阿杜伊诺
MQTT公司
立方体(代数)
计算机科学
微控制器
执行机构
树莓皮
物联网
人工智能
机电一体化
计算机硬件
计算机图形学(图像)
嵌入式系统
计算机视觉
数学
组合数学
作者
Alexander Scheidt,Tim Pulver
出处
期刊:Proceedings of Mensch und Computer 2019
日期:2019-09-08
卷期号:: 893-895
被引量:53
标识
DOI:10.1145/3340764.3345375
摘要
Here we present Any-Cubes, a prototype toy with which children can intuitively and playfully explore and understand machine learning as well as Internet of Things technology. Our prototype is a combination of deep learning-based image classification [12] and machine-to-machine (m2m) communication via MQTT. The system consists of two physical and tangible wooden cubes. Cube 1 ("sensor cube") is inspired by Google's teachable machine [14,15]. The sensor cube can be trained on any object or scenery. The machine learning functionality is directly implemented on the microcontroller (Raspberry Pi) by a Google Edge TPU Stick. Via MQTT protocol, the microcontroller sends its current status to Cube 2, the actuator cube. The actuator cube provides three switches (relays controlled by an Arduino board) to which peripheral devices can be connected. This allows simple if-then functions to be executed in real time, regardless of location. We envision our system as an intuitive didactic tool for schools and maker spaces.
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