CN115439958A - Remote control system and method for intelligent door lock - Google Patents
Remote control system and method for intelligent door lock Download PDFInfo
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- G07C9/00—Individual registration on entry or exit
- G07C9/00174—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys
- G07C9/00571—Electronically operated locks; Circuits therefor; Nonmechanical keys therefor, e.g. passive or active electrical keys or other data carriers without mechanical keys operated by interacting with a central unit
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- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
- G10L15/18—Speech classification or search using natural language modelling
- G10L15/1822—Parsing for meaning understanding
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- G10L15/00—Speech recognition
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
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- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
- G10L2015/223—Execution procedure of a spoken command
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Abstract
The invention discloses a remote control system of an intelligent door lock and a remote control method of the intelligent door lock, wherein the remote control system comprises: the signal acquisition terminal is configured for acquiring voice data of a user at a far end; the data processing end is configured for carrying out voice recognition and semantic analysis on the collected voice data so as to obtain a corresponding control instruction; and the intelligent door lock end is configured to control the state of the intelligent door lock according to the acquired control instruction.
Description
Technical Field
The invention relates to the technical field of control of intelligent door locks, in particular to a remote control system and a remote control method of an intelligent door lock.
Background
With the development of the technology of the internet of things, the development trend of connecting various physical objects to the internet is represented. The system can be interconnected from common household articles such as refrigerators and bulbs, to commercial assets such as transportation labels and medical equipment, to unprecedented wearable equipment and intelligent equipment, and even to smart cities and everything existing only due to the Internet of things.
More and more intelligent devices are interconnected and intercommunicated, including intelligent door locks. The intelligent door lock is different from a traditional mechanical lock, and is more intelligent and simpler in user safety, identification and manageability. In the current market, the keys of non-contact intelligent door locks comprise magnetic cards, radio frequency cards and the like, and the keys are high in safety, convenient to configure and carry and low in price. In addition, the non-mechanical type can be used as the mature technology of user identity identification such as fingerprint lock, iris identification entrance guard and the like, the unlocking technology belongs to the biological identification type, the safety is high, loss damage does not exist, but the configuration is inconvenient and the cost is high.
In the prior art, the power supply mode of the popular intelligent door lock in the market mainly takes a battery or an external power supply as a main mode, and the unlocking method mainly takes fingerprint unlocking, card swiping unlocking or code scanning unlocking as a main mode. For the intelligent door lock in the prior art, if the intelligent door lock is required to be intelligently interconnected with other intelligent equipment, higher requirements are placed on miniaturization, intellectualization, networking and diversification of power supply modes of the intelligent door lock.
In order to further expand the application range of the intelligent door lock, the invention provides a door lock remote control technology combining a semantic analysis function, which can enable a user to remotely control the state of the door lock through a voice instruction, thereby facilitating the control of the user on the state of the door lock and improving the user experience.
Disclosure of Invention
The following presents a simplified summary of one or more aspects in order to provide a basic understanding of such aspects. This summary is not an extensive overview of all contemplated aspects, and is intended to neither identify key or critical elements of all aspects nor delineate the scope of any or all aspects. Its sole purpose is to present some concepts of one or more aspects in a simplified form as a prelude to the more detailed description that is presented later.
In order to further expand the application range of the intelligent door lock, the first aspect of the invention provides a remote control system of the intelligent door lock. This remote control system of intelligence lock includes: the signal acquisition terminal is configured for acquiring voice data of a user at a far end; the data processing terminal is configured for carrying out voice recognition and semantic analysis on the collected voice data so as to obtain a corresponding control instruction; and the intelligent door lock end is configured to control the state of the intelligent door lock according to the acquired control instruction. This remote control system of intelligence lock can let the user pass through the state of voice command remote control lock to be convenient for the user and control the lock state, and promote user experience.
In order to further expand the application range of the intelligent door lock, the second aspect of the invention provides a remote control method of the intelligent door lock. The remote control method of the intelligent door lock is to utilize the remote control system of the intelligent door lock provided by the first aspect of the invention to control the state of the intelligent door lock. Therefore, by using the remote control system, the remote control method can also enable the user to remotely control the state of the door lock through the voice instruction, so that the user can conveniently control the state of the door lock, and the user experience is improved.
To further expand the scope of applications of intelligent door locks, a third aspect of the present invention provides a computer-readable storage medium having computer instructions stored thereon. When being executed by a processor, the computer instructions implement the method configured by the signal acquisition end, the data processing end and/or the intelligent door lock end in the remote control system of the intelligent door lock. Therefore, by implementing the remote control method, the computer-readable storage medium can also enable the user to remotely control the state of the door lock through the voice instruction, so that the user can conveniently control the state of the door lock, and the user experience is improved.
In summary, the present invention provides a remote control system and a remote control method for an intelligent door lock, and a computer readable storage medium storing the remote control method. According to the intelligent door lock, the signal acquisition end, the data processing end and the intelligent door lock end form a remote control system of the intelligent door lock together, so that the intelligent door lock can be remotely controlled, and the intelligent door lock can be intercommunicated and interconnected with other intelligent equipment.
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The above features and advantages of the present disclosure will be better understood upon reading the detailed description of embodiments of the disclosure in conjunction with the following drawings. In the drawings, components are not necessarily drawn to scale, and components having similar associated characteristics or features may have the same or similar reference numerals.
FIG. 1 illustrates an interaction flow diagram for a remote control system for an intelligent door lock provided in accordance with some embodiments of the present invention;
FIG. 2 illustrates a system framework diagram of a remote control system for an intelligent door lock provided in accordance with some embodiments of the present invention; and
fig. 3 shows a schematic diagram of a control device of a remote control system of an intelligent door lock provided according to some embodiments of the invention.
Detailed Description
The following description of the embodiments of the present invention is provided for illustrative purposes, and other advantages and effects of the present invention will become apparent to those skilled in the art from the present disclosure. While the invention will be described in connection with the preferred embodiments, there is no intent to limit the features of the invention to those embodiments. On the contrary, the invention is described in connection with the embodiments for the purpose of covering alternatives or modifications that may be extended based on the claims of the present invention. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. The invention may be practiced without these particulars. Moreover, some of the specific details have been left out of the description in order to avoid obscuring or obscuring the focus of the present invention.
In the description of the present invention, it should be noted that, unless otherwise explicitly specified or limited, the terms "mounted," "connected," and "connected" are to be construed broadly, e.g., as meaning either a fixed connection, a removable connection, or an integral connection; can be mechanically or electrically connected; they may be connected directly or indirectly through intervening media, or they may be interconnected between two elements. The specific meanings of the above terms in the present invention can be understood in a specific case to those of ordinary skill in the art.
Also, the terms "upper," "lower," "left," "right," "top," "bottom," "horizontal," "vertical" and the like used in the following description shall be understood to refer to the orientation as it is drawn in this section and the associated drawings. The relative terms are used for convenience of description only and do not imply that the described apparatus should be constructed or operated in a particular orientation and therefore should not be construed as limiting the invention.
It will be understood that, although the terms first, second, third, etc. may be used herein to describe various elements, regions, layers and/or sections, these elements, regions, layers and/or sections should not be limited by these terms, but rather are used to distinguish one element, region, layer and/or section from another element, region, layer and/or section. Thus, a first component, region, layer or section discussed below could be termed a second component, region, layer or section without departing from some embodiments of the present invention.
Referring to fig. 1, fig. 1 illustrates an interaction flow diagram of a remote control system of an intelligent door lock provided according to some embodiments of the present invention. As shown in fig. 1, in this embodiment, an intelligent door lock is applied to a car machine system, so as to implement intercommunication and interconnection between the intelligent door lock and the car machine.
The intelligent door lock is an improved lock which is different from the traditional mechanical lock and is more intelligent and simpler in the aspects of user safety, identification and manageability. The intelligent door lock is an execution component for locking a door in an access control system. The intelligent door lock is different from a traditional mechanical lock, and is a composite lockset with safety, convenience and advanced technology.
The technical requirements of the intelligent door lock are mainly divided into three parts, namely a mechanical structure, identification control and communication service. The mechanical structure technical part of the intelligent door lock mainly comprises a lock core, a panel and a lock body. The identification control technology part of the intelligent door lock mainly comprises biological information, an intelligent terminal, a password and the like. The technology has high relevance to human-computer interaction, and more technologies are used, such as fingerprint recognition, face recognition and the like. The communication service technology part mainly comprises a chip, software, a cloud and communication modes (WI-FI, bluetooth, 433, zigBee, NB-IoT, lora and the like). The technology determines the reliability and stability of the intelligent door lock on the 'intelligent' two-character, and is the embodiment of the software value of the intelligent door lock.
The remote control system of the intelligent door lock in the embodiment mainly comprises a signal acquisition end, a data processing end and an intelligent door lock end. Corresponding to fig. 1, the signal acquisition end in this embodiment may be disposed in the vehicle system, and the data processing end may be applied to the cloud control system.
As shown in fig. 1, a signal acquisition end applied in a car-mounted device system is mainly used for acquiring voice data of a user at a far end. In the car machine system, the signal acquisition end acquires a plurality of recording analog signals of a user by using the microphone module, respectively converts the plurality of recording analog signals into corresponding voice digital signals, and then sends each voice digital signal to the data processing end.
The digital signal is formed by sampling, quantizing and encoding on the basis of the analog signal. Specifically, sampling is to obtain sample values of each time point from an input analog signal at appropriate time intervals; the quantization is to represent the values of each time moment measured by sampling by a binary code system; the encoding is to arrange the binary numbers generated by quantization together to form a sequential pulse sequence. The analog signal is generally quantized into a digital signal by a PCM (Pulse Code Modulation) method, that is, different amplitudes of the analog signal correspond to different binary values respectively.
After the recording analog signal is converted into a voice digital signal, the confidentiality of communication is enhanced. After A/D conversion, the voice signal can be encrypted and then transmitted, and then be restored into analog signal through D/A conversion after being decrypted at the receiving end. After the recording analog signal is converted into a voice digital signal, the anti-interference capability of the signal is improved. Transmission errors during analog-to-digital conversion can be controlled, thereby improving the transmission quality of signals.
In the present embodiment, for example, when the user is located in the car, the user initiates a voice saying "unlock door lock", where "open", "door", and "lock" are four recorded analog signals, respectively. The microphone module in the vehicle collects the four recording analog signals and converts the four recording analog signals into corresponding voice digital signals. And then the information acquisition end positioned in the vehicle machine system sends the four voice digital signals to the data processing end one by one.
Referring to fig. 1, a data processing end of the remote control system of the intelligent door lock is disposed in the cloud control system, and is mainly used for performing voice recognition and semantic analysis on the collected voice data to obtain a corresponding control instruction.
As shown in fig. 1, in this embodiment, a data processing end in the cloud control system acquires voice digital signals transmitted from an information acquisition end, synthesizes the voice digital signals into voice stream data according to a time sequence, and then inputs the voice stream data into a voice recognition system to acquire corresponding text information. And analyzing the acquired character information by using a pre-trained semantic processing model so as to obtain a corresponding control instruction. And if the control instruction comprises slot position information indicating unlocking operation or locking operation, the data processing end sends a corresponding control instruction to the intelligent door lock end.
In a speech recognition system at a data processing side, speech stream data is arranged and synthesized in accordance with a time sequence of a plurality of received speech digital signals. For example, in a speech recognition system, four speech digital signals of "open", "door" and "lock" transmitted from an information acquisition end are received in sequence, and speech stream data of "open door lock" is synthesized according to the sequence of the receiving time.
And then extracting the voiceprint characteristics of the synthesized voice stream data. Voiceprint (Voiceprint) is a sound wave spectrum which is displayed by an electroacoustic instrument and carries speech information, is a biological feature which is composed of hundreds of feature dimensions such as wavelength, frequency and intensity, and has the characteristics of stability, measurability, uniqueness and the like. The purpose of extracting the voiceprint feature in this embodiment is to acquire the identity information of the person who unlocks the lock so that the subsequent user can inquire the use condition of the unlocking record, and to verify the authority of the person who unlocks the lock at present according to the voiceprint feature.
And carrying out voiceprint recognition on the extracted voiceprint characteristics of the voice stream data according to the voiceprint characteristics of the authorized user of the intelligent door lock. Voiceprint recognition, a type of biometric identification technology, also known as speaker recognition, includes speaker identification and speaker verification. Voiceprint recognition is the conversion of acoustic signals into electrical signals, which are then recognized by a computer. Voiceprint recognition mainly involves two key aspects, namely feature extraction and pattern matching.
The task of feature extraction is to extract and select acoustic or language features with characteristics of strong separability, high stability and the like for the voiceprint of a speaker. Unlike speech recognition, the features of voiceprint recognition must be "personalized" features, while the features of speaker recognition must be "generic" to the speaker. Although most voiceprint recognition systems use acoustic level features, the features that characterize a person should be multi-level. From the standpoint of modeling by mathematical methods, the features that can be used by the voiceprint automatic recognition model include: (1) acoustic features (cepstrum); (2) Lexical features (speaker dependent word n-grams, phoneme n-grams); (3) Prosodic features (pitch and energy "poses" described by n-grams); (4) language, dialect and accent information; (5) channel information (what channel to use); and so on.
For pattern recognition, there are several broad categories of methods:
(1) The template matching method comprises the following steps: training and testing feature sequences are aligned using Dynamic Time Warping (DTW), mainly for fixed phrase applications (usually text-related tasks);
(2) The nearest neighbor method comprises the following steps: all the feature vectors are reserved during training, the nearest K training vectors are found for each vector during identification, and identification is carried out according to the K training vectors, so that the model storage and the similar calculation are large in quantity;
(3) The neural network method comprises the following steps: there are many forms, such as multilayer perception, radial Basis Function (RBF), etc., can train explicitly to distinguish the speaker from its background speaker, its training amount is very large, and the model is not very generalizable;
(4) Hidden Markov Model (HMM) method: usually, a single-state HMM or a Gaussian Mixture Model (GMM) is used, which is a common method and has better effect;
(5) VQ clustering method (as LBG): the effect is good, the algorithm complexity is not high, and better effect can be achieved by matching with an HMM method;
(6) Polynomial classifier method: the accuracy is higher, but the model storage and calculation amount are larger; and the like.
After the voiceprint recognition is finished, if the extracted voiceprint features of the voice stream data accord with the recognition result of the voiceprint features of the authorized user, the voice stream data are continuously processed in the voice recognition system to obtain corresponding character information. However, if the extracted voice stream data voiceprint features do not conform to the recognition result of the voiceprint features of the authorized user, returning to the information acquisition end, and re-acquiring the voice digital signal.
In this embodiment, after the extracted voice stream data voiceprint features conform to the recognition result of the voiceprint features of the authorized user, the voice stream data is converted into corresponding text information in the voice recognition system, and then the text information is converted into a word-art text and sent to the semantic processing system for semantic processing. The semantic processing system is mainly responsible for analyzing the received dialect words.
In particular, the text message may be a spoken text message spoken by the user in a whisper, such as "please help me open the door lock". The dialect words refer to words which are extracted by the voice recognition system, conform to a specific structure and contain key information, such as 'unlocking a door'. The purpose of converting the text information into the dialect text is to analyze the control instruction contained in the received text information more quickly and accurately when a subsequent semantic processing system analyzes the received text information.
When the semantic processing system analyzes the dialect, firstly, a corresponding semantic expression vector is determined according to the dialect, and the semantic expression vector is multidimensional data T { T1, T2, \8230;, tn }.
In similar environments different things produce similar characteristics, a phenomenon known as distribution assumptions. In languages where different words in the same context have similar meanings, semantic representation vectors are the instantiations of the distribution hypotheses, i.e. the conversion of symbolic representations of text into vector representations in the semantic space. And learning the semantic representation of the word in an unsupervised mode according to the context of the word.
The semantic representation vector combines two directions:
1. distribution: defining a word by observing other words in the context;
2. vector quantity: a word is defined as a vector represented by a string of numbers, i.e. a point in N-dimensional space.
A vector representing a word is a word embedding, which may be specifically interpreted as embedding the word into a particular vector space. The method has the advantages that learning is carried out in an unsupervised mode, word similarity and phrase similarity are found, and classification is carried out. Common models for word vectors are: cosine similarity, calculating the similarity of two words, sentences and short texts by using vectors; the TF-IDF model changes the words into sparse vectors; and Word2Vec, constructing a dense short vector with semantic properties.
In this embodiment, after obtaining the corresponding semantic expression vector, a first semantic matching degree between the semantic expression vector and a first expression vector indicating an unlocking operation is calculated, and a second semantic matching degree between the semantic expression vector and a second expression vector indicating a locking operation is calculated.
In this embodiment, a word vector model of cosine similarity is used to obtain a first semantic matching degree and a second semantic matching degree. The cosine similarity is used for defining the similarity between two target words v and w, and a measurable quantity is needed for obtaining the vectors of the two words and simultaneously returning the similarity of the vectors. Cosine similarity is the most commonly used method for measuring similarity at present, and the cosine of an included angle between vectors is measured.
In some embodiments, the semantic Processing system includes a Natural Language Processing (NLP) module. The majority of the metric methods of the present invention using vector similarity in the NLP module are based on dot product (or inner product). The dot product can be used as a measure of similarity because the dot product results are large if both vectors have a large value in the same dimension. If the vectors are orthogonal, the dot product is 0. The dot product may represent a strong dissimilarity between the vectors. The formula is as follows:
in this embodiment, the semantic processing system calculates a cosine included angle between the semantic expression vector and the first expression vector to obtain a first semantic matching degree. And if the first semantic matching degree is greater than or equal to a preset first matching degree threshold value, judging that the obtained control instruction comprises slot position information indicating unlocking operation. Otherwise, if the first semantic matching degree is smaller than the first matching degree threshold, it is determined that the slot position information indicating the unlocking operation is not included in the control instruction.
In addition, the semantic processing system also calculates a cosine included angle between the semantic expression vector and the second expression vector to obtain a second semantic matching degree. And if the second semantic matching degree is greater than or equal to a preset second matching degree threshold value, judging that the obtained control instruction comprises slot position information indicating the locking operation. Otherwise, if the second semantic matching degree is smaller than the second matching degree threshold, it is determined that the slot information indicating the locking operation is not included in the control instruction.
Further, if the first semantic matching degree is smaller than the first matching degree threshold value and the second semantic matching degree is smaller than the second matching degree threshold value, the semantic processing system determines that the control instruction does not include slot position information indicating the unlocking operation or slot position information indicating the locking operation, so that the step of sending the control instruction to the intelligent door lock end is skipped, and the step of obtaining the voice digital signal is returned.
In this embodiment, the slot information is a mark of key information used to accurately express an intention in a sentence in which the user expresses the intention. A slot is a variable that can help a machine understand human intent from a semantic perspective. Each slot is associated with one or more entity libraries. The semantic processing system can provide the functions and services of remotely controlling the intelligent door lock for the user in a voice interaction mode by utilizing the intelligent door lock management skills (kills) configured in the semantic processing system.
In particular, the management skill (kill) of the intelligent door lock can configure a dialogue model for the user to remotely control the intelligent door lock. The dialogue model further relates to a plurality of slots of characters, time, places, behaviors, objects and the like required in the remote control service of the intelligent door lock. The management skill of the intelligent door lock can extract corresponding text contents from the dialect characters provided by the user according to the preset slot positions to serve as slot position information of the corresponding slot positions.
For example, for the part of the lingering text information of "please help me to open the door lock", the management skill of the intelligent door lock can extract the slot information of "open" according to the slot of the behavior, and the corresponding identifier is "action". In addition, the management skill of the intelligent door lock can also extract the slot position information of the door lock according to the slot position of the object, and the corresponding mark of the slot position information is 'object'. Therefore, the management skills of the intelligent door lock can combine the extracted slot position information into a language and skill character which accords with a specific structure, namely, the intelligent door lock is opened, and therefore the cloud control system is helped to understand the real intention of the user from the semantic perspective.
With reference to fig. 1, after the data processing end of the cloud control system analyzes the spoken text to obtain slot position information therein, and obtains a corresponding control instruction, the control instruction is sent to the smart door lock end. If the analyzed slot position information indicates unlocking operation, the intelligent door lock end executes the unlocking control instruction, and the state of the intelligent door lock is adjusted to be an unlocking state; and if the analyzed slot position information indicates locking operation, the intelligent door lock end executes a locking control instruction, and the state of the intelligent door lock is adjusted to be in a locking state.
The intelligent door lock end can comprise an intelligent door lock, an intelligent door lock control device, power supply equipment, network communication equipment and other auxiliary equipment. Furthermore, after the intelligent door lock end completes the adjustment of the state of the intelligent door lock, the intelligent door lock end can feed back the execution result to the user at the signal acquisition end in time. And the user of the signal acquisition end receives the execution result of the intelligent door lock and reports the execution result to the user, so that the remote control operation of the intelligent door lock is completed once.
Referring to fig. 2, fig. 2 illustrates a system framework diagram in a remote control system of an intelligent door lock provided according to some embodiments of the present invention.
As shown in fig. 2, the intelligent door lock in the embodiment is divided into a software layer and a hardware layer. In a software layer, the intelligent door lock comprises an IPv6 communication module, a message transceiving service module, a power management service module and a recording and playing module.
IPv6 is known as Internet Protocol version 6, version 6 of the Internet Protocol, and is a next-generation IP Protocol designed by the Internet Engineering Task Force (IETF) to replace IPv 4. The biggest problem of IPv4 is that network address resources are insufficient, and application and development of the Internet are severely restricted. The use of IPv6 not only solves the problem of the number of network address resources, but also solves the obstacle of connecting various access devices to the Internet.
The hardware layer of this intelligence lock includes loudspeaker, recording wheat, battery, wiFi module and cellular network module. In this embodiment, the WiFi module and the cellular network module are configured at the same time, and the WiFi module accesses the public network based on an independent IPv6 communication protocol and forms redundant communication with the cellular network module.
In communication engineering, redundancy refers to artificially repeating configuration of some key components or functions for the sake of system safety and reliability. When a system fails, for example, a certain device is damaged, the redundantly configured components can be used as a backup to timely intervene and undertake the work of the failed components, thereby reducing the failure time of the system. Redundancy is particularly useful for emergency handling.
In this embodiment, under the condition that the WiFi module works, when the intelligent door lock end performs data interaction with the data processing end and the signal acquisition end, the WiFi module is preferentially used for communication. When the WiFi module fails, the intelligent door lock end uses the cellular network module to perform data interaction with the data processing end and the signal acquisition end. Redundant communication at this place has prevented to a great extent that communication module from breaking down, and the control command that comes from the data processing end can't in time be received to intelligence lock end to and the result information that intelligence lock end can't in time convey the execution feedback to the information acquisition end.
The cellular network module in this embodiment may be a 5G low power consumption chip. 5G refers to the fifth generation mobile communications, which has three performance levels, high network speed, low latency, and multiple connections. The high network speed means that the transmission speed of 5G is hundreds times of that of 4G network theoretically, and can reach the transmission speed of tens of GB per second. The low delay means that the delay time of a 5G network is reduced to be less than 1 millisecond, and the low delay device plays a significant role in the fields of video call, industrial internet of things, unmanned driving, commercial unmanned aerial vehicles and the like. The multi-connection finger is characterized in that the 5G network connects people and objects, and the objects and the like, and urban facilities, home life, logistics states and the like are integrated by using a network technology, so that the 'interconnection of everything' is really realized.
This intelligence lock end has still disposed alternating current power module and battery module simultaneously. The alternating current power supply module is connected with a mains supply at the intelligent door lock end and forms redundant power supply with the battery module. The battery module can be a lithium battery. In this embodiment, the alternating current power supply module is preferentially used for supplying power to the intelligent door lock. After the alternating current power supply module is powered off, the standby battery module is used for supplying power to the intelligent door lock, and power-off notification information is sent to a user located at the signal acquisition end. The redundant power supply mode can supply power to the door lock for one to two weeks by the lithium battery after the household alternating current power supply suddenly fails, so that failure of the intelligent door lock is prevented, power failure notification information can be sent to a user of the information acquisition terminal while the standby battery power supply is adopted, the user can be helped to know the condition of the intelligent door lock in time, and accordingly safety of the intelligent door lock is greatly increased.
Particularly, in this embodiment, the signal acquisition end of the remote control system of the intelligent door lock is configured in the vehicle system. In other embodiments, the signal acquisition end of the remote control system of the intelligent door lock may also be configured in a mobile device such as a mobile phone of a user. The signal acquisition end in the present invention is not limited to the mentioned range of the present embodiment.
In addition, the data processing end in this embodiment is configured at the cloud end. However, in other embodiments, the data processing terminal may be integrated with the intelligent door lock terminal. The data processing end in the present invention is not limited to the mentioned scope of the present embodiment.
The invention provides a remote control system of an intelligent door lock, which is used for controlling the state of the intelligent door lock. This remote control system of intelligence lock can let the user pass through the state of voice command remote control lock to be convenient for the user and control the lock state, and promote user experience.
According to a second aspect of the present invention, the present invention also provides a remote control method of an intelligent door lock, which is implemented by using the above-described remote control system of the intelligent door lock. The specific operation is as described above, and will not be described herein again.
While, for purposes of simplicity of explanation, the methodologies are shown and described as a series of acts, it is to be understood and appreciated that the methodologies are not limited by the order of acts, as some acts may, in accordance with one or more embodiments, occur in different orders and/or concurrently with other acts from that shown and described herein or not shown and described herein, as would be understood by one skilled in the art.
Referring to fig. 3, fig. 3 is a schematic diagram illustrating a control device of a remote control system of an intelligent door lock according to some embodiments of the present invention. As shown in fig. 3, the control device 30 of the remote control system of the intelligent door lock provided by the present invention includes a memory 31 and a processor 32. The processor 32 is coupled to the memory 31 and configured to execute computer instructions stored in the memory 31 to implement a method for remote control of an intelligent door lock.
According to a third aspect of the invention, there is also provided a computer readable storage medium having stored thereon computer instructions. When being executed by a processor, the computer instructions implement the method configured by the signal acquisition end, the data processing end and/or the intelligent door lock end in the remote control system of the intelligent door lock.
Although the signal acquisition terminal, the data processing terminal and the intelligent door lock terminal described in the above embodiments can be implemented by a combination of software and hardware. However, it is understood that the signal acquisition end, the data processing end and the intelligent door lock end can also be implemented in software and hardware. For a hardware implementation, the signal acquisition terminal, the data processing terminal, and the intelligent door lock terminal may be implemented in one or more Application Specific Integrated Circuits (ASICs), digital Signal Processors (DSPs), programmable Logic Devices (PLDs), field Programmable Gate Arrays (FPGAs), processors, controllers, micro-controllers, microprocessors, other electronic devices configured to perform the above functions, or a selected combination thereof. For software implementation, the signal acquisition end, the data processing end, and the intelligent door lock end may be implemented by separate software modules such as program modules (programs) and function modules (functions) running on a common chip, where each module performs one or more of the functions and operations described herein.
Those of skill in the art would understand that information, signals, and data may be represented using any of a variety of different technologies and techniques. For example, data, instructions, commands, information, signals, bits (bits), symbols, and chips that may be referenced throughout the above description may be represented by voltages, currents, electromagnetic waves, magnetic fields or particles, optical fields or particles, or any combination thereof.
Those of skill would further appreciate that the various illustrative logical blocks, modules, circuits, and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, computer software, or combinations of both. To clearly illustrate this interchangeability of hardware and software, various illustrative components, blocks, modules, circuits, and steps have been described above generally in terms of their functionality. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the overall system. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present invention.
The various illustrative logical modules, and circuits described in connection with the embodiments disclosed herein may be implemented or performed with a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing devices, e.g., a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
The previous description of the disclosure is provided to enable any person skilled in the art to make or use the disclosure. Various modifications to the disclosure will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other variations without departing from the spirit or scope of the disclosure. Thus, the disclosure is not intended to be limited to the examples and designs described herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (14)
1. A remote control system of intelligence lock, its characterized in that includes:
the signal acquisition terminal is configured for acquiring voice data of a user at a far end;
the data processing terminal is configured for carrying out voice recognition and semantic analysis on the collected voice data so as to obtain a corresponding control instruction; and
and the intelligent door lock end is configured for controlling the state of the intelligent door lock according to the acquired control instruction.
2. The remote control system of claim 1, wherein the signal acquisition terminal is configured to:
acquiring a plurality of recording analog signals of the user by using a microphone module;
respectively converting the plurality of recording analog signals into corresponding voice digital signals; and
and sending each voice digital signal to the data processing terminal.
3. The remote control system of claim 2, wherein the data processing end is configured to:
acquiring the voice digital signals, and synthesizing the voice digital signals into voice stream data according to a time sequence;
inputting the voice stream data into a voice recognition system to obtain corresponding text information;
analyzing the text information by utilizing a pre-trained semantic processing model to obtain a corresponding control instruction, wherein the control instruction comprises slot position information indicating unlocking operation or locking operation; and
and sending the control instruction to the intelligent door lock end.
4. The remote control system of claim 3, wherein the data processing end is further configured to:
after synthesizing the voice stream data, extracting voiceprint features from the voice stream data;
according to the voiceprint characteristics of the authorized user of the intelligent door lock, voiceprint recognition is carried out on the voiceprint characteristics of the voice stream data;
responding to the voiceprint feature of the voice stream data to accord with the recognition result of the voiceprint feature of the authorized user, and inputting the voice stream data into a voice recognition system to obtain corresponding text information; and
and returning to the step of acquiring the voice digital signal in response to the voiceprint feature of the voice stream data not conforming to the recognition result of the voiceprint feature of the authorized user.
5. The remote control system of claim 3, wherein the data processing end is further configured to:
determining a corresponding semantic expression vector according to the text information;
calculating a first semantic matching degree of the semantic expression vector and a first expression vector indicating the unlocking operation, and if the first semantic matching degree is greater than or equal to a preset first matching degree threshold value, judging that the control instruction comprises slot position information indicating the unlocking operation; and
and calculating a second semantic matching degree of the semantic expression vector and a second expression vector indicating the locking operation, and if the second semantic matching degree is greater than or equal to a preset second matching degree threshold value, judging that the control instruction comprises slot position information indicating the locking operation.
6. The remote control system of claim 5, wherein the data processing end is further configured to:
calculating a cosine included angle between the semantic expression vector and the first expression vector to obtain the first semantic matching degree; and
and calculating a cosine included angle between the semantic expression vector and the second expression vector to obtain the second semantic matching degree.
7. The remote control system of claim 5, wherein the data processing end is further configured to:
and when the first semantic matching degree is smaller than the first matching degree threshold value and the second semantic matching degree is smaller than the second matching degree threshold value, judging that the control instruction does not comprise slot position information indicating unlocking operation or slot position information indicating locking operation, skipping the step of sending the control instruction to the intelligent door lock end, and returning to the step of acquiring the voice digital signal.
8. The remote control system of claim 3, wherein the smart door lock end is configured to:
acquiring the control instruction sent by the data processing end, and analyzing the control instruction to acquire slot position information in the control instruction;
responding to the analyzed slot position information indicating the unlocking operation, and adjusting the state of the intelligent door lock into an unlocking state; and
and adjusting the state of the intelligent door lock to a locking state in response to analyzing the slot position information indicating the locking operation.
9. The remote control system of claim 8, wherein the smart door lock end is further configured to:
and feeding back an execution result to a user at the signal acquisition end in response to the completion of the operation of adjusting the state of the intelligent door lock.
10. The remote control system of claim 8, wherein the smart door lock terminal is configured with both a WiFi module and a cellular network module, the WiFi module accessing a public network based on an independent IPv6 communication protocol and forming redundant communications with the cellular network module, the smart door lock terminal further configured to:
preferentially using the WiFi module to perform data interaction with the data processing terminal and the signal acquisition terminal; and
and responding to the failure of the WiFi module, and performing data interaction with the data processing terminal and the signal acquisition terminal by using the cellular network module.
11. The remote control system of claim 8, wherein the smart door lock terminal is configured with an ac power module and a battery module, the ac power module is connected to a mains power of the smart door lock terminal and forms a redundant power supply with the battery module, the smart door lock terminal is further configured to:
preferentially using the alternating current power supply module to supply power to the intelligent door lock; and
and responding to the power failure of the alternating current power supply module, using the battery module to supply power to the intelligent door lock, and sending power failure notification information to a user at the signal acquisition end.
12. The remote control system according to any one of claims 1 to 11, wherein the signal acquisition end is configured in a car machine system or a mobile phone of a user, and the data processing end is configured in a cloud; or
The signal acquisition end is configured on a vehicle machine system or a user mobile phone, and the data processing end is integrated on the intelligent door lock end.
13. A remote control method of an intelligent door lock, characterized in that the state of the intelligent door lock is controlled by using the remote control system as described in any one of 1 to 12.
14. A computer-readable storage medium having stored thereon computer instructions, wherein the computer instructions, when executed by a processor, implement the method configured by the signal acquisition terminal, the data processing terminal and/or the intelligent door lock terminal in the remote control system according to any one of claims 1 to 12.
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| CN202110612913.9A CN115439958A (en) | 2021-06-02 | 2021-06-02 | Remote control system and method for intelligent door lock |
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| CN202110612913.9A CN115439958A (en) | 2021-06-02 | 2021-06-02 | Remote control system and method for intelligent door lock |
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Application publication date: 20221206 |