DFRobot Showcases AI Maker Projects at Robot Hokoten in Akihabara
Electronic Nose: Integrating TinyML with On-Device AI
The "Electronic Nose" project combines edge AI with embedded hardware. It uses four MEMS gas sensors connected to an
During the demonstration, the sensor probe was placed above a glass of beer. Within 20 to 30 seconds, the system completed odor sampling and analysis. The results were then transmitted to the LattePanda Sigma, a compact x86 computing module, which generated descriptive content or tasting notes using a locally deployed language model. The entire process was executed on-device, without relying on network connectivity.
AI Cell Recognition: Bringing AI into the STEAM Classroom
Another featured project focused on educational applications. DFRobot presented an AI-powered cell recognition teaching system designed to integrate artificial intelligence into middle school biology education. The system is built using the HUSKYLENS 2 AI vision sensor and the UNIHIKER K10 development board.
Powered by the K230 processor with up to 6 TOPS of AI computing performance, HUSKYLENS 2 can efficiently run both pre-trained and user-trained models with low latency. In the demonstration, the system performed real-time identification and classification of cells under a microscope, making abstract AI and machine learning concepts tangible through hands-on interaction.
The project showcases the complete AI workflow—from data collection and model training to edge inference—highlighting its practical applicability in educational settings.
Partnering with DigiKey to Expand the Open-Source Hardware Ecosystem
DFRobot and DigiKey jointly showcased at Robot Hokoten to promote open-source hardware and AI education. The two parties will continue collaborating on technical content, global marketing, and educational solutions, lowering the barrier to AI and open hardware adoption, and accelerating the transition from maker projects to real STEAM classroom applications.
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SOURCE DFRobot
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