1013 results about "Safety zone" patented technology

Various embodiments of a system and method for a smart work zone are described. In one example, the system includes smart cone devices configured to transmit smart cone device localization data, a wearable device comprising a processor configured to transmit worker localization data of a worker wearing the garment device and to receive an alert, and a base station. The base station includes an internal edge computing system configured to process the smart cone device localization data to define a virtual geofence boundary of a safe area, process the worker localization data, broadcast a location of the worker wearing the wearable device, and in response to a vehicle or the worker approaching the virtual geofence boundary, provide an alert to at least one of: the worker wearing the wearable device, a passing motorist, or a connected and automated vehicle (CAV).

The invention provides a BIM-based central air conditioner safety monitoring method and system. The method comprises the following steps: generating a BIM model of a building; according to the internal structural layout of the building in the BIM model and the arrangement of the central air conditioning equipment, carrying out initial safety area division on the building, carrying out dynamic adjustment based on a risk index of a time change regular term, and updating the risk index into the BIM model in real time; fault features are extracted from the real-time environment data and the equipment state data, and whether a fault exists or not is preliminarily judged; constructing a fault traceability model according to a fault positioning result, and determining a fault propagation path; a digital twinborn model is constructed for risk prediction, and a preventive maintenance plan is automatically generated; and designing an adaptive optimization algorithm based on reinforcement learning to maximize the operation efficiency of the system and minimize the risk level, and performing closed-loop feedback optimization. The invention provides a comprehensive, intelligent and efficient central air-conditioning system management scheme, and has wide application prospect and practical value.

The invention relates to the technical field of data processing, in particular to a tunnel fire temperature field prediction and safety area division method and system, and the method comprises the following steps: carrying out the preprocessing of the historical data of a tunnel fire, and obtaining the standardized data; establishing a combustion equation of the tunnel fire based on the standardized data; constructing a combustion model of the tunnel fire according to the combustion equation; using the standardized data to train the combustion model; and predicting a temperature field of a tunnel fire according to the trained combustion model, and imaging a prediction result to divide a safety area. According to the method, the combustion model of the tunnel fire is constructed based on the physical constraint neural network, the most matched combustion model is selected according to different tunnel fire conditions, the temperature field of the tunnel fire is predicted in real time, the prediction result is visualized, the accuracy and real-time performance of tunnel fire prediction are effectively improved, and the tunnel fire prediction efficiency is improved. And according to a visualization result, a safety area is divided, and powerful support is provided for emergency rescue.

A personal safe area is determined for extended reality (XR) devices, such as head mounted devices in virtual reality (VR) sessions, sharing a common larger play area. The personal safe areas may be sized based on user size, may have radii centered on the XR device and parallel to a floor, and may move with the XR device as the XR device moves in an immersive reality session. A notification indicating proximity to another XR device may be generated, and the notification may indicate the direction from which the other XR device is approaching. Also contemplated is real time adjusting an XR gameplay, game display or game flow of one or more XR devices to avoid overlap of safe spaces by shifting virtual game objects in a safer direction.

The invention relates to the field of vehicle intelligent control, in particular to a vehicle control method and a vehicle. According to the method provided by the embodiment of the invention, by monitoring the passive rotation amount of the vehicle door in real time, when the vehicle door is passively rotated due to external force, the target is always clear to guide the corresponding rotating vehicle door to the closed position or the safe area no matter whether the single vehicle door or the two vehicle doors are controlled to rotate at the same time. Therefore, in the whole control process, the vehicle doors cannot be simultaneously located in non-safe areas which are possibly in contact with each other, and the safety of the positions of the vehicle doors in the using process of the vehicle is guaranteed. Meanwhile, the whole process does not need manual processing of the user, and smoother and more efficient vehicle using experience is brought to the user.

The invention belongs to the field of unmanned aerial vehicle emergency control systems, and relates to a risk identification and emergency method when an unmanned aerial vehicle flies in an airspace adjacent to an expressway, and the method comprises the steps: obtaining the balance state of the unmanned aerial vehicle through constructing a six-degree-of-freedom dynamic model and incorporating environmental factors and control intentions; dynamically comparing the balance state with real-time data to obtain a state deviation, deducing the fault probability of the unmanned aerial vehicle according to the state deviation, and realizing sensitive early warning of possible faults of the unmanned aerial vehicle; besides, the method constructs a double-layer linkage framework of an electromagnetic safety boundary and a physical safety boundary, realizes safety risk identification in combination with a fault probability, and ensures that a safety area between the unmanned aerial vehicle and a motorcade on a highway can be represented by a risk value along with speed, motorcade density and interference intensity; the fault probability of the unmanned aerial vehicle flying in the air is considered, when the fault probability is larger than a preset threshold value, the out-of-control state of the unmanned aerial vehicle is judged, a corresponding control strategy is adopted, and the flight safety of the unmanned aerial vehicle during partial or comprehensive out-of-control is guaranteed.

The invention discloses a safety-enhanced trajectory planning method based on an Astar algorithm, and belongs to the technical field of intelligent robot navigation and path planning, and the method comprises the following steps: 1, constructing a grid map, and marking an obstacle region; 2, establishing a security evaluation mechanism, evaluating the surrounding environment of the path node, and quantifying a security index; 3, in a node expansion process, combining a heuristic item and a security index in a cost function to realize priority search for a security region during path selection; 4, key nodes of the obtained initial safety path are extracted based on a Douglas-Peucker algorithm to generate a rectangular safety corridor, and smoothing processing of the initial path is achieved based on a segmented Bezier curve. On the basis of guaranteeing path optimality, safety is used as an auxiliary guiding basis in the path searching process, and the path searching efficiency is improved. Therefore, consideration of the path length and the environmental risk is realized, and the navigation path with higher execution safety is generated.

The invention relates to a mechanical arm autonomous obstacle avoidance method and device based on deep reinforcement learning and a medium, and solves the obstacle avoidance problem of a mechanical arm in the process from an initial position to a target position through a reward function comprehensively designed in the deep reinforcement learning. Multiple aspects of obstacle avoidance of the tail end of the mechanical arm, obstacle avoidance of the mechanical arm body, self-collision avoidance, accurate reaching of a target position, smoothness of a movement track and the like are comprehensively considered. When an environment map is uncertain or obstacles dynamically change, the method has high adaptability. The working area of the mechanical arm is divided into the safety area, the warning area and the dangerous area, so that the mechanical arm can adopt a stricter obstacle avoidance strategy when the mechanical arm is in the dangerous area, and collision between the mechanical arm and the obstacle is avoided. Compared with the prior art, the method has the advantages of high success rate, wide application range, high reliability and the like.

The invention relates to a safe starting control method, device, equipment and medium for a bootstrap drive inverter, and the method comprises the steps: obtaining a detection voltage representing an output filter inductance voltage after responding to any starting event and before formally transmitting a drive signal; comparing the negative voltage with a preset negative voltage safety threshold value; only when the detected voltage is higher than the safety threshold, a driving enable signal is generated to allow the inverter to be normally started; otherwise, generating a driving blocking signal, carrying out detection and judgment again after waiting for preset time delay, and circulating the process until the system state enters the safe area; the method is realized by modifying a control algorithm, no power hardware needs to be added, the starting impact risk is eliminated with low cost, and the contradiction between the hardware limitation of a bootstrap drive circuit and the negative residual voltage possibly existing on the output inductance of the inverter is solved; therefore, the safety problem of direct connection between the impact current and the bridge arm during starting in an unfavorable initial state is solved.

The invention provides a construction site safety supervision method and system based on multi-mode intelligent perception, and relates to the technical field of highway construction supervision. A construction area is scanned through a 5G camera, multi-mode intelligent sensing data such as videos, positioning and environment sensors are fused, a three-dimensional model of a construction site is constructed, and the positions of equipment and personnel are accurately determined. Beidou positioning and safe area setting are combined, real-time safety detection is carried out, illegal intrusion of external vehicles and personnel is effectively prevented, and construction of equipment and personnel outside a safe area is avoided. According to the method, illegal behaviors of not wearing safety helmets and the like are intelligently identified by using AI, post-accident tracing is realized through the Internet of Things, accurate traffic guidance information is published in combination with Atdes and Baidu maps, the collision risk and potential safety hazards are reduced, and the safety of a highway construction site is comprehensively improved.

The invention relates to the technical field of geo-fence triggering, in particular to a multi-mode positioning data fused GEO fence triggering method and triggering system. The method comprises the following steps that according to the distance between equipment and the fence boundary, a layered positioning strategy is adopted to demarcate a safe area, a transition area and a critical area; when the device is located in the safe area, outputting a coarse position coordinate of the device and a corresponding coarse positioning confidence coefficient by adopting a low-power-consumption coarse positioning algorithm; when the equipment is located in the transition area, fusing the GPS data and the IMU data by adopting an adaptive fusion algorithm to obtain an intermediate fusion position, an intermediate fusion speed and an intermediate positioning confidence coefficient; fusing the multi-modal data when the equipment is located in the critical zone, and predicting the probability that the equipment invades the fence by combining a trajectory risk assessment algorithm based on the equipment acceleration and the distance between the equipment and the fence boundary. Through hierarchical positioning strategy and multi-modal data fusion, the problems of insufficient precision and high power consumption of a single positioning mode in a complex scene are solved.

The invention relates to the technical field of virtual reality redirection, and particularly provides a redirection walking method and system based on deep reinforcement learning, a terminal and a storage medium, and the method comprises the steps: obtaining the physical positions of a user in a real space and a virtual space in real time; dividing a walkable area of a user in a real space, and calculating a space feasible entropy in the real space; calculating a real-virtual environment state; based on the real-virtual environment state and the space feasible entropy, reward functions of deep reinforcement learning are calculated, and the reward functions comprise a position reward function, a space alignment reward function and a reset penalty function; judging whether the walking state of the user needs to be reset or not, and if not, using a position reward function and a space alignment reward function; and if so, calculating the optimal reset direction, and guiding the walking path of the user to the optimal safe area. According to the invention, the collision probability between the user and the obstacle is greatly reduced.

The invention relates to the technical field of fire safety, in particular to a multi-dimensional fire safety management system which comprises an environment monitoring module, a data analysis module, a real-time video monitoring module, an intelligent decision module and a self-adaptive evacuation navigation module. The data analysis module processes and analyzes the collected environmental data, the real-time video monitoring module monitors the internal situation of the building by adopting a high-resolution camera, the intelligent decision-making module generates a fire coping strategy, and the self-adaptive evacuation navigation module dynamically generates and updates a safe evacuation route in the building. The self-adaptive evacuation navigation module is introduced, so that a safe evacuation route in the building can be dynamically generated and updated in real time. The system can adjust the evacuation route according to the current environmental condition by analyzing the fire behavior development and the personnel distribution condition in the building in real time, thereby effectively preventing the personnel from entering a high-risk area by mistake, and ensuring that the personnel can be quickly and orderly guided to a safe area in an emergency.

A method for determining and adjusting the landing safety area of ​​an aircraft based on laser radar. It includes the following steps: setting a landing safety area; calculating whether there are points in the landing safety area that are more than 1 / 2H in height; moving the landing point A outward; calculating the height difference between the highest point and the lowest point in the landing surface, if the height difference is ≤10cm, it is considered to be relatively flat; otherwise, moving the landing point A outward. Beneficial effects of the present invention: 1. It can accurately determine the landing safety area, thereby greatly improving the safety of the aircraft during landing, which is of great significance; 2. It can automatically adjust the landing safety area without the need to pre-equip the landing point, thus saving energy consumed by the transfer, which has very important economic benefits; 3. As the price of laser radar becomes lower and lower, it has a higher cost-effectiveness than equipment such as millimeter-wave radar, image recognition and other equipment and technologies, so it has a wider application prospect.

An apparatus for controlling autonomous driving of a vehicle is introduced. The apparatus may comprise a controller configured to determine, in a merging section on a road, at least one area of a safety area, a yield area, or a stop area, wherein the safety area may comprise a first part of the merging section designated for vehicles that have a right of way, the yield area may comprise a second part of the merging section designated for vehicles that should yield to traffic on the road, and the stop area may comprise a third part of the merging section designated for vehicles that should stop before merging onto the road, and determine a driving strategy of the vehicle for the at least one area, and a brake configured to, based on the driving strategy, adjust a speed of the vehicle.

The invention discloses a simulator supporting multiple debugging permissions. According to the embodiment of the invention, the simulator supporting multiple debugging permissions comprises a simulator management module which comprises a configuration unit, and the configuration unit is used for configuring the debugging permissions; a storage unit of the simulator hardware module is divided into a safe area and a non-safe area; the security area is used for storing security data, the non-security area is used for storing non-security data, and the debugging permission comprises a security mode and a limited mode; in the security mode, allowing access to the security area and the non-security area; and in the limited mode, the access to the safe area is prohibited, and the access to the non-safe area is allowed. According to the emulator supporting the multiple debugging permissions, debugging requirements of different security levels can be effectively distinguished, and flexible access control is provided for development and maintenance while data security is guaranteed.

The invention discloses an aircraft deployment method based on a dynamic airspace network and reinforcement learning, and relates to the field of air traffic management, and the method comprises the steps: obtaining flight information and task priority weight information of each flight in a historical time period and a current time period; dynamically dividing the airspace into an independent sub-airspace and a shared airspace by using flight information in a historical time period; calculating the safe area of each flight through a space-time buffer zone model, and determining a flight path according to the safe area; and according to the flight information, the airspace division result and the flight path, a release action instruction set including height adjustment, course correction and speed change is generated, and real-time deployment is performed on the flight. The technical effects of the invention lie in that airspace changes can be responded in real time, flight paths of flights are optimized, potential conflicts are reduced, and the airspace utilization rate is improved, so that the air traffic control efficiency and the flight safety are improved.

According to the motion planning method and device for the multi-mechanical-arm cooperative task, a large number of potential conflicts are actively avoided in the early stage of task allocation through division of a virtual wall and a safety area and a danger area, the difficulty and the calculated amount of follow-up track collaboration are remarkably reduced, and the success rate and the efficiency of planning are improved. Cost and load balance are considered in the task allocation stage; in the path point sorting stage, minimizing the total movement distance and the total completion time is taken as a target; and track generation adopts a time optimal algorithm. The layered decoupling design avoids the huge calculation overhead of centralized planning, and meanwhile, the quality of a final solution is ensured through the optimization strategy of each stage. The innovative cost function takes collision distance into consideration, and guides the planner to select a safer path. Through layered and ordered collision solution strategies, such as deceleration, local re-planning and optimal waiting, it is ensured that a collision-free solution can be always found in a complex dynamic environment, and robustness is high.

An autonomous mobile device (AMD) may move around a physical space while performing tasks. The AMD may have sensors with a field of view (FOV) facing forward. As the AMD moves forward, a safe region is determined based on data from those forward-facing sensors. The safe region describes a geographical area that is clear of obstacles during recent travel. If the AMD moves outside of the FOV, such as moving backwards, a check is made as to whether the AMD remains within the safe region. If a portion of the AMD moves beyond the safe region, the AMD stops. This prevents the AMD from colliding with obstacles that are outside of the safe region and also outside of the FOV while moving.

The invention discloses a bulldozer remote control system which comprises a vehicle-mounted control system, a remote control cabin control system and a handheld remote control system. The vehicle-mounted system monitors the environment through positioning navigation and data analysis, and coordinates the operation and protection of the bulldozer; the remote control cabin system remotely controls walking, steering and operation of the bulldozer, and has the functions of remote automatic fire extinguishing, manual fire extinguishing and spraying. The handheld remote control system carries out remote operation through a wireless handle and a switch, the remote operation comprises spraying, air inlet cut-off, accelerator adjustment and machine start-stop switching, and quick response under the emergency condition is ensured. By means of the system, the problems that an existing remote control bulldozer is poor in performance and lacks environment recognition, safe area protection, data recording, self-learning and upgrading capacity in scenes such as a fire scene, high temperature and low visibility can be solved.

The invention relates to the technical field of intelligent security and protection, and discloses an intelligent security and protection alarm method and system based on an intelligent park. The method comprises the following steps: acquiring original security and protection data by using sensing equipment arranged in a smart park; performing standardization and redundancy elimination processing on the original security and protection data, dividing safety areas of the park through a pattern recognition algorithm, calculating a load intensity index of each area, and generating a security and protection situation summary; according to the security situation summary, a heuristic search algorithm is adopted to determine alarm trigger parameter initial values including detection sensitivity and alarm intervals, and a basic alarm parameter group is generated; performing nonlinear correction on the basic alarm parameter group, and outputting an environment perception alarm parameter group; training the historical security data set by adopting a neural network model, and analyzing the interaction between the load and the threat to obtain a threat diffusion model; and comparing the threat diffusion model with the real-time security data points, performing difference measurement, reconstructing alarm trigger logic according to a measurement result, and completing autonomous regulation and control of security and protection of the smart park.

Systems and methods for generating safety zones for a mobile robot are described. The systems and methods can include receiving information about a cart or topper to be used on the mobile robot such as a size and number of posts of the cart. The systems and methods can further include generating safety zones based on the type of mobile robot and the information about the cart or topper. The systems and methods can further include operating the mobile robot based on the safety zone such that when an object is detected within the safety zone, a controlled stop of the mobile robot is triggered.

The invention discloses an under-mine environment accurate positioning system based on a UWB technology, and relates to the technical field of data processing and positioning, an underground area is divided into a safe area and a dangerous area by obtaining the structure risk value of each sub-area and combining the structure risk value and the position information of the corresponding sub-area, and the safe area and the dangerous area are accurately positioned. A plurality of rescue robots are arranged in the underground area; acquiring position information of the mobile tag, displaying the position information on an electronic map, generating an air quality coefficient, and dividing the plurality of sub-regions into risk regions and safety regions according to the air quality coefficient; and sending inquiry information to the miner, acquiring a corresponding safety coefficient, and if the acquired safety coefficient is lower than a safety threshold value, planning a support path to the miner for the rescue robot, so that the rescue robot rescues the miner along the support path. After the miner is found according to the position information of the miner, the miner is rescued through guidance of the rescue robot, and the miner is prevented from getting lost and being lost.

The invention provides a dynamic adjustment method for robot parameters, electronic equipment and a storage medium, and the method comprises the steps: obtaining the current position of a collaborative robot and the current information of at least one pre-configured safety region corresponding to the collaborative robot, the current information of the security area comprises plane information of the security area and current function information of the security area; according to the current position and the current information of each safety area, a target safety area where the collaborative robot is located currently is determined, the target safety area comprises a working sub-area and a collaborative sub-area, and the collaborative sub-area is pre-configured with corresponding safety parameters; and adjusting the current safety parameter of the collaborative robot to be the safety parameter of the collaborative sub-region in the target safety region, so that the collaborative robot executes collaborative operation according to the safety parameter of the collaborative sub-region. Dynamic adjustment of the safety parameters of the collaborative robot is achieved, and the requirements of different safety areas for the safety parameters can be met.

The invention discloses a system based on an unattended power station platform. The system comprises a system architecture module, an information processing module and an operation module. The system architecture is divided into four areas, the safety area III is an overall architecture construction area, hardware is deployed in the safety area III based on a J2EE technical system, and the safety area III covers the functions of model management and the like. And the information processing module stores and reads the alarm data by adopting a Kafka message queue technology, and acquires the in-station real-time alarm data by using a 104 scheduling protocol. The running operation module is provided with a home page submodule for displaying key data and alarm and event information of a power station; the basic data management sub-module manages roles, users, an equipment library and a point table information library; the signal identification sub-module classifies the signals and constructs a working condition signal reference library; the event handling sub-module displays and handles emergency events and integrates experience; and the report management sub-module realizes unified generation and management of reports. The system aims at solving the problem in unattended transformation of the power station and improving the operation efficiency and safety.

The invention relates to the technical field of environment monitoring, in particular to an environment parameter real-time early warning method and system for a digital chicken house, and the method comprises the following steps: collecting ammonia gas concentration, temperature and humidity and illumination intensity data in a chicken house, uniformly integrating and generating a monitoring record, extracting a safety interval, counting the exposure time of ammonia gas, and judging a multi-factor deviation state; and carrying out conjoint analysis on environment distribution change, and outputting a risk state and early warning information. According to the method, multi-source environment data are integrated through a unified time reference, the time sequence consistency among parameters is improved, the identification capability of low-concentration long-term exposure is enhanced by screening an ammonia gas safety interval and counting the exposure duration, and a multi-factor time sequence offset feature is constructed by collecting the deviation state of temperature and humidity and illumination intensity; the conjoint analysis of exposure and deviation distribution is combined, the continuity and accuracy of environmental risk judgment are improved, high-risk time periods and monitoring data thereof are extracted, and the positioning and response efficiency of abnormal states is enhanced.

To provide a power generation device capable of reducing a safety area with respect to the case of kite falling.SOLUTION: A power generation device comprises a support body, a kite, a movable body, and a power generator. The support body includes an inclined plane which becomes an upward inclination from a windward side to a leeward side. The kite includes: a flying body; and a first cord and a second cord which are connected to the flying body. The movable body is connected to the first cord and the second cord, includes a kite control unit which enables the flying body to fly in the air along a figure-of-eight shaped orbit by changing a cord length difference which is a difference between a length of the first cord and a length of the second cord, and can reciprocate in the inclined plane to the leeward side and the windward side in accordance with a magnitude of traction force received from the kite. The power generator includes a power generation mechanism installed on the ground and a connection part, which connects the power generation mechanism with the movable body, and converts the reciprocation of the movable body on the inclined plane into electric power.SELECTED DRAWING: Figure 1

The invention relates to a quadruped robot mountain path planning method based on deep reinforcement learning, which comprises the following steps: S1, constructing a mountain digital terrain model, dividing the mountain digital terrain model according to a gradient grading principle, and defining a safe area and a dangerous area; s2, introducing a black hole principle to optimize and improve an artificial potential field method, constructing a global slope potential field, and simplifying a high-dimensional complex environment; s3, performing weighting processing on potential energy in the potential field, inputting the potential energy into a deep reinforcement learning network, guiding the quadruped robot to avoid the abrupt slope area and move towards a target point, and improving the training speed of the algorithm; s4, introducing a gradient security domain and a gradient reward function, and re-planning a real-time path; according to the path planning method combining the artificial potential field method and the deep reinforcement learning, the robot can plan an optimal path with a proper gradient and a short distance only according to interaction data of the current and historical environments, and the problem that path planning is difficult due to the fact that the terrain gradient is too large in the complex mountain environment is solved.

The invention belongs to the technical field of road slope monitoring, and discloses a multi-source information fusion road slope comprehensive monitoring and early warning system, which comprises the following steps: acquiring slope geometric data and soil mass data; obtaining soil body properties based on the constructed soil body viscosity prediction model; the method comprises the following steps: carrying out block division on a side slope to obtain side slope blocks, carrying out stability calculation on the side slope blocks to obtain a stability coefficient, constructing a minimum stability coefficient objective function based on the stability coefficient and determining a minimum division scheme of the stability coefficient, and carrying out block aggregation on the minimum division scheme of the stability coefficient through a clustering algorithm to obtain # imgabs0 edge block clusters; performing safety analysis on the edge block cluster to obtain a safe area and a dangerous area; constructing a stability prediction model based on the safety area, and performing future safety analysis on the safety area through a prediction result of the stability prediction model; the accuracy and timeliness of slope monitoring are greatly improved.