COMPUTATIONAL INFORMATICS

Thank youCSIRO Computational InformaticsProf. Paulo de SouzaOCE Science Leadert +61 3 6232 5578e paulo.desouza@csiro.au w www.csiro.au/ict

Paulo de Souza | OCE Science Leader – CSIRO Computational Informatics26 November 2013

CSIRO COMPUTATIONAL INFORMATICS

Swarm Sensing

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing | Prof. Paulo de Souza

MotivationThe real need

Technology Roadmap

Swarm Sensing | Prof. Paulo de Souza

Silverster (2011)

Technology Roadmap: Where are we?

Swarm Sensing | Prof. Paulo de Souza

[Silverster11]

Our Targetby 2016

…

Technology Roadmap

Swarm Sensing | Prof. Paulo de Souza

Technology Roadmap

Swarm Sensing | Prof. Paulo de Souza

Technology Readiness Level

cm

Immature

Disruptive

Applications

BetterIP Space

PopulatedIP Space

Too BlueSky

Maturemm mm nm

Our Target

• To develop a 100 mm sensor platform that is able to:• Harvest and store energy• Process data and store it• Make environmental measurements• Communicate

• Perform environmental monitoring and insect monitoring

• Considering:• Cost ($0.30/unit)• Theoretical formalism to interpret data from these sensors

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing:Challenges we are facing

Where we are focusing now, next and later?

Swarm Sensing | Prof. Paulo de Souza

Research Challenges• Energy

• Harvesting (from insect movement)• Storage (3D batteries)

• Integration• Design, optimisation, prototyping, manufacturing, testing

• Communications• Increasing distance• Tracking insects

• Analytics• Interpreting data coming from thousands of sensors in real-time• Modelling insect behaviour

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing:Functions of micro-devices

What can we do with it?

Functions of Micro-Devices

• Tagging• Challenge: Distance achieved with wireless communication

• Tracking• Challenge: landscape, size of supporting structure, energy, antenna

• Sensing• Challenges: Communication,

energy harvesting and storage

Micro-devices | Page 13

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing:What are we doing?

What are we doing?• Tagging 5,000 honey bees

• 2.5 x 2.5 x 0.4 mm RFID manufactured by Hitachi Japan • Four identical hives

– Feeder stations with different nutritional contents– Pollen excluders– Pesticides on pollen

• Aiming at gathering information on:– Bee behaviour x environmental changes– Pre-swarming management– Pollination under stress– Real impact of pesticides– Insight to bee collapse – Interactions between individuals

What are we doing?

What are we doing?

Swarm Sensing | Prof. Paulo de Souza

What are we doing?• Theoretical Formalism

• Statistical Mechanics• Thermodynamic-equivalent

– States– Constants

• Modelling/Simulation– How to integrate large data sets– What can we learn from data

longitudelatitude

time

Energy Harvesting

Swarm Sensing | Prof. Paulo de Souza

Energy Harvesting

Swarm Sensing | Prof. Paulo de Souza

3D MicrobatteriesMaximised Energy on a Small Footprint Area

3D Microbattery Project | Page 22

~15 µm ~500 µm

Higher electrode surface area = Increased Energy per Footprint Area

Thin Film Battery 3D Microbattery

Integration of Micro-Devices

3-D Micro-Battery

Energy Harvesting Micro-Devices

3-D Micro-Battery

Energy Harvesting Micro-Devices

Micro-Electronics & RF Module

Micro-Sensors

Antenna

Micro-Electronics & RF Module

Micro-Sensors

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing:What’s next?

What are we doing ?

What’s next?• Tracking

• Antenna• Harmonic Radar

• Aiming– Migration– Dispersal of invasive species– Disease vector, pest and beneficial

insect movement– Mining operations x insect behaviour

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing:What’s later?

What we dream of achieving?

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing | Prof. Paulo de Souza

Insects as Sensors

• Fact 1:• Insects are very sensitive to chemicals

(reported 10-19)

• Fact 2:• Exposure to some chemicals create a specific pattern through the insect

nerve system

19:4

0

23:4

5

25:2

1

26:5

2

21:5

4

24:3

2

22:4

9

EAD

FID

antenna reaction

Female pheromone gland extract

Swarm Sensing | Prof. Paulo de Souza

Insects as sensors?

In jection

M ake-up gas

F ID

EA D

FID

Stim ulus delivery tube

Am plifier

G roundelectrode

Split

G C colum n

A ir flowH eated transfer line

Swarm Sensing | Prof. Paulo de Souza

Insects as Sensor

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing:Partnerships

We can’t make it happen alone!

Swarm Sensing | Prof. Paulo de Souza

• Current• Capability

– SSN-TCP (CCI, CPSE, CET) & CES– UTAS– Desert Research Institute– University of Michigan

• Output– Biosecurity Flagship– Vale Institute of Technology– Tasmanian Beekeepers Association– Fruit Growers Tasmania– Seed Producers– Quarantine Tasmania– EPA - TasGov

Partnerships

Swarm Sensing | Prof. Paulo de Souza

Swarm Sensing:Conclusions

What we have seen today?

To reflect

• Technology Development Requires:• Discipline and strategic thinking;• A relevant application;• Capability in R&D

(people, infrastructure and relationships);• Scientific relevance;• Resources.

• CSIRO is the place to make it happen.

• This is a team effort.

COMPUTATIONAL INFORMATICS

Thank youCSIRO Computational InformaticsProf. Paulo de SouzaOCE Science Leadert +61 3 6232 5578e paulo.desouza@csiro.au w www.csiro.au/ict