Monitor access to buildings

Access to barns and recording the access is more important today than ever before.  Biosecurity and monitoring labor are just two of the reasons it makes sense to have a basic understanding of the coming and goings of people at the farm site.  I have put together using a basic door sensor a system that can provide quite a bit of insight into a farm's activity and compare to other similar farm's activity for benchmarking purposes.

Certainly I realize that this is a fairly low-cost monitoring system.  Undeniably there are bigger and better ways to monitor exactly who is coming and going and at exactly what time.  You could retina or fingerprint scan workers like 007 movies but at what cost?  You could have card scanners but then look at the expense of installing that for one or two workers.  What if they forget their card or lose it?  Often the "home office" is far away and the logistics of getting a new card could take days.  Or a substitute needs to go to the site who doesn't have a card?  A simple low-cost employee monitoring device could be the solution.

Here is what I did.

I installed a simple door sensor that sends a count of how many seconds the door is open in 5 minute intervals for each time it is opened.  That information is then sent to Grovestreams where I am doing some simple analysis with it that provides me with some excellent information.

Data #1.  I get the first time of the day that the door was opened up.  This is huge.  If the employee is supposed to be at the site at 6am and they regularly arrive at 9am that is a problem.  

The image above shows activity on a system that monitors a door at my office.  Grovestreams allows for an easy way to determine the first and last timestamp of activity received for the day and shows it in a dashboard.

In addition I can take the last timestamp and subtract the first and get an estimate of the time the site was occupied for the day.  

I also chart this for quick viewing (guess I haven't been to the office at all in the last few days):

Interesting alerts on this.

1.  Send an alert to email or phone on the first arrival every day.

2.  Send an alert to email or phone on activity outside of a time filtered period.  Example send an alert for every activity outside the hours of 6am to 6pm.

3.  Send an email at 12:01am if the duration of the previous day was less than 4 hours.

4.  Same alert as #3 except for exclude weekends.

Expanded analysis:

Many sites have multiple barns.  As part of the Multisense sensor gateway users could add door sensors to each barn entrance and managers could track how much time is spent in each of the barns on the site.  Alerts for barn doors left open would be simple to include as part of any package as well.

Grovestreams and Multisense make prototyping IoT projects simple and low cost.  This door sensor project took me hardly any time or money and now I think this could be used in barns all around to monitor employee time.

Bin Sensors Help Order Feed

Talk to any feed mill operator and they will tell you that the biggest issues that affect their efficiency all surround feed ordering.  Too many orders on Mondays and Fridays, missed orders that result in emergency deliveries after hours all have produced many grey hairs amongst feed mill staffers.

The Binlogic bin sensor provides some good data which can help feed mills know or predict when bins are empty and need a delivery scheduled.  As this goes to press, we are still working on refining and improving the sensor but initial data is promising.

Installing even more sensors as well as predictive growth software can provide a lot of contextual information to effectively put a feed ordering program together for an entire feed mill system.

Some ways this can work:

Utilize 1 high sensor and 1 low sensor.  This is a great way to know a time frame from when a bin begins to be depleted until it is in the cone and more feed can be delivered.  In the example below a trigger can be set for as soon as the sensor in the high goes from closed to open to put a feed order in for 45 hours later.

Furthermore, many sites use tandem bins.  The example below shows that from the time that bin 31 starts going down to the time that bin 32 goes below cone is 96 hours.  So, in this case a date range of between 45 and 96 hours from the time bin 31 first goes down could be pushed to the mill as a delivery window to ensure the site doesn't run out of feed.

Another strategy would be to look at these 2 time spans for the order window.

This strategy would call for a feed delivery from 66 hours to 119 hours from the time Bin 31 first starts to go down to ensure feed doesn't run out.

Even another strategy would be to send a notification to the feed mill as soon as a bin goes empty which triggers an order to drop and go out within X hours.  If the feed mill has a queue of empty feed bins for which to deliver feed against it could make for an efficient system.

Yet another option would be to simply have a single high sensor and as soon as the feed went below the sensor an order was placed for X days from that moment.  The days could be calculated based upon assumed consumption for animals of that size/age etc.

All of these strategies can be modeled in Grovestreams and passed into any feed mill software.

As with any of the sensors a full suite of intelligent alerting is available.  Example: Receive notification when a bin goes below a certain level, feed is ordered but hasn't arrived, intake is faster/slower than the assumed order rate among many others.

Much work is still needed on using these bin sensors to accurately order feed.  Initial results have shown promise.  Combining bin sensors with many other sensors ensures even better data and automation at a livestock site.

Grovestreams is a great IoT platform

Grovestreams is an IoT platform that is under the radar now; but that shouldn't last for too long.  I am listing 10 reasons Grovestreams is a great IoT platform for our solution.  Farmstreams is built on the Grovestreams platform and is leveraging the tools built to deliver value to livestock production.

1.  Simple to put data in and take data out of the store.  The APIs are published and open.  Easy enough that non-programmers can accomplish it.  Powerful enough for talented software developers to build apps and websites pulling and putting data in and out.  This also allows larger organizations to leverage Grovestreams for its cloud-based data gathering and analytics without sacrificing or needing to switch from the enterprise software they run their business with.

2.  Built with Big Data technology.  Scales to nearly unlimited size.  When it needs to get bigger, a new cluster is added.

3.  Cost.  A user can get started with a Free account to play around with developing a solution.  Pricing is data driven.  You pay for what you use.  No mandatory consulting fees or annual contracts.

4.  Quick to deploy a solution.  Whether its an app or a sensor feed, its easy and fast to run calculations, build dashboards and deploy your IoT solution.  Location/Map integration is also a nice feature.

5.  The roll-up stream data is a really efficient way to get to the data you need.  The in the field sensors can simply send raw data in.  Once received, they go to the store but then are accessed with the roll-up time selection (example hourly) and the preferred statistic (example average).  So, if you want the average hourly humidity, send the raw data in every minute and the data automatically rolls up to the hourly average.  Furthermore, minimum and maximum are also readily available in the store - so you can also view average, minimum and maximum on the same chart.  Even furthermore, you can monitor the quality of your data by monitoring gap counts in the rollup streams.

6.  The analytics package is really good.  You can run very complex expressions on any stream in the store.  You can then run more expressions on those created streams.  For example, I am calculating a feed bin inventory using data inputs from 5 different sensor streams and/or app entry streams.

7.    Blueprinting an organization makes setting up new organizations really easy.  When new sites (like a farm) needs to be set up simply create a blueprint and start the new organization exactly as the previous one was very quickly.  Also, switching organizations is all done in one log-in so a user can have access to all of their organizations without having to log out and log back in.

8.  The alerting engine is solid.  Users can get alerts upon arrival for those alarm type streams.  Users can run a condition alert, example temperature  > 32 send alert.  Or with latency, too much time has passed between data streams.  Features like time filters are effective in mitigating false alerts.  Example: feed latency alerts are ignored in the middle of the night.

9.  The dashboards to visualize the data are really good and easy to use.  Drag and drop graphs or spend more time and develop a super-dashboard.  A lot of well thought out features to quickly and accurately create the visual tools needed for stakeholders to your project.

10.  We are just at the beginning.  The base platform is already great.  With the enhancement roadmap laid out the platform will get even better.

So, why would I boast about this platform?  Shouldn't this be my best kept secret?  First, I want customer farms and potential customer farms to know how good this back-end solution is.  Feedlogic's focus is on providing intelligent and connected devices at the farm.  Without a platform like Grovestreams that endeavor is somewhat pointless,  Second, the IoT space is like a really large sandbox right now.  There is plenty of room for a lot of people to play in it.  For Farmstreams to continue improving more and more people need to find Grovestreams and use it.  Then Grovestreams can grow its support system, add enhancements and developer networks can be started for collaboration within and across industry can make all solutions better.  I encourage you to check it out or contact us with questions/comments.

Sensor Spotlight: Poultry Scale

Poultry scales are not new technology for chicken or turkey producers to incorporate in their live production operations.  Weighing birds has many advantages throughout the supply chain starting in the live production area (nutrition, vet services, etc) to finished production planning, sales and marketing and accounting.  Many stakeholders in a poultry production system have a need for accurate, timely live weights in the barn.

The average weight itself has some limit to its value.  It is valuable to understand nutrition and other factors from a learning and KPI standpoint.  The more frequent weights and accurate, frequent, surrounding data the more learning and improvement a system can gain.  What producers really want is an estimate of when a weight that triggers an event (like marketing) is going to be obtained.  Example: in 4 days the weight should be 6 pounds.  This is the crucial information needed for planning within an organization.

A quick google search shows many poultry scale options.  Any follower of this blog will know that FarmStreams is all about getting the data off the farm and into the cloud where it can be accessed and consumed by the users who need the information but are not going to the farm every day.

The FarmWeight VEIT Bat2 scale is a scale we have had success implementing with the FarmHub patform.  If a producer is already invested in a different type of scale a retrofit is possible; but this is one that we have successfully connected to the cloud and is ready to install today.

It offers the following features.

1.  Wireless connectivity to Grovestreams data platform.  Which can in turn be pushed into an enterprise system.

2.  Network multiple scales over a single connection point at a site.

3.  24/7 monitoring and reporting of the following:
a. average weight (male & female)
b. weight gain
c. number of samples

4. Alerting if certain weight related thresholds occur.  The thresholds can be variable and change with other data or time passing.

5. Data allows a producer to predict market dates.

Beyond just the single data points related to bird weights integrating with feed data, temperature, water usage and other data surrounding the environment of the barn in real-time in a powerful analytics engine like Grovestreams allows producers to glean new information to improve processes even further.

Similar to the other sensors, the data is valuable on its own as discussed above and can have even greater value as part of a larger more complex analytics program on the farm.

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.

Tracking medication use on the farm

Medication use, specifically antibiotics on the farm are a spotlight issue for animal agriculture.  Consumers, restaurants, retailers and politicians are joining the discussion.  Traceability is a common buzzword that is heard on medications at the farm.  This is a particularly difficult issue to install an iot solution around because of the intrinsic need for people to execute at the ground level.  Since we are not medicating animals daily, it is not a part of the daily routine, which makes it more difficult to train people to execute these important processes.  We think the data platform and mobile app we have developed can help.  Here is what we are doing in FarmStreams:

The mobile app allows two different type of updates:

1.  A QR code or NFC type system where medications are bar-coded or QR coded before going to the farm.  Each doser or medicator in the farm site is also bar coded or NFC coded.  A barn worker would scan in the medicine, verify its correct.  Enter the amount.  Then scan the doser at the water line before setting it.  Repeat same process for stopping the medicine only just scan the doser code and STOP.

Some snapshots of what that looks like is below:

   

2.  If the QR/barcode/NFC type system is too complex we also have the option to just have the barn worker use the app to select from a drop-down menu what and where they are adding meds to the water.  Enter the amount.  When finished stop the medication in the app.

The mobile app can also be set up to do other process verification steps such as:

1.  Have the vet dispatch instructions for a specific group to be given a specific medication and a specific amount by a certain time.

2.  Send customized and frequently updated instructions/messages for the selected medication.  Withdrawal days, mixing instructions, other pertinent data that may not be on the bag itself.

3.  An email can be sent to the vet notifying them the medication event began / ended.

4.  If the medication event has not occurred within a specific timeframe then an alert notifying the vet and supervisor is also sent.

The mobile app cannot ensure that the medication that was entered into it actually got into the water and to the animals.  These processes break down quickly when you don't have participation from the workforce.  We have discussed labor quality previously in the blog.

On the sensor side most of the dosers in the market today do not have cloud connectivity or even local data storage.  This often makes people throughout the organization blind to what is going on inside the farm.  If there are issues like plugged diaphragms they must be troubleshot and recorded by the worker on site.  Data quality is often compromised and not uniformly gathered.

There are newer doser products that are sold at Farm Tech Store that connect to the cloud using the MultiSense sensor gateway.  These measure water consumption, medications injected (how much and when) to the cloud.  When combined with the data entered in the mobile app, you have a report of exactly what went in the water, how much and at what times.  Critical streams needed for a good traceability program.

One issue that is not resolved yet is having that medicine / medicator handshake on what product is going into the water.  You still need a human to enter that data, a potential weak link in the data chain.  In the future some type of cartridge or other medication reading technology may be placed within the medicator hardware; but for now that is futuristic thinking.  It can be done; but need someone to pay for it.

Another issue that is possible; but not practical today is to have the vet receive an email telling them that the medication is in the medicator ready to be inserted into the water.  The medicator can be started with an approval from the vet's mobile app.  100% possible, impractical to develop until someone says they want that level of control over their medications on the farm.

When we get over to the data side in Grovestreams this is where we can put some logic and alerts around checks / balances to ensure the processes are followed properly.

For example,

If a vet has dispatched a medication event, set an alert that lets you know if it has not been done within 4 hours in the barn.  Double check not only the app but also the medicator data stream.  The medication should be entered into the app and flowing to animals within X hours or vet/supervisor are being alerted.

Once the medication has started check to see if it has stopped by X hours.  If it is still medicating after 48 hours for example, send an alert or if medicator is set up to be turned on/off remotely, turn off remotely either with software or with an app.

Cross reference other data in the store.  If a specific medication shouldn't be given to birds greater than 24 pounds.  Check that, cross reference it.  If its greater, send an alert.

Produce reports that document how much and over what times were medications given by barn.  Further analytics from the feed sensors, scales and water lines would dive into whether they were effective and possibly deliver payback scenarios in real-time.

There is technology that can help organize the process around medications on the farm.  However there is not an easy button.  It still requires 100% buy-in throughout the organization in the value of the data and a commitment to the process.

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.