AI has arrived in trucking and fleet management. Akin to a smart helper, it can contribute to making routes smarter, saving fuel and ensuring smoother fleet operations.
Driven by data, fleet management AI solutions can help fleets keep trucks on the road longer by optimizing maintenance schedules. They can also relieve back-office personnel by handling administrative tasks and scheduling, for example.
AI driver safety enhancements such as cameras can monitor fatigue and unsafe driving behaviors, making training sessions more productive and allowing for real-time fleet performance monitoring.
There is no doubt about it: AI isn’t just an upgrade, it’s essential for fleets to boost driver happiness, enhance road safety, and ensure smooth fleet operations. In our webinar, “Using Data Analytics & AI to Simplify Fleet Operations”, hosted by FreightWaves, we explored the buzz around AI, how it can be specifically applied to the trucking industry, its practical impact, and ethical considerations.
The Power of Big Data in Freight Transportation
Imagine trying to solve a puzzle with a million pieces. That’s what handling big data with no experience can feel like. But what if you had a way to understand exactly where each piece goes? That’s where AI in trucking and fleet management comes in.
We have been aware of the importance of big data for a while now. Since 2016, our telematics collects vast amounts, every day, from every truck of every fleet we collaborate with. We collect over 200 terabytes of data per year.
However, we are deeply aware that it’s not just about the quantity. We also uphold high standards in terms of data variety and data quality. High-quality data can help AI generate high-quality insights, which will greatly aid fleet managers in making smart fleet management decisions. This includes planning better routes and optimizing truck maintenance schedules.
Using AI for Driver Happiness
Driver happiness—for a fleet, it means higher safety scores, smoother operations, a more positive company culture, and better retention rates.
AI-driven fleet management trends, such as sentiment analysis programs, can analyze how drivers talk to the back office or how they handle their routes. With trucking industry AI innovations such as these, fleet managers can ensure that drivers are not just getting the job done, but that they’re feeling good doing it.
Trucking Operational Efficiency and AI
Drivers feeling good on the job is just a start. AI in trucking and fleet management can also help drivers drive better. For instance, our ISAAC scores that come with the ISAAC Coach assess driver behavior in real time.
Guiding drivers towards smooth acceleration and turns, as well as eco-driving practices, has been shown to increase fuel efficiency and safety scores. The result is improved fleet performance, all powered by AI in the trucking industry.
Ethical AI Trucking Practices—A Must
As Corey Cox from the Tandet Group of Companies recognizes during our webinar on the subject, fairness, reliability, privacy, transparency, accountability, and inclusiveness are the six pillars that sit at the base ISAAC’s ecosystem. Or, in other words, with great power comes great responsibility. At ISAAC, we fully recognize the meaning of this saying.
Our teams are aware of AI’s potential and its dangers, and therefore have put strict policies in place concerning data handling. We also place a high priority on isolating client data for our AI’s learning capabilities, to minimize cross-contamination of results between different organizations or unauthorized data sharing. These measures not only protect our clients’ privacy, but also enhances the data quality, which in turn will help fleet managers make better and more informed decisions.
Real-World Applications of AI in Trucking and Fleet Management
What are some other examples of how AI can help in fleet management?
AI technology is great at looking at vast amounts of data and identifying patterns and trends without the setback of human error. For instance, take the holiday season, a time where reduced staff and more deliveries can really highlight a fleet’s inefficiencies. By analyzing idling patterns in bulk, an AI program can allow fleet managers to adjust schedules, routes, or staffing levels proactively, making sure that the fleet performs at its best, even during peak times.
Another example would be the ISAAC score. As an aggregation of vast amounts of data points, it can show a fleet manager how effective strategies have been year over year. These strategies, whether targeted at driver performance, fuel efficiency, or safety, can be globally improved much faster and efficiently with the aid of AI.
Lastly, AI can help fleet managers identify safety incidents at particular locations. By aggregating and analyzing data on near misses or accidents, ISAAC’s AI can highlight high-risk areas or times, enabling targeted interventions such as enhanced driver training or route adjustments to mitigate these risks. This capability not only enhances safety but also contributes to long-term cost savings by reducing the likelihood of accidents.
Bringing Data-Driven Decisions to Trucking Companies
The positive effect of AI on fleet operations is undeniable. Improved safety, higher fleet efficiency, and increased driver happiness are all effects of making sense of collected data with technologically advanced tools.
With ethical handling of data and future-facing strategies in place, such as client-protected data handling and analysis, we aim to put the vast amounts of data we collect and interpret every day at the service of the transportation industry. By helping carriers to make more informed decisions and act more intentionally, we can all contribute to the greater good of the communities we serve.
