Task scheduling method and system based on dynamic adjustment

Abstract

The present invention discloses a task scheduling method and system based on dynamic adjustment, which constructs corresponding action combinations according to task actions and action positions, and constructs a task list according to multiple action combinations, thereby realizing the construction of the task list and ensuring the rationality of the task list. Further, the priorities of multiple action combinations are defined according to the second priority coefficient, the first priority coefficient and the task list, ensuring the accuracy of the priorities of multiple action combinations, and then triggering the action optimization of the intelligent device according to the priorities of multiple action combinations, the corresponding action distances and the working status of the intelligent device. At the same time, when the intelligent device performs synchronous actions on at least two action combinations, the task scheduling is triggered based on the dynamically adjusted task list, the intelligent device and the current scene, which is compatible with the dynamically adjusted task list, the intelligent device and the current scene, and realizes the adaptive regulation of the intelligent device in various scenes.

Description

Technical Field

[0001] The present invention relates to the technical field of task scheduling of intelligent devices, and in particular to a task scheduling method and system based on dynamic adjustment. Background Art

[0002] With the development of science and technology, smart devices are gradually applied to people's lives. Smart devices include smart home devices. Smart devices have multiple working modules and perform corresponding task actions through multiple working modules. In the prior art, a task list of smart devices is collected, and the task list sorts multiple action combinations according to a preset logic. The same preset logic is used in any scenario, and dynamic adjustment of the task list cannot be achieved, which even affects the dynamic compatibility of task scheduling of smart devices in various scenarios. Summary of the invention

[0003] The purpose of the present invention is to overcome the shortcomings of the prior art. The present invention provides a task scheduling method and system based on dynamic adjustment, which defines multiple task information of the smart device in the current scene based on the scene in which the smart device is located and multiple task signals of the smart device; defines corresponding task actions and action positions based on multiple task information, constructs corresponding action combinations according to the task actions and action positions, and constructs a task list according to multiple action combinations, thereby realizing the construction of the task list and ensuring the rationality of the task list, and fully considering the task actions and action positions of the smart device.

[0004] Furthermore, a first priority coefficient of multiple action combinations is defined based on the task list, the action module corresponding to the smart device and the current position of the smart device; a second priority coefficient is defined based on the task list, the urgency of the action evaluated by the smart device and the current time; the priority of multiple action combinations is defined according to the second priority coefficient, the first priority coefficient and the task list, so as to perform multi-dimensional control based on the second priority coefficient, the first priority coefficient and the task list, and ensure the accuracy of the priority of multiple action combinations, and then trigger the action optimization of the smart device according to the priority of multiple action combinations, the corresponding action distance and the working status of the smart device, thereby ensuring the autonomous optimization of the action by the smart device, and at the same time, when the smart device performs synchronous actions on at least two action combinations, the dynamic adjustment of the task list is triggered according to the working trajectory of the corresponding working module and the working time corresponding to the multiple working modules, and the task scheduling is triggered based on the dynamically adjusted task list, the smart device and the current scene, which is compatible with the dynamically adjusted task list, the smart device and the current scene, and the task scheduling of the task list after dynamic adjustment is realized, which ensures the dynamic compatibility of task scheduling and realizes the adaptive regulation of smart devices in various scenes.

[0005] The embodiment of the present invention provides a task scheduling method based on dynamic adjustment, which is applied to the task scheduling scenario of smart devices;

[0006] The task scheduling method based on dynamic adjustment includes:

[0007] Defining multiple task information of the smart device in the current scene based on the scene in which the smart device is located and multiple task signals of the smart device;

[0008] Define corresponding task actions and action positions based on multiple task information, construct corresponding action combinations according to the task actions and action positions, and construct a task list according to the multiple action combinations;

[0009] Defining first priority coefficients of multiple action combinations based on the task list, the action modules corresponding to the smart device, and the current location of the smart device;

[0010] defining a second priority coefficient based on the task list, the urgency of the action assessed by the smart device, and the current time;

[0011] Defining priorities of multiple action combinations according to the second priority coefficient, the first priority coefficient, and the task list, and triggering action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances, and the working status of the smart device;

[0012] When the smart device performs synchronous actions on at least two action combinations, the task list is dynamically adjusted according to the working trajectory of the corresponding working module and the working time corresponding to multiple working modules, and task scheduling is triggered based on the dynamically adjusted task list, smart device and current scene.

[0013] Optionally, the defining of multiple task information of the smart device in the current scene based on the scene in which the smart device is located and multiple task signals of the smart device includes:

[0014] In the indoor space where the smart device is located, collect the location of the smart device;

[0015] Defining multiple surrounding environment features based on the surrounding environment detection of the location of the smart device;

[0016] Associating the location of the smart device and multiple surrounding environment features, triggering scene detection according to the location of the smart device and multiple surrounding environment features;

[0017] Dynamically monitor smart devices and collect multiple task signals of smart devices in real time;

[0018] Multiple task information of the smart device in the current scene is defined according to the scene in which the smart device is located and multiple task signals of the smart device.

[0019] Optionally, defining corresponding task actions and action positions based on multiple task information, constructing corresponding action combinations according to the task actions and action positions, and constructing a task list according to the multiple action combinations includes:

[0020] Freeze multiple task information;

[0021] Defining corresponding task actions and action positions based on the analysis of multiple task information;

[0022] Dynamically associate task actions and action positions, and define corresponding association coefficients;

[0023] Construct corresponding action combinations based on multiple correlation coefficients, task actions, and action positions;

[0024] Collect the previous action status of the smart device and define the action sorting method according to the previous action status of the smart device;

[0025] Build a task list based on multiple action combinations and action ordering.

[0026] Optionally, the first priority coefficients of the plurality of action combinations are defined based on the task list, the action modules corresponding to the smart device, and the current location of the smart device, including:

[0027] Freeze task list;

[0028] Divide into multiple action combinations based on the analysis of the task list;

[0029] Matching the action module corresponding to the smart device and the current position of the smart device according to the multiple action combinations;

[0030] Defining a first matching coefficient based on each action combination and an action module corresponding to the smart device;

[0031] defining a second matching coefficient based on each action combination and the current position of the smart device;

[0032] The first priority coefficients of the plurality of action combinations are defined according to the first matching coefficient, the second matching coefficient, the model of the smart device and the preliminary priority matching table.

[0033] Optionally, defining the second priority coefficient based on the task list, the urgency of the action assessed by the smart device, and the current time includes:

[0034] Freeze task list;

[0035] Divide into multiple action combinations based on the analysis of the task list;

[0036] Matching the action urgency assessed by the smart device and the current time according to the combination of multiple actions;

[0037] Defining importance levels of the multiple action combinations according to the multiple action combinations and the action urgency assessed by the smart device;

[0038] Collect the current time and define the corresponding time level based on the current time and the previous work content of the smart device;

[0039] The time level, the importance level, and the plurality of work combinations are associated to define second priority coefficients of the plurality of action combinations.

[0040] Optionally, defining priorities of multiple action combinations according to the second priority coefficient, the first priority coefficient, and the task list, and triggering action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances, and the working status of the smart device, includes:

[0041] Set the second priority coefficient and the first priority coefficient;

[0042] Match the corresponding priority logic according to the current scene of the smart device, and control the second priority coefficient, the first priority coefficient and the task list in the priority logic;

[0043] The priorities of the plurality of action combinations are defined according to the second priority coefficient, the first priority coefficient and the task list.

[0044] Optionally, defining the priorities of multiple action combinations according to the second priority coefficient, the first priority coefficient, and the task list, and triggering the action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances, and the working status of the smart device, further includes:

[0045] Collect the continuous working time of the smart device, and define the action attenuation coefficient of the smart device according to the continuous working time of the smart device and the corresponding action loss;

[0046] Associating the priorities of multiple action combinations, the action attenuation coefficients of smart devices, and the corresponding action distances;

[0047] The operation time of each action combination is defined according to the priority of multiple action combinations, the action attenuation coefficient of the smart device and the corresponding action distance;

[0048] Trigger the action optimization of the smart device based on the operation time of each action combination and the working status of the smart device.

[0049] Optionally, when the smart device performs synchronous actions on at least two action combinations, the task list is dynamically adjusted according to the work track of the corresponding working module and the working time corresponding to the multiple working modules, and the task scheduling is triggered based on the dynamically adjusted task list, the smart device and the current scene, including:

[0050] Monitor the task list of the smart device in real time, define the synchronization state of the smart device according to the task list of the smart device and the response signal of the multiple action combinations, and at this time, trigger at least two action combinations to be performed simultaneously in the synchronization state of the smart device;

[0051] When the intelligent device performs synchronous actions on at least two action combinations, the working trajectories of the corresponding working modules are collected.

[0052] Optionally, when the smart device performs synchronous actions on at least two action combinations, the task list is dynamically adjusted according to the work track of the corresponding working module and the working time corresponding to the multiple working modules, and the task scheduling is triggered based on the dynamically adjusted task list, the smart device and the current scene, and further includes:

[0053] Associate the work tracks of the corresponding work modules and the work times corresponding to the multiple work modules;

[0054] Define the work progress of the corresponding work combination according to the work track of the corresponding work module and the work time corresponding to the multiple work modules, and trigger the update of the work progress of the corresponding work combination;

[0055] Triggering dynamic adjustment of the task list based on the update of the work progress of the corresponding work combination;

[0056] Multiple action combinations in the task list are dynamically adjusted according to the working progress of the smart device, and the working progress, priority and sorting of multiple action combinations are regulated;

[0057] The dynamically adjusted task list, smart device and current scene are associated, and task scheduling is triggered based on the dynamically adjusted task list, smart device and current scene.

[0058] In addition, an embodiment of the present invention further provides a task scheduling system based on dynamic adjustment, and the task scheduling system based on dynamic adjustment includes:

[0059] A task information module, used to define multiple task information of the smart device in the current scene based on the scene in which the smart device is located and multiple task signals of the smart device;

[0060] A task list module is used to define corresponding task actions and action positions based on multiple task information, construct corresponding action combinations according to the task actions and action positions, and construct a task list according to multiple action combinations;

[0061] A first priority coefficient module, used to define first priority coefficients of multiple action combinations based on the task list, the action module corresponding to the smart device, and the current position of the smart device;

[0062] A second priority coefficient module, used to define a second priority coefficient based on the task list, the urgency of the action assessed by the smart device, and the current time;

[0063] an action optimization module, used to define the priorities of multiple action combinations according to the second priority coefficient, the first priority coefficient and the task list, and trigger the action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances and the working status of the smart device;

[0064] The task scheduling module is used to trigger the dynamic adjustment of the task list according to the working trajectory of the corresponding working module and the working time corresponding to multiple working modules when the smart device performs synchronous actions on at least two action combinations, and trigger task scheduling based on the dynamically adjusted task list, smart device and current scene.

[0065] In an embodiment of the present invention, through the method in the embodiment of the present invention, multiple task information of the smart device in the current scene is defined based on the scene in which the smart device is located and multiple task signals of the smart device; corresponding task actions and action positions are defined based on the multiple task information, corresponding action combinations are constructed according to the task actions and action positions, and a task list is constructed according to the multiple action combinations, thereby realizing the construction of the task list and ensuring the rationality of the task list, and fully considering the task actions and action positions of the smart device.

[0066] Furthermore, a first priority coefficient of multiple action combinations is defined based on the task list, the action module corresponding to the smart device and the current position of the smart device; a second priority coefficient is defined based on the task list, the urgency of the action evaluated by the smart device and the current time; the priority of multiple action combinations is defined according to the second priority coefficient, the first priority coefficient and the task list, so as to perform multi-dimensional control based on the second priority coefficient, the first priority coefficient and the task list, and ensure the accuracy of the priority of multiple action combinations, and then trigger the action optimization of the smart device according to the priority of multiple action combinations, the corresponding action distance and the working status of the smart device, thereby ensuring the autonomous optimization of the action by the smart device, and at the same time, when the smart device performs synchronous actions on at least two action combinations, the dynamic adjustment of the task list is triggered according to the working trajectory of the corresponding working module and the working time corresponding to the multiple working modules, and the task scheduling is triggered based on the dynamically adjusted task list, the smart device and the current scene, which is compatible with the dynamically adjusted task list, the smart device and the current scene, and the task scheduling of the task list after dynamic adjustment is realized, which ensures the dynamic compatibility of task scheduling and realizes the adaptive regulation of smart devices in various scenes. BRIEF DESCRIPTION OF THE DRAWINGS

[0067] In order to more clearly illustrate the embodiments of the present invention 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 invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0068] Figure 1 is a flowchart of a task scheduling method based on dynamic adjustment in an embodiment of the present invention;

[0069] Figure 2 is a flow chart of S11 in the task scheduling method based on dynamic adjustment in an embodiment of the present invention;

[0070] Figure 3 is a flow chart of S12 in the task scheduling method based on dynamic adjustment in an embodiment of the present invention;

[0071] Figure 4 is a flow chart of S13 in the task scheduling method based on dynamic adjustment in an embodiment of the present invention;

[0072] Figure 5 is a flow chart of S14 in the task scheduling method based on dynamic adjustment in an embodiment of the present invention;

[0073] Figure 6is a flow chart of S15 in the task scheduling method based on dynamic adjustment in an embodiment of the present invention;

[0074] Figure 7 is a flow chart of S16 in the task scheduling method based on dynamic adjustment in an embodiment of the present invention;

[0075] Figure 8 is a schematic diagram of the structure of a task scheduling system based on dynamic adjustment in an embodiment of the present invention;

[0076] Fig. 9 The figure is a hardware diagram of an electronic device according to an exemplary embodiment. DETAILED DESCRIPTION

[0077] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0078] See also Figures 1 to 9 , a task scheduling method based on dynamic adjustment is applied to the task scheduling scenario of smart devices; the task scheduling method based on dynamic adjustment includes:

[0079] Step S11: defining multiple task information of the smart device in the current scene based on the scene in which the smart device is located and multiple task signals of the smart device;

[0080] Step S12: defining corresponding task actions and action positions based on multiple task information, constructing corresponding action combinations according to the task actions and action positions, and constructing a task list according to the multiple action combinations;

[0081] Step S13: defining first priority coefficients of multiple action combinations based on the task list, the action modules corresponding to the smart device, and the current location of the smart device;

[0082] Step S14: defining a second priority coefficient based on the task list, the urgency of the action assessed by the smart device, and the current time;

[0083] Step S15: defining priorities of multiple action combinations according to the second priority coefficient, the first priority coefficient and the task list, and triggering action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances and the working status of the smart device;

[0084] Step S16: When the smart device performs synchronous actions on at least two action combinations, the task list is dynamically adjusted according to the working trajectory of the corresponding working module and the working time corresponding to multiple working modules, and task scheduling is triggered based on the dynamically adjusted task list, smart device and current scene.

[0085] In an embodiment of the present invention, through the method in the embodiment of the present invention, multiple task information of the smart device in the current scene is defined based on the scene in which the smart device is located and multiple task signals of the smart device; corresponding task actions and action positions are defined based on the multiple task information, corresponding action combinations are constructed according to the task actions and action positions, and a task list is constructed according to the multiple action combinations, thereby realizing the construction of the task list and ensuring the rationality of the task list, and fully considering the task actions and action positions of the smart device.

[0086] Furthermore, a first priority coefficient of multiple action combinations is defined based on the task list, the action module corresponding to the smart device and the current position of the smart device; a second priority coefficient is defined based on the task list, the urgency of the action evaluated by the smart device and the current time; the priority of multiple action combinations is defined according to the second priority coefficient, the first priority coefficient and the task list, so as to perform multi-dimensional control based on the second priority coefficient, the first priority coefficient and the task list, and ensure the accuracy of the priority of multiple action combinations, and then trigger the action optimization of the smart device according to the priority of multiple action combinations, the corresponding action distance and the working status of the smart device, thereby ensuring the autonomous optimization of the action by the smart device, and at the same time, when the smart device performs synchronous actions on at least two action combinations, the dynamic adjustment of the task list is triggered according to the working trajectory of the corresponding working module and the working time corresponding to the multiple working modules, and the task scheduling is triggered based on the dynamically adjusted task list, the smart device and the current scene, which is compatible with the dynamically adjusted task list, the smart device and the current scene, and the task scheduling of the task list after dynamic adjustment is realized, which ensures the dynamic compatibility of task scheduling and realizes the adaptive regulation of smart devices in various scenes.

[0087] refer to Figure 2 In step S11, based on the scene in which the smart device is located and multiple task signals of the smart device, multiple task information of the smart device in the current scene is defined;

[0088] In the specific implementation process of the present invention, the specific steps may be:

[0089] S111: In the indoor space where the smart device is located, collect the location of the smart device;

[0090] S112: defining a plurality of surrounding environment features based on the surrounding environment detection of the location of the smart device;

[0091] S113: Associating the location of the smart device and multiple surrounding environment features, and triggering scene detection according to the location of the smart device and the multiple surrounding environment features;

[0092] S114: dynamically monitor the smart device and collect multiple task signals of the smart device in real time;

[0093] S115: defining multiple task information of the smart device in the current scene according to the scene in which the smart device is located and multiple task signals of the smart device.

[0094] In an embodiment of the present application, in an indoor space where a smart device is located, the location of the smart device is collected, the location of the smart device is introduced, and multiple surrounding environment features are defined based on the surrounding environment detection of the location of the smart device. At this time, multiple surrounding environment parameters of the location of the smart device are defined for the surrounding environment detection, so as to define corresponding surrounding environment features according to multiple surrounding environment parameters and corresponding directions, thereby clarifying multiple surrounding environment features. Optionally, the multiple surrounding environment features include work surface features, obstacle features, space features, etc.

[0095] Furthermore, the location of the smart device and multiple surrounding environment features are associated, and scene detection is triggered based on the location of the smart device and multiple surrounding environment features, so as to introduce multi-dimensional control of the location of the smart device and multiple surrounding environment features, thereby realizing scene detection.

[0096] At this time, the smart device is dynamically monitored, and multiple task signals of the smart device are collected in real time. The multiple task signals of the smart device are further controlled to facilitate the association of the scene in which the smart device is located and the multiple task signals of the smart device, thereby realizing multi-dimensional control of the scene in which the smart device is located and the multiple task signals of the smart device, thereby realizing the matching of the scene and the corresponding task signals, and then defining the multiple task information of the smart device in the current scene according to the scene in which the smart device is located and the multiple task signals of the smart device, thereby ensuring the accuracy of the multiple task information of the smart device in the current scene, and realizing the control of the multiple task information of the smart device in the current scene.

[0097] refer to Figure 3 In step S12, corresponding task actions and action positions are defined based on multiple task information, corresponding action combinations are constructed according to the task actions and action positions, and a task list is constructed according to the multiple action combinations;

[0098] In the specific implementation process of the present invention, the specific steps may be:

[0099] S121: freeze multiple task information;

[0100] S122: defining corresponding task actions and action positions based on the analysis of multiple task information;

[0101] S123: dynamically associate task actions and action positions, and define corresponding association coefficients;

[0102] S124: constructing a corresponding action combination based on multiple correlation coefficients, task actions, and action positions;

[0103] S125: collecting the previous action status of the smart device, and defining an action sorting method according to the previous action status of the smart device;

[0104] S126: Construct a task list according to the plurality of action combinations and the action ordering method.

[0105] In an embodiment of the present application, multiple task information of the smart device in the current scene is defined based on the scene in which the smart device is located and multiple task signals of the smart device; corresponding task actions and action positions are defined based on the multiple task information, corresponding action combinations are constructed according to the task actions and action positions, and a task list is constructed according to the multiple action combinations, thereby realizing the construction of the task list and ensuring the rationality of the task list, and fully considering the task actions and action positions of the smart device.

[0106] At this time, multiple task information are frozen and controlled. At this time, corresponding task actions and action positions are defined based on the analysis of multiple task information, and task actions and action positions are introduced to facilitate dynamic association of task actions and action positions, thereby achieving a high degree of control over task actions and action positions.

[0107] Furthermore, the task actions and action positions are dynamically associated, and the corresponding association coefficients are defined. The association coefficients are introduced to present the degree of association between the task actions and action positions, so as to construct corresponding action combinations based on multiple association coefficients, task actions and action positions.

[0108] Therefore, the previous action status of the smart device is collected, and the action sorting method is defined according to the previous action status of the smart device, so as to clarify the action sorting method, and further associate multiple action combinations and action sorting methods to facilitate constructing a task list based on multiple action combinations and action sorting methods, thereby completing the construction of the task list and further clarifying the task list to facilitate further processing of the task list.

[0109] refer to Figure 4, in step S13, defining first priority coefficients of multiple action combinations based on the task list, the action modules corresponding to the smart device, and the current location of the smart device;

[0110] In the specific implementation process of the present invention, the specific steps may be:

[0111] S131: freeze task list;

[0112] S132: Dividing into multiple action combinations based on the analysis of the task list;

[0113] S133: Matching the action module corresponding to the smart device and the current position of the smart device according to the multiple action combinations;

[0114] S134: defining a first matching coefficient based on each action combination and an action module corresponding to the smart device;

[0115] S135: defining a second matching coefficient based on each action combination and the current position of the smart device;

[0116] S136: Define first priority coefficients of multiple action combinations according to the first matching coefficient, the second matching coefficient, the model of the smart device, and the preliminary priority matching table.

[0117] In an embodiment of the present application, the task list is frozen, and further processed, thereby dividing multiple action combinations based on the analysis of the task list, so as to introduce multiple action combinations and realize subsequent processing of the multiple action combinations.

[0118] At this time, the action module corresponding to the smart device and the current position of the smart device are matched according to multiple action combinations, so as to introduce the action module corresponding to the smart device and the current position of the smart device, and further process the action module corresponding to the smart device and the current position of the smart device, so as to dynamically match the action module corresponding to the smart device and the current position of the smart device.

[0119] Furthermore, a first matching coefficient is defined based on each action combination and the action module corresponding to the smart device, and the action module corresponding to the smart device and the current position of the smart device are further controlled so as to introduce the first matching coefficient, thereby further controlling the first matching coefficient. At this time, the matching degree between each action combination and the action module corresponding to the smart device is presented through the first matching coefficient so as to ensure the matching between each action combination and the action module corresponding to the smart device.

[0120] At the same time, each action combination and the current position of the smart device are introduced to further control each action combination and the current position of the smart device, so as to define a second matching coefficient based on each action combination and the current position of the smart device, and then further control the second matching coefficient, and control the accuracy of the second matching coefficient in multiple dimensions.

[0121] Furthermore, the first matching coefficient and the second matching coefficient are associated to facilitate further processing of the first matching coefficient, the second matching coefficient, the model of the smart device, and the preliminary priority matching table, thereby defining the first priority coefficients of multiple action combinations according to the first matching coefficient, the second matching coefficient, the model of the smart device, and the preliminary priority matching table, and being compatible with the consideration of the first matching coefficient, the second matching coefficient, the model of the smart device, and the preliminary priority matching table, and ensuring the accuracy of the first priority coefficients of multiple action combinations, thereby controlling the first priority coefficients of multiple action combinations. Optionally, the first priority coefficient is used as a primary coefficient.

[0122] refer to Figure 5 , S14: defining a second priority coefficient based on the task list, the urgency of the action assessed by the smart device, and the current time;

[0123] In the specific implementation process of the present invention, the specific steps may be:

[0124] S141: freeze task list;

[0125] S142: Dividing into a plurality of action combinations based on the analysis of the task list;

[0126] S143: Matching the action urgency assessed by the smart device and the current time according to the multiple action combinations;

[0127] S144: defining importance levels of the plurality of action combinations according to the plurality of action combinations and the action urgency levels assessed by the smart device;

[0128] S145: collecting the current time, and defining a corresponding time level based on the current time and the previous work content of the smart device;

[0129] S146: Associating the time level, the importance level, and the multiple work combinations to define the second priority coefficients of the multiple action combinations.

[0130] In an embodiment of the present application, the task list is frozen, and the task list is further processed, so that multiple action combinations are divided based on the analysis of the task list, so as to introduce multiple action combinations and achieve further control of the multiple action combinations.

[0131] At this time, according to the matching of multiple action combinations, the action urgency assessed by the smart device and the current time, multiple action combinations, the action urgency assessed by the smart device and the current time are introduced, and dynamic matching is performed on the multiple action combinations, the action urgency assessed by the smart device and the current time, thereby achieving further control of multiple action combinations, the action urgency assessed by the smart device and the current time.

[0132] Therefore, the importance levels of multiple action combinations are defined according to the action urgency evaluated by the smart device, the importance levels of multiple action combinations are introduced, and the level division of multiple action combinations is realized to facilitate sorting of multiple action combinations.

[0133] Furthermore, the current time is collected, and the corresponding time level is defined based on the current time and the previous work content of the smart device. The current time and the previous work content of the smart device are introduced, and the current time and the previous work content of the smart device are controlled in multiple dimensions, thereby clarifying the time level and realizing the control of the time level. Further, the second priority coefficients of multiple action combinations are defined by associating the time level, the importance level and multiple work combinations, realizing the output of the second priority coefficients of multiple action combinations, and ensuring the accuracy of the second priority coefficients of multiple action combinations, thereby controlling the second priority coefficients of multiple action combinations. Optionally, the second priority coefficient is used as a high-level coefficient.

[0134] refer to Figure 6 , S15: defining priorities of multiple action combinations according to the second priority coefficient, the first priority coefficient and the task list, and triggering action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances and the working status of the smart device;

[0135] In the specific implementation process of the present invention, the specific steps may be:

[0136] S151: fix the second priority coefficient and the first priority coefficient;

[0137] S152: matching a corresponding priority logic according to the current scenario of the smart device, and controlling the second priority coefficient, the first priority coefficient, and the task list in the priority logic;

[0138] S153: defining priorities of a plurality of action combinations according to the second priority coefficient, the first priority coefficient, and the task list;

[0139] S154: collecting the continuous working time of the smart device, and defining the action attenuation coefficient of the smart device according to the continuous working time of the smart device and the corresponding action loss;

[0140] S155: Associating the priorities of the plurality of action combinations, the action attenuation coefficient of the smart device, and the corresponding action distance; defining the operation time of each action combination according to the priorities of the plurality of action combinations, the action attenuation coefficient of the smart device, and the corresponding action distance;

[0141] S156: triggering action optimization of the smart device based on the operation time of each action combination and the working status of the smart device.

[0142] In an embodiment of the present application, the second priority coefficient and the first priority coefficient are fixed, and the second priority coefficient and the first priority coefficient are further processed. At this time, the corresponding priority logic is matched according to the current scene of the smart device, and the second priority coefficient, the first priority coefficient and the task list are controlled in the priority logic, thereby realizing priority control of the second priority coefficient, the first priority coefficient and the task list.

[0143] Furthermore, the priorities of multiple action combinations are defined according to the second priority coefficient, the first priority coefficient and the task list, and multi-dimensional control is performed based on the second priority coefficient, the first priority coefficient and the task list to facilitate the accuracy of the priorities of multiple action combinations.

[0144] At the same time, the continuous working time of the smart devices is collected, and the motion attenuation coefficient of the smart devices is defined based on the continuous working time of the smart devices and the corresponding motion loss. The continuous working time of the smart devices and the corresponding motion loss are introduced, the motion attenuation coefficient of the smart devices is clarified, and the motion attenuation coefficient of the smart devices is fully considered.

[0145] Therefore, the priorities of multiple action combinations, the action attenuation coefficient of the smart device and the corresponding action distance are associated; the operation time of each action combination is defined according to the priorities of multiple action combinations, the action attenuation coefficient of the smart device and the corresponding action distance, so as to facilitate multi-dimensional control of the priorities of multiple action combinations, the action attenuation coefficient of the smart device and the corresponding action distance, thereby controlling the operation time of each action combination, so as to introduce the operation time of each action combination, and at the same time, trigger the action optimization of the smart device based on the operation time of each action combination and the working status of the smart device, so as to control the action of the smart device, so as to ensure the superiority of the action of the smart device, realize the action optimization of the smart device, and be compatible with the comprehensive consideration of the operation time of each action combination and the working status of the smart device.

[0146] refer to Figure 7, S16: When the smart device performs synchronous actions on at least two action combinations, triggering dynamic adjustment of the task list according to the working trajectory of the corresponding working module and the working time corresponding to the multiple working modules, triggering task scheduling based on the dynamically adjusted task list, the smart device and the current scene;

[0147] In the specific implementation process of the present invention, the specific steps may be:

[0148] S161: monitoring the task list of the smart device in real time, defining the synchronization state of the smart device according to the task list of the smart device and the response signals of the multiple action combinations, and triggering at least two action combinations to be performed simultaneously in the synchronization state of the smart device;

[0149] S162: When the smart device performs synchronous actions on at least two action combinations, collecting work trajectories of corresponding work modules;

[0150] S163: Associating the work tracks of the corresponding work modules and the work times corresponding to the multiple work modules;

[0151] S164: defining the work progress of the corresponding work combination according to the work track of the corresponding work module and the work time corresponding to the multiple work modules, and triggering the update of the work progress of the corresponding work combination;

[0152] S165: triggering dynamic adjustment of the task list based on the update of the work progress of the corresponding work combination; the multiple action combinations in the task list are dynamically adjusted according to the work progress of the smart device, and the work progress, priority and order of the multiple action combinations are regulated;

[0153] S166: Associating the dynamically adjusted task list, the smart device, and the current scene, and triggering task scheduling based on the dynamically adjusted task list, the smart device, and the current scene.

[0154] In the specific implementation process of the present invention, the first priority coefficient of multiple action combinations is defined based on the task list, the action module corresponding to the smart device and the current position of the smart device; the second priority coefficient is defined based on the task list, the urgency of the action evaluated by the smart device and the current time; the priorities of multiple action combinations are defined according to the second priority coefficient, the first priority coefficient and the task list, so as to perform multi-dimensional control based on the second priority coefficient, the first priority coefficient and the task list, and ensure the accuracy of the priorities of multiple action combinations, and then trigger the action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances and the working status of the smart device, thereby ensuring autonomous optimization of the actions by the smart device.

[0155] At the same time, when the smart device performs synchronous actions on at least two action combinations, the dynamic adjustment of the task list is triggered according to the working trajectory of the corresponding working module and the working time corresponding to multiple working modules. Task scheduling is triggered based on the dynamically adjusted task list, smart device and current scene. It is compatible with the dynamically adjusted task list, smart device and current scene, realizes task scheduling after the task list is dynamically adjusted, ensures the dynamic compatibility of task scheduling, and realizes adaptive control of smart devices in various scenarios.

[0156] Specifically, the task list of the smart device is monitored in real time, and the synchronization state of the smart device is defined according to the task list of the smart device and the response signals of multiple action combinations. At this time, at least two action combinations are triggered simultaneously in the synchronization state of the smart device, and the synchronous actions of the smart device are further controlled to achieve the synchronization of actions of multiple action combinations at the same time.

[0157] At this time, when the intelligent device performs synchronous actions on at least two action combinations, the working trajectory of the corresponding working module is collected, and the working trajectory of the working module is further analyzed so as to divide the corresponding working nodes based on the analysis of the working trajectory of the working module, thereby further controlling the working nodes.

[0158] Therefore, the working trajectory of the corresponding work module and the working time corresponding to the multiple work modules are associated, and the working trajectory of the work module and the working time corresponding to the multiple work modules are further processed, so as to define the work progress of the corresponding work combination according to the work trajectory of the corresponding work module and the working time corresponding to the multiple work modules, and trigger the update of the work progress of the corresponding work combination, thereby realizing the dynamic update of the work progress of the work combination and ensuring the controllability of the progress of multiple work combinations.

[0159] Furthermore, dynamic adjustment of the task list is triggered based on the update of the work progress of the corresponding work combination; multiple action combinations in the task list are dynamically adjusted with the work progress of the smart device, and the work progress, priority and sorting of the multiple action combinations are regulated; the dynamically adjusted task list, smart device and current scene are associated, and task scheduling is triggered based on the dynamically adjusted task list, smart device and current scene, which is compatible with the dynamically adjusted task list, smart device and current scene, and realizes task scheduling after the dynamic adjustment of the task list, ensures the dynamic compatibility of task scheduling, and realizes adaptive regulation of smart devices in various scenarios.

[0160] In an embodiment of the present invention, through the method in the embodiment of the present invention, multiple task information of the smart device in the current scene is defined based on the scene in which the smart device is located and multiple task signals of the smart device; corresponding task actions and action positions are defined based on the multiple task information, corresponding action combinations are constructed according to the task actions and action positions, and a task list is constructed according to the multiple action combinations, thereby realizing the construction of the task list and ensuring the rationality of the task list, and fully considering the task actions and action positions of the smart device.

[0161] Furthermore, a first priority coefficient of multiple action combinations is defined based on the task list, the action module corresponding to the smart device and the current position of the smart device; a second priority coefficient is defined based on the task list, the urgency of the action evaluated by the smart device and the current time; the priority of multiple action combinations is defined according to the second priority coefficient, the first priority coefficient and the task list, so as to perform multi-dimensional control based on the second priority coefficient, the first priority coefficient and the task list, and ensure the accuracy of the priority of multiple action combinations, and then trigger the action optimization of the smart device according to the priority of multiple action combinations, the corresponding action distance and the working status of the smart device, thereby ensuring the autonomous optimization of the action by the smart device, and at the same time, when the smart device performs synchronous actions on at least two action combinations, the dynamic adjustment of the task list is triggered according to the working trajectory of the corresponding working module and the working time corresponding to the multiple working modules, and the task scheduling is triggered based on the dynamically adjusted task list, the smart device and the current scene, which is compatible with the dynamically adjusted task list, the smart device and the current scene, and the task scheduling of the task list after dynamic adjustment is realized, which ensures the dynamic compatibility of task scheduling and realizes the adaptive regulation of smart devices in various scenes.

[0162] See also Figure 8 , Figure 8 It is a schematic diagram of the structural composition of a task scheduling system based on dynamic adjustment in an embodiment of the present invention.

[0163] like Figure 8 As shown, a task scheduling system based on dynamic adjustment, the task scheduling system based on dynamic adjustment includes:

[0164] A task information module 21, used to define multiple task information of the smart device in the current scene based on the scene in which the smart device is located and multiple task signals of the smart device;

[0165] A task list module 22, used to define corresponding task actions and action positions based on multiple task information, construct corresponding action combinations according to the task actions and action positions, and construct a task list according to multiple action combinations;

[0166] A first priority coefficient module 23, used to define first priority coefficients of multiple action combinations based on the task list, the action module corresponding to the smart device and the current position of the smart device;

[0167] A second priority coefficient module 24, for defining a second priority coefficient based on the task list, the urgency of the action assessed by the smart device, and the current time;

[0168] an action optimization module 25, for defining priorities of a plurality of action combinations according to the second priority coefficient, the first priority coefficient and the task list, and triggering action optimization of the smart device according to the priorities of the plurality of action combinations, the corresponding action distances and the working status of the smart device;

[0169] The task scheduling module 26 is used to trigger the dynamic adjustment of the task list according to the working trajectory of the corresponding working module and the working time corresponding to multiple working modules when the smart device performs synchronous actions on at least two action combinations, and trigger task scheduling based on the dynamically adjusted task list, smart device and current scene.

[0170] See also Fig. 9 , refer to the following Fig. 9 The electronic intelligent device 40 according to this embodiment of the present invention is described. Fig. 9 The electronic intelligent device 40 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0171] like Fig. 9 As shown, the electronic intelligent device 40 is in the form of a general computing intelligent device. The components of the electronic intelligent device 40 may include but are not limited to: at least one processing unit 41, at least one storage unit 42, and a bus 43 connecting different system components (including the storage unit 42 and the processing unit 41).

[0172] The storage unit stores program codes, which can be executed by the processing unit 41, so that the processing unit 41 executes the steps according to various exemplary embodiments of the present invention described in the above “Embodiment Method” section of this specification.

[0173] The storage unit 42 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 421 and / or a cache unit 422 , and may further include a read-only memory unit (ROM) 423 .

[0174] The storage unit 42 may also include a program / utility 424 having a set (at least one) of program modules 425, such program modules 425 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0175] Bus 43 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0176] The electronic smart device 40 may also communicate with one or more external smart devices (e.g., keyboards, pointing smart devices, Bluetooth smart devices, etc.), one or more smart devices that enable a user to interact with the electronic smart device 40, and / or any smart device that enables the electronic smart device 40 to communicate with one or more other computing smart devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 44. Furthermore, the electronic smart device 40 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 45. Fig. 9 As shown, the network adapter 45 communicates with other modules of the electronic intelligent device 40 via the bus 43. It should be understood that although Fig. 9 Not shown, other hardware and / or software modules may be used in conjunction with the electronic intelligent device 40, including but not limited to: microcode, intelligent device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup planning systems.

[0177] Through the description of the above implementation, it is easy for those skilled in the art to understand that the example implementation described here can be implemented by software, or by software combined with necessary hardware. Therefore, the technical solution according to the implementation of the present disclosure can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes several instructions to enable a computing intelligent device (which can be a personal computer, a server, a terminal device, or a network intelligent device, etc.) to execute the method according to the implementation of the present disclosure.

[0178] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium, and the storage medium can include: a read-only memory (ROM), a random access memory (RAM), a disk or an optical disk, etc. In addition, it stores computer program instructions, and when the computer program instructions are executed by a computer, the computer executes the above method.

[0179] In addition, the above describes in detail the task scheduling method and system based on dynamic adjustment provided by the embodiments of the present invention. Specific examples are used herein to illustrate the principles and implementation methods of the present invention. The description of the above embodiments is only used to help understand the method of the present invention and its core idea. At the same time, for those skilled in the art, according to the ideas of the present invention, there will be changes in the specific implementation methods and application scopes. In summary, the content of this specification should not be understood as a limitation on the present invention.

Claims

1. A task scheduling method based on dynamic adjustment, characterized in that: Applied to task scheduling scenarios of smart devices; The task scheduling method based on dynamic adjustment includes: Defining multiple task information of the smart device in the current scene based on the scene in which the smart device is located and multiple task signals of the smart device; Define corresponding task actions and action positions based on multiple task information, construct corresponding action combinations according to the task actions and action positions, and construct a task list according to the multiple action combinations; Defining first priority coefficients of multiple action combinations based on the task list, the action modules corresponding to the smart device, and the current location of the smart device; defining a second priority coefficient based on the task list, the urgency of the action assessed by the smart device, and the current time; Defining priorities of multiple action combinations according to the second priority coefficient, the first priority coefficient, and the task list, and triggering action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances, and the working status of the smart device; When the smart device performs synchronous actions on at least two action combinations, the task list is dynamically adjusted according to the working tracks of the corresponding working modules and the working times corresponding to the multiple working modules, and the task scheduling is triggered based on the dynamically adjusted task list, the smart device and the current scene; The method comprises: defining corresponding task actions and action positions based on multiple task information, constructing corresponding action combinations according to the task actions and action positions, and constructing a task list according to multiple action combinations, including: freezing multiple task information; defining corresponding task actions and action positions based on the analysis of multiple task information; dynamically associating task actions and action positions, and defining corresponding association coefficients; constructing corresponding action combinations based on multiple association coefficients, task actions, and action positions; collecting previous action states of smart devices, and defining action sorting methods according to the previous action states of smart devices; and constructing a task list according to multiple action combinations and action sorting methods. The method of defining the first priority coefficients of multiple action combinations based on the task list, the action modules corresponding to the smart device and the current position of the smart device includes: freezing the task list; dividing the multiple action combinations based on the analysis of the task list; matching the action modules corresponding to the smart device and the current position of the smart device according to the multiple action combinations; defining a first matching coefficient based on each action combination and the action module corresponding to the smart device; defining a second matching coefficient based on each action combination and the current position of the smart device; and defining the first priority coefficients of multiple action combinations according to the first matching coefficient, the second matching coefficient, the model of the smart device and the preliminary priority matching table.

2. The task scheduling method based on dynamic adjustment according to claim 1, characterized in that: The method of defining multiple task information of the smart device in the current scene based on the scene in which the smart device is located and multiple task signals of the smart device includes: In the indoor space where the smart device is located, collect the location of the smart device; Defining multiple surrounding environment features based on the surrounding environment detection of the location of the smart device; Associating the location of the smart device and multiple surrounding environment features, triggering scene detection according to the location of the smart device and multiple surrounding environment features; Dynamically monitor smart devices and collect multiple task signals of smart devices in real time; Multiple task information of the smart device in the current scene is defined according to the scene in which the smart device is located and multiple task signals of the smart device.

3. The task scheduling method based on dynamic adjustment according to claim 1, characterized in that: The second priority coefficient is defined based on the task list, the urgency of the action assessed by the smart device, and the current time, including: Freeze task list; Divide into multiple action combinations based on the analysis of the task list; Matching the action urgency assessed by the smart device and the current time according to the combination of multiple actions; Defining importance levels of multiple action combinations according to the multiple action combinations and the action urgency assessed by the smart device; Collect the current time and define the corresponding time level based on the current time and the previous work content of the smart device; The time level, the importance level, and the plurality of work combinations are associated to define second priority coefficients of the plurality of action combinations.

4. The task scheduling method based on dynamic adjustment according to claim 3 is characterized in that: Defining priorities of multiple action combinations according to the second priority coefficient, the first priority coefficient, and the task list, and triggering action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances, and the working status of the smart device, includes: Set the second priority coefficient and the first priority coefficient; Match the corresponding priority logic according to the current scene of the smart device, and control the second priority coefficient, the first priority coefficient and the task list in the priority logic; The priorities of the plurality of action combinations are defined according to the second priority coefficient, the first priority coefficient and the task list.

5. The task scheduling method based on dynamic adjustment according to claim 4 is characterized in that: The method further includes defining priorities of multiple action combinations according to the second priority coefficient, the first priority coefficient, and the task list, and triggering action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances, and the working status of the smart device. Collect the continuous working time of the smart device, and define the action attenuation coefficient of the smart device according to the continuous working time of the smart device and the corresponding action loss; Associating priorities of multiple action combinations, action attenuation coefficients of smart devices, and corresponding action distances; defining operation time of each action combination according to the priorities of multiple action combinations, action attenuation coefficients of smart devices, and corresponding action distances; Trigger the action optimization of the smart device based on the operation time of each action combination and the working status of the smart device.

6. The task scheduling method based on dynamic adjustment according to claim 5, characterized in that: When the smart device performs synchronous actions on at least two action combinations, the task list is dynamically adjusted according to the work tracks of the corresponding working modules and the working times corresponding to the multiple working modules, and the task scheduling is triggered based on the dynamically adjusted task list, the smart device and the current scene, including: Monitor the task list of the smart device in real time, define the synchronization state of the smart device according to the task list of the smart device and the response signal of the multiple action combinations, and at this time, trigger at least two action combinations in the synchronization state of the smart device to be performed simultaneously; When the intelligent device performs synchronous actions on at least two action combinations, the working trajectories of the corresponding working modules are collected.

7. The task scheduling method based on dynamic adjustment according to claim 6, characterized in that: When the smart device performs synchronous actions on at least two action combinations, the task list is dynamically adjusted according to the working tracks of the corresponding working modules and the working times corresponding to the multiple working modules, and the task scheduling is triggered based on the dynamically adjusted task list, the smart device and the current scene, further comprising: Associate the work tracks of the corresponding work modules and the work times corresponding to the multiple work modules; Define the work progress of the corresponding work combination according to the work track of the corresponding work module and the work time corresponding to the multiple work modules, and trigger the update of the work progress of the corresponding work combination; The task list is dynamically adjusted based on the update of the work progress of the corresponding work combination; multiple action combinations in the task list are dynamically adjusted according to the work progress of the smart device, and the work progress, priority and sorting of multiple action combinations are regulated; The dynamically adjusted task list, smart device and current scene are associated, and task scheduling is triggered based on the dynamically adjusted task list, smart device and current scene.

8. A task scheduling system based on dynamic adjustment, characterized in that: The task scheduling system based on dynamic adjustment is applied to the task scheduling method based on dynamic adjustment as claimed in any one of claims 1 to 7, and the task scheduling system based on dynamic adjustment includes: A task information module, used to define multiple task information of the smart device in the current scene based on the scene in which the smart device is located and multiple task signals of the smart device; A task list module is used to define corresponding task actions and action positions based on multiple task information, construct corresponding action combinations according to the task actions and action positions, and construct a task list according to multiple action combinations; A first priority coefficient module, used to define first priority coefficients of multiple action combinations based on the task list, the action module corresponding to the smart device, and the current position of the smart device; A second priority coefficient module, used to define a second priority coefficient based on the task list, the urgency of the action assessed by the smart device, and the current time; an action optimization module, used to define the priorities of multiple action combinations according to the second priority coefficient, the first priority coefficient and the task list, and trigger the action optimization of the smart device according to the priorities of the multiple action combinations, the corresponding action distances and the working status of the smart device; The task scheduling module is used to trigger the dynamic adjustment of the task list according to the working trajectory of the corresponding working module and the working time corresponding to multiple working modules when the smart device performs synchronous actions on at least two action combinations, and trigger task scheduling based on the dynamically adjusted task list, smart device and current scene.

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