Invest in process improvement not band-aids

Technology enables improved process management.  Process management is the antidote to common issues in the industry.  Often times producers will take steps to reduce issues by dealing with the symptoms of the problem.  For example, installing larger feed bins or bigger feeders on the site.  That can help reduce problems but won't solve and is massively more expensive than implementing process-focused technology.  Livestock farming is one of many industries that can adopt M2M / IoT systems to improve existing processes in an organized and meaningful way.

Some ways we are doing this is with:

• Feed management.  Ordering feed, tandem bin management, feed outages, and intake analysis are some ways we can impact an existing process that some producers struggle with.
• Group management.  Farmstreams app collects placements, mortalities, marketing and other customizable data entry streams. 
• Medication / antibiotic tracking.
• Environmental alerting. Water usage, temperature and air quality.
• Deeper big data analytics.

Within the industry commonly approaches to deal with issues are to go bigger.  For example, when feed bins running out of feed it is often suggested to spend the capital to upgrade to larger feed bins on the site.  When digging into the results of this investment - often results are a mixed bag.  It is nearly as common for feed to run out when larger feed bins are used as smaller ones.  Barn workers have a false sense of security with all that feed capacity on site and the bins run out even in tandem.  Or both slides are left open and both bins run open catching the worker by surprise.  It happens frequently.  If the process isn't fixed, the problem isn't fixed.

I have been at a layer facility where tandem bins 36 tons each were sitting within the line of sight of the feed mill no more than 1/2 mile away.  The bins would run empty and be waiting on feed from the mill.  

That much capacity also makes it very difficult for industries, like egg layers, who might want to change nutrition quickly to do so.  You have to go through 4 days of feed before you can change the ration when that much is on site.

More feed capacity inside the barn is another common solution to feed outages.  Without a doubt it is helpful but expensive.  It also doesn't guarantee that there are not times when feed is not flowing and that bunk is not full.  

One last comment, process improvement and band-aids come in waves.  Process improvements made today will make waves that result in even more process improvements in the future.  Band-aids work the same way, a 24 ton bin today becomes 36 tons in a few years.  You have to keep making the band-aid bigger and bigger, they don't get smaller.

What is Big Data?

Big Data was created or if not created at least taken mainstream by the powerhouse known as Google.  So, who better to turn to ask what the definition of Big Data is:

big da·ta

noun

COMPUTING

1. extremely large data sets that may be analyzed computationally to reveal patterns, trends, and associations, especially relating to human behavior and interactions.

   "much IT investment is going towards managing and maintaining big data"

I would say this is a fairly accurate representation of what it means to me with the caveat replacing "especially relating to human behavior and interactions" will soon be replaced with more industrial terms, like machines, robots, software or business processes.  

Big Data processes like FarmStreams can constantly be verifying conditions in barns and alerting when conditions are not ideal for maximum production.  In addition, additional "smart automation" can be installed where several dependents are monitored and when conditions are met then equipment is remotely controlled to perform different tasks.  

Some good examples of a simple smart command would be to automate a bin slide to switch bins when one runs empty, open the full bin and shut the empty bin and order new feed for the empty bin.  That is a simple automation that could be accomplished pretty easily with Big Data.

A more complex automation that could be done is to calculate weight of feed consumed per bird and once it exceeds a certain percentage of body weight for the day to switch feed rations or stop feeding for the day.  Additional complexity could be added to cross reference water consumption before making a decision.  I am not sure if this is a realistic scenario but it is illustrating that many different streams can come together to automate a variety of decisions inside a barn.

Furthermore, within animal agriculture this level of data collection from the farm has never been available.  Most data that is available remains on the site.  Once the smart professionals within the animal ag industry get their hands on this amount of production data I am certain the value they find and impact will be tremendous.

So, how big is our data?  The data platform, Grovestreams follows the Google Big Data architecture with its own wrinkles.  This is called Hadoop.

So, what can we do?

• Farmstreams can store 94,000,000 samples for each stream - this is 3 years of one-second resolution.
• 140 different statistics for each sample available for each rollup period from one second to many years, with customizable time definitions in between.
• Each sample can have unlimited derivations (formulas) occurring with them. 
• The derived samples can also have unlimited derivations (formulas) occurring with them.
• Near real-time processing and flow-through.
• Data in / out seamlessly from cloud data platform back to the enterprise level system.  Users can add us as another user interface; but don't have to.

Most livestock farms will not need single second resolution on their data; but it is nice to know the data platform was built to handle that heavy of a workload.  The ability to run derivations / formulas in real time converts several data feeds into valuable information that ensures the livestock barn is optimal.

That is what Big Data means to us.  We are focused on data quality from the sensors.  Connecting the sensors in rugged, tough environments.  The data piece on the back-end.  Optimizing the production environment for the best performance possible.

Feed inventory in mobile app

We discussed using various sensors to estimate on farm feed inventory in the last blog entry.  Several different sensors are on the market, we prefer the BinLogic sensor for its simplicity and cost.  Whatever sensor is used, getting the data into Grovestreams for analytics/alerting is crucial.  However, in some cases some farms may still want the person at the farm to climb bins each week or several times a week and take a feed inventory and report it more efficiently to the feed mill or management.  Even if bin sensors are installed it may be valuable to also get physical inventory entries on the site pushed into the data store.

Here is how it works.  The Farmsteams mobile app allows for a user to submit feed inventory based on a visual assessment of the feed bins on the farm.  The app has been programmed to allow setting up to 10 feed bins for each group housing unit.  Any more would be a custom programming request.  A user on the farm must submit feed inventory for all feed bins in the group during a single submission.  This ensures the most accurate data in the data store.  A screenshot of the app's interfact is shown:

The FarmStreams mobile app (which can be downloaded here:) 

       Android http://tinyurl.com/mqgskr3

       Apple http://tinyurl.com/pclejlh

Pros/Cons.

Pros:

1.  Writing down and calling/faxing in later has flaws.  Timing may be off, people lose their scribblings, the person answering the phone might not be available, etc.  Entering in the mobile app as it happens reduces lost communications and bad data.

2.  Grovestreams alerting engine allows us to set alerts around timing of entries.  If the rule is once a week to take an inventory, management can get an alert to their email on the 8th day without an entry.  Easier to manage than reviewing a spreadsheet or scribblings in an office.

3.  Phone calls and faxes are difficult to track for employee performance.  The database is set up to keep track of all the times it was entered but also can be set up to track all the times it was supposed to be entered but wasn't.  This can be included in the report at the end of the turn.

4.  Software streams can produce graphical feed curves, compare to a budget range, estimate feed orders, etc.  An example graphical feed curve chart that looks like below can be produced and delivered via email daily/weekly/etc. or accessed in real time by logging into the platform and viewing your dashboards.

Cons:

1.  People don't always climb the bins, perhaps they throw a rock or just guess.  Climbing the bins in January isn't fun.

2.  Feed, particularly mash feed is very difficult to estimate visually.  It doesn't always flow evenly and peering down the top of a bin can be visually tricky.  The bin sensors like BinLogic and ultrasonic have similar issues; but at least their error factors should be relatively consistent.  Meaning that a 1/2 ton discrepancy from actual is consistent every reading which minimizes the noise in the reading data and can be dealt with in software.

3.  May be difficult to enforce at some sites (likely your worst performers).  If they are not climbing bins now giving them an app and asking them to do it isn't going to change that.  Perhaps with the Farmstreams mobile app and the powerful back-end data system, management could implement incentive programs with measurable performance standards.

Strategy: Installing bin sensors is the best; but if that is not possible entering the inventory in a mobile app is better than the way it is normally done of calling or faxing data in.  If a user is not ready to go all the way with fully integrated sensor systems the mobile app can be a great way to get started collecting important information from the farm site and using cloud-based Big Data technology to find value in your livestock operation.

What is a farm stream?

FarmStreams collects, stores, organizes, analyzes and displays data from livestock farms.  In our world a stream is a piece of data collected from a sensor, person or piece of software.  The data is stored in the cloud using the latest Big Data structures.  Grovestreams is a very powerful platform and analytics engine that we use to mashup the data in the cloud.  

Examples of remote sensors:

• bin level sensors to estimate feed bin level
• feed line sensors to estimate feed flowing through a flex auger
• water meters to estimate water consumption
• air temperature sensor
• humidity sensor
• CO2 sensor
• weight scales to get bird or hog weights
• door open/shut to estimate how many hours a day laborers are at the site

Example of data that can be collected from people:

• FarmStreams mobile app collects data visible by people on the site, like: 
• mortalities
• medications
• health conditions
• water (if sensors are not available)
• temperature (if sensors are not available)  
• feed bin estimates (if sensors are not available)
• customizable inputs for each operation

The app can be found here for downloading: 

       Android http://tinyurl.com/mqgskr3

       Apple http://tinyurl.com/pclejlh

Lastly, we can create streams from software, such as:

• day, week, etc. of turn
• Animal inventory and subsequently feed/animal, water/animal, cost/animal
• Estimated budget intake based on feed curve
• Weight estimates, market prediction dates
• Feed inventory and feed ordering predictions

The data platform can analyze each and every one of these streams for alert conditions for immediate action.  Totally customize-able to each producer's needs with time filters (only alert certain times of day).  Different people in an organization can receive different alerts.  Examples could include:

• feed outage, alerts site manager that the animals are not getting feed
• water / animal decreases or increases compared to previous 2, 3, 4, or 5 days.
• feed bin is empty
• temperature is too hot / cold
• many many more 

View the streams in real time, summarized by second, minute, hour, day, week, month, or turn.  Charts and graphs quickly show the data needed.  Customize-able charts and graphs provides users maximum value with their data streams.  Users with an intermediate or higher understanding of Excel of Sequel query can develop powerful real time tools in our platform.

Follow our blog!  In the coming posts we will dive into different sensors and observations from the world of animal agriculture.  We will have technical and industry experts contribute.  The internet of things has impacted many industries.  In the world of agriculture, crop agriculture more so than animal ag.  the livestock side of ag has big opportunities for improved processes by combining cloud connected sensors, data from people and software.