The present invention relates to a safety compliance, identification, and security monitoring system that includes a monitoring device operable to capture images/videos of a predefined area and persons and events within the area. The monitoring device is further operable to determine whether persons within the area are wearing required personal protective equipment. In one embodiment, the monitoring device initiates an alert a safety equipment infraction. In one embodiment, the system is operable to further record an incident report identifying the nature, date, and location of the infraction, as well as the identity of the person committing the infraction. In one embodiment, the system is operable to monitor various external conditions, such as heat, humidity, smoke, and initiate an alert of the external condition detected. In one embodiment, the system detects quality assurance/quality control issues, including situations involving inspecting equipment, tools, and/or materials for non-conformance.

A system and processes detect, identify a Unexploded Ordnances (UXOs) and/or categorize UXOs in near real-time using Unmanned Aerial Vehicles (UAVs). In accordance with various disclosed embodiments, the equipment includes such UAVs (also referred to herein as drones,) that include a plurality of sensors for imaging the terrain of a geographic area to analyze the terrain and detect anomalies and/or changes that may be indicative location of UXOs, for example, soil moving activity performed in association with the burying the UXO. Additionally, the UAVs include processing equipment, e.g., one or more small form factor devices, e.g., Next Unit of Computing (NUC) compute elements or the like, that provide processing power to provide EDGE computing on the data gathered at the UAV.

Provided is a management assistance system capable of saving man-hours and improving safety in construction or civil engineering works by the worker. The system contains a database that stores attribute information for BIM or CIM; a plurality of target markers attached to specific structures; a mobile robot structured to patrol a yard of the building or the civil engineering structure, and to scan the periphery with a scanner, thereby acquiring three-dimensional point cloud data; and a computer apparatus structured to recognize position and posture of the specific structures having the target markers detected by analyzing the point cloud data, and, if the identification information of the target markers acquired by the computer apparatus is corresponded to an existing object stored in the database, the information regarding the existing object is updated with reference to the position and the posture of the specific structure recognized by the computer apparatus.

An estimated target position is generated based on agent data received from an agent sensor system of a reinforcement learning (RL) agent and teammate data received from a plurality of teammate RL agents. An information metric reward is generated based on a confidence level associated with the estimated target position. The confidence level is based on the estimated target position and historical estimated target positions. A distance metric reward is generated based on an agent position and the estimated target position. A combined reward is generated based on the information metric reward and the distance metric reward. A movement action is generated for the RL agent based on the agent position, the estimated target position, and the combined reward in accordance with a multi-agent reinforcement learning (MARL) algorithm.

A Crime Detection robotic System is provided to detect a wide range of crimes through four functions: the pre-processing function, the evaluation function, the decision-making function, and the key manager function. The crime detection system accomplishes the mission either by a single robot or by a group of robots, which is determined and managed by the key manager function. The crime detection mission can be pre-determined and stored in the system library. A new crime detection mission can be newly created by software and a new set of keys. The key manager along with the three other functions can dynamically re-define and re-assign a single or multiple robots for a single or multiple crime detection missions on the same robotic platform leading to a cost-effective method for a wide range of crimes.

An information providing system according to the present disclosure inputs input information including information on a plurality of robot units that enable a robot to execute a plurality of different services by being used in combination with a certain robot that moves autonomously and another type of robot, information on a place and a time period in which the robot operates, and information on a type of a required service. The information providing system performs a calculation process of calculating, for each robot, information related to a resource amount for a robot and a plurality of robot units required for a service based on the input information, and outputs a result calculated in the calculation process.

A mobile security robot includes a human-sized mannequin mounted on a vehicle. A storage unit, mounted on the vehicle, stores security devices and high-powered energy storage devices for facilitating extended patrols without recharge. A video recording system, disposed in the mannequin, continuously records images of a patrol area. Multiple sensors mounted on and proximal to the mannequin generate sensor data based on environmental conditions of the patrol area. A computing system coupled to the sensors processes the sensor data using artificial intelligence models and generates action commands for execution of tasks by actuators including electric motors, robotic arms, and supplementary attachment devices. The electric motors run the vehicle at different speeds with wheel speed feedback based on the environmental conditions and navigate the vehicle along a predefined travel path with object avoidance during patrols. User interface devices facilitate auditory and visual communication with humans in the patrol area.

A patrol robot including a plurality of magnetic sensors for detecting a magnetic marker laid on a traveling road has at least two or more magnetic sensors arrayed on a sensor array line linearly extending along any direction. In the patrol robot, two sensor array lines are formed, and since at least any one sensor array line can cross with respect to a relative moving direction of the magnetic marker with a movement of the patrol robot, the magnetic marker can be detected with high reliability, irrespective of the moving mode.

A robotic dog empowered by generative artificial intelligence (Gen-AI) is disclosed, capable of autonomously performing essential tasks such as guiding visually impaired individuals, detecting drugs and arms, and providing companionship. The robotic dog's lifelike design includes a head, eyes, ears, a nose, a mouth with teeth, a neck, a body, four legs with paws, and a tail, all meticulously crafted to mimic the appearance and behavior of a real dog. A trained AI model functions as the brain, processing environmental data captured by video cameras, audio microphones, and sensors to provide guidance commands to a control system that control the movements of the robotic dog. A well-trained live dog can serve as a teacher for one or multiple robotic dogs using a generative AI-based real-time training method, enabling efficient and effective training of robotic dogs.

An intelligent security method, system, and storage medium based on a quadruped robot are provided. The method includes receiving first coordinates corresponding to a target object and formulating a navigation path; dynamically correcting the navigation path during movement; when a distance between the quadruped robot and the target object reaches a preset tracking threshold, activating a surveillance camera and capturing a contour image of the target object; calculating a similarity between the contour image and a preset reference image; when the similarity is less than the preset value, initiating an attack and/or an alarm action, and calculating second coordinates; updating the navigation path and continuously tracking. Problems of limited surveillance coverage of traditional systems, inability to actively track moving targets, and untimely response to unexpected targets are solved.