Cargo-Sensing Unit With Triggered Imaging for Low-Power Load Estimation
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Solution Overview
Problem
Traditional cargo sensors face inefficiencies such as high power consumption, latency issues, and lack of multiple sensor types, leading to ineffective cargo estimation and installation complexity.
Innovation Solution
A cargo-sensing unit equipped with an image sensor, multiple auxiliary sensors, and processors for efficient image analysis, allowing for low-power operation and accurate cargo space utilization estimation, with features like edge detection and comparison to baseline images, and integration with door and environmental sensors for triggered image capture.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional cargo sensors utilize ultrasonic sensors or cameras to detect cargo presence, then cargo detection capability is provided, but accurate cargo amount estimation is not achieved
Solution Approach 1:
The system segments cargo detection into multiple independent sensor measurements (ultrasonic distance measurements at different positions, light sensor readings at different locations) that are individually simple but collectively provide comprehensive cargo amount estimation through comparative analysis
Solution Approach 2:
The sensor system is designed to perform multiple functions: detecting cargo presence, estimating cargo amount, and monitoring cargo level, using a integrated array of sensors that can operate in different modes depending on the required measurement type
2Ease of operation
If sensors are positioned at the container's backside (nose), then installation is simplified, but cargo blocks the sensor view when loaded against the backside
Solution Approach 1:
The sensor system is divided into multiple spatially distributed sensors positioned at different locations (front, back, sides) within the container, allowing each sensor to monitor specific zones and collectively providing complete coverage regardless of cargo loading patterns
Solution Approach 2:
The system transitions from single-point detection to multi-dimensional spatial detection by placing sensors at various positions throughout the container volume, enabling detection around and through cargo rather than being blocked by it
3Loss of time
If cargo sensors perform frequent time-varied sampling to observe cargo changes, then cargo change detection capability is improved, but power consumption increases and latency problems occur
Solution Approach 1:
The sensor system performs periodic sampling at optimized intervals rather than continuous monitoring, with the ability to adjust sampling frequency based on cargo activity levels, thereby reducing overall power consumption while maintaining timely detection of significant cargo changes
Solution Approach 2:
The system uses feedback from initial cargo detection to dynamically adjust subsequent sampling rates, increasing monitoring frequency when cargo changes are detected and reducing frequency when cargo is stable, optimizing the balance between detection latency and power consumption
4Measurement precision
If single-type sensors are used for cargo detection, then device complexity is reduced, but measurement accuracy and cargo estimation capability are limited
Solution Approach 1:
The system merges multiple sensor types (ultrasonic sensors, light sensors, door sensors) into an integrated cargo monitoring system where each sensor type contributes complementary information, and the combined data provides more accurate and comprehensive cargo detection than any single sensor type alone
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 solution provides accurate cargo space utilization estimation with reduced power consumption, enabling extended field operation without external power and simplified installation, while improving latency and sensor accuracy through multi-sensor integration.
Implementation Method 1
an image sensor... to capture an image of a cargo space within a cargo container
Implementation Method 2
traditional cargo sensors utilize one or more ultrasonic sensors to detect the presence/absence of cargo when comparing the signature of an empty container to the signature obtained when cargo is present
Data Source
AI summary
A cargo-sensing unit including: an image sensor; a transceiver; at least one processor; and a memory having stored thereon computer program code that, when executed by the processor, controls the at least one processor to: receive, from a controlling server and through the transceiver, an instruction to capture an image of cargo space within a cargo container; control the image sensor to capture an image of the cargo space in response to receiving the instruction; and operate in accordance with a determined cargo container status based on an analysis of the captured image.