Intelligent emergency medical logistics stowage method based on mobile artificial intelligence

Abstract

The invention relates to an intelligent emergency medical logistics stowage method based on mobile artificial intelligence, and the method comprises the steps: building an air-ground collaborative logistics distribution system in advance, carrying out the processing of the system, obtaining an emergency medical logistics stowage scheme, and further obtaining a medical logistics land transportation distribution initial line and a medical logistics land transportation distribution optimized line. Emergency medical materials loaded according to the emergency medical logistics loading scheme are subjected to logistics land transportation distribution according to the medical logistics land transportation distribution optimized route, and an unmanned aerial vehicle cooperative distribution planning route for current emergency medical material distribution is executed according to the emergency medical logistics distribution timeliness demand and the executed logistics land transportation distribution progress. And enabling the unmanned aerial vehicle to execute emergency medical logistics distribution according to the current unmanned aerial vehicle collaborative distribution planning path. Therefore, multimodal transport of land transportation and air transportation of the emergency medical materials is realized, adverse effects of land transportation traffic congestion on emergency medical material transportation are avoided, and stowage and distribution efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the field of medical logistics distribution, and in particular to a smart emergency medical logistics loading method based on mobile artificial intelligence. Background Art

[0002] Emergency medical logistics is of special importance in responding to public emergencies such as natural disasters (such as earthquakes or mudslides), accidents, public health incidents and social security incidents, and is crucial for treating the wounded in the first place.

[0003] In the traditional logistics distribution process of emergency medical supplies, emergency medical supplies and transportation tools (i.e. logistics vehicles) are usually loaded and processed, and then the logistics distribution routes are planned according to the origin and demand places of the emergency medical supplies. The logistics distribution routes rely on mature land transportation methods, that is, emergency medical supplies are transported to the demand places of emergency medical supplies by logistics vehicles.

[0004] However, the existing emergency medical logistics loading method has shortcomings: it does not take into account the adverse impact of land traffic congestion on the land transportation distribution process, and it is impossible to dynamically adjust the initial distribution route according to the situation of each distribution point, resulting in emergency medical supplies being unable to be delivered to the emergency medical supplies demand areas in a timely manner, greatly reducing the efficiency of emergency medical logistics distribution. Summary of the Invention

[0005] In view of this, the technical problem to be solved by the present invention is to provide an intelligent emergency medical logistics loading method based on mobile artificial intelligence in response to the above-mentioned existing technology.

[0006] The technical solution adopted by the present invention to solve the above technical problems is: a smart emergency medical logistics loading method based on mobile artificial intelligence, characterized by comprising the following steps:

[0007] Step 1: Pre-build a land-air collaborative logistics distribution system based on the linkage of vehicle-based land transportation and drone-based air transportation;

[0008] Step 2: Based on the emergency medical logistics distribution needs and emergency medical logistics vehicle information, an emergency medical logistics loading plan is obtained;

[0009] Step 3: Plan the initial medical logistics land transportation distribution route based on the emergency medical logistics distribution needs and the starting point of emergency medical supplies;

[0010] Step 4: Extract the delivery point information of each delivery point on the initial medical logistics land transportation delivery route, and optimize the initial medical logistics land transportation delivery route based on the acquired delivery point information of all delivery points to obtain the optimized medical logistics land transportation delivery route;

[0011] Step 5: The emergency medical supplies loaded according to the emergency medical logistics loading plan will be distributed by land transportation according to the optimized medical logistics land transportation distribution route;

[0012] Step 6: Based on the timeliness requirements of emergency medical logistics and the progress of the executed land transportation, execute the drone collaborative delivery planning route for the current emergency medical supplies delivery;

[0013] Step 7: Instruct the drone to perform emergency medical logistics delivery according to the current drone collaborative delivery planning path.

[0014] Improved, in the intelligent emergency medical logistics loading method based on mobile artificial intelligence, in step 2, the process of obtaining the emergency medical logistics loading plan based on emergency medical logistics distribution needs and emergency medical logistics vehicle information processing includes the following steps:

[0015] Step a1: extracting the distribution urgency of each medical supply in the emergency medical logistics distribution demand; wherein, medical supplies with a high distribution urgency are given priority in distribution;

[0016] Step a2: Obtain vehicle condition information for each logistics vehicle managed by the medical supplies originating point, and perform quantitative post-processing on each logistics vehicle based on this condition information to obtain a safe transport index for the logistics vehicle. The condition information includes the normal speed and risk factor of the logistics vehicle when fully loaded, with the risk factor being positively correlated with the full load of the logistics vehicle.

[0017] Step a3: sort the logistics vehicles in descending order of their safety load index to obtain a logistics vehicle loading sequence;

[0018] Step a4: Match each medical supply to each logistics vehicle in the logistics vehicle loading sequence in descending order of delivery urgency, obtaining a vehicle-cargo loading mapping relationship list; each medical supply is preferentially matched to a logistics vehicle with a higher safety load index; if the number of logistics vehicles at the origin is limited, the logistics vehicles are loaded until they are full according to the delivery urgency of the medical supplies; medical supplies not loaded by the current batch of logistics vehicles are configured to be loaded onto the next batch of logistics vehicles;

[0019] Step a5: Load each medical supply onto the corresponding logistics vehicle according to the obtained vehicle-cargo loading mapping relationship list.

[0020] Further improved, in the intelligent emergency medical logistics loading method based on mobile artificial intelligence, in step a2, the safe carrying index of the logistics vehicle is calculated as follows:

[0021]

[0022] in, is the safety carrying index of logistics vehicle i, v i is the normal driving speed of logistics vehicle i under full load, |v i | is the normal driving speed v i The value after removing the unit, M i is the full load of logistics vehicle i, where the full load is the mass of the loaded goods, |M i | is the full load M i The values ​​after removing the unit are: α is the adjustment parameter corresponding to the normal driving speed of the logistics vehicle when fully loaded; β is the adjustment parameter corresponding to the full load of the logistics vehicle when fully loaded; N is the total number of logistics vehicles managed by the medical supplies departure point.

[0023] Furthermore, in the mobile artificial intelligence-based intelligent emergency medical logistics loading method, in step 3, the process of planning the initial medical logistics land transportation distribution route according to the emergency medical logistics distribution demand and the starting point of the emergency medical supplies includes the following steps:

[0024] Step b1, obtaining the location of the demand point for emergency medical logistics distribution;

[0025] Step b2: connecting the demand point and the emergency medical supplies origin point, and using the resulting line segment as a reference line segment for emergency medical supplies distribution;

[0026] Step b3: constructing a logistics distribution coverage area corresponding to the emergency medical logistics distribution demand, with the midpoint of the emergency medical supplies distribution reference line segment as the center and half the length of the emergency medical supplies distribution reference line segment as the radius;

[0027] Step b4, selecting all preliminary land transport delivery points located within the logistics distribution coverage area from all land transport delivery points for emergency medical supplies distribution, and forming a preliminary land transport delivery point set from all selected preliminary land transport delivery points;

[0028] Step b5: selecting preferred land transport delivery points that meet the current emergency medical logistics delivery needs from all the preliminarily selected land transport delivery point sets to form a preferred land transport delivery point set;

[0029] Step b6: All distribution points in the preferred land transport distribution point set are connected in ascending order of distance from the emergency medical supplies departure point, and the route formed by connecting all preferred land transport distribution points is used as the initial route for the medical logistics land transport distribution.

[0030] Further improved, in the intelligent emergency medical logistics loading method based on mobile artificial intelligence, in step 4, the process of optimizing and obtaining the optimized medical logistics land transportation distribution route includes the following steps:

[0031] Step c1, estimating the estimated arrival time of the emergency medical supplies at each preferred land transport delivery point in sequence by logistics vehicles; wherein, during the delivery process, the emergency medical supplies are delivered from the previous preferred land transport delivery point to the next preferred land transport delivery point;

[0032] Step c2: Obtain weather information for each preferred land delivery point at its corresponding estimated arrival time;

[0033] Step c3: Determine whether the weather environment information obtained for each preferred land transportation delivery point is severe weather.

[0034] If any of the preferred land transport delivery points is experiencing severe weather conditions, proceed to step c4; otherwise, continue to deliver emergency medical supplies along the original medical logistics land transport delivery route.

[0035] Step c4: Send a request to the logistics distribution manager to extend the vehicle delivery route, and process the request based on the feedback from the logistics distribution manager:

[0036] When the feedback allows the current logistics vehicle's delivery route to be extended, the current vehicle is instructed to skip any preferred land delivery point and directly extend the delivery to the next preferred land delivery point after any preferred land delivery point; otherwise, the current logistics vehicle is instructed to continue delivering the emergency medical supplies to any preferred land delivery point.

[0037] Further improved, in this invention, the intelligent emergency medical logistics loading method based on mobile artificial intelligence also includes: according to the emergency medical logistics distribution timeliness requirements and the executed logistics land transportation distribution progress, determining the land-air combined transport distribution point where the emergency medical supplies are transported by land-operated drones among all the preferred land transportation distribution points, and making the drone execute the drone collaborative distribution planning path for the current emergency medical supplies distribution at the land-air combined transport distribution point, so as to transport the medical supplies directly to the last preferred land transportation distribution point in the medical logistics land transportation distribution optimization route.

[0038] Furthermore, in the mobile artificial intelligence-based intelligent emergency medical logistics loading method, the process of determining the land-air transport distribution point includes the following steps:

[0039] Step d1: pre-acquire traffic congestion indexes for the areas near each preferred land transport delivery point at different time periods within a day to obtain traffic congestion information for the preferred land transport delivery points; wherein, in the traffic congestion information for the preferred land transport delivery points, for each preferred land transport delivery point, the time period corresponds to the traffic congestion index;

[0040] Step d2: pre-estimating the time period during which the emergency medical supplies will arrive from the previous land transport delivery point to the next land transport delivery point, and the traffic congestion index corresponding to the time period, based on the traffic congestion information of the preferred land transport delivery point;

[0041] Step d3: making a judgment based on the arrival time period corresponding to the last preferred land transportation delivery point in the pre-estimated optimized medical logistics land transportation delivery route and the emergency medical logistics delivery timeliness requirement:

[0042] If the arrival time is later than the emergency medical logistics delivery time requirement, proceed to step d4; otherwise, continue to perform land transportation delivery according to the original medical logistics land transportation delivery optimization route;

[0043] In step d4, the preferred land transport delivery point that has completed the logistics land transport delivery is used as the failed delivery point in the preferred land transport delivery point set, and the non-failed delivery point in the preferred land transport delivery point set and whose estimated traffic congestion index is greater than the preset index threshold is used as the land-air combined transport delivery point.

[0044] Compared with the existing technology, the advantages of the present invention are: the intelligent emergency medical logistics loading method based on mobile artificial intelligence pre-constructs a land-air collaborative logistics distribution system, and obtains an emergency medical logistics loading plan based on the emergency medical logistics distribution needs and emergency medical logistics vehicle information processing. Then, based on the emergency medical logistics distribution needs and the starting point of the emergency medical supplies, an initial medical logistics land transportation distribution route is obtained, and the initial medical logistics land transportation distribution route is optimized to obtain an optimized medical logistics land transportation distribution route. The emergency medical supplies loaded according to the emergency medical logistics loading plan are then transported by land along the optimized medical logistics land transportation distribution route. The drone-assisted delivery route for the current emergency medical supplies distribution is executed according to the emergency medical logistics distribution timeliness requirements and the executed logistics land transportation distribution progress, and the drone is instructed to perform emergency medical logistics distribution according to the current drone-assisted delivery route. In this way, the large-scale transportation of emergency medical supplies is realized by logistics vehicles, and the drone is used to intervene in land transportation congestion to avoid the adverse effects of land transportation congestion on emergency supplies, ensuring that the emergency medical supplies can be delivered to the emergency medical supplies demand location in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0045] In order to more clearly illustrate the specific embodiments of the present disclosure or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0046] Figure 1 This is a flow chart of a smart emergency medical logistics loading method based on mobile artificial intelligence in an embodiment of the present invention;

[0047] Figure 2 This is a schematic diagram of a process for obtaining an emergency medical logistics loading plan in an embodiment of the present invention;

[0048] Figure 3 This is a schematic diagram of the planning process of the initial route of medical logistics land transportation distribution in an embodiment of the present invention;

[0049] Figure 4 This is a schematic diagram of the process of optimizing the medical logistics land transportation distribution route in accordance with the embodiment of the present invention;

[0050] Figure 5 2 is a flow chart of the process of determining the land-air intermodal transport delivery point in an embodiment of the present invention. DETAILED DESCRIPTION

[0051] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only 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 making creative efforts shall fall within the scope of protection of the present invention.

[0052] To facilitate understanding of the embodiments of the present invention, specific embodiments will be further explained below with reference to the accompanying drawings. The embodiments do not limit the embodiments of the present invention.

[0053] The present invention will be described in further detail below with reference to the accompanying drawings and embodiments.

[0054] This embodiment provides a smart emergency medical logistics loading method based on mobile artificial intelligence. Figure 1 As shown, the intelligent emergency medical logistics loading method based on mobile artificial intelligence in this embodiment includes the following steps 1 to 7:

[0055] Step 1: Pre-build a land-air collaborative logistics distribution system based on the linkage of vehicle-based land transportation and drone-based air transportation;

[0056] Step 2: Based on the emergency medical logistics distribution needs and emergency medical logistics vehicle information, an emergency medical logistics loading plan is obtained;

[0057] Step 3: Plan the initial medical logistics land transportation distribution route based on the emergency medical logistics distribution needs and the starting point of emergency medical supplies;

[0058] Step 4: Extract the delivery point information of each delivery point on the initial medical logistics land transportation delivery route, and optimize the initial medical logistics land transportation delivery route based on the acquired delivery point information of all delivery points to obtain the optimized medical logistics land transportation delivery route;

[0059] Step 5: The emergency medical supplies loaded according to the emergency medical logistics loading plan will be distributed by land transportation according to the optimized medical logistics land transportation distribution route;

[0060] Step 6: Based on the timeliness requirements of emergency medical logistics and the progress of the executed land transportation, execute the drone collaborative delivery planning route for the current emergency medical supplies delivery;

[0061] Step 7: Instruct the drone to perform emergency medical logistics delivery according to the current drone collaborative delivery plan. The drone here can be a model of drone currently available on the market that meets the requirements of logistics transportation.

[0062] It should be noted that, in this embodiment, the above steps 2 to 7 can be executed as needed by the mobile processing equipment responsible for planning the emergency medical logistics loading routes, the relevant land transport distribution route information is received and processed by the mobile terminal device on the logistics vehicle, and the relevant air routes that the drone is responsible for are received and processed by the mobile device on the drone.

[0063] Specifically, see Figure 2 As shown, in step 2 of this embodiment, the process of obtaining the emergency medical logistics loading plan based on the emergency medical logistics distribution demand and the emergency medical logistics vehicle information processing includes the following steps a1 to a5:

[0064] Step a1: extracting the delivery urgency of each medical supply in the emergency medical logistics distribution demand; wherein, medical supplies with a high delivery urgency are given priority in delivery;

[0065] Step a2: Obtain vehicle condition information for each logistics vehicle managed by the medical supplies originating point, and perform quantitative post-processing on each logistics vehicle based on this condition information to obtain a safe transport index for the logistics vehicle. The condition information includes the normal speed and risk factor of the logistics vehicle when fully loaded, with the risk factor being positively correlated with the full load of the logistics vehicle.

[0066] Specifically, in this embodiment, the safe transport index of the logistics vehicle is calculated as follows:

[0067]

[0068] in, is the safety carrying index of logistics vehicle i, v iis the normal driving speed of logistics vehicle i under full load, |v i | is the normal driving speed v i The value after removing the unit, M i is the full load of logistics vehicle i, where the full load is the mass of the loaded goods, |M i | is the full load M i The values ​​after removing the unit are: α is the adjustment parameter corresponding to the normal driving speed of the logistics vehicle when fully loaded; β is the adjustment parameter corresponding to the full load of the logistics vehicle when fully loaded; N is the total number of logistics vehicles under the management of the medical supplies departure point;

[0069] Step a3: sort the logistics vehicles in descending order of their safety load index to obtain a logistics vehicle loading sequence;

[0070] Step a4: Match each medical supply to each logistics vehicle in the logistics vehicle loading sequence in descending order of delivery urgency, obtaining a vehicle-cargo loading mapping relationship list; each medical supply is preferentially matched to a logistics vehicle with a higher safety load index; if the number of logistics vehicles at the origin is limited, the logistics vehicles are loaded until they are full according to the delivery urgency of the medical supplies; medical supplies not loaded by the current batch of logistics vehicles are configured to be loaded onto the next batch of logistics vehicles;

[0071] Step a5: Load each medical supply onto the corresponding logistics vehicle according to the obtained vehicle-cargo loading mapping relationship list.

[0072] Also, see Figure 3 As shown, in step 3 of this embodiment, the process of planning the above-mentioned initial medical logistics land transportation distribution route according to the emergency medical logistics distribution demand and the starting point of the emergency medical supplies includes the following steps b1 to b6:

[0073] Step b1, obtaining the location of the demand point for emergency medical logistics distribution;

[0074] Step b2: connecting the demand point and the emergency medical supplies origin point, and using the resulting line segment as a reference line segment for emergency medical supplies distribution;

[0075] Step b3: constructing a logistics distribution coverage area corresponding to the emergency medical logistics distribution demand, with the midpoint of the emergency medical supplies distribution reference line segment as the center and half the length of the emergency medical supplies distribution reference line segment as the radius;

[0076] Step b4, selecting all preliminary land transport delivery points located within the logistics distribution coverage area from all land transport delivery points for emergency medical supplies distribution, and forming a preliminary land transport delivery point set from all selected preliminary land transport delivery points;

[0077] Step b5: selecting preferred land transport delivery points that meet the current emergency medical logistics delivery needs from all the preliminarily selected land transport delivery point sets to form a preferred land transport delivery point set;

[0078] In step b6, all distribution points in the preferred land transport distribution point set are connected in order of distance from the emergency medical supplies starting point from the smallest to the largest, and the route formed by connecting all the preferred land transport distribution points is used as the aforementioned initial route for medical logistics land transport distribution.

[0079] In step b5 above, the process of selecting the preferred land delivery point includes the following steps:

[0080] Step b51: pre-acquire traffic congestion information for the default output routes of each of the preliminary land transport delivery points in the set of preliminary land transport delivery points during each preset delivery time period, and form a set of prior traffic congestion information using all acquired traffic congestion information; wherein each preliminary land transport delivery point corresponds to a default output route one-to-one, and the default output route is the driving route of a delivery logistics vehicle from the exit of the preliminary land transport delivery point to the intersection with the traffic light closest to the exit of the preliminary land transport delivery point; the traffic congestion information includes information about the preliminary land transport delivery point, each preset delivery time period, and a traffic congestion index corresponding to the preset delivery time period; the pre-acquired traffic congestion information for the default output routes of the preliminary land transport delivery points during each preset delivery time period serves as the prior traffic congestion information;

[0081] Step b52: Obtain the loadable delivery status of each preliminarily selected land transport delivery point. The loadable delivery status information includes the number of idle delivery personnel, the number of idle delivery vehicles, and the available cargo parameters of each delivery vehicle. The available cargo parameters of the delivery vehicle include the weight of the cargo that can be loaded.

[0082] In step b53, based on the estimated time period for the delivery of emergency medical supplies from each of the preselected land transportation distribution points, the established priori information on traffic congestion, and the load capacity of each preselected land transportation distribution point, a preferred preselected land transportation distribution point suitable for the current emergency medical supplies delivery is determined. The estimated delivery time period can be estimated using established methods for estimating travel (driving pattern) time, and will not be further described here.

[0083] This embodiment adopts the following steps b531 to b534 to determine the preferred preliminary land transportation delivery point:

[0084] Step b531, according to the loadable delivery status of each preliminary land transport delivery point, calculate the loadable delivery index of each preliminary land transport delivery point respectively, and calculate the loadable delivery index average of all loadable delivery indexes; wherein, the preliminary land transport delivery point s nThe load distribution index is marked as Ωs n The average value of all load delivery indices is marked as μ Ω :

[0085] Ωs n =min(P,M)·{Qs n / min(P,M)};Qs n =q1+q2+…+q M ;

[0086] μ Ω =(Ωs1+Ωs2…+Ωs M ) / M;

[0087] Among them, P is the primary land transportation distribution point s n The number of idle delivery personnel in the distribution center, M is the ... n The number of idle delivery vehicles in the

[0088] Qs n Preliminary land transport distribution points n The total weight of cargo that can be assembled on all idle vehicles in the n The weight of the cargo that can be assembled on the first delivery vehicle in the idle state, q2 is the initial land transport delivery point s n The weight of the cargo that can be assembled on the second delivery vehicle in an idle state, q M Preliminary land transport distribution points n The weight of cargo that can be assembled on the Mth delivery vehicle in an idle state;

[0089] Step b532: Select the primary land transportation delivery point corresponding to the loadable delivery index greater than the obtained average loadable delivery index as the first-level delivery point;

[0090] Step b533: Based on the aforementioned traffic congestion prior information set, the traffic congestion index corresponding to the estimated delivery time period of each first-level delivery point is matched; wherein the estimated delivery time period of each first-level delivery point is matched one-to-one with the preset delivery time period in the traffic congestion prior information set;

[0091] The road traffic operation index ranges from 0 to 10 and is divided into five levels. Among them, 0-2, 2-4, 4-6, 6-8, and 8-10 correspond to the five levels of "smooth", "basically smooth", "mild congestion", "moderate congestion", and "severe congestion" respectively; the higher the value of the road traffic operation index, the more serious the traffic congestion;

[0092] In step b534, the first-level distribution point whose traffic congestion index is less than the preset traffic congestion index threshold is selected as the preferred distribution point suitable for the current emergency medical supplies distribution; wherein, for the same estimated distribution time period, the first-level distribution point with the smallest traffic congestion index is selected as the preferred preliminary land transportation distribution point suitable for the current emergency medical supplies distribution.

[0093] See also Figure 4 As shown, in step 4 of this embodiment, the process of optimizing and obtaining the optimized medical logistics land transportation distribution route includes the following steps c1 to c4:

[0094] Step c1, estimating the estimated arrival time of the emergency medical supplies at each preferred land transport delivery point in sequence by logistics vehicles; wherein, during the delivery process, the emergency medical supplies are delivered from the previous preferred land transport delivery point to the next preferred land transport delivery point;

[0095] Step c2: Obtain weather information for each preferred land delivery point at its corresponding estimated arrival time;

[0096] Step c3: Determine whether the weather environment information obtained for each preferred land transportation delivery point is severe weather.

[0097] If any of the preferred land transport delivery points is experiencing severe weather conditions, proceed to step c4; otherwise, continue to deliver emergency medical supplies along the original medical logistics land transport delivery route.

[0098] Step c4: Send a request to the logistics distribution manager to extend the vehicle delivery route, and process the request based on the feedback from the logistics distribution manager:

[0099] When the feedback allows the current logistics vehicle's delivery route to be extended, the current vehicle is instructed to skip any preferred land delivery point and directly extend the delivery to the next preferred land delivery point after any preferred land delivery point; otherwise, the current logistics vehicle is instructed to continue delivering the emergency medical supplies to any preferred land delivery point.

[0100] Taking into account that when transporting emergency medical supplies by land, the forward speed of logistics vehicles performing land transportation may be affected by traffic congestion and other situations, this embodiment has made the following improvement measures for this situation, that is, the intelligent emergency medical logistics loading method based on mobile artificial intelligence in this embodiment also includes: according to the emergency medical logistics distribution timeliness requirements and the executed logistics land transportation distribution progress, the land-air combined transport distribution point where the emergency medical supplies are transported by land-operated drones is determined among all preferred land transportation distribution points, and the drone is ordered to execute the drone collaborative distribution planning path for the current emergency medical supplies distribution at the land-air combined transport distribution point, so as to transport the medical supplies directly to the last preferred land transportation distribution point in the medical logistics land transportation distribution optimization route.

[0101] For the above-mentioned land-air transport distribution points, see Figure 5 As shown, in this embodiment, the process of determining the land-air intermodal delivery point includes the following steps d1 to d4:

[0102] Step d1, pre-acquire the traffic congestion index of the area near each preferred land transport distribution point in different time periods of a day to obtain the traffic congestion information of the preferred land transport distribution point; wherein, in the traffic congestion information of the preferred land transport distribution point, for the area near each preferred land transport distribution point, the time period corresponds to the traffic congestion index one by one; the traffic congestion index (or traffic operation index) is a conceptual index value that comprehensively reflects the smoothness or congestion of the road network. The traffic index ranges from 0 to 10 and is divided into five levels (i.e., "smooth", "basically smooth", "mild congestion", "moderate congestion", and "severe congestion"). The higher the value, the more serious the traffic congestion. As the relevant calculation method of the traffic congestion index is common knowledge in this field, it will not be described here;

[0103] Step d2: pre-estimating the time period during which the emergency medical supplies will arrive from the previous land transport delivery point to the next land transport delivery point, and the traffic congestion index corresponding to the time period, based on the traffic congestion information of the preferred land transport delivery point;

[0104] Step d3: making a judgment based on the arrival time period corresponding to the last preferred land transportation delivery point in the pre-estimated optimized medical logistics land transportation delivery route and the emergency medical logistics delivery timeliness requirement:

[0105] If the arrival time is later than the emergency medical logistics delivery time requirement, proceed to step d4; otherwise, continue to perform land transportation delivery according to the original medical logistics land transportation delivery optimization route;

[0106] In step d4, the preferred land transport delivery points that have completed land transport delivery are used as failed delivery points in the preferred land transport delivery point set, and the non-failed delivery points in the preferred land transport delivery point set and whose estimated traffic congestion index is greater than the preset index threshold are used as land-air combined transport delivery points.

[0107] Although the preferred embodiments of the present invention have been described in detail above, it should be clearly understood that various modifications and variations are possible for those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention are intended to be included within the scope of protection of the present invention.

Claims

1. A smart emergency medical logistics loading method based on mobile artificial intelligence, characterized by: The steps include: Step 1: Pre-build a land-air collaborative logistics distribution system based on the linkage of vehicle-based land transportation and drone-based air transportation; Step 2: Based on the emergency medical logistics distribution needs and emergency medical logistics vehicle information, an emergency medical logistics loading plan is obtained; Step 3: Plan the initial medical logistics land transportation distribution route based on the emergency medical logistics distribution needs and the starting point of emergency medical supplies; Step 4: Extract the delivery point information of each delivery point on the initial medical logistics land transportation delivery route, and optimize the initial medical logistics land transportation delivery route based on the acquired delivery point information of all delivery points to obtain the optimized medical logistics land transportation delivery route; Step 5: The emergency medical supplies loaded according to the emergency medical logistics loading plan will be distributed by land transportation according to the optimized medical logistics land transportation distribution route; Step 6: Based on the timeliness requirements of emergency medical logistics and the progress of the executed land transportation, execute the drone collaborative delivery planning route for the current emergency medical supplies delivery; Step 7: Instruct the drone to perform emergency medical logistics delivery according to the current drone collaborative delivery planning path.

2. The intelligent emergency medical logistics loading method based on mobile artificial intelligence according to claim 1 is characterized in that: In step 2, the process of obtaining the emergency medical logistics loading plan based on the emergency medical logistics distribution demand and the emergency medical logistics vehicle information processing includes the following steps: Step a1: extracting the distribution urgency of each medical supply in the emergency medical logistics distribution demand; wherein, medical supplies with a high distribution urgency are given priority in distribution; Step a2: Obtain vehicle condition information for each logistics vehicle managed by the medical supplies originating point, and perform quantitative post-processing on each logistics vehicle based on this condition information to obtain a safe transport index for the logistics vehicle. The condition information includes the normal speed and risk factor of the logistics vehicle when fully loaded, with the risk factor being positively correlated with the full load of the logistics vehicle. Step a3: sort the logistics vehicles in descending order of their safety load index to obtain a logistics vehicle loading sequence; Step a4: Match each medical supply to each logistics vehicle in the logistics vehicle loading sequence in descending order of delivery urgency, obtaining a vehicle-cargo loading mapping relationship list; each medical supply is preferentially matched to a logistics vehicle with a higher safety load index; if the number of logistics vehicles at the origin is limited, the logistics vehicles are loaded until they are full according to the delivery urgency of the medical supplies; medical supplies not loaded by the current batch of logistics vehicles are configured to be loaded onto the next batch of logistics vehicles; Step a5: Load each medical supply onto the corresponding logistics vehicle according to the obtained vehicle-cargo loading mapping relationship list.

3. The intelligent emergency medical logistics loading method based on mobile artificial intelligence according to claim 2 is characterized in that: In step a2, the safe transport index of the logistics vehicle is calculated as follows: in, is the safety carrying index of logistics vehicle i, v i is the normal driving speed of logistics vehicle i under full load, |v i | is the normal driving speed v i The value after removing the unit, M i is the full load of logistics vehicle i, where the full load is the mass of the loaded goods, |M i | is the full load M i The values ​​after removing the unit are: α is the adjustment parameter corresponding to the normal driving speed of the logistics vehicle when fully loaded; β is the adjustment parameter corresponding to the full load of the logistics vehicle when fully loaded; N is the total number of logistics vehicles managed by the medical supplies departure point.

4. The intelligent emergency medical logistics loading method based on mobile artificial intelligence according to claim 3 is characterized in that: In step 3, based on the emergency medical logistics distribution needs and the starting point of emergency medical supplies, the process of planning the initial medical logistics land transportation distribution route includes the following steps: Step b1, obtaining the location of the demand point for emergency medical logistics distribution; Step b2: connecting the demand point and the emergency medical supplies origin point, and using the resulting line segment as a reference line segment for emergency medical supplies distribution; Step b3: constructing a logistics distribution coverage area corresponding to the emergency medical logistics distribution demand, with the midpoint of the emergency medical supplies distribution reference line segment as the center and half the length of the emergency medical supplies distribution reference line segment as the radius; Step b4, selecting all preliminary land transport delivery points located within the logistics distribution coverage area from all land transport delivery points for emergency medical supplies distribution, and forming a preliminary land transport delivery point set from all selected preliminary land transport delivery points; Step b5: selecting preferred land transport delivery points that meet the current emergency medical logistics delivery needs from all the preliminarily selected land transport delivery point sets to form a preferred land transport delivery point set; Step b6: All distribution points in the preferred land transport distribution point set are connected in ascending order of distance from the emergency medical supplies departure point, and the route formed by connecting all preferred land transport distribution points is used as the initial route for the medical logistics land transport distribution.

5. The intelligent emergency medical logistics loading method based on mobile artificial intelligence according to claim 3 is characterized in that: In step 4, the process of optimizing and obtaining the optimized medical logistics land transportation distribution route includes the following steps: Step c1, estimating the estimated arrival time of the emergency medical supplies at each preferred land transport delivery point in sequence by logistics vehicles; wherein, during the delivery process, the emergency medical supplies are delivered from the previous preferred land transport delivery point to the next preferred land transport delivery point; Step c2: Obtain weather information for each preferred land delivery point at its corresponding estimated arrival time; Step c3: Determine whether the weather environment information obtained for each preferred land transportation delivery point is severe weather. If any of the preferred land transport delivery points is experiencing severe weather conditions, proceed to step c4; otherwise, continue to deliver emergency medical supplies along the original medical logistics land transport delivery route. Step c4: Send a request to the logistics distribution manager to extend the vehicle delivery route, and process the request based on the feedback from the logistics distribution manager: When the feedback allows the current logistics vehicle's delivery route to be extended, the current vehicle is instructed to skip any preferred land delivery point and directly extend the delivery to the next preferred land delivery point after any preferred land delivery point; otherwise, the current logistics vehicle is instructed to continue delivering the emergency medical supplies to any preferred land delivery point.

6. The intelligent emergency medical logistics loading method based on mobile artificial intelligence according to claim 5 is characterized in that: Also includes: According to the timeliness requirements of emergency medical logistics distribution and the progress of the executed logistics land transportation distribution, a land-air combined transport distribution point where emergency medical supplies are transported by land-operated drones is determined among all the preferred land transportation distribution points, and the drone is ordered to execute the drone collaborative distribution planning path for the current emergency medical supplies distribution at this land-air combined transport distribution point to transport the medical supplies directly to the last preferred land transportation distribution point in the medical logistics land transportation distribution optimization route.

7. The intelligent emergency medical logistics loading method based on mobile artificial intelligence according to claim 6 is characterized in that: The process of determining the land-air intermodal transport distribution point includes the following steps: Step d1: pre-acquire traffic congestion indexes for the areas near each preferred land transport delivery point at different time periods within a day to obtain traffic congestion information for the preferred land transport delivery points; wherein, in the traffic congestion information for the preferred land transport delivery points, for each preferred land transport delivery point, the time period corresponds to the traffic congestion index; Step d2: pre-estimating the time period during which the emergency medical supplies will arrive from the previous land transport delivery point to the next land transport delivery point, and the traffic congestion index corresponding to the time period, based on the traffic congestion information of the preferred land transport delivery point; Step d3: making a judgment based on the arrival time period corresponding to the last preferred land transportation delivery point in the pre-estimated optimized medical logistics land transportation delivery route and the emergency medical logistics delivery timeliness requirement: If the arrival time is later than the emergency medical logistics delivery time requirement, proceed to step d4; otherwise, continue to perform land transportation delivery according to the original medical logistics land transportation delivery optimization route; In step d4, the preferred land transport delivery point that has completed the logistics land transport delivery is used as the failed delivery point in the preferred land transport delivery point set, and the non-failed delivery point in the preferred land transport delivery point set and whose estimated traffic congestion index is greater than the preset index threshold is used as the land-air combined transport delivery point.

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