Once relegated to science fiction, artificial intelligence (AI) and machine learning (ML) are now hot topics in the world of fleet technology and more specifically, asset tracking. It’s easy to see why; both innovations are making their way into every facet of our daily lives, from the way we drive our cars to the way we do our shopping.
It’s not just consumer-facing applications that are benefiting from AI. Businesses in a wide range of industries are beginning to adopt AI technology in order to improve their operations.
One such industry is transport and commercial fleets, where AI asset tracking tools are giving fleet managers greater visibility and control over their assets.
In this article, we’ll discuss some of the ways AI asset tracking can benefit your business.
What Is Artificial Intelligence?
AI is a branch of computer science focused on mimicking human-like intelligence in machines. AI research deals with the question of how to create computers that are capable of behaviour such as decision-making, natural communication, and problem-solving.
A great example of this technology in present use would be virtual assistants such as Siri and Alexa, which answer questions and perform tasks based on user requests.
What Is Machine Learning?
Machine learning (ML) is a subset of AI. ML also emulates human intelligence in computer systems, only with a specific focus on pattern recognition.
This means that, rather than being explicitly programmed with a set of rules and regulations to follow, machine learning algorithms are “trained” on data sets. The more data the algorithm is exposed to, the better it becomes at generalizing from that data and making predictions.
It’s very likely that you’ve encountered ML in your day-to-day life; common examples include spam filters on your email and product recommendations on sites such as Amazon.
The Role of AI Asset Tracking
AI and ML are increasingly commonplace in modern devices and products. Asset tracking tools are no exception, and use the technology to enhance and automate work processes.
AI asset tracking provides an enhanced level of automation without the need for human input. This is done through a combination of sensors and RFID tags, which are able to collect data on the location, movement, and status of a given asset.
This data is then fed into an AI system which uses predictive modeling to generate real-time updates on the location of each asset. This is an extremely valuable capability as it frees up resources that would otherwise be dedicated to manual tracking, and reduces the potential for human error.
Inventory management is another key area where AI asset tracking can streamline work processes.
AI asset tracking systems can automatically keep track of inventory levels, and notify relevant personnel when stock is running low. This eliminates the need for manual checks and helps to ensure that inventory is always kept at optimum levels.
Predictive maintenance refers to the proactive maintenance of equipment and devices. The goal is to prevent issues before they happen by using data to identify potential problems and schedule maintenance accordingly.
This is accomplished by training machine learning algorithms on data sets that include information on past failures. By detecting patterns in this data, the algorithm is able to make predictions on whether or not a particular asset is likely to experience an issue, and when. This information can then be used to plan maintenance and avoid costly downtime.
Product Quality Inspections
Product quality inspections are another common use for AI asset tracking. By using machine learning algorithms to analyze data from sensors and cameras, it’s possible to automatically detect defects in products. This information can then be used to trigger quality control measures or stop production altogether if necessary.
Asset tracking systems often need to plan routes for commercial vehicles. This can be a time-consuming and challenging task, particularly when dealing with a large number of assets.
By taking into account a variety of factors such as traffic, weather, and the current location of assets, AI asset tracking systems are able to generate optimized routes much more efficiently. This not only saves time, but also reduces fuel costs and carbon emissions while improving driver safety.
As you can see, AI and ML have a major impact on asset tracking. Businesses can improve efficiency, save time and money, and prevent issues before they cause problems. If you’re not already using these technologies in your asset tracking system, now is the time to start.