UAV Biometric Data Prioritization for Forestry Planting

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Solution Overview

Problem

Current forestry management systems lack efficient and timely methods for identifying suitable planting areas and monitoring seed growth, particularly in remote or hard-to-access locations, due to limitations in data collection and processing capabilities.

Innovation Solution

A system utilizing an unmanned aerial vehicle (UAV) equipped with LIDAR/LADAR sensors, hyperspectral image sensors, and a pneumatic seed delivery system, which collects data on soil conditions, identifies qualified planting areas, and automatically plants seeds using interchangeable seed capsules with hydrogels and fertilizers, enabling remote reconnaissance and monitoring of seed growth.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If manual data collection and processing methods are used in forestry management, then system complexity is reduced, but productivity and timeliness of identification are significantly limited

Engineering Contradiction:

Improveidentification speedVSAvoidsystem complexity

Core Design Contradiction:

ProductivityVSDevice complexity

Solution Approach 1:

The patent replaces manual field data collection and processing with an automated system comprising UAVs equipped with LIDAR/LADAR sensors, hyperspectral image sensors, and machine learning algorithms that automatically identify suitable planting areas and monitor seed growth, eliminating the need for manual surveying and analysis

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The system enables self-service through automated biometric data collection, processing, and prioritization, where the system independently identifies planting areas and monitors growth without requiring continuous human intervention in data gathering and analysis operations

Inventive Principle:

Principle #25Self-service

2Measurement precision

If comprehensive data collection is performed across entire land tracts, then measurement precision is improved, but loss of time increases due to extended data processing requirements

Engineering Contradiction:

Improvedata accuracyVSAvoidprocessing time

Core Design Contradiction:

Measurement precisionVSLoss of time

Solution Approach 1:

The patent extracts and processes only the most critical biometric data parameters (such as vegetation health indices, soil moisture levels, and structural characteristics) from the comprehensive sensor data, using machine learning models to identify and prioritize only the most relevant information for planting area determination and seed growth monitoring

Inventive Principle:

Principle #2Taking out (Extraction)

Solution Approach 2:

The system performs preliminary data processing and prioritization by automatically analyzing biometric data in real-time during UAV flight operations, pre-identifying suitable planting areas and prioritizing critical monitoring locations before ground truth verification is needed, thereby reducing overall processing time while maintaining accuracy

Inventive Principle:

Principle #10Preliminary action

3Ease of operation

If remote locations are accessed for forestry monitoring, then ease of operation is improved by reducing manual intervention, but reliability of data collection may be compromised due to environmental challenges

Engineering Contradiction:

Improvemanual interventionVSAvoiddata collection reliability

Core Design Contradiction:

Ease of operationVSReliability

Solution Approach 1:

The patent replaces manual field operations with autonomous UAV systems that fly over remote areas, collecting data through LIDAR/LADAR and hyperspectral sensors without requiring personnel to physically access difficult-to-reach locations, thereby maintaining operational ease while improving reliability through consistent automated data gathering

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

Solution Approach 2:

The UAV system acts as an intermediary between the operator and the remote forested areas, transmitting collected biometric data back to processing systems where machine learning algorithms analyze the information, ensuring reliable data collection in remote locations while maintaining operator safety and ease of operation

Inventive Principle:

Principle #24Intermediary (Mediator)

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 system allows for efficient and accurate identification of suitable planting areas, automated seed planting, and remote monitoring of seed growth, enhancing the efficiency and effectiveness of forestry management by reducing manual intervention and improving data processing timelines.

Implementation Method 1

unmanned aerial vehicle (UAV) equipped with LIDAR/LADAR sensors

Methodology Applied

Scientific EffectLIDAR: LIDAR

Implementation Method 2

hyperspectral image sensors

Methodology Applied

Scientific EffectOptical detection: Photoelectric Effect

Implementation Method 3

interchangeable seed capsules with hydrogels and fertilizers

Methodology Applied

Scientific EffectHydrogel absorption: Absorption (physical)

Data Source

PatentUS10078784B2Forestry information management systems and methods streamlined by automatic biometric data prioritization

Publication Date: 2018.09.18 DRONESEED CO

AI summary

Methods and systems are presented for obtaining photographic data recently taken via one or more airborne vehicles (drones, e.g.) and for prioritizing forestry-related review and decision-making as an automatic response to the content of the photographic data even where remote decision-makers are only available via limited-bandwidth connections.