OSPE - The Voice - May 2019 - 20

COVER

Picture courtesy of indus.ai

Statistical analysis of large amounts
of data is used by a technique known as
Machine Learning (ML) to find elements
that correlate to a certain classification
(e.g. dump truck vs. concrete truck).
While this seems like an extraordinary
feat, ML applications remain narrow
and deeply algorithmic, relying on
iterative numerical calculations to find
an optimal classifier.
It has been enabled by the massive
amount of data and computational
power now available. Machine Learning
has opened up the possibility for
machines to be applied to new industries
and consumer needs, typically those
involving unstructured/analog data
inputs (such as video & images, analog
sensor or financial data, handwritten
text & speech as well as natural
language) that were too difficult to
classify programmatically.
Thanks to early government support
and the presence of strong technical
talent in Ontario, the province has
gotten a head start in AI innovation.
In 2012, a team at the University of
Toronto achieved the highest score in
image recognition at the ImageNet Large
Scale Visual Recognition Challenge
(ILSVRC) using a Machine Learning
technique known as Convolutional
Neural Network (CNN). This has
20

THE VOICE

Summer 2019

helped establish Ontario as a hotbed
for AI innovation which has enticed
heavyweights such as Google and Uber
to establish operations in Toronto, along
with a healthy round of start-ups.
One such San Francisco/Toronto
start-up, indus.ai, has specialised
in AI-based video analysis for the
construction industry. Indus.ai is able to
significantly improve safety and provide
real time information on progress at the
construction site. Consider the video
feed in the animated picture below.

Picture courtesy of indus.ai

In this example, indus.ai's model is able
to use live video feed from constructionsite cameras to simultaneously detect
missing Personal Protective Equipment
(PPE), track progress towards the
construction blueprint and log arrival
and departure time for specialized
equipment such as a concrete mixer

In 2012, a team at the
University of Toronto
achieved the highest
score in image recognition
at the ImageNet Large
Scale Visual Recognition
Challenge (ILSVRC) using a
Machine Learning technique
known as Convolutional
Neural Network (CNN).
This has helped establish
Ontario as a hotbed for
AI innovation which has
enticed heavyweights
such as Google and Uber
to establish operations in
Toronto, along with a healthy
round of start-ups.


http://www.indus.ai http://www.indus.ai http://www.Indus.ai http://www.indus.ai

OSPE - The Voice - May 2019

Table of Contents for the Digital Edition of OSPE - The Voice - May 2019

Table of Contents
OSPE - The Voice - May 2019 - Cover1
OSPE - The Voice - May 2019 - Cover2
OSPE - The Voice - May 2019 - Table of Contents
OSPE - The Voice - May 2019 - 4
OSPE - The Voice - May 2019 - 5
OSPE - The Voice - May 2019 - 6
OSPE - The Voice - May 2019 - 7
OSPE - The Voice - May 2019 - 8
OSPE - The Voice - May 2019 - 9
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OSPE - The Voice - May 2019 - 38
OSPE - The Voice - May 2019 - Cover3
OSPE - The Voice - May 2019 - Cover4
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