Sensor spotlight: BinLogic feed bin level sensor

BinLogic is a bin level sensor that is valuable for managing feed inventory in the FarmStreams feed inventory system.  There are many other types of bin level sensors such as ultrasonic, load cells among others.  Our focus is really about getting data streams out of the farm site into the cloud analytics engine and/or an enterprise level system.  So, we could integrate with other bin level sensors and are willing to do that if a farm feels very strongly or has already invested heavily in another type of sensor.  With that said, our preference right now is the BinLogic sensor because it is low cost and effective to help tell a user remotely when a bin needs a feed order.

The BinLogic sensor is very simple device.  It provides a boolean (1 or 0) output.  1 is when feed is covering it and 0 is when feed is not covering it.  My preference is to put two sensors in each feed bin.  One at the top and one at the cone.  A user could put several in each bin for improved accuracy or a single sensor at a single level.  A picture of two sensors from the top of the bin is shown here.

We encountered some initial issues with ratholing when the center sensor was down the center of the bin causing false empty readings.  We moved the lower sensor off from the sensor and that has largely eliminated false empty readings.  A 2nd lower sensor on the opposite side would eliminate false empty readings.  Software also is very important in interpreting the data.  A single top sensor combined with other information like population, age and especially a feed line sensor to estimate feed flow is also a very tidy effective solution to order feed accurately.

Primary benefits to BinLogic Sensor:

1. Send alerts to specific users when thresholds are met, triggering feed orders.
2. Provide an off-site party ability to easily see inventory levels on the farm.  People such as feed mill personnel, managers, or the barn worker.
3. Provide managers / nutritionists verification their nutrition plan is being executed.  Tandem bins are being switched, in order and on time.
4. When combined with other sensors and software streams effectively keep track of inventory and feed consumption.
5. Calibrate other sensors such as the feed line sensor in the cloud based on actual feed disappearance over time, improving the sensor's future accuracy.
6. Feed inventory values at specific timestamps to create very accurate feed curve charts.  Track vs budget.
7. Timestamp bin fill events to ensure feed is delivered to the correct bin at the right time.
8. Ensure there is room for feed in the bins when the truck leaves the mill.
9. Reduce need to climb bins improving safety and employee morale.

The BinLogic sensor is a valuable tool to manage feed ordering and ALSO provide very valuable feed intake data for your analytics.  All stored and accessible indefinitely in real time.  Provide alerts around the analytics or deliver meaningful, customizable reports to management on a schedule or on the fly to correspond with site visits.  Benchmark your performance internally or externally if you choose.  The sky is the limit...and it all starts with a simple bin sensor.  

Recording mortalities

The original purpose of why we created the FarmStreams mobile app was because we needed an easy way to upload daily mortalities into Grovestreams.  This was important because animal inventory was needed to run certain ratios, such as water/pig or feed/chicken.  Recording mortalities and keeping track of inventory is a task that is done today on paper or a local computer at nearly every farm.  Typically the barn worker calls or faxes in the results once a week to an office somewhere that enters them into a spreadsheet or database.

As the mobile app evolved we began adding more features that people wanted.  But its origin truly was only to give us a way to easily enter mortalities into Grovestreams for record keeping and as required for the analytics engines.

Here is how the mortalities work:

Step 1, open the app.

Step 2, click the "Mortalities" icon

Step 3, select the group the mortality occurred in, the date and enter the found / euth.

The app then uploads the data via API transfer into Grovestreams where we can do all sorts of things with it.  Some examples:

• Keep a running count of mortalities and inventory.  
• Push the data into an enterprise level system through the API Transfer
• Chart mortality %

• Chart mortality % versus budget

• Although I have not accomplished this yet it would be fairly easy to benchmark and chart each site's mortality against the entire system's mortality based upon the day/week in the turn.

• Accurately update various ratios such as: water gallons / pig with current inventory each day.

• Generate alerts from the mortality data.  For example, 
• alert when mortality goes above the budget and stays there for more than 7 consecutive days.
• alert when no mortalities are entered for 7 or more days.
• alert when more than 1% of the population is reported in a 3 day period.

I am outlining a lot of complicated reports and alerts that can be generated just to show readers the robustness of the system we have developed.  In reality, most producers just want a way to submit mortalities from their cell phone or tablet and easily view the running total online or get the data into their own enterprise level system easier or faster.  We are working on getting the running total back into the mobile app; but don't have that piece developed yet.  Stay tuned.

Mobile app for livestock producers

In my first blog post I discussed sensors and software and their usefulness in managing a confined livestock farm.  As great as sensors are that just sit and collect useful data on the site storing in the cloud with near real-time analytics (and that is very great) managers still need to collect data from the people working on the site each and every day.  Most systems require certain information to be recorded each day on the farm site.  Common pieces of data would include:

• mortalities for each group by type
• water readings from the meter 
• temperature from the controller (high and low) 
• feed deliveries
• medications
• feed estimates in the bin (this is perhaps a weekly or bi-weekly task)

Recording the information at the site is fraught with problems.  The information stays local.  Other people in the chain like vets, nutritionists, feed mill operators and animal owners experience delays in receiving the information.  What if the barn worker does chores from 6am-11am each day and the vet needs information at noon.  They have to wait until the barn worker can return to the site before they can get the information.  The exact timing of the information can be lost.  Employees can also sanitize the information before sending it out so that it doesn't make them look so bad.

Collecting data still comes down to how motivated the worker on the farm is, no different than when it is required to take the daily paper logs.  Collecting the data to the cloud will allow other people in the system to access information quickly and in a uniform manner.  Poor data collectors will quickly be identified with the alerting functions already available in Grovestreams.  The poor performers can be given measures to improve quickly.  

We created an app called FarmStreams to allow this information to be collected into the cloud for further processing or direct transfer into a larger enterprise level system.  The app can be found here for downloading: 

       Android http://tinyurl.com/mqgskr3

       Apple http://tinyurl.com/pclejlh 

Future blog posts will go into detail on each of the pieces of data that we collect, how we do it, why we do it and what it is used for.  Certain data is very cut and dry like mortalities.  Other data like medications is more abstract because they can be administered in so many different ways and in so many different units of measure.  We will work through how this is programmed in the app as we engage more producers with different needs.  Other data like temperature, water, and feed estimating are best collected with a sensor; but cost and connecting to cloud can be a constraint.

Dealing with Feed Interruptions

I woke up this morning and saw an email alert from a hog site that we had a feed line hung up and was running continuously in an empty state since about 2am the night before.  This is an indication of a feed interruption.  Grovestreams alerting engine has several different ways it processes alerts, which is nice because over-alerting is a big issue in remote monitoring applications.  Grovestreams has thought of this and has functions such as dwell, latency, time-filters and other factors to eliminate unwanted alerts and only gives you the ones you need.

The way our system is set up is that the gateway sends a message to Grovestreams every 15 minutes that this running empty feed line state is being met.  Upon arrival in the database, I get an email notifying me of the situation, reminding me every 15 minutes until the situation is eradicated.

This past weekend we had several issues like this.  2 on Saturday and 1 on Sunday.  It seems to happen most frequently when the tandem bins are being switched.  Indications of poor feed flow.  The barn manager believes the feed is ground to fine and doesn't flow properly.  Yours truly climbed each of the 12 feed bins on site and saw for myself feed clumping to the side of the bins and not flowing.  I even took a short youtube video to document what I was seeing in one of the bins.  In the video you can also see my high and low sensors.

One item worth noting on this issue at this site that gives me some pause before suggesting a coarser grind or a bin-beater is the solution to our feed flow issues:

1.  The bins are not being completely emptied between deliveries.  These pigs are still relatively small, 90 lbs.  Going through perhaps 2-3 tons per day per group.  The barn manager who is scared to run out of feed is ordering feed very aggressively and this has resulted in delivering feed on top of feed often.  See the chart below which represents a high and a low sensor in the bin.  100 means the bin is completely full of feed.  50 means its somewhere in the middle and 0 means feed is below the cone.  If you look at my video you can see about how it is laid out.

This shows me that since the turn started in July, one of the feed bins in the tandem set has not emptied below the cone before receiving the next order of feed.  This is potentially disrupting the nutrition plan and possibly contributing to feed flow issues.  Old feed clumps easier and doesn't flow.  Additionally, logistics issues arise when the feed in the truck doesn't fit in the bin it belongs to.  All breakdowns in the feed process which add cost.

Solutions:  

1.  Monitor feed flow issues, document what the cause is potentially include a feed flow documentation module to the mobile app.  

2.  Fix feed ordering.  Ordering feed is not an easy task for a barn manager.  There are many factors to consider and timing it correctly to fit the feed mill's schedule is not a simple task.  Going forward, having the software manage the feed ordering will improve that process a great deal.  By fully emptying the bins we can know for certain that older feed is not clogging the bin from flowing properly.  Grovestreams uses data from all types of streams - sensors, app, and software which gives us a remarkably accurate estimate of feed on site and predictions on when it may go empty.

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.