AI has been taking the world by storm. Every company in every industry has been finding ways to implement it to improve their existing operations. In this search, companies have found uses for AI like predictive analytics to be a hopefully improvement to operations. However, by seeking out AI on its own right away, they’re skipping a step in the implementation process. In order for AI to give suggestions on how to optimize your operations, it needs access to a strong base of data. AI, given the proper data, can improve your logistics operations more than you could imagine. But without that data, it won’t be able to do its job.


 

Increase Your ROI by Investing in AirFinder Everywhere

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  • Security Alerts. Know when a delay in shipment has occurred so the problem
    can be addressed immediately.

 

The Move to AI

Typically, people have one of two opinions on the use of AI. One being pro, with no hesitation. The other being against, in fear that AI would steal their job. AI will take over some menial job responsibilities that take long labor hours such as counting inventory, but that is usually a once a year count. Odds are, you have other responsibilities outside of that. AI doesn’t have to be seen as the machine stealing your job and money; it should instead be seen as your co-pilot, a tool to help you optimize your existing operations. The use of AI is shifting how fleet managers approach problem solving and decision making. This move toward AI represents not just a technological advancement but a fundamental transformation in how businesses operate, adapt, and thrive. Using an IoT platform paired with AI capabilities is a sure way to improve logistics operations. But why do you need that platform in the first place?

What You Need Before AI (And Why)

The integration of AI with access to current and historical location data is not just beneficial—it's essential for optimizing overall supply chain performance. Location data serves as the cornerstone upon which AI-driven logistics operations are built, providing crucial insights into the movement of goods, trailers, and personnel in real time. By leveraging collected location data, AI algorithms can dynamically adjust routes and allocate resources more effectively. Asset location data enables AI-powered predictive analytics in logistics, allowing organizations to anticipate demand and proactively address issues before they escalate. By analyzing historical location data, AI algorithms can forecast future demand patterns with a high degree of accuracy. But in order to analyze historical data, you first need to collect it. That’s where asset tracking comes in. By continuously monitoring the location and status of vehicles, containers, and other assets in real time, IoT systems provide the data that AI needs to optimize resource allocation, improve asset utilization, and enhance overall fleet efficiency. 

Location data facilitates enhanced visibility and transparency across the entire logistics chain, enabling stakeholders to track the movement of goods from origin to destination. This not only improves accountability and security but also enables rapid response to any unforeseen disruptions or delays. By providing stakeholders with real-time updates on shipment status, estimated time of arrival, and other relevant information, AI-driven logistics systems streamline communication and ultimately deliver a seamless and frictionless experience for all parties involved. The integration of tracking trailer location is indispensable for leveraging AI.

What AI Looks Like With Location Data

Equipment Utilization

Do you know what your utilization rate is? You likely have an estimate, but do you really know exactly which percentage of trailers are being used to their fullest extent? After all, if you don’t have a tracker on each of your trailers, how do you know for sure what that rate is? There’s a high chance if you’re not tracking your trailers’ usage, that some are going underutilized. Consider how much money that’s costing you. If you have just 5 trailers going underutilized, then that’s 5 trailers receiving maintenance when they don’t need it. That also means there are a significant number of trailers being overutilized, not receiving the maintenance they need or experiencing more wear and tear than necessary. When you track your trailers, you know where they are at all times. You know when they are being used and who they are being used by. Through historical usage data, fleet management AI can identify which trailers are going underutilized and work them into the rotation. On a larger scale, you can help out other warehouses that may be short on trailers. Logistics AI can determine which warehouse facility has extra trailers and which ones don’t have enough. It can help you plan where to send trailers so additionally purchases don’t need to be made. When you use asset tracking and AI in fleet management, you are able to cut costs by optimizing uptime and increase overall supply chain efficiency. 

Maintenance Efficiency

Maintenance efficiency was mentioned above since it’s heavily impacted by utilization insights, but it’s worth looking at it on its own, too. Predictive maintenance is a strategy many companies have adapted to cut costs by running inspections and conducting minor maintenance to prevent larger, more costly issues from arising. When proactively maintaining vehicles, you are saving money in the long run. But how can you proactively maintain your trailers if you don’t know how often they’re being used? You don’t want to do too much maintenance or not enough, so you make an assumption on usage and go by that. Using this method, you are likely to do brake checks on trailers that haven’t been used since the last check. Think about all of that labor wasted. Or consider the vehicles being overutilized. They’ll need brake checks more often than you are performing them and you run the risk of missing an easily fixable issue that turns into an expensive problem. AI in logistics can use the location data being collected to plan maintenance activities.

Asset tracking devices have monitoring capabilities that can let you know information about driver behavior. If a driver has a certain number of hard braking events, AI for logistics can determine it’s time for a maintenance check ahead of schedule. Trailer tracking allows AI logistics solutions to trailer maintenance efforts to be tailored to vehicle wear and tear. By tailoring maintenance schedules and procedures to the specific wear and tear patterns of individual vehicles, fleet managers can ensure that maintenance activities are performed when they are most needed, maximizing the effectiveness of maintenance efforts while minimizing unnecessary costs and disruptions. This proactive approach not only reduces the risk of unexpected breakdowns but also extends the lifespan of vehicles, ultimately improving overall fleet reliability and reducing total cost of ownership.

Billing Leakage

For those who rent trailers or equipment, you know the difficulties that come with billing. Accurate billing can be difficult to conduct through direct communication and self-reporting alone. If a customer is using a piece of equipment for 10 days and says they’re dropping it off on a day you’re closed, how do you know it was definitely dropped off when they said it was? Location data allows AI to analyze rental data to identify discrepancies and detect instances of potential billing leakage in real time. AI solutions for logistics allow fleet managers to precisely track rental durations, monitor equipment usage, and ensure that all billable services or products are accurately invoiced. Also, some companies may take time to process returns, meaning there is a long turnaround time for renting it out again. By tracking the location of equipment or trailers, you can receive an alert when it’s back on property. AI can then update to let you know which assets are available to rent out again, increasing the revenue you can generate using that asset. AI-powered analytics provide valuable insights into rental trends, customer behavior, and pricing strategies, allowing companies to optimize pricing models and enhance overall revenue generation. Through proactive monitoring, automated billing, and data-driven decision-making, AI empowers rental companies to improve financial performance and deliver better customer experiences.

The Solution Before AI

How do you collect the location data AI needs to operate? It’s simple - invest in asset tracking. Asset tracking solutions like our AirFinder solution track and monitor the location of assets in real time. In fleet management, the ability to track the movement of goods and vehicles in real time enables AI algorithms to optimize routing, predict delivery times, and streamline operations. By leveraging AirFinder Everywhere's robust location tracking capabilities, organizations can unlock the full potential of AI at the edge, driving innovation, and achieving their business objectives with confidence. AirFinder offers organizations a powerful tool to improve asset visibility, operational efficiency, and productivity. With its complete location tracking capabilities and seamless integration with AI platforms, this solution enables businesses to make data-driven decisions, drive innovation, and achieve their strategic objectives with confidence.

Will You Collect the Data You Need to Successfully Use AI?

The integration of location data is fundamental for unlocking the full potential of AI across logistics operations. Location data provides invaluable insights into asset usage, enabling AI systems to make informed decisions, deliver personalized experiences, and optimize operations. Whether it's enhancing fleet efficiency, predicting maintenance needs, or reducing billing leakage, the combination of AI and location data offers transformative possibilities for companies striving to succeed in today's IoT-driven landscape. By leveraging location data to fuel AI algorithms, organizations can gain a competitive edge, drive innovation, and achieve tangible business outcomes. As you continue to harness the potential of AI, it's essential for companies to stay abreast of emerging technologies that drive the use of AI. To learn how our solution can get you started on your journey to further automation, book a demo with our team of experts. 

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Written by Emily Saldivar

Emily Saldivar is a Marketing Specialist for Link Labs and has been with the company since 2020. She has a background in content writing and is furthering the Link Labs mission through social media and other platforms.

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