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ODYSS Unveils AI Necklace That Tracks Your Diet Without Logging a Bite

ODYSS Unveils AI Necklace That Tracks Your Diet Without Logging a Bite

Berlin – September 08, 2026 -- ODYSS, winner of the IFA Innovation Award 2026, has unveiled the N1, an AI-powered necklace designed to automatically track eating habits and eliminate manual food logging.

The necklace detects eating without any typing or photos

The ODYSS N1 uses a G-sensor and contact sensors to detect when it's being worn, while a wide-angle camera captures visual food cues and hand-to-mouth movements to identify eating behavior in real time. Unlike smartwatches, which track calories burned but not consumed, the device is built specifically to capture dietary intake data that has long been missing from personal health tracking.

More than 300 million people use food-logging apps, but most quit

Despite over 300 million registered users across mainstream food-logging apps, long-term adherence remains low. A 2015 CHI study from the University of Washington attributed this drop-off to logging fatigue and the social embarrassment of manually recording meals in public. ODYSS positions the N1 as a passive alternative that works quietly in the background instead of requiring constant user input.

The device generates three separate scores for every meal

The N1 produces three Dietary Scores -- Quality, Energy, and Rhythm -- and explains how each meal affects energy levels, physical recovery, and sleep. The company describes it as a continuous nutrition companion meant to fit into daily routines without demanding active engagement.

A physical switch lets users turn off all sensors instantly

ODYSS built privacy controls directly into the hardware. A dedicated physical switch allows users to disable all sensing functions immediately, and the device operates in a quiet-by-default mode that automatically reduces activity when the wearer isn't eating. On the software side, the system is designed to focus exclusively on food-related information, filtering out unrelated data, blurring faces and personal features captured in images, and deleting raw images after processing.

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