Aerial Forestry Imaging for Environment-Aware Machine Routing
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Solution Overview
Problem
Current forestry operation planning and monitoring rely heavily on human observation and manual analysis, which is inefficient and unsuitable for guiding forestry machines in real-time, especially in terms of environmental impact and path decision-making.
Innovation Solution
A forestry monitoring system comprising an unmanned aerial vehicle (UAV) and a computing device that collects and processes site information using imaging arrangements and AI/ML techniques to determine optimal paths for forestry machines, reducing human intervention and improving environmental control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If human operators manually evaluate forestry sites using aerial photography, then environmental requirements can be considered, but the process is inefficient and cannot provide real-time guidance for forestry machines
Solution Approach 1:
The patent replaces manual human evaluation with an automated system comprising a UAV that captures imagery and a computing device that processes the data using image processing and machine learning algorithms. This substitution eliminates the time-consuming manual review process while enabling real-time path decision-making for forestry machines.
Solution Approach 2:
The system enables self-service through autonomous operation where the UAV automatically navigates the forestry site, captures imagery, and the computing device automatically processes the data to generate path decisions. This eliminates the need for continuous human intervention in the path planning process, significantly improving efficiency.
2Object-affected harmful factors
If more information about the forestry site is collected to improve path decisions, then environmental impact control improves, but the system complexity increases
Solution Approach 1:
The UAV is designed as a multi-functional platform that performs multiple tasks: capturing aerial imagery, collecting site information, and providing real-time monitoring. The computing device similarly performs multiple functions including image processing, path analysis, and environmental impact assessment. This consolidation of multiple functions into unified systems reduces overall complexity compared to having separate specialized systems.
Solution Approach 2:
The patent introduces an intermediary processing layer that collects raw data from the UAV, processes it through machine learning algorithms, and converts it into actionable path decisions. This intermediary layer simplifies the complexity by abstracting the complex data processing from the final decision-making, making the system more manageable while still capturing comprehensive environmental information.
3Measurement precision
If AI and machine learning techniques are used to process collected information, then path decision accuracy improves, but computational requirements and energy consumption increase
Solution Approach 1:
The patent segments the computational workload by separating data collection (performed by the UAV in the field) from data processing (performed by a remote computing device). This segmentation allows the energy-intensive AI and machine learning computations to be performed remotely rather than on the UAV itself, reducing the energy consumption burden on the mobile platform while maintaining high path decision accuracy.
Data Source
AI summary
Disclosed herein is a forestry monitoring system comprising an unmanned aerial vehicle. UAV (30) and a computing device (35). The UAV comprises an electrical energy storage (31). an electric motor (32) powered by the electrical energy storage, a propulsion arrangement (33) driven by the electric motor and configured to aerially manoeuvre the UAV and an imaging arrangement (34) configured to collect information about a forestry site, the forestry site having one or more forestry machines performing forestry operations therein. The computing device is configured to obtain the collected information from the UAV, process the collected information to determine monitoring information for the forestry site, and determine a path decision for at least one of the one or more forestry machines based on the determined monitoring information of the forestry site.