29 results about "Home security" patented technology

Smart Home Security Device with Predictive Threat Detection

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.

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.

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.

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.

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.

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 application discloses a kind of intelligent home voice security test method and device based on voiceprint anti-counterfeiting, it is related to intelligent home security test technical field.The core of the device includes main control module, attack simulation module and response acquisition module.Attack simulation module generates multi-dimensional voice deception attack sample including replay, synthesis, conversion and countermeasure sample.Main control module is built-in dynamic countermeasure reinforcement learning algorithm, and dynamically generates digital domain control instruction and physical domain control instruction according to the response state of the device to be measured, wherein the physical domain control instruction directly drives the stepper motor of physical replay sub-module to carry out angle rotation, realizes the deep binding of algorithm strategy and physical hardware action.Response acquisition module comprehensively captures the state feedback of the device to be measured by multi-modal perception means.The device can further include environment simulation module and evaluation and output module to construct physical test space with specific acoustic characteristics and output quantitative evaluation report.The application first proposes a comprehensive test device combining software and hardware from the perspective of active attack test, which can comprehensively and automatically evaluate the voiceprint anti-counterfeiting performance of intelligent home voice control system and Internet of Things devices.

1. The name of the design product: smart middle screen (TB-CE003). 2. The use of the design product: The product is used for smart middle screen, and the main functions are audio and video interaction, Internet TV 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 application relates to the field of home safety, in particular to an AI intelligent home safety control system; the AI intelligent home safety control system comprises a management center, the management center is in communication connection with a home user behavior module, a home user control module and a safety detection control module. Historical instruction data of the user to the intelligent home are acquired, the historical instruction data are analyzed, a user instruction graph is constructed, and user control data are generated in combination with the user instruction graph; a network path link is constructed in combination with the historical instruction data and the user control data; the network path link is analyzed to generate a standard path link template; real-time home path links are generated through the acquired current control behavior of the user, a home behavior control model is obtained according to the user instruction graph and the network path link; real-time instruction data collected are analyzed in combination with the home behavior control model to generate a risk mapping index table, and the intelligent home is controlled in safety through the risk mapping index table. The application can improve the safety of the intelligent home.

The application provides a vehicle password service management method and system. The method takes the vehicle-end password service bus as the core of the whole vehicle unified password management architecture. The originally heterogeneous password libraries of each ECU, domain controller and upper-layer application are integrated into a distributed password node cluster divided according to security domains, and the password service bus is used as the unified password service entrance of the whole vehicle. At the same time, by identifying the service type and the home security domain of the request, the matching execution node is screened in the distributed password node cluster of the corresponding security domain, the whole vehicle password computing power is scheduled as needed, and the safety execution standard of the password operation is uniformly controlled. Finally, the target password node is called to perform the password operation with the exclusive domain key of the corresponding security domain, the isolation of the key according to the security domain and the controllable management of the whole process are realized, the originally disordered key storage and distribution mode is replaced, the risk of key leakage and illegal tampering is avoided, and the safety of the whole vehicle password service management is effectively improved.

The present application belongs to the field of physical security, near and far full scene anti-theft alarm technology, discloses a kind of physical security system based on connection state and behavior trend analysis, system includes monitoring terminal and protection terminal, monitoring terminal gathers wireless connection state and article physical behavior double signal, trend analysis and alarm decision are completed by pure hardware circuit, do not depend on fixed distance and signal strength threshold;Decision logic is: link is directly alarmed unusable;When link is available, only double signal trend synchronous anomaly alarms, single exception inhibits alarm.The present application is low false alarm, anti-cracking, full protocol compatible, full scene adaptation, suitable for close-to-body anti-lost, asset protection, home security and other global physical security scene, patent barrier is high, and judicial stability is strong.

The application discloses a kind of self-adapting risk protection method and system of smart home equipment control, and relates to the technical field of smart home security.The method comprises the following steps: receiving the device control request of control end and extracting context information;Determine the risk analysis module to be called through decision scheduling module;Each risk analysis module carries out risk scoring;Comprehensive scoring engine carries out weighted aggregation and risk amplification to each risk score, and gives comprehensive risk score;According to the comprehensive risk score, the safety policy is executed on the device control request, including release, secondary authentication or interception operation;Finally, the device control request released by terminal is executed.The application realizes multi-dimensional dynamic risk assessment, and improves the security of smart home equipment control.

This invention provides an AI-powered emotion monitoring, multi-member access control, and security incident tracing system and method, belonging to the fields of AI emotion recognition and multi-user home security management. The system includes: an AI emotion risk recognition module, which, with user authorization, collects only voice tone and text semantic features, uses local inference to identify high-risk emotions, and sets limits on collection duration and reporting frequency; a multi-scenario heartwarming intervention module, which desensitizes and reports high-risk emotions and automatically matches rescue entities, forming an intervention closed loop; a multi-member access control module, which automatically identifies roles in multiple scenarios, achieving hierarchical access control and self-adaptive differentiated security strategies; a full-scenario security incident collection module; and a desensitized tracing and evidence storage module. Under the premise of privacy compliance, this invention achieves accurate emotion recognition across all scenarios, fine-grained access control, rapid cross-entity rescue, and reliable incident tracing, forming a complete security closed loop of pre-event prevention, in-event intervention, and post-event tracing, applicable to various scenarios.

The application relates to the field of artificial intelligence and smart home technology, and specifically provides a home algorithm network host application method and system. After the home algorithm network host is powered on, a voice module, a semantic understanding module, an AI monitoring module, a system control module and a communication module are started in sequence; the voice module loads a wake-up word model and VAD parameters, and is ready to receive user voice input; the semantic understanding module realizes semantic analysis and context understanding; the AI monitoring module starts a camera and an environment sensor, realizes real-time collection of video streams and environment data; the system control module initializes a local device interface, and provides interface support for home appliance control; the communication module establishes an internal message queue and an external network interface, and provides guarantee for data interaction among modules and external device communication. Compared with the prior art, the application can construct a high-performance, low-delay, safe and reliable home smart algorithm network host, and provides an integrated solution for home environment control and home security.

This application provides a control method and system for a home security robot dog based on MoT and Transformer, belonging to the field of robot control technology. This application synchronously collects the original command sequence, communication link arrival time sequence, and command feedback sequence of the home security robot dog, extracts damaged commands by bit comparison, and calculates the bit error rate of each control frequency band. Simultaneously, it calculates the information entropy of the arrival time sequence and combines both to obtain the communication confidence level of each frequency band. The confidence level is used as a priori identifier and concatenated with the action lexical of the damaged command to form a fusion tensor. This tensor is input into a Transformer encoder to extract the target vector. Then, the optimal expert network is matched using the gated routing mechanism of the MoT architecture, and the target control command is retrieved from the safety control library. This application can intelligently identify damaged commands and automatically invoke safety actions in strong interference environments, effectively preventing the robot dog from performing dangerous misoperations.

1. Name of the product in this design: Smart door lock. 2. Purpose of this design: This design is intended for use in a home security product. Component 1 is used for the outer lock of the smart door lock, and component 2 is used for the inner lock of the smart door lock. 3. The key design feature of this product is its shape. 4. Images or photos that best illustrate the design key points: Combined state reference diagram.

This utility model relates to the field of smart home device technology and discloses a child lock structure for preventing accidental activation in smart home devices. It includes a smart door lock with a handle rotatably connected to its surface; it also includes a movable component for restricting the handle; and a positioning component for positioning the handle. The movable component includes a fixing block. This child lock structure works by rotating a control panel to drive the rotation of a rotating shaft and a control axis. When the rotating shaft rotates, it drives the rotation axis to rotate. When the rotation axis rotates, it abuts against a sliding rod and abutting block. When the abutting block moves, it rests on the bottom of a limiting rod and pushes the limiting rod upwards. When the limiting rod moves upwards, it moves to both sides of the handle to restrict its movement, preventing children from accidentally opening the smart door lock or other smart home devices due to curiosity or accidental operation. This enhances home security and reduces safety hazards.

This invention provides a multi-dimensional dynamic monitoring and early warning method and system for smart device security. The method includes continuously monitoring all operations and state changes of the smart device in real time, digitizing its behavior to form a device behavior sequence, and identifying abnormal sequences that deviate from the normal behavior pattern of the smart device. A preset smart home scenario logic is transformed into a predictive path model for security analysis, and this model is compared with the abnormal sequences. The causal chain of the TTP knowledge graph is used to determine whether the abnormal sequences constitute a security risk. The comparison results and security risk status are presented intuitively in the form of a heatmap to show the risk distribution and intensity of devices or areas. It can also integrate the analysis of unprotected major disaster types generated by TTP prediction and the protection effect diagram based on the ATT&CK framework. This invention solves the problems of low efficiency, incomplete coverage, and limitation to "single-point alarms" in existing smart home security solutions.

The present application relates to the field of smart home, especially to a kind of smart home security door, including door body, rotating drum, first drive assembly, pivot and second drive assembly;Door body is rotatably connected with several rotating drums;First drive assembly is connected in door body;Pivot is provided in rotating drum;Second drive assembly is connected in door body.The present application realizes that the closed surface of rotating drum corresponds to the front and rear sides of door body in the state of no ventilation, and the flow surface is hidden in door body, to avoid the flow surface hole exposed, easy to be blocked by sundries, affect the air flow effect, and vulnerable to outdoor personnel damage problem, at the same time, closed surface can be set to the same color as door body, the present application ensures the overall aesthetic property when no ventilation, rotating drum is rotated to switch when needing to open ventilation, without occupying large activity space, while ensuring the maximum ventilation area.

1. Name of the product in this design: Smart door lock. 2. Purpose of this design: This design is intended for use in a home security product. Component 1 is used for the outer lock of the smart door lock, and component 2 is used for the inner lock of the smart door lock. 3. The key design feature of this product is its shape. 4. The image or photograph that best illustrates the key design points: Design 1 combined state reference diagram. 5. Design 1 is designated as the basic design.

This invention relates to the technical field of home safety, and discloses a home safety method and system based on edge-cloud collaboration. The method includes: collecting home scene behavior data sequences using multi-source sensing devices, and performing target association on the home scene behavior data sequences; extracting target micro-exploration events using a multi-dimensional behavior trajectory determination algorithm, and generating event feature vectors for the target micro-exploration events; constructing a sliding time window, performing sliding aggregation on the target micro-exploration events, and combining the event feature vectors of the target micro-exploration events in the aggregated events to generate a dangerous exploration evolution intensity vector for the aggregated events; selecting aggregated events with a trend growth rate higher than a preset stable rate threshold as home dangerous events, and generating danger status labels for home dangerous events for graded early warning. This invention achieves early identification, dynamic evolution modeling, and graded early warning of children's dangerous exploration behaviors, and improves real-time performance and identification accuracy through an edge-cloud collaborative architecture.

This invention relates to the field of smart home security technology and discloses a method and system for linkage response to security alarms of smart home devices. The method acquires initial security event information, visual characteristic information of image data, communication status information of security protection devices, and minute change data of environmental sensors, and performs real-time correlation and comprehensive evaluation of these multi-source heterogeneous information. It can effectively identify and judge secondary events such as interference or alteration of image information, localized and purposeful communication interference, and covert environmental interference.

1. The name of the design product: wisdom in the screen (E8-R). 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 application discloses a kind of home security intelligent early warning device, system and method, it is related to intelligent security technology field.The device includes static electric field perception module, vibration detection module, airflow analysis module, feature fusion module, target identification module, risk assessment module, early warning control module and response execution module.Through distributed high impedance antenna array detection space static electric field change, piezoelectric sensor gathers building structure vibration, hot flow sensor monitors airflow disturbance, realizes the collaborative perception of three-dimensional physical field.Adopting space-time alignment and adaptive weighted fusion technology generates multidimensional feature vector, combined with mahalanobis distance matching and hidden markov model carries out target identification and behavior analysis, assesses threat risk and executes graded early warning response by comprehensive multi-factor.The application realizes the technical upgrading from single detection to multidimensional perception, from passive record to active early warning, sensor stealth deployment in home facilities, improve detection accuracy while protecting user privacy.

This invention relates to an AI-powered smart home security control system, belonging to the field of smart home security control. It utilizes an environmental perception module to collect multi-dimensional sensor data and generate an environmental state vector; a behavior modeling module to integrate historical user command data to construct a joint environment-behavior feature space; a self-evolving learning module to use an incremental autoencoder combined with time-aware location embedding to perform online learning and trend prediction of real-time behavior flows; a path modeling module to perform online statistical analysis of network path chains to generate dynamic path templates; and a risk prediction and control module to calculate a weighted risk index based on the degree of behavior deviation, path deviation, and environmental anomaly. Based on the risk index, a tiered security control strategy is executed, and the behavior model dynamically evolves through a model self-updating trigger. This invention achieves a shift from static matching to dynamic evolution, from post-event identification to pre-event prediction, improving anomaly detection accuracy and enhancing the intelligence and adaptability of smart home security control.

Embodiments of the present disclosure disclose an environment monitoring method, an environment monitoring system and a robot controller. A specific embodiment of the method comprises: in response to a robot receiving detection exception information sent by a detection device, determining a position area indicated by the detection exception information, wherein the detection device is installed in a working environment of the robot, and a signal connection component is arranged on the robot to establish a connection with the detection device; controlling the robot to move to the position area and confirming an abnormal event indicated by the detection exception information; and in response to confirming that the abnormal event exists, controlling the robot to generate prompt information and sending the prompt information to a corresponding user. The embodiment is related to home security monitoring technology, and uses the flexibility and intelligence of the robot and the direct connection with the detection device to realize localized monitoring of environmental safety. The situation that an alarm message cannot reach a user due to network abnormalities can be reduced or avoided.

This invention belongs to the field of smart home security and proposes a nighttime low-light target detection method based on multimodal information collaborative perception. This method constructs a heterogeneous sensor network by deploying an infrared thermal imaging module, millimeter-wave radar, and a low-light visible light camera. The main control unit first performs spatiotemporal alignment processing on the multi-source data, and then uses an improved joint probabilistic data association algorithm to achieve cross-modal feature fusion. Specifically, infrared data undergoes noise suppression through bilateral filtering, radar point clouds are used to extract target candidate regions through the DBSCAN clustering algorithm, and visible light images are initially detected using a lightweight YOLOv8-tiny model. The three-modal detection results are fused through a dynamic weight allocation strategy. When the overall confidence level reaches a preset threshold, the system triggers a relay-controlled audible and visual alarm device, and simultaneously uploads the target location information to a cloud server via a Wi-Fi module. The multimodal redundancy design significantly reduces the false alarm rate, and the detection distance for small and medium-sized targets in extremely low-light environments is significantly improved compared to traditional single-infrared solutions, making it particularly suitable for nighttime intrusion prevention scenarios.