SignalTrace, a new technology by Leonardo, links wireless device signals to license plate data, raising significant privacy concerns regarding the tracking of individuals’ movements and associations.
SignalTrace, developed by security company Leonardo, is designed to detect wireless signals from consumer devices and associate them with license plate data, effectively creating electronic fingerprints for law enforcement use.
Imagine you regularly carpool to work with a colleague. As your vehicle passes a roadside license plate reader, the system records your license plate along with the time and location. Simultaneously, another sensor picks up wireless signals emitted by devices traveling nearby, which could include your smartphone, smartwatch, or even wireless headphones. Over time, the software may identify that certain signals frequently appear together, establishing a recurring electronic pattern linked to your vehicle.
Weeks later, if one of those signals is detected in a different location, perhaps near another vehicle involved in an investigation, police may not immediately know who owns the device. However, the historical connections could provide investigators with a valuable starting point.
The concept behind SignalTrace raises critical questions about privacy: How anonymous is a device signal when it can be linked to a vehicle, repeated locations, and other nearby devices? This technology is marketed to law enforcement agencies, but its implications extend far beyond traditional policing.
SignalTrace operates in conjunction with automatic license plate reader (ALPR) technology. While traditional ALPR systems photograph vehicles and record license plate numbers, vehicle details, and timestamps, SignalTrace adds an additional layer by detecting and analyzing electronic signals from consumer devices. This includes signals from smartphones, wearables, and RFID devices. By identifying patterns of signals that frequently co-occur, the system can create what Leonardo refers to as an electronic fingerprint for that group of devices.
According to the company’s product information, SignalTrace allows investigators to connect recurring device patterns with license plate information and timestamped locations. This capability enables law enforcement to search for these patterns later, potentially identifying a vehicle even when its license plate is obscured. This shifts the traditional investigative approach, which typically begins with a known plate number or suspect, to one that starts with a pattern of electronic signals.
Leonardo emphasizes that while SignalTrace detects and correlates publicly broadcast electronic signals, it does not decrypt communications, access message content, or collect stored information from devices. The company asserts that SignalTrace does not identify individuals or associate electronic signatures with specific persons. However, investigators can correlate an electronic signature with a license plate, and subsequently use vehicle registration records to identify the registered owner, subject to legal requirements.
Leonardo clarifies that SignalTrace data serves as an investigative lead rather than definitive proof of identity. The company stresses that any association with an individual requires further investigative work and corroborating information in accordance with applicable laws and agency procedures. “Leonardo believes technology should support, not replace, sound investigative practices,” the company stated.
The privacy implications of this technology are significant. Federal privacy guidelines do not limit identifying information to obvious markers such as names or Social Security numbers. The National Institute of Standards and Technology indicates that information can be considered personally identifiable if it can trace someone’s identity on its own or when combined with other linkable data. Movement patterns, in particular, can be revealing.
A widely referenced study published in *Scientific Reports* analyzed 15 months of mobility data from 1.5 million individuals. Researchers found that just four time-and-place points were sufficient to uniquely identify 95% of the mobility traces in the dataset. While this study did not examine SignalTrace specifically, it highlights the potential for repeated location patterns to become distinctive, even in the absence of personal identifiers.
Moreover, the association between devices can be telling. Your phone may frequently travel alongside your spouse’s smartwatch, your coworker’s phone, or your child’s tablet. These patterns can reveal relationships and connections that may not be immediately apparent.
Another study published in the *Proceedings of the National Academy of Sciences* tracked 94 participants using phones that recorded Bluetooth proximity and communication patterns. The researchers found that the behavioral data could accurately classify 95% of reported friendships among participants. Although SignalTrace employs a different methodology, the broader implications of repeated proximity revealing social relationships remain relevant.
However, there are limitations to what these patterns can indicate. Two individuals may commute together without any other connection, or a phone may remain in a vehicle after its owner departs. Proximity alone does not imply a relationship or wrongdoing, yet it can create investigative leads that may misdirect law enforcement.
Leonardo notes that SignalTrace is still in the early stages of deployment, with a limited number of installations. The company has not disclosed the exact number of agencies or locations utilizing the technology, but interest is reportedly growing beyond law enforcement applications, with potential uses in parking management, traffic monitoring, and commercial automotive sectors.
The legal landscape surrounding this technology is evolving. In 2018, the Supreme Court ruled in *Carpenter v. United States* that individuals have a reasonable expectation of privacy concerning historical cellphone location records held by wireless carriers. More recently, in June 2026, the Court ruled in *Chatrie v. United States*, stating that police conducting a geofence warrant search for location data from Google constituted a Fourth Amendment search, reinforcing the expectation of privacy in cellphone location information.
While the Supreme Court has not yet ruled on whether the collection of data by SignalTrace constitutes a Fourth Amendment search, the ongoing legal discussions highlight the need for careful consideration of privacy rights in the context of emerging technologies.
As the capabilities of SignalTrace and similar technologies expand, individuals may want to take steps to protect their digital privacy. Turning off Bluetooth while driving can limit some wireless activity, although it may disconnect devices like wireless headphones or smartwatches. Limiting location access on devices may also help reduce the amount of location data collected by apps.
It is advisable to inquire whether local police departments utilize automatic license plate readers and if they have policies in place regarding data retention, access, and sharing with other agencies. While these measures can mitigate some digital exposure, they cannot guarantee complete invisibility to roadside sensors.
As the definition of identification continues to evolve, the implications of technologies like SignalTrace warrant careful scrutiny. While the technology may assist in legitimate public safety efforts, it raises important questions about privacy and the extent to which investigators can infer connections based on electronic signals.
Would you feel comfortable with law enforcement using electronic signatures from your devices to track your movements and associations? Should such tracking require a warrant? Share your thoughts with us at CyberGuy.com.
According to CyberGuy, the implications of SignalTrace and similar technologies are significant and merit ongoing discussion.