The rise of the Internet of Things (IoT) has led to the creation, development and evolution of cutting-edge technology for the commercial vehicle industry. Fleets now have access to a wealth of real-time data about the performance, safety and efficiency of their vehicles.
However, in order to leverage this valuable information to their benefit, they need to know how to collect, process and interpret it. The ability to improve vehicle uptime and increase operational efficiencies is only possible by being in a position to quickly and effectively transform the information provided by IoT technology into something usable.
“For fleets to make use of this information, it must be flowing in real time,” says Steve Mitgang, CEO, SmartDrive Systems, a provider of patented vehicle data and video event recording technology (www.smartdrive.net). “The most important thing to know is how to process this data, make it usable and make it fit within the physical and financial constraints of the wireless/cellular network.”
Real-time, contextual data about an asset (i.e. telematics, warranty, service bulletins, preventive maintenance status, detailed build information, service history, etc.) can not only help fleets improve efficiency and minimize downtime, it can also help reduce complexity and stress, as well as improve their respective bottom lines.
“Increased interconnectedness between systems in an IoT world brings more insight into actual operations of the vehicle, particularly how the driver operates the vehicle,” says Mitgang. “This will yield opportunities to optimize operating margins by increasing revenue and reducing costs in a number of key areas.”
Challenges
Many fleets, however, do not have precise enough data or actionable information to obtain the benefits provided by IoT technology, including fuel efficiency, labor efficiency, maintenance safety and more. For some of those that do, data overload prevents the ability to extract anything of use.
“Fleets are grappling with making traditional telematics and other vehicle system data usable, and IoT will bring even more data,” says Mitgang.
The key, he says, will be to deliver data-based insights in a simple and understandable manner that creates shared insights across a fleet’s operational departments. Since the information is siloed, Mitgang continues, that creates a self-limiting situation.
“This will remain important as long as people, rather than machines, are making critical business decisions that impact operational efficiency,” he says. “It is critical to unlocking the full potential efficiency improvements that IoT can bring to fleet operations.”
Trends
Traditional telematics systems were an early example of IoT, as they provided a vehicle’s location and other operating data available to a central application. However, as time has gone on and technology has advanced, a new trend has emerged.
“That new trend has been richer onboard processing of data for deriving intelligence, rather than simple down-sampling of data to deal with network capacity constraints which imposes tradeoff constraints that are unnecessarily limiting in a number of ways,” says Mitgang. “Also, the addition of video systems and other system and performance sensors to the vehicle expands the breadth of data available.”
The bandwidth of available for video, vehicle and sensor data, he adds, will always exceed the capacity of the cellular networks, in connected fleets and IoT in general, so local processing is critical to fully realize the potential of IoT in the transportation industry.
Where We’re Headed
The adoption of IoT technology by the commercial vehicle is expected to be a gradual one, says Mitgang. This is largely because fleets will need to be certain they have an appropriate amount of insight into the effectiveness of the technology and how drivers will interact with its features.
Data overload should continue to be less of an issue with time, as fleets will become more comfortable with utilizing rich telematics and vehicle data, along with video, to bring new insights and additional efficiencies.
“Predictive and prescriptive analytics that rely on connected vehicle data will mature, and we will see a shift from data overload to data insights,” says Mitgang. “This shift will be driven by better data, better analytics and intelligence applications that make these insights available and accessible to fleets of every size – not just the largest fleets that can afford to invest in staff and technologies to make sense of the data.”
