9 results about "Unsafe condition" patented technology

Smart vehicle-to-everything (V2X) preemptive connections for emergency and / or potential accident scenarios. A V2X-enabled vehicle may determine a current route of the vehicle and high-risk areas through which the vehicle may travel (e.g., a hospital zone, high pedestrian traffic area, etc.). The vehicle may determine a distance (d) from a beginning of the high-risk area and begin establishing a V2X connection upon reaching the determined distance. The V2X-enabled vehicle may also, or alternatively, pre-emptively establish a V2X connection upon detecting an event initiative of an emergency, a hazardous situation, or a potential emergency. Examples of such events may include a sharp turn, a vehicle speed exceeding a speed threshold, a sudden acceleration or declaration, etc. A preemptive V2X connection may, for example, enable vehicles to begin communicating with one another faster in case of a threat, emergency, or unsafe conditions for vehicles in the area.

The invention discloses a power worker behavior monitoring method and system based on AI vision, and the method comprises the steps: collecting and preprocessing continuous real-shot images of a power worker in a working process, obtaining a preprocessed image, determining the limb features of a human body, and carrying out the prediction through a preset AI model and the limb features, thereby obtaining an action prediction image; determining motion characteristics of a human body in the motion prediction image to determine a motion type; based on the working scene and the action type in the preprocessed image, evaluating the behavior of the power operator to obtain a behavior safety evaluation value; and determining a state risk level based on the behavior safety evaluation value, and sending out a corresponding safety early warning prompt. According to the invention, the AI vision is applied to behavior monitoring of the electric power operation personnel, potential dangerous behaviors or unsafe states can be detected in time, corresponding safety early warning prompts can be given out, and the working personnel can be reminded to take measures in time to avoid accidents, so that the accident risk is effectively reduced, and the personnel safety is guaranteed.

A computer-implemented method, system, and computer program product for detecting crashes and unsafe conditions. Real-time data on vehicle movements and road users are captured. The captured real-time data is processed to detect and track vehicle and road user movements. Based on the processed real-time data, trajectories of the vehicle and road user movements are predicted. Such predicted trajectories are analyzed, where a risk assessment for each detected vehicle movement and road user movement is conducted based on such analysis. A potential crash or unsafe condition is then identified in response to the risk assessment for a detected vehicle movement or road user movement exceeding a threshold value. Upon identifying a potential crash or unsafe condition, a warning message or alert of an impending crash or unsafe condition is generated. Such a warning message or alert is transmitted to the drivers and / or vulnerable road users so as to prevent a collision.

The invention relates to a manufacturing workshop security situation awareness method based on a virtual-real mixed data set. The method comprises the following steps: classifying unsafe states of workers in a manufacturing workshop, and constructing a quantitative evaluation system of a comprehensive safety situation and a safety level dynamic evaluation model; aiming at the problem of scarcity of real data of an unsafe state of a manufacturing workshop, a workshop unsafe state virtual data set is generated through a Stable Diffusion model, and after the workshop unsafe state virtual data set is mixed with a real data set, a target detection network is trained to realize real-time detection of the real workshop; according to the visual detection result and the multi-source discrete unsafe points, the current safety level is judged in real time in combination with an established comprehensive level judgment model; and the change of the future security situation is predicted through a Markov model, and targeted early warning measures are formulated. According to the invention, the safety level of the workshop can be detected in real time, the change of the future safety situation can be predicted, and early warning and processing can be carried out when the safety risk of the workshop is too high.

The present invention is entitled "System and method for calculating flight control for landing a vehicle". The present invention discloses a method, system and non-transitory computer-readable medium for landing a vehicle. For example, the method may include: receiving a landing zone confirmation from a service before a descent transition point, the landing zone confirmation including landing zone location information and an indication that the landing zone is clear; determining a landing flight path based on the landing zone location information; and when the vehicle begins to descend to the landing zone using the landing flight path: receiving landing zone data from at least one of a radar system, a camera system, an altitude and heading reference system (AHRS), and a GPS system; performing an analysis based on the landing zone data to determine whether an unsafe condition exists; and calculating flight control for the vehicle to continue the descent or modify the descent based on the analysis.

Techniques are disclosed for an unsafe hot spot detection and reporting system to identify unsafe “hotspot” zones. The system functions to identify hotspot zones that are associated with an increased number of detected warnings regarding unsafe conditions, vehicle collisions, near misses, or other hazardous events. The hotspots are determined based upon historical data that may include safety-based warnings issued from vehicle with respect to in-vehicle monitoring data or other data sources. The system leverages the hotspot location information to identify a safety data model (SDM) rule and automatically adjust one or more safety data model (SDM) parameters of the SDM rule such as follow distance, speed settings, etc., and / or to route the vehicle to an alternate course to avoid an identified unsafe hotspot zone.

A work monitoring assistance device (1) of the present disclosure comprises: an unsafe determination unit (17) that, using sensor information acquired by a sensor (2) which detects the conditions of a work site, performs first detection processing for detecting whether or not an environment in which a worker working at the work site is present is an unsafe environment, and second detection processing for detecting whether or not the worker is in an unsafe state, that determines an occurrence of an unsafe event if the result of the first detection processing and the result of the second detection processing indicate that the worker is present in an unsafe environment and the worker is in an unsafe state, and that generates unsafe information indicating the determination result; and a transmission / reception unit (11) that outputs the unsafe information.

Techniques are disclosed for an unsafe hot spot detection and reporting system to identify unsafe “hotspot” zones. The system functions to identify hotspot zones that are associated with an increased number of detected warnings regarding unsafe conditions, vehicle collisions, near misses, or other hazardous events. The hotspots are determined based upon historical data that may include safety-based warnings issued from vehicle with respect to in-vehicle monitoring data or other data sources. The system leverages the hotspot location information to identify a safety data model (SDM) rule and automatically adjust one or more safety data model (SDM) parameters of the SDM rule such as follow distance, speed settings, etc., and / or to route the vehicle to an alternate course to avoid an identified unsafe hotspot zone.