Various semi-autonomous entities will need to cooperate in order to execute multiple IoT applications. These entities will have to be self-aware and have a different amount of knowledge of the task at hand and the environment where they are located. Unfortunately, it is not always possible to provide all the necessary knowledge to the entities, especially in changing environments. To keep the knowledge of the entities up to date, they need to extend it by applying learning technologies based on Artificial Intelligence and Machine Learning. New knowledge can either be acquired by interacting with the environment (via sensors) or by interacting with the other entities in the environment. By exchanging information via a reliable and secure communication network, the entities in the environment will need to collaborate with each other to update their own knowledge to fulfill their assigned task.

The Collaborative IoT pillar includes a set of architectural components available for integration. The following are the one-pagers for each component which can be downloaded directly as PDFs:

• Web-based EUP IDE for Hypermedia MAS
• Hypermedia MAS Infrastructure
• Global AI
• End User Goal Specification Front End
• Manufacturing AI
• Interoperability Box
• Resource-Aware Training and Inference