In the opening days of COP26, it became clear that the event would not accomplish the lofty goals necessary to tackle the climate crisis. For example, instead of agreeing to and implementing concrete policies, world leaders at the G20 summit all threw coins into the Trevi Fountain in Rome for "luck" to face the climate crisis.
Luck isn't going to change our current trajectory toward catastrophic climate change. However, AI might.
If we want to transform our current course, we need the private sector's commitment. In the words of Paul Polman, "Sustainability makes good business sense, and we're all on the same team at the end of the day."
According to an October 2021 article by Analytics Insight, the global AI in the transportation market is predicted to reach up to $3.8 billion by 2025 and is estimated to grow at a CAGR of 15.8% during 2020 to 2025. Optimizing AI resources and procedures to create less waste would be hugely beneficial for both the private sector and the planet's future.
What's The Shipping Industry's Environmental Impact?
Shipment waste is where most pollution in the private commerce sector comes from, mostly carbon dioxide emissions. According to Environmental Protection Agency data cited by FreightWaves, passenger and freight transportation was responsible for a total of 28% of the GHG emissions in 2018, the equivalent of 1,870 million metric tons of CO2. As the freight transportation demand increases, so do the CO2 emissions.
Another byproduct of shipment waste is fuel or energy consumption. The fuel is manufactured in factories, emitting CO2 into the atmosphere. The less fuel that trucks consume while delivering cargo, the lower the total emissions.
As of now, 78% of the S&P 500 have internal corporate environmental impact goals related to sustainability and carbon reduction. To transport more efficiently with less pollution, companies should use an ecological type of transport, such as electric, or rethink the structure of a particular supply chain. Optimizing logistics at every stage can yield significant results.
How AI Can Optimize Resources
AI applications in the transport sector include more than just driverless vehicles. On a broader scale, AI can help solve a variety of problems in transport, related to safety, reliability and predictability, as well as efficiency and sustainability.
The number one way AI can optimize resources in trucking and shipment is by optimizing backhauls. Thirty-five percent of all miles are driven by unloaded trucks. An empty truck not performing its primary function is a complete waste of fuel. To find a return load, truckers and companies have to either look for them at load boards or call multiple brokers, which takes up a lot of time and effort in a world where profit hinges on efficiency.
Multiple AI apps help drivers find and deliver backhauls. Digital freight apps such as Convoy, Uber Freight or my company, Doft, have designed solutions to solve the problem of empty return trips. Freight apps allow trucks to book backhauls immediately when a load is reserved or grab several orders to achieve a larger non-empty return trip. By efficiently loading the truck and constantly booking backhauls early in the journey, companies decrease empty running mileages, effectively reducing CO2.
AI can also be utilized to reduce greenhouse gas emissions from the electric power industry. Electric power accounts for 25% of greenhouse gas emissions worldwide. There is a space for AI to optimize the power grid, increase energy efficiency and enhance reliability and resiliency. To do this, AI can identify factors that most impact energy demand and immediately optimize energy output.
Amy L. Stein, a professor at the University of Florida Levin College of Law, notes that 68% of energy produced in the United States is "lost to the environment." This explains things like the warm exhaust from automobiles, also called waste heat. She suggests that AI can help isolatewould-be rejected energy before it is lost. We already know something of this caliber is possible because Google used artificial intelligence to reduce its data centers’ excess heat production by 40%. Using AI to address these energy inefficiencies has the potential to reduce greenhouse gas pollution in half by 2050.
How The Private Sector Can Pollute Less
To accomplish what world leaders haven't been able to yet, every business must adopt a road map to reduce pollution and emissions for three, five and 10 years and follow it, no matter how much it costs. This notion may seem scary for businesses where the main objective is to cut costs, save money and earn more, but it is a price that must be paid for the sake of humanity. The reason the climate crisis isn't even close to being solved is that it's not profitable to do so.
Some challenges business leaders in the transportation industry may face as they adopt AI solutions include computing power and trust deficit. To use AI solutions, companies must be able to provide adequate computing systems. Many companies in the transportation industry have yet to implement as many tech solutions as other industries and may need to play catch-up in terms of the available technology. Due to the many unknown variables in how deep learning models predict the output, it may be hard for companies new to implementing AI technology to trust it at first.
The integration of AI technology into the commerce business will create solutions for pollution. And AI innovations will also lead to more profits and a competitive edge in the market. To save the world as we know it, commerce companies must step up and follow the latest AI technology and quality standards in their field and move toward cleaner production wherever possible — at every stage of the business cycle.
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Dmitri Fedorchenko, CEO and co-founder of Doft, an online freight shipping marketplace matching shippers and truck drivers across the U.S. Read Dmitri Fedortchenko's full executive profile here.
Source: Forbes