A Way Through the Complexity of Telematics

A Way Through the Complexity of Telematics

Modern fleets are a rich mix of telematics sources, both factory-installed and aftermarket, that produce an abundant amount of machine data. Equipment managers face numerous logins, interfaces, separate reports and redundant data. It is hard to see ROI for the APIs.

Even with the telematics standard developed 15 years ago by the Association of Equipment Management Professionals and the Association of Equipment Manufacturers, few fleets have the resources to fully integrate all the data coming in. In new research on telematics conducted by Construction Equipment, only 14 percent of respondents use the telematics standard, ISO/TS 15143-3:2020, to monitor data internally. Others monitor individual dashboards or rely on their traders to monitor data.

One in three fleets still does not use telematics at all.

Another option to cost-effectively access fleet data is the use of third-party aftermarket telematics providers. These solutions replace layers of complexity with simpler technology that funnels all incoming equipment data into a single system designed to display relevant information via a single user interface. Third-party systems recognize the incoming data type and position it for easy access by various computer functions.

How telematics providers help fleets

Third-party systems enable mixed fleets—those with multiple brands—to integrate multiple sources of data. Dave Swan, SVP at Trackunit, says that all fleets are mixed when all the data-making devices are considered.

“The construction industry is a very interesting market for digitization as there are so many specialized categories of machinery built for specific tasks,” says Swan. “For example, if we look at the data points of a scissor lift compared to that of an excavator, that data is vastly different. The 19 data points [covered in the ISO standard] will mainly be what is common to both categories of machines and therefore useful to fleets and owners.”

A telematics system “conditions” data flowing from various digital sources, eliminating inconsistencies and harmonizing data types and frequency, according to Swan. Fine-tuning enables fleet managers to organize the incoming data into actionable solutions.

Telematics solutions also simplify data management by moving it from legacy hardware and networks to cloud-native systems.

Cloud-native technology means that the entire telematics system’s configuration is built entirely in the cloud. Functions including services (email), data integration, computing and archiving are all located at one cloud address—not in the fleet owner’s computer. Tasks that were once handled by hardware or separate programming have been replaced with digital functions, streamlining processing and connectivity. Task-specific modules (applications) and background programming remain in the cloud until called upon to operate. Fleet managers no longer need to purchase and maintain multiple software programs because the web-based versions are instantly accessible via the Internet.

Where once there were dedicated and somewhat arcane computing devices maintained by an IT department, located somewhere in the fleet owner’s facility, there is now an internet portal with a single login and instant access to fleet data with almost any device: laptop, tablet or smartphone. The on-premises products (and IT department) are gone.

With little tangible physical presence required, cloud-native systems are agile and allow software and computer procedures to be updated with little fanfare or effort. The software as a service (SaaS) computing model stores no programming on devices and mimics traditional desktop applications. The applications and services that are in the cloud are portable and connectable over the Internet. Features such as unified mapping, pre-formatted report queries and maintenance management come in lightweight prepackaged modules that can be clicked into the systems with little effort.

Work projects produced using the cloud SaaS protocol can be stored online, archived on an internal computer or network and easily shared. Often access to SaaS is through subscription that includes product updates, patches and pre-formatted modules that welcome customization.

Cloud-native systems also function smoothly with industry-specific APIs that “borrow” data and functionality from other applications without digging into the underlying code. This agility is important for making sense of multiple data streams.

Scalability is central to how Omnitracs reduces complexity.

“Omnitracs solutions enable fleet managers to control what and how much data they deem necessary for their operation,” said Richard Pearlman, VP of Business Development for Omnitracs / Solera. “Small and medium-sized contractors want to stay on top of what data is being reported, but tell us they don’t have the time or desire to sit in front of a computer all day. The ability to filter in and filter out data allows contractors to pack in actionable amounts of information and keep things concise. They want to prepare abbreviated reports for communication with field managers.”

Scalable systems also give seasonal contractors the option to scale back their data usage during the off-season without losing all of their data and computing capabilities. This option works well for smaller fleets that want to leverage their telematics capabilities and manage technology costs by only paying for services they use.

Pearlman says matching the system’s capabilities to the driver’s needs makes it easier to use. “If you can use Google maps, you can use us.”

Less complexity also comes from simplifying bells and whistles. Tony Nicoletti, VP of sales and business development at DPL Telematics, says fleet managers shopping for a third-party program often tell him they want to use all their data. “All this? Are you sure?” Nicoletti says he asks them.

“They don’t realize the sheer volume of data their fleet will produce,” he says. “They’re going to swim in it, pick through it all looking for the one or two things they’re actually interested in.”

Instead, Nicoletti suggests that fleet managers start with single questions or situations like “Where’s my stuff?” and build confidence using the system to find that answer.

“Work from the problem back to the data,” he says. “Start simply with location data, add run time data and then pull in the more complex CAN bus data such as fuel, temps, pressures, fault codes and engine direct data.

“DPL telematics hardware and system software are designed specifically for the construction industry,” says Nicoletti. “We understand that not all assets are created equal, and what worked on a truck yesterday may not work on a loader today.” DPL links the appropriate products to the fleet’s assets, he says.

Third-party vendors of all denominations encourage their customers to plan for the future.

“Contractors now expect to have telematics systems with their new equipment delivery, as opposed to just a few years ago when telematics was considered an option,” said Oded Ran, co-founder of Clue Insights. “Today, telematics is a standard tool.”

Ran sees the introduction of AI into telematics configurations as an excellent way to add predictive maintenance scheduling to a fleet’s management. Ran says that too much of the use of telematics is based on past events—what has already happened. With the addition of AI capabilities to enhance telematics functionality, fleet managers can set actionable parameters that give the machine permission to act when faced with recognizable data.

“Contractors will be able to train their telematics system to automatically respond to a vehicle’s data,” says Ran. For example, if AI recognizes a pattern in operating data that has led to repairs previously or in other machines in its fleet, the system can proactively alert the operator to adjust his operation.

Ran sees new data points emerging that will meet legislative or policy requirements, such as measuring real-time carbon emissions to report CO2 depositions and tracking battery health in EV machines.

As sharing data analytics improves, historical data trends based on a manufacturer’s or dealer’s much larger equipment databases will allow equipment managers to predict problems or repairs by comparing specific models operating in similar conditions.

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