Detecting more than fill level in farmers’ bins with machine vision How INO and BinSentry are revolutionizing the animal feed supply chain industry with 3D sensors. ino.ca SHEDDING LIGHT Case study DETECTING MORE THAN FILL LEVEL IN FARMERS’ BINS WITH MACHINE VISION INO — CASE STUDY I 2 close collaboration An agricultural Iot company specializing in feed supply chain solutions, BinSentry is helping to reduce feed costs and eliminate operational efficiencies in the animal feed industry through highly accurate inventory monitoring of onfarm feed bins. Their flagship solution was based on a LiDAR system which used a single beam pointing downward from the top of the feed bin to detect diminishing feed levels. Understanding how even the slightest disruption in the supply of feed for the farmer’s livestock can result in significant losses and increased costs, BinSentry was interested in developing a solution which would provide farmers and feed mills a highly accurate portrait of feed inventory levels inside the bins in real-time. Looking to leverage INO’s expertise in machine vision based on 3D sensors, BinSentry approached INO for consultation and assistance to go further with their idea. BinSentry and INO collaborated on this project from 2018 to 2022. the client BinSentry Kitchener, ON https://www.binsentry.com Project date: 2019-2022 With BinSentry’s best-in-class 3D sensors and innovative software, feed mills and producers are reducing feed waste and miles traveled, optimizing truck loads, and eliminating accidents from climbing bins as they work to provide high-quality protein for a growing global population. DETECTING MORE THAN FILL LEVEL IN FARMERS’ BINS WITH MACHINE VISION INO — CASE STUDY I 3 Detection of fill levels It is critical for livestock farmers to keep track of how much feed is in their bins to ensure a steady inventory to avoid feed outages and overfills. To determine feed levels, farmers may manually check the bins by climbing to the top of it to measure the height of the grain or hitting the side of it with a rubber mallet to estimate the remaining feed level. These traditional methods often result in inaccurate and unanticipated, low inventory levels. Operational efficiency Feed mills rely on farmers to report when their feed bins are going to be empty. Delayed reporting or inaccurate data can result in last-minute orders, causing disruptions in production schedules and delivery. These inefficiencies in operations result in increased costs for raw materials, transportation, and labour for feed mills. Addressing the Challenges – From farms to feed mills DETECTING MORE THAN FILL LEVEL IN FARMERS’ BINS WITH MACHINE VISION INO — CASE STUDY I 4 A customized solution for accurate detection When BinSentry and INO began working together, INO’s remote sensing team demonstrated the use of a time-of-flight camera module for collecting 3D profile measurements, which led to testing prototypes in feed bins. INO then worked with BinSentry to de

1. Detectingmorethanfilllevelinfarmers’
binswithmachinevision
How INO and BinSentry are revolutionizing the animal
feed supply chain industry with 3D sensors.
ino.ca SHEDDING LIGHT
Case study

2. INO — CASE STUDY I 2
DETECTING MORE THAN FILL LEVEL IN FARMERS’ BINS WITH MACHINE VISION
close collaboration
An agricultural Iot company specializing in feed
supply chain solutions, BinSentry is helping to
reduce feed costs and eliminate operational
efficienciesintheanimalfeedindustrythrough
highly accurate inventory monitoring of on-
farm feed bins. Their flagship solution was
based on a LiDAR system which used a single
beam pointing downward from the top of
the feed bin to detect diminishing feed levels.
Understanding how even the slightest
disruption in the supply of feed for the
farmer’s livestock can result in significant
losses and increased costs, BinSentry was
interested in developing a solution which
would provide farmers and feed mills a highly
accurate portrait of feed inventory levels inside
the bins in real-time.
Looking to leverage INO’s expertise in
machine vision based on 3D sensors,
BinSentry approached INO for consultation
and assistance to go further with their idea.
BinSentry and INO collaborated on this project
from 2018 to 2022.
the client
BinSentry
Kitchener, ON
https://www.binsentry.com
Project date: 2019-2022
With BinSentry’s best-in-class 3D sensors
and innovative software, feed mills and
producers are reducing feed waste and
miles traveled, optimizing truck loads,
and eliminating accidents from climbing
bins as they work to provide high-quality
protein for a growing global population.

3. INO — CASE STUDY I 3
DETECTING MORE THAN FILL LEVEL IN FARMERS’ BINS WITH MACHINE VISION
Detection of filllevels
It is critical for livestock farmers to keep track
of how much feed is in their bins to ensure a
steady inventory to avoid feed outages and
overfills. To determine feed levels, farmers
may manually check the bins by climbing to
the top of it to measure the height of the grain
or hitting the side of it with a rubber mallet
to estimate the remaining feed level. These
traditional methods often result in inaccurate
and unanticipated, low inventory levels.
Operationalefficiency
Feed mills rely on farmers to report when
their feed bins are going to be empty. Delayed
reporting or inaccurate data can result in
last-minute orders, causing disruptions in
production schedules and delivery. These
inefficiencies in operations result in increased
costs for raw materials, transportation, and
labour for feed mills.
Addressing the Challenges –
From farms to feed mills

4. INO — CASE STUDY I 4
DETECTING MORE THAN FILL LEVEL IN FARMERS’ BINS WITH MACHINE VISION
Acustomized solution for accurate detection
When BinSentry and INO began working
together, INO’s remote sensing team
demonstrated the use of a time-of-flight
camera module for collecting 3D profile
measurements, which led to testing prototypes
in feed bins. INO then worked with BinSentry
to develop a hardware solution capable of
meeting the required specifications while
also partnering with them to develop data
processing algorithms to convert camera data
to 3D feed depth profiles into their advanced
software.
The Millof the Future
The BinSentry 3D Bin Monitoring Sensor is
a solar-powered sensor which provides over
9,000 data points in the bin, resulting in the
widest field of view for mapping the complete
interior of a feed bin in 3D.
Installed at the top of the feed bin, the 3D
sensor takes readings of the feed bin every 4
hours. Farmers can monitor their feed bins
online, while the feed bin sensor data, such as
feed levels and distances, is sent directly to the
feed mill via wireless networks.
Making life easier for farmers
Using the 3D monitoring sensor, farmers and
feed mills can view the entire bin interior from
any angle to see the exact feed level and feed
flow. Unlocking this information provides
both parties 24/7 insight into on-farm feed
inventory, helping them better manage their
livestock by tracking exact feed consumption
levels to reduce feed waste and outages.
Revolutionizing the
feed logistics industry
Making life easier for feed mills
To create a more efficient, proactive feed
supply chain, feed mills can view the 3D models
of the feed bins to see feed levels in real-time
and project empty dates. Having this level of
visibility helps to optimize feed mill production
and transportation schedules to operate more
efficiently – delivering feed to the farms only
when necessary.

5. INO — CASE STUDY I 5
DETECTING MORE THAN FILL LEVEL IN FARMERS’ BINS WITH MACHINE VISION
Whyworkwith INO?
INO’s extensive expertise in vision systems was
a fundamental contributor to the development
of the machine vision 3D sensors for BinSentry.
In this project, INO worked with BinSentry and
a commercial supplier to develop a customised
3D profiling camera and assisted with the
data collection and processing, and artificial
intelligence algorithms that convert the camera
raw data to actionable feed profiles.
Working with its partners, INO proposes a
5-step integrated process for the development
of innovative technologies. BinSentry and INO
completed the first 4 of these steps together.
From requirements analysis of studying all
the possible approaches to the challenge,
to the solution design, proof-of-concept
and prototyping and validation step, INO
closely collaborated with the BinSentry team
throughout the project.
INO’s Structured Five-Step Approach

6. Learn more
Contact us!
INO has been very professional
throughout the entire process.
There were times when we weren’t
sure what we wanted to do, but
INO was always patient with us. At
one point we changed course quite
substantially which changed how
INO was involved but INO continued
to offer the same high-quality advice
and service.
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- Nathan Hoel, Chief Technology Officer
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