183 results about "Home security" patented technology

The invention discloses a household Internet of Things integrated fire alarm system and a linkage control method thereof, and relates to the technical field of smart home security. A first sensing recognition module, a second deep recognition module, a linkage control module, a cloud management platform module and a system self-checking module are integrated; the problems that in an existing fire alarm system, the false alarm rate is high, linkage equipment is prone to false triggering, linkage control logic is complex, and errors are prone to occurring are effectively solved. According to the invention, multi-modal data fusion and a deep learning algorithm are adopted to carry out fire identification, a dynamic threshold adjustment algorithm is combined to optimize the sensitivity of a sensor, and intelligent linkage configuration and an anomaly detection function are provided through a cloud management platform; the accuracy of fire identification and the stability of the system are greatly improved, the credibility of a user to the system and the comprehensiveness of family safety protection are remarkably improved, and resource waste and unnecessary panic caused by false alarm are effectively reduced.

The invention relates to the technical field of security alarm, in particular to a home security integrated system and method based on artificial intelligence, and the system comprises a multi-source data collection module which collects environment data through an infrared sensor, a thermal imaging camera and a standard video camera, carries out the data fusion, and generates an environment data fusion result. According to the invention, the acquisition module fuses infrared, thermal imaging and video cameras, so that the monitoring coverage is expanded, the capability of capturing environmental details is enhanced, and the detection rate of abnormal behaviors is improved. Standardized monitoring data is generated through data fusion and format unified processing, high-quality input is provided for feature extraction and behavior analysis, data streams are optimized, and information loss is reduced. A pre-trained deep learning model is applied to an intelligent analysis module, recognition of complex behavior modes is enhanced, and the accuracy and timeliness of anomaly detection are improved.

The invention discloses a home monitoring method and system based on a multi-agent large model, the multi-agent large model comprises a central large model and agents, and the central large model is used for scheduling at least one agent to execute monitoring, analysis and alarm tasks; the method comprises the following steps: reading video stream data of a household camera in real time, and preprocessing source data to obtain unified video format data; and inputting the processed video data into the multi-agent large model, distributing a task to at least one agent by the central large model, and executing corresponding monitoring, analysis and alarm operations by the at least one agent according to the task. By performing uniform format processing on real-time read camera video streams, the accuracy of system data is ensured, and monitoring identification and intelligent alarm of abnormal conditions in a home environment are realized through a multi-agent collaborative decision-making mechanism in combination with intelligent analysis and reasoning capabilities of a large language model. And the reliability, the intelligence, the user experience and the like of the home safety monitoring system are remarkably improved.

The invention relates to the technical field of smart home security and protection, and discloses a smart home security and protection system based on a body, and the method comprises the steps: collecting real-time sensing data through Wi-Fi multipath scattered waves, constructing a body sensing network, recognizing behavior feature information, optimizing a preset security and protection model decision architecture, and obtaining an optimized security and protection process. The method comprises the following steps: firstly, generating a security response path, determining a personnel activity space-time distribution state, calculating a security efficiency value, then determining an optimization direction according to the security efficiency value, generating a dynamic protection organization unit, calculating a misjudgment attenuation rate, and finally determining a security state and analyzing a security dimension according to the misjudgment attenuation rate, thereby constructing a more accurate and intimate intelligent security scheme. According to the invention, the intelligent level of autonomous decision making and active protection of home security can be improved.

The invention discloses a door lock collaborative identity recognition method and system, and the method comprises the steps: obtaining a locally stored MAC-face binding relation table according to face recognition verification completed by a resident through an intelligent door lock; according to the moving path of the resident from the floor entrance to the home door lock, identity recognition is completed through cooperation of multicast communication and the home door lock, an identity confirmation result is obtained, and a directional multicast network is constructed; according to a leaving event that a resident opens a door lock from a room, triggering a passing door lock to collect leaving person information, and obtaining a leaving person identity confirmation result; and selecting to send a unicast or multicast confirmation message by the own door lock according to the completion degree of identity confirmation of the leaving person, and triggering the passing door lock to send an IGMP leaving message to the router to obtain a simplified multicast forwarding table. According to the embodiment of the invention, seamless identity cooperation of the whole process from home returning to home leaving can be realized, and the automation degree of home security and protection and the user experience are improved.

The invention discloses a non-intrusive dual-channel smart home security monitoring method, and belongs to the technical field of network security. Aiming at the problem that the existing smart home privacy security monitoring method has defects, an audio channel takes a pre-training model Vgish as an audio feature extractor, and a pixel spectrogram corresponding to each section of 960ms frame length audio obtained through discrete Fourier framing processing is vectorized into 128-dimensional feature representation; then, a support vector machine (SVM-RBF) classifier identifies and obtains an audio event category sequence Ea; five-tuple information contained in event traffic is extracted in a traffic channel to be matched with a predefined event-rule base mode, a traffic event category sequence Et is recognized, and then event alignment, verification and fusion are carried out on the sequences Es and Et so as to monitor the security problem in the smart home. According to the method, the accuracy of event identification of the two-channel model is proved through an experiment carried out on a self-built experiment platform, and meanwhile, the necessity of safety monitoring by adopting two-channel fusion is also proved.

Determining a sequence for providing a notification regarding activity recorded by a camera is described. In one aspect, a priority sequence for can be determined based on a variety of characteristics of the available devices registered with the home security system of the camera.

The invention relates to the field of home safety, in particular to an AI intelligent home safety control system. Comprising a management center, and the management center is in communication connection with a home user behavior module, a home user control module and a safety detection control module. Acquiring historical instruction data of a user for the smart home, analyzing the historical instruction data, constructing a user instruction map, and generating user control data in combination with the user instruction map; constructing a network path link in combination with the historical instruction data and the user control data; analyzing the network path chain to generate a standard path chain template; generating a real-time home path chain through the obtained current control behavior of the user, and obtaining a home behavior control model according to the user instruction map and the network path chain; and analyzing the collected real-time instruction data in combination with the home behavior control model, generating a risk mapping index table, and performing safety control on the smart home through the risk mapping index table. According to the invention, the security of the smart home can be improved.

The invention relates to the technical field of smart home security, and discloses a smart AI-based home security real-time video anti-shielding defense system, which comprises a monitoring unit, a smart network camera unit, a signal shielding detection unit, a terminal control unit and an execution unit, the monitoring unit is used for detecting the surrounding environment of the detection unit in different dimensions or controlling the monitoring unit to change the environment through a terminal, and the intelligent network camera unit serves as a core unit of the system and is used for receiving data information collected by the monitoring unit and pushing the data information to the terminal control unit in an APP mode. The terminal control unit is used for receiving a control command sent by the intelligent network camera unit and displaying data of the intelligent network camera unit, the signal shielding detection unit is used for carrying out electromagnetic safety detection on the intelligent network camera unit in a family space environment, and an alarm is given if abnormity comprises malicious radio attack. And the execution unit is used for receiving instruction information sent by the terminal control unit through the intelligent network camera unit, sending data information to access the execution unit after accurate confirmation of audio and video, and executing security and fire-fighting tasks according to the instruction.

The invention discloses a home security prediction method and device, electronic equipment and a storage medium, and relates to the technical field of data processing. Visual and non-visual data can be fused to generate perceptual event features, and a dynamic causal knowledge graph including home entities, events and situational states is constructed; deep modeling of association between the overall state of the family and the event causality is realized; complex scene anomalies can be captured through causal chain template matching and anomaly marking, multiple groups of causal hypotheses are generated, an optimal result is screened, explainable early warning containing causal logic is generated in combination with risk scores, and the limitation of a traditional static rule or a single sensor is avoided, so that the method is suitable for popularization and application. The technical problem that an existing traditional scheme lacks deep modeling capability of family overall state, member behavior mode and causal association between events and is difficult to adapt to complex dynamic scenes can be solved. The technical effects of improving the adaptability of the home security system to complex dynamic scenes, improving the early warning accuracy and interpretability and enhancing the intelligent level of the system are achieved.

The invention relates to the technical field of smart home, and discloses a real-time video behavior recognition and anomaly monitoring system based on edge computing, which comprises an edge computing node, a video preprocessing module, a background separation and target detection module, an alarm triggering and equipment linkage module, a behavior recognition module and an anomaly monitoring module, the edge computing node is connected with the video preprocessing module and the alarm triggering and equipment linkage module, and the edge computing node is connected with the video preprocessing module and the alarm triggering and equipment linkage module. The system has multiple advantages of real-time performance and high efficiency, privacy protection and security, accurate identification and low false alarm rate, equipment linkage and intelligence, strong adaptability and expandability, energy conservation and environmental protection, and the like, and the system has wide application prospects and important practical values in the field of smart home security protection due to the advantages.

The invention discloses a cooperative processing method and system for visitor unlocking, and the method comprises the steps: detecting that an abnormal visitor inputs wrong passwords for multiple times according to a door lock A, generating an abnormal visitor broadcast message, and obtaining a broadcast notification of the abnormal visitor; according to the abnormal visitor broadcast message received by the door lock B, accumulating the error input times of the lock and the error input times in the broadcast message; according to the fact that a door lock C detects that a normal visitor inputs wrong passwords for multiple times, an abnormal visitor broadcast message is generated, and a misoperation notification of the normal visitor is obtained; according to the abnormal visitor broadcast message received by the door lock A, generating an abnormal visitor exclusion broadcast message, and obtaining an identity confirmation result of a normal visitor; and according to the abnormal visitor exclusion broadcast message received by the door lock C, obtaining a visitor guiding result. By utilizing the embodiment of the invention, the response speed of the intelligent door lock on abnormal condition processing can be improved, and the safety protection capability of a family is further enhanced.

The invention relates to the technical field of home safety, and discloses an intelligent door lock identification and hierarchical response control method, which comprises the following steps: acquiring multi-modal data in a learning mode to train and construct an authorized behavior baseline model; in the working mode, the current feature vector is extracted in real time, the abnormal score of the current feature vector relative to the baseline model is calculated, when the abnormal score is larger than a threshold value, potential threats are judged, the potential threats are responded, the micro actuator is driven to apply physical disturbance signals, and feedback signals are synchronously collected; analyzing the time sequence characteristics of the feedback signal to discriminate whether the event category of the potential threat is benign or malicious, and executing a hierarchical response strategy; and dynamically correcting the model based on the event category, if the model is benign, updating the authorized behavior baseline model, and if the model is malicious, extracting malicious feature signatures and storing the malicious feature signatures in a high-priority threat signature library. Through active discrimination and closed-loop adaptive learning, the recognition accuracy is significantly improved, and the false alarm rate is reduced.

The embodiment of the present application provides a face detection method, which is applied to the field of face detection, by obtaining a text instruction carrying an image condition, generating an image that meets the image condition according to the text instruction through a preset first large model, training a preset face detection model through a training data set after data enhancement, and in the training process, adjusting the face detection model using a preset staged loss function, generating a target face detection model, obtaining an image to be detected collected by a home security monitoring system, using the target face detection model, detecting the image to be detected, and obtaining a face detection result. The face detection model is trained through a training data set after data enhancement, which improves the richness of the training data and the comprehensiveness of the model training. When facing face recognition tasks under various conditions, the robustness of the model is greatly enhanced, and the accuracy of face detection is further improved through the introduction of a staged loss function.

The invention discloses a home-entry security check gas equipment classification detection method, and relates to the field of equipment classification, and the method comprises the steps: firstly obtaining a field image through a mobile equipment camera, and carrying out the preprocessing and feature extraction of the image through an attention-enhanced visual feature extraction network; secondly, a hierarchical detection head assembly is adopted for equipment recognition, the large class of equipment is detected firstly, and then secondary recognition is conducted on the class needing to be further subdivided; and finally, constructing a gas equipment space relation rule set, and performing context sensing and optimization on an initial detection result based on the rule set. Detection results which are low in confidence coefficient or possibly wrong are corrected by utilizing inherent space and function association between gas equipment. According to the method, efficient, accurate and automatic classification detection of the gas equipment is realized, and the limitation of traditional manual detection and the identification difficulty in a complex environment are remarkably overcome.

The invention provides a smart home security authentication management method and system based on a wireless local area network. The method comprises the following steps: constructing a home network security authentication domain; when a new smart home device is accessed, marking the new smart home device as a second smart home device, and obtaining a device authentication state matrix of a home network security authentication domain; generating an authentication challenge vector based on the device authentication state matrix, and sending the authentication challenge vector to the second smart home device and the first smart home device for cooperative verification; and if the authentication challenge vector passes the cooperative verification, updating keys of all smart home devices in the home network security authentication domain according to a preset dynamic key synchronization protocol. Through construction of a home network security authentication domain, intra-domain sharing of security parameters such as a device authentication state and key management is realized, when any key is updated, other devices update synchronously, and associated dependence exists among keys, so that a risk conduction path of a whole network falling situation caused by key leakage of a single device is blocked.

A system and method for providing customized security to cater to different security needs of a people. The system makes private security accessible and affordable to many in society. The system includes an interface configured to allow a service seeker and a service provider to interact with each other. The interface includes a hire screen that is split into an upper section and lower section. The upper section has a map, and the lower section presents a profile of a contractor or service provider. Current locations of the service seeker and provider are presented on the map. Also, the system provides a personal digital assistant implemented on a home security device that allows audio and video telephony with a visitor.

The invention discloses an emergency linkage and emotion recognition integrated household intelligent guard system and method, and relates to the technical field of Internet of Things, artificial intelligence and emergency response, the system comprises the following components: a front-end sensing device, an edge AI processing unit, a voice broadcast interaction module, a remote linkage module and a background data platform; by integrating the front-end sensing device and the edge AI processing unit, multi-dimensional real-time monitoring of human body behaviors, emotional states and environment information is achieved, the abnormal behaviors and emotional states of a user can be accurately recognized by the system through the behavior recognition module, the emotional analysis module and the multi-modal fusion module, and the user experience is improved. And active care and family interaction are carried out through the voice broadcast interaction module, and the remote linkage module is triggered to inform family members or an emergency platform if necessary, so that a closed-loop intervention mechanism is formed, and the intelligent level and the response speed of family safety monitoring are effectively improved.

Determining a sequence for providing a notification regarding activity recorded by a camera is described. In one aspect, a priority sequence for can be determined based on a variety of characteristics of the available devices registered with the home security system of the camera.

Smart Home Security Device with Predictive Threat Detection

The invention discloses an operation system of an accompanying robot, and belongs to the technical field of intelligent robots. The system is composed of a sensing module, an operation control system and an execution operation and maintenance system, and can achieve multiple functions of family safety patrol, pet accompanying care, human emotion interaction and the like. Environmental and target information is obtained through the upper laser radar and the bottom visual AI module, corresponding operation is executed by the execution operation and maintenance system after the environmental and target information is processed by the operation control system, the problem that an existing product is single in function and not intelligent enough is solved, and the system has the advantages of being convenient to use, high in intelligent degree and capable of achieving anthropomorphic emotional interaction.

This application discloses a smart lock system, relating to the field of home security technology. The system includes: a door, with a hidden sensor module integrated inside the exterior door panel; the hidden sensor module includes a radar sensor, a UWB antenna, and a voice receiving module. The radar sensor detects objects approaching the door; the voice receiving module collects sounds around the door; a main control MCU, located inside the door, is electrically connected to the radar sensor, UWB antenna, and voice receiving module; and a motor control system, including a motor driver chip and a DC motor. The input of the motor driver chip is connected to the main control MCU, and the output is connected to the DC motor to drive the bolt. This smart lock system eliminates the need for a front panel, avoiding the problem of exposed panels being easily damaged or having their passwords stolen. While ensuring the smart lock functions normally, it minimizes security risks associated with smart locks.

The application belongs to the technical field of intelligent security and protection home, and relates to a smart floor system capable of identifying falling behaviors, which comprises a smart pressure sensing floor, a data acquisition system and an upper computer, the smart pressure sensing floor is a composite structure of a solid floor and a flexible sensing fabric, the flexible sensing fabric contains 40 electrodes and 40*40 array distributed sensors, and a piezoresistive sensing layer is constructed by a graphene-carbon black mixed filler to form a conductive network; the data acquisition system collects signals through FPC flat cable, transmits data to the upper computer through a sensor router and a public network router; the upper computer adopts a "cloud-edge-end" architecture, carries a machine learning identification algorithm, can accurately identify falling and intrusion behaviors, the falling identification accuracy is more than 98%, and the response time is less than or equal to 1 second; the terminal side is associated with a cloud program to realize alarm pushing and data viewing functions. The disclosed system simultaneously integrates two core functions of old people falling monitoring and home safety protection, and meets the diversified needs of users living alone.

The invention relates to the technical field of smart home security, in particular to a visual doorbell active security scenarized alarm live broadcast method, which comprises the following steps: scene triggering, multi-terminal scenarized notification, user interaction response, danger judgment and conventional interaction ending if no danger exists. If danger exists, active expelling control is executed; alarm live broadcast is started; evidence solidification and feedback are carried out; according to the invention, alarm live broadcast is realized by innovatively combining with a conference: during alarm, on-site videos, position codes and interactive records are automatically synchronized to the conference, real-time check by multiple parties (police, family members, property management and the like) is supported, and the police can intuitively judge the danger level (such as whether an instrument is held or not and whether a door is broken or not) and accurately deploy police strength; and meanwhile, videos and voices in the whole process are automatically recorded and stored, so that a complete evidence chain of'triggering-interaction-expelling-alarming 'is formed. According to the linkage mode, the police decision-making time can be shortened by 50%, the evidence effectiveness is improved by 90%, and the pain points of information lag and evidence fragmentation of traditional alarm are solved.

The invention provides an intelligent voice door magnetic alarm and a multi-language and tone switching method thereof. The method belongs to the cross technical field of smart home security, man-machine interaction and edge speech synthesis. The method comprises the steps of performing multi-mode identity recognition module deployment on the intelligent voice door magnetic alarm, and generating a user identity feature database; performing voiceprint portrait construction according to the user identity feature database to form a personalized voiceprint model set; according to the multi-language and tone switching method of the intelligent voice door magnetic alarm provided by the invention, the adaptability and individuation degree of voice alarm are remarkably improved, and the multi-mode identity recognition and environment perception technology is adopted, so that the intelligent voice door magnetic alarm can be realized according to different user identities and situations. And synthesizing and broadcasting a multi-language and personalized timbre voice alarm adaptive to the current scene in real time.

Embodiments of the present disclosure disclose an object behavior monitoring method, an object behavior monitoring device and an electronic device. A specific implementation of the method comprises: in response to receiving multi-modal monitoring data sent by a monitoring device, performing feature extraction on each image in a monitoring video or a sequence of monitoring images to obtain a sequence of image features; performing user behavior prediction according to the sequence of image features and generating text description data; generating unified text data based on the text description data of the multi-modal monitoring data; in response to determining that there is a security problem according to the unified text data, generating a prompt information and sending the prompt information to a corresponding object. The implementation is related to home security monitoring technology, can predict future behavior of a user according to multi-modal monitoring data, thereby realizing safety warning for behavior about to occur. Not only can the accuracy of the prediction result be improved, but also the occurrence of safety accidents can be reduced.

The utility model relates to a lifting head-shaking video instrument, which realizes rotation and height lifting of a camera in any direction up and down and left and right through collaborative design of a lifting assembly, a rotating assembly and a camera assembly, and remarkably expands the monitoring range and scene adaptability. Illumination and monitoring functions are integrated, the light-emitting assembly provides illumination and can also supplement light for the camera, and the low-light environment monitoring effect is improved. A manual lifting mode and an electric lifting mode are provided, manual lifting is matched with silica gel ring friction positioning, the structure is simple, and the cost is low; lifting is driven by the motor, and adjustment is more accurate and stable. In the two modes, the abutting buckles are matched with the lifting grooves, so that the assembly is prevented from falling off, and the use safety is improved; universal parts such as an eccentric motor are adopted, so that the manufacturing cost is reduced while the function is ensured; the whole device is directly connected to the mains supply through a threaded interface or a socket, does not need an external adapter, is convenient to install and use, is suitable for various scenes such as home security and shop monitoring, and improves the user experience and the equipment practicability.

The invention relates to the technical field of smart home and Internet of Things, in particular to a solitary elderly guard monitoring method and system based on an air source heat pump water heater, a storage medium and a computer program product. According to the method, multi-source data such as water flow switching pulse, compressor current and water tank temperature difference are collected, feature vectors are constructed, a lightweight neural network is executed at the edge end to infer the physical activity state of the elderly, a personalized water use base line is updated in combination with a cloud recurrent neural network, and accurate recognition and graded warning of behavior abnormity are achieved. The system has the functions of national standard alarm, remote communication, self-calibration and energy-saving control, has the advantages of accurate effect, timely response, energy conservation, high efficiency, low deployment cost and the like, and is suitable for smart old-age care and home security scenes.

The invention relates to the technical field of smart home security, and discloses a method, a device, equipment and a medium for smart door control, the method comprises the following steps: acquiring video information in a smart door vision field, and extracting gait features and facial features in the video information; determining the gait feature confidence coefficient based on the matching degree of the gait features and the gait features in a gait feature library; determining facial feature confidence based on the similarity between the facial features and facial features in a facial feature library; fusing the gait feature confidence coefficient and the facial feature confidence coefficient to obtain a recognition result of the target in the video; according to the method, the gait features and the facial features are combined to perform target recognition, so that the accuracy and the safety of target recognition in the video can be improved, and the defect of single feature is avoided; meanwhile, the recognition result is combined with the behavior intention, corresponding intelligent door control is carried out, and the use experience of the user is improved.

1. The name of the design product: home robot. 2. The use of the design product: for smart home security and smart voice communication. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view.