Railroad Crossing LiDAR Fall Detection via Beam Count Change
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Solution Overview
Problem
Existing surveillance systems struggle to accurately detect individuals who have fallen at railroad crossings due to transmission waves being output in a horizontal direction, which fails to detect persons lying on the ground.
Innovation Solution
Employing a LiDAR sensor that emits multiple laser beams with varying ranges and angles to enhance detection accuracy by determining a decrease in detection with shorter-range beams when an object is detected, indicating a potential fall.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Area of stationary object
If the transmission wave is output in a substantially horizontal direction to the ground, then the transmission wave covers the obstacle detection area, but the transmission wave does not hit a person who has fallen down
Solution Approach 1:
The patent segments the detection task by using multiple laser beams with different ranges (short-range and long-range beams) to detect objects at different heights and positions. This segmentation allows the system to cover both standing persons and fallen persons simultaneously, resolving the contradiction between covering the detection area and detecting fallen individuals.
Solution Approach 2:
The patent introduces a new dimension to detection by comparing detection results across multiple ranges (vertical dimension). Instead of relying on a single horizontal detection plane, the system uses the range dimension to detect changes in object height, enabling detection of fallen persons who have transitioned from a standing to a lying position.
2Reliability
If a single detection method is used, then the device complexity is low, but the detection reliability for different object states is insufficient
Solution Approach 1:
The patent makes the LiDAR sensor universal by configuring it to emit multiple types of laser beams (short-range and long-range) that can detect both standing and fallen persons. This multi-functionality approach allows a single device to handle multiple detection scenarios, improving reliability without requiring separate specialized devices for each detection type.
Solution Approach 2:
The system uses feedback by comparing detection results from multiple laser beams. When the number of detecting beams decreases or the detection pattern changes, the system identifies this as feedback indicating a fall event. This feedback mechanism enables reliable detection without complex additional hardware.
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
Improves the accuracy of detecting fallen individuals by utilizing the LiDAR sensor's multiple beams to differentiate between walking and fallen states, ensuring reliable detection in railroad crossing environments.
Implementation Method 1
a LiDAR sensor configured to emit a plurality of laser beams with different ranges to a surveillance area, and output a detection signal indicating a detection status of an object by each of the laser beams
Data Source
AI summary
Provided are a surveillance system, an information processing device, a fall detection method, and a non-transitory computer readable medium capable of improving the accuracy of detecting a person who has fallen down in a railroad crossing. A surveillance system according to the present disclosure includes a LiDAR sensor (10) that emits a plurality of laser beams with different ranges to a surveillance area, and outputs a detection signal indicating a detection status of an object by each of the laser beams, and an information processing device (20) that determines that the object has fallen down when the detection status by a laser beam with a shorter range than a predetermined range indicates that the object is detected and the number of laser beams detecting the object decreases.