An information processing apparatus controls a road surface marking apparatus configured to form any road surface marking by changing light emission patterns of a plurality of light emitters provided on a road surface. In the information processing apparatus, a control unit detects, when switching from a second traffic lane through which a pedestrian is allowed to pass to a first traffic lane through which a pedestrian is prohibited from passing is executed, a user who is a pedestrian remaining in the first traffic lane after the switching. Then, the control unit causes the road surface marking apparatus to form an urging marking used for urging the user to withdraw from the first traffic lane after the switching.

A surveillance system for traffic on a road includes a number of surveillance units. Each of the surveillance units is mounted at height, and includes at least one road traffic detection sensor. The surveillance units are placed along the road alternately on a first side and on a second side of the road. The surveillance system can be used in an associated surveillance method for traffic on a road.

A surveillance system for traffic on a road includes a number of surveillance units. Each of the surveillance units is mounted at height, and includes at least one road traffic detection sensor. The surveillance units are placed along the road alternately on a first side and on a second side of the road. The surveillance system can be used in an associated surveillance method for traffic on a road.

An optical fiber sensing system according to the present disclosure includes: an optical fiber (10) provided along a road R to detect vibrations; a detection unit (21) configured to detect a vibration pattern of a vibration caused by a traffic accident that has occurred on the road R from optical signals received from the optical fiber (10); and an estimation unit (22) configured to estimate a situation of the traffic accident based on the vibration pattern.

A traffic management system for controlling traffic flow in an area is provided. The system has sensors (10) positioned at respective junctions (2) in the area, forming a network of nodes (2). Software (25) processes the sensor signals to derive vehicle signatures indicative of a particular vehicle detected at the node at a particular time. This is used to track the progress of vehicles traveling across the network and derive vehicle statistics (60) as to traffic volumes (64), routes (66) and journey times (62) at various times. Artificial intelligence (AI) (80) trained on historical vehicle statistics arranged to predict traffic arriving at plural junctions at a future time based on receiving a current count of vehicles sensed at nodes in the network. Based on the prediction, a control plan for traffic lights (3) is determined to optimise traffic flow.

A traffic management system for controlling traffic flow in an area is provided. The system has sensors (10) positioned at respective junctions (2) in the area, forming a network of nodes (2). Software (25) processes the sensor signals to derive vehicle signatures indicative of a particular vehicle detected at the node at a particular time. This is used to track the progress of vehicles traveling across the network and derive vehicle statistics (60) as to traffic volumes (64), routes (66) and journey times (62) at various times. Artificial intelligence (AI) (80) trained on historical vehicle statistics arranged to predict traffic arriving at plural junctions at a future time based on receiving a current count of vehicles sensed at nodes in the network. Based on the prediction, a control plan for traffic lights (3) is determined to optimise traffic flow.

The present invention relates to system and method that detects objects and assigns trackers to each object and maps it to detections to its corresponding Geo-Coordinates. Based on the number of detections, it assigns new trackers and counts the objects identified using optimal and efficient computation. The present system requires just one detection and its location to create a tracker accurately. Also, if an object is missing in any given location, the present system identifies the Geo-Coordinates and shows the image along with its details.

Methods, devices, and systems for vehicle tracking are described herein. In some examples, one or more embodiments include a computing device comprising a memory and a processor to execute instructions stored in the memory to receive tracking data for an vehicle at an airport, where the tracking data includes a data record including a number of data fields, determine whether the vehicle is being actively tracked using the tracking data, and generate a mapped data record using the tracking data to track the vehicle at the airport in response to the vehicle being actively tracked.

Methods, devices, and systems for vehicle tracking are described herein. In some examples, one or more embodiments include a computing device comprising a memory and a processor to execute instructions stored in the memory to receive tracking data for an vehicle at an airport, where the tracking data includes a data record including a number of data fields, determine whether the vehicle is being actively tracked using the tracking data, and generate a mapped data record using the tracking data to track the vehicle at the airport in response to the vehicle being actively tracked.

The disclosure provides a method and a system for muck truck management in a smart city based on Internet of Things. The method is performed by a management platform, including: obtaining construction site information, determining a target monitoring device of a target site based on the construction site information, obtaining muck truck monitoring data of the target site through the target monitoring device, and performing muck processing information analysis based on the muck truck monitoring data to generate muck truck management information.