An intelligent control system and method based on activity flow

Abstract

The present application discloses an intelligent control system and method based on activity flow, which relates to the field of intelligent management technology, and solves the technical problem that it is difficult to comprehensively monitor the flow of activities in the existing activity flow control, resulting in low flexibility in dealing with emergencies and failure to promptly deal with problems arising in the activities; the application comprises: an interactive module: used to obtain basic activity data; an activity planning module: generating activity planning according to basic activity data; an activity quality inspection module: obtaining real-time activity data, and generating adjustment signals based on the activity planning and real-time activity data activity progress; an adjustment module: obtaining adjustment signals, and adjusting the activity content based on the adjustment signals, activity planning and real-time activity data, and updating the activity planning; being able to monitor the activity progress in real time, promptly discover anomalies in the activity progress, and adjust subsequent activity projects according to the anomalies; and improving the flexibility in dealing with emergencies.

Description

Technical Field

[0001] The present application belongs to the field of intelligent management technology, and relates to intelligent management technology, specifically an activity process-based intelligent control system and method. Background Art

[0002] Activity process management covers the entire process of meticulous planning and orderly management of each link from the initial stage of activity planning to the entire process of activity execution. This process includes clarifying the goals of the activity, making detailed plans, coordinating resources from all parties, monitoring the progress of the activity, and ensuring that the activity proceeds smoothly according to the predetermined process. Activity process management requires professional knowledge and skills to ensure the successful implementation of the activity, and continuously optimize and improve the process to meet the needs and expectations of participants or stakeholders. Through scientific and systematic process management, activities can better achieve their expected goals and bring greater value to enterprises or organizations. Existing activity process management is usually planned and managed manually; however, the workload of manual planning and management is large. When managing activities that take a long time, employees have limited energy and it is difficult to fully monitor the process of the activity, resulting in low flexibility in dealing with emergencies and failure to respond to problems that arise in the activity in a timely manner; therefore, an intelligent control system and method based on activity processes are needed. Summary of the invention

[0003] The present application aims to solve at least one of the technical problems existing in the prior art; to this end, the present application proposes an intelligent control system and method based on activity flow, which is used to solve the technical problems in the existing activity flow control that it is difficult to comprehensively monitor the activity flow, resulting in low flexibility in dealing with emergencies and failure to promptly deal with problems arising in the activity. The present application solves the above problems by obtaining the project progress and process time of the activity in real time and updating the activity planning in a timely manner.

[0004] To achieve the above-mentioned purpose, the first aspect of the present application provides an intelligent control system based on activity flow, including: an interaction module, an activity planning module, an activity self-checking module, an adjustment module and a database;

[0005] Interaction module: obtains basic activity data through interactive devices; the basic activity data includes activity theme, time range, region range and number of participants;

[0006] Activity planning module: input the activity theme and the number of participants in the basic data of the activity into the content planning model to obtain the activity content; the content planning model is obtained by training the artificial intelligence model; the activity form is generated based on the project venue in the activity content; the activity location is generated based on the activity content and the regional scope; the activity time is selected based on the activity content and the time range; the activity content, activity location and activity time are integrated into the activity plan;

[0007] Activity quality inspection module: obtains real-time activity data, including activity projects, project progress and process time; generates adjustment signals based on activity planning and real-time activity data activity progress;

[0008] Adjustment module: obtains adjustment signals, and adjusts the activity content based on the adjustment signals, activity planning and real-time activity data, and updates the activity planning.

[0009] The present application obtains basic activity data, generates activity content according to the activity theme and number of participants in the basic activity data; generates activity form according to the project venue of the activity content; generates activity location according to the activity content and regional scope; selects activity time according to the activity content and time range; integrates activity content, activity location and activity time into activity planning; obtains real-time activity data, and determines whether there is any abnormality in the activity process according to the activity project, project progress and progress time in the real-time activity data, as well as the activity planning; if there is any abnormality, generates a corresponding adjustment signal, and updates the activity planning according to the adjustment signal; can monitor the activity process in real time, promptly discover abnormalities in the activity process, and adjust subsequent activity projects according to the abnormalities; and improves flexibility in responding to emergencies.

[0010] Preferably, the content planning model is obtained by training an artificial intelligence model, including:

[0011] Acquire a number of historical activity data through a database, extract activity themes, number of participants and activity content from the historical activity data; integrate the activity themes, number of participants and activity content into a number of training data and test data;

[0012] The artificial intelligence model is trained using training data, and is tested using test data; ultimately a content planning model is obtained, with activity theme and number of participants as input and activity content as output; wherein the activity content includes a number of activity stage data, and the activity stage data includes a number of activity projects, project duration, and corresponding project venues; the project venue includes venue size and venue type; the artificial intelligence model includes a BP neural network model or an RBF neural network model.

[0013] Preferably, generating the activity form based on the project venue in the activity content includes:

[0014] Determine whether the site types in each project site are the same;

[0015] If yes, then when the venue types in each project venue are all indoor venues, the activity form is set to indoor form; otherwise, the activity form is set to outdoor form;

[0016] No, set the activity format to mixed format;

[0017] The venue types include indoor venues and outdoor venues.

[0018] Preferably, generating the activity location based on the activity content and the regional scope includes:

[0019] Extract several project sites in each activity stage in the activity content; obtain the site size with the largest value among several project sites with the same site type, and mark it as the activity site area of ​​the corresponding site type;

[0020] Obtain several vacant activity venues within a region, as well as their corresponding venue areas and venue forms; calculate the venue areas corresponding to the activity venues whose venue forms include the activity forms among several activity venues; generate available venues based on the venue areas and activity venue areas;

[0021] Get the unit time rental of all available venues; take the available activity venue corresponding to the smallest unit time rental as the activity location; the venue type and activity type have the same data type, including indoor type, outdoor type and mixed type.

[0022] Preferably, generating the available venue based on the venue area and the activity venue area includes:

[0023] Determine whether the activity form is a mixed form;

[0024] If yes, then extract the indoor venue area and outdoor venue area from the venue area corresponding to the activity venue; when the indoor venue area is larger than the activity venue area of ​​the indoor venue, and the outdoor venue area is larger than the activity venue area of ​​the outdoor venue; then mark the activity venue as an available venue;

[0025] If not, then when the activity type is indoor, obtain the indoor venue area of ​​the activity venue; when the venue area is larger than the activity venue area of ​​an indoor venue, set the activity venue as an available venue; when the activity type is outdoor, obtain the outdoor venue area of ​​the activity venue; when the venue area is larger than the activity venue area of ​​an outdoor venue, set the activity venue as an available venue; wherein the venue area includes the indoor venue area and the outdoor venue area.

[0026] Preferably, the activity time is selected based on the activity content and time range, including:

[0027] Mark the project time corresponding to each activity item in the activity content as XMi, where i is the number of each activity item in the activity content, and they are numbered in sequence according to the order in which the activities are carried out;

[0028] By formula Calculate the rest time XXi corresponding to the activity item numbered i; where α is the adjustment coefficient; β is the accuracy coefficient; ZS is the maximum rest time, i=1, 2, ..., n-1; n is the total number of activity items in the activity content; the rest time corresponding to the last activity item is "0";

[0029] The activity duration HC is calculated by the formula HC=∑(XMi+XXi); wherein i=1, 2, ..., n;

[0030] According to the activity duration, continuous time is selected in the time range as the activity time, and the project activity time of each activity project is marked in the activity time.

[0031] This application generates corresponding rest time according to the project time of the activity project, so that the rest time can adapt to the corresponding activity project, so that the people participating in the activity can have enough time to rest, increase the enthusiasm of the people participating in the activity, and increase the satisfaction of the activity.

[0032] Preferably, generating the adjustment signal based on activity planning and real-time activity data activity progress includes:

[0033] Extract the current active project, project progress and process time from the real-time activity data; generate an estimated project time based on the project progress and process time; obtain the project activity time of the activity project corresponding to the current active project in the activity plan; determine whether the estimated project time is greater than the sum of the project activity time and its corresponding rest time;

[0034] If yes, a timeout adjustment signal is generated;

[0035] If not, when the estimated project time is greater than the project activity time and less than the sum of the project activity time and its corresponding rest time, a rest time adjustment signal is generated; the adjustment signal includes an overtime adjustment signal and a rest time adjustment signal.

[0036] Preferably, generating the estimated project time according to the project progress and progress time includes:

[0037] The project process is marked as XJa and the process time is marked as JCa. The estimated project time is calculated using the formula YSa=γ×XJa / JCa. Among them, γ is the adjustment coefficient, which is set based on experience.

[0038] Preferably, adjusting the activity content based on the adjustment signal, the activity plan and the real-time activity data, and updating the activity plan, comprises:

[0039] Determine whether the adjustment signal is a rest duration adjustment signal;

[0040] If yes, then obtain the project time XMa and the corresponding rest time XXa of the activity project corresponding to the current activity project; calculate the estimated project time YSa of the current activity project; and obtain the adjusted rest time TXa by the formula TXa=XMa+XXa-YSa; and update the corresponding project time and rest time in the activity plan with the estimated project time and rest time;

[0041] If not, then replace the corresponding project time in the activity plan according to the estimated project time, and calculate the estimated activity duration and the estimated rest duration of each project according to the project time in the activity plan; when the difference between the estimated activity duration and the activity duration is greater than the smallest project duration among the remaining activity projects; delete the activity project, generate new activity content, and update the activity plan according to the activity content; otherwise, update the corresponding project time and rest duration in the activity plan according to the estimated project time and the estimated rest duration of each project.

[0042] The second aspect of the present application provides an activity flow-based intelligent control method, comprising the following steps:

[0043] Step 1: Obtain basic activity data; the basic activity data includes activity theme, time range, region range and number of participants;

[0044] Step 2: Input the activity theme and the number of participants in the basic data of the activity into the content planning model to obtain the activity content; the content planning model is obtained by training the artificial intelligence model;

[0045] Step 3: Generate the activity form according to the project venue in the activity content; generate the activity location according to the activity content and regional scope; select the activity time according to the activity content and time range; integrate the activity content, activity location and activity time into the activity plan;

[0046] Step 4: Acquire real-time activity data, which includes activity projects, project progress, and progress time;

[0047] Step 5: Generate adjustment signals based on activity planning and real-time activity data activity progress;

[0048] Step 6: Adjust the event content and update the event plan based on the adjustment signal, event plan and real-time event data.

[0049] Compared with the prior art, the beneficial effects of this application are:

[0050] 1. This application obtains basic activity data, generates activity content according to the activity theme and number of participants in the basic activity data; generates activity form according to the project venue of the activity content; generates activity location according to the activity content and regional scope; selects activity time according to the activity content and time range; integrates activity content, activity location and activity time into activity planning; obtains real-time activity data, and determines whether there is any abnormality in the activity process based on the activity project, project progress and process time in the real-time activity data, as well as the activity planning. If there is any abnormality, a corresponding adjustment signal is generated, and the activity planning is updated according to the adjustment signal; the activity process can be monitored in real time, abnormalities in the activity process can be discovered in time, and subsequent activity projects can be adjusted according to the abnormalities; and the flexibility in responding to emergencies is improved.

[0051] 2. This application generates corresponding rest time according to the project time of the activity project, so that the rest time can adapt to the corresponding activity project, so that the participants can have enough time to rest, increase the enthusiasm of the participants, and increase the satisfaction of the activity. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0053] Figure 1 This is a schematic diagram of the principle of this application;

[0054] Figure 2 Schematic diagram of the method steps in this application. DETAILED DESCRIPTION

[0055] The technical solution of the present application will be described clearly and completely below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in the field without creative work are within the scope of protection of the present application.

[0056] See also Figure 1-Figure 2 , the first aspect of the present application provides an intelligent control system based on activity flow, including: an interaction module, an activity planning module, an activity self-checking module, an adjustment module and a database;

[0057] Interactive module: obtain basic activity data through interactive devices; basic activity data includes activity theme, time range, region range and number of participants; interactive devices include mobile phones, computers and tablets, etc.;

[0058] Activity planning module: input the activity theme and the number of participants in the basic data of the activity into the content planning model to obtain the activity content; the content planning model is obtained through the training of the artificial intelligence model; the activity form is generated based on the project venue in the activity content; the activity location is generated based on the activity content and the regional scope; the activity time is selected based on the activity content and time range; the activity content, activity location and activity time are integrated into the activity plan;

[0059] Activity quality inspection module: obtain real-time activity data, including activity projects, project progress and process time; generate adjustment signals based on activity planning and real-time activity data activity progress;

[0060] Adjustment module: obtains adjustment signals, and adjusts the activity content based on the adjustment signals, activity planning and real-time activity data, and updates the activity planning.

[0061] In this embodiment, by acquiring basic activity data, the activity content is generated according to the activity theme and the number of participants in the basic activity data; the activity form is generated according to the project venue of the activity content; the activity location is generated according to the activity content and the regional scope; the activity time is selected according to the activity content and the time range; the activity content, activity location and activity time are integrated into an activity plan; real-time activity data is acquired, and it is determined whether there is any abnormality in the activity process according to the activity project, project progress and progress time in the real-time activity data, as well as the activity plan. If there is any abnormality, a corresponding adjustment signal is generated, and the activity plan is updated according to the adjustment signal; the activity process can be monitored in real time, abnormalities in the activity process can be discovered in time, and subsequent activity projects can be adjusted according to the abnormalities; the flexibility in responding to emergencies is improved.

[0062] The content planning model is obtained through artificial intelligence model training, including:

[0063] Acquire a number of historical activity data through a database, extract activity themes, number of participants and activity content from the historical activity data; integrate the activity themes, number of participants and activity content into a number of training data and test data;

[0064] The artificial intelligence model is trained using training data, and is tested using test data; ultimately a content planning model is obtained, with activity theme and number of participants as input and activity content as output; wherein the activity content includes a number of activity stage data, and the activity stage data includes a number of activity projects, project duration, and corresponding project venues; the project venue includes venue size and venue type; the artificial intelligence model includes a BP neural network model or an RBF neural network model.

[0065] Generate activity forms based on the project sites in the activity content, including:

[0066] Determine whether the site types in each project site are the same;

[0067] If yes, then when the venue types in each project venue are all indoor venues, the activity form is set to indoor form; otherwise, the activity form is set to outdoor form;

[0068] No, set the activity format to mixed format;

[0069] The venue types include indoor venues and outdoor venues.

[0070] Generate event locations based on event content and regional scope, including:

[0071] Extract several project sites in each activity stage in the activity content; obtain the site size with the largest value among several project sites with the same site type, and mark it as the activity site area of ​​the corresponding site type;

[0072] Obtain several vacant activity venues within a region, where it can be understood that vacant activity venues refer to venues that are not rented within a time range; and their corresponding venue areas and venue forms; obtain the venue areas corresponding to the activity venues whose venue forms include the activity forms among several activity venues; generate available venues based on the venue areas and activity venue areas; specifically, include: determining whether the activity form is a mixed form;

[0073] If yes, then extract the indoor venue area and outdoor venue area from the venue area corresponding to the activity venue; when the indoor venue area is larger than the activity venue area of ​​the indoor venue, and the outdoor venue area is larger than the activity venue area of ​​the outdoor venue; then mark the activity venue as an available venue;

[0074] If not, then when the activity type is indoor, obtain the indoor venue area of ​​the activity venue; when the venue area is larger than the activity venue area of ​​an indoor venue, set the activity venue as an available venue; when the activity type is outdoor, obtain the outdoor venue area of ​​the activity venue; when the venue area is larger than the activity venue area of ​​an outdoor venue, set the activity venue as an available venue; wherein the venue area includes the indoor venue area and the outdoor venue area.

[0075] Get the unit time rental of all available venues; take the available activity venue corresponding to the smallest unit time rental as the activity location; the venue type and activity type have the same data type, including indoor type, outdoor type and mixed type.

[0076] It can be understood that when the venue form is a mixed form, no matter whether the activity form is indoor, outdoor or mixed, the venue form includes the activity form; when the venue form is indoor, the venue form only includes the indoor activity form; when the venue form is outdoor, the venue form only includes the outdoor activity form.

[0077] In this embodiment, the venue type of each project venue in the activity content and the rental of each available venue are comprehensively considered to select the most cost-effective available venue as the event location, ensuring that sufficient venues are provided for each project of the activity while the rental is low.

[0078] Select the activity time based on the activity content and time range, including:

[0079] The project time corresponding to each activity item in the activity content is marked as XMi, where i is the number of each activity item in the activity content, and is numbered in sequence according to the order in which the activities are carried out; the project time is the planned time for the corresponding activity item;

[0080] By formula Calculate the rest time XXi corresponding to the activity item numbered i; where α is the adjustment coefficient; β is the accuracy coefficient; ZS is the maximum rest time, i=1, 2, ..., n-1; n is the total number of activity items in the activity content; the rest time corresponding to the last activity item is "0";

[0081] The activity duration HC is calculated by the formula HC=∑(XMi+XXi); wherein i=1, 2, ..., n;

[0082] According to the activity duration, continuous time is selected in the time range as the activity time, and the project activity time of each activity project is marked in the activity time.

[0083] In this embodiment, corresponding rest time is generated according to the project time of the activity project, so that the rest time can adapt to the corresponding activity project, so that the participants can have enough time to rest, increase the enthusiasm of the participants, and increase the satisfaction of the activity.

[0084] Generating the adjustment signal based on activity planning and real-time activity data activity progress includes:

[0085] Extract the current activity project, project progress and process time from the real-time activity data; generate an estimated project time based on the project progress and process time; the estimated project time is the estimated duration of the corresponding activity project inferred based on the activity progress and process time; obtain the project activity time of the activity project corresponding to the current activity project in the activity plan; determine whether the estimated project time is greater than the sum of the project activity time and its corresponding rest time;

[0086] If yes, a timeout adjustment signal is generated;

[0087] No, when the estimated project time is greater than the project activity time and less than the sum of the project activity time and its corresponding rest time, a rest time adjustment signal is generated; the adjustment signal includes an overtime adjustment signal and a rest time adjustment signal; the overtime adjustment signal indicates that the actual activity time is far longer than the planned activity time, and the rest time adjustment signal indicates that the actual activity time exceeds the planned activity time, but the excess is not much, which can be resolved by coordinating the rest time; the signal generated.

[0088] Generate estimated project time based on project progress and progress time, including:

[0089] The project process is marked as XJa and the process time is marked as JCa. The estimated project time is calculated using the formula YSa=γ×XJa / JCa. Among them, γ is the adjustment coefficient, which is set based on experience.

[0090] In this embodiment, an estimated project time is obtained based on a prediction made according to the actual real-time activity progress. The project activity time of the activity project corresponding to the activity plan is used to determine whether there is any abnormality in the activity. If so, an adjustment signal is generated based on the abnormal situation, and the activity plan is adjusted based on the adjustment signal to ensure that the activity can proceed smoothly.

[0091] Adjust event content based on adjustment signals, event planning, and real-time event data, and update event planning, including:

[0092] Determine whether the adjustment signal is a rest duration adjustment signal;

[0093] If yes, then obtain the project time XMa and the corresponding rest time XXa of the activity project corresponding to the current activity project; calculate the estimated project time YSa of the current activity project; and obtain the adjusted rest time TXa by the formula TXa=XMa+XXa-YSa; and update the corresponding project time and rest time in the activity plan with the estimated project time and rest time;

[0094] If not, then replace the corresponding project time in the activity plan according to the estimated project time, and calculate the estimated activity duration and the estimated rest duration of each project according to the project time in the activity plan; when the difference between the estimated activity duration and the activity duration is greater than the smallest project duration among the remaining activity projects; delete the activity project, generate new activity content, and update the activity plan according to the activity content; otherwise, update the corresponding project time and rest duration in the activity plan according to the estimated project time and the estimated rest duration of each project.

[0095] In this embodiment, when an actual activity is in progress and an activity project has a long delay time, the activity project with the smallest project duration among the remaining unperformed activity projects in the activity plan will be deleted; so that the total duration of the activity will not exceed the planned activity duration in the activity plan; when the activity project delay time is short, the corresponding rest time will be shortened to ensure that the activity can be completed within the specified time.

[0096] The second aspect of the present application provides an activity flow-based intelligent control method, comprising the following steps:

[0097] Step 1: Obtain basic activity data; the basic activity data includes activity theme, time range, region range and number of participants;

[0098] Step 2: Input the activity theme and the number of participants in the basic data of the activity into the content planning model to obtain the activity content; the content planning model is obtained by training the artificial intelligence model;

[0099] Step 3: Generate the activity form according to the project venue in the activity content; generate the activity location according to the activity content and regional scope; select the activity time according to the activity content and time range; integrate the activity content, activity location and activity time into the activity plan;

[0100] Step 4: Acquire real-time activity data, which includes activity projects, project progress, and progress time;

[0101] Step 5: Generate adjustment signals based on activity planning and real-time activity data activity progress;

[0102] Step 6: Adjust the event content and update the event plan based on the adjustment signal, event plan and real-time event data.

[0103] Part of the data in the above formula is calculated by removing the dimension and taking its numerical value. The formula is a formula closest to the actual situation obtained by software simulation of a large amount of collected data; the preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained through simulation of a large amount of data.

[0104] How this application works:

[0105] The present application obtains basic activity data, generates activity content according to the activity theme and number of participants in the basic activity data; generates activity form according to the project venue of the activity content; generates activity location according to the activity content and regional scope; selects activity time according to the activity content and time range; integrates activity content, activity location and activity time into activity planning; obtains real-time activity data, and determines whether there is any abnormality in the activity process according to the activity project, project progress and progress time in the real-time activity data, as well as the activity planning; if there is any abnormality, generates a corresponding adjustment signal, and updates the activity planning according to the adjustment signal; can monitor the activity process in real time, promptly discover abnormalities in the activity process, and adjust subsequent activity projects according to the abnormalities; and improves flexibility in responding to emergencies.

[0106] The above embodiments are only used to illustrate the technical method of the present application and are not intended to limit it. Although the present application has been described in detail with reference to the preferred embodiments, a person of ordinary skill in the art should understand that the technical method of the present application may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present application.

Claims

1. An intelligent control system based on activity flow, comprising: Interaction module, activity planning module, activity self-checking module, adjustment module and database; characterized in that, Interaction module: obtains basic activity data through interactive devices; the basic activity data includes activity theme, time range, region range and number of participants; Activity planning module: input the activity theme and the number of participants in the basic data of the activity into the content planning model to obtain the activity content; the content planning model is obtained by training the artificial intelligence model; the activity form is generated based on the project venue in the activity content; the activity location is generated based on the activity content and the regional scope; the activity time is selected based on the activity content and the time range; the activity content, activity location and activity time are integrated into the activity plan; the activity time is selected based on the activity content and the time range, including: Mark the project time corresponding to each activity item in the activity content as XMi, where i is the number of each activity item in the activity content, and they are numbered in sequence according to the order in which the activities are carried out; By formula Calculate the rest time XXi corresponding to the activity item numbered i; where α is the adjustment coefficient; β is the accuracy coefficient; ZS is the maximum rest time, i=1, 2, ..., n-1; n is the total number of activity items in the activity content; the rest time corresponding to the last activity item is "0"; The activity duration HC is calculated by the formula HC=∑(XMi+XXi); wherein i=1, 2, ..., n; According to the activity duration, select continuous time in the time range as the activity time, and mark the project activity time of each activity project in the activity time; Activity quality inspection module: obtains real-time activity data, including activity projects, project progress and process time; generates adjustment signals based on activity planning and real-time activity data activity progress; Adjustment module: obtains adjustment signals, and adjusts the activity content based on the adjustment signals, activity planning and real-time activity data, and updates the activity planning.

2. According to claim 1, an intelligent control system based on activity flow is characterized in that: The content planning model is obtained through artificial intelligence model training, including: Acquire a number of historical activity data through a database, extract activity themes, number of participants and activity content from the historical activity data; integrate the activity themes, number of participants and activity content into a number of training data and test data; The artificial intelligence model is trained using training data, and is tested using test data; ultimately a content planning model is obtained, with activity theme and number of participants as input and activity content as output; wherein the activity content includes a number of activity stage data, and the activity stage data includes a number of activity projects, project duration, and corresponding project venues; the project venue includes venue size and venue type; the artificial intelligence model includes a BP neural network model or an RBF neural network model.

3. The intelligent control system based on activity flow according to claim 1 is characterized in that: The activity form is generated based on the project site in the activity content, including: Determine whether the site types in each project site are the same; If yes, then when the venue types in each project venue are all indoor venues, the activity form is set to indoor form; otherwise, the activity form is set to outdoor form; No, set the activity format to mixed format; The venue types include indoor venues and outdoor venues.

4. The intelligent control system based on activity flow according to claim 3 is characterized in that: The activity location is generated based on the activity content and the regional scope, including: Extract several project sites in each activity stage in the activity content; obtain the site size with the largest value among several project sites with the same site type, and mark it as the activity site area of ​​the corresponding site type; Obtain several vacant activity venues within a region, as well as their corresponding venue areas and venue forms; calculate the venue areas corresponding to the activity venues whose venue forms include the activity forms among several activity venues; generate available venues based on the venue areas and activity venue areas; Get the unit time rental of all available venues; take the available activity venue corresponding to the smallest unit time rental as the activity location; the venue type and activity type have the same data type, including indoor type, outdoor type and mixed type.

5. The intelligent control system based on activity flow according to claim 4 is characterized in that: The available venue is generated based on the venue area and the activity venue area, including: Determine whether the activity form is a mixed form; If yes, then extract the indoor venue area and outdoor venue area from the venue area corresponding to the activity venue; when the indoor venue area is larger than the activity venue area of ​​the indoor venue, and the outdoor venue area is larger than the activity venue area of ​​the outdoor venue; then mark the activity venue as an available venue; If not, then when the activity type is indoor, obtain the indoor venue area of ​​the activity venue; when the venue area is larger than the activity venue area of ​​an indoor venue, set the activity venue as an available venue; when the activity type is outdoor, obtain the outdoor venue area of ​​the activity venue; when the venue area is larger than the activity venue area of ​​an outdoor venue, set the activity venue as an available venue; wherein the venue area includes the indoor venue area and the outdoor venue area.

6. The intelligent control system based on activity flow according to claim 1 is characterized in that: Generating the adjustment signal based on activity planning and real-time activity data activity progress includes: Extract the current active project, project progress and process time from the real-time activity data; generate an estimated project time based on the project progress and process time; obtain the project activity time of the activity project corresponding to the current active project in the activity plan; determine whether the estimated project time is greater than the sum of the project activity time and its corresponding rest time; If yes, a timeout adjustment signal is generated; If not, when the estimated project time is greater than the project activity time and less than the sum of the project activity time and its corresponding rest time, a rest time adjustment signal is generated; the adjustment signal includes an overtime adjustment signal and a rest time adjustment signal.

7. The intelligent control system based on activity flow according to claim 6 is characterized in that: The estimated project time is generated based on the project progress and progress time, including: The project process is marked as XJa and the process time is marked as JCa; the estimated project time is calculated using the formula YSa=γ×XJa / JCa; where γ is the adjustment coefficient.

8. The intelligent control system based on activity flow according to claim 7 is characterized in that: Adjusting the activity content based on the adjustment signal, the activity plan and the real-time activity data, and updating the activity plan, including: Determine whether the adjustment signal is a rest duration adjustment signal; If yes, then obtain the project time XMa and the corresponding rest time XXa of the activity project corresponding to the current activity project; calculate the estimated project time YSa of the current activity project; and obtain the adjusted rest time TXa by the formula TXa=XMa+XXa-YSa; and update the corresponding project time and rest time in the activity plan with the estimated project time and rest time; If not, then replace the corresponding project time in the activity plan according to the estimated project time, and calculate the estimated activity duration and the estimated rest duration of each project according to the project time in the activity plan; when the difference between the estimated activity duration and the activity duration is greater than the smallest project duration among the remaining activity projects; delete the activity project, generate new activity content, and update the activity plan according to the activity content; otherwise, update the corresponding project time and rest duration in the activity plan according to the estimated project time and the estimated rest duration of each project.

9. An intelligent control method based on an activity flow, operating based on any one of the intelligent control systems based on an activity flow according to claims 1 to 8, characterized in that: The following steps are involved: Step 1: Obtain basic activity data; the basic activity data includes activity theme, time range, region range and number of participants; Step 2: Input the activity theme and number of participants in the basic data of the activity into the content planning model to obtain the activity content; The content planning model is obtained through artificial intelligence model training; Step 3: Generate activity form according to the project venue in the activity content; Generate activity locations based on activity content and regional scope; select activity time based on activity content and time range; Integrate the event content, event location and event time into event planning; Step 4: Acquire real-time activity data, which includes activity projects, project progress, and progress time; Step 5: Generate adjustment signals based on activity planning and real-time activity data activity progress; Step 6: Adjust the event content and update the event plan based on the adjustment signal, event plan and real-time event data.

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