Making IoT education fun: How prototyping sparks learning with this unique approach

Learn how Phase Dock is simplifying IoT prototyping for aspiring engineers.

Chris Lehenbauer, CEO and co-founder of Phase Dock Inc., sat down with the All Things Open team to share insights on the growing field of Internet of Things (IoT) and its potential to transform education. His company specializes in making it easier to prototype and develop IoT projects by creating modular systems that simplify the integration of development boards like Arduino and Raspberry Pi. By designing tools to speed up the assembly process, Phase Dock helps users focus on the creative aspects of building their projects rather than the cumbersome hardware setup.

One of the highlights of the interview is Phase Dock’s commitment to education. Chris presents a scaled-down industrial robot model that teaches middle and high school students important engineering principles through hands-on experience. This robot, based on an open source design, integrates mechatronics, electronics, and programming. The robot’s design enables students to learn about microcontrollers, sensors, and programming logic—skills essential for understanding IoT. The robot’s versatility, from being controlled with a PS4 controller to playing Tic-Tac-Toe, provides a fun and engaging way for students to develop their engineering skills.

Chris also shares an exciting roadmap for incorporating machine vision and machine learning into the robot. By adding ESP32 cams and leveraging machine learning, the robot will be able to autonomously identify objects, such as color-coded blocks, and complete tasks like sorting them. This move demonstrates how affordable, simple robots can be upgraded with advanced AI functionalities, making them suitable for both educational and practical applications in IoT.

Key takeaways

• Educational focus in IoT: Phase Dock is using hands-on projects like a desktop robot to teach young students critical skills in mechatronics, electronics, and programming, aiming to make engineering fun and accessible.
• Advancing IoT with AI: By integrating machine vision and machine learning into their robot, Phase Dock is making advanced AI capabilities more accessible, demonstrating the potential for simple, affordable robots to handle complex tasks.
• Open source commitment: Phase Dock is open sourcing both its curriculum and software, and is exploring open sourcing hardware, fostering a collaborative approach that benefits the broader community and accelerates innovation.

Conclusion

Chris Lehenbauer’s work at Phase Dock exemplifies how IoT can both inspire the next generation of engineers and drive technological innovation. By simplifying the prototyping process and focusing on education, Phase Dock makes it easier for newcomers to engage with IoT technologies. The inclusion of AI and machine learning into their projects shows the vast potential for growth in this space. Moreover, their commitment to open source principles ensures that the wider community can contribute to and benefit from their innovations, making the future of IoT more collaborative and accessible than ever before.

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