Developing teaching resources to introduce artificial intelligence (AI) fundamentals in K-12 is a key topic in computing education worldwide. Most of the existing approaches align with the AI4K12 initiative guidelines, which establish five big ideas to frame the resources, with different goals according to the educational level. In the current work, a new big idea based on multiagent systems and collective computing is proposed, as it plays a key role in the AI field, and students should learn its fundamentals. In this realm, collective computing relies on the connection of independent computational systems to face challenges coordinatively. Ambient Intelligence (AmI) is a computer science field in which collective computing is applied to real environments that interact with humans in an autonomous way. AmI is commonly employed in smart environments like homes, buildings, factories, or cities. Core topics, including environmental sensors, actuators, communication, and coordination policies, are considered essential for students’ knowledge. This paper presents a structured activity within an Erasmus + project involving thirty K-12 students from five European countries. The goal was to create an AmI application using the Home Assistant framework for autonomous classroom monitoring. A network of real sensors and actuators was used, controlled through a centralized asynchronous programming approach with Python. Benefits and open issues have arisen from this experience that could be helpful for other teachers interested in this new idea. All the teaching resources have been developed for the teacher, and they are open for public distribution or modification.