Passenger Tracking List Generation for Elevator Dispatch
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Modern elevator systems face challenges in optimizing passenger travel time due to high and low traffic periods, leading to inconvenience and delays for users, as existing systems lack efficient passenger tracking and traffic management solutions.
Innovation Solution
A depth sensor-based passenger tracking system that captures 2D and 3D data to track passengers from origin to destination lobbies, using sensors like LIDAR and computational imaging techniques, and processes this data to generate passenger traffic lists, optimizing elevator operations by adjusting door times and dispatching based on real-time passenger data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If traditional elevator systems are used without passenger tracking, then device complexity is low, but passenger travel time cannot be optimized and wait times increase during high traffic periods
Solution Approach 1:
The system performs preliminary tracking of passengers from origin to destination lobbies before elevator dispatch decisions are made. By capturing sensor data and generating traffic lists in advance, the system prepares optimization information proactively, allowing elevators to be dispatched more efficiently during high traffic periods without adding complex real-time decision-making infrastructure.
Solution Approach 2:
The system creates a digital copy of passenger traffic patterns through sensor data collection and traffic list generation. This virtual representation of passenger flow allows the control system to analyze and optimize elevator dispatch without requiring physical modifications to the elevator infrastructure, reducing device complexity while enabling time optimization.
2Measurement precision
If depth sensors and passenger tracking systems are deployed, then passenger tracking accuracy improves, but device complexity and cost increase
Solution Approach 1:
The sensor system is designed to perform multiple functions: capturing depth data for passenger tracking, identifying passenger locations in lobbies and elevators, and generating traffic lists. By making the sensor system multi-functional, the patent reduces the need for separate specialized devices, thereby improving tracking accuracy without proportionally increasing overall system complexity.
Solution Approach 2:
The system uses existing sensor infrastructure and processing capabilities to automatically generate traffic lists and track passengers without requiring additional dedicated hardware for each tracking function. The processing module leverages available computational resources to perform tracking and analysis, reducing the need for complex specialized sensor systems.
3Productivity
If real-time passenger data processing is implemented, then elevator dispatch optimization improves, but processing time and computational resources increase
Solution Approach 1:
The system generates traffic lists and processes passenger data in advance of elevator dispatch decisions. By preparing optimization information proactively rather than reactively, the system reduces real-time processing requirements and enables faster dispatch decisions without sacrificing throughput optimization.
Solution Approach 2:
The sensor system and processing module operate continuously to capture and process passenger data, maintaining an up-to-date traffic list without requiring intermittent batch processing. This continuous operation eliminates processing interruptions and ensures smooth elevator throughput optimization without computational bottlenecks.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system improves passenger satisfaction by reducing wait times and optimizing elevator traffic performance by accurately tracking passengers and adjusting elevator operations in real-time, enhancing both passenger experience and system efficiency.
Implementation Method 1
the depth-sensing sensor comprises a structured light measurement, phase shift measurement, time of flight measurement, stereo triangulation device, sheet of light triangulation device, light field cameras, coded aperture cameras, computational imaging techniques
Implementation Method 2
the depth-sensing sensor comprises scanning LIDAR, flash LIDAR
Data Source
AI summary
A passenger tracking system includes a multiple of sensors for capturing depth map data of objects. A processing module in communication with the multiple of sensors to receive the depth map data, the processing module uses the depth map data to track an object and calculate passenger data associated with the tracked object to generate a passenger tracking list that tracks each individual passenger in the passenger data from an origin lobby to a destination lobby and through an in-car track between the origin lobby and the destination lobby.