New Jersey Transit Pilots Rail Monitoring Technology

Published: March 4, 2024

The IoT based solution from Humatics Corporation leverages a Wi-Fi and cellular connected sensor installed in railcars to track conditions over time on the track

Following a two-month proof of concept (PoC) in 2023, New Jersey Transit (NJT) is launching a one-year pilot of wireless rail condition monitoring technology provided by Humatics Corporation.

The solution will be tested on three active passenger lines and six trains, covering 100 miles of track, using wireless sensors installed in the operator cab rail cars. The sensors are a combination of location and wireless technologies to send data to a cloud-based server.

The software uses machine learning and AI to measure changes in rail conditions as well as identifying anomalies on the track or train in real time.

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Measuring Train Movement

Trains tend to sway, rattle and shift as they travel from one station to the next. But those gyrations can provide a wireless solution with granular information about the conditions of the tracks, that may be imperceptible to passengers.

The Humatics Focus track condition monitoring technology enables rail companies to conduct predictive maintenance by providing real-time, geotagged insights into track conditions or potential defects, said Aaron Whittemore, Humatics’ mobility general manager.

And unlike other track-condition monitoring solutions, it does this by collecting data during revenue service trips.

Additive to Periodic Tracks Scans

Most rail companies already use a variety of methods to track the conditions of their rail lines. With a manual method, inspectors may regularly walk the tracks and visually check for problems, using their domain knowledge and manually writing down on a piece of paper any reported problems.

The high-tech version of track monitoring consists of a machine that periodically travels the length of tracks taking geometric scans every three, six or 12 months. This high-powered, high-technology vehicle slowly travels the tracks scanning rails in three dimensions.

These maintenance vehicles are often rented, which is costly. And because they travel at their own pace, they can impede the actual revenue service of the system itself.

Solution Results from Accelerator Program

The Humatics pilot project with NJ Transit launched at the Transit Tech Lab, an accelerator program for new technologies and innovations from the startup partnering companies to solve specific issues for transit agencies. The 2023 challenge was centered on operations and maintenance.

Humatics has previously provided an ultra-wideband-based (UWB) solution for New York’s MTA. For the New York City project, Humatics’ technology tracked data from devices with inertial measurement acceleration units that identified location and were transmitted via UWB sensors.

The Massachusetts-based company leveraged this experience and created a solution for the Transit Tech Lab that used inertial measurement data to identify track defects. The system uses wireless technologies—such as Global Navigation Satellite System (GNSS), LTE and Wi-Fi—that were already deployed by the transit agency. In that way, no gateway or other infrastructure would need to be installed along the track.

Proof of Concept

Following the results of that PoC, NJ Transit chose to proceed with the pilot meaning addition of four additional light rail train sets and covering a total of 100 miles of track.

Once the 12 months is over at the end of this year, NJ Transit will again examine the results and make their decision about whether they deploy the solution permanently.

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How Humatics Focus System Works

Humatics solution is intended to be a lower total cost solution that can automate and enhance the data collected only periodically by the existing methods.

The software, using sensor data, tracks seven metrics: lateral alignment, vertical alignment, superelevation, track twist, track warp, hard contact, and passenger comfort, said Jared Bruton, Humatics Corp.’s senior product manager for mobility.

With the pilot, a Humatics sensor is mounted on the interior roof, in the operator cab of rail cars. Each one collects data such as tilts, twists and curves or drops, and sends that data via 5G, LTE or Wi-Fi along with the location of the train on the tracks via satellite and RTK correction.

The software receives the data and applies advanced machine learning and AI techniques, says Bruton.

“This approach looks for variations,” he says, in real time as well as over an extended period.

Problem Indicator

While Bruton points out that “while we detect major track defects or alignment shifts,” it is not intended to replace the other periodic track condition monitoring that can view additional conditions such as detecting corrosion on the bolts underneath the tracks.

“We give them a very good idea of the big problems that are starting to develop and then they can go and have their inspector respond,” to that specific location to review, Bruton explains.

The GNSS provides location data along with RTK (real-time kinematic positioning) correction to further pinpoint where the sensor reading was collected, within about three feet.

If the system loses access to satellite connection—such as in a tunnel—the software can estimate the car’s location using dead reckoning and other positioning techniques so that an anomaly can still be linked to where on the track it was detected.

State of Good Repair

With significant investments from the federal government, the U.S. transit industry is seeking to ensure their infrastructure is in a state of good repair.

The Humatics Focus system aims to confirm “that their maintenance is being done effectively and that there’s no major flaws developing overtime,” said Whittemore. “Were a safety backup for them.”

Problems that can occur with track anomalies can include issues such as rail breaks, derailments, damage to the train, but also can affect the comfort of the passengers.

“The goals of New Jersey Transit and other agencies in the US is to move towards predictive maintenance and to start the digitization of processes. So we’re helping enable that shift” Whittemore said.

Key Takeaways:
  • NJTransit is piloting a senor-based solution to detect conditions of tracks based on data captured by Humatics Corp.
  • The technology company’s sensor and Software as a Service is intended to provide sensor measurements, location and AI to help the rail company understand changes in tracks over time.