Intelligent degree evaluation method and device, equipment and storage medium

Abstract

The embodiment of the invention discloses an intelligent degree evaluation method and device, equipment and a storage medium, and the method comprises the steps: obtaining an intelligent equipment list corresponding to a target space, and generating an intelligent service set corresponding to the target space based on the types of intelligent equipment in the intelligent equipment list, the intelligent service set comprises at least one intelligent service; determining a first weight coefficient and a service score corresponding to each intelligent service in the intelligent service set; and according to the first weight coefficient and the service score corresponding to each intelligent service, evaluating the intelligent degree of the target space. According to the scheme, the user does not need to consume a lot of energy and time to evaluate the intelligent degree of the smart home, so that the efficiency of evaluating the intelligent degree is improved.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and in particular to an intelligent degree evaluation method, device, equipment and storage medium. Background Art

[0002] Smart home is a networked intelligent home control system that uses residence as a platform and integrates automation control system, computer network system and network communication technology. It improves home safety, convenience, comfort and artistry, and realizes an environmentally friendly and energy-saving living environment.

[0003] However, there are many types of smart devices and their functions are complex. The intelligence of smart homes is also a problem that users find difficult to evaluate. Because the intelligence of smart homes depends not only on the types and number of smart devices, but also on the interconnection between smart devices and the quality of smart services. Therefore, users often need to spend a lot of energy and time to learn and evaluate smart home solutions, which brings great inconvenience and pressure to users. Summary of the invention

[0004] In view of this, the present application provides a method, device, equipment and storage medium for evaluating the degree of intelligence, which is used to solve the problem that users need to spend a lot of energy and time to learn and evaluate smart home solutions in the prior art. In order to achieve one or part or all of the above purposes or other purposes, the present application proposes a method, device, equipment and storage medium for evaluating the degree of intelligence.

[0005] First aspect:

[0006] The present application provides an intelligent degree assessment method, comprising:

[0007] Acquire a list of smart devices corresponding to the target space, and generate a smart service set corresponding to the target space based on the types of smart devices in the list of smart devices, wherein the smart service set includes at least one smart service;

[0008] Determine a first weight coefficient and a service score corresponding to each intelligent service in the intelligent service set;

[0009] The intelligence level of the target space is evaluated according to the first weight coefficient and the service score corresponding to each intelligent service.

[0010] Second aspect:

[0011] The present application provides an intelligent degree assessment method, comprising:

[0012] Displaying an intelligent evaluation interface corresponding to the target space, wherein the intelligent evaluation interface includes evaluation function items;

[0013] In response to a trigger operation for the evaluation function item, the intelligence level of the target space is displayed. The intelligence level of the target space is determined based on the first weight coefficient and service score corresponding to each intelligent service in the target space. The intelligent service is determined based on the type of each intelligent device in the target space.

[0014] In a third aspect, the present application provides an intelligent degree assessment device, comprising:

[0015] The acquisition module is used to obtain the list of smart devices corresponding to the target space;

[0016] A generating module, based on the type of smart devices in the smart device list, generates a smart service set corresponding to the target space, wherein the smart service set includes at least one smart service;

[0017] A determination module, configured to determine a first weight coefficient and a service score corresponding to each intelligent service in the intelligent service set;

[0018] An evaluation module is used to evaluate the intelligence level of the target space according to the first weight coefficient and the service score corresponding to each intelligent service.

[0019] In some embodiments of the present application, the generating module is specifically used for:

[0020] Determining device capabilities of the smart device based on the type of the smart device in the smart device list;

[0021] Determine the sub-service corresponding to the device capability;

[0022] The intelligent service corresponding to the target space is determined according to the sub-service, and an intelligent service set corresponding to the target space is generated, wherein the intelligent service includes at least one of the sub-services.

[0023] In some embodiments of the present application, the determining module is specifically used to:

[0024] Acquire a second weight coefficient corresponding to each of the sub-services included in each of the intelligent services, where the second weight coefficient is determined based on the universality and / or complexity of the sub-service;

[0025] A service score corresponding to the intelligent service is determined according to the second weight coefficient corresponding to each of the sub-services.

[0026] In some embodiments of the present application, the determining module is specifically used to:

[0027] Acquire a space identifier of the target space, and determine a space type of the target space based on the space identifier;

[0028] A first weight coefficient corresponding to each intelligent service in the intelligent service set is obtained according to the space type, where the first weight coefficient is determined based on attributes of the intelligent service within the space type, where the attributes include general attributes, characteristic attributes and / or auxiliary attributes.

[0029] In some embodiments of the present application, the generating module is specifically used for:

[0030] Obtaining a spatial identifier of the smart device;

[0031] According to the correspondence between the subspaces and the space identifiers, obtaining a sublist of smart devices corresponding to each of the subspaces;

[0032] Generate, according to the type of smart devices in each of the smart device sub-lists, a smart service subset corresponding to each of the sub-spaces, wherein the smart service subset includes at least one smart service;

[0033] The evaluation module includes:

[0034] a calculation unit, configured to calculate a spatial intelligence score corresponding to the subspace according to a first weight coefficient and a service score corresponding to each intelligent service in the intelligent service subset;

[0035] An evaluation unit is used to evaluate the intelligence level of the target space according to the spatial intelligence score of each subspace.

[0036] In some embodiments of the present application, the evaluation unit is specifically used for:

[0037] Determining a third weight coefficient corresponding to each of the subspaces according to a space type of each of the subspaces;

[0038] The intelligent score of the target space is calculated according to the spatial intelligence score of each subspace and the third weight coefficient, and the intelligent score is used to evaluate the intelligence degree of the target space.

[0039] In some embodiments of the present application, the evaluation unit is further configured to:

[0040] According to the space type of each of the subspaces, determining all subspaces whose space type is the target type;

[0041] A type score corresponding to the target type is determined according to the spatial intelligence scores of all subspaces within the target type.

[0042] In a fourth aspect, the present application provides an intelligent degree assessment device, comprising:

[0043] A first display module is used to display an intelligent evaluation interface corresponding to the target space, wherein the intelligent evaluation interface includes evaluation function items;

[0044] The second display module is used to display the intelligence level of the target space in response to the trigger operation of the evaluation function item. The intelligence level of the target space is determined according to the first weight coefficient and service score corresponding to each intelligent service in the target space, and the intelligent service is determined based on the type of each intelligent device in the target space.

[0045] Fifth aspect:

[0046] A computer program is stored thereon, and when the computer program is executed by the processor, the computer program in the intelligent degree evaluation method of each embodiment of the present application is implemented.

[0047] Sixth aspect:

[0048] The present application provides a computer program product, including a computer program, which, when executed by a processor, implements the steps in the intelligent degree assessment method of each embodiment of the present application.

[0049] Implementing the embodiments of the present application will have the following beneficial effects:

[0050] After obtaining a list of smart devices corresponding to the target space, and generating a smart service set corresponding to the target space based on the types of smart devices in the smart device list, the smart service set includes at least one smart service, and then, determining a first weight coefficient and a service score corresponding to each smart service in the smart service set. Finally, based on the first weight coefficient and the service score corresponding to each smart service, the intelligence level of the target space is evaluated. Therefore, in a scenario where there are many types of smart devices and complex functions, a smart service set corresponding to the target space can be generated according to the list of smart devices corresponding to the target space, and based on the smart services in the smart service set, the intelligence level of the target space can be evaluated, without the user spending a lot of energy and time to evaluate the intelligence level of the smart home, thereby improving the efficiency of the intelligence level evaluation. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0052] in:

[0053] Figure 1 An application environment diagram of the intelligent degree evaluation method provided in an embodiment of the present application;

[0054] Figure 2 A flowchart of the intelligent degree evaluation method provided in the embodiment of the present application;

[0055] Figure 3 Another schematic diagram of the process of the intelligent level evaluation method provided in the embodiment of the present application;

[0056] Figure 4 Another flowchart of the intelligent degree evaluation method provided in the embodiment of the present application;

[0057] Figure 5 A schematic diagram of the structure of an intelligent level evaluation device provided in an embodiment of the present application;

[0058] Figure 6 Another structural schematic diagram of the intelligent level evaluation device provided in an embodiment of the present application;

[0059] Figure 7 An internal structure diagram of a computer device is provided for an embodiment of the present application. DETAILED DESCRIPTION

[0060] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0061] The intelligent degree evaluation method provided in this application can be applied to Figure 1 In the application environment shown in the figure, Figure 1 Provided is an intelligent level evaluation system, which includes an intelligent device 100, a gateway 200 communicatively connected to the intelligent device 100, a router 300, a server 400, and a terminal 500.

[0062] The smart device 100 accesses the gateway 200 in the intelligent degree evaluation system, and communicates with the gateway 200 through its own configured communication module, and is then controlled by the gateway 200. In one embodiment, the smart device 100 accesses the gateway 200 through a local area network path or a wide area network path, and is deployed in the gateway 200. The local area network may include ZIGBEE or Bluetooth, and the wide area network may include 2G / 3G / 4G / 5G / WIFI, etc.

[0063] The gateway 200 establishes a network connection with the terminal 500 or the server 400 through the router 300. In one embodiment, the gateway 200 and the terminal 500 may establish a network connection through a local area network or a wide area network path. The network 200 is connected to interact with the terminal 500, so that the user can control the smart home device connected to the gateway to perform corresponding actions with the help of the terminal 500 or the smart device 100.

[0064] The terminal 500 may be a smart phone, a laptop, a personal computer, a tablet computer, a smart control panel or other smart devices that can be connected to a network, which is not limited here. The server may be implemented as an independent server or a server cluster composed of multiple servers.

[0065] The present application provides a method for evaluating the degree of intelligence, including: obtaining a list of smart devices corresponding to a target space, and generating a smart service set corresponding to the target space based on the types of smart devices in the smart device list; determining a first weight coefficient and a service score corresponding to each smart service in the smart service set; and evaluating the degree of intelligence of the target space according to the first weight coefficient and the service score corresponding to each smart service.

[0066] See also Figure 2 , provides a method for evaluating the degree of intelligence, and takes the method applied to an electronic device as an example for explanation, the electronic device can be specifically Figure 1 The terminals, smart devices, gateways, servers, etc. in the system specifically include the following steps:

[0067] S101: Obtain a list of smart devices corresponding to a target space, and generate a smart service set corresponding to the target space based on the types of smart devices in the list of smart devices.

[0068] The smart service set includes at least one smart service. The smart device list refers to a list containing the names and characteristics of various smart devices. These devices can be connected through the Internet or a local area network to achieve remote control, automatic operation, or work with other devices. Smart devices can be smart bulbs, dimmer switches, scene switches, smart thermostats, or smart door locks, etc. The type of smart device is determined based on the main functions of the smart device and the services it provides. The types of smart devices may include lighting, temperature control, and air quality monitoring.

[0069] Obtaining a list of smart devices corresponding to the target space is the first step in evaluating and controlling a smart home system. The following are the general steps and considerations for obtaining a list of smart devices:

[0070] For example, you can determine the scope of the space that needs to be evaluated or controlled, such as a single room, an entire residence, or a commercial space (i.e., the target space). Collect specific information about all smart devices in the target space, including device information such as brand, model, and function. Then, identify the function and type of each device in the list of smart devices. Analyze the capabilities of each smart device. For example, a smart light bulb may have the capabilities of dimming, color adjustment, and timer switching. Next, define smart services based on device capabilities. Services can be single, such as lighting control in a single room, or combined, such as a security monitoring system for the entire home. Finally, combine the capabilities of devices with similar functions or that can work together to form a collection of smart services.

[0071] In one embodiment, the target space can be a family's living room. In the living room, the following smart devices are installed: smart bulbs (functions: dimming, color adjustment, timed switch), smart sockets (functions: remote switch, timing, power statistics), security cameras (functions: motion detection, night vision, two-way audio) and smart thermostats (functions: automatic temperature adjustment, learning user habits). Smart bulbs are lighting control type devices with dimming, color adjustment and timing functions; smart sockets are power control type devices that can remotely control the switch of connected devices; security cameras are security monitoring type devices with motion detection and night vision functions; smart thermostats are temperature control type devices that can automatically adjust the indoor temperature. The capabilities of smart bulbs include providing lighting with different brightness and color temperatures; the capabilities of smart sockets are to control the power status of connected devices; the capabilities of security cameras are to monitor the security of the living room area, provide real-time video and motion alerts; the capabilities of smart thermostats are to automatically adjust the temperature to improve energy efficiency and comfort. According to the list of smart devices in the living room, and based on the types of each smart device in the list of smart devices, the smart services corresponding to the living room are determined, including lighting control service: using smart bulbs to adjust the brightness and color temperature of the living room to create a comfortable lighting environment; power management service: using smart sockets to control electrical appliances in the living room, such as turning off devices that have not been used for a long time; security monitoring service: using security cameras to monitor the living room, providing motion alerts and real-time video access; temperature adjustment service: using smart thermostats to automatically adjust the temperature of the living room to maintain a comfortable indoor environment. The above services are combined to form a smart service collection for the living room.

[0072] The collection of smart services helps to realize more automation scenarios, such as automated lighting, temperature control and security monitoring. In addition, the collection of smart services can provide data support for subsequent evaluation of the intelligence level of the target space.

[0073] S102: Determine a first weight coefficient and a service score corresponding to each intelligent service in the intelligent service set.

[0074] The first weight coefficient is a numerical value used to indicate the relative importance or priority of the smart service in the target space. The first weight coefficient can be determined based on the frequency of use of the smart service, the user's preference for the smart service, or the attributes of the smart service in a specific space type (such as general attributes, characteristic attributes, and auxiliary attributes). General attributes refer to smart service functions that may be required in different spaces, and they are not specific to a certain space type; characteristic attributes are smart service attributes designed for a specific space type, which can meet the unique needs of the space or enhance the user experience, such as sleep services in bedrooms, cooking assistance services in kitchens, etc.; auxiliary attributes refer to those smart service attributes that play a supplementary role in intelligent scenes. Auxiliary attributes may not be the main function of a specific room or space, but they provide additional convenience and functionality for intelligent controls. For example, in a bedroom, environmental monitoring may be used as an auxiliary attribute to monitor air quality, humidity, etc. to provide a more comfortable sleeping environment.

[0075] First, identify and understand the type of target space, such as living room, bedroom, kitchen, etc., because different space types have different needs and importance for smart services. Determine all relevant smart services for the target space, such as security monitoring, lighting control, temperature adjustment, etc. Evaluate the role of smart services in the target space based on their attributes (general attributes, characteristic attributes, auxiliary attributes). For example, the first weight coefficient can be determined based on the following attributes:

[0076] Universal properties: The general applicability of the service in multiple rooms or spaces.

[0077] Distinctive Attributes: The unique value or importance of a service in a particular room or space.

[0078] Auxiliary attributes: The function of the service as a supplement to other primary services.

[0079] When there are multiple factors affecting the importance of a service, a weighted average method may be used to determine the final first weight coefficient.

[0080] This process ensures that the first weight coefficient of the intelligent service can be quantified and evaluated, which facilitates the subsequent evaluation of the degree of intelligence.

[0081] S103: Evaluate the intelligence level of the target space according to the first weight coefficient and service score corresponding to each intelligent service.

[0082] The degree of intelligence of the target space refers to the level of automation, convenience, comfort and security achieved by the smart home system in a specific space (such as home, office, etc.).

[0083] The target space can be a single space or composed of multiple subspaces. When the target space is a single space, the service score of each intelligent service can be multiplied by its first weight coefficient to obtain the weighted service score of the intelligent service, and then the weighted service scores of all intelligent services are added to obtain the spatial intelligence score of the target space. Finally, the calculated spatial intelligence score is analyzed to determine the intelligence level of the target space. The score is interpreted using a predefined scoring standard or threshold. In some embodiments of the present application, feedback can be provided to the user based on the evaluation results, pointing out the advantages of intelligence and possible improvement directions. When the target space is composed of multiple subspaces, the spatial intelligence score corresponding to each subspace can be calculated, and finally, the intelligence level of the target space can be evaluated based on the spatial intelligence score. Thus, the intelligence level of the target space can be quantified by the spatial intelligence score, providing the user with a clear intelligence level indicator, without the user spending a lot of energy and time to evaluate the intelligence level of the smart home, thereby improving the efficiency of the intelligence level evaluation.

[0084] From the above, it can be seen that the embodiment of the present application provides a method for evaluating the degree of intelligence. After obtaining a list of smart devices corresponding to the target space and generating a smart service set corresponding to the target space based on the types of smart devices in the smart device list, the smart service set includes at least one smart service. Then, the first weight coefficient and service score corresponding to each smart service in the smart service set are determined. Finally, the degree of intelligence of the target space is evaluated according to the first weight coefficient and service score corresponding to each smart service. Therefore, in a scenario where there are many types of smart devices and complex functions, a smart service set corresponding to the target space can be generated according to the list of smart devices corresponding to the target space, and the degree of intelligence of the target space can be evaluated based on the smart services in the smart service set. Users do not need to spend a lot of energy and time to evaluate the degree of intelligence of smart homes, thereby improving the efficiency of intelligence evaluation.

[0085] In some embodiments of the present application, the step of “generating a smart service set corresponding to the target space based on the type of smart device in the smart device list” may specifically include:

[0086] Determine the device capability of the smart device based on the type of the smart device in the smart device list;

[0087] Determine the sub-services corresponding to the device capabilities;

[0088] The intelligent service corresponding to the target space is determined according to the sub-service, and a set of intelligent services corresponding to the target space is generated.

[0089] Among them, a smart service can contain at least one sub-service, which is determined by the device capabilities of the smart device. Device capabilities refer to the specific functions and operating characteristics of smart devices. These capabilities enable smart devices to perform corresponding tasks, provide diverse services, and work with other smart devices to meet user needs. A sub-service is a small, specific functional unit in a smart home system that is derived from the specific capabilities of a smart device and provides actual services or operations to users. Sub-services can usually be combined with other sub-services to form a more comprehensive smart service.

[0090] For example, based on the list of smart devices, identify the type of each smart device. For example, identify the devices in the list as smart bulbs, smart sockets, smart thermostats, etc. Analyze the capabilities of each type of smart device. For example: smart bulbs: dimming, color adjustment, timer switch; smart sockets: remote control switch, timed tasks, power statistics; smart thermostats: temperature adjustment, user preference learning. Define the sub-services that can be provided based on the device capabilities. For example: dimming capability can provide "brightness adjustment" sub-service; remote control switch can provide "remote power control" sub-service; temperature adjustment capability can provide "real-time temperature control" sub-service. Integrate one or more sub-services into smart services to meet the needs of a specific space. For example: the "movie viewing mode" smart service in the living room may include "brightness adjustment" and "remote power control" sub-services. According to the target space sub-services, determine the corresponding smart services, thereby generating a smart service set for the target space. For example, for the target space of the bedroom: the smart service set includes "sleep mode" (integrating "thermostat adjustment" and "light dimming" sub-services) and "get up assistance" (integrating "curtain automatic opening" and "soft music playback" sub-services).

[0091] For example, the target space is the living room, and the list of smart devices includes smart light bulbs, smart curtains, smart thermostats, and smart TVs. Based on these devices, the following device capabilities can be determined and corresponding sub-services can be generated: the "dimming" capability of the smart light bulb corresponds to the "brightness adjustment" sub-service; the "remote control opening and closing" capability of the smart curtain corresponds to the "curtain control" sub-service; the "temperature adjustment" capability of the smart thermostat corresponds to the "temperature control" sub-service; the "content playback" capability of the smart TV corresponds to the "media playback control" sub-service. Then, these sub-services are combined into one or more smart services, such as the "movie viewing mode" smart service, including: "brightness adjustment" to create a comfortable viewing environment; "curtain control" to ensure privacy and prevent external light interference; "media playback control" to facilitate users to select and play content.

[0092] In this way, not only can customized smart services be provided for the living room, but it is also convenient for subsequent evaluation of the intelligence level of the living room and providing optimization suggestions to users.

[0093] In some embodiments of the present application, the target space includes multiple subspaces, and the step of "obtaining a list of smart devices corresponding to the target space, and generating a set of smart services corresponding to the target space based on the types of smart devices in the smart device list" may specifically include:

[0094] Get the spatial identification of the smart device;

[0095] According to the correspondence between the subspace and the space identifier, obtain the smart device sublist corresponding to each subspace;

[0096] Generate a smart service subset corresponding to each subspace according to the type of smart devices in each smart device sublist, where the smart service subset includes at least one smart service;

[0097] The first weight coefficient and service score corresponding to each intelligent service in the root intelligent service subset are used to calculate the spatial intelligence score corresponding to the subspace;

[0098] The intelligence level of the target space is evaluated based on the spatial intelligence score of each subspace.

[0099] A subspace is a specific area within the target space with independent functions and environmental requirements. The space identifier can be a simple name, number, or a more complex code to identify each subspace.

[0100] For each subspace, collect information about all smart devices in the subspace, including device type, model, function, etc. Associate each smart device with the corresponding subspace identifier to ensure that the device can be correctly mapped to the subspace where it is located. Create a smart device sublist for each subspace based on the space identifier. This list includes all smart devices belonging to the subspace. Then, analyze the functions and capabilities of each smart device to determine the types of services they can provide. Generate a subset of smart services for each subspace based on the functions of the smart devices. These services can be independent services for a single device or combined services for multiple devices working together.

[0101] For example, the target space (residence) contains three subspaces: living room (space identifier LR), bedroom (space identifier BD) and kitchen (space identifier K). Each subspace has its own unique space identifier. According to the correspondence between the subspace and the space identifier and the space identifier corresponding to the smart device, the smart devices in each subspace are listed. The specifics can be as follows:

[0102] The smart home system corresponding to the target space may be an application network topology, that is, different subspaces are covered by different network nodes or gateways. Therefore, the gateway to which the smart device is connected can determine the subspace to which the smart device belongs. In addition, it should be noted that the smart devices in the subspace are added by the user. Therefore, in some embodiments of the present application, whenever the user adds a smart device to the subspace, the smart device can be associated with the subspace, such as associating the device identifier corresponding to the smart device with the subspace identifier corresponding to the subspace. Thus, the smart devices in each subspace can be listed according to the subspace identifier.

[0103] For example, the three subspaces (living room, bedroom, kitchen) in the target space are distinguished by assigning unique space identifiers (LR, BD, K), that is, the living room corresponds to the space identifier LR, the bedroom corresponds to the space identifier BD, and the kitchen corresponds to the space identifier K. According to the subspace identifier and the association between the device identifier and the subspace identifier, the smart device sublist corresponding to the subspace is output. For example, the smart device sublist of the living room (LR) includes: smart TV, smart lighting system, smart curtain. The smart device sublist of the bedroom (BD) includes: smart thermostat, smart alarm clock, door and window sensor. The smart device sublist of the kitchen (K) includes: smart refrigerator, smoke alarm, water leakage sensor. Then, analyze the type of smart devices in each subspace and the service capabilities they can provide. For example: smart TV: provides entertainment services; smart lighting system: provides lighting control services; smart curtains: provides privacy and light control services. According to the type and capabilities of smart devices, generate a subset of smart services for each subspace. For example: the smart service subset of the living room (LR) includes: movie viewing mode (smart light dimming, smart curtain closing), leisure mode (smart light adjustment to soft state). The smart service subsets for the bedroom (BD) include: sleeping mode (smart thermostat adjusts to the appropriate temperature, door and window sensors ensure safety), waking up mode (smart alarm wakes up, curtains gradually open). The smart service subsets for the kitchen (K) include: cooking mode (smart refrigerator displays the list of ingredients, smoke alarm monitors safety), cleaning mode (water leak sensor prevents flooding).

[0104] In some embodiments of the present application, the step of “determining a first weight coefficient corresponding to each intelligent service in the intelligent service set” may specifically include:

[0105] Obtaining a space identifier of a target space, and determining a space type of the target space based on the space identifier;

[0106] A first weight coefficient corresponding to each intelligent service in the intelligent service set is obtained according to the space type.

[0107] The first weight coefficient is determined based on the attributes of the smart service within the space type, which attributes include general attributes, characteristic attributes and / or auxiliary attributes. The space type of the target space defines the main functions of the space, such as bedroom, living room, kitchen, bathroom, etc.

[0108] Identify and record the unique identifier of each room or space. This can be a room name, number, or other identifier to distinguish different spaces in the home. Based on the space identifier, clarify the main function and purpose of each space, such as bedroom, living room, kitchen, bathroom, etc. Each space type has its own specific usage scenarios and requirements. List all smart services that can be applied to the target space, such as lighting control, temperature adjustment, security monitoring, etc. For each smart service, identify its attributes within a specific space type. These attributes include:

[0109] Common properties: Services that apply to multiple space types, such as basic lighting and temperature control.

[0110] Featured properties: Services specific to certain space types, such as sleep monitoring services for bedrooms.

[0111] Auxiliary attributes: Services that support or enhance the primary service functionality, such as environmental monitoring.

[0112] Finally, a first weight coefficient is assigned to each service based on the attributes of the smart service. The first weight coefficient reflects the importance and applicability of the service in a specific space type. It is understandable that for the same smart service, the first weight coefficients corresponding to different types of spaces may be the same or different.

[0113] The service score is a quantitative indicator for evaluating the performance of intelligent services. It can integrate multiple aspects of intelligent services, including the performance of sub-services, user satisfaction, and the complexity of technical implementation. For example, a second weight coefficient can be determined for each sub-service based on the commonality and complexity of the sub-service. The second weight coefficient reflects the importance and implementation difficulty of the sub-service in the overall service. Combining the performance evaluation of the sub-service and the second weight coefficient, a sub-service score is determined for each sub-service. For all sub-services in an intelligent service, their sub-service scores are multiplied by the corresponding second weight coefficient, and then these weighted scores are added to obtain the service score of the entire intelligent service.

[0114] Through this process, the service score of the smart service can comprehensively reflect its performance and user satisfaction in a specific space type, providing a quantitative basis for the evaluation and optimization of the smart home system.

[0115] In some embodiments of the present application, the step of “determining a service score corresponding to each intelligent service in the intelligent service set” may specifically include:

[0116] Obtaining the second weight coefficient corresponding to each sub-service included in each intelligent service,

[0117] A service score corresponding to the intelligent service is determined according to the second weight coefficient corresponding to each sub-service.

[0118] The second weight coefficient is determined based on the universality and / or complexity of the sub-service; a sub-service is a functional unit in a smart service, which provides specific functions or meets specific needs of users. For example, a smart service may be composed of one or more sub-services that work together to provide a comprehensive smart home experience.

[0119] For example, all included sub-services are identified from each smart service. For example, if the smart service is "smart lighting", the sub-services may include "brightness adjustment", "color temperature adjustment", etc. The versatility of each sub-service is analyzed, that is, their application frequency and applicability in different scenarios and different smart services. At the same time, the technical complexity required to implement each sub-service is evaluated, including the complexity of the required hardware, software and algorithms. Based on the versatility and / or complexity of the sub-service, a second weight coefficient is assigned to each sub-service. This second weight coefficient reflects the importance and implementation difficulty of the sub-service in the overall smart service. Data on the performance of each sub-service is collected, such as user satisfaction, service reliability, response time, etc. Using the performance data of the sub-service, a preliminary sub-service score is determined for each sub-service. The sub-service score reflects the performance of the sub-service in actual applications. The service score of each sub-service is multiplied by its second weight coefficient to obtain a weighted service score. The weighted service scores of all sub-services are added together to obtain a comprehensive service score for the entire smart service.

[0120] In some embodiments of the present application, the step of “evaluating the intelligence level of the target space according to the first weight coefficient and the service score corresponding to each intelligent service” may specifically include:

[0121] Calculate the spatial intelligence score corresponding to the subspace according to the first weight coefficient and the service score corresponding to each intelligent service in the intelligent service subset;

[0122] The intelligence level of the target space is evaluated based on the spatial intelligence score of each subspace.

[0123] First, identify all subspaces within the target space. For example, a home may contain multiple subspaces, such as a living room, bedroom, kitchen, etc. For each subspace, multiply the service scores of all smart services in each subspace by the corresponding first weight coefficient, and then add the weighted scores to obtain the spatial intelligence score of the subspace. Finally, evaluate the intelligence level of the target space based on the spatial intelligence score corresponding to each subspace.

[0124] For example, the target space is a house, which includes three subspaces: a living room, a bedroom, and a bathroom.

[0125] For each subspace, the corresponding intelligent services are as follows:

[0126] Living room: smart lighting, smart curtains, smart temperature control.

[0127] Bedroom: smart lighting, smart mattress, smart temperature control.

[0128] Bathroom: smart toilet, water leak sensor.

[0129] The first weight coefficient is assigned to the smart services in each subspace: the weight coefficient of smart lighting in the living room is 0.2, the weight coefficient of smart curtains is 0.1, and the weight coefficient of smart temperature control is 0.3; the weight coefficient of smart lighting in the bedroom is 0.1, the weight coefficient of smart mattress is 0.3, and the weight coefficient of smart temperature control is 0.2.

[0130] Based on the performance evaluation of each smart service, the service score is calculated. For example, the performance score of smart lighting is 8 points, smart curtains is 7 points, and smart temperature control is 9 points.

[0131] Multiply the service scores of all smart services in each subspace by the corresponding first weight coefficient, and then add the weighted scores to get the smart score of the subspace. For example: living room smart score = (8*0.2) + (7*0.1) + (9*0.3) = 2.6; bedroom smart score = (8*0.1) + (7*0.3) + (9*0.2) = 3.6. Sum up the smart scores of all subspaces to get the smart score of the entire family home. It should be noted that if the bedroom and living room have a higher degree of intelligence, the bedroom and living room will contribute more to the overall score.

[0132] Therefore, the degree of intelligence of the target space can be quantified through the spatial intelligence score, providing users with a clear indicator of the intelligence level. Users do not need to spend a lot of energy and time to evaluate the intelligence level of smart homes, thereby improving the efficiency of intelligence level evaluation.

[0133] In some embodiments of the present application, the step of “evaluating the intelligence level of the target space according to the spatial intelligence scores of each subspace” may specifically include:

[0134] Determine a third weight coefficient corresponding to each subspace according to the space type of each subspace;

[0135] The intelligent score of the target space is calculated based on the spatial intelligence score of each subspace and the third weight coefficient.

[0136] Among them, the intelligence score is used to evaluate the intelligence level of the target space, and the third weight coefficient is a coefficient used to weightedly consider each subspace (such as a living room, bedroom, etc.) when evaluating the intelligence level of the entire target space (such as the entire home).

[0137] The third weight coefficient is a coefficient used to weight each subspace (such as a living room, bedroom, etc.) when evaluating the degree of intelligence of the entire target space (such as the entire family). First, determine the types of all subspaces in the target space. For example, the subspaces in a family home may include a living room, a bedroom, a kitchen, a bathroom, etc. A third weight coefficient is assigned to each subspace type. The third weight coefficient reflects the relative importance of the subspace in the overall target space intelligence or the degree of its impact on the user's quality of life. For each subspace, the intelligence score of the subspace is calculated based on the intelligent services in the intelligent service set and the first weight coefficient. The intelligence score of each subspace is multiplied by its corresponding third weight coefficient to weight the intelligence score of the subspace. All weighted subspace intelligence scores are added together to obtain a preliminary intelligence score of the target space. Based on the results of the weighted subspace score summary, the final intelligence score of the target space is calculated.

[0138] In some embodiments of the present application, the intelligent degree evaluation method of the present application may further include:

[0139] According to the space type of each subspace, all subspaces whose space type is the target type are determined;

[0140] According to the spatial intelligence scores of all subspaces within the target type, the type score corresponding to the target type is determined.

[0141] Space type refers to the classification based on the function and purpose of the room. In some embodiments of the present application, the space is divided into "core space" and "auxiliary space". The core space is the main activity area in the home, such as the bedroom, living room, dining room, etc.; the auxiliary space can be a storage room, balcony and other infrequently used areas. The target type is the space type with common characteristics or uses determined after different subspaces are classified according to specific evaluation purposes. The target type can be a core space type or an auxiliary space type, depending on the actual situation.

[0142] First, all subspaces in the home are divided into "core spaces" and "auxiliary spaces" according to the functions of the rooms. Core spaces include bedrooms, living rooms, bathrooms, dining rooms, etc., while auxiliary spaces may include storage rooms, balconies, garages, etc. When the target type is "core space", all subspaces are identified. For example, if there are 3 bedrooms, 2 living rooms, 1 bathroom, and 1 dining room in the home. For each subspace, calculate the smart score. For each type of subspace in the "core space", calculate the mean of its smart score. For example, if there are three bedrooms, and the smart scores are 8.5, 9.0, and 8.0 respectively, the mean smart score of the bedrooms is (8.5+9.0+8.0) / 3=8.5.

[0143] Therefore, the degree of intelligence of the target space can be quantified through the spatial intelligence score, providing users with a clear indicator of the intelligence level. Users do not need to spend a lot of energy and time to evaluate the intelligence level of smart homes, thereby improving the efficiency of intelligence level evaluation.

[0144] The above is the intelligent level evaluation process provided in the embodiment of the present application.

[0145] In order to further understand the intelligent level evaluation scheme of the present application, the following is an example of evaluating the intelligent level of a certain residence. Figure 3 As shown, first, (1) obtain the user's room tag and device information: list the smart devices in each room based on the correspondence between the room and the room tag and the room tag corresponding to the smart device.

[0146] (2) Extract capabilities from devices in each room: For smart devices in the user's room, the capabilities of each smart device can be extracted according to the room dimension. For example, for lighting devices, the basic lighting, brightness adjustment, and color temperature adjustment capabilities of smart devices can be extracted; for human body sensor devices, the mobile monitoring capabilities of human body sensor devices can be extracted.

[0147] (3) Generate intelligent sub-services based on the capabilities of the device: Intelligent services include a variety of service types and various sub-services, which are pre-defined by the evaluation system. The system generates intelligent services based on the capabilities of the device, and each intelligent service is composed of one or more sub-services. For example, the intelligent dimming service mainly generates intelligent services around the dimming capabilities of lights, which include basic dimming, dynamic dimming, sensor control, adaptive lighting dimming and other sub-services. When the user turns on the intelligent evaluation function on the client, the system can automatically classify the devices in the user's home into intelligent services / sub-services according to pre-defined rules.

[0148] (4) Calculate the score of each smart service based on the weight: Take the smart dimming service as an example, as shown in Table 1, basic dimming and basic switch are common services, so the score is 3; the sensor light control service is a combination of multiple capabilities, which is a more complex and commonly used combination, so the score is 5; the remaining sub-services are less commonly used services, so the score is 1. The weight coefficient is calculated by weighted average of the scores. Among them, the weight of the sub-service under smart dimming = sub-service score / the sum of the scores of all sub-services under the smart service. For example: the weight of the basic switch = 3 / (3+3+1+1+5+1) = 0.214.

[0149] Table 1

[0150] Serve Subservices Fraction Weight Intelligent dimming Basic switch 3 0.214 Intelligent dimming Basic dimming 3 0.214 Intelligent dimming Dynamic dimming 1 0.071 Intelligent dimming Lighting group control 1 0.071 Intelligent dimming Sensor control light 5 0.357 Intelligent dimming Adaptive lighting dimming 1 0.071

[0151] For example, the weight score design principle is: room smart services include special services, general services, and auxiliary services, among which the weight score corresponding to special services is 3 points, the weight score corresponding to general services is 2 points, and the weight score corresponding to auxiliary services is 1 point. For another example, taking the calculation of bedroom smart scores as an example, the bedroom type of room determines which smart services are needed (such as smart dimming, privacy shading, intelligent heating and cooling control, air purification, sleep service, environmental monitoring and energy consumption monitoring services). Different weights are given to them according to the importance and characteristics of the services. For example, the sleep service is a special service in the bedroom, so it scores 3 points; the smart dimming service is a general service commonly needed in the room, so it scores 2 points; environmental monitoring is an auxiliary service in the bedroom, so it scores 1 point. Assuming that the bedroom includes smart dimming (2 points), privacy shading (2 points), intelligent heating and cooling control (2 points), air purification (2 points), sleep service (3 points), environmental monitoring (1 point) and energy consumption monitoring (1 point), the weight coefficient of each smart service in the bedroom is calculated by the weighted average method. Then, the smart dimming weight coefficient of the bedroom = 2 / (2+2+2+2+3+1+1) = 0.15385.

[0152] (5) The smart service types are divided into whole-house attribute services and room attribute services, and the corresponding weights are assigned. The system can automatically determine the whole-house attribute services and room attribute services according to the smart service types, and assign corresponding weights. For example, service A is determined as the whole-house attribute service, and service B is determined as the room attribute service. The corresponding weight of service A is 3, and the corresponding weight of service B is 1.

[0153] (6) Calculate the room intelligence score and the whole house attribute service score based on the room label and the intelligent service score.

[0154] For example, the smart score of the bedroom type is the sum of each smart service score * weight coefficient. According to step (3), the bedroom has smart dimming (0.5 points), privacy shading (0.4 points), intelligent heating and cooling control (0.3 points), environmental monitoring (0.2 points), and bathroom personal care (0.1 points); then the smart score of the bedroom = 0.5*0.15385+0.4*0.15385+0.3*015385+0.2*0.07692+0.1*0. The whole house attribute service score is calculated based on the smart scores of each room, such as the bedroom, living room, and kitchen.

[0155] (7) Based on the room label, it is divided into core space and auxiliary space, and the average intelligence score of the same type of space is calculated. Based on the room label, it is divided into core space and auxiliary space. The core space is bedroom, living room, bathroom, dining room, and living room. The rest of the space is classified as auxiliary space. The average intelligence score of the same type of space is calculated. The intelligence score of the core-level space is calculated as follows:

[0156] Find the average value of the same spatial type

[0157] For example: Family A has 3 bedrooms (a, b, c).

[0158] Then bedroom type intelligence score = mean(a,b,c)

[0159] Calculation of auxiliary level space intelligence score: average of all auxiliary level spaces

[0160] For example: Family A has 1 study and 1 balcony, then the auxiliary level intelligence score = mean (study, balcony)

[0161] (8) The smart scores of the same room types and the whole house attribute service scores are calculated according to the weights to obtain the home smart score. The smart scores of the same room types and the whole house attribute service scores are calculated according to the weights to obtain the home smart score. For example, the weights of each room type are bedroom (1), living room (1), dining room (1), bathroom (1), kitchen (1), auxiliary space (0.5), and whole house service (2); the weighted average of the scores of bedroom, living room, dining room, bathroom, kitchen, auxiliary space, and whole house service is calculated to obtain the final home smart score.

[0162] See also Figure 4 , provides a method for evaluating the degree of intelligence, and takes the method applied to an electronic device as an example for explanation, the electronic device can be specifically Figure 1 The terminal in the embodiment specifically comprises the following steps:

[0163] S201. Display the intelligent evaluation interface corresponding to the target space.

[0164] The smart evaluation interface includes evaluation function items. The smart evaluation interface is a user interface that allows users to evaluate and understand the intelligence level of their home through a client of a smart home system (such as a smartphone application, a tablet computer, or a smart control panel). The evaluation function items are specific function points provided to users in the smart evaluation interface, allowing users to conduct detailed evaluation and analysis of the intelligence level of their home. The evaluation function items can be buttons, sliders, or controls. For example, a user can access the smart evaluation interface through a client of a smart home system (such as a smartphone application, a tablet computer, or a smart control panel).

[0165] S202: In response to a trigger operation on an evaluation function item, display the intelligence level of the target space.

[0166] Among them, the intelligence level of the target space is determined according to the first weight coefficient and service score corresponding to each intelligent service in the target space. The intelligent service is determined based on the type of each intelligent device in the target space. The intelligence level of the target space refers to the level of automation, convenience, comfort and security achieved by the intelligent home system in a specific space (such as home, office, etc.). The user can trigger the intelligence level evaluation process of the target space by clicking the evaluation function item, which is as follows: the terminal identifies all intelligent devices installed in the target space and records their types and functions. The terminal determines the service type provided by each intelligent device, such as lighting control, temperature adjustment, security monitoring and other service types, and determines the first weight coefficient of each intelligent service, and combines the second weight coefficient of the sub-service in the intelligent service to determine the service score corresponding to the intelligent service. Then, according to the first weight coefficient and service score corresponding to each intelligent service in the intelligent service set, the space intelligence score corresponding to the sub-space is calculated. Finally, according to the space intelligence score of each sub-space, the intelligence level of the target space is evaluated.

[0167] The above is the intelligent level evaluation process provided in the embodiment of the present application.

[0168] From the above, it can be seen that the embodiment of the present application provides a method for evaluating the degree of intelligence. After displaying the intelligent evaluation interface corresponding to the target space, the degree of intelligence of the target space is displayed in response to the triggering operation of the evaluation function item. In a scenario where there are many types of smart devices and complex functions, the degree of intelligence of the target space can be quickly evaluated by triggering the evaluation function item, without the user spending a lot of energy and time to evaluate the degree of intelligence of the smart home, thereby improving the efficiency of the intelligence evaluation.

[0169] See also Figure 5 , Figure 5This is a schematic diagram of the structure of the first implementation of the intelligent degree evaluation device provided in the embodiment of the present application. The intelligent degree evaluation device includes an acquisition module 301, a generation module 302, a determination module 303 and an evaluation module 304. Specifically, it can be as follows:

[0170] The acquisition module 301 is used to acquire a list of smart devices corresponding to the target space.

[0171] The generating module 302 generates a smart service set corresponding to the target space based on the types of smart devices in the smart device list, where the smart service set includes at least one smart service.

[0172] The determination module 303 is used to determine a first weight coefficient and a service score corresponding to each intelligent service in the intelligent service set.

[0173] The evaluation module 304 is used to evaluate the intelligence level of the target space according to the first weight coefficient and the service score corresponding to each intelligent service.

[0174] In some embodiments of the present application, the generation module 302 may be specifically used to:

[0175] Determine the device capability of the smart device based on the type of the smart device in the smart device list;

[0176] Determine the sub-services corresponding to the device capabilities;

[0177] The intelligent service corresponding to the target space is determined according to the sub-service, and an intelligent service set corresponding to the target space is generated, wherein the intelligent service includes at least one sub-service.

[0178] In some embodiments of the present application, the determination module 303 is specifically used to:

[0179] Acquire a second weight coefficient corresponding to each sub-service included in each intelligent service, where the second weight coefficient is determined based on the universality and / or complexity of the sub-service;

[0180] A service score corresponding to the intelligent service is determined according to the second weight coefficient corresponding to each sub-service.

[0181] In some embodiments of the present application, the determination module 303 may be specifically used to:

[0182] Obtaining a space identifier of a target space, and determining a space type of the target space based on the space identifier;

[0183] A first weight coefficient corresponding to each intelligent service in the intelligent service set is obtained according to the space type, where the first weight coefficient is determined based on attributes of the intelligent service in the space type, where the attributes include general attributes, characteristic attributes and / or auxiliary attributes.

[0184] In some embodiments of the present application, the generation module 302 may be specifically used to:

[0185] Get the spatial identification of the smart device;

[0186] According to the correspondence between the subspace and the space identifier, obtain the smart device sublist corresponding to each subspace;

[0187] According to the types of smart devices in each smart device sub-list, a smart service subset corresponding to each subspace is generated, and the smart service subset includes at least one smart service.

[0188] In some embodiments of the present application, the evaluation module 304 may specifically include:

[0189] a calculation unit, configured to calculate a spatial intelligence score corresponding to the subspace according to a first weight coefficient and a service score corresponding to each intelligent service in the intelligent service subset;

[0190] The evaluation unit is used to evaluate the intelligence level of the target space according to the spatial intelligence scores of each subspace.

[0191] In some embodiments of the present application, the evaluation unit may be specifically used for:

[0192] Determine a third weight coefficient corresponding to each subspace according to the space type of each subspace;

[0193] The intelligent score of the target space is calculated according to the spatial intelligence score of each subspace and the third weight coefficient. The intelligent score is used to evaluate the intelligence degree of the target space.

[0194] In some embodiments of the present application, the evaluation unit may also be used for:

[0195] According to the space type of each subspace, all subspaces whose space type is the target type are determined;

[0196] According to the spatial intelligence scores of all subspaces within the target type, the type score corresponding to the target type is determined.

[0197] An embodiment of the present application provides an intelligent degree evaluation device. After the acquisition module 301 acquires the list of intelligent devices corresponding to the target space, the generation module 302 generates an intelligent service set corresponding to the target space based on the types of intelligent devices in the intelligent device list, and the intelligent service set includes at least one intelligent service. Then, the determination module 303 determines the first weight coefficient and service score corresponding to each intelligent service in the intelligent service set. Finally, the evaluation module 304 evaluates the intelligence degree of the target space according to the first weight coefficient and service score corresponding to each intelligent service. Therefore, in a scenario where there are many types of intelligent devices and complex functions, an intelligent service set corresponding to the target space can be generated according to the list of intelligent devices corresponding to the target space, and the intelligence degree of the target space can be evaluated based on the intelligent services in the intelligent service set. There is no need for users to spend a lot of energy and time to evaluate the intelligence degree of smart homes, thereby improving the efficiency of intelligence degree evaluation.

[0198] See also Figure 6 , Figure 6 This is a schematic diagram of the structure of a second implementation of the intelligent level evaluation device provided in an embodiment of the present application. The intelligent level evaluation device includes a first display module 401 and a second display module 402. Specifically, it can be as follows:

[0199] The first display module 401 is used to display the intelligent evaluation interface corresponding to the target space, and the intelligent evaluation interface includes evaluation function items.

[0200] The second display module 402 is used to display the intelligence level of the target space in response to the trigger operation of the evaluation function item. The intelligence level of the target space is determined based on the first weight coefficient and service score corresponding to each intelligent service in the target space. The intelligent service is determined based on the type of each intelligent device in the target space.

[0201] The embodiment of the present application provides a method for evaluating the degree of intelligence. After the first display module 401 displays the intelligent evaluation interface corresponding to the target space, the second display module 402 responds to the triggering operation of the evaluation function item to display the degree of intelligence of the target space. In a scenario where there are many types of smart devices and complex functions, the degree of intelligence of the target space can be quickly evaluated by triggering the evaluation function item, without the user spending a lot of energy and time to evaluate the degree of intelligence of the smart home, thereby improving the efficiency of the intelligence evaluation.

[0202] In one embodiment, a computer device is provided. The computer device may be a terminal, and its internal structure diagram may be as follows: Figure 7As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with an external terminal through a network connection. When the computer program is executed by the processor, an intention recognition method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or it can be a computer device.

[0203] Those skilled in the art will understand that Figure 7 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0204] In one embodiment, a computer device is further provided, including a memory and a processor, wherein a computer program is stored in the memory, and the processor implements the steps in the above method embodiments when executing the computer program.

[0205] In one embodiment, a computer-readable storage medium is provided, storing a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0206] In one embodiment, a computer program product or computer program is provided, the computer program product or computer program includes computer instructions, the computer instructions are stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the steps in the above-mentioned method embodiments.

[0207] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and the computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0208] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0209] The above-described embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be construed as limiting the scope of the patent application. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent application shall be subject to the attached claims.

Claims

1. A method for evaluating the degree of intelligence, characterized in that: include: Acquire a list of smart devices corresponding to the target space, and generate a smart service set corresponding to the target space based on the types of smart devices in the list of smart devices, wherein the smart service set includes at least one smart service; Determine a first weight coefficient and a service score corresponding to each intelligent service in the intelligent service set; The intelligence level of the target space is evaluated according to the first weight coefficient and the service score corresponding to each intelligent service.

2. The intelligent degree evaluation method according to claim 1, characterized in that: The generating, based on the type of the smart device in the smart device list, a smart service set corresponding to the target space includes: Determining device capabilities of the smart device based on the type of the smart device in the smart device list; Determine the sub-service corresponding to the device capability; The intelligent service corresponding to the target space is determined according to the sub-service, and an intelligent service set corresponding to the target space is generated, wherein the intelligent service includes at least one of the sub-services.

3. The intelligent degree evaluation method according to claim 2, characterized in that: The determining of a service score corresponding to each intelligent service in the intelligent service set includes: Acquire a second weight coefficient corresponding to each of the sub-services included in each of the intelligent services, where the second weight coefficient is determined based on the universality and / or complexity of the sub-service; A service score corresponding to the intelligent service is determined according to the second weight coefficient corresponding to each of the sub-services.

4. The intelligent degree evaluation method according to claim 1, characterized in that: The determining of a first weight coefficient corresponding to each intelligent service in the intelligent service set includes: Acquire a space identifier of the target space, and determine a space type of the target space based on the space identifier; A first weight coefficient corresponding to each intelligent service in the intelligent service set is obtained according to the space type, where the first weight coefficient is determined based on attributes of the intelligent service within the space type, where the attributes include general attributes, characteristic attributes and / or auxiliary attributes.

5. The intelligent degree evaluation method according to any one of claims 1 to 4, characterized in that: The target space includes a plurality of subspaces, and obtaining a list of smart devices corresponding to the target space and generating a set of smart services corresponding to the target space based on the types of smart devices in the list of smart devices include: Obtaining a spatial identifier of the smart device; According to the correspondence between the subspaces and the space identifiers, obtaining a sublist of smart devices corresponding to each of the subspaces; Generate, according to the type of smart devices in each of the smart device sub-lists, a smart service subset corresponding to each of the sub-spaces, wherein the smart service subset includes at least one smart service; The step of evaluating the intelligence level of the target space according to the first weight coefficient and the service score corresponding to each intelligent service includes: Calculating a spatial intelligence score corresponding to the subspace according to a first weight coefficient and a service score corresponding to each intelligent service in the intelligent service subset; The intelligence level of the target space is evaluated according to the spatial intelligence score of each subspace.

6. The intelligent level evaluation method according to claim 5, characterized in that: The step of evaluating the intelligence level of the target space based on the spatial intelligence scores of each subspace includes: Determining a third weight coefficient corresponding to each of the subspaces according to a space type of each of the subspaces; The intelligent score of the target space is calculated according to the spatial intelligence score of each subspace and the third weight coefficient, and the intelligent score is used to evaluate the intelligence degree of the target space.

7. The intelligent level evaluation method according to claim 5, characterized in that: The method further comprises: According to the space type of each of the subspaces, determining all subspaces whose space type is the target type; A type score corresponding to the target type is determined according to the spatial intelligence scores of all subspaces within the target type.

8. A method for evaluating the degree of intelligence, characterized in that: include: Displaying an intelligent evaluation interface corresponding to the target space, wherein the intelligent evaluation interface includes evaluation function items; In response to a trigger operation for the evaluation function item, the intelligence level of the target space is displayed. The intelligence level of the target space is determined based on the first weight coefficient and service score corresponding to each intelligent service in the target space. The intelligent service is determined based on the type of each intelligent device in the target space.

9. An intelligent level evaluation device, characterized in that: include: The acquisition module is used to obtain the list of smart devices corresponding to the target space; A generating module, configured to generate a smart service set corresponding to the target space based on the type of smart devices in the smart device list, wherein the smart service set includes at least one smart service; A determination module, configured to determine a first weight coefficient and a service score corresponding to each intelligent service in the intelligent service set; An evaluation module is used to evaluate the intelligence level of the target space according to the first weight coefficient and the service score corresponding to each intelligent service.

10. An intelligent level evaluation device, characterized in that: include: A first display module is used to display an intelligent evaluation interface corresponding to the target space, wherein the intelligent evaluation interface includes evaluation function items; The second display module is used to display the intelligence level of the target space in response to the trigger operation of the evaluation function item. The intelligence level of the target space is determined according to the first weight coefficient and service score corresponding to each intelligent service in the target space, and the intelligent service is determined based on the type of each intelligent device in the target space.

11. An electronic device comprising at least one processor and at least one memory, wherein a computer program is stored in the memory, wherein: When the processor executes the computer program, the steps of the intelligence level evaluation method according to any one of claims 1 to 8 are implemented.

12. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the intelligent degree evaluation method according to any one of claims 1 to 8 are implemented.

13. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the intelligent degree evaluation method according to any one of claims 1 to 8 are implemented.

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