Dmitri Fedorchenko, CEO and co-founder Doftan online freight shipping marketplace that matches shippers and truckers across the US
On its opening days COP26, it became clear that the event would not achieve the lofty goals needed to address the climate crisis. For example, instead of agreeing and implementing specific policies, world leaders at the G20 summit tossed coins at Fontana di Trevi in Rome for “luck” to face the climate crisis.
Luck is not going to change our current trajectory towards catastrophic climate change. However, artificial intelligence can.
If we want to change our current course, we need the commitment of the private sector. In the words of Paul Polman, “Sustainability makes business sense and at the end of the day we’re all on the same team.”
According to an October 2021 article by Analytics Insightthe global artificial intelligence in transportation market is projected 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 processes to create less waste would be extremely beneficial for both the private sector and the future of the planet .
What is the environmental impact of the shipping industry?
Shipping waste is where most of the pollution in the private commercial sector comes from, mainly carbon dioxide emissions. According to Environmental Protection Agency data cited by FreightWaves, passenger and freight transportation was responsible for a total of 28% of GHG emissions in 2018, equivalent to 1,870 million metric tons of CO2. As freight demand increases, so do CO2 emissions.
Another byproduct of transportation waste is fuel or energy consumption. The fuel is manufactured in factories, emitting CO2 into the atmosphere. The less fuel trucks use when delivering cargo, the lower the overall emissions.
From now on, 78% of the S&P 500 have internal corporate environmental impact targets 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 artificial intelligence can optimize resources
AI applications in transportation include more than driverless vehicles. On wider scaleartificial intelligence can help solve a variety of problems in transportation, related to safety, reliability and predictability, as well as efficiency and sustainability.
The number one way AI can optimize resources in transportation and shipping is by optimizing backhauls. Thirty-five percent of all miles driven by unloaded trucks. An empty truck that is not performing its primary function is a complete waste of fuel. To find a return shipment, truckers and companies must either search for them on load tables or call multiple brokers, which takes a lot of time and effort in a world where profit depends on efficiency.
Multiple AI applications help drivers find and provide backhauls. Digital freight applications like Convoy, Uber Freight or my company, Doft, have designed solutions to solve the problem of empty return trips. Freight applications allow trucks to book backhauls immediately when a load is booked or grab multiple orders to achieve a longer non-empty return trip. By efficiently loading the truck and constantly holding backhauls early in the journey, companies reduce empty kilometers, effectively reducing CO2.
Artificial intelligence can also be used to reduce greenhouse gas emissions from the electricity industry. Electricity represents 25% of greenhouse gas emissions Worldwide. There is a place for artificial intelligence to optimize the electricity grid, increase energy efficiency and enhance reliability and resilience. To do this, AI can identify factors that most affect energy demand and immediately optimize energy production.
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 hot exhaust from cars, also called waste heat. It suggests that AI can help with isolation the potential energy that will be discarded before it is lost. We already know that something like this is possible because Google used artificial intelligence to reduce the excessive heat of its data centers 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 achieve what world leaders have yet to achieve, every business must adopt a three-, five- and ten-year pollution and emissions reduction roadmap and stick to it, no matter what the cost. This idea may seem scary to businesses where the main goal is to reduce 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 is not even close to being solved is that it is not profitable to do so.
Some challenges that business leaders in the transportation industry may face as they adopt AI solutions include computing power and trust deficit. To use artificial intelligence solutions, companies must be able to provide adequate computing systems. Many companies in the transportation industry have not yet implemented as many technology solutions as other industries and may need to catch up in terms of available technology. Because of the many unknown variables in how deep learning models predict the outcome, it can be difficult for companies new to applying AI technology to trust it at first.
Integrating AI technology into commercial enterprise will create solutions to 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, commercial companies must step up and follow the latest AI technology and quality standards in their field and move towards cleaner production where possible — at every stage of the business cycle.
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