Eddie Soulier, Philippe Calvez,
Hypergraph of massive digital traces as representation of human activities: a way to reduce energy consumption by identifying sustainable practices
GREEN 2016, The First International Conference on Green Communications, Computing and Technologies
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On the one hand the ecological transition and sustainable development issues are today a reality that can not be ignored given the negative impacts of human activities on their environments. On the other side, an increasingly important digitization of these environments results in the generation of massive volumes of digital traces, which are all signs of actors’ activities. A significant challenge is to understand the ins and outs of environmental impact due to activities and considering Energy Impact (EI) as a key indicator and how this indicator can strongly change from an activity to another. Our approach considers the Practices recognition on the basis of these digital traces generated by human and non-human entities during specific activities. Practice (instantiation of activity) uses more or less resources (physical and virtual) during their existence. Being able to identify which one is more resources dependent would help to better understand how to promote ecological transition. Promoting, or at least identifying on the basis of indicators (i.e Energy Impact), practices that have a low impact on the environment could be an innovative approach. These practices, defined as coordination of multiple heterogeneous entities in time and space, can be formalized in the form of multidimensional activities structures – Activities’s Hypergraph – using the Assemblage Theory (“Agencement” in French) and using a set of mathematical tools (Simplicial Complexes, Hypernetworks). This research attempts to model the phenomenon of human and non-human activity based on the characterization of the context (massive contextual data). These Assemblages are represented and computed in a research platform (IMhoTEP) which aims to build these complex structures not based on a priori entities’ classification, but by focusing on the relationships they maintain in several dimensions. The main goal is to offer a decision tool which supports actors’ ecological transition by understanding activities inducing consumption or production of resources. This academic research in the field of computer science is based on continuous digitization of physical and virtual spaces, particularly highly connected urban areas (Smart City, Internet of Everything).