obtain a level score corresponding to each sub-level in the target level; An initial assessment module, used to determine an initial risk assessment result corresponding to each sub-level in the target level according to the level scoring score; The target assessment module is used to determine the target risk assessment result corresponding to the target object according to the initial risk assessment result.

9. A terminal device, characterized in that: The terminal device includes a processor and a memory; The memory is used to store computer programs; The processor is used to execute the computer program and implement the method for risk assessment of navigation lights based on multi-level heterogeneous data according to any one of claims 1 to 7 when executing the computer program.

10. A computer storage medium for computer storage, characterized in that: The computer storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the steps of the navigation lighting risk assessment method based on multi-level heterogeneous data as described in any one of claims 1 to 7.

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