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How Artificial Intelligence Will Mold The Future Of Fleet Management

Category:GPS fleet tracker

smarketingDecember 20, 2022

Opinions about Artificial Intelligence (AI) and how it will change the world differ from one person to another. Proponents have great expectations from it, and they sing praises in the name of its capabilities. AI usually deals with the problem of simulating cognitive intelligence in computing systems and its applications. While it existed as an esoteric research field from the days of Alan Turing, it gained considerable attention in the recent past because of some of the impressive applications that resulted from the massive amount of data we have started collecting and analyzing using advanced machine learning algorithms.

The disrupting power of Artificial Intelligence has been felt by numerous industries and businesses. Fleet management is no different, of course. The ever-growing need to prioritize driver safety without compromising cost-efficiency has fuelled the adoption of smart fleet management systems and devices, such as a GPS fleet tracker.

The average fleet driver relies heavily on telematics solutions and smartphones Previously, fleet managers and drivers had to deal with the hassle of determining routes on paper maps and listening to radio broadcasts to gauge traffic conditions. Today, scalable routing algorithms work autonomously in conjunction with predictive vehicle performance models and massive amount of traffic data analytics to present you with the optimal route in real-time. Moreover, OBD-II trackers and traffic applications are combining AI algorithms and GPS technology for personalizing the user experience and making the journey easier.

Fleets have much to gain from powerful systems bolstered by Artificial Intelligence that can take care of everything from recommending routes to analyzing on-road risk management data and even training drivers to do their jobs safely. Where earlier technologies failed, AI succeeded in delivering accuracy, convenience, efficiency, and ease of operation, since it simplifies our lives.

A Basic Explanation of AI-based Fleet Management

Artificial Intelligence fleet management involves leveraging AI-based technology to oversee fleet operations. In a world that is changing constantly, AI streamlines the work of fleet managers by eliminating human error from all processes.

Recommendations from AI-powered solutions ensure fleet drivers, managers, and mechanics make better decisions that improve long-term fleet performance. It works as assistive tech to ensure drivers retain autonomy during each transport cycle. Here are some of the aspects of fleet management AI can optimize.

1)Fleet Analytics in Real-Time

Data collection is a mission-critical element in every operational process. After all, without conducting data analysis, it will not be possible for fleet managers to make informed decisions. Fleet managers can prioritize opportunities and risks when they have access to historical insights or data points to analyze in real time. Then, they can determine the best course of action to solve potentially problematic situations.

AI systems can accumulate data for predictive analytics, including information on traffic and road conditions, real-time weather, environmental hazards, and mechanical faults. You can use this data to predict incoming risks and make better routes, schedules, maintenance deliveries, and dispatch arrangements to improve your business activities and outcomes.

2)Decisions Regarding Repair and Maintenance

Expecting vehicles to operate entirely without human intervention may still seem somewhat futuristic. However, the feature of vehicular autonomy has been around longer than you probably know. Various household names among automobile brands have joined the race to build autonomous vehicles for a radically changing world of consumers. The history of autonomous vehicles is colorful and deserves attention. You can learn about it here.

Now, back to the matter at hand. AI can predict potential faults before they even happen. For instance, a regular vehicle with a diagnostics system will signal an issue affecting the engine only after it occurs. However, AI-powered IoT systems, data analytics, and predictive maintenance can detect faults before they even happen. Based on a study by evidence to prove that the need for automotive and diesel technicians will increase by up to 5% by 2028. Furthermore, the American Trucking Association predicts that there will be a severe shortage of drivers by 2026 - 175,000 to be exact.

Once the older generation of technicians and drivers retire, there will be a need for younger, tech-savvy replacements. Then again, it will create a problem with onboarding and training. Artificial Intelligence can eliminate the complexities by capturing the specialized skills of these workers before they leave.

This feature is particularly great for technicians who incorporate exclusive strategies to carry out their tasks. Artificial Intelligence can also suggest the most qualified drivers suitable for fulfilling the company's bottom line from a pool of hundreds and thousands of applicants, reducing recruiter strain.

Integrating Artificial Intelligence with Fleet Management

Devices or software programs empowered by AI are “sophisticated" in every sense of the word, as they are made of multiple applications and devices, such as predictive data analysis & machine learning systems, IoT, sensors & HD cameras, communication & display systems, and WiFi.

You have to know about the purpose served by every component before understanding how all of them come together to make fleet management a breeze.

1.IoT: The Internet of Things is now a household topic of discussion that refers to a network of sensors and actuators. They collect data from the environment continuously. In the field of fleet management, IoT captures adequate data for analysis. Simultaneously, it promotes seamless information sharing between all stakeholders in the supply chain, including manufacturers and retailers.

Fleet management IoT utilizes these three technologies;
  • Wireless communication (4G, Bluetooth, WiFi) - to convey relevant information
  • GPS - for real-time location tracking
  • Onboard Diagnostics - OBDII scanners for self-diagnostics and reporting

2.Machine learning: ML allows fleets to learn from data collected over time and make managed adjustments based on the same. It results in the creation of smart systems in which Artificial Intelligence can learn the ability to make decisions that further enable more effective handling of practical situations.

3.HD cameras: Cameras allow fleet managers to capture and analyze video data they can access at any time to get a better view of driver behavior, hazards, or road conditions. An AI-powered system can perform the tasks mentioned below when connected to these components.

  • Collecting road data accurately and transmitting the same to other devices
  • Transferring information across every arm of the supply chain
  • Analyzing data in real-time and educating the driver regarding the best course of action for any situation
  • Detecting drowsy or distracted driving behaviors in drivers because they may cause an accident
  • Capturing video footage of accidents from various external angles of the vehicle
  • Conducting self-diagnostics and recommending solutions through predictive maintenance

Everything mentioned above is significant because they create a future for fleet management where human error becomes non-existent in various aspects of the transport cycle. Once implemented, you may get better results and cost savings.

AI will Dictate the Future of Fleet Management

Right now, the automotive industry faces several problems affecting profitability and fleet activities. Artificial Intelligence and telematics devices like a GPS fleet tracker can solve these issues and build a better future for businesses leveraging vehicle fleets if properly applied.

Some of these problems include,

Prioritizing risks and generating efficiency

  • Risky driving behaviors leading to accidents
  • Collecting data and analyzing it
  • Risks on the road
  • Cost containment
  • Compliance

Other than risky behaviors, such as drowsy and distracted driving, fleet managers suggest drivers watch out for a few signs. Here are some of them,

  • Constant blinking
  • Yawning
  • Missing exits or turns
  • Using the phone
  • Drifting out of the lane
  • Slower reaction times

Normally, managers depend on their drivers to avoid these signs as they have no way of knowing whether a driver has been texting while driving or dozing off at the wheel. However, you can train AI systems to detect missed exits, head turns, blinking frequencies, yawning, and other signs of risky behavior. Then, you can broadcast these signals to fleet managers in real-time to let them take corrective measures.

Changes in road conditions present challenges for managers because they are difficult to detect without the right tools. These conditions pose risks, evident from the number of deaths they cause every year - 42,000! Predictive technology powered by Artificial Intelligence can reduce the risks associated with this issue by studying and charting routes. Simultaneously, it will draw from data gathered by other vehicles. AI can even be trained to make smart predictions about the weather and detect environmental changes, such as fog before a driver reaches that area.

What AI has in Store for Fleet Management

The future of businesses utilizing fleet vehicles looks more promising than ever because of the exciting applications of Artificial Intelligence in fleet management. Operational costs, unpredictable road conditions, and driver retention problems would become obsolete once fleets move to AI-powered devices and software. Stakeholders can benefit from the reliability and efficiency of this technology due to the reduction in accidents, costs, driver turnover, and other problems that may reflect on fleet service pricing. It can also ensure that other commuters on the road remain safe.

Vyncs is here to rethink and reshape mobility. Whether it is about location tracking, driver safety monitoring, or vehicle health reports, our connected car solutions use powerful onboard and in-cloud distributed data management and analytics platforms to access vehicle sensor data and provide valuable intelligence. We wish to roll out AI sooner rather than later, and when we do, we shall change the experience of fleet management for our customers beyond their comprehension.