A task distribution method, system and terminal based on gig market

Abstract

The present invention relates to a task distribution method, system, and terminal based on a gig market, and relates to the technical field of the gig market, which includes: obtaining a preset trigger signal of a mobile terminal; based on the consistency of the trigger signal with a preset search signal, controlling the mobile terminal to perform an object shooting prompt to obtain object image information; determining the characteristics of the object in the image based on the object image information; determining whether a preset domain database contains an object corresponding to the object characteristics in the image; if the domain database contains an object corresponding to the object characteristics in the image, determining the specific object to be photographed based on the object characteristics in the image; determining the appropriate work field and the number of appropriate fields based on the specific object to be photographed; based on the number of appropriate fields not exceeding the preset number of fields, controlling the mobile terminal to display the work content of the appropriate work field based on the appropriate work field. This application has the effect of improving the efficiency of task allocation.

Description

Technical Field

[0001] The present invention relates to the field of gig market, and in particular to a task distribution method, system and terminal based on the gig market. Background Art

[0002] The gig market is a flexible labor market with a large number of short-term, temporary, or one-time work tasks. Task distribution is about how to allocate these tasks to the right workers.

[0003] Currently, the technologies related to task distribution in the gig market usually rely on traditional information interaction models, such as offline job notices and simple online information lists.

[0004] However, under this model, the scope of information dissemination is limited and updates are not timely, making it difficult for workers to quickly find tasks that match their skills and time, thereby reducing the efficiency of task allocation and requiring improvement. Summary of the Invention

[0005] In order to improve the efficiency of task allocation, the present invention provides a task distribution method, system and terminal based on the gig market.

[0006] In a first aspect, the present invention provides a task distribution method based on a gig market, which adopts the following technical solutions:

[0007] A task distribution method based on a gig market, comprising:

[0008] Obtaining a preset trigger signal of a mobile terminal;

[0009] When the trigger signal is consistent with the preset search signal, the mobile terminal is controlled to take a picture of the object to obtain the image information of the object;

[0010] Determine the features of the item in the image based on the item image information;

[0011] Determine whether a preset domain database contains an item corresponding to the item feature in the image;

[0012] If the domain database contains items corresponding to the features of the items in the image, the specific item photographed is determined based on the features of the items in the image;

[0013] Determine the appropriate work areas and the appropriate number of areas based on the specific items being photographed;

[0014] When the number of suitable fields does not exceed the preset number of fields, the mobile terminal is controlled to display the work content of the suitable work field according to the suitable work field.

[0015] By employing this technical solution, when the trigger signal matches the search signal, the user is guided to photograph the object, thereby acquiring its image information. The image then identifies the object's features and searches for matching objects in the domain database. If a matching object exists, the specific object photographed is further identified, and the appropriate work domain and quantity are determined. When the number of suitable domains falls within a reasonable range, the user is presented with the work content for the corresponding domain. This effectively addresses the low efficiency of task allocation under traditional models and improves the efficiency of task allocation in the gig economy.

[0016] Optionally, a field reduction method is also included:

[0017] When the number of suitable fields exceeds a preset excessive number of fields, controlling the mobile terminal to report a keyword input prompt and obtaining screen image information of the mobile terminal;

[0018] Determine the input box position based on screen image information and preset input box features;

[0019] Determine text input content based on screen image information, input box position, and preset text features;

[0020] Update appropriate work areas based on text input and specific photographed items;

[0021] The mobile terminal is controlled to display work content based on the updated appropriate work area.

[0022] Optionally, the method further includes the following steps after controlling the mobile terminal to take a picture of the object to obtain image information of the object:

[0023] If the domain database does not contain an item corresponding to the item feature in the image, the mobile terminal is controlled to perform a gesture shooting prompt to obtain a working gesture video;

[0024] Describe the content with actual gestures based on the working gesture video;

[0025] Determine the work content of the item based on the gesture description content and the features of the item in the picture;

[0026] Determine the appropriate work area based on the work content of the item;

[0027] The mobile terminal is controlled to display work content based on the appropriate work domain, and the corresponding relationship between the object features in the image and the appropriate work domain is input into the domain database to update the domain database.

[0028] Optionally, include corrections for the appropriate work area:

[0029] Obtaining a video background image based on the work gesture video;

[0030] When the video background image contains preset working equipment features, the background working equipment is determined according to the video background image and the working equipment features;

[0031] Determine the benchmark work equipment based on the work content of the item;

[0032] When the reference work equipment is inconsistent with the background work equipment, determine the work difference based on the reference work equipment and the background work equipment;

[0033] When the work difference does not exceed a preset benchmark difference, controlling the mobile terminal to display work content recommendations in appropriate work areas;

[0034] When the work difference exceeds the preset baseline difference, the appropriate work area is modified based on the background work equipment, gesture description content and object features in the picture;

[0035] The mobile terminal is controlled to display the work content recommendation in the corrected suitable work field, and the corresponding relationship between the object features in the image and the corrected suitable work field is input into the field database to update the field database.

[0036] Optionally, it also includes process streamlining methods:

[0037] When the specific photographed object is a preset industrially manufactured object, the manufacturing process and the number of process steps of the object are determined based on the specific photographed object;

[0038] When the number of item production processes is greater than 1, the actual production process is determined based on the item production process and gesture description content;

[0039] Determine the appropriate work content and quantity based on the actual production process;

[0040] When the number of work contents is not greater than the preset benchmark work quantity, similar work contents are determined based on appropriate work contents and appropriate work areas;

[0041] Control the mobile terminal to display appropriate work content and similar work content.

[0042] Optionally, it also includes non-legacy processing methods:

[0043] When the specific photographed item is a preset handmade item, the mobile terminal is controlled to provide an item production prompt to obtain an item production video;

[0044] Based on the preset craftsmanship database, determine whether the specific photographed item is a preset intangible cultural heritage item;

[0045] If the specific photographed item is an intangible cultural heritage item, determine whether the specific photographed item has a preset untransmitted craft based on the preset intangible cultural heritage database;

[0046] If there is a craft that is not passed down, the specific item will be photographed to determine the craftsmanship of the item;

[0047] Determine the video clips to be coded based on the item production video, item production process, and non-transmitted process;

[0048] The video of item production is coded based on the video coding clip.

[0049] Optionally, also include a craft rating method:

[0050] After obtaining the item production video, determine the item production time based on the item production video;

[0051] Determine the baseline production time based on the specific item being photographed;

[0052] When the benchmark production time is inconsistent with the item production time, the difference between the benchmark production time and the item production time is calculated as the time difference value;

[0053] Determine craftsmanship rating based on duration difference value;

[0054] When the craftsmanship rating is lower than a preset benchmark rating, determining whether a preset teaching database contains a teaching video for the handmade item;

[0055] If included, the mobile terminal is controlled to display the teaching video corresponding to the handmade item.

[0056] Optionally, also include character verification method:

[0057] Determine whether the work gesture video contains preset facial features;

[0058] If the work gesture video contains facial features, determine whether the facial features are consistent with preset baseline facial features;

[0059] When the facial features of a person are inconsistent with the baseline facial features, an abnormal prompt of the person will be reported;

[0060] If the work gesture video does not contain facial features, hand features are determined based on the work gesture video;

[0061] When the hand features are inconsistent with the preset baseline hand features, a person abnormality prompt is reported.

[0062] Secondly, this application provides a task distribution system based on the gig market, which adopts the following technical solutions:

[0063] A task distribution system based on a gig market, comprising:

[0064] An acquisition module is used to obtain trigger signals and screen image information;

[0065] A memory for storing a program for any one of the aforementioned gig market-based task distribution methods;

[0066] The processor is configured to load, execute, and implement the program stored in the memory.

[0067] In a third aspect, the present application provides a terminal that adopts the following technical solution:

[0068] A terminal includes a memory and a processor, wherein the memory stores information that can be loaded and executed by the processor.

[0069] In summary, this application includes at least one of the following beneficial technical effects:

[0070] 1. When the trigger signal matches the search signal, the worker is guided to take a photo of the item to obtain the item's image information. The item's features are then determined based on the image, and matching items are searched for in the domain database. If a matching item exists, the specific item photographed is further identified, and the appropriate work area and quantity are determined. When the number of suitable areas is within a reasonable range, the work content of the corresponding work area is displayed to the user, effectively solving the problem of low task allocation efficiency in the traditional model and improving the efficiency of task allocation in the gig economy.

[0071] 2. When there is no item in the domain database that corresponds to the features of the item in the picture, the worker is guided to shoot a gesture to obtain a video of the work gesture. The gesture description is then determined based on the video, and the work content of the item is clarified in combination with the features of the item, thereby determining the appropriate work area. Subsequently, the mobile terminal is controlled to display the content of the work area, and the correspondence between the features of the item in the picture and the appropriate work area is entered into the domain database for update, thereby providing more task options for the workers. At the same time, the update of the database continuously improves the information reserve, which helps to allocate tasks more accurately and efficiently in the future;

[0072] 3. When the specific item being photographed is handmade, the mobile terminal is controlled to obtain a video of the item's production. Next, the craft database is used to determine whether the item is an intangible cultural heritage item. If so, the intangible cultural heritage database is further used to determine whether it contains any untransmitted craftsmanship. If so, the production process is determined, and then, based on the item's production video, the production process, and the untransmitted craftsmanship, a coded segment of the video is determined. This balances the display of handmade items and the protection of intangible cultural heritage in the distribution of tasks in the gig market. This allows workers to participate in related work while protecting the untransmitted craftsmanship in intangible cultural heritage items from being disseminated indiscriminately by determining the coded segments. This balances the relationship between cultural inheritance and market application, improving the efficiency of task allocation while also promoting the rational protection and inheritance of intangible cultural heritage. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 is a method flow chart of a method for distributing tasks based on a gig market in an embodiment of the present invention;

[0074] Figure 2 is a method flow chart of a method for streamlining the number of fields in an embodiment of the present invention;

[0075] Figure 3 This is a flowchart of the steps after controlling the mobile terminal to take a picture of an object to obtain image information of the object in an embodiment of the present invention;

[0076] Figure 4 is a method flow chart of a correction method for a suitable working field in an embodiment of the present invention;

[0077] Figure 5 This is a method flow chart of a process streamlining method according to an embodiment of the present invention;

[0078] Figure 6 is a method flow chart of the intangible cultural heritage processing method in an embodiment of the present invention;

[0079] Figure 7 is a method flow chart of a craftsmanship rating method according to an embodiment of the present invention;

[0080] Figure 8 4 is a flowchart of a method for character verification in an embodiment of the present invention. DETAILED DESCRIPTION

[0081] The present invention is further described in detail below with reference to the accompanying drawings and embodiments.

[0082] Reference Figure 1 , the embodiment of the present application discloses a task distribution method based on the gig market, comprising the following steps:

[0083] Step 100: Obtain a preset trigger signal of a mobile terminal.

[0084] A mobile terminal refers to an electronic device that migrant workers can use while on the move. In this embodiment, the mobile terminal is a mobile phone. A trigger signal is a signal generated by a migrant worker touching, clicking, or otherwise interacting with the screen of the mobile terminal. The trigger information is obtained by a controller chip on the mobile terminal. The mobile terminal is equipped with a touch sensor, which converts the touch information into electrical signals and transmits these signals to the controller chip. The controller chip processes and analyzes the signals, identifies the touch location, and then converts them into instructions that can be understood and processed by the mobile terminal.

[0085] Step 101: When a trigger signal is consistent with a preset search signal, the mobile terminal is controlled to take a picture of the object to obtain image information of the object.

[0086] A search signal is a signal generated when a worker taps the screen of a mobile terminal to indicate a search request. An item capture prompt is a prompt from a mobile terminal requesting the worker to capture items related to their area of ​​expertise. Both the search signal and the item capture prompt are pre-set by those skilled in the art and are not detailed here. Item image information refers to the image of an item captured by the worker. Item image information is captured by the worker controlling the mobile terminal.

[0087] When the trigger signal is consistent with the search signal, it means that the worker needs to search for odd jobs and needs to control the mobile terminal to take pictures of objects, thereby providing the worker with the opportunity to take pictures of objects related to his or her field of expertise to obtain object image information for subsequent steps.

[0088] Step 102: Determine features of the object in the image based on the object image information.

[0089] The object features in an image refer to the appearance and outline features of the object in the image. These features can be obtained by scanning and identifying the object in the image information. Image recognition technology is common knowledge among those skilled in the art and will not be discussed in detail here.

[0090] Step 103: Determine whether the preset domain database contains an item corresponding to the item feature in the image.

[0091] The domain database contains different items corresponding to different image item features. Professionals in this field pre-assigned the different image item features to the corresponding items in the domain database, and then recorded these correspondences to form a database. The specific matching and recording process is not detailed here.

[0092] By determining whether the domain database contains items corresponding to the features of the items in the image, we can know whether the specific photographed items can be matched.

[0093] Step 104: If the domain database contains an object corresponding to the object features in the image, the specific object to be photographed is determined based on the object features in the image.

[0094] Specific items are the specific categories of items photographed by the workers. The domain database can be used to match the specific items photographed with the features of the items in the image, including the corresponding relationship between the features of the items in the image and the specific items photographed.

[0095] If the domain database contains items corresponding to the features of the items in the image, it means that the specific items in the image can be determined by the features of the items in the image, and the specific items in the image can be matched directly.

[0096] Step 105: Determine the appropriate working area and the number of appropriate areas based on the specific photographed object.

[0097] Suitable work areas refer to areas suitable for the worker. The number of suitable work areas refers to the number of suitable work areas for the worker. Suitable work areas corresponding to specific photographed items can be matched using the domain database, which records the corresponding information between various items and related work areas. Once a specific photographed item is identified, a precise search using that item as a search keyword in the domain database can quickly filter out all suitable work areas corresponding to it. All suitable work areas are then accumulated and counted to determine the number of suitable areas.

[0098] Step 106: When the number of suitable fields does not exceed the preset excessive number of fields, control the mobile terminal to display the work content of the suitable work field according to the suitable work field.

[0099] The excessive number of fields refers to a value indicating that the number of suitable work fields matched is excessive. The excessive number of fields is set in advance by those skilled in the art and will not be described in detail here.

[0100] When the number of suitable fields does not exceed the excessive number of fields, it means that the number of matched suitable work fields is not too many, and the mobile terminal can be directly controlled to display the work content corresponding to the suitable work fields for the workers to choose.

[0101] Reference Figure 2 ,The method for reducing the number of fields includes the following steps:

[0102] Step 200: When the number of suitable fields exceeds a preset excessive number of fields, the mobile terminal is controlled to report a keyword input prompt and screen image information of the mobile terminal is obtained.

[0103] A keyword input prompt refers to a prompt that prompts a worker to enter a keyword. Keyword input prompts are pre-set by those skilled in the art and are not described in detail here. Screen image information refers to an image of the current screen of a mobile terminal. Screen image information is obtained by taking a screenshot of the mobile terminal.

[0104] When the number of suitable fields exceeds the excessive field number, it means that the number of matched suitable work fields is too large. It is necessary to first control the mobile terminal to report the keyword input prompt, and then obtain the screen image information of the mobile terminal for subsequent steps.

[0105] Step 201: Determine the position of the input box according to the screen image information and the preset input box features.

[0106] Input box features refer to the appearance characteristics of the input box used to enter keywords. Input box features are pre-determined by those skilled in the art and are not described in detail here. Input box position refers to the position of the input box on the screen. The input box position can be determined by identifying input box features in screen image information. Image recognition technology is common knowledge in the art and is not described in detail here.

[0107] Step 202: Determine text input content based on screen image information, input box position, and preset text features.

[0108] Text features refer to the appearance characteristics of the text entered into the input box. Text features are pre-determined by those skilled in the art and are not described in detail here. Text input content refers to the text content within the input box. The text input content can be obtained by identifying the text features at the input box location within the screen image information. Image recognition technology is common knowledge in the art and is not described in detail here.

[0109] Step 203: Update the appropriate work area based on the text input content and the specific photographed object.

[0110] The domain database is used to re-match the appropriate work domain corresponding to the specific photographed object and the text input content, so as to update the appropriate work domain and further reduce the number of work domains.

[0111] The database records the corresponding information between specific photographed objects and text inputs and suitable work fields. Once the specific photographed objects and text inputs are determined, they can be used as search keywords to conduct precise searches in the field database, quickly screening all corresponding suitable work fields.

[0112] Step 204: Control the mobile terminal to display work content based on the updated appropriate work area.

[0113] The mobile terminal is controlled to display the updated work content corresponding to the appropriate work field for the workers to choose.

[0114] Reference Figure 3 , further comprising the steps of controlling the mobile terminal to shoot the object to obtain the image information of the object:

[0115] Step 300: If the domain database does not contain an object corresponding to the object feature in the image, control the mobile terminal to perform a gesture shooting prompt to obtain a working gesture video.

[0116] A gesture capture prompt is a prompt that prompts workers to describe their work content with gestures. Gesture capture prompts are pre-set by those skilled in the art and will not be described in detail here. A work gesture video is a video of workers describing their work content with gestures.

[0117] When the domain database does not contain the item corresponding to the item features in the picture, it means that the specific photographed item cannot be determined through the item features in the picture. It is necessary to control the mobile terminal to perform gesture shooting prompts to prompt the workers to shoot work gesture videos, and then obtain the work gesture videos shot by the workers.

[0118] Step 301: Describe the content with actual gestures based on the working gesture video.

[0119] Gesture descriptions refer to the specific information about work content conveyed by workers through their hand movements and postures in work gesture videos. The work gesture videos are pre-processed for noise reduction and deblurring. An object detection algorithm is then used to locate and segment the hands. These features, including geometry, motion, and appearance, are then input into a trained gesture classification model to identify the gesture descriptions. Object detection algorithms are well-known in the art and are not described in detail here. The gesture classification model is pre-trained by those skilled in the art and is not described here.

[0120] Step 302: Determine the working content of the object according to the gesture description content and the features of the object in the image.

[0121] Item work content refers to the specific work situation and task content associated with an item. By combining the information about the work conveyed by the worker through gesture descriptions and the item features extracted from the item image, the item work content associated with the item can be determined.

[0122] Step 303: Determine the appropriate work area based on the work content of the item.

[0123] This step is similar to the above step 105 and will not be described in detail here.

[0124] Step 304: Control the mobile terminal to display the work content based on the appropriate work domain, and input the corresponding relationship between the object features in the image and the appropriate work domain into the domain database to update the domain database.

[0125] The mobile terminal is controlled to display the work content corresponding to the appropriate work field, and the corresponding relationship between the object features in the image and the appropriate work field is input into the field database to update the field database.

[0126] Reference Figure 4 , the correction method for the appropriate working area includes the following steps:

[0127] Step 400: Obtain a video background image based on the work gesture video.

[0128] The video background image refers to the background image in the work gesture video. This video background image is obtained by analyzing the work gesture video frame by frame and using image segmentation technology to separate the foreground (the portion showing the worker's hand movements) from the background in each frame. Image segmentation technology is common knowledge in the field and will not be discussed in detail here.

[0129] Step 401: When the video background image contains preset working equipment features, the background working equipment is determined according to the video background image and the working equipment features.

[0130] Work equipment features refer to the features of the equipment used when performing work related to specific photographed items. Work equipment features are set in advance by those skilled in the art and will not be described in detail here. Background work equipment refers to the specific equipment used by workers when performing work related to specific photographed items. By performing image recognition on the work equipment features in the video background image, the background work equipment corresponding to the work equipment features is matched from the preset equipment database. The database stores different background work equipment corresponding to various types of work equipment features. The equipment database is a manually set database and will not be described in detail here.

[0131] When the background image of the video contains work equipment features, it means that the workers have equipment used to carry out related work on the specific photographed objects. The specific background work equipment must be determined first for subsequent steps.

[0132] Step 402: Determine the reference working equipment according to the working content of the item.

[0133] Reference work equipment refers to equipment that, based on the work content of an item, plays a key role in completing the work associated with that item and serves as the primary operating tool. Reference work equipment corresponding to each item's work content can be matched using the equipment database, which stores different reference work equipment corresponding to different item work contents.

[0134] Step 403 : When the reference working device and the background working device are inconsistent, determine the working difference based on the reference working device and the background working device.

[0135] Operational diversity refers to the degree of difference between the reference and background devices in terms of device type, function, performance, operation mode, and applicable scenarios. The operational diversity of reference and background devices can be matched using a pre-set database. This database stores the different operational diversity corresponding to various reference and background devices. This database is generated by technicians in this field by sequentially measuring different reference and background devices, and is not detailed here.

[0136] Step 404: When the work difference does not exceed a preset reference difference, control the mobile terminal to display work content recommendations in a suitable work field.

[0137] The reference difference refers to the maximum value allowed for the working difference. The reference difference is set in advance by those skilled in the art and will not be described in detail here.

[0138] When the work difference does not exceed the benchmark difference, it means that the work content between the two is not much different, and the mobile terminal can be directly controlled to display the work content in the appropriate work field for recommendation.

[0139] Step 405: When the work difference exceeds a preset reference difference, the appropriate work area is modified according to the background work equipment, gesture description content, and features of the objects in the image.

[0140] When the work difference exceeds the benchmark difference, it means that the work content between the two is too different and the appropriate work area needs to be corrected first for subsequent steps. The correction method is the same as step 203 and will not be repeated here.

[0141] Step 406: Control the mobile terminal to display the work content recommendation in the corrected suitable work field, and input the correspondence between the object features in the image and the corrected suitable work field into the field database to update the field database.

[0142] The mobile terminal is controlled to display the work content in the corrected appropriate work area to advance, and then the corresponding relationship between the object features in the image and the corrected appropriate work area is input into the area database to update the area database.

[0143] Reference Figure 5 The process streamlining method includes the following steps:

[0144] Step 500: When the specific photographed object is a preset industrially manufactured object, determine the manufacturing process of the object and the number of the manufacturing process of the object according to the specific photographed object.

[0145] Industrially manufactured goods are manufactured through industrial production methods using a variety of raw materials, machinery, equipment, and process technologies, following specific design requirements and quality standards through a series of processing, manufacturing, and assembly processes. The manufacturing process for an item refers to the specific steps involved in transforming raw materials into the final industrially manufactured item. The number of steps in an item's production process refers to the specific number of steps involved in the production of the industrially manufactured item.

[0146] A pre-set process database can be used to match specific photographed items with the corresponding production process and process quantity. This database stores the different production process and process quantity corresponding to each specific photographed item. This process database is generated by technicians in this field through sequential testing on different specific photographed items and is not detailed here.

[0147] When the specific item being photographed is an industrially manufactured item, it is necessary to first determine the item's manufacturing process and the number of item manufacturing processes for subsequent steps.

[0148] Step 501: When the number of steps for an item is greater than 1, the actual production step is determined based on the item production step and the gesture description content.

[0149] The actual production process refers to the specific operational procedures and steps that the worker went through when making the item. By understanding the established production process for the item and the actual operational information conveyed by the worker through gestures, the actual sequence of steps actually executed to produce the specific photographed item is the actual production process.

[0150] When the number of steps for an item is greater than 1, it means that multiple steps are required to manufacture the item, and the actual production steps must be determined first for subsequent steps.

[0151] Step 502: Determine appropriate work content and work content quantity based on the actual production process.

[0152] Appropriate work content refers to specific work tasks that match and adapt to the operations performed by the worker based on the actual production process. The number of work contents refers to the number of specific work tasks that match and adapt to the operations performed by the worker based on the actual production process. Appropriate work content corresponding to the actual production process can be matched through the domain database, which records the corresponding association information between various actual production processes and appropriate work content. After the actual production process is determined, the production process is used as the search keyword to conduct an accurate query in the domain database, which can quickly screen out all corresponding appropriate work content. All appropriate work contents are then accumulated and counted to obtain the number of suitable fields.

[0153] Step 503: When the number of work contents is not greater than the preset benchmark work number, similar work contents are determined based on suitable work contents and suitable work fields.

[0154] The baseline workload refers to the number used to compare whether the workload is sufficient. The baseline workload is pre-determined by those skilled in the art and will not be detailed here. Similar workload refers to other tasks that are similar to the worker's current workload in terms of nature, skill requirements, operational procedures, and work objectives, based on the worker's appropriate workload and their appropriate work field, when the workload is insufficient.

[0155] Suitable work content and similar work content corresponding to suitable work fields can be matched using a preset work database. This database stores various types of suitable work content and similar work content corresponding to suitable work fields. The work database is formed by those skilled in the art sequentially recording different suitable work content and suitable work fields, and is not further described here.

[0156] Step 504: Control the mobile terminal to display the appropriate work content and similar work content.

[0157] The mobile terminal is controlled to display suitable work content and similar work content for workers to select.

[0158] Reference Figure 6 The intangible cultural heritage processing method includes the following steps:

[0159] Step 600: When the specific photographed item is a preset handmade item, the mobile terminal is controlled to provide an item production prompt to obtain an item production video.

[0160] Handmade items are items that are primarily crafted from raw materials using manual skills and hand tools, rather than large-scale mechanized production equipment, through the maker's creativity, design, and manual labor. Item production prompts are prompts used to record videos of migrant workers making handmade items. Item production prompts are pre-set by those skilled in the art and are not detailed here. Item production videos are videos of migrant workers making handmade items. Item production videos are recorded using mobile devices.

[0161] When the specific photographed item is a handmade item, it is necessary to control the mobile terminal to provide an item production prompt, thereby prompting the worker to shoot an item production video, and then obtain the item production video shot by the worker.

[0162] Step 601: Determine whether the specific photographed item is a preset intangible cultural heritage item based on a preset craftsmanship database.

[0163] Intangible cultural heritage items refer to handicrafts related to intangible cultural heritage. These items are pre-defined by those skilled in the art and will not be detailed here.

[0164] By determining whether the specific photographed item is an intangible cultural heritage item from the craft database, it is determined whether the subsequent step 602 needs to be performed. The craft database stores different intangible cultural heritage items corresponding to each specific photographed item. The craft database is formed by those skilled in the art by sequentially recording all intangible cultural heritage items, and will not be described in detail here.

[0165] Step 602: If the specific photographed item is an intangible cultural heritage item, determine whether the specific photographed item has a preset non-transmitted craft based on a preset intangible cultural heritage database.

[0166] Untransmitted crafts refer to unique production techniques that are not easily passed on during the process of intangible cultural heritage. Untransmitted crafts are pre-determined by those skilled in the art and will not be detailed here.

[0167] If the specific item being photographed is an intangible cultural heritage item, it is necessary to check the intangible cultural heritage database to determine whether the item uses any unconventional craftsmanship, so as to determine whether the item's production video should be coded. The intangible cultural heritage database stores the different unconventional craftsmanship corresponding to each specific item. This database is compiled by those skilled in the art by sequentially recording the unconventional craftsmanship of all intangible cultural heritage items, and will not be detailed here.

[0168] When the specific item being filmed is not an intangible cultural heritage item, the video of the item production can be made public directly.

[0169] Step 603: If there is any untransmitted process, the manufacturing process of the item is determined based on the specific photographed item.

[0170] The manufacturing process refers to the overall handcrafting process for a specific photographed item. A pre-set manufacturing process database can be used to match the manufacturing process for a specific photographed item. This database stores different manufacturing processes for each specific item. This database can be created by those skilled in the art by sequentially recording the manufacturing processes for different specific items, and will not be detailed here.

[0171] If the specific item being photographed has a production process that is not yet known, you must first determine the production process for the item in order to proceed with the next steps.

[0172] Step 604: Determine the video coded segment based on the item production video, the item production process, and the non-transmitted process.

[0173] Blurred video clips are clips that censor hidden manufacturing processes within production videos. By breaking down each frame of the production video, the specific manufacturing process is revealed. By comparing the video footage with known hidden manufacturing processes, the sections involving these processes are precisely identified. These sections are then labeled as censored video clips.

[0174] Step 605: Perform coding processing on the item production video based on the video coding segment.

[0175] The mobile terminal is controlled to perform coding processing on the video coding segment in the item production video. Video coding technology is common knowledge in this field and will not be described in detail here.

[0176] Reference Figure 7 , the craft rating method includes the following steps:

[0177] Step 700: After obtaining the item production video, determine the item production time based on the item production video.

[0178] The production time is the length of time it takes a worker to create the item. This is calculated by calculating the time difference between the moment the worker begins actual production operations on the raw materials and the moment the item is completed in the production video.

[0179] After obtaining the item production video, you need to first determine the item production time for subsequent steps.

[0180] Step 701: Determine a baseline production time based on the specific photographed object.

[0181] The baseline production time refers to the baseline length of time required to produce an item. A preset production database can be used to match the baseline production time for a specific item. This database stores different baseline production times for each specific item. This database was created by those skilled in the art through sequential testing and recording of baseline production times for different specific items. This database is not detailed here.

[0182] Step 702: When the benchmark production time is inconsistent with the item production time, the difference between the benchmark production time and the item production time is calculated as the time difference value.

[0183] The duration difference value refers to the difference between the worker's production time and the baseline production time. The duration difference value is calculated by subtracting the baseline production time from the item production time. In this embodiment, the duration difference value can be a negative number. If the duration difference value is negative, it indicates that the worker produced the item too quickly.

[0184] When the benchmark production time is inconsistent with the item production time, the time difference needs to be calculated so that the workers' craftsmanship can be rated later.

[0185] Step 703: Determine a craftsmanship rating based on the duration difference value.

[0186] Craftsmanship ratings are a comprehensive assessment of the worker's proficiency in crafting an item. Craftsmanship ratings corresponding to duration differences are matched using a pre-set ratings database. This database stores different craftsmanship ratings for different duration differences. This database is generated by technicians in this field, who sequentially evaluate and record the different craftsmanship ratings corresponding to different duration differences. This database is not detailed here.

[0187] Step 704: When the craftsmanship rating is lower than a preset benchmark rating, determine whether a preset teaching database contains a teaching video for the handmade item.

[0188] The baseline rating is a standard level used to measure skill levels. The instructional video is a video used to teach crafts to workers whose skill ratings are below the baseline rating. Both the baseline rating and instructional video are pre-set by those skilled in the art and will not be detailed here.

[0189] When the craftsmanship rating is lower than the benchmark rating, it means that the worker's skills need to be further improved. It is necessary to first determine whether the teaching database contains teaching videos of the handmade items for subsequent steps.

[0190] The teaching database stores different teaching videos corresponding to various types of handmade items. The teaching database is formed by technicians in this field recording the teaching videos of different handmade items in sequence, which will not be described in detail here.

[0191] Step 705: If included, control the mobile terminal to display the teaching video corresponding to the handmade item.

[0192] If the teaching database contains a teaching video of the handmade item, the mobile terminal can be controlled to display the teaching video corresponding to the handmade item for the worker to learn.

[0193] Reference Figure 8 , the character verification method includes the following steps:

[0194] Step 800: Determine whether the work gesture video contains preset facial features.

[0195] Facial features refer to various physiological characteristics and attributes that make a person's face unique. Facial features are pre-defined by those skilled in the art and will not be described in detail here.

[0196] By determining whether the work gesture video contains facial features, we can determine whether the worker's face is visible and whether subsequent hand feature recognition is necessary. Hand features refer to the various unique physiological characteristics and attributes of the human hand.

[0197] Step 801: If the work gesture video contains facial features, determine whether the facial features are consistent with preset reference facial features.

[0198] The baseline facial features refer to the specific facial feature information associated with the account on the mobile terminal. The baseline facial features are pre-entered by the worker.

[0199] If the work gesture video contains facial features, it means that the worker's face is exposed. It is necessary to determine whether the facial features are consistent with the baseline facial features in order to know whether the worker is incorrect.

[0200] Step 802: When the facial features of the person are inconsistent with the reference facial features, a person abnormality prompt is reported.

[0201] The abnormal person prompt is a prompt issued when the worker makes a mistake. The abnormal person prompt is set in advance by those skilled in the art and will not be described in detail here.

[0202] When the facial features are inconsistent with the baseline facial features, it means that the worker is incorrect and the person anomaly prompt must be reported.

[0203] Step 803: If the work gesture video does not contain facial features, determine hand features based on the work gesture video.

[0204] If the hand gesture video doesn't contain facial features, it means the worker's face isn't visible. Hand features must be determined based on the video for subsequent steps. Hand features are determined by analyzing the overall hand contours in the hand gesture video, including palm size, shape, finger thickness, length ratios, and joint morphology. Video feature recognition technology is common knowledge in the field and will not be detailed here.

[0205] Step 804: When the hand feature is inconsistent with the preset reference hand feature, a person abnormality prompt is reported.

[0206] The baseline hand features refer to the hand feature information of the person associated with the account on the mobile terminal. The baseline hand features are pre-entered by the worker.

[0207] When the hand features are inconsistent with the baseline hand features, it means that the worker is incorrect and the person abnormality prompt must be reported.

[0208] Based on the same inventive concept, an embodiment of the present invention provides a task distribution system based on a gig market, including:

[0209] An acquisition module is used to obtain trigger signals and screen image information;

[0210] a memory for storing a program for a method for distributing tasks based on a gig market;

[0211] The processor is configured to load, execute, and implement the program stored in the memory.

[0212] Based on the same inventive concept, an embodiment of the present invention provides a terminal including a memory and a processor, wherein the memory stores a task distribution method based on a gig market that can be loaded and executed by the processor.

[0213] Those skilled in the art will clearly understand that for the sake of convenience and brevity, the division of the above-mentioned functional modules is only used as an example for illustration. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. The specific working processes of the above-mentioned systems, devices, and units can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0214] The above description is merely a preferred embodiment of the present invention. The scope of protection of the present invention is not limited to the above embodiment. All technical solutions based on the concept of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should also be considered within the scope of protection of the present invention.

Claims

1. A task distribution method based on gig market, characterized in that: include: Obtaining a preset trigger signal of a mobile terminal; When the trigger signal is consistent with the preset search signal, the mobile terminal is controlled to take a picture of the object to obtain the image information of the object; Determine the features of the item in the image based on the item image information; Determine whether a preset domain database contains an item corresponding to the item feature in the image; If the domain database contains items corresponding to the features of the items in the image, the specific item photographed is determined based on the features of the items in the image; Determine the appropriate work areas and the appropriate number of areas based on the specific items being photographed; When the number of suitable fields does not exceed the preset number of fields, controlling the mobile terminal to display work content of the suitable work field according to the suitable work field; The method further includes the following steps after controlling the mobile terminal to take a picture of the object to obtain image information of the object: If the domain database does not contain an item corresponding to the item feature in the image, the mobile terminal is controlled to perform a gesture shooting prompt to obtain a working gesture video; Describe the content with actual gestures based on the working gesture video; Determine the work content of the item based on the gesture description content and the features of the item in the picture; Determine the appropriate work area based on the work content of the item; Controlling the mobile terminal to display work content based on the appropriate work domain, and inputting the correspondence between the features of the objects in the image and the appropriate work domain into the domain database to update the domain database; Also includes non-legacy processing methods: When the specific photographed item is a preset handmade item, the mobile terminal is controlled to provide an item production prompt to obtain an item production video; Based on the preset craftsmanship database, determine whether the specific photographed item is a preset intangible cultural heritage item; If the specific photographed item is an intangible cultural heritage item, determine whether the specific photographed item has a preset untransmitted craft based on the preset intangible cultural heritage database; If there is a craft that is not passed down, the specific item will be photographed to determine the craftsmanship of the item; Determine the video clips to be coded based on the item production video, item production process, and non-transmitted process; Based on the video coding clips, the item production video is coded; Also included are corrections for appropriate work areas: Obtaining a video background image based on the work gesture video; When the video background image contains preset working equipment features, the background working equipment is determined according to the video background image and the working equipment features; Determine the benchmark work equipment based on the work content of the item; When the reference work equipment is inconsistent with the background work equipment, determine the work difference based on the reference work equipment and the background work equipment; When the work difference does not exceed a preset benchmark difference, controlling the mobile terminal to display work content recommendations in appropriate work areas; When the work difference exceeds the preset baseline difference, the appropriate work area is modified based on the background work equipment, gesture description content and object features in the picture; Controlling the mobile terminal to display the work content recommendation in the corrected suitable work field, and inputting the correspondence between the features of the objects in the image and the corrected suitable work field into the field database to update the field database; It also includes process streamlining methods: When the specific photographed object is a preset industrially manufactured object, the manufacturing process and the number of process steps of the object are determined based on the specific photographed object; When the number of item production processes is greater than 1, the actual production process is determined based on the item production process and gesture description content; Determine the appropriate work content and quantity based on the actual production process; When the number of work contents is not greater than the preset benchmark work quantity, similar work contents are determined based on appropriate work contents and appropriate work areas; Control the mobile terminal to display appropriate work content and similar work content.

2. A method for distributing tasks based on a gig market according to claim 1, characterized in that: Also includes methods for reducing the number of fields: When the number of suitable fields exceeds a preset excessive number of fields, controlling the mobile terminal to report a keyword input prompt and obtaining screen image information of the mobile terminal; Determine the input box position based on screen image information and preset input box features; Determine text input content based on screen image information, input box position, and preset text features; Update appropriate work areas based on text input and specific photographed items; The mobile terminal is controlled to display work content based on the updated appropriate work area.

3. The task distribution method based on the gig market according to claim 1, characterized in that: Also includes craft rating methods: After obtaining the item production video, determine the item production time based on the item production video; Determine the baseline production time based on the specific item being photographed; When the benchmark production time is inconsistent with the item production time, the difference between the benchmark production time and the item production time is calculated as the time difference value; Determine craftsmanship rating based on duration difference value; When the craftsmanship rating is lower than a preset benchmark rating, determining whether a preset teaching database contains a teaching video for the handmade item; If included, the mobile terminal is controlled to display the teaching video corresponding to the handmade item.

4. The task distribution method based on the gig market according to claim 1, characterized in that: Also includes character verification method: Determine whether the work gesture video contains preset facial features; If the work gesture video contains facial features, determine whether the facial features are consistent with preset baseline facial features; When the facial features of a person are inconsistent with the baseline facial features, an abnormal prompt of the person will be reported; If the work gesture video does not contain facial features, hand features are determined based on the work gesture video; When the hand features are inconsistent with the preset baseline hand features, a person abnormality prompt is reported.

5. A task distribution system based on gig market, characterized in that: include: An acquisition module is used to obtain trigger signals and screen image information; A memory for storing a program of a method for distributing tasks based on a gig market according to any one of claims 1 to 4; The processor is configured to load, execute, and implement the program stored in the memory.

6. A terminal, characterized in that: The method comprises a memory and a processor, wherein the memory stores a task distribution method based on a gig market that can be loaded and executed by the processor as described in any one of claims 1 to 4.

Images