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Deepscent AI Submitted to CES 2026 Innovation Awards in Four Categories

Deepscent Inc., a South Korean IT company specializing in digital olfactory solutions, announced that its Deepscent AI platform has been submitted to the CES 2026 Innovation Awards in four categories: Home Appliances, Smart Home, Smart Communities, and Content & Entertainment.

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“By embedding scent into spatial computing, Deepscent AI establishes a new benchmark for immersive, emotion-driven innovation.”

Engineering Breakthroughs

  • Multimodal AI Algorithm: Interprets image, audio, mood, and environmental inputs within 3 seconds, matching optimal fragrance profiles.
  • Digitized Dataset: Trained on 100,000+ fragrance metadata points (accords, notes, reviews) for context-aware precision.
  • Dynamic Blending: Uses 20 biodegradable capsules × 3 intensity levels to generate 392,445 unique scent combinations. Capsules auto-calibrate to temperature, humidity, and airflow.
  • Device Performance: Covers 538 ft² (50m²) with <30dB ultra-quiet diffusion and supports MQTT/RESTful API for real-time IoT integration.

Design & Sustainability

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Constructed with recyclable ABS-aluminum composites and 100% biodegradable scented capsules, Deepscent AI balances eco-conscious materials with advanced engineering.

Intellectual Property

Deepscent AI has secured 6 granted patents and 21 pending applications, spanning hardware, algorithms, and system integration. This portfolio reinforces its leadership in AI-powered olfactory computing.

Category Impact

  • Home Appliances: Enhances living spaces with adaptive scent personalization.
  • Smart Home: Creates seamless, responsive, mood-driven atmospheres.
  • Smart Communities: Scales across public venues, improving collective well-being and identity.
  • Content & Entertainment: Synchronizes with digital media for hyper-realistic multisensory storytelling.

Marco, CEO of Deepscent Inc., said, “By embedding scent into spatial computing, Deepscent AI establishes a new benchmark for immersive, emotion-driven innovation.”

Also Read: Developing Autonomous Security Agents Using Computer Vision and Generative AI

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