Neural Network Warning Sign for Restricted Area Detection
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Solution Overview
Problem
Existing safety measures for restricted areas, such as those during forestry work, are inadequate in preventing unauthorized entry and detecting unauthorized persons, as they rely solely on visual cordoning which may be overlooked, leading to safety risks.
Innovation Solution
An information sign unit equipped with a motion sensor, camera, and signal devices using neural networks for image processing to detect and identify critical objects, providing optical and acoustic warnings, and communicating with a central unit to alert responsible personnel.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If visual cordoning is used to mark restricted areas, then the area can be cordoned off, but persons may overlook or disrespect the cordoning and enter the restricted area
Solution Approach 1:
The patent replaces passive mechanical cordoning (visual barriers) with an active electronic monitoring system comprising motion sensors, cameras, and neural network-based image processing. This substitution transforms the system from static visual warnings to dynamic detection and warning capabilities, significantly improving reliability while managing complexity through automated processing.
Solution Approach 2:
The system employs autonomous operation where the motion sensor automatically detects movements, the camera captures images, and the image processing device autonomously analyzes images using neural networks to identify critical objects. This self-service capability eliminates the need for continuous human monitoring, improving reliability while keeping the system manageable.
2Measurement precision
If motion sensors and image processing are added to detect unauthorized persons, then detection reliability improves, but device complexity and cost increase
Solution Approach 1:
The system performs preliminary actions by continuously capturing images with the camera and pre-processing them before full analysis. The motion sensor triggers image capture only when movements are detected, and the image processing device prepares images for neural network analysis. This preliminary processing reduces the computational burden during critical detection phases, improving precision while managing complexity.
Solution Approach 2:
The patent introduces an intermediary image processing device that acts as a mediator between the camera and the neural network-based critical object recognition. This intermediary performs initial image processing, filtering, and preparation, reducing the complexity load on the neural network while maintaining high detection precision through multi-stage processing.
Data Source
AI summary
An information sign unit includes at least one motion sensor, which detects movements of objects in the environment of the information sign unit, and at least one signal device for outputting different optical and/or acoustic signals. Different optical and/or acoustic signals depends on whether the motion sensor has detected a movement of an object in the environment of the information sign unit. A camera captures a digital image of an object in the environment. An image processing device is provided for processing the digital image with algorithms of a neural network. The algorithms are based on at least one database containing digital images of critical objects and wherein processing of the image with the algorithms delivers a result, which the object in the captured digital image as a critical object with a predefined level of reliability. A warning system and a method for operating a warning system are also provided.