The telecommunications landscape is currently undergoing a radical transformation as we redefine the very purpose of mobile infrastructure. Beyond the traditional role of high-speed data transmission, the industry is pioneering Integrated Sensing and Communication, or ISAC, which essentially turns the radio waves surrounding us into a high-precision sensory net. This shift allows networks to perceive the physical world, detecting movement and density without the need for invasive visual hardware. By leveraging existing 5G infrastructure as a foundation for the 6G era, we are moving toward a future where the network itself acts as a distributed environmental awareness platform, balancing sophisticated data collection with strict user privacy.
How does ISAC technology turn radio signal “impairments” into actionable intelligence about our physical environment?
In traditional wireless systems, we have spent decades trying to eliminate signal “impairments”—the way radio waves bounce off buildings, cars, or moving people. With ISAC, we have completely flipped that script by recognizing that these reflections and distortions are actually rich sources of spatial information. As a signal travels from a base station to a device, every object it strikes leaves a unique physical signature on the wave. By capturing and analyzing these altered signals, the network can essentially “see” the environment and understand the presence of objects like drones or vehicles. We are effectively reframing the entire mobile communication system to function as a distributed sensing platform that leverages the behavior of waves to map its surroundings in real time.
What were the specific technical components and the primary objectives of the recent trial conducted with Verizon in Dallas?
During the trial in Dallas, we utilized commercial 5G devices and the CBRS spectrum to test these sensing capabilities in a demanding, live-event atmosphere. The setup integrated Samsung’s virtualized Radio Access Network (vRAN) alongside a specialized AI-based application designed to interpret signal data. Our primary goal was to see if we could accurately measure crowd density and movement within a sports stadium without relying on traditional sensors or cameras. By processing the signal fluctuations across the venue, the system generated real-time estimates of how many people were present and how they were moving through the space. This was a critical milestone in proving that existing infrastructure can handle sophisticated sensing tasks while simultaneously supporting normal data traffic for thousands of users.
Given the growing concerns over surveillance, how does this approach to crowd monitoring address privacy differently than traditional camera-based systems?
The beauty of ISAC lies in its ability to provide high-level environmental awareness without ever identifying a specific individual. Unlike cameras, which capture facial features and personal characteristics, radio sensing creates a gradient or heat map based on the physical mass and movement of objects. We can differentiate between a low, medium, or high-density crowd, but the technology does not have the capacity to recognize faces or pinpoint individual identities. This allows venue operators at stadiums or transport hubs to manage traffic flow and safety with a “privacy-first” mindset. It provides the same operational value as visual analytics while removing the ethical and legal baggage associated with constant video surveillance.
Looking beyond large-scale public events, what other practical applications do you see for environmental awareness platforms in industrial or urban settings?
The potential use cases for these environmental awareness platforms are incredibly broad, ranging from industrial safety to autonomous logistics. In a manufacturing setting, ISAC could trigger intrusion alerts or safety stops if it detects a person moving too close to heavy machinery, creating a safer workspace without installing thousands of individual sensors. We also see significant promise in drone detection, where the network can identify unauthorized flight paths in restricted urban airspaces using existing signal patterns. Furthermore, for the future of connected vehicles, this technology could allow cars to sense hazards around corners by reading the reflections of radio waves bouncing off buildings. It essentially gives the city a central nervous system that can monitor safety and efficiency across a variety of sectors.
What are the most significant computational and technical challenges currently preventing ISAC from becoming a mainstream standard in our networks?
Moving from these successful trials to a global standard is a massive undertaking because the radio environment produces an overwhelming volume of data every second. It requires an immense amount of compute power to process these signals, as AI models must constantly learn and relearn to maintain high levels of accuracy. We have to retrain these algorithms frequently to ensure they can distinguish between a person, a vehicle, or a simple environmental change with high precision. Additionally, operators must establish clear standards for service responsibility and security before this becomes a commercial reality. The work we are doing in 2026 is focused on validating these concepts so that when the industry moves toward 6G standardization, we have a reliable framework for deployment.
What is your forecast for the evolution of this technology as we move closer to the full standardization of 6G?
I expect that over the next two years, we will see a rapid maturation of the AI models that underpin these sensing capabilities, leading to more widespread pilot programs in smart cities and logistics hubs. By 2028, ISAC will likely be a cornerstone of the 6G standard, allowing operators to monetize their infrastructure in ways that were previously impossible. We will move away from thinking of mobile networks as just “communication pipes” and start seeing them as essential utilities for public safety and urban management. As we refine the accuracy of these systems, the boundary between the digital and physical worlds will continue to blur, making our environments more responsive and intelligent than ever before.