Autonomous Vessel for Floating Waste Removal
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Solution Overview
Problem
Current methods for removing floating undesired objects from water masses, such as plastic waste and wooden debris, are laborious and ineffective, posing environmental hazards and obstructing shipping traffic, particularly in areas with tidal currents.
Innovation Solution
A method and system utilizing a computer-controlled autonomous vessel equipped with image recognition software and an artificial neural network to detect, predict the trajectory of, and collect undesired objects, which are then directed to a temporary storage using a trap or pusher blade, allowing for efficient removal regardless of tidal changes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual tracking and removal of floating objects is performed, then objects can be removed from water, but the process becomes laborious and ineffective
Solution Approach 1:
The system performs automatic detection, tracking, and removal of floating objects without human intervention. The computer-controlled vessel autonomously navigates, detects objects using sensors, calculates trajectories, and collects objects, eliminating the need for manual tracking and removal operations.
Solution Approach 2:
The patent replaces manual mechanical operations with an automated system combining computer vision, trajectory calculation algorithms, and automated vessel control. The mechanical system includes automated grabbing installations controlled by computer algorithms rather than manual operation.
2Productivity
If automatic garbage cleaning systems are deployed, then removal efficiency improves, but the system becomes complex
Solution Approach 1:
The vessel is designed as a multi-functional platform that combines detection sensors, computer vision processing, trajectory calculation, automated navigation, and object collection capabilities in a single integrated system, reducing the need for multiple separate systems.
Solution Approach 2:
The computer acts as an intermediary that coordinates between detection sensors, trajectory calculations, and vessel control systems. The central computer processes data from various sensors and generates control commands, simplifying the integration of complex subsystems.
3Productivity
If floating objects are collected in temporary storage, then objects are removed from water, but tidal currents affect storage positioning
Solution Approach 1:
The temporary storage is designed as a floating structure that dynamically adapts to changing water levels and tidal currents. The storage position and orientation adjust automatically with tidal variations, maintaining operational effectiveness throughout the tide cycle.
Solution Approach 2:
The system uses sensors to detect the position of floating objects and the state of tidal currents, then the computer calculates and adjusts the vessel's navigation and storage positioning in real-time to compensate for tidal effects and maintain optimal collection efficiency.
4Measurement precision
If image recognition is used to identify undesired objects, then object classification accuracy improves, but processing time increases
Solution Approach 1:
The system pre-processes and analyzes object characteristics as they are detected, calculating trajectory and classification simultaneously during the detection phase rather than in separate sequential steps, reducing overall processing time while maintaining accuracy.
Data Source
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Figure 2C
AI summary
Described is a method for removing floating undesired objects from a water mass in an area. The method comprises of determining an entry of an object into the area. Properties of the object, which show the undesirability of the object, are then determined with image recognition. After this, undesired objects are carried in floating state to a temporary storage, preferably with an autonomously navigating vessel, and then removed therefrom, preferably once again with an autonomously navigating vessel. A system with which the method can be performed is also described. The method preferably proceeds under the control of a computer via a digital network.