Today is a big day for us.  After two Small Business Research Awards,  one 
from DoD and one from USDA (which ended this August), we are launching the  
Beta testing Phase of our Honey Bee Acoustic Scanner, starting with a  
presentation this morning at the Montana Beekeepers Association Meeting in  
Bozeman by Robert Seccomb, the Principal Director for this project, and one of  
my research and business partners.
 
I really wanted to be there, but some bug hit the family this week, and  
I've had to stay home. Call me Nurse Crabby.
 
We've struggled with making this device affordable - and we finally  made 
the breakthrough when a new technology became available in July.   The good 
news is that we managed to use this  to put  together a  prototype device.  
Bad news, we're out of money, just as it is time to  calibrate the unit.  As 
of current date, its about 86% accurate for several  variables like varroa 
mites, Nosema, queenless.  Does really well for  Africanized bees - but 
that's based on a really small set of AHB  recordings.
 
We accomplished two things this summer - produced a working prototype, and  
expanded the acoustic sampling system from the audible (to humans) into the 
 ultrasonic (up to 75,000 HZ).
 
Moths jam bat sonar by producing ultrasonic sounds, and we expect to find  
some mechanical sounds in this range from activities such as chewing by  
beetles.  We've already found some ultrasonic sounds (possibly harmonics)  from 
queens.  We also suspect that there may be less background  environmental 
noise in the ultrasonic range deep inside a beehive.
 
In practice, one walks up to an undisturbed hive, slides in a 12" long,  
1/8" diameter probe microphone and take a recording.  For the Beta phase  
testing, we're asking for a two minute recording.  In use, when trained,  the 
device only requires a 30 second recording.
 
The system identifies pests and diseases, based on the sounds produced by  
the colony, using Artificial Neural Networks (ANNs).  That's a fancy  way of 
saying the computer programs use pattern recognition - same system used  to 
process human speech.  The more recordings of known variables (such as  
presence of mites at specific levels), the better it gets.  In fact, not  only 
do we train on multiple recordings, we also use multiple training systems  
(networks of ANNs all processing the data together).  
 
For the Beta testing, we are conducting a pre-sale of the device.  We  will 
sell it for our cost (~ $650) plus shipping, and will supply two 32 GB SD  
cards.  We want experienced beekeepers and researchers.  We ask each  
participant to record colonies, then inspect and quantify where possible  
conditions like mite presence, levels.   We're working on a  checklist.  Then, when 
a card is full, send it with the colony report to  us.  Robert Seccomb, who 
is my research partner and developer of the unit,  will use these data sets 
to retrain and upgrade the system.  The  participant will get an empty SD 
card back, and periodic updates to the  software.
 
As an example, the device is currently scoring about 96% on Africanized  
Bees, but that's based on a small number of very African hives.  If we can  
get recordings of 100 or even 1000 AHB colonies, the pattern recognizing  
software can only get better.
 
So we plan on conducting a year-long Beta testing by real customers in  
their real environments prior to the release and sale of the device.   The very 
good news is that we had 7 years of funding from DoD and USDA to work  out 
the kinks, produce the prototypes.  We've a draw full of units that are  now 
obsolete.  We've gone down many exploratory paths that resulted in no  
improvement or even failure.
 
The prototypes are being hand built, so the cost is still higher than I  
like.  If, in the Beta testing, we could get orders for 100 units, the  
supplier of some of the main components will cut the cost of the parts by as  much 
as 26%.
 
Since we're out of money, so to speak, I'm looking for funding to cover the 
 cost of cleaning up (for the training sets, we have to remove background 
sounds)  the data sets, entering them into our library, then processing with 
the ANNS,  and finally upgrading the algorithms in the device).  Again, 
looking to  cover costs, so we're going to ask - if we sell this  to you at 
cost, would  you  donate something for the data processing and device updates?   
Maybe an annual subscription?
 
Bottom line, we could go back through the competitive grant process, try to 
 find funding for the Beta stage, but that will delay everything by another 
 year.  Or, we can go to the potential users.
 
The more units, the more verified data files, the faster they come in, the  
quicker this system will convert from a research prototype into a useful  
tool for bee management.
 
You can see what the prototype looks like on my personal Facebook page  
(jerry bromenshenk).  Nice thing  about  having a unique name,  there's only 
one on Facebook.  We're working on a web page for the Beta  testing.
 
Thanks

Jerry
 
 
 
 
 
 
 

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