Aspects of the subject disclosure may include, for example, obtaining a first group of video content streams of an event, determining a first point of view of a plurality of audience members of the event, and selecting a first portion of the first group of video content streams of the event according to the first point of view of the plurality of audience members. Further aspects can include aggregating the first portion of the first group of video content streams resulting in first aggregated video content, generating first augmented reality content from the first aggregated video content according to the first point of view, and providing the first augmented reality content to a communication device. The communication device can present the first augmented reality content. Other embodiments are disclosed.

A method of tracking rotations of a drum includes activating a three axis accelerometer located on a side of the drum, measuring linear accelerations along three orthogonal axes using the accelerometer, determining whether a predetermined angle of the drum has been rotated based on the measured linear accelerations from the accelerometer, activating a gyroscope when it is determined that the predetermined angle of the drum has been rotated, measuring angular speed at the gyroscope, calculating a number of rotations of the drum from the measured angular speed, and deactivating the gyroscope when it is determined that the measured angular speed is lower than a noise floor level.

The present disclosure provides a construction management system capable of ascertaining information about a construction site more accurately than before. A construction management system 100 comprises: a position sensor 16a detecting position information about a transport vehicle 10 that transports payload; a position sensor 26 detecting position information about a loading machine 20 that loads payload onto the transport vehicle 10; a weight detection device 120 detecting weight information about the payload held by the loading machine 20; and an information management controller 130 which, based on chronological information of the position information about the transport vehicle 10, chronological information of the position information about the loading machine, and chronological information of the weight information, calculates the load weight of the payload loaded onto the transport vehicle 10.

The present disclosure provides a construction management system capable of ascertaining information about a construction site more accurately than before. A construction management system 100 comprises: a position sensor 16a detecting position information about a transport vehicle 10 that transports payload; a position sensor 26 detecting position information about a loading machine 20 that loads payload onto the transport vehicle 10; a weight detection device 120 detecting weight information about the payload held by the loading machine 20; and an information management controller 130 which, based on chronological information of the position information about the transport vehicle 10, chronological information of the position information about the loading machine, and chronological information of the weight information, calculates the load weight of the payload loaded onto the transport vehicle 10.

Systems and methods are provided for managing a construction project using a digital twin or digital execution verification. A data ingestion module receives construction project data from data sources through a communication interface. An infrastructure module generates a digital twin of the construction project using a first data subset, and generates a plan model of the construction project using a second data subset. A display interface displays at least a portion of the digital twin overlaid with a corresponding portion of the plan model in a virtual environment. The plan model contains at least one planned component. The digital twin contains at least one construction component associated with a corresponding constructed component at a construction site. A construction mismatch is determined based on a comparison of the digital twin and the plan model, and is used to made adjustments for the construction project.

This non-destructive inspection system 1 has a non-destructive inspection device 2 and a management device 3. The non-destructive inspection device 2 is provided with: a neutron emission unit 10 capable of emitting a neutron beam; a gamma ray detection unit 20 capable of detecting gamma rays; a device casing 30 covering the neutron emission unit 10 and the gamma ray detection unit 20, an opening 30a being formed in the device casing 30; an outer shutter 31 that opens/closes the opening 30a; dose monitors 51, 52, 53 provided to the device casing 30, the dose monitors 51, 52, 53 detecting the radiation dose; a device communication unit 56 capable of transmitting device information including the detected radiation dose to the management device 3, and capable of receiving inspection permission information from the management device 3; and a device control unit 40 that, when the inspection permission information is acquired, opens the outer shutter 31 and enables emission of a neutron beam from the neutron emission unit 10.

An AI-and IoT-driven real-time construction management system continuously acquires and analyzes high-frequency sensor data, including temperature, GPS, and RFID inputs. Utilizing advanced predictive machine learning and reinforcement learning algorithms, the system forecasts schedule deviations and resource conflicts with an accuracy exceeding 90%. Upon identifying deviations, it autonomously triggers corrective actionssuch as reallocating resources or adjusting task sequencestypically within five seconds. This integrated, closed-loop management approach seamlessly interfaces with external project management tools, achieving approximately 15-20% improved schedule adherence and notable cost reductions based on preliminary data. The system's modular architecture supports diverse sensor technologies and AI frameworks, ensuring adaptability and sustained performance in large-scale, dynamic construction environments.

An AI-and IoT-driven real-time construction management system continuously acquires and analyzes high-frequency sensor data, including temperature, GPS, and RFID inputs. Utilizing advanced predictive machine learning and reinforcement learning algorithms, the system forecasts schedule deviations and resource conflicts with an accuracy exceeding 90%. Upon identifying deviations, it autonomously triggers corrective actionssuch as reallocating resources or adjusting task sequencestypically within five seconds. This integrated, closed-loop management approach seamlessly interfaces with external project management tools, achieving approximately 15-20% improved schedule adherence and notable cost reductions based on preliminary data. The system's modular architecture supports diverse sensor technologies and AI frameworks, ensuring adaptability and sustained performance in large-scale, dynamic construction environments.

The present disclosure provides a construction management system capable of ascertaining information about a construction site more accurately than before. A construction management system 100 comprises: a position sensor 16a detecting position information about a transport vehicle 10 that transports payload; a position sensor 26 detecting position information about a loading machine 20 that loads payload onto the transport vehicle 10; a weight detection device 120 detecting weight information about the payload held by the loading machine 20; and an information management controller 130 which, based on chronological information of the position information about the transport vehicle 10, chronological information of the position information about the loading machine, and chronological information of the weight information, calculates the load weight of the payload loaded onto the transport vehicle 10.

The present disclosure provides a construction management system capable of ascertaining information about a construction site more accurately than before. A construction management system 100 comprises: a position sensor 16a detecting position information about a transport vehicle 10 that transports payload; a position sensor 26 detecting position information about a loading machine 20 that loads payload onto the transport vehicle 10; a weight detection device 120 detecting weight information about the payload held by the loading machine 20; and an information management controller 130 which, based on chronological information of the position information about the transport vehicle 10, chronological information of the position information about the loading machine, and chronological information of the weight information, calculates the load weight of the payload loaded onto the transport vehicle 10.