115 results about "Home security" patented technology

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 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 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 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 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.

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.

A base station used in a home security or home automation / / control system is described. The base station is configured to automatically accept new sensors or control modules by placing such new sensors or control modules in proximity to the base station.

The utility model relates to the technical field of smart home safety, and discloses a real-time video anti-shielding defense system based on smart AI home safety, 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.

A Security System comprises (1) a Wearable Edge Computing AI Chipset (Edge AI) interoperating with one or more Cameras into a Wearable Security System, In-Vehicle Security System, and a Home Security System as part of the Unified AI (Artificial Intelligence) Security System. The security system contains one or more GPS tracked devices that utilizes either an Edge Computing AI Chipset containing a System-on-Chip (SOC) or a custom design Application-Specific Integrated Circuit (ASIC). The Wearable, In-Vehicle and Home Security Systems are controlled by a common Application Programming Interface (API) residing in the Cloud. Each camera video stream is analyzed by the Wearable Edge AI Chipset to detect objects, behaviors, or patterns of interest. When the required conditions are met, alerts are then triggered and sent to the user's mobile app on the cell phone for user review and display, and to his / her trusted contacts.

This invention discloses a home intelligent guardian robot and its intelligent detection and obstacle avoidance method, relating to the field of intelligent home robot technology. The robot includes two sets of symmetrically arranged support arms. The inner sides of the two sets of support arms are rotatably connected to both ends of a connecting rod, and the middle of the connecting rod is rotatably connected to the outer wall of the main unit. Mecanum wheels are fixedly mounted at the bottom end of each set of support arms. An auxiliary functional unit is fixedly arranged on the outer side of the main unit, and an AI intelligent gimbal is fixedly mounted on the outer wall of the main unit or the auxiliary functional unit. This invention features an ingenious robot design, deeply integrating mechanical structure, protection, functional expansion, and intelligent perception to adapt to the home environment. Its intelligent detection and obstacle avoidance method allows the robot to autonomously perceive, identify, and make operational decisions, enhancing home security response capabilities, ensuring smooth movement, improving intelligence, safety, and convenience, and meeting daily family needs.

The invention provides a multi-mode home security anomaly detection method and device and a medium. The method comprises the steps of obtaining home monitoring multi-mode data; extracting a feature vector of each modal data in the family monitoring multi-modal data, and splicing and fusing the feature vector with the candidate abnormal semantic vector to obtain a multi-modal feature tensor; inputting the multi-modal feature tensor into a trained lightweight neural network model, and outputting a confidence coefficient weight of each modal; the confidence coefficient weight of each mode is optimized through DDPG reinforcement learning, and the optimized confidence coefficient weight of each mode is obtained; and inputting the confidence coefficients of all the modals into a pre-trained Transform sequence modeling network to obtain an identification result of home security anomaly detection. According to the method, the device and the medium, the problem of low recognition accuracy in a complex environment due to the fact that an existing home security anomaly detection method mostly depends on a single mode to carry out anomaly detection can be solved.

1. The name of the design product: wisdom in the screen (TB-CE007). 2. The use of the design product: the product is used for wisdom in the screen, and the main functions are audio and video interaction, Internet television playing, smart home control, home security, office video conference, home network learning, etc. 3. The design points of the design product: in shape. 4. The picture or photo that best indicates the design points: perspective view 1.

The invention discloses a household protection system based on intelligent monitoring, which remarkably improves the intelligent level of household safety monitoring through the combination of multi-modal perception and deep learning. The system adopts a dual-spectrum camera and an improved NeRF + + algorithm, high-precision reconstruction of submillimeter three-dimensional face point cloud is realized, and the point cloud precision is improved by 17.5 times. And in combination with a YOLOv5s model and dynamic expression compensation, the recognition accuracy of the system in a complex scene is improved by 4.3%, and the false alarm rate is remarkably reduced. Besides, the synthetic image is generated based on the physical GAN, the robustness of the system is enhanced, and the system is excellent in performance under the conditions of strong side light, rapid blinking, extreme expressions and the like. In the aspect of hardware, a low-power-consumption high-performance module is adopted, so that the real-time performance and the stability of the system are ensured. According to the system, the defects of a traditional monitoring system are effectively overcome, and an intelligent and precise solution is provided for family safety.

The application provides a wireless local area network-based smart home security authentication management method and system, comprising: 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 the 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 a first smart home device for collaborative verification; if the authentication challenge vector passes the collaborative verification, updating the keys of all smart home devices in the home network security authentication domain according to a preset dynamic key synchronization protocol. Through the construction of the home network security authentication domain, the security parameters such as the device authentication state and the key management are shared in the domain, when any key is updated, other devices are synchronously updated, and there is a correlation and dependence between the keys, thereby blocking the risk transmission path of the single device key leakage leading to the collapse of the whole network.

The invention discloses a family safety AI monitoring method and system based on multi-modal algorithm fusion, and particularly relates to the technical field of smart home monitoring. The method comprises the following steps: acquiring original video image data and original audio data in a home monitoring scene; performing target identification by using a convolutional neural network model, generating bounding box position information of a monitored object, and extracting behavior characteristics of the monitored object by using a long-short term memory neural network; performing feature extraction on the audio frame sequence, and identifying a corresponding sound event type in combination with an event classification model; synchronously correcting the target position information, the behavior characteristics and the sound event type to generate a joint behavior characteristic vector; performing abnormal behavior recognition based on the joint feature vector, judging whether the monitored object has a predefined risk behavior, and outputting a behavior recognition result; and a home security alarm instruction is generated according to the behavior recognition result, and the alarm content is pushed to the user terminal, so that the accuracy and the real-time performance of the home monitoring system are improved.

The invention discloses an EEG-based state anomaly detection method and system, a terminal and a medium, and belongs to the technical field of brain-computer interfaces. The method comprises the steps that electroencephalogram signals of a user are collected in real time and preprocessed, and power spectrum density characteristics of a preset frequency band and an inter-brain phase synchronization index are extracted; inputting the features into a tensity quantification model to obtain continuous tensity scores; on the basis of the tensity score and the power change trend of the specific electroencephalogram frequency band, dynamic calibration is carried out in combination with historical baseline data of a user individual, and whether the user is in a violent stress abnormal state or not is judged according to a preset multi-level judgment rule; and if the judgment result is abnormal, triggering a response action. According to the method, through continuous quantification of the tensity, construction of a'tensity-violent state 'strong correlation model and individual dynamic calibration, high-precision, low-delay and low-misjudgment-rate abnormal state recognition is realized, and the method is particularly suitable for home security, public security and vulnerable group protection.

The utility model discloses a family security guard teaching aid, and belongs to the technical field of teaching aids. The utility model aims to solve the technical problem of how to improve the function application display and understanding of students on some circuit devices. According to the technical scheme, the window simulation device is characterized by comprising a mounting plate, a window simulation part, a wire arrangement frame and a circuit module assembly, the window simulation part comprises a window frame and a window body, the window frame and the window body are rotationally connected through hinges installed on the upper edges, a curtain is installed on the upper edge of the window frame, and a driving mechanism is installed on the top of the window frame; the driving mechanism drives the end portion of the curtain to horizontally move on one side of the window body, the travel switch is further fixed on the window frame and used for limiting the movement travel of the curtain, the teaching ability is improved through circuit demonstration, and the device has the advantages of being convenient to use, capable of being repeatedly used and facilitating teaching and improving the learning and manipulative ability of students.

The application relates to the technical field of artificial intelligence, and provides a household safety device and a security door, wherein the household safety device is arranged on the security door and comprises a camera device and a sound recognition device; the camera device is used for shooting a picture outside the door, performing behavior recognition on a person outside the door, and issuing an alarm prompt if the person outside the door behaves abnormally; and the sound recognition device is used for detecting a sound outside the door and recognizing a safety hidden danger. According to the household safety device arranged on the traditional household security door, the camera device is used for shooting a picture outside the door and performing behavior recognition on a person outside the door, the abnormal behavior of the person outside the door can be intelligently recognized and an alarm can be issued, the sound recognition device is used for detecting a sound outside the door, a safety hidden danger can be timely recognized, and therefore the household safety protection capability and the protection level are effectively improved.

This utility model discloses an anti-pry alarm device for a smart lock, relating to the field of smart home security technology. The utility model includes an outer shell and an inner shell, with a lock body positioned between them. A rectangular groove is formed on one side of the outer shell, and an anti-pry device is fixedly installed inside the groove. The anti-pry device includes a base plate, with multiple pins fixedly connected to one side of the base plate. Springs are fitted onto the outer surfaces of each pin. A pressure sensor is fixedly installed on one side of the base plate. A pressure plate is slidably fitted onto the outer surfaces of the multiple pins. A pressure rod is fixedly connected to one side of the pressure plate. This utility model, through the anti-pry device and the smart lock's built-in clamping structure, achieves the effect of forcibly triggering an alarm even if the alarm circuit is maliciously damaged, and provides a convenient and stable anti-pry device.

The invention discloses a home security system based on the Internet of Things technology, and relates to the technical field of home security, comprising a home security system, a security monitoring system used for monitoring home security in real time, a networking system used for networking the home security system and transmitting data information monitored and collected by the security monitoring system, the networking system is used for realizing networking data exchange between multiple devices and multiple nodes in the home security system, the networking analysis system is used for carrying out abnormity analysis on data information transmitted by the networking system, and the early warning processing system is used for carrying out alarm processing on an abnormal result. According to the invention, a setting mode of a home security system is utilized, seamless access of equipment is realized through a multi-protocol integrated network module, a dynamic encryption protocol and identity authentication are adopted to ensure data transmission security, a regional linkage and data cross validation mechanism is designed to improve early warning accuracy, and an equipment state diagnosis and self-healing process is introduced to ensure system stability.