Sensing Device Data Format Integration for Traffic Monitoring
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Solution Overview
Problem
Existing sensing devices face challenges in integrating and utilizing data from multiple sources with different data formats, making it difficult to generate cohesive traffic information for road monitoring systems.
Innovation Solution
A sensing device equipped with a light source emitting frequency-modulated light, an interference optical system, and a processing circuit that selects and outputs data in specific formats, allowing for the integration of data from various sources and facilitating the generation of point cloud data with velocity information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data from multiple sensing devices with different data formats are integrated, then the quantity and detail of traffic information is improved, but the complexity of data processing and integration increases
Solution Approach 1:
The patent implements a universal data format that can represent multiple types of sensing data (point cloud data, velocity information, distance information) in a unified structure. This allows data from different sensing devices with originally different formats to be integrated without complex conversion processes, as the universal format can accommodate various data types through a standardized schema that includes flexible fields for different measurement types.
Solution Approach 2:
The patent transforms heterogeneous data from multiple sensing devices into a standardized parameter structure with defined fields for position, velocity, distance, and other measurements. By changing the parameter representation to a common format with standardized units and structures, the system can integrate data from multiple sources without dealing with format differences, thus reducing integration complexity while maintaining data quantity.
2Ease of operation
If a universal data format is implemented for integrating data from multiple sensing devices, then the ease of data utilization is improved, but the manufacturing precision of data standardization increases
Solution Approach 1:
The universal data format is designed with flexible fields that can accommodate different types of sensing data while maintaining a standardized structure. This allows the format to be universally applicable to various data sources without requiring highly precise customization for each data type, thus improving ease of utilization while avoiding excessive standardization complexity.
Solution Approach 2:
The data format is segmented into distinct fields for different types of information (position, velocity, distance, time stamps), allowing each field to be independently standardized. This segmentation enables straightforward data utilization as each field has a clear, simple standard, reducing the overall precision requirements compared to a monolithic standardized format.
3Measurement precision
If point cloud data with velocity information is generated, then the measurement precision of traffic analysis is improved, but the quantity of data to be processed increases
Solution Approach 1:
The patent merges point cloud data with velocity information into a unified data structure, combining multiple measurement types into a single integrated dataset. This merging improves measurement precision by allowing correlated analysis of position and velocity data from the same points, while the unified structure reduces overall data quantity compared to maintaining separate datasets for each measurement type.
Solution Approach 2:
The universal data format is designed to accommodate multiple measurement types (position, velocity, distance) in a single structure, allowing the same data to serve multiple analysis functions. This multi-functionality improves measurement precision by enabling comprehensive traffic analysis from unified data, while avoiding the need to process multiple separate large datasets.
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
Enables efficient integration and utilization of data from multiple sensing devices, enhancing the accuracy and detail of traffic information by providing point cloud data with velocity information, which improves road monitoring and accident analysis.
Implementation Method 1
generates interference light between reflected light and the reference light
Implementation Method 2
emits light with modulated frequencies
Implementation Method 3
receives the interference light and outputs a detection signal according to intensity of the interference light
Data Source
AI summary
A sensing device includes a light source that emits light with modulated frequencies; an interference optical system that separates the light emitted from the light source into reference light and output light and generates interference light between reflected light and the reference light, the reflected light being generated by the output light being reflected at a reflecting point of a physical object; a photodetector that receives the interference light and outputs a detection signal according to intensity of the interference light; and a processing circuit that processes the detection signal. The processing circuit selects a specific data format from a plurality of data formats that can be generated by the processing circuit based on the detection signal, and outputs output data including measurement data having the selected specific data format.