Mobile networks may soon do more than help us make phone calls and access the Internet.They have the potential to be used as high-resolution sensors capable of detecting things in the environment, including people, cars or drones.
Integrated sensing and communications (ISAC) technology repurposes the signals continuously transmitted by cell phone towers.By analysing subtle distortions in radio waves as they travel through the air and reflect off objects, ISAC systems can detect the presence and movement of obstacles, similar to radar.
Researchers expect it to become one of the defining features of the next generation of so-called 6G networks, planned for release around 2030.
“With ISAC, sensing will be possible essentially anywhere with a signal,” explains Masakatsu Ogawa, a professor in the Department of Information and Communication Sciences at Sophia University in Tokyo, Japan.The technology opens new sensing opportunities that may help address major challenges — but some experts warn we should be aware of the potential for misuse of the technology too.
Powered by 6G
Research on ISAC has gained traction since telecommunications regulators began discussing technical requirements for 6G in late 2023, says Tomoki Murakami, a researcher at the Access Network Service Systems Laboratories of NTT, Inc., one of Japan’s largest and most influential technology and telecommunications companies.
On 6G networks, ISAC will become far more powerful.While 4G mainly relies on sub-6 GHz bands, and 5G extends from mid-band (around 3–7 GHz) up to millimetre-wave frequencies near 30-40 GHz, 6G is expected to use even higher sub-THz bands above roughly 90–100 GHz, enabling much higher-resolution sensing.
The wider 6G bandwidths will soon enable the precise mapping of objects and movement at the millimetre level within the reach of signals from base stations.This could allow for capturing gestures as small as the wave of a hand without sensing equipment nearby.
While this may raise questions about privacy, ISAC systems are lower risk, say some experts, as they do not capture images directly like cameras, or as many identifying features of individuals.
“The first real-world applications for ISAC will probably be for presence detection of intruders and moving objects such as cars” says Ogawa.
Real-world studies
Realizing sensing via mobile networks, beyond solely theory and simulations, was difficult until recently.
Full test setups that mimic commercial networks are expensive, and, because their internal designs are proprietary, researchers cannot modify waveforms that commercial base stations transmit into sensing-friendly forms.
While some research teams build their own customized waveforms for the purposes of study and obtain licenses to conduct experiments, this demands significant time and cost.
In contrast, research using Wi-Fi and similar sensing principles has progressed more quickly because it operates on unlicensed bands.Individual laboratories are free to set up access points indoors and can freely experiment with how movement affects the shape and timing of radio waves.
These studies have produced promising results for detecting motion within reach of Wi-Fi access points like homes and offices.
The vast coverage of cellular signals is unrivalled, and Wi-Fi signals weaken over longer distances.“If we want to transform the scale at which we sense things, we also need mobile networks,” says Murakami.
A recent study by Murakami, Ogawa, and colleagues, showed that ISAC can be studied in the real world without transmitting signals1.The team used low-cost hardware to capture commercial signals and combined it with open-source software to interpret their structure.
Using an antenna to receive signals and their changes, their experiment compared when no one was in front of the antenna, and when a person walked across its line of vision at various distances.
On analysing changes to the signals, the team found that their system could reliably detect a person walking outdoors at distances of up to 10 metres.Sensing a combination of different frequency ranges, rather than focusing on a single one, covered for blind spots in each range and improved accuracy.
“Our study emphasizes that ISAC experiments give meaningful insights without specialized and expensive equipment,” says Murakami.Their approach lowers the barrier for entry into ISAC research and paves the way for more to follow.
Sensing foot traffic
Murakami explains that organizations are keen to detect the general numbers of people in a given area and the flow of crowds in real-time.
For example, public authorities could refer to these insights during large-scale events, such as festivals, to facilitate visitor flow.From a commercial perspective, the data can also be utilized to gathering marketing insights such as measuring event success.
In a 2025 study2, which won the best paper award at the International Conference on Information Networking 2025, Murakami and Ogawa’s team found a way to estimate the number of people moving outdoors with commercial radio waves.
Through experiments conducted on Sophia University’s campus, the team observed signals from commercial 4G base stations during and between classes.They used AI to calculate associations between changes to signals and the number of people, while ensuring the algorithm was trained to eliminate noise.
In particular, they were trying to identify when foot traffic on campus was highest.
“These are the very signals that we use every day for our phones.This is evidence that ISAC works reliably with standard communication devices,” says Murakami.
But other experts have noted potential privacy and safety considerations associated with these technologies, suggesting that it’s important to explore whether they could be used for monitoring or misused in unintended ways.The researchers in Japan agree these are important questions to be debated.
Digital twin computing applications
With further development, data from ISAC systems will help advance digital twin computing technologies, which is the creation of replicas of people, objects and their environment in the virtual world.
An example is the representation of entire cities including real-time information on pedestrians and vehicles.Such reconstructions could warn people about obstacles for safer driving and congestion to facilitate traffic flow.
ISAC systems could also detect rain and water flow, contributing to management of flash floods in cities.
Murakami explains that digital twin computing is a core pillar of NTT’s Innovative Optical and Wireless Network (IOWN), a vision to advance sustainability and well-being through next-generation telecommunications and information processing technology.
“ISAC data will fill the blind spots that other sensing devices like cameras would have missed,” he says.“Adding this data to digital twin computing will give us new ways of tackling major societal challenges.That’s where I think the impact will be enormous.”.