Accelerating the Data-Driven Agriculture Revolution · Agriculture Revolution Colleen Josephson...

Accelerating the Data-Driven Agriculture Revolution

Colleen Josephson (cajoseph@stanford.edu)June 2019 1

Using Wireless Soil Moisture Sensors

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Theewaterskloof Dam in 2018near Cape Town, South Africa

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Nearly 70% of fresh water is used to grow food...4

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And more than 80% in Africa and Asia!

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Projected to reach ~10 billion by 2050!

How do we feed 10 billion people when we’re already using 70% of our water on 7 billion?

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Precision agricultureUsing data to make decisions about water, fertilization, etc.

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20-50% water savings via soil moisture sensors!

Why do <20% of US farms use moisture sensors?

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1. High sensor cost

● Average sensor is > $100● Excludes power source (e.g. solar panel)● Also excludes the ‘data logger’, which

collects and records measurements

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The Teros-12 soil sensor retails for $225

$1 millionIs the cost of recommended sensor

deployment for the average 434 acre US farm

USDA Survey11

2. Difficulty of deploying + maintaining sensors

● Installation● Waterproofing● Power harvesting● External tampering...like

curious cows

Wires, weather and watts

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3. Difficulty collecting + processing sensor data

3G/4G cellular module? Expensive.

Ad-hoc network? Failure prone.

Manual collection? Often tedious.

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(Fields don’t have WiFi)

Microsoft’s Farmbeats

Uses a combination of drones, tractors and TV whitespace networks to collect sensor measurements and upload them to the cloud

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NSDI ‘17, D. Vasisht, et. al

This talk will focus on

sensor cost-AND-

deployment + maintenance15

What is soil moisture?volumetric water content

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How do sensors approximate soil moisture?

● Dielectric permittivity, ε, is ability of a substance to hold electrical charge

● Relative permittivity (sometimes dielectric constant):εr = ε/ε0

● εr changes as water content of soil changes →

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Topp equation (1983)

● Apparent dielectric constant Ka , function mostly of εr ● Soil moisture Θ related to Ka by the Topp equation:

θ = 4.3x10-6 * Ka3 - 5.5x10-4 * Ka

2 + 2.92x10-2 * Ka -5.3x10-2

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Time of Flight (ToF)

● Time an electromagnetic wave takes to propagate from A to B● Can approximate Ka (and therefore soil moisture) using ToF:

Ka ≅ (cτ/d)2

where c is speed of light, τ is ToF and d is distance

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Anything that gives accurate ToF can measure soil moisture!

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Soil Measurements Using RF (SMURF)2018 MSR Whitepaper, J. Ding

● Senses soil moisture using MIMO WiFi● Drawbacks:

○ Requires burying multiple antennas in soil

○ Limited WiFi chips give access to necessary info

○ Not very accurate

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What if we could use RF without burying wires?

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Backscatter: the scattering of radiation or particles back towards the source

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Passive vs. Active RF CommunicationsACTIVE PASSIVE

(backscatter)

amplifiers24

~$2is the cost of agricultural RFID tags. With mass production,

our backscatter tags could cost similarly.

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Three parts of a backscatter system1. Excitation signal generator2. Backscatter tag3. Receiver

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Backscatter to sense soil moisture

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Accurate is ToF hard

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Two discernible pulses

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Pulse smearing: one big pulse

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Ultra-Wideband (UWB) Radar

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Experimentsetup

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Buried prototype

Ultra-wideband radar

Backscatter prototype

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ultra-wideband antenna

RF switch

MCU (acts as oscillator)

Isolating the backscatter signal

34Backscatter tag off Backscatter tag on

60 Hz ambient noise 125 Hz backscatter

Aliased backscatter harmonics

Signal strength vs tag depth (preliminary)

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Commercial vs radar soil moisture (preliminary)

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Average difference between commercial sensor and radar measurements:

0.005cm3/cm3

The long-term vision

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[S]mallholder farms operate on 12% of the world's agricultural land and produce 80% of the food that is consumed in Asia and sub-Saharan Africa...

https://www.cropscience.bayer.com/en/crop-science/smallholder-farming39

Developing world [has] 98.7 per cent mobile phone adoption (as of 2017)

https://www.theregister.co.uk/2017/08/03/itu_facts_and_figures_2017/40

59%Of the world owns a smartphone

http://www.pewglobal.org/2018/06/19/2-smartphone-ownership-on-the-rise-in-emerging-economies/41

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What remains?REMAINING WORK

● Experiment with more types of soil w/ ground-truth measurements

● Extend viable sensor depth range● Do experiments in a real farm field● Study effects of temperature and

soil salinity on the measurements

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LIMITATIONS

● Measurement time depends on radar frame rate and tag depth

● Environmental impact not understood

● Assumes relatively stable soil conditions

● FCC doesn’t currently allow unlicensed UWB below 3 Ghz

Going forward: the bigger picture

● This system is just one small part ● New kinds of data at unprecedented volume and variety● Pressing need for systems to be mobile friendly

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Ag is one of tech’s final frontiers

Sources● Deepak Vasisht, Zerina Kapetanovic, Jong-ho Won, Xinxin Jin, Ranveer Chandra, Ashish Kapoor, Sudipta N.

Sinha, Madhusudhan Sudarshan, and Sean Stratman, Farmbeats: An iot platform for data-driven agriculture, Proceedings of the 14th USENIX Conference on Networked Systems Design and Implementation (Berkeley, CA, USA), NSDI’17, USENIX Association, 2017, pp. 515–528

● Ranveer Chandra Jian Ding, Estimating soil moisture and electrical conductivity using wi-fi, (2018).● Topp, G.C., J.L. David, and A.P. Annan 1980. Electromagnetic, Determination of Soil Water Content:

Measurement in Coaxial Transmission Lines. Water Resources Research 16:3. p. 574-582.● https://www.cropscience.bayer.com/en/stories/2016/automated-agricultural-helpers-ripe-for-robots● https://www.gatesnotes.com/Development/FarmBeats● http://www.pewglobal.org/2018/06/19/2-smartphone-ownership-on-the-rise-in-emerging-economies/● https://www.theregister.co.uk/2017/08/03/itu_facts_and_figures_2017/● https://www.cropscience.bayer.com/en/crop-science/smallholder-farming

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