● Covered by 1 source · 1 reportMedium impact1 neutral
Swedish Researchers Develop AI System to Detect Concealed Handguns Using Wi-Fi Signals
Key points
- WiFireNet uses Wi-Fi signal distortion to detect concealed handguns.
- The system achieved 72.5% precision in controlled trials.
- It was trained on a dataset of Wi-Fi signals and RGB footage.
- The project is open source and plans to use modern Wi-Fi standards.
WiFireNet System Overview
AI researchers at the Swedish Defense Research Agency (FOI) have created WiFireNet, an AI system designed to detect concealed handguns. This system operates by analyzing channel state information (CSI), which describes how objects alter ambient Wi-Fi signals. The complete setup includes a Wi-Fi transmitter, a Wi-Fi receiver, and the WiFireNet AI.
How Wi-Fi Signal Analysis Works
When Wi-Fi signals encounter an object, they penetrate and reflect in ways specific to the object's shape, orientation, and material. This interaction generates unique channel state information. By analyzing this data, the system can identify specific objects. Previous research has shown Wi-Fi routers can identify people with high accuracy using similar techniques.
Dataset Creation and Training
To develop WiFireNet, researchers compiled the WiFire Dataset. This dataset consists of synchronized RGB video footage and reflected Wi-Fi signals of individuals carrying various items, including phones and handguns. A deep learning model was then trained on this data, correlating visual handgun appearances with their distinct Wi-Fi signatures. The training included plastic handguns, metal water bottles, real metal handguns, and phones to ensure differentiation from common items.
Performance and Limitations
In controlled indoor trials with up to four moving individuals, WiFireNet achieved an average handgun-detection precision of 72.5%. However, precision decreased to 53.8% when stricter localization of the weapon was required. The neural network also showed reduced accuracy in unfamiliar indoor environments. The current prototype uses a modified IEEE 802.11a standard for proof of concept.
Future Development and Open Source Release
The WiFireNet system is still experimental, with plans for further improvements. Future iterations will incorporate modern Wi-Fi 7 and Wi-Fi 8 networks to utilize higher-resolution CSI for enhanced detection capabilities. The researchers have made the project open source, releasing the code and models for further development.
✨ This summary was generated by AI from the outlets' reporting listed below. It is not independently verified and may contain errors — check the original sources. How BrevFeed works →
The daily brief
One email each morning: the day's tech stories, clustered across outlets and summarized. No account needed.
One email a day. Unsubscribe in one click, any time.
Today's brief
Spend a few minutes, get the whole day. Every topic's top stories in one hands-free rundown — listen, watch, or read the transcript.
▶ Play today's brief
New every morning, and the back catalogue is archived by date.
Reporting from
Researchers at the Swedish Defense Research Agency (FOI) developed WiFireNet, an AI system that identifies concealed handguns by analyzing how objects distort ambient Wi-Fi signals. This system offers a non-intrusive method for detection, utilizing channel state information from Wi-Fi interactions. While experimental, it presents a new approach to security screening without visible cameras or metal detectors.