We are sitting on this mountain of information.
We are only looking at the tip of an iceberg,
and there's all this data out there—
which is high value data—
observations about our planet Earth,
and we're not taking advantage of that
to make better decisions?
Perhaps more than ever,
the climate crisis is creating
strains on businesses—
from damage to their assets,
disruptions to their supply chains and operations,
as well as increasing pressure
from consumers and regulators
to create and meet sustainability goals.
How do you prepare
for the impact of climate change
in a smarter way?
IBM is working on technologies
designed to bridge the gap
between climate science
and business operations,
bringing IBM Research innovations
into AI powered software
that businesses can start using today.
This begins with the ability
to digest and analyze
massive geospatial datasets.
Put simply,
geospatial data is information
that describes objects,
events,
or other features
with a location on or near
the surface of the earth—
such as maps
weather,
agricultural,
and air quality data.
In the climate domain,
you deal with very large datasets.
Climate data is massive.
And that means
you have to be very very clever
how to avoid data movement.
Because each time you move data,
it will slow you down.
To help solve this problem,
IBM Research developed
a geospatial analytics engine—
powered by AI and the hybrid cloud.
Think about satellite observations—
you observe imagery information
of our planet Earth.
And so, how can I analyze it?
How can I understand for example,
the tree growth,
vegetation growth,
how much carbon is being stored
in that vegetation.
That's all geospatial analytics.
But the true power
for companies is unlocked
when combining the geospatial analytics engine
with a new Climate and Environmental Impact Modeling Framework.
This innovative framework is powered
by a set of AI accelerators
designed to help clients efficiently
predict the risk and potential impact
of upcoming climate
and weather threats to their business.
At the end, climate affects people,
affects buildings if there are floods, right.
It affects highways.
So it's really the geospatial context
of that information,
which means you’ve got to
combine that eventually.
You've got to combine
flood risk information
with the road information,
with elevation information,
with many other sets of information
to understand:
what is the impact?
What's the economic damage of a flood?
It allows you to deploy,
develop,
and run AI models
on top of all this
massive curated geospatial data—
climate data.
So let's say you're a utility company.
You have tens of thousands of substations
which you use to supply electricity,
right, to your customers.
And so the question comes:
which of those asset locations
are at the biggest risk, and when?
How would you prioritize it?
How would you prepare these sites?
In which order?
How do you allocate your investments?
So we are not just about
letting people know about the risks,
but we then eventually feed it
into a list of priorities
which then go to actionable
business decisions and insights.
Really, it's all about the actions.
Developed in IBM Research
and commercialized through the
IBM Environmental Intelligence Suite,
the innovations are available
to businesses right now.
The suite brings
a wide variety of weather,
climate,
AI,
and operational technologies
into a single software solution
that companies can use
not only to predict climate risk,
but also to help manage
sustainability initiatives.
It also includes a new
carbon performance engine that provides
an efficient way for companies
to track their carbon footprint.
Every business needs to account
and measure its carbon footprint.
But accounting is just the first step.
Now the next question comes,
how can I improve on my carbon footprint?
How can I improve the carbon performance?
And that's where
the carbon performance engine can help.
Using AI such as natural language processing
helps capture data across
different emission types,
which can provide a view of emission hotspots
for companies to target areas
to reduce their emissions.
You can use the carbon performance engine
to optimize order fulfillment.
You as a consumer,
you might order something.
It can come from different places.
It can come from a store.
It can come from a warehouse.
There are different shipping options.
You may want to get it immediately
or you may have some time.
There are different cost options.
So how do you make that decision
to execute on that order fulfillment?
And the carbon performance engine
has the intelligence,
it has the ability,
to take carbon information
then optimize across
all these different objectives
and then eventually come to
the best business decision.
The advancements are part of
IBM's efforts to accelerate
the development of technologies
intended to help society mitigate
and adapt to climate change.
By bringing these innovations
from the lab into IBM software
that can integrate with broader
business technologies,
organizations can begin
taking the practical steps
to becoming more sustainable
and resilient.
Whether it's extending the life
of physical assets,
optimizing their supply chains,
managing the impact of climate change
on business operations,
or even running more efficient
IT operations.
IBM software can also help
companies analyze the vast amounts
of sustainability data
scattered throughout their business—
helping them address compliance mandates
and regulatory requirements
and streamline environmental reporting initiatives.
Fundamentally,
what we're really trying to see is:
How can we accelerate
through these technologies
finding viable
solutions and applications
to solve this climate crisis?
Because time is of the essence.
There's no time to be wasted here.