610 results about "Safe system" patented technology

Techniques described herein can generate customized, user-based security response recommendations for users of security system(s), such as for security analysts tasked with performing responses to computing security threats. A user-based response recommendation engine can generate the user-based security response recommendations based on incident data associated with security incidents and based on historical user response data. Furthermore, user role inference techniques can optionally be used in conjunction with the user-based response recommendation engine.

The invention discloses a UWB-based multifunctional integrated vehicle-mounted safety control method and system, and the method comprises the following steps: collecting the dynamic environment data around and in a vehicle in real time based on a plurality of sensors, carrying out the path adjustment and driving mode optimization through generating a multi-level three-dimensional environment model, and carrying out the control of the driving mode. The system performs risk assessment and dynamic adjustment by using external data such as obstacles, road conditions, weather and the like collected by a sensor and combining a behavior mode of a driver and a health state of a passenger, and in a collision prediction and protection mechanism, the system gradually activates a protection system by analyzing factors such as vehicle speed and acceleration, so that the safety is guaranteed, and the safety is ensured. The system optimizes the energy distribution of a key system through an energy scheduling model, improves the energy efficiency, and preferentially guarantees the operation of a safety system in an emergency. According to the invention, a self-adaptive learning algorithm and a multi-scene optimized driving assistance function are integrated, and self-adaptive adjustment and safety control of the vehicle in different driving environments are realized.

The invention relates to an intelligent driving safety system and method based on AI multi-source data fusion. The system comprises an environment modeling sensing module which obtains vehicle end multi-mode sensing data and vehicle size parameters to construct a surrounding environment model, and multi-vehicle environment data of collaborative sensing is formed through vehicle-vehicle communication; the behavior scene generation module analyzes the traffic flow characteristics of the multi-vehicle environment data, calculates the attention weight of the vehicle characteristics, associates the attention weight with the target size information, and generates a unified behavior scene representation. The collision risk judgment module fuses the unified behavior scene representation and the dynamic environment modeling data to generate multi-target fusion trajectory data, and if the uncertainty exceeds a threshold value, a historical database is checked to judge the risk level; and the path planning generation module performs classification according to risk levels and risk levels, and performs matching and speed adjustment instruction integration on the collaborative path optimization instruction to obtain a path planning rule. By adopting the system, the sensing precision, risk response capability and cooperative efficiency of the automatic driving vehicle can be improved, and the driving safety is guaranteed.

The invention relates to the technical field of power grid safety management, in particular to a digital twinning-based power grid control safety system and method.The digital twinning-based power grid control safety system comprises a power grid model unit, an intelligent recognition unit, a strategy making unit and a block chain cooperation unit. The method improves the operation safety and reliability of a power grid, optimizes the resource configuration of the power grid, reduces the energy consumption, provides detailed safety reports and risk assessment for the operation of the power grid, dynamically recognizes potential safety threats and abnormal behaviors, automatically generates a response strategy in real time, improves the overall safety of the system, and improves the safety of the system through the introduction of a block chain technology and the combination with digital twinning. According to the method, transparent information sharing and collaborative management among each level and each region of the power grid are realized, and through decentralized data storage and security guarantee, the power distribution networks in different regions can be ensured to be efficiently collaborative when facing network attacks or faults, and the response efficiency is improved.

The embodiment of the invention discloses a vehicle safety system optimization method and device, equipment and a storage medium, and the method comprises the steps: constructing a dynamic model of a target safety system of a target vehicle; wherein the target safety system comprises an active safety system and a passive safety system; performing a simulation test on the kinetic model based on a preset simulation scene to obtain a simulation test result; and adjusting control parameters of the target safety system based on the simulation test result so as to complete the safety system optimization process of the target vehicle. According to the technical scheme, the problems that an existing vehicle safety system is long in optimization period and insufficient in vehicle design efficiency are solved, the simulation model of the vehicle safety system can be constructed, the parameters of the vehicle safety system are adjusted based on the simulation test, the optimization period is shortened, and the design efficiency of the vehicle safety system is improved.

The invention relates to safety compliance evaluation, in particular to a safety compliance evaluation system and method based on a multi-modal large model, and a functional module cluster, which are used for managing each functional module in the system, supporting cross-modal consistency detection and comparing answer consistency under different modals. The self-developed security system is responsible for execution of an assessment task, including resistance test enhancement and built-in multi-granularity data variation strategy, improves assessment robustness by simulating a real attack scene, realizes end-to-end automation from data generation, tested model test to risk assessment, supports configurable parameters and reproducible results, and has the advantages of high reliability and high reliability. The self-iteration and version management of the evaluation model are realized, and the self-iteration mechanism is deeply combined with a compliance label system, so that the risk identification capability under legal, ethical and industrial specifications can be continuously optimized; according to the technical scheme provided by the invention, the limitation that evaluation can be carried out only under a single mode and a single rule in the prior art can be effectively overcome.

The invention relates to a deep learning method for fire risk monitoring and early warning, and belongs to the technical field of fire safety. Through integration of various sensors (such as an infrared imager, a smoke detector and a temperature sensor), the method realizes omnibearing perception of a monitoring area, and significantly improves the accuracy and reliability of fire monitoring. A convolutional neural network (CNN) and a long and short term memory network (LSTM) are adopted, so that the system can effectively reduce false alarm and missing alarm, monitors key parts in real time, collects multiple parameters such as temperature and voltage, and dynamically evaluates the fire risk through intelligent analysis. In addition, an efficient communication link between the early warning system and other safety systems is established, and it is ensured that emergency measures can be taken quickly when the fire risk is detected. The system also has the functions of target tracking and behavior recognition so as to judge the authenticity and severity of the fire. Through modular design and environmental adaptability optimization, the system still operates stably in various complex environments.

A safety system for improving road compatibility of a vehicle includes a monitoring system and an integrated safety domain control unit. The monitoring system includes a vehicle external information monitoring module and a vehicle body posture monitoring module. The integrated safety domain control unit is configured to compute a collision condition between the vehicle and an obstacle based on data acquired by the vehicle external information monitoring module and the vehicle body posture monitoring module, the collision condition including a collision relative speed and a collision overlap rate, and determine, based on the collision relative speed and the collision overlap rate, whether to deploy an external airbag. A determination condition for controlling triggering of deployment of the external airbag includes determining whether the collision relative speed is less than a first speed threshold and / or whether the collision overlap rate is less than a first overlap rate threshold. The present disclosure further relates to a safety apparatus and method for improving road compatibility of a vehicle, and a medium, as well as a vehicle safety system, a vehicle safety apparatus, a method for enhancing safety of a vehicle, and a readable storage medium.

The invention discloses an active and passive safety fusion evaluation weight coefficient determination method and system, and relates to the technical field of automobile safety evaluation, and the method comprises the steps: obtaining active safety data and passive safety data; combining the active and passive data to obtain total sample data; constructing an analytic hierarchy model and a judgment matrix of each hierarchy; calculating a total level sequence of all indexes in the scheme layer to obtain a weight value of each index; performing weighted scoring on each data sample to obtain a total score; constructing a multi-layer perceptron model; and extracting the final weight of each index. According to the method, the vehicle speed after braking of the vehicle active safety system is taken as the collision speed of human-vehicle collision simulation in the passive safety system, and an active safety index and a passive safety index are associated to carry out active and passive safety fusion evaluation; and the index weight coefficient value for fusion evaluation is extracted through an analytic hierarchy process and construction of a multi-layer perceptron model, so that the data accuracy is high, the objectivity is high, and the comprehensiveness is high.

The invention provides a wearable safety system (100; 100 ') configured for use in combination with a helmet (200); 100 '). The system comprises a strap (1; 1 ') comprising two shoulder straps (3a, 3b); at least one inflator (10a, 10b), an ECU (13) and a battery (14). The ECU (13) is arranged in communication with the at least one inflator (10a, 10b). The system further comprises at least one airbag (9a, 9b). The system is configured to generate an enable signal upon detection of an accident. The at least one bladder (9a, 9b) is configured to be inflated upon generation of the activation signal and to be deployed to form at least one inflated C-shape covering a portion of a face region (302) and a neck portion (301) of the wearer. The invention also relates to a bag arrangement.

The present invention describes a system comprised of sensors, microcontrollers, wireless communication modules, and methods for utilizing said sensor system to determine, in real-time, a threat and / or theft of a catalytic converter. An alarm signal is then generated by connecting with the security system of a premises, if available, and relevant parties and law enforcement are notified of the threat and / or theft event.

The invention discloses an electric motorcycle intelligent safety control system based on multi-sensor fusion. The system comprises a sensor module, a data processing unit, a target detection and classification module, a danger level evaluation module and a motor control module, and realizes all-weather and all-around environmental perception and target detection through data fusion of a millimeter wave radar, a visible light camera and an infrared camera. And the power output of the motor is intelligently regulated and controlled according to the detected danger level, so that the driving safety of the electric motorcycle is improved. The problem of limitation of a single sensor of an existing electric motorcycle safety system is solved, the stability and reliability of the system in a complex environment are improved, and early warning and intelligent prevention and control of potential risks are achieved.

A security system of a building includes a processing circuit. The processing circuit is configured to detect, based on data of security equipment of the building, that a security alarm of the building is a false alarm and search, responsive to the detection of the false alarm, a database to identify a past corrective action accepted for implementation and at least one false alarm occurring after the past corrective action was accepted and before detection of the false alarm. The processing circuits is configured to generate a corrective action to reduce an occurrence of the false alarm based on a result of the search and implement the corrective action to update operation of the security equipment to reduce the occurrence of the false alarm.

Resealable bottles for beverages. A bottle may include a main body with an opening for receiving contents and a reservoir for storing contents, a lid, and a bottom, which is interchangeable with an accessory for changing a characteristic of the contents. The lid may close the bottle and / or facilitate consumption of its contents. The bottle may support one or more indicators, such as LEDs, including a safety indicator that is configured to activate when the safety system is active and the resealable bottle enters an unsafe state. The accessory may provide, for example, heating and / or cooling.

A system and method for managing permissions in a security system. A computing system is adapted to associate a first user account and a second user account with the security system, grant permissions associated with the security system for the first user account, and receive a request for activating the security system from the first user account. The computing system further adapted to prompt the second user account to assume control of the security system following receiving the request, modify permissions associated with the security system for the second user account in response to the second user account assuming control of the security system, and restrict permissions associated with the security system for the first user account following the second user account assuming control of the security system.

The invention provides a global full-automatic intelligent safety system and a control method. The global full-automatic intelligent safety system comprises monitoring equipment, a sensor, communication equipment, an alarm device and a server. Wherein the monitoring equipment and the sensor are connected with the server through the communication equipment; the server is provided with an edge server and a cloud server which form a collaborative architecture; the edge server is deployed with multiple containers, and independent image recognition modules are packaged in the containers; the edge server is also connected with the alarm device; the cloud server is provided with a shadow system of an edge server, a training module and an online upgrading module. In combination with the corresponding control method, the system is simple in structure and low in deployment and maintenance cost, local quick response is achieved through the edge and cloud server collaborative architecture, effective and quick updating is carried out through the cloud under the corresponding control method, and therefore stable operation of the safety system and the recognition accuracy of monitoring are guaranteed, and the safety performance of the system is improved. And the requirements of different scenes can be quickly adapted, and the system use difficulty is simplified.

The invention relates to the technical field of safety systems, in particular to a feedback system for early warning safety of elderly people living alone or left-behind children by using big data, which comprises a health monitoring module, a visual monitoring module, a weather information acquisition module, a processing computing platform and an early warning feedback system, the health monitoring module is used for monitoring the body health states of the old and children in real time, and the visual monitoring module is arranged in the family environment where the old and children are located to achieve visual recognition; according to the invention, early warning can be carried out when left-behind children touch dangerous areas in families, meanwhile, old people and children can be distinguished, early warning cannot be triggered when the left-behind children touch the dangerous areas, and disturbance can be reduced while safety protectiveness is improved.

The invention discloses a server security situation awareness and risk early warning system, and particularly relates to the technical field of network security, a data acquisition module collects server security situation feature data in real time to form a security situation feature data set; the data analysis module analyzes the data input rule and the feature matching model to generate an output result; the risk early warning module triggers early warning operation according to the analysis result; the evaluation module evaluates the sensitivity and coverage of the rule model, and generates a false report quality index and a missing report quality index respectively; the fuzzy reasoning module is used for reasoning an optimization direction based on an evaluation result; the feedback module adjusts the rule model according to the optimization direction and feeds back an optimization result to the data analysis module to form a dynamically optimized closed-loop system, so that the detection accuracy and coverage are improved; according to the method, the rule and the feature matching model can be dynamically adjusted, closed-loop optimization of the security system is realized, and the rule model is ensured to be always in an optimal state so as to adapt to a rapidly changing attack scene.

A fire safety system, comprising a first-level fire-fighting unit (11) and a second-level fire-fighting unit (12), wherein the first-level fire-fighting unit (11) cooperates with the second-level fire-fighting unit (12) to perform safety protection on batteries of the entire energy storage device, thereby improving the safety of the entire energy storage device, and solving the problems of the treatment effects of fire safety measures for existing energy storage devices not being ideal and the energy storage devices having safety hazards. Further disclosed are a centralized fire safety system, an energy storage device, and an energy storage system.

The invention discloses an AI automatic monitoring and early warning system for an oil refining chemical plant area and a use method thereof, and relates to the technical field of artificial intelligence and video analysis, and the AI automatic monitoring and early warning system comprises a data acquisition module, a preprocessing module, an AI analysis module, a danger awareness and early warning module and a feedback learning module, the data acquisition module comprises an image acquisition module, a sound acquisition module, a pressure acquisition module and a temperature acquisition module. The system is integrated with an existing safety system, an existing monitoring system, an existing equipment management system and the like in an oil refining chemical plant area to form a unified data platform and a unified management center, a visual user interface is designed, and the system has the functions of real-time video display, early warning information prompt, system state monitoring, historical data analysis and the like; therefore, effective monitoring and operation by management personnel are facilitated, the safety condition of the oil refining chemical plant area can be monitored in real time, potential risks can be automatically identified and pre-warned, the production process can be optimized, and the performance can be continuously improved through deep learning.

The invention belongs to the technical field of multi-chain collaboration and big data processing, particularly relates to a multi-value-chain collaboration evaluation method, and aims to solve the problem that in the prior art, efficient collaboration and collaboration evaluation of multi-value chains cannot be achieved, and consequently the risk of a safety system is high. The method comprises the following steps: collecting multi-source heterogeneous data of each influence factor on an enterprise multi-value chain; carrying out weight distribution on the influence factors on each value chain by adopting a fuzzy comprehensive evaluation method to obtain an influence factor set on each value chain; adopting an analytic hierarchy process to obtain an interaction relationship among the value chains; constructing a node feature matrix and an adjacent matrix, and inputting the node feature matrix and the adjacent matrix into a pre-constructed graph neural network to obtain a final node embedding vector; determining an optimal decision path in combination with the final node embedding vector; and according to the optimal decision path, collaboration of the enterprise multi-value chain is carried out, and a collaboration evaluation report is generated. According to the invention, efficient collaboration and evaluation among multiple value chains are realized, and the stability and security of an enterprise security system are ensured.

A ladder safety system is configured to prevent falls from prematurely stepping off the ladder by providing a left-side panel and right-side panel that extends from the sides of the ladder out from a front side of the ladder. Also, the ladder safety system has step extensions from at least the first step and preferably from the first and second step that create a larger step extending out from the front side of the ladder to catch a person's foot when they step back prematurely thinking they are lower on the ladder than they actually are. Also, the left-side and right-side panel prevent a person from stepping off to the side of the ladder when they think they are lower on the ladder than they are.

A safety system for a boat, watercraft or other vehicle includes a kill switch connected to the motor for preventing the motor from running under dangerous circumstances. The system may include proximity sensors operatively connected to the kill switch, so that the motor only runs when the proximity sensor detects a person properly positioned at the captain's console. Other sensors may form an array to communicate with the kill switch, to automate certain features and systems, or to otherwise provide alarms upon detection of dangerous situations, including a carbon monoxide detection sensor system, gate sensors, anchor-down sensors, ladder sensors, ambient light sensors, optical rain sensors for operating an automated windshield wiper safety system, an array of cameras strategically positioned around the periphery of the watercraft for monitoring purposes, and an automated anchor / navigation light system.

A natural language query is received via a chatbot to monitor and / or control one or more security devices of the security system. The natural language query is processed to identify one or more descriptors of one or more security system devices that are a subject of the natural language query and to identify a desired result of the natural language query. One or more security system commands are assembled and submitted to the security system to identify one or more specific security system devices of the security system that correspond to the natural language query. One or more security system commands are assembled and submitted to each of the specific security system devices of the security system that are tailored to achieve the desired result. Confirmation from the security system is received.

The invention relates to a method for operating an autonomously controlled vehicle (2), comprising at least one automated driving system (8) for controlling a vehicle journey, a vehicle interior (4) for a vehicle occupant (6), with at least one comfort system (10) for providing a comfort function for the vehicle occupant (6), and with at least one safety system (12) for protecting the vehicle occupant (6), an interior sensor (14) for detecting an interior situation (16) of the vehicle occupant (6), and an environment sensor (18) for detecting an environment situation (20), wherein a current actual driving situation is detected on the basis of system data (36) of the driving system (8), the comfort system (10) and / or the safety system (12) as well as sensor data (38) of the interior sensor (14) and the environment sensor (18).a key parameter (40) relating to the vehicle occupants (6) for a future driving situation is predicted and evaluated based on the system data (36) and the sensor data (38), based on the evaluation a vehicle behavior to realize a target driving situation is determined, the specific vehicle behavior is adapted taking into account an interaction between the interior situation (16) and / or the exterior situation (20), and the adapted vehicle behavior (42) is set by controlling the driving system (8), the comfort system (10) and / or the safety system (12).

A security evaluation device calculates a threat evaluation value for each of all threats present in a system configuration plan based on an evaluation value of a probability of a threat occurring, an evaluation value of an execution frequency of the threat, and an evaluation value of an effectiveness of a mitigation measure for the threat that is possessed by a countermeasure against the threat, which are defined for each type of security threat, and calculates a quantitative security evaluation value for the system configuration plan based on the threat evaluation values calculated for each of all of the threats.

The present disclosure relates to a method for an elevator safety system, and to a computer-readable medium therefor. Provided is an abnormal sign-detecting elevator that can prevent safety-related accidents by means of various sensors, the elevator (20) comprising an elevator car (21), a governor (22), and a rope (23), wherein the elevator car (21) can move vertically along guide rails (25), the governor (22) comprises an upper sheave (22a) and a lower sheave (22b), and the rope (23) winds around the upper sheave (22a) and lower sheave (22b).

Disclosed are methods and / or a system of incident based camera device activation in a safety system of a structure having a fixed piping system implemented therein to supply breathable air thereacross. In accordance therewith, one or more sensor(s) associated with one or more component(s) of the safety system is integrated with a computing platform executing on a data processing device. Based on the integration of the one or more sensor(s) with the computing platform, one or more environmental parameter(s) of the one or more component(s) of the safety system is sensed. One or more camera device(s) in a vicinity of and / or on the one or more component(s) of the safety system is automatically activated based on determining, from the sensing, occurrence of an incident.

The invention discloses an operation real-time monitoring system based on risk factor dynamic assessment, and relates to the technical field of desilting operation risk assessment, the system can comprehensively assess various potential risks in the desilting operation process through multi-dimensional environmental data acquisition and real-time monitoring, and the risk factor dynamic assessment is realized. Comprise dam instability, water flow shearing force, sediment disturbance, soft foundation stability and the like. The system calculates comprehensive risk factors according to the data, timely identifies risks and triggers early warning, and ensures the safety of an operation area. The system can dynamically evaluate the soil liquefaction risk by monitoring the soil liquefaction factor and the volume change of the workboat in real time, and prevents the workboat from inclining or sinking. In addition, the system generates and implements specific emergency strategies according to different early warning instructions, and takes effective protective measures to deal with sudden risks. The safety and efficiency of the dredging operation are improved, the potential accident risk is reduced, and the sustainability of the dredging operation is guaranteed.

A smart lighting system is described in which an array of smart luminaires such as LED luminaires forms a network, each luminaire comprising a microphone, a power source or driver, and a network communication device. The system is configured such that in response to a sound indicative of a dangerous incident such as a gunshot, the network conveys information to a command center to raise alerts about the dangerous incident, and the system in turn directs the network to modify its light output in order to assist the evacuation of individuals in the building or to assist in mitigation of the threat posed by the dangerous incident. Other countermeasures can be implemented as well.