CN115456373A - Task monitoring method and device, electronic equipment and storage medium - Google Patents
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Abstract
The invention provides a task monitoring method and a device, belonging to the technical field of task management, wherein the method comprises the following steps: acquiring task information of a task to be monitored; inputting the task information into a task analysis model to obtain a task analysis result output by the task analysis model; according to the task analysis result, estimating the predicted completion condition of the task to be monitored; the task analysis result comprises a first probability and a second probability; the first probability is a probability value that the task to be monitored is completed within preset completion time, and the second probability is a probability value that the task to be monitored meets preset completion quality. According to the invention, the task information of the task to be monitored is input into the business analysis model which is trained and completed in advance, so that the completion condition of the task to be monitored is predicted and evaluated from two aspects of completion time and completion quality, and the problem that the task progress risk is difficult to grasp effectively can be solved.
Description
Technical Field
The present invention relates to the field of task management technologies, and in particular, to a task monitoring method and apparatus, an electronic device, and a storage medium.
Background
With increasingly refined socialization and division of labor, task management is gradually replaced by a multi-organization and multi-department collaborative task management mode from a single self-organization team.
At present, task management mostly adopts a mode of detailed decomposition, and a task is divided into subtasks with small granularity so as to evaluate time and reduce risks, however, the subtasks have relevance and can generate new unpredictable problems and new subtasks in the execution process, so that the plan cannot catch up with changes, and further the overall progress is out of control.
Therefore, how to comprehensively evaluate the progress risk of the task becomes an urgent problem to be solved for the formulated task.
Disclosure of Invention
The invention provides a task monitoring method and device, electronic equipment and a storage medium, which are used for solving the defect that the progress risk of a task is difficult to evaluate comprehensively in the prior art.
In a first aspect, the present invention provides a task monitoring method, including: acquiring task information of a task to be monitored; inputting the task information into a task analysis model to obtain a task analysis result output by the task analysis model; estimating the predicted completion condition of the task to be monitored according to the task analysis result; the task analysis model is obtained by training based on sample task information and sample task analysis results corresponding to the sample task information; the task analysis result comprises a first probability and a second probability; the first probability is a probability value that the task to be monitored is completed within preset completion time, and the second probability is a probability value that the task to be monitored meets preset completion quality.
According to the task monitoring method provided by the invention, the estimating of the predicted completion condition of the task to be monitored according to the task analysis result comprises the following steps: determining that the task to be monitored can be completed within the preset completion time under the condition that the first probability is greater than or equal to a first threshold; determining that the task to be monitored cannot be completed within the preset completion time if the first probability is less than a first threshold; determining that the task to be monitored can be completed according to the preset completion quality under the condition that the second probability is greater than or equal to a second threshold; and determining that the task to be monitored cannot be completed according to the preset completion quality under the condition that the second probability is smaller than a second threshold.
According to the task monitoring method provided by the invention, the estimation of the predicted completion condition of the task to be monitored according to the task analysis result further comprises the following steps: acquiring the occurrence frequency of the key point names in the task information under the condition that the second probability is greater than a third threshold and smaller than the second threshold; estimating the predicted completion condition of the task to be monitored according to the occurrence frequency and the preset frequency; the preset frequency is determined based on sample task information of a sample task with the same type as the task to be monitored.
According to the task monitoring method provided by the invention, the estimating of the predicted completion condition of the task to be monitored according to the occurrence frequency and the preset frequency comprises the following steps: calculating the difference value between the occurrence frequency and a preset frequency; calculating the ratio of the difference value to the preset frequency; and determining that the task to be monitored can be completed according to the preset completion quality under the condition that the ratio is greater than or equal to a fourth threshold value.
According to the task monitoring method provided by the invention, under the condition that the task to be monitored can be completed within the preset completion time, the preset completion time is taken as the predicted completion time of the task to be monitored; and under the condition that the task to be monitored cannot be completed within the preset completion time, determining the predicted completion time of the task to be monitored according to the preset completion time, the task starting time and the first probability of the task to be monitored.
According to the task monitoring method provided by the invention, the predicted completion time of the task to be monitored is determined according to the preset completion time, the task start time and the first probability of the task to be monitored, and the specific formula is as follows:
b＝(c-d)×(1-K1)+c
wherein b is the predicted completion time, c is the preset completion time, d is the task start time, and K1 is the first probability.
According to a task monitoring method provided by the invention, the task information comprises: task basic information, task process records, task key points and task completion timeliness; and the task completion time comprises the preset completion time and the preset completion quality of the task to be monitored.
In a second aspect, the present invention further provides a task monitoring apparatus, including:
the first processing module is used for acquiring task information of a task to be monitored;
the second processing module is used for inputting the task information into the task analysis model to obtain a task analysis result output by the task analysis model;
the third processing module is used for evaluating the predicted completion condition of the task to be monitored according to the task analysis result;
the task analysis model is obtained by training based on sample task information and sample task analysis results corresponding to the sample task information; the task analysis result comprises a first probability and a second probability; the first probability is a probability value that the task to be monitored is completed within preset completion time, and the second probability is a probability value that the task to be monitored meets preset completion quality.
In a third aspect, the present invention provides an electronic device, comprising a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the task monitoring method according to any one of the above-mentioned embodiments.
In a fourth aspect, the present invention also provides a non-transitory computer-readable storage medium having stored thereon a computer program which, when executed by a processor, performs the steps of the task monitoring method as described in any one of the above.
According to the task monitoring method and device provided by the invention, the task information of the task to be monitored is input into the business analysis model trained and completed in advance, so that the completion condition of the task to be monitored is predicted and evaluated from two aspects of completion time and completion quality, and the problem that the task progress risk is difficult to grasp effectively can be solved.
Drawings
In order to more clearly illustrate the present invention or the technical solutions in the prior art, the drawings used in the embodiments or the description of the prior art will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without creative efforts.
FIG. 1 is a schematic flow chart diagram of a task monitoring method provided by the present invention;
FIG. 2 is a schematic diagram of a task monitor provided in the present invention;
fig. 3 is a schematic structural diagram of an electronic device provided in the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings, and it is obvious that the described embodiments are some, but not all embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
It should be noted that in the description of the embodiments of the present invention, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrases "comprising one of 8230; \8230;" 8230; "does not exclude the presence of additional like elements in a process, method, article, or apparatus that comprises the element. The specific meanings of the above terms in the present invention can be understood according to specific situations by those of ordinary skill in the art.
The terms "first," "second," and the like in this application are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It will be appreciated that the data so used may be interchanged under appropriate circumstances such that embodiments of the application may be practiced in sequences other than those illustrated or described herein, and that the terms "first," "second," and the like are generally used herein in a generic sense and do not limit the number of terms, e.g., the first term can be one or more than one.
The following describes a task monitoring method and apparatus provided by an embodiment of the present invention with reference to fig. 1 to fig. 3.
Fig. 1 is a schematic flowchart of a task monitoring method provided by the present invention, as shown in fig. 1, including but not limited to the following steps:
step 101: and acquiring task information of the task to be monitored.
The task information comprises but is not limited to the task type, the basic information of the task, the task process record, the key points of the task and the task completion time limit which are related to each other; the task completion timeliness comprises preset completion time and preset completion quality of the task to be monitored.
The task type can be described in detail with the following information: task number, task type, task link, task docking department and the like.
The task basic information can be described in detail by using the following information: task number, task type, task link, task content description and the like.
The task process record can be described in detail with the following information: task number, record number, task link and record content. The recording content can record the information of the mission key points, such as the name and the grade of the key points.
The mission critical points may be described in detail with the following information: task number, key point name, and level. Wherein, the grade can be understood as the criticality of the mission key point or the difficulty level. A task key point may be understood as a key node or step that is of importance for completing a task to be monitored.
The task completion aging can be described in detail using the following information: task number, preset completion time and preset completion quality.
The preset completion time is the required time for completing the task to be monitored; the preset completion quality is the required quality for completing the task to be monitored.
It can be understood that the task type, the task basic information, the task process record, the task key points and the task completion timeliness are associated by taking the task number as the associated information, so that the overall description of the task to be monitored is realized.
Step 102: and inputting the task information into a task analysis model to obtain a task analysis result output by the task analysis model.
The task analysis result comprises a first probability and a second probability; the first probability is a probability value that the task to be monitored is completed within preset completion time, and the second probability is a probability value that the task to be monitored meets preset completion quality.
The task analysis model is obtained by training based on sample task information and sample task analysis results corresponding to the sample task information. The task analysis model can be a support vector machine, an artificial neural network and the like.
The sample task information may be obtained based on a sample task of the same type as the task to be monitored. Sample task information includes, but is not limited to: the method comprises the steps of sample task type, sample task basic information, sample task process records, sample task key points and sample task completion timeliness.
For the sample task analysis result, the historical completion time, the historical completion quality, the preset completion time and the preset completion quality of the sample task can be determined.
Specifically, a first probability of the sample task is determined according to a ratio of historical completion time of the sample task to preset completion time; and determining the second probability of the sample task according to the historical completion quality and the preset completion quality of the sample task.
Step 103: and evaluating the predicted completion condition of the task to be monitored according to the task analysis result.
It is to be appreciated that the first probability can predict a time-of-progress of evaluating the task to be monitored and the second probability can predict a completion quality of evaluating the task to be monitored. Through the task analysis result, the task to be monitored can be subjected to prediction evaluation on time and quality to determine the predicted completion condition of the task.
According to the task monitoring method provided by the invention, the task information of the task to be monitored is input into the business analysis model trained and completed in advance, so that the completion condition of the task to be monitored is predicted and evaluated from two aspects of completion time and completion quality, and the problem that the task progress risk is difficult to effectively grasp can be solved.
Based on the content in the foregoing embodiment, as an optional embodiment, the present invention provides a task monitoring method, where the evaluating, according to the task analysis result, the predicted completion condition of the task to be monitored includes: determining that the task to be monitored can be completed within the preset completion time under the condition that the first probability is greater than or equal to a first threshold; determining that the task to be monitored cannot be completed within the preset completion time if the first probability is smaller than a first threshold; determining that the task to be monitored can be completed according to the preset completion quality under the condition that the second probability is greater than or equal to a second threshold; and determining that the task to be monitored cannot be completed according to preset completion quality under the condition that the second probability is smaller than a second threshold value.
Optionally, in a case that it is determined that the task to be monitored can be completed within the preset completion time, taking the preset completion time as a predicted completion time of the task to be monitored; and under the condition that the task to be monitored cannot be completed within the preset completion time, determining the predicted completion time of the task to be monitored according to the preset completion time, the task starting time and the first probability of the task to be monitored.
For example, in one embodiment, the present invention sets the first threshold value to 0.8 and the second threshold value to 0.8. For the task A to be monitored, the first probability is 0.83 and the second probability is 0.84 through the solution of the task analysis model.
It can be seen that the first probability 0.83 is greater than the first threshold 0.8 and the second probability 0.84 is greater than the second threshold 0.8. Based on this, it can be determined that the task a to be monitored can be completed within the preset completion time and can be completed according to the preset completion quality.
Further, the present invention may consider the predicted completion time of task a to be monitored as the preset completion time.
In another embodiment, the present invention sets the first threshold value to 0.75 and the second threshold value to 0.8. And for the task B to be monitored, the first probability is 0.7 and the second probability is 0.75 through the solution of the task analysis model.
It can be seen that the first probability 0.7 is less than the first threshold 0.75 and the second probability 0.75 is less than the second threshold 0.8. Based on this, it can be determined that the task B to be monitored cannot be completed within the preset completion time and cannot be completed according to the preset completion quality.
Further, for the task B to be monitored, the method can determine the predicted completion time of the task to be monitored according to the preset completion time, the task start time and the first probability.
The concrete formula is as follows:
b＝(c-d)×(1-K1)+c
wherein b is the predicted completion time, c is the preset completion time, d is the task start time, and K1 is the first probability.
Based on the content in the foregoing embodiment, as an optional embodiment, the present invention provides a task monitoring method, where the estimating a predicted completion condition of the task to be monitored according to the task analysis result further includes: optionally, under the condition that the second probability is greater than a third threshold and smaller than the second threshold, obtaining the occurrence frequency of the key point names in the task information; estimating the predicted completion condition of the task to be monitored according to the occurrence frequency and the preset frequency; the preset frequency is determined based on sample task information of a sample task with the same type as the task to be monitored.
Optionally, the occurrence frequency is the number of times that the key point name in the task key point information of the task to be monitored appears in the task recording process; and presetting the times of the occurrence of the sample key names in the sample task key point information of the sample tasks with the same type in the sample task recording process.
Based on the content of the foregoing embodiment, as an optional embodiment, the evaluating the predicted completion condition of the task to be monitored according to the occurrence frequency and the preset frequency includes: calculating the difference value between the occurrence frequency and a preset frequency; calculating the ratio of the difference value to the preset frequency; and determining that the task to be monitored can be completed according to the preset completion quality under the condition that the ratio is greater than or equal to a fourth threshold value.
Specifically, the second threshold value is set to 0.8, the third threshold value is set to 0.7, and the fourth threshold value is set to 0.8. Taking the key point names W1 in the key point information of the sample tasks of the same type as a set, and calculating the times N1 of the key point names appearing in the sample task process under the condition of the same time delay; similarly, calculating the occurrence frequency N2 of the key point name W1 in the task process record of the task to be monitored; when the second probability is less than the second threshold 0.8 and greater than the third threshold 0.7 and (N2-N1)/N1 is greater than the fourth threshold 0.8, it is determined that quality completion can be guaranteed.
According to the task monitoring method provided by the invention, the task completion time and the completion quality are comprehensively analyzed by recording the information such as the task type, the task basic information, the task process record, the task key point and the task completion timeliness, a task analysis model is formed by using big data analysis and training, and the task analysis model is applied to other companies or departments, so that the task completion timeliness is intelligently analyzed, the task completion time is predicted, the task work development is effectively monitored and guided, the task execution risk is timely discovered, and the enterprise operation efficiency is promoted to be improved.
The invention provides a scientific and effective new thought and means for enterprise task monitoring management, can effectively discover task execution risks and improve operation efficiency; focusing on the analysis of task completion progress and quality in the enterprise operation process, the progress and quality of various tasks of an enterprise are intelligently analyzed by means of cloud computing and big data technology, completion time is predicted, and the problems that task risks are difficult to control effectively and risk prediction is difficult are solved.
It should be noted that the task analysis model in the present invention is preferably built by a Support Vector Machine (SVM). For example, for the sample task D1, a task analysis model based on an SVM algorithm is established for its sample task information and sample task analysis results. In consideration of the accuracy and robustness of the established task analysis model, the number of the sample tasks D1 can be set according to requirements.
Then, for the task D2 to be monitored of the same type as the sample task D1, the predicted completion condition can be evaluated directly by using the pre-established task analysis model.
Optionally, in order to improve the prediction accuracy of the task analysis model, the model may be further corrected according to the subsequent actual completion of the task to be monitored.
For how to specifically utilize the task analysis result output by the task analysis model provided by the present invention to evaluate the predicted completion condition of the task to be monitored, reference may be made to the contents of the foregoing embodiments, and details are not described here.
The invention adopts measures to establish an experience base aiming at the similar tasks, outputs the task analysis result aiming at the tasks to be monitored with consistent characteristics through task information, and helps task responsible persons to adjust the task planning so as to improve the task completion efficiency.
Fig. 2 is a schematic structural diagram of a task monitoring device provided by the present invention, and as shown in fig. 2, the task monitoring device includes: a first processing module 201, a second processing module 202 and a third processing module 203.
The first processing module 201 is configured to obtain task information of a task to be monitored;
the second processing module 202 is configured to input the task information to a task analysis model to obtain a task analysis result output by the task analysis model;
the third processing module 203 is configured to evaluate a predicted completion condition of the task to be monitored according to the task analysis result;
the task analysis model is obtained by training based on sample task information and sample task analysis results corresponding to the sample task information; the task analysis result comprises a first probability and a second probability; the first probability is a probability value that the task to be monitored is completed within preset completion time, and the second probability is a probability value that the task to be monitored meets preset completion quality.
According to the task monitoring device provided by the invention, the task information of the task to be monitored is input into the business analysis model which is trained and completed in advance, so that the completion condition of the task to be monitored is predicted and evaluated from two aspects of completion time and completion quality, and the problem that the task progress risk is difficult to grasp effectively can be solved.
It should be noted that, when the task monitoring device provided in the embodiment of the present invention is in specific operation, the task monitoring method described in any of the above embodiments may be executed, and details of this embodiment are not described herein.
Fig. 3 is a schematic structural diagram of an electronic device provided in the present invention, and as shown in fig. 3, the electronic device may include: a processor (processor) 310, a communication Interface (Communications Interface) 320, a memory (memory) 330 and a communication bus 340, wherein the processor 310, the communication Interface 320 and the memory 330 communicate with each other via the communication bus 340. The processor 310 may call logic instructions in the memory 330 to perform a task monitoring method comprising: acquiring task information of a task to be monitored; inputting the task information into a task analysis model to obtain a task analysis result output by the task analysis model; according to the task analysis result, estimating the predicted completion condition of the task to be monitored; the task analysis model is obtained by training based on sample task information and sample task analysis results corresponding to the sample task information; the task analysis result comprises a first probability and a second probability; the first probability is a probability value of the task to be monitored completing within preset completing time, and the second probability is a probability value of the task to be monitored meeting preset completing quality.
In addition, the logic instructions in the memory 330 may be implemented in the form of software functional units and stored in a computer readable storage medium when the software functional units are sold or used as independent products. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
In another aspect, the present invention also provides a computer program product, which includes a computer program stored on a non-transitory computer-readable storage medium, the computer program including program instructions, when the program instructions are executed by a computer, the computer being capable of executing the task monitoring method provided by the above embodiments, the method including: acquiring task information of a task to be monitored; inputting the task information into a task analysis model to obtain a task analysis result output by the task analysis model; estimating the predicted completion condition of the task to be monitored according to the task analysis result; the task analysis model is obtained by training based on sample task information and sample task analysis results corresponding to the sample task information; the task analysis result comprises a first probability and a second probability; the first probability is a probability value that the task to be monitored is completed within preset completion time, and the second probability is a probability value that the task to be monitored meets preset completion quality.
In yet another aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored, the computer program being implemented by a processor to perform the task monitoring method provided in the above embodiments, the method including: acquiring task information of a task to be monitored; inputting the task information into a task analysis model to obtain a task analysis result output by the task analysis model; according to the task analysis result, estimating the predicted completion condition of the task to be monitored; the task analysis model is obtained by training based on sample task information and sample task analysis results corresponding to the sample task information; the task analysis result comprises a first probability and a second probability; the first probability is a probability value that the task to be monitored is completed within preset completion time, and the second probability is a probability value that the task to be monitored meets preset completion quality.
The above-described embodiments of the apparatus are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. One of ordinary skill in the art can understand and implement it without inventive effort.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. Based on the understanding, the above technical solutions substantially or otherwise contributing to the prior art may be embodied in the form of a software product, which may be stored in a computer-readable storage medium, such as ROM/RAM, magnetic disk, optical disk, etc., and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method according to the various embodiments or some parts of the embodiments.
Finally, it should be noted that: the above examples are only intended to illustrate the technical solution of the present invention, and not to limit it; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.
Claims (10)
1. A task monitoring method, comprising:
acquiring task information of a task to be monitored;
inputting the task information into a task analysis model to obtain a task analysis result output by the task analysis model;
according to the task analysis result, estimating the predicted completion condition of the task to be monitored;
the task analysis model is obtained by training based on sample task information and sample task analysis results corresponding to the sample task information; the task analysis result comprises a first probability and a second probability; the first probability is a probability value of the task to be monitored completing within preset completing time, and the second probability is a probability value of the task to be monitored meeting preset completing quality.
2. The task monitoring method according to claim 1, wherein the evaluating the predicted completion of the task to be monitored according to the task analysis result comprises:
determining that the task to be monitored can be completed within the preset completion time under the condition that the first probability is greater than or equal to a first threshold; determining that the task to be monitored cannot be completed within the preset completion time if the first probability is smaller than a first threshold;
determining that the task to be monitored can be completed according to the preset completion quality under the condition that the second probability is greater than or equal to a second threshold; and determining that the task to be monitored cannot be completed according to preset completion quality under the condition that the second probability is smaller than a second threshold value.
3. The task monitoring method according to claim 2, wherein the evaluating the predicted completion of the task to be monitored according to the task analysis result further comprises:
acquiring the occurrence frequency of the key point names in the task information under the condition that the second probability is greater than a third threshold and smaller than the second threshold;
estimating the predicted completion condition of the task to be monitored according to the occurrence frequency and the preset frequency;
the preset frequency is determined based on sample task information of a sample task with the same type as the task to be monitored.
4. The task monitoring method according to claim 3, wherein the evaluating the predicted completion of the task to be monitored according to the occurrence frequency and the preset frequency comprises:
calculating the difference value between the occurrence frequency and a preset frequency;
calculating the ratio of the difference value to the preset frequency;
and determining that the task to be monitored can be completed according to the preset completion quality under the condition that the ratio is greater than or equal to a fourth threshold value.
5. The task monitoring method according to claim 2, wherein in a case where it is determined that the task to be monitored can be completed within the preset completion time, the preset completion time is taken as an expected completion time of the task to be monitored;
and under the condition that the task to be monitored cannot be completed within the preset completion time, determining the predicted completion time of the task to be monitored according to the preset completion time, the task starting time and the first probability of the task to be monitored.
6. The task monitoring method according to claim 5, wherein the predicted completion time of the task to be monitored is determined according to the preset completion time, the task start time and the first probability of the task to be monitored, and the specific formula is as follows:
b＝(c-d)×(1-K1)+c
wherein b is the predicted completion time, c is the preset completion time, d is the task start time, and K1 is the first probability.
7. The task monitoring method according to claim 1, wherein the task information comprises: task basic information, task process records, task key points and task completion timeliness;
and the task completion time comprises the preset completion time and the preset completion quality of the task to be monitored.
8. A task monitoring device, comprising:
the first processing module is used for acquiring task information of a task to be monitored;
the second processing module is used for inputting the task information into a task analysis model to obtain a task analysis result output by the task analysis model;
the third processing module is used for evaluating the predicted completion condition of the task to be monitored according to the task analysis result;
the task analysis model is obtained by training based on sample task information and sample task analysis results corresponding to the sample task information; the task analysis result comprises a first probability and a second probability; the first probability is a probability value that the task to be monitored is completed within preset completion time, and the second probability is a probability value that the task to be monitored meets preset completion quality.
9. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the task monitoring method according to any of claims 1 to 7 when executing the computer program.
10. A non-transitory computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the steps of the task monitoring method according to any one of claims 1 to 7.
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