CN113592205A - Intelligent scheduling method, device, equipment and medium based on multidimensional data analysis - Google Patents
Intelligent scheduling method, device, equipment and medium based on multidimensional data analysis Download PDFInfo
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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Abstract
The embodiment of the invention discloses an intelligent scheduling method, an intelligent scheduling device, intelligent scheduling equipment and an intelligent scheduling medium based on multidimensional data analysis. The method comprises the following steps: determining pickup motion parameter information when a target receiving user respectively goes to at least two express delivery cabinets to pick up the express; according to the pickup motion parameter information when the target receiving user goes to different express cabinets to pick up the express, the pickup consumption cost when the target receiving user goes to at least two express cabinets to pick up the express is determined; and determining a target express cabinet from at least two express cabinets according to the express item taking consumption cost so as to place deposited items after the target receiving user places an order. By adopting the scheme, the express cabinet is not selected according to the distance between the express cabinet and the express user, but the express cabinet is selected according to the express taking cost adaptability of the express taking parameter comprehensive consideration of the motion parameter in the express taking process of the express user, so that the express placing position is optimized from the angle of multi-dimensional data analysis, the service quality of community management is improved, and the intelligent community management efficiency is improved.
Description
Technical Field
The embodiment of the invention relates to the technical field of logistics express delivery, in particular to an intelligent scheduling method, device, equipment and medium based on multidimensional data analysis.
Background
The express delivery cabinet is along with the new-born thing of express delivery industry constantly developing, sets up the express delivery cabinet at the community periphery, and when the express delivery of customer inconvenient taking, can post express delivery article and have the express delivery cabinet, realize that the express delivery access is convenient.
The concept of the future community is essentially to improve the living bodies of residents, and the express cabinet which needs to be reasonably selected for express placement of the express cabinet of the community is convenient for the addressees to take the express nearby. However, express delivery article are placed usually by user's appointed or dispatch person and are appointed, if not appointed then unordered placing, cause some customers to get a distance longer, lead to the customer to need to spend more time and get a piece to make the customer produce not good use experience, then can be unfavorable for community management efficiency to promote because of lacking intelligent service consciousness in the long-term past.
Disclosure of Invention
The embodiment of the invention provides an intelligent scheduling method, device, equipment and medium based on multidimensional data analysis, which are used for realizing position optimization placement of express delivery articles and intelligent optimization of delivery service.
In a first aspect, an embodiment of the present invention provides an intelligent scheduling method based on multidimensional data analysis, where the method includes:
determining pickup motion parameter information when a target receiving user respectively goes to at least two express delivery cabinets to pick up the express;
according to the pickup motion parameter information when the target receiving user goes to different express cabinets to pick up the express, the pickup consumption cost when the target receiving user goes to at least two express cabinets to pick up the express is determined;
and determining a target express cabinet from at least two express cabinets according to the express item taking consumption cost so as to place deposited items after the target receiving user places an order.
In a second aspect, an embodiment of the present invention further provides an intelligent scheduling apparatus based on multidimensional data analysis, where the apparatus includes:
the motion parameter determining module is used for determining pickup motion parameter information when the target receiving user respectively goes to at least two express cabinets to pick up the express;
the express delivery system comprises a delivery cost determining module, a delivery cost determining module and a delivery cost determining module, wherein the delivery cost determining module is used for determining delivery consumption costs when a target receiving user respectively goes to at least two express delivery cabinets to take the delivery according to delivery motion parameter information when the target receiving user goes to different express delivery cabinets to take the delivery;
and the express dispatching and placing module is used for determining a target express cabinet from the at least two express cabinets according to the express taking cost so as to place deposited articles after the target receiving user places the order.
In a third aspect, an embodiment of the present invention further provides an electronic device, including:
one or more processing devices;
storage means for storing one or more programs;
when the one or more programs are executed by the one or more processing devices, the one or more processing devices are enabled to implement the intelligent scheduling method based on multidimensional data analysis as provided in any embodiment of the invention.
In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processing apparatus, implements the intelligent scheduling method based on multidimensional data analysis as provided in any embodiment of the present invention.
The embodiment of the invention provides an intelligent scheduling method based on multidimensional data analysis, which is characterized by determining pickup motion parameter information when a target pickup user respectively goes to at least two express cabinets to pick up a pickup, and determining pickup consumption cost when the target pickup user respectively goes to at least two express cabinets to pick up a pickup according to the pickup motion parameter information when going to different express cabinets to pick up the pickup, so that when deposited articles of the target pickup user are deposited and placed, the target express cabinet is determined from the at least two express cabinets according to the pickup consumption cost, and the deposited articles after the target pickup user orders are placed by using the selected target express cabinet. By adopting the scheme, when the placement positions of the deposited objects are selected, the fixed express cabinet is not used, the express cabinet is not simply selected according to the distance between the recipient user and the express cabinet, the express cabinet is suitable for being selected according to the pickup cost adaptability, which is comprehensively considered by determining the motion parameters of the recipient user in the express taking process, so that the express placement positions are optimized from the perspective of multi-dimensional data analysis, the service quality of community management is improved, and the intelligent community management efficiency is improved.
The above summary of the present invention is merely an overview of the technical solutions of the present invention, and the present invention can be implemented in accordance with the content of the description in order to make the technical means of the present invention more clearly understood, and the above and other objects, features, and advantages of the present invention will be more clearly understood.
Drawings
Other features, objects and advantages of the invention will become more apparent upon reading of the following detailed description of non-limiting embodiments thereof, made with reference to the accompanying drawings. The drawings are only for purposes of illustrating the preferred embodiments and are not to be construed as limiting the invention. Also, like reference numerals are used to refer to like parts throughout the drawings. In the drawings:
fig. 1 is a flowchart of an intelligent scheduling method based on multidimensional data analysis provided in an embodiment of the present invention;
FIG. 2 is a flow chart of another intelligent scheduling method based on multidimensional data analysis provided in the embodiment of the present invention;
FIG. 3 is a flowchart of another intelligent scheduling method based on multidimensional data analysis, provided in the embodiment of the present invention;
fig. 4 is a structural block of an intelligent scheduling apparatus based on multidimensional data analysis provided in an embodiment of the present invention;
fig. 5 is a schematic structural diagram of an electronic device provided in an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention. It should be further noted that, for the convenience of description, only some of the structures related to the present invention are shown in the drawings, not all of the structures.
Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations (or steps) can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
The following embodiments and alternatives thereof will explain the intelligent scheduling method, apparatus, electronic device and storage medium based on multidimensional data analysis provided in the present application in detail.
Fig. 1 is a flowchart of an intelligent scheduling method based on multidimensional data analysis according to an embodiment of the present invention. The embodiment of the invention can be suitable for the condition that the express cabinet at a proper position is selected for the deposited articles to be deposited in the express cabinet by the recipient user. The method can be executed by an intelligent scheduling device based on multidimensional data analysis, the device can be realized in a software and/or hardware mode, and is integrated on any electronic equipment with a network communication function, and the electronic equipment can be a platform server of an express delivery cabinet operator.
As shown in fig. 1, the intelligent scheduling method based on multidimensional data analysis provided in the embodiment of the present application may include the following steps:
and S110, determining pickup motion parameter information when the target receiving user respectively goes to at least two express delivery cabinets to pick up the express.
And S120, determining the pickup cost of the target receiving user when the target receiving user respectively goes to at least two express cabinets to pick up the express according to the pickup motion parameter information when the target receiving user goes to different express cabinets to pick up the express.
Near the express delivery deposit service area, for example near various communities, a plurality of express delivery cabinets are usually configured in advance, and a courier can pick deposit items to be deposited and place the deposit items in grids of the express delivery cabinets for temporary placement. However, in order to facilitate the service community, the express cabinets are usually distributed around the express delivery deposit service area, rather than being uniformly arranged in one location.
In some conventional geographical location areas, such as areas with gentle terrain, a proper express cabinet is selected according to the distance from the express cabinet, so that the deposited articles are placed, and the addressee can take the articles nearby. However, in other non-conventional geographical location areas, for example, areas with complex terrain or great difficulty in walking (such as climbing a slope) even if the express delivery cabinet is relatively close to the express delivery cabinet, the express delivery cabinet cannot be taken to take deposited articles easily, and thus simple nearby taking is not easy.
Therefore, the express delivery cabinets are not selected by using simple distance related parameters, the pickup motion parameter information when the target receiving users respectively go to different express delivery cabinets to pick up the express items is selected, and the pickup motion parameter information can reflect motion consumption data of the receiving users in the process of going to different express delivery cabinets to pick up the express items. According to the motion parameter information of taking the express when going to different express cabinets to take the express, the difficulty of taking the express can be analyzed from the parameters of multiple dimensions, the consumption cost of taking the express when the target addressee user goes to the express cabinet to take the express is obtained, the consumption cost of taking the express is not limited to the distance condition, and meanwhile, the consumption condition of the body function of the target addressee user is also included.
In an alternative of this embodiment, determining the pickup movement parameter information when the target recipient user respectively goes to at least two express cabinets for pickup may include the following steps a1-a 2:
and step A1, acquiring pickup motion parameter information which is acquired by the wearable device and is used when the target receiving user goes to the express cabinet to pick up the pickup.
And A2, counting pickup motion parameter information of the target recipient user when the target recipient user respectively goes to different express cabinets to pick up the express within a preset time period.
Target addressee user can normally wear wearable device, for example all kinds of intelligent bracelet, wearable devices such as intelligent wrist-watch, installs the APP of express delivery cabinet operation side on the wearable device and uses. The APP application installed on the wearable device can be in data communication with a platform server of an express operator. When the target receiving user goes to the express cabinet to take the express, the wearable device collects the pickup motion parameter information of the target receiving user in the corresponding process. The exercise parameters include, but are not limited to, step count, heart rate, blood pressure, and exercise parameters such as caloric expenditure, exercise path, and calories expended.
At the beginning, the courier places the express at random in a plurality of express cabinets that set up around the community, and the target addressee user receives the deposit article to the corresponding express cabinet according to the notice. After a period of time, the platform server may count pickup movement parameter information of each recipient user when the recipient user respectively goes to different express cabinets for pickup within a preset time period, for example, count pickup movement parameter information of the recipient user from a residence to each express cabinet within the preset time period.
In an alternative of this embodiment, the obtaining of the pickup motion parameter information, which is collected by the wearable device and is obtained when the target recipient user goes to the express delivery cabinet to pick up the pickup, may include the following steps B1-B2:
and step B1, when the movement speed of the target pickup user is detected to be larger than the preset threshold value, starting and controlling the wearable device to acquire the movement parameter information of the target pickup user in the moving process.
The wearable device can acquire the motion parameters anytime and anywhere, and it becomes more important to correctly acquire pickup motion parameters in the pickup process of the target recipient user. Considering that the human body can generate the step number when walking fast, the step counting can not be carried out when the human body is static relatively, therefore, the walking step number of the target receiving user can be intercepted in real time through the application APP on the wearable device, and the walking movement speed of the target receiving user is calculated.
If the movement speed of the target pickup user is detected to be smaller than or equal to the preset threshold value, the user is considered to be at home if the step counting speed is low, and the wearable device is not started to collect the data. If the movement speed of the target pickup user is detected to be greater than the preset threshold value, the possibility that the target recipient user is on the road is very high, and at the moment, the application APP on the wearable device is started and used for continuously acquiring the continuously generated movement parameter information in the moving process of the target pickup user.
And step B2, when the target pickup user adopts the wearable device to scan and open the express cabinet, acquiring the motion parameter information of the target pickup user collected by the wearable device when the express cabinet is opened, and taking the motion parameter information as pickup motion parameter information when the target pickup user starts from a residential place and goes to the express cabinet for pickup.
When the target addressee finishes scanning and opening the express delivery cabinet to take the express delivery, the APP installed on the wearable device can upload motion parameters continuously obtained from leaving a residence to opening the express delivery cabinet or closing the express delivery cabinet to the express delivery cabinet, and upload motion parameter information of taking the express delivery when the target addressee user goes to the express delivery cabinet to take the express delivery to a platform server of an express delivery operator by means of the express delivery cabinet. Optionally, after the collected motion parameters are uploaded to the express delivery cabinet and a reception confirmation message of the express delivery cabinet is obtained, the motion parameters collected by the APP application installed on the wearable device are cleared, so that the motion parameters can be collected continuously.
Optionally, when the APP application installed on the wearable device detects that the wearable device is not step-counted for a long time (e.g., a preset time) or that the step-counting is slow, the APP application installed on the wearable device clears the motion parameter recorded by the APP application. When the wearable device is rapidly counting the steps, the APP application installed on the wearable device continuously counts the steps, and the recipient user is explained to move.
S130, according to the express item taking consumption cost, determining a target express cabinet from at least two express cabinets so as to place deposited items after ordering by a target receiving user.
Optionally, determining the target express delivery cabinet from the at least two express delivery cabinets according to the respective pickup consumption cost may include: and selecting the express cabinet with the lowest express item taking cost when the express cabinet is moved to for taking the express item from the at least two express cabinets as the target express cabinet. After the consignee places the deposit item, the courier can place the deposit item to the target express cabinet which is away from the residence of the consignee and has the least comprehensive pickup consumption cost by default.
According to the intelligent scheduling method based on multidimensional data analysis provided by the embodiment of the invention, when the placement position of the deposited object is selected, a fixed express cabinet is not used, and the selection is not simply carried out according to the distance between the recipient user and the express cabinet, but a proper express cabinet is selected according to the pickup cost which is comprehensively considered by determining the motion parameters of the recipient user in the process of picking up the express, so that the express placement position is optimized from the perspective of multidimensional data analysis, the service quality of community management is improved, and the management efficiency of an intelligent community is improved.
Fig. 2 is a flowchart of another intelligent scheduling method based on multidimensional data analysis in an embodiment of the present invention, and this embodiment further optimizes the foregoing embodiment on the basis of the foregoing embodiment, and may be combined with various alternatives in one or more of the foregoing embodiments. As shown in fig. 2, the intelligent scheduling method based on multidimensional data analysis provided in the embodiment of the present application may include the following steps:
s210, determining pickup movement parameter information when the target receiving user respectively goes to at least two express delivery cabinets to pick up the express.
Optionally, determining pickup movement parameter information when the target recipient user respectively goes to at least two express delivery cabinets to pick up the item may include: acquiring pickup motion parameter information acquired by a wearable device when a target receiving user goes to an express cabinet for pickup; the exercise parameters include step number, heart rate, blood pressure and caloric expenditure; and counting pickup motion parameter information of the target pickup user when the target pickup user respectively goes to different express cabinets to pick up the pickup within a preset time period.
S220, analyzing the unit function consumption corresponding to different step number intervals when the target receiving user goes to the express cabinet to take the express item aiming at different express cabinets.
Wherein, the function consumption comprises heart rate, blood pressure and heat consumption, and the size of the single-computer function consumption is in direct proportion to the weight.
In the region with fluctuating terrain, the addressee user is closer to the express delivery cabinet A from the residential area, but may need to climb up in the pickup process. On the contrary, the receiving user is slightly far away from the residence to the express delivery cabinet B, but the position of the receiving user is possibly gentle and easy in the express delivery taking process. Therefore, as can be seen from the foregoing analysis, it is not particularly reasonable to select couriers based solely on the number of steps or distance the recipient user has from the residence to the various courier cabinets.
Certainly, although the target receiving user goes to the same express delivery cabinet to pick up the target, the physical function consumption is different at different walking step stages in the pick-up process; for example, taking the unit function consumption as the unit heart rate, for example, the recipient takes a total of 1000 steps from the residence to the express delivery cabinet, and the heart rates are measured at 84/s, 105/s and 121/s at 500 steps, 300 steps and 200 steps, respectively, so that the difference of the unit function consumption of the body at different stages can be seen.
Therefore, the unit computer energy consumption can be divided into different consumption levels, different unit consumption levels are endowed with different weight values, the unit machine energy consumption is in direct proportion to the weight, and the larger the unit machine energy consumption is, the larger the weight is; a higher weight indicates a greater impact on the pickup cost per consumption level. For example, the heart rate may be divided into a plurality of consumption levels such as 80/s, 100/s, 120/s, etc., each consumption level being weighted by 1, 1.1, 1.2, respectively.
And S230, determining weights corresponding to the deployments of the different step intervals according to the unit function consumption corresponding to the different step intervals, and performing weighted summation on the deployments of the different step intervals to obtain pickup consumption cost when the target receiving user goes to the express cabinet to pick up the target receiving user, so as to obtain pickup consumption cost when the target receiving user goes to at least two express cabinets to pick up the target receiving user.
When calculating the pickup consumption cost, the pickup consumption cost is not determined by only integrating the steps from the residence to the express delivery cabinet of the pickup user, but the steps from the residence to the express delivery cabinet of the pickup user and the unit function consumption corresponding to different step intervals in the pickup process are combined and comprehensively analyzed. For example, the wearable device of the recipient user has a motion parameter measurement function. For the same recipient user, walking habits of the same recipient user are usually kept consistent, so that the wearable device APP measures the motion parameters of the recipient user every other preset time period to obtain corresponding unit function consumption.
And carrying out weighted summation on the deployments in different step intervals to obtain a comprehensive step of comprehensive multidimensional data analysis, and taking the comprehensive step as the pickup consumption cost when the target receiving user goes to the express cabinet to pick up the piece. For example, taking the unit function consumption as the heart rate, the recipient user has 1000 steps from the residence to the express delivery cabinet, and if the heart rates are measured 84 times/second, 105 times/second and 121 times/second at 500 steps, 300 steps and 200 steps, respectively, the total number of steps is 500 × 1+300 × 1.1+200 × 1.2=500+330+240=1070 steps, and this is used as the pickup consumption cost when the target recipient user goes to the express delivery cabinet for pickup.
S240, according to the express item taking consumption cost, determining a target express cabinet from the at least two express cabinets so as to place deposited items after the target receiving user places an order.
According to the intelligent scheduling method based on multidimensional data analysis provided by the embodiment of the invention, when the placement position of a deposited object is selected, a fixed express cabinet is not used, and the selection is also not simply carried out according to the distance between a recipient user and the express cabinet, but the motion parameters of the recipient user in the express taking process are determined to comprehensively consider the motion parameters such as the step number, the heart rate, the blood pressure and the heat consumption in the express taking process to comprehensively analyze the express taking consumption condition, so that the appropriate express cabinet is adaptively selected, the express placement position is optimized from the perspective of multidimensional data analysis, the service quality of community management is improved, and the intelligent community management efficiency is improved.
Fig. 3 is a flowchart of another intelligent scheduling method based on multidimensional data analysis in an embodiment of the present invention, and this embodiment further optimizes the foregoing embodiment on the basis of the foregoing embodiment, and may be combined with various alternatives in one or more of the foregoing embodiments. As shown in fig. 3, the intelligent scheduling method based on multidimensional data analysis provided in the embodiment of the present application may include the following steps:
s310, determining pickup motion parameter information when the target receiving user respectively goes to at least two express delivery cabinets to pick up the express.
And S320, determining the pickup cost of the target receiving user when the target receiving user respectively goes to at least two express cabinets to pick up the express according to the pickup motion parameter information when the target receiving user goes to different express cabinets to pick up the express.
S330, determining a target express cabinet from the at least two express cabinets according to the express item taking cost so as to place deposited items after the target receiving user places an order.
S340, determining at least one candidate receiving user having a neighbor relation with the target receiving user and the geographic information of the residence where the target receiving user is located.
In an alternative aspect of this embodiment, determining at least one candidate recipient user having a neighbor relationship with the target recipient user may include the following steps C1-C2:
and step C1, sending an interception notification to the express application of the target recipient user so as to instruct the express application to detect the Media Access Control (MAC) address of the wireless local area network within the preset detection range of the target recipient user in the early morning.
And step C2, determining at least one candidate recipient user within the preset detection range of the target recipient user according to the detected wireless local area network media access control MAC address within the preset time period.
When the APP installed on the wearable device is registered, an application identifier APP-ID can be obtained from a platform server of an express cabinet operator and used for representing a recipient user. The APP installed on the wearable device sends a wireless local area network Media Access Control (MAC) (wifi) address of the wearable device to the platform server, and the platform maintains an association relationship between the APP-ID and the wifi.
Platform server of express delivery cabinet operator can inform the APP of installation on every wearable device to use and listen near the wearable device in the period of early morning and predetermine the wifimac in the detection range to and place geographical position information, upload to platform server together, so select this time in early morning, because this time point is the time that everybody sleeps, the wifimac that passes through temporarily is less, therefore the wifimac of gathering is the MAC address information of neighbor usually. Through the incidence relation between the APP-ID and the wifi mac recorded during registration, the platform server can obtain the APP-ID set of the neighbor user living together with the target recipient user and the geographic information of the living place.
Optionally, within a preset time (one month), continuously collecting the wifi macs installed on the wearable device and used for intercepting nearby the wearable device and the geographical positions of the APP applications in the early morning, performing intersection processing on the wifi macs collected in different early morning periods by the platform server, selecting a relatively stable wifi macs set, wherein the set comprises the wifi macs corresponding to the collected APP-IDs, that is, obtaining the APP-ID set of the neighbor user which accurately resides together with the target recipient user, so that at least one candidate recipient user in the preset detection range of the target recipient user can be obtained.
S350, determining a reference receiving user from at least one candidate receiving user; the express cabinet corresponding to the reference receiving user and determined according to the pickup consumption cost is not the target express cabinet.
Because the pickup route of each recipient user is selected independently, the express cabinets determined by different recipient users according to the pickup consumption cost may be different from the target express cabinet selected by the target recipient user. For example, some express cabinets selected by the at least one candidate express receiving user according to the pickup consumption cost may be target express cabinets selected by the target express receiving user, and some express cabinets selected by the other candidate express receiving users according to the pickup consumption cost may not be target express cabinets selected by the target express receiving user.
And S360, if the ratio of the reference receiving users in the at least one candidate receiving user is larger than the preset ratio, prompting to change and correct the target express cabinet determined by the target receiving user.
Under normal conditions, the target receiving user and the candidate receiving user have a neighbor relation, and the target receiving user and the candidate receiving user usually go to the same express cabinet to deposit articles according to the pickup consumption cost. Based on the analysis, if the candidate receiving users corresponding to most APP-IDs in the at least one candidate receiving user determine that one express cabinet is closer to the residence of the candidate receiving user according to the pickup consumption cost, and the candidate receiving users corresponding to a small number of individual APP-IDs in the at least one candidate receiving user determine that other express cabinets are closer to the residence of the candidate receiving user according to the pickup consumption cost, it is indicated that the pickup routes taken by the candidate receiving users corresponding to the small number of individual APP-IDs are probably not correct.
If the proportion of the reference receiving users in the at least one candidate receiving user is larger than the preset proportion, the most candidate receiving users which have a neighbor relation with the target receiving user are indicated to have lower pickup consumption cost of other express cabinets except the target express, so that the pickup route of the target receiving user can be prompted to be corrected, the pickup consumption cost can be calculated again, and the determined target express cabinet is changed and corrected according to the recalculated pickup consumption cost to obtain a new target express cabinet. If the proportion of the reference receiving users in the at least one candidate receiving user is smaller than or equal to the preset proportion, the fact that most candidate receiving users having a neighbor relation with the target receiving user accept the target express is lower in pickup consumption cost, and the target receiving user is still determined to select the determined target express cabinet to place deposited goods.
For example, the platform server finds the abnormal situation, issues the electronic map for the community to the APP-ID corresponding recipient users, and enables the APP application records installed on the wearable devices of the APP-ID corresponding recipient users to travel from the residence to the express cabinet. It can be found that most of the APP-IDs corresponding to the recipient users have similar routes, and only the routes of the recipient users corresponding to the individual APP-IDs are different. The platform server records a route RouteA where the receiving users corresponding to most APP-IDs walk, and places the express mails of the receiving users corresponding to the individual APP-IDs into an express cabinet A. When individual APP-ID recipient users go to the express cabinet A to take the parcel, a recommended route RouteA from the residence to the express cabinet is displayed on the screen, and the recipient users are prompted to take the RouteA route closer to the express cabinet A.
According to the intelligent scheduling method based on multidimensional data analysis provided by the embodiment of the invention, when the placement position of the deposited object is selected, a fixed express cabinet is not used any more, and the selection is not simply carried out according to the distance between the addressee and the express cabinet, but comprehensively analyzes the pickup consumption condition by comprehensively considering the motion parameters such as the step number, the heart rate, the blood pressure, the heat consumption and the like in the pickup process by determining the motion parameters in the pickup process of the recipient user, further adaptively selecting a proper express cabinet, realizing the optimization of the express placing position from the angle of multi-dimensional data analysis, realizing the reminding of the optimized route based on the analysis of the multi-dimensional data, and the conceptual design of the comprehensive steps is provided, the calculation of the optimized route is realized, the service quality of community management can be improved, and the management efficiency of the intelligent community can be improved.
Fig. 4 is a structural block of an intelligent scheduling apparatus based on multidimensional data analysis provided in an embodiment of the present invention. The embodiment of the invention can be suitable for the condition that the express cabinet at a proper position is selected for the deposited articles to be deposited in the express cabinet by the recipient user. The device can be realized in a software and/or hardware mode and integrated on any electronic equipment with a network communication function, and the electronic equipment can be a platform server of an express cabinet operator.
As shown in fig. 4, the intelligent scheduling apparatus based on multidimensional data analysis provided in the embodiment of the present application may specifically include the following: a motion parameter determination module 410, a pickup cost determination module 420 and a courier dispatch placement module 430. Wherein
The motion parameter determining module 410 is configured to determine pickup motion parameter information when a target recipient user separately goes to at least two express delivery cabinets to pick up a pickup;
the pickup cost determining module 420 is configured to determine, according to pickup motion parameter information when the target recipient user goes to different express cabinets to pick up a pickup, pickup consumption costs when the target recipient user goes to at least two express cabinets to pick up a pickup respectively;
and the express dispatching and placing module 430 is configured to determine a target express cabinet from the at least two express cabinets according to the express pickup consumption cost, so as to place deposited items after the target recipient user places an order.
On the basis of the above embodiment, optionally, the motion parameter determining module 410 includes:
acquiring pickup motion parameter information which is acquired by a wearable device and is used when a target pickup user goes to an express cabinet to pick up a pickup; the exercise parameters comprise step number, heart rate, blood pressure and caloric consumption;
and counting pickup motion parameter information of the target pickup user when the target pickup user respectively goes to different express cabinets to pick up the pickup within a preset time period.
On the basis of the above embodiment, optionally, acquiring pickup motion parameter information, collected by the wearable device, of the target recipient user when the target recipient user goes to the express delivery cabinet to pick up the item includes:
when the movement speed of the target pickup user is detected to be larger than a preset threshold value, starting and controlling the wearable device to acquire the movement parameter information of the target pickup user in the moving process;
when the target pickup user adopts the wearable device to scan and open the express cabinet, acquiring the motion parameter information of the target pickup user collected by the wearable device by opening the express cabinet, and taking the motion parameter information as the pickup motion parameter information when the target pickup user goes to the express cabinet from the residence to pick up the pickup.
On the basis of the foregoing embodiment, optionally, the pickup cost determining module 420 includes:
analyzing the unit function consumption corresponding to different step intervals when the target receiving user goes to the express cabinet to take the express according to different express cabinets;
determining weights corresponding to the deployments of the different step intervals according to the unit function consumptions corresponding to the different step intervals, and performing weighted summation on the deployments of the different step intervals to obtain a pickup consumption cost when a target receiving user goes to an express cabinet for pickup;
the energy consumption comprises heart rate, blood pressure and heat consumption, and the energy consumption of the single computer is in direct proportion to the weight.
On the basis of the foregoing embodiment, optionally, the apparatus further includes:
determining at least one candidate receiving user having a neighbor relation with the target receiving user and the geographic information of the residence where the target receiving user is located;
determining a reference recipient user from at least one candidate recipient user; the express cabinet corresponding to the reference receiving user and determined according to the pickup consumption cost is not the target express cabinet;
and if the ratio of the reference receiving users in the at least one candidate receiving user is greater than the preset ratio, prompting to change and correct the target express cabinet determined by the target receiving user.
Based on the foregoing embodiment, optionally, determining at least one candidate recipient user having a neighbor relationship with the target recipient user includes:
sending a monitoring notice to an express application of a target recipient user to indicate the express application to detect a Media Access Control (MAC) address of a wireless local area network within a preset detection range of the target recipient user in the early morning;
and determining at least one candidate receiving user in a preset detection range of the target receiving user according to the Media Access Control (MAC) address of the wireless local area network detected in a preset time period.
On the basis of the foregoing embodiment, optionally, the express dispatching and placing module 430 includes:
and selecting the express cabinet with the lowest express item taking cost when the express cabinet is moved to for taking the express item from the at least two express cabinets as the target express cabinet.
The intelligent scheduling device based on multidimensional data analysis provided in the embodiment of the present invention can execute the intelligent scheduling method based on multidimensional data analysis provided in any embodiment of the present invention, and has the corresponding functions and beneficial effects of executing the intelligent scheduling method based on multidimensional data analysis.
Fig. 5 is a schematic structural diagram of an electronic device provided in an embodiment of the present invention. As shown in fig. 5, the electronic device provided in the embodiment of the present invention includes: one or more processors 510 and storage 520; the processor 510 in the electronic device may be one or more, and fig. 5 illustrates one processor 510 as an example; storage 520 is used to store one or more programs; the one or more programs are executed by the one or more processors 510, so that the one or more processors 510 implement the intelligent scheduling method based on multidimensional data analysis according to any one of the embodiments of the present invention.
The electronic device may further include: an input device 530 and an output device 540.
The processor 510, the storage device 520, the input device 530 and the output device 540 in the electronic apparatus may be connected by a bus or other means, and fig. 5 illustrates an example of connection by a bus.
The storage device 520 in the electronic device is used as a computer-readable storage medium for storing one or more programs, which may be software programs, computer-executable programs, and modules, such as program instructions/modules corresponding to the intelligent scheduling method based on multidimensional data analysis provided in the embodiment of the present invention. The processor 510 executes various functional applications and data processing of the electronic device by executing software programs, instructions and modules stored in the storage device 520, that is, implements the intelligent scheduling method based on multidimensional data analysis in the above method embodiments.
The storage device 520 may include a storage program area and a storage data area, wherein the storage program area may store an operating system, an application program required for at least one function; the storage data area may store data created according to use of the electronic device, and the like. Further, the storage 520 may include high speed random access memory and may also include non-volatile memory, such as at least one magnetic disk storage device, flash memory device, or other non-volatile solid state storage device. In some examples, the storage 520 may further include memory located remotely from the processor 510, which may be connected to the device over a network. Examples of such networks include, but are not limited to, the internet, intranets, local area networks, mobile communication networks, and combinations thereof.
The input device 530 may be used to receive input numeric or character information and generate key signal inputs related to user settings and function control of the electronic apparatus. The output device 540 may include a display device such as a display screen.
And, when the one or more programs included in the electronic device are executed by the one or more processors 510, the programs perform the following operations:
determining pickup motion parameter information when a target receiving user respectively goes to at least two express delivery cabinets to pick up the express;
according to the pickup motion parameter information when the target receiving user goes to different express cabinets to pick up the express, the pickup consumption cost when the target receiving user goes to at least two express cabinets to pick up the express is determined;
and determining a target express cabinet from at least two express cabinets according to the express item taking consumption cost so as to place deposited items after the target receiving user places an order.
Of course, it will be understood by those skilled in the art that when one or more programs included in the electronic device are executed by the one or more processors 510, the programs may also perform related operations in the intelligent scheduling method based on multidimensional data analysis provided in any embodiment of the present invention.
An embodiment of the present invention provides a computer-readable medium, on which a computer program is stored, which, when executed by a processor, is configured to perform an intelligent scheduling method based on multidimensional data analysis, the method including:
determining pickup motion parameter information when a target receiving user respectively goes to at least two express delivery cabinets to pick up the express;
according to the pickup motion parameter information when the target receiving user goes to different express cabinets to pick up the express, the pickup consumption cost when the target receiving user goes to at least two express cabinets to pick up the express is determined;
and determining a target express cabinet from at least two express cabinets according to the express item taking consumption cost so as to place deposited items after the target receiving user places an order.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a Read Only Memory (ROM), an Erasable Programmable Read Only Memory (EPROM), a flash Memory, an optical fiber, a portable CD-ROM, an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. A computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take a variety of forms, including, but not limited to: an electromagnetic signal, an optical signal, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, Radio Frequency (RF), etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. An intelligent scheduling method based on multidimensional data analysis, the method comprising:
determining pickup motion parameter information when a target receiving user respectively goes to at least two express delivery cabinets to pick up the express;
according to the pickup motion parameter information when the target receiving user goes to different express cabinets to pick up the express, the pickup consumption cost when the target receiving user goes to at least two express cabinets to pick up the express is determined;
and determining a target express cabinet from at least two express cabinets according to the express item taking consumption cost so as to place deposited items after the target receiving user places an order.
2. The method of claim 1, wherein determining pickup movement parameter information when the target recipient user respectively goes to at least two express delivery cabinets for pickup comprises:
acquiring pickup motion parameter information which is acquired by a wearable device and is used when a target pickup user goes to an express cabinet to pick up a pickup; the exercise parameters comprise step number, heart rate, blood pressure and caloric consumption;
and counting pickup motion parameter information of the target pickup user when the target pickup user respectively goes to different express cabinets to pick up the pickup within a preset time period.
3. The method according to claim 2, wherein the obtaining of the pickup movement parameter information collected by the wearable device when the target recipient user goes to the express delivery cabinet for pickup comprises:
when the movement speed of the target pickup user is detected to be larger than a preset threshold value, starting and controlling the wearable device to acquire the movement parameter information of the target pickup user in the moving process;
when the target pickup user adopts the wearable device to scan and open the express cabinet, acquiring the motion parameter information of the target pickup user collected by the wearable device by opening the express cabinet, and taking the motion parameter information as the pickup motion parameter information when the target pickup user goes to the express cabinet from the residence to pick up the pickup.
4. The method of claim 2, wherein determining the pickup cost of the target recipient user when the target recipient user respectively goes to at least two express cabinets for pickup according to the pickup motion parameter information when going to different express cabinets for pickup comprises:
analyzing the unit function consumption corresponding to different step intervals when the target receiving user goes to the express cabinet to take the express according to different express cabinets;
determining weights corresponding to the deployments of the different step intervals according to the unit function consumptions corresponding to the different step intervals, and performing weighted summation on the deployments of the different step intervals to obtain a pickup consumption cost when a target receiving user goes to an express cabinet for pickup;
the energy consumption comprises heart rate, blood pressure and heat consumption, and the energy consumption of the single computer is in direct proportion to the weight.
5. The method of claim 1, wherein after determining the target courier cabinet from the at least two courier cabinets based on the respective pickup cost, further comprising:
determining at least one candidate receiving user having a neighbor relation with the target receiving user and the geographic information of the residence where the target receiving user is located;
determining a reference recipient user from at least one candidate recipient user; the express cabinet corresponding to the reference receiving user and determined according to the pickup consumption cost is not the target express cabinet;
and if the ratio of the reference receiving users in the at least one candidate receiving user is greater than the preset ratio, prompting to change and correct the target express cabinet determined by the target receiving user.
6. The method of claim 5, wherein determining at least one candidate recipient user that has a neighbor relationship with the target recipient user comprises:
sending a monitoring notice to an express application of a target recipient user to indicate the express application to detect a Media Access Control (MAC) address of a wireless local area network within a preset detection range of the target recipient user in the early morning;
and determining at least one candidate receiving user in a preset detection range of the target receiving user according to the Media Access Control (MAC) address of the wireless local area network detected in a preset time period.
7. The method of claim 1, wherein determining the target courier cabinet from the at least two courier cabinets based on the respective pickup cost comprises:
and selecting the express cabinet with the lowest express item taking cost when the express cabinet is moved to for taking the express item from the at least two express cabinets as the target express cabinet.
8. An intelligent scheduling apparatus based on multidimensional data analysis, the apparatus comprising:
the motion parameter determining module is used for determining pickup motion parameter information when the target receiving user respectively goes to at least two express cabinets to pick up the express;
the express delivery system comprises a delivery cost determining module, a delivery cost determining module and a delivery cost determining module, wherein the delivery cost determining module is used for determining delivery consumption costs when a target receiving user respectively goes to at least two express delivery cabinets to take the delivery according to delivery motion parameter information when the target receiving user goes to different express delivery cabinets to take the delivery;
and the express dispatching and placing module is used for determining a target express cabinet from the at least two express cabinets according to the express taking cost so as to place deposited articles after the target receiving user places the order.
9. An electronic device, comprising:
one or more processing devices;
storage means for storing one or more programs;
when executed by the one or more processing devices, cause the one or more processing devices to implement the intelligent scheduling method based on multidimensional data analysis of any of claims 1-7.
10. A computer-readable medium, on which a computer program is stored, which, when being executed by a processing means, carries out the intelligent scheduling method based on multidimensional data analysis of any of claims 1-7.
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