Helsinki May 2019: OpenTech AI

Data Standard for Adaptive Self-Organization

Published on May 3, 2019 / Updated on May 7, 2019 | Susu Nousala (Tongj Univesity, Shanghai, China; University of Melbourne, Melbourne, Australia), Marco Cataffo (Politecnico di Torino) and David Ing (Aalto University)

The second OpenTechAI workshop in Helsinki, Finland will be held on May 6 and 7. The event is sponsored by IBM & VTT and is by invitation only. The workshop focuses on open source AI topics particularly relevant to Finland, and to Europe as a whole. On May 6 a number of posters will be on display, and there will be an opportunity to talk with the poster authors. This is an ideal venue to network and build new collaborations. The following is a list of the posters.

Data Standard for Adaptive Self-Organization

The Creative Systemic Design Platform work focuses on facilitating learning of a diverse set of organizations, researching on the quality of interactions occurring among different agents, both human and non, and their context. A major communication channel available today employs sensors to observe otherwise invisible conditions of the environment, enabling a detailed understanding of how patterns of interactions among biological elements influence the global conditions. To address some of the most urgent need resulting from urbanization, industrialization and globalization processes, in 2018 we started working on micro-farming automated systems to bring self-organization capacity in human settlements. To start building knowledge models that fit diverse range of human agents, we set the preconditions for a class of Design Students to interact with an indoor greenhouse, in order to constrain the space and time of natural cycles of vegetation and water and the number of observable interactions. This process led to work on the development of data standards for collection and integration protocols to embed qualitative observation. On a slightly longer term time scale, it is key element to enable access to self-monitoring practice into farm management, distributing learning and adaptation capacity as basis for autonomous, ecologically fitting human settlements.