[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"branding":3,"analytics":7,"article-swedish-wi-fi-gun-detector-hits-725-precision-in-lab-tests":10,"sections":35},{"siteName":4,"siteTagline":5,"publisherName":4,"contactEmail":6},"The Revision","Tech news, decoded.","editor@therevision.news",{"gaMeasurementId":8,"adsenseClientId":9},"G-ZW2MV82GYR","ca-pub-8533917693782264",{"article":11},{"id":12,"slug":13,"title":14,"dek":15,"body_md":16,"tags_json":17,"published_at":18,"created_at":19,"updated_at":20,"status":21,"review_note":22,"review_notes":23,"image_url":22,"persona_id":22,"persona_name":22,"section":24,"tags":25,"sources":30,"feedback":34,"feedback_at":22,"cost_usd":34,"total_tokens":34},11766,"swedish-wi-fi-gun-detector-hits-725-precision-in-lab-tests","Swedish Wi-Fi Gun Detector Hits 72.5% Precision in Lab Tests","A Swedish defense lab's WiFireNet spots concealed handguns from Wi-Fi distortion, but accuracy falls sharply when the room or the task gets harder.","Swedish researchers have trained an AI to spot concealed handguns by reading how bodies and belongings distort Wi-Fi signals, and in controlled tests it reached 72.5% average precision.\n\nThe team at the Swedish Defense Research Agency (FOI) described the system, called WiFireNet, in a paper posted to arXiv on October 13. It needs a Wi-Fi transmitter, a receiver and the model. Signals crossing a room bounce and bend depending on an object's shape, orientation and material. Those measurements are known as channel state information (CSI), and WiFireNet reads them to guess what a person is carrying.\n\nTo train it, the researchers recorded video and reflected Wi-Fi signals at the same time while people walked around with different objects, then used the footage to label the signals. The props included a real metal handgun, a plastic handgun, a metal water bottle and a phone, picked to test whether the system could tell a gun from lookalikes in shape or material.\n\nPrecision, the share of the system's handgun alerts that were correct, averaged 72.5% with up to four people moving in a small indoor space. Asking it to also pinpoint where on the person the weapon sat dropped that to 53.8%. The model also struggles in indoor layouts it has not seen before.\n\nThat last weakness is the one to watch. A detector that needs retraining for every room is a lab result, not a replacement for a metal detector, which at least works the same way anywhere. The prototype also ran on a modified version of the 1999 802.11a standard. The researchers said later phases will use Wi-Fi 7 and Wi-Fi 8, whose higher-resolution CSI should help. They released the code, models and dataset as open source.\n\nThe privacy question travels with the technique. Security researchers previously showed that ordinary Wi-Fi routers can identify people with 99.5% accuracy, and critics say the spread of Wi-Fi sensing has outrun any regulatory framework. If gun detection gets good enough to deploy, the open question is who decides where the same signals may be read.","[\"wi-fi-sensing\",\"weapons-detection\",\"surveillance\",\"open-source\"]","2026-10-18T11:00:00.000Z","2026-10-18T12:25:26.483Z","2026-10-18T12:25:28.585Z","published",null,[],"ai",[26,27,28,29],"wi-fi-sensing","weapons-detection","surveillance","open-source",[31],{"name":32,"url":33},"Tom's Hardware","https:\u002F\u002Fwww.tomshardware.com\u002Ftech-industry\u002Fartificial-intelligence\u002Fresearchers-train-ai-to-detect-concealed-handguns-using-wi-fi-signals-open-source-wifirenet-achieves-precision-detection-on-older-802-11a-standard-by-analyzing-how-weapons-distort-wireless-signals",0,{"sections":36},[37,40,45,50,55,60,65,70,75,80,85,90,95,100],{"name":38,"slug":24,"count":39,"latest_published_at":18},"AI",7040,{"name":41,"slug":42,"count":43,"latest_published_at":44},"Security","security",1004,"2026-10-18T12:05:00.000Z",{"name":46,"slug":47,"count":48,"latest_published_at":49},"Policy","policy",539,"2026-10-17T19:38:12.000Z",{"name":51,"slug":52,"count":53,"latest_published_at":54},"Deals","deals",524,"2026-10-17T07:00:00.000Z",{"name":56,"slug":57,"count":58,"latest_published_at":59},"Hardware","hardware",265,"2026-10-18T13:24:23.000Z",{"name":61,"slug":62,"count":63,"latest_published_at":64},"Consumer Tech","consumer-tech",236,"2026-10-16T23:36:26.000Z",{"name":66,"slug":67,"count":68,"latest_published_at":69},"Science","science",203,"2026-10-17T12:40:00.000Z",{"name":71,"slug":72,"count":73,"latest_published_at":74},"Startups","startups",134,"2026-10-18T12:02:57.000Z",{"name":76,"slug":77,"count":78,"latest_published_at":79},"Software","software",129,"2026-10-15T22:21:06.000Z",{"name":81,"slug":82,"count":83,"latest_published_at":84},"Dev Tools","dev-tools",118,"2026-10-16T15:52:39.000Z",{"name":86,"slug":87,"count":88,"latest_published_at":89},"General","general",82,"2026-10-16T16:06:38.000Z",{"name":91,"slug":92,"count":93,"latest_published_at":94},"Gaming","gaming",77,"2026-10-17T16:59:39.000Z",{"name":96,"slug":97,"count":98,"latest_published_at":99},"Reviews","reviews",37,"2026-10-14T10:00:00.000Z",{"name":101,"slug":102,"count":103,"latest_published_at":104},"How-To","how-to",8,"2026-10-05T09:00:00.000Z"]