There is provided an information processing apparatus in which a processor executes acquiring a three-dimensional virtual map corresponding to a real space in which a moving object moves, acquiring sense information acquired by the moving object in the real space, and causing the sense information to be displayed on the virtual map.

An apparatus and method for monitoring illegally parked/stopped vehicles using a movable camera device or a fixed camera device are provided. In an example of the monitoring method, the monitoring apparatus receives location information of a plurality of parking/stopping monitoring areas and generates a patrol route for a movable camera device to collect captured images based on the location information of the parking/stopping monitoring areas. The monitoring apparatus provides the patrol route to the movable camera device, receives, from the movable camera device, first captured images of the parking/stopping monitoring areas included in the patrol route and second captured images of the parking/stopping monitoring areas after a specified time has elapsed, and determines that a vehicle commonly detected in the first and second captured images is an illegally parked/stopped vehicle.

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.

Systems and methods for landmine avoidance by using a legged robot platform are disclosed including mine detection equipment, a robotic arm, a legged robot capable of transporting that equipment to a site of interest to identify a potential location of a landmine.

Once a site of interest is identified, the robot may step over or actively avoid the designated area of interest.

A system designed to continuously and autonomously monitor power lines using AI Drones and Wireless Charging Towers. The Wireless Charging Towers are powered by solar panels, which provide energy to wireless charging pads that recharge the AI Drones. These AI Drones are equipped with sensors to detect heat anomalies, such as sparks from power lines caused by faulty equipment or trees falling onto the lines. Sparks left undetected can lead to wildfires. The drones patrol between the towers, placed along the power lines, and this system may allow early detection of sparks before they escalate into fires. By identifying these hazards quickly, the system may significantly reduce the number of wildfires caused by power line failures.

A repellence system and method for repelling animals includes an imaging device arranged to generate image data from a railway track, one or more deterrence devices arranged to carry out deterrence actions for repelling animals and a repellence sub-system having one or more processors and memory storing instructions for execution by the one or more processors. The repellence sub-system being configured to receive image data of the railway track from the imaging device, detect an animal in the image data, identify animal species of the detected animal in the image data, provide species specific deterrence instructions to the one or more deterrence devices based on the identified animal species.

An architecture for autonomous school safety robots with behavior reinforcement is provided. The architecture can include a management server, a management portal and a number of robots for patrolling a school environment. The management portal provides an interface for an administrator to control the robots using prompts. These prompts can describe the type of behavior, object, event, occurrence, etc. that the robots should detect and can define how the robots should respond to a detection. The management portal also provides an interface for the administrator to review and respond to any reported detection.

An autonomous drone swarm system and method utilizing artificial intelligence for coordinated operations comprises command drones equipped with large language model processors and subordinate drones coordinated through a hierarchical Queen-Worker architecture. The system processes natural language commands, generates autonomous mission plans, and coordinates multi-drone operations through an encrypted self-healing mesh communication network utilizing laser, radio frequency, and visual communication channels. Multi-modal sensor integration including electro-optical, infrared, LiDAR and photogrammetry, radio frequency, and chemical detection provides comprehensive environmental awareness while federated learning algorithms enable distributed coordination in signal-denied environments. The system implements configurable operational modes spanning tactical (15 minutes-2 hours over 2 to 5 square kilometers), operational (6-24 hours over 20 to 50 square kilometers), and strategic (7-30+days over 200 to 500 square kilometers) mission profiles for military and commercial applications. Fault-tolerant protocols ensure continued operation despite individual failures through automatic task redistribution and leader election procedures.

A patrol inspection method includes: determining that an offset exists between a position of a to-be-inspected point and a position of a predetermined inspection point; obtaining a simulated three-dimensional (3D) object model by scanning a surrounding environment of a robot at the to-be-inspected point; comparing the simulated 3D object model and a pre-stored 3D object model to obtain adjustment information, the pre-stored 3D object model being 3D object information obtained by scanning the surrounding environment of the robot at the predetermined inspection point; based on the adjustment information, adjusting a pose of the robot; and capturing a two-dimensional (2D) image of an inspection target by the robot after adjustment.

A patrol system for performing a night patrol using an indoor robot includes at least one robot and a control device that controls the at least one robot. The control device performs a night patrol for a patrol target using the at least one robot, receives a request to identify an unidentified moving object from a first robot among the at least one robot during the night patrol, selects a second robot to identify the unidentified moving object among the at least one robot in response to the request, and identifies the unidentified moving object using the second robot.