Big Data. Big Decisions
InformationWeek
Special Coverage Series


Farmers Try Smart Tech To Save Water

One Startup's Story

(Page 3 of 3)

One Startup's Story

PureSense was founded four years ago by a team of technologists and farmers determined to give farmers a better sense of what's going on in the ground on their farms, beyond just giving them weather data and related calculations such as ET. Farmers have been "running blind for years," says John Williamson, co-founder and chief operating officer of PureSense, which says it has about 200 customers, mostly in California.

PureSense's system relies on monitors in the ground that include wireless transmitters, at least one wireless weather station, and software on farmers' PCs, which they use to access and analyze the data held on PureSense servers. (Other companies such as Acequia and Hydropoint apply similar technology to landscape watering.)

There are a lot of challenges to getting a system right. Each one needs to be calibrated to a farm's particular conditions--some might need a probe every 150 acres, others every 20 acres if the soil is more variable or the crop types are more water-sensitive. That's one of the limits on PureSense growing its business: It takes a lot of staff time and resources to deliver a unique system and build the trust of farmers.

But it's necessary for vendors to be so service-intensive because past failures have made farmers wary of IT, Williamson says. Too often, systems are sold without the support to make it work in that particular farm. "Selling a grower a piece of hardware that collects data isn't of much help," he says.

Apple and peach farmer VanKonynenburg, a customer, describes PureSense as a "tool in its early stages." He pushes the PureSense team to improve the product, and he credits them with listening. "They're a little less confident than they were two years ago, but they're providing better information," he says.

Consider that change VanKonynenburg wanted to make, from collecting data every 15 minutes to collecting every minute. The solar panels in the field that run the probes and transmitters couldn't power that much data transmission over the wireless network. PureSense had to recode the systems to allow data to be collected and held, then sent in a bundle every 15 minutes.

VanKonynenburg is still using ET calculations in parallel to the soil moisture data monitoring, and he considers both when making irrigation decisions.

VanKonynenburg also is looking for more uses for the data he's collecting on soil moisture, temperature, and sunshine. He'd like to use the dashboard he gets from PureSense, which is focused on irrigation decisions, to determine risks for certain pests, fungus, and bacteria, to know when best to spray for them. Like any busy executive, he wants one decision-making dashboard.

Irrigation, like most elements of farming, won't become automated. It's no different from providing greater visibility into a supply chain or sales pipeline: Soil moisture provides insight into what's happening in the fields and allows more informed decisions, but there are still critical judgments to be made. "You need data, and then you need smart people with enough experience to interpret that," VanKonynenburg says. "A lot of those decisions are subjective."

Solar-powered, wireless links
Solar-powered, wireless links
Rogers believes that as well--and the data that this 57-year-old almond farmer is getting has him rethinking some of his long-held ideas about the water trees need. With four years of data in hand, he thinks he may start irrigating trees slightly in early December, something he's never done. "I'm thinking I've been wrong," he says.

Rogers and VanKonynenburg share something besides a faith in technology to improve farming--it's a belief that farmers are going to face mounting pressure to cut water use, and they need to prepare for it. VanKonynenburg has what are considered long-term water rights, which come with the land, but he knows the political climate could change. "Just because this is where my grandfather settled, I don't think those long-term rights are bulletproof," he says.

VanKonynenburg's trust in technology goes back 20 years, when he unpacked a TRS 80 computer and ran a cost accounting and payroll system on it to figure out the real costs of activities like running a tractor per acre. He considers such moves good business, but admits it's also his passion. "Some people have guns, some people race boats, I like this stuff," VanKonynenburg says.

Not that he jumps on every technology trend. While he could access his moisture sensor data on an iPhone, he laughs off the idea. "I'm 69 years old," he says, adding that checking data once a day on the computer is fine. Then, a moment later, VanKonynenburg can't help but confess: "I suspect that a year from now, I will be carrying one."

Chris Murphy is editor of InformationWeek.

Continue to the sidebar:
Companies Look To Cut Landscape Water Use

« Previous Page | 12 3  


Related Reading


More Insights




Currently we allow the following HTML tags in comments:

Single tags

These tags can be used alone and don't need an ending tag.

<br> Defines a single line break

<hr> Defines a horizontal line

Matching tags

These require an ending tag - e.g. <i>italic text</i>

<a> Defines an anchor

<b> Defines bold text

<big> Defines big text

<blockquote> Defines a long quotation

<caption> Defines a table caption

<cite> Defines a citation

<code> Defines computer code text

<em> Defines emphasized text

<fieldset> Defines a border around elements in a form

<h1> This is heading 1

<h2> This is heading 2

<h3> This is heading 3

<h4> This is heading 4

<h5> This is heading 5

<h6> This is heading 6

<i> Defines italic text

<p> Defines a paragraph

<pre> Defines preformatted text

<q> Defines a short quotation

<samp> Defines sample computer code text

<small> Defines small text

<span> Defines a section in a document

<s> Defines strikethrough text

<strike> Defines strikethrough text

<strong> Defines strong text

<sub> Defines subscripted text

<sup> Defines superscripted text

<u> Defines underlined text

BYTE encourages readers to engage in spirited, healthy debate, including taking us to task. However, BYTE moderates all comments posted to our site, and reserves the right to modify or remove any content that it determines to be derogatory, offensive, inflammatory, vulgar, irrelevant/off-topic, racist or obvious marketing/SPAM. BYTE further reserves the right to disable the profile of any commenter participating in said activities.

Disqus Tips To upload an avatar photo, first complete your Disqus profile. | View the list of supported HTML tags you can use to style comments. | Please read our commenting policy.

Follow InformationWeek

By The Numbers

What Are Your Primary Concerns About Using Big Data Software?

Base: 417 respondents at organizations using or planning to deploy data analytics, BI or statistical analysis software
Data: InformationWeek 2013 Analytics, Business Intelligence and Information Management Survey of 541 business technology professionals, October 2012

What Do You Think?

What's your attitude about SQL analysis on top of Hadoop?
We want fast, standard SQL analysis capabilities on Hadoop ASAP
Hadoop is for unstructured data; SQL is for relational databases
We'll give SQL on Hadoop a try, but relational DBs will remain the mainstay
Given strong SQL support on Hadoop, we'd nix the data warehouse
We're not interested in Hadoop
No opinion



Related Content

From Our Sponsor

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Five Big Data Challenges and How to Overcome Them with Visual Analytics

Business leaders often need a visual snapshot of data to quickly grasp and use it. This paper identifies five challenges in presenting data and how visual analytics can resolve them. Solutions are suggested to overcome the challenges of: speed, data clarity, data quality, displaying meaningful results, and dealing with outliers.

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Game-Changing Analytics: How IT Executives Can Use Analytics to Create Innovation and Business Success

Today's competitive advantage requires a deeper understanding of your business, your market and your customers. As an IT executive, you can drive that knowledge transformation. In this white paper, learn how to make decisions as a strategic business leader and three steps to begin an analytics initiative within your enterprise.

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

Data Visualization Techniques: From Basics to Big Data with SAS Visual Analytics

High-performance data visualization turns sophisticated analyses into meaningful graphics, leading to faster and smarter decision making. In this white paper, learn how visual analytics can transform big data, with additional features such as real-time functionality, mobile compatibility, robust applications for technical groups and accessibility for nontechnical users.

Big Data: Lessons from the Leaders

Big Data: Lessons from the Leaders

Financial performance, competitive advantage, operational efficiency, strategic decision making - every business goal can extract value from big data, and the time for doubt or inaction has long passed. In this Economist Intelligence Unit report, in-depth interviews with data pioneers reveal the link between the effective use of big data and the bottom line among other results.

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Decision-Driven Data Management: A Strategy for Better Decisions with Better Data

Which came first, the data or the decision? This white paper makes the case for having a decision in mind, then tailoring big data's volume, variety and velocity to achieve business results such as overcoming customer dissatisfaction or creating well-informed strategies in real time.

Informationweek Reports

Research: The Big Data Management Challenge

Research: The Big Data Management Challenge

The challenge of big data is real, but most organizations don't differentiate 'big data' from traditional data, and nearly 90% of respondents to our survey use conventional databases as the primary means of handling data. We'll help you understand what constitutes big data (it's not just size) and the numerous management challenges it poses.