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LiDAR sensing system

  • US 10,288,737 B2
  • Filed: 09/19/2017
  • Issued: 05/14/2019
  • Est. Priority Date: 09/19/2017
  • Status: Active Grant
First Claim
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1. A three-dimensional LiDAR device sensing system comprising at least two time-of-flight LiDAR ranging devices, each LiDAR device includes an optical transmitter, an optical receiver assembly, power regulation electronics, control electronics, data conversion electronics, and processing electronics;

  • and each LiDAR device covering a field or area of sensing of human traffic subjects, the two devices being mounted within a building on a support structure in spaced relationship from each other, the fields of sensing from each LiDAR device being at least adjacent the other whereby collectively an enhanced field or area of sensing of an area in the building is achieved, each LiDAR device being tuned to sense human traffic, a unit for collecting sensed data from each LiDAR device such that tracking information and movement of human traffic over the enhanced area is received by the unit, the sensing data of each LiDAR device being stitched by a stitching analytical process with data from the other data from the associated LiDAR device to provide an enlarged sensing profile, and wherein the stitching analytic process is effected on a principal of providing a predicted movement of sensing of the human traffic subjects being sensed in a queue, such that when movement of separate sensing of movement of the human traffic subjects does not occur within a predetermined time, the stitching analytic process projects representative movement of the subjects in the queue including inputs of tracking information being (i) counts the number of subjects that enter and exit a queue, (ii) generating real time velocity vectors for selected parts of the queue, (iii) detecting subject population density of the selected parts of the queue, and (iv) rendering sensed subjects to follow a path based on this processed analysis of the inputs (i);

    (ii) and (iii), thereby to obtain data on queue performance without the need to track each subject all of the time.

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