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biosecurity built on science

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PBCRC 5055 Evaluating Unmanned Aerial Systems for Deployment in Plant Biosecurity Dr Felipe Gonzalez (Project Leader-QUT/ARCAA), Aaron McFayden (QUT), Dr David Eagling (PBCRC), Prof Duncan Campbell (QUT)

Senior Lecturer QUT Aerospace Engineering



QUT/ARCAA: UAVs Agriculture and Environmental Monitoring

Summary

QUT and ARCAA undertakes fundamental research into

unmanned aerial vehicles and apply these technologies to

agriculture and environmental monitoring.

The strength of our research is indicated by many highly

influential, cited papers and link with external partners such as

Boeing , Ergon Energy and Insitu Pacific..

We have developed specialist UAVs and sensors for

agriculture and environmental monitoring.

Largest UAV group in Australia.



QUT/ARCAA capability: UAVs Agriculture and Environmental

Monitoring The UAVs include:

• Long-duration petrol-powered fixed-wing aircraft

• Novel energy-efficien solar powered fixed-wing aircraft

• Multi-rotor vertical takeoff and landing, electric powered

With specialist payloads and sensors include:

Spore trap which can detect and monitor spores of plant pathogens, for

plant bio-security applications. The sampling system has the ability to

spatially monitor fungal spores, and protocols to interpret their spatial

distribution. In collaboration with the Plant Bio-security CRC (Dr

Gonzalez)

Multispectral cameras and advanced image processing algorithms to

assist scientists in determining nitrogen deficient areas and areas of

potential bio-security threat. In collaboration with the Plant Bio-security

CRC (Dr Gonzalez)

Gas sensing, with onboard intelligent software that can track the

boundaries of gas plumes and identify their source (Dr Gonzalez)


Problem being addressed

Early and cost effective detection and monitoring of harmful plant pest

or disease incursions is time consuming but extremely important for

plant biosecurity.

Remote sensing with Unmanned aerial vehicles (UAV’s) could provide

economical and technical solutions to the problem.

This project explored the feasibility (e.g. technical, economic and

legal) of deploying UAV’s in a plant biosecurity context.

A number of features with regard to plant biosecurity are consistent

with a favourable environment for UAV’s.

These include Australia’s expansive land mass and low population

density, particularly in northern Australia.

This project explored where UAV’s could add value in the plant

biosecurity continuum.


Who will use research?

Growers

Agricultural consultants

Federal agencies

Peers


Results so far

A report providing qualitative evaluation of Unmanned Aircraft Systems (UAS) and on-board

sensor technology for use in plant bio-security in the Australian context was developed

The focus was to identify how and under what circumstances UAS may be useful for plant

biosecurity.

The report first identifies some high priority threats to Australian biosecurity, namely those

affecting broad acre cereal crops such as wheat, barley and oats.

The advantages and opportunities of dynamic airborne mobile sensing platforms for these tasks

over traditional static sensing stations is highlighted.

They include the ability to operate in remote or rural locations for long hours at lower altitudes

with little to no environmental impact.


Results so far

Subclass A B C D

Weight (kg) <2 2-7 7-20 >20

Speed (knots) 15 40 - -

Approval

Requirements

M: Mandatory

P: Potential

Online Approval

No additional

documentation

Online Approval

Ops Manual

Maintenance Manual

Airworthiness

Operational Risk

Assessment

Ops Manual

Maintenance Manual

Airworthiness

Operational Risk

Assessment

Ops Manual

Maintenance Manual

Flight Manual

Airworthiness

Operational Risk

Assessment

Table 1: Expected UAS Classes

It is expected that subclass A and B UAS Table 1: Expected UAS Classes Table 1: Expected UAS Classes Table 1: Expected UAS Classes

Expected UAS Classes

• UAV classes, performance characteristics and regulatory issues that govern their access to

the national airspace are discussed in the report.

• This results in a series of important considerations when selecting or designing UAS to be

used in various biosecurity applications.


Results so far

Item Approximate Cost (AUD)

UAV controllers approval/

Unmanned pilot's licence)

160

UOC approval process (worst

case scenario)

7000 - 8000

Renewals at the anniversary

points, not including additional

aircraft or information.

(Initial licences for 1 year. The

indication is then to have 3

yearly renewals, but this has yet

to be confirmed)

480

Approximate costs for obtaining unmanned operators certificate

(UUOC) not including items such as theory exams, platform

purchase and insurance. Modified from [49].


Results so far

UAS Platform design/selection

considerations

(Regulatory) Payload Sensor

Placement

Endurance Launch/

Recovery

Requirement

Regulatory Operator

Fixed Wing

(A,B,C)

Limited Flexible Crop-

District

Low-Mod Low Amateur/ Owner-Operator

Fixed Wing

(D,>150)

Flexible Flexible Crop-

Region

Mod-High Mod-High Professional, Outsourced

Rotary Wing

(A,B,C)

Limited Limited Plant-Crop Low Low Amateur/ Owner-Operator

Rotary Wing

(D,>150)

Flexible Limited Plant-Crop Low Mod-High Professional, Outsourced


Results so far

By combining mature UAS technology and advanced sensing systems, important

disease and pest specific in-field data can be collected in novel ways.

Current and emerging sensor technology that can be operated on-board aerial

platforms, given their size, weight and power limitations, is discussed.

They can provide information on pre and post infection crop status to help

discriminate healthy and unhealthy crop regions, or to prevent an outbreak or

spread of potential threats.

Large and diverse in-field data sets would then be obtained which will help

improve the accuracy of pest/disease discrimination.


Results so far

Band

Wavelength

(nm)

Reflectance:

Healthy

Reflectance

– Unhealthy

Application

Visual (VIS) 400-700 Low High Measuring green leaf

content, discoloration

Near-infrared

(NIR)

700-1200 High Low Defoliation, growth

rate, biomass

estimation

Short-wave-

infrared (SWIR)

1200-2400 Low High Water content,

Root/Stem disease

Medium-wave-

infrared

3000-5000 NA NA NA

Long-wave-

infrared (LWIR)

7500-9500 NA NA NA

Thermal-infrared

(TIR) (VLWIR)

8000-14000 Low High Transpiration rate

change, Root/Stem

disease, Foliar

Pathogens, Leaf

Wetness


Results so far

The report includes a technology survey which can be used

as a reference to currently demonstrated or proposed

sensing solutions in plant biosecurity.

It may be used to help match the appropriate sensor and

platform configuration to a specific biosecurity task.

In many instances the sensors and platforms used could be

used for other crops, pests and growing regions or climates

than stated.


Results so far

Fixed Wing Operator Auto Max

Dim.

Payload

(kg)

Cruise

Speed

Endurance Sensor Coverage Unit

Cost

Silvertone:

Flamingo

ARCAA/QUT

(AUS)

Semi 4.0m 10 65-

140km

/h

600min ST/EO Crop,

District,

Regional

30,000

CyberEye II ARCAA/QUT

(AUS)

Full 4.5m 20 90-

100km

/h

600min EO/MS/

HS/ST

Crop,

District,

Regional

>100,

000

Sensefly:

Swinglet

ARCAA/QUT

(AUS)

Full 0.8 NA 36km/

h

30min EO Plant, Crop 12,000

CropCam SkyView

Solutions

(AUS)

Semi 2.44m NA 60km/

h

55min EO Crop 10,000

MLB BAT 3/4

USDA/NMU

(USA)

Full 1.8m 9.0 75-130km

/h

360min EO/MS Crop, District

50,000-

150,00

0

UAV Factory:

Penguin B

UTAS

(AUS)

Semi 3.3m 8-10 79km/h

1200min HS/EO Crop, District,

Regional

13,000-

60,000

UAVs


Results so far

Rotary

Wing

Align:

T-REX 600E

FHNW

(SUI)

▲ 2011

No 1.34

m

7.0 - <30min HS Plant,

Crop

1,200

Vario:

XLV/XLC

AU/UC

(DEN)

▲ 2010

NA 1.63-

1.78

m

7 - 30min EO/MS Plant,

Crop

2,500

Microdrone

:

Md4-1000

FGI/MTT/

VTT

(FIN)

▲ 2012

NA <2m 1.0 - 88min EO/MS/

NIR

Plant,

Crop

>54,000

Other

MLB V-Bat

(Hybrid

rotary/fixe

d)

MLB

(USA)

▼ Full 2.6m 2.2 0-167

km/h

600min EO/MS Plant,

Crop,

District,

Regional

>100,00

0

Custom

Parasails

UE

(ENG)

Semi 1.75 NA NA 74km/h NA MS Crop,

District

NA

UAVs


Results so far

Traps Appearance Data Rate SpecRes.

(nm)

Pixel Res. FOV (deg) Max Dim

(m)

Weight

(kg)

Power (W) Pest/Disease Unit Cost

Multi-

Spectral

Insect/Disease

Damage

Biomass Est.

Nutrient

Deficient

Tetracam:

mini-MCA

4-12

Cameras:

450-1050nm

VAR 4-12 Bands 1280x1024 VAR 0.155 0.6-1.3 NA Aphid

Damage, Water Stress:

Wheat, Cotton

15,000

Visual

Imaging

Insect/Disease

Damage

Mapping

Quarantine

Pentax

Optio Line

1 Camera 30fps RGB +

Filter

5-12 MP VAR <0.1m <0.2kg NA Pest Damage:

Macadamia Crops

<500

PointGrey:

Spherical

6 Cameras 10-30fps RGB 4-30MP 360 0.197 1.2-3.0kg 11 -13W NA 10,000-

30,000

Survey of sensor technology for UAS plant

biosecurity

Sensors Sensors


Challenges and issues arising from this research

Recommendations:

• A series of key points and recommendations for further research and

development are derived throughout the report

• They have been derived by considering the potential benefits UAS could

provide to the broader plant biosecurity community (farmers, commercial

growers, government etc.) to help protect Australia’s local agricultural

investments.

• Operations, aerial platforms, sensors and data



Operations

A2. Platform design/ choice should be primarily dictated by application requirements

and not as a result of an attempt to circumvent strict regulation. As such, experience and

familiarisation with the approval process should be sought, acquired and applied in

conjunction to designing any UAS for plant biosecurity.

A3. Regulatory requirements should be taken into consideration when designing a

platform configuration for plant biosecurity applications. However, they should not be

considered a deterrent from using UAS.

A4. For rapid adoption of UAS technology in biosecurity, small UAS under 2kg operating

under 400’ within visual line of sight (VLOS) and away from populous areas (rural,

remote and farm-based operations) should be employed.



Aerial Platform

B1. Larger UAS should be used when flexibility and re-configurability is required. A

range of sensors for various biosecurity tasks may be needed and/or new applications

may emerge. They will be useful for broad area coverage and long endurance

operations.

B2. For frequent and/or long-term operations (high temporal resolution), multiple

platforms of the same type (fleet of UAS) and/or medium to high end products should

be acquired.

B4. Fixed wing platforms are recommended when broad area (distinct, regional)

coverage. Rotary wing aircraft are recommended for localised, close proximity

coverage (plant, crop, ports)

B5. Rotary wing aircraft are recommended for high spatial resolution. Fixed wing

platforms are recommended when decreased spatial resolution is acceptable.



Sensors

C2. Imaging: Research aimed at improving imaging sensor quality alone

should not be undertaken in the plant biosecurity framework.

C3. Hyperspectral Imaging: Research should be directed at acquiring pest

specific in-field data sets throughout the growing season.

C4. Multispectral Imaging: Research should be directed at developing

interchangeable filters for in-field testing of multiple pests or

diseases of different crops. Additionally, pest specific in-field data

sets should be acquired throughout the growing season.

Table 5: Reflectance of healthy and unhealthy crops over various spectral bands and possible applications



Sensors

C5. Visual Imaging: Research should be directed toward using

visual imagery as a complimentary sensor to improve pest

detection, localisation and mapping as well as augment UAS

guidance and control.

C7. Volatile Organic Compounds (VOC): Research should be

directed toward estimating the feasibility of using VOC sensors

onboard UAS (see A1).

C9. Sensor fusion: Research should be directed at identifying how

novel systems using multiple sensors (sensor fusion) can be used

specifically for plant biosecurity.



Flight Control, Guidance & Coordination

D1. Research should be directed at dynamic re-configurable control and guidance,

using sampled data or otherwise.

D3. Research should be directed toward advanced control and guidance to improve

image rectification and coverage whilst ensuring effective sampling can be achieved

each flight. This may require additional onboard sensors.

D4. Research should be direct toward effective mission/path planning targeted at

ensuring unbiased sampling.



Data Processing & Transmission

E2. Research should be directed toward parallelization of image processing and control tasks

using appropriate hardware such as field programmable gate arrays (FPGA) and Graphical

Processing Units (GPU).

E3. Research should focus on using UAS based data sets to help quantify the sensing and

platform requirements specific to robust detection, localisation and discrimination of

biosecurity threats.

Example: Certain invertebrates may only be accurately identified using adequate image sensor

resolution and robust classification schemes. The optimal parameters of such a classification

scheme will differ for images taken s taken on different crop seasons

Figure 16: Example information sharing and data flow using UAS technology for

plant biosecurity


Prospects for success

• Excellent however recommendation above are suggested

• International collaboration will be a key for success

Figure 16: Example information sharing and data flow using UAS technology for

plant biosecurity


Thank you

For more information, please email

[[email protected]]

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