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Posts from the ‘Data Collection & Analysis’ Category

Are Arduinos Practical and Cost Effective?

Last spring my daughter, Sarah, needed a project for the science fair, and since she has always been interested in scientific measurements, we decided to try and figure out when it was time to water her mother’s plants. Since we’ve fielded a lot of calls from customers asking about using Arduinos (user-programmable microprocessors) lately, I thought I would kill two birds with one stone and give one a try. My preference would have been the speed and simplicity of a METER data logger, but I was curious about how practical and cost-effective this method might be for taking measurements.

Young Girl Concentrating on Helping with the Soldering

Arduino Science Project with my daughter

The Arduino is an inexpensive, user-programmable microprocessor on a circuit board that has exposed analog inputs for measuring voltages and digital ports for measuring incoming digital signals. It can also run displays and is programmed by an Arduino IDE running on your computer.

I purchased a book called Arduino Recipes that taught us the basics of Arduino programming, which was pretty straightforward. The Arduino board itself has rows of pinheaders, so I brought some of the male pinheaders from work and soldered all the wires to them, in preparation to attach the water content sensor. It looked medusa-like with all the wires coming off the pinheaders, but we could then just hook up kid-friendly snap circuits and try some elementary tests to get used to the system.

We hooked up Decagon’s (now METER) analog water content sensor (EC5)  first and started measuring. It has a really nice calibration equation supplied by METER, so we used that for a while to measure water content. We took one of mom’s dry plants and measured before and after watering and used the readings to make a linear relationship between the reading on the sensor when it was dry and the reading on the sensor when it was wet.

Small Cactus in the Window

Our biggest challenge was that Sarah wanted to display this to mom to make sure she knew when to water the plants. So she and I then had to figure out how to integrate an LCD display.

Sarah was excited to get the digital soil moisture sensor integrated because we could then measure water content AND electrical conductivity (EC) to get an idea of the fertilizer in the soil. We used my work colleague’s code to read the digital sensor output, which worked quite well.  It only took a few minutes to insert his piece in the code into our program and start reading water content. Our biggest challenge was that Sarah wanted to display this to mom to make sure she knew when to water the plants. So she and I then had to figure out how to integrate an LCD display. Luckily, all the details were on the Arduino website.  We just cut and pasted the code into our program and then did all the wiring.

Finally, we had it all put together, and we inserted the 5TE digital sensor into the pot. It worked, but the device was large and unwieldy. Mom wasn’t happy that we were putting it right in the middle of her clean living room, but Sarah pointed out that we have to make sacrifices for science, so we put the sensors in the soil, set up the display, and ran it for about a week. Sarah took water content data morning and night and watered it when it reached our “dry” point. She took the finished system to the science fair and was excited to find a few future customers.

Close up on a circuit board

The biggest challenge would be all the details in the system. We’d need a circuit board, a power supply, a data logging interface board, and a box to put it in, and if we were going to set it outside, that box would have to be waterproof.

Are Arduinos practical for use in your experiments?

It depends. Sarah and I found out that it just doesn’t take a lot to integrate a sensor into the Arduino system and be able to make measurements. However, if we were to try the above experiment long-term, the biggest challenge would be all the details in the system. We’d need a circuit board, a power supply, a data logging interface board, and a box to put it in, and if we were going to set it outside, that box would have to be waterproof. We’d also need ways to connect the sensor to the circuitry, and all these things take time and resources. For me, the take-home message was that Arduinos are a lot of fun, and might fit your application exactly the way you want. However, you’ll need time (often a lot of it) to spend making sure it’s waterproof, doing all the programming, writing a code durable enough to fit your field applications, and getting the hardware prepped. In fact, Decagon support staff take calls every week from frustrated do-it-yourselfers who’ve found this is not as easy as it seems. Thus, in my opinion, an EM50 or Campbell Scientific data logger are more practical options than an Arduino-like microprocessor.

Are Arduinos cost effective?

A lot of scientists want to make measurements out in the field with small budgets. I am certainly one of those. Arduinos are $85 versus a complete data logger that costs several hundred dollars. However, people tend to forget that things like labor even cost discrepancies.

So, if you have plenty of time, want the versatility, and you love this stuff, go ahead and make an Arduino sensor, but at the end of the day, the cost shouldn’t be a driver, because there are data loggers that can do the job of an Arduino more simply and quickly, without all the hassle.

Download the “Researcher’s complete guide to SDI-12″—>

Download the “Researcher’s complete guide to water potential”—>

Download the “Researcher’s complete guide to soil moisture”—>

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Modeling Available Soil Moisture

Both the amount and the availability of water in soil is important to plant roots and soil-dwelling organisms. To describe the amount of water in the soil we use the term water content. To describe the availability we talk of water potential. In thermodynamics, the water content would be referred to as the extensive variable and the water potential as the intensive variable. Both are needed to correctly describe the state of water in soil and plants.

Measuring soil moisture with the WP4C

Measuring soil moisture with the WP4C

In addition to describing the state of water in the soil, it may also be necessary to know how fast water will move in the soil. For this, we need to know the hydraulic conductivity. Other important soil parameters are the total pore space, the drained upper limit for soil water, and the lower limit of available water in a soil. Since these properties vary widely among soils, it would be helpful to establish correlations between these very useful parameters and easily measured properties such as soil texture and bulk density. This paper will present the information needed for simple models of soil water processes.

Click here to download the paper.

Download the “Researcher’s complete guide to water potential”—>

Download the “Researcher’s complete guide to soil moisture”—>

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Near Real-Time Data Analysis

We are entering an era of cheap data.  Sensor technology has advanced to the point where it has become easy to collect large amounts of measurement data at high spatiotemporal resolution.

real-time data analysis

Hydroserver map screen: Using an off-the-shelf open source informatics system like Hydroserver kept us from reinventing what’s already out there, but allowed flexibility to program to our own needs.

We are now to the point where we have gigabytes worth of data on soil moisture, plant canopy processes, precipitation, wind speed, and temperature, but the amount of data is so overwhelming that we are having a difficult time dealing with it. The cost of measurement data is dropping so quickly, people are forced to change from a historical mindset where they analyzed individual data points to the mindset of turning gigabytes of data into knowledge.

real-time data analysis

Because Bioinformatics students are used to working with DNA data, they understand how to write computer programs that analyze large amounts of data in near real-time.

One approach suggested by my colleague Rick Gill, a BYU Ecologist, is to collaborate with bioinformatics students.  Because they are used to working with DNA data, these students understand how to write computer programs that analyze large amounts of data in near real-time.  Rick came up with the idea to tap these students’ expertise in order to analyze the considerable information he anticipates collecting in our Desert FMP Project, an experiment which will use TEROS 21 and SRS sensors to determine the role of varying environmental and biological factors involved in rangeland fire recovery.

Rick and I are predicting that near real-time data analysis will give us several advantages. First, we need readily available information so we can tell that sensors and systems are working at the remote site.  Large gaps in data are common for sites that aren’t visited often, and sensor failures are missed when data are collected but never analyzed.  With our new approach, all data are databased instantly, and the results are visualized as we go.  Not only that, we’ll be able to control what’s being analyzed as we see what’s happening.  We can tell the bioinformatics students what we need as we begin to see the results come in.  If we see important trends, we can assign them to analyze new data that may be relevant right away.

These techniques have the potential to help scientists from all disciplines become more efficient at collection and analysis of large data streams. Although we’ve started the process, we have yet to determine its effectiveness.  I will post more information as we see how well it is working and as new developments arise.

Watch Dr. Gill’s data analysis webinar: Finding Insights in Big Data Sets

Download the “Researcher’s complete guide to soil moisture”—>

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Solving the Problem of Disappearing Science Lab Technicians

One of the hardest issues university researchers face today is the lack of funding for lab technicians. Although it’s frustrating that universities are no longer able to support this type of personnel, can technology close the gap? This is a question we’ve tried to answer in our Desert FMP project in collaboration with BYU.

lab technicians

Source: Simplyhired.com. Job listings for Science Lab Technicians have decreased 38% from March 2013-March 2014

I was talking to my colleague, Rick Gill, several weeks ago, and he had this to say about the disappearance of the previously indispensable lab technician: “We have fewer people in the lab, and the people we have are more expensive. We need to be deliberate in how we use their time. If we can make the entire system more efficient using technology, we’ll use the people we have in a way that is meaningful. In ecology right now, one of the things that we’re beginning to recognize is that the typical process where the lab tech would go out and take ten samples and average them is not what’s interesting. What’s interesting is when it’s been dry for four weeks, and you get a big rain event. This is because the average for four weeks is really low for almost all processes, but the data three days after it rains swamps the previous four weeks. So the average condition means almost nothing in terms of the processes we’re studying for global change. We need technology to take the place of the technician who would be monitoring the weather and trying to guess when the big events will occur.”

To capture these pulses in the Desert FMP project, we’re using a continuous monitoring system that communicates feedback directly to us as the principal investigators. Using advanced analysis techniques, we can painlessly assure that data are being collected properly and important events are never missed. Although we don’t have a technician, the goals of the project are still being met.

What do you think? How have you dealt with the disappearance of the lab tech?

Download the “Researcher’s complete guide to soil moisture”—>

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