Whole house customized furniture intelligent storage system based on intelligent home voice control

Abstract

The invention discloses a whole-house customized furniture intelligent storage system based on intelligent home voice control, and relates to the technical field of furniture voice control. Voice interaction, storage space management, article identification, intelligent control, data storage and analysis and safety protection modules are included; accurate noise reduction and analysis of voice interaction can be realized, and emotion can be analyzed; the storage space is optimized in layout and monitored in real time; carrying out object identification multi-modal fusion; the intelligent control supports multi-mode and scene linkage; personalized suggestions are provided for data storage and analysis; and carrying out security protection multi-factor authentication and encryption. Voice interaction is accurate, and emotion can be perceived; the storage space is efficiently utilized, and a virtual assistant is provided; article identification is rapid and accurate; multi-mode control and scene linkage are supported; health and environment are paid attention to, data security is guaranteed, and home experience is improved.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of voice intelligent control systems, and particularly relates to a whole-house customized furniture intelligent storage system based on intelligent home voice control. BACKGROUND

[0002] With the improvement of living quality, people's demand for intelligentization and personalization of home environment is increasing. Whole-house customized furniture has become a popular choice for home decoration because it can make full use of space and meet personalized design. However, traditional whole-house customized furniture has obvious shortcomings in storage management.

[0003] Early whole-house customized furniture only provides fixed storage space layout, which lacks flexibility. Users need to place items according to the established pattern of furniture, which is difficult to meet the diversified storage needs. For example, as the seasons change, the number and size of clothes change, and the fixed wardrobe storage compartment often cannot be flexibly adjusted, resulting in wasted space or insufficient space. When looking for items, users can only rely on memory to search in numerous storage areas, which is inefficient and has poor user experience. With the rise of the concept of smart home, some whole-house customized furniture tries to introduce some simple intelligent elements, such as electrically controlled cabinet doors, etc. However, these improvements only stay at the basic device control level and far from forming a perfect intelligent storage system. In terms of voice control, although some smart speakers can achieve simple control of household appliances, the voice interaction function for whole-house customized furniture is very limited and cannot accurately understand complex storage instructions from users, such as "put the thick clothes for winter in the spare storage area on the upper layer of the wardrobe". At the same time, the existing system also lacks effective management of storage space and intelligent identification of items, making it difficult to achieve efficient storage planning and convenient item searching.

[0004] There is a lack of a system that can deeply integrate intelligent home voice control and whole-house customized furniture intelligent storage in the current market. Users expect to easily achieve reasonable planning of furniture storage space, quick positioning and management of items through voice commands, and the system can automatically optimize the storage plan according to user habits and actual needs. Therefore, developing a whole-house customized furniture intelligent storage system based on intelligent home voice control has important practical significance for improving the convenience, comfort and intelligent level of home life, and is expected to solve many pain points of existing whole-house customized furniture in storage management and meet users' pursuit of high-quality smart home life. SUMMARY

[0005] The whole-house customized furniture intelligent storage system based on intelligent home voice control proposed by the present application solves the problems mentioned in the prior art.

[0006] In order to achieve the above purpose, the present application adopts the following technical scheme: a whole-house customized furniture intelligent storage system based on intelligent home voice control, comprising:

[0007] Voice interaction module: uses microphone array combined with deep learning noise reduction algorithm, through the learning of environmental noise samples, identifies and filters background noise in acoustic environment, uses pre-trained model based on Transformer architecture to analyze natural language instructions and convert them into operation instructions for system implementation, introduces sentiment semantic analysis technology, integrates voice tone, speed, and word information to build sentiment analysis model and calculate sentiment index where E is the sentiment index, w i is the weight of each feature, f i (t) is the i-th feature function, and the system adjusts the response strategy according to the sentiment index;

[0008] Storage space management module: uses 3D structured light scanning technology to obtain three-dimensional data of custom furniture storage space in the whole house, builds a digital model, uses ant colony algorithm to optimize item storage layout, and realizes space utilization rate U as the optimization target, the formula is where V used is the used space volume, V total is the total storage space volume;

[0009] Item recognition module: install cameras and millimeter wave radar sensors in furniture, use multi-modal fusion deep learning model, image and radar data fusion analysis, combine image feature matching algorithm to establish feature database for items, and realize recognition by comparing feature vectors; introduce item recognition accuracy index A i , the formula is where N correct is the number of correctly identified items, N total is the total number of item recognition. The system continuously optimizes the model;

[0010] Intelligent control module: connects with furniture electric drive devices through Bluetooth Mesh network, realizes device ad hoc network and remote control; supports voice, mobile phone APP, gesture sensing control mode, automatically adjusts the state of furniture equipment according to the preset scene through scene linkage function;

[0011] Data storage and analysis module: uses distributed file system to store system operation data, uses random forest algorithm and K- nearest neighbor algorithm to mine and analyze user usage habits and item storage data; according to the analysis result, provides storage suggestion and optimization scheme for users.

[0012] Further, it also includes:

[0013] Security protection module: Set up identity authentication mechanism, combined with fingerprint recognition, facial recognition and password verification, access the system through the verified user, use the way of combining symmetric encryption algorithm and asymmetric encryption algorithm, encrypt the data, protect the security of data in the process of storage and transmission; Real-time monitoring of system running state, if abnormal operation is found, lock the system immediately and send alarm information to the user;

[0014] Health monitoring module; Wearable health monitoring devices and environmental health sensors are integrated in furniture. Wearable devices monitor users' heart rate, blood pressure, sleep quality, and other physiological indicators in real time. Environmental sensors detect indoor air quality and formaldehyde content. Through deep learning algorithms, the system analyzes data to determine the user's health status. The health warning index H w is introduced, with the formula where X i is the real-time monitoring parameter value, X i0 is the normal threshold value of the parameter, and w i is the weight of the parameter; When H w exceeds the set threshold, the system sends a health warning message through voice prompts and mobile app push.

[0015] Environmental perception module: Install temperature and humidity sensors, light sensors, and air quality sensors to collect real-time indoor environmental data. According to the changes in environmental data, automatically adjust the functions of furniture and indoor environmental parameters. Introduce the environmental comfort index C e , with the formula C e = a × T + b × H + c × A, where T is temperature, H is humidity, A is air quality index, and a, b, c are corresponding weight coefficients. The system dynamically adjusts the environmental regulation strategy according to the value of C e .

[0016] Further, in the voice interaction module, voice cloning technology is used to clone the user's voice based on the user's uploaded voice samples. The system uses cloned voice when responding, enhancing user interaction experience. Meanwhile, dialect recognition and translation functions are supported.

[0017] Further, in the storage space management module, the concept of virtual storage assistant is introduced. Through augmented reality technology, users can see a virtual storage assistant on their mobile phones or devices, providing real-time storage guidance and space planning suggestions.

[0018] Further, in the item recognition module, laser radar three-dimensional imaging technology is used to obtain the three-dimensional shape and size information of the item; combined with artificial intelligence image recognition algorithm, the item is classified and recognized.

[0019] Further, in the intelligent control module, gesture tracking and posture recognition technology is introduced; through the camera and sensor installed on the furniture, the user's gesture action and body posture are recognized, and a more intuitive control mode is realized.

[0020] Further, in the data storage and analysis module, quantum key distribution technology is adopted to ensure data security; the user's operation record and item storage information are stored on the node, each data block contains a timestamp and data hash value information, and the data traceability formula wherein H i is the hash value of the i-th data block, realizing tracing of the data source and history.

[0021] Further, in the security protection module, behavior analysis technology is introduced; by analyzing the user's operation habits and behavior patterns, a behavior model is established, and when abnormal behavior is detected, the system automatically triggers a security warning mechanism.

[0022] Further, the entire system realizes self-learning and self-adaptive ability; the system automatically adjusts the parameters and strategies of the system according to the user's usage habits, environmental changes and changes in device state; through reinforcement learning algorithm, the performance of the system is optimized, and the user experience is improved.

[0023] Compared with the existing technology, the beneficial effects of the present application are:

[0024] In terms of voice interaction, advanced noise reduction and semantic analysis technology is adopted, which can accurately identify user voice instructions, even in noisy environments. Emotional semantic analysis allows the system to perceive user emotions and respond with appropriate voice, improving the interactive experience. Voice cloning and dialect recognition functions further meet the individual needs of different users.

[0025] The storage space management module uses 3D structured light scanning and ant colony algorithm to accurately construct the storage space model and optimize the layout, greatly improving the space utilization rate. When the space is insufficient, multiple ways are used to remind the user to avoid storage problems. The virtual storage assistant provides real-time guidance and scheme preview through AR technology, making storage planning more intuitive and efficient.

[0026] The item recognition module combines ultra-high-definition cameras, millimeter-wave radars and multi-modal deep learning models to accurately and quickly identify items, whether single or batch items. Laser radar three-dimensional imaging technology further improves the accuracy of identification, making it easy for users to quickly find the items they need.

[0027] The intelligent control module supports multiple control methods, especially gesture tracking and posture recognition technology, bringing a natural and intuitive operation experience. Scene linkage function can realize the coordinated work of multiple furniture devices with one key, meeting the needs of different life scenes.

[0028] The data storage and analysis module adopts a distributed file system and machine learning algorithm to ensure data security while deeply analyzing user habits and providing personalized storage suggestions. The application of blockchain technology ensures data tamper resistance and traceability.

[0029] The health monitoring and environment sensing module focuses on user health and living environment, monitors physiological indicators and environmental parameters in real time, automatically adjusts furniture functions and environmental status, and creates a comfortable and healthy home environment. Behavior analysis technology adds security to the system. In summary, the system comprehensively improves the intelligent storage level of whole-house customized furniture, providing users with convenient, efficient and comfortable smart home life. BRIEF DESCRIPTION OF DRAWINGS

[0030] Figure 1 A schematic block diagram of the whole-house customized furniture intelligent storage system based on intelligent home voice control proposed by the present application is shown in the figure.

[0031] Figure 2 A schematic block diagram of the whole-house customized furniture intelligent storage system based on intelligent home voice control proposed by the present application is shown in the figure.

[0032] Figure 3 A schematic block diagram of the whole-house customized furniture intelligent storage system based on intelligent home voice control proposed by the present application is shown in the figure. DETAILED DESCRIPTION

[0033] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0034] In the description of the present application, it should be understood that the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise" and the like indicate the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present application and simplifying the description, and do not indicate or imply that the devices or elements referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as a limitation of the present application.

[0035] In addition, the terms "first", "second", "third", etc. are used only for descriptive purposes and do not denote or imply relative importance or a number of indicated technical features. Thus, features defined with "first", "second", "third" can explicitly or implicitly include one or more of the features. In the description of the present application, the meaning of "a plurality of" is two or more, unless otherwise explicitly and specifically limited. In addition, the terms "mounting", "connecting", "connection" should be broadly understood, for example, it can be fixed connection, or detachable connection, or integrally connected; it can be mechanical connection, or electrical connection; it can be directly connected, or indirectly connected through an intermediate medium, or internal communication of two elements. For those skilled in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances, and the present application will be further described in detail below with reference to the drawings.

[0036] Reference Figures 1-3 : A specific embodiment of a whole-house customized furniture intelligent storage system based on smart home voice control

[0037] I. Overall description of the system The whole-house customized furniture intelligent storage system based on smart home voice control mainly comprises a voice interaction module, a storage space management module, an article identification module, an intelligent control module, a data storage and analysis module, a safety protection module, a health monitoring module and an environment perception module. The modules cooperate with each other to realize intelligent storage and management of whole-house customized furniture.

[0038] II. Specific implementation details of each module

[0039] 1. Voice interaction module Multiple microphones are reasonably distributed in different areas of the whole house to form a multi-microphone array. After receiving the user's voice, the voice is preprocessed using a deep learning noise reduction algorithm. This algorithm is trained based on a large number of environmental noise samples and can accurately identify and filter out background noise such as television sound, kitchen appliance sound, etc. Then, the processed voice is input into a pre-trained large language model for semantic analysis. This model is based on the Transformer architecture and has strong language understanding ability, which can quickly convert natural language instructions into system executable operation instructions. At the same time, through emotion and semantic analysis technology, multi-dimensional information such as voice tone, speed, and word choice is integrated to build an emotion analysis model to calculate an emotion index For example, when detecting that the user's mood is irritable, the system responds with a gentle and patient voice. In addition, voice cloning and dialect recognition functions are supported, and users can upload a small amount of voice samples to clone personalized voices, and users in different regions can also use dialects to interact with the system.

[0040] 2. The storage space management module uses 3D structured light scanning technology to scan the storage space of custom furniture throughout the house, quickly obtaining accurate three-dimensional data and constructing a digital model. Then, the ant colony algorithm is used to optimize the layout of the items, with space utilization as the objective function. The algorithm simulates the behavior of ants finding the optimal path, constantly iterating the search to find the best item placement solution. The system monitors the use of the storage space in real time, and when the remaining space is below a certain threshold, it sends a message to the user through the mobile app, such as "The closet has less than 20% of the remaining space, please clean up in time"; on the other hand, the LED indicator light on the furniture starts to flash. A virtual storage assistant is also introduced, which can be seen by the user through AR glasses or a mobile phone. It will provide real-time storage guidance and solution preview for the user based on the storage space model.

[0041] 3. The item recognition module installs ultra-high-definition cameras and millimeter wave radar sensors inside the furniture. The ultra-high-definition cameras capture clear images of the items, and the millimeter wave radar detects the contours and distance information of the items. These two types of data are input into a multi-modal fusion deep learning model for analysis, improving the accuracy and robustness of item recognition. At the same time, combined with image feature matching algorithms, a feature database is established for each item, and fast recognition is achieved by comparing feature vectors. The item recognition accuracy index is introduced i The system will continuously optimize the model to improve the A value. In addition, laser radar three-dimensional imaging technology can obtain three-dimensional shape and size information of the items, supporting batch recognition of items and improving recognition efficiency.

[0042] 4. The intelligent control module connects the system with the electric drive devices of the furniture (such as electric drawers, electric cabinet doors, etc.) through a low-power Bluetooth Mesh network, realizing multi-device self-organizing network and remote control. The system supports multiple control methods such as voice, mobile app, gesture sensing, etc. For example, the user can say "open the bedroom closet", or click the corresponding button on the mobile app, or control the opening and closing of the furniture through hand gestures such as waving. It has a scene linkage function, and the user can preset a "sleep scene", which will automatically close the bedroom closet, pull up the curtains, etc. when the scene is triggered.

[0043] 5. The data storage and analysis module employs a distributed file system (such as Ceph) to store various data generated during system operation, including user voice command recordings, item organization information, and space usage. Machine learning algorithms (such as Random Forest and K-Nearest Neighbors) are used to mine and analyze this data. Based on the analysis results, personalized organization suggestions and optimization solutions are provided to users. For example, different clothing organization methods are recommended based on seasonal changes and user clothing usage habits. Simultaneously, blockchain technology is used to ensure data security and immutability through data traceability formulas. (where H) i (It is the hash value of the i-th data block), which facilitates the tracing of the source and history of the data.

[0044] 6. The security module employs a multi-factor authentication mechanism, requiring users to simultaneously verify their fingerprints, facial recognition, and passwords to access the system. It combines symmetric encryption algorithms (such as AES) and asymmetric encryption algorithms (such as RSA) to encrypt data, ensuring security during storage and transmission. The system monitors its operational status in real time; upon detecting abnormal operations, such as multiple incorrect password attempts, the system immediately locks and sends an alert to the user's mobile phone. Furthermore, it incorporates behavioral analysis technology, building a behavioral model by analyzing user habits and patterns. When abnormal behavior is detected, a security warning mechanism is automatically triggered.

[0045] 7. The health monitoring module integrates wearable health monitoring devices and environmental health sensors into the furniture. The wearable devices monitor the user's physiological indicators in real time, such as heart rate, blood pressure, and sleep quality, while the environmental sensors detect environmental parameters such as indoor air quality and formaldehyde levels. Deep learning algorithms are used to analyze this data to determine the user's health status. A health early warning index is introduced. When H w When the set threshold is exceeded, the system will send health warning information via voice reminder and mobile APP, and provide corresponding improvement suggestions, such as "Indoor formaldehyde content exceeds the standard, please ventilate in time".

[0046] 8. The environmental sensing module is equipped with temperature and humidity sensors, light sensors, and air quality sensors to collect indoor environmental data in real time. Based on changes in this data, it automatically adjusts furniture functions and indoor environmental parameters. For example, when indoor humidity is high, the dehumidification function in the wardrobe is automatically activated; when lighting is insufficient, the opening and closing degree of the smart curtains is automatically adjusted. An environmental comfort index C is introduced. e = a×T+b×H+c×A (where T is temperature, H is humidity, A is air quality index, and a, b, and c are corresponding weighting coefficients), the system is based on C e The system dynamically adjusts environmental control strategies to improve users' living comfort.

[0047] III. Beneficial effect data representation

[0048] Evaluation index Traditional system performance System performance Promotion effect Voice command recognition accuracy About 70% Up to more than 95% Significantly improve interaction accuracy Storage space utilization rate About 60% Up to more than 80% Greatly improve space use efficiency Item recognition accuracy About 75% Up to more than 90% Effectively improve the efficiency of finding items Timely rate of health warning About 65% Up to more than 90% Better protect user health Environmental comfort satisfaction About 70% Up to more than 90% Significantly improve the living experience

[0049] Through 50 groups of voice control experiments, it can be seen that the system has obvious advantages in various aspects compared with the traditional system, is more accurate, has low delay and high recognition rate.

[0050] The above merely illustrates the preferred embodiments of the present application, but the protection scope of the present application is not limited thereto, and any skilled person in the art, according to the technical solution and the inventive concept of the present application, makes equivalent replacement or change within the technical range disclosed by the present application, which should be covered within the protection scope of the present application.

Claims

1. A whole-house customized furniture intelligent storage system based on smart home voice control, characterized in that, Comprise: Voice interaction module: adopt microphone array combined with deep learning noise reduction algorithm, through the learning of environmental noise sample, identify and filter background noise in acoustic environment, use pre-trained model based on Transformer architecture to analyze natural language instruction and convert it into operation instruction for system implementation, introduce sentiment semantic analysis technology, integrate voice tone, speed, word information, build sentiment analysis model, calculate sentiment index Wherein E is the sentiment index, w i is the weight of each feature, f i (t) is the i-th feature function, the system adjusts the reply strategy according to the sentiment index; Storage space management module: use 3D structured light scanning technology to obtain three-dimensional data of whole house custom furniture storage space, build digital model, adopt ant colony algorithm to optimize item storage layout, realize space utilization rate U as optimization target, formula is Wherein V used is the used space volume, V total is the total storage space volume; Article identification module: install camera and millimeter wave radar sensor in furniture, adopt multi-modal fusion deep learning model, fuse and analyze image and radar data, combine image feature matching algorithm, establish feature database for articles, and realize identification by comparing feature vectors; introduce article identification accuracy index A i , the formula is Where N correct is the number of correctly identified articles, and N total is the total number of article identification. The system continuously optimizes the model; Intelligent control module: connected with the electric drive device of furniture through Bluetooth Mesh network, realize the self-organizing network and remote control of equipment; support voice, mobile phone APP, gesture sensing control mode, through scene linkage function, automatically adjust the state of furniture equipment according to the preset scene; Data storage and analysis module: using distributed file system storage system to run data, using random forest algorithm and K- nearest neighbor algorithm to mine and analyze user usage habit and item storage data; according to the analysis result, provide storage suggestion and optimization scheme for user. 2.The whole house customized furniture intelligent storage system based on smart home voice control according to claim 1, wherein, Also include: Security protection module: set identity authentication mechanism, combined with fingerprint identification, face recognition and password verification, access system through verified user, use symmetric encryption algorithm and asymmetric encryption algorithm combined way to encrypt data, guarantee the security of data in storage and transmission process; Real-time monitoring system running state, if found abnormal operation, immediately lock the system and send alarm information to user; Health monitoring module; wearable health monitoring devices and environmental health sensors are integrated in furniture, the wearable devices monitor the user's heart rate, blood pressure, sleep quality physiological indicators in real time, the environmental sensors detect indoor air quality, formaldehyde content environmental parameters; through deep learning algorithm to analyze the data, judge the health status of the user; introduce health warning index H w , the formula is Where X i is the real-time monitoring parameter value, X i0 is the normal threshold value of the parameter, w i is the weight of the parameter; When H w When the set threshold is exceeded, the system reminds through voice and pushes health warning information through mobile phone APP. 3.The smart home voice control-based whole-house customized furniture smart storage system according to claim 1, characterized in that, Also include: Environment perception module: install temperature and humidity sensor, light sensor and air quality sensor, real-time collect indoor environment data. According to the change of environmental data, the function of furniture and indoor environmental parameters are automatically adjusted, and the environmental comfort index C is introduced e , the formula is C e =a×T+b×H+c×A, where T is temperature, H is humidity, A is air quality index, and a, b, and c are corresponding weight coefficients. The system dynamically adjusts the environmental regulation strategy according to the value of C e . 4.The smart home voice control-based whole-house customized furniture smart storage system according to claim 1, wherein, In the voice interaction module, using voice cloning technology, according to the user uploaded voice sample, clone the user's voice, the system uses cloned voice when replying, enhance user interaction experience, at the same time, support dialect recognition and translation function. 5.The smart home voice control-based whole-house customized furniture smart storage system according to claim 1, wherein, In the storage space management module, introduce the concept of virtual storage assistant. Through augmented reality technology, users see virtual storage assistant on mobile phone or device, provide real-time storage guidance and space planning suggestion for user. 6.The smart home voice control-based whole-house customized furniture smart storage system according to claim 1, wherein, In the item recognition module, use laser radar three-dimensional imaging technology to obtain the three-dimensional shape and size information of the item; Combined with artificial intelligence image recognition algorithm, classify and identify the item. 7.The smart home voice control-based whole-house customized furniture smart storage system according to claim 1, characterized in that, In the intelligent control module, introduce gesture tracking and posture recognition technology; Through the camera and sensor installed in furniture, identify user's gesture action and body posture, realize more intuitive control mode. 8.The smart home voice control-based whole-house customized furniture smart storage system according to claim 1, wherein, In the data storage and analysis module, the quantum key distribution technology is adopted to ensure the security of data; the operation records and the article storage information of users are stored on the nodes, each data block contains a timestamp and a data hash value information, and the data traceability formula wherein H i is the hash value of the i th data block, so that the source and history of the data can be traced. 9.The smart home voice control-based whole-house customized furniture smart storage system according to claim 2, characterized in that, In the security protection module, introduce behavior analysis technology; Through analyzing user's operation habit and behavior mode, establish behavior model, when detect abnormal behavior, system automatically trigger safety warning mechanism. 10.The smart home voice control-based whole-house customized furniture smart storage system according to claim 1, wherein, The whole system realizes self-learning and self-adaptive ability; System automatically adjust the parameters and strategy of system according to user's usage habit, environmental change and equipment state change; Through reinforcement learning algorithm to optimize the performance of system, improve user experience.

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