English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Zendy Open

Presents the pdf analysis as premium feature

PDF Analysis

Insights

Presents the summarisation as premium feature

Summarisation

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the zaia usage as premium feature

ZAIA

Zendy Tools

Zendy Plus

Presents the access of premium content as premium feature

Premium Content

Energy consumption and performance assessment of Smart Cities must consider different levels, various sub-domains, and several stakeholders. A comprehensive energy profile of a city, in fact, should work at the city, district, and building levels. At the same time and for each level, it should take into account both electrical and thermal consumptions, and gather these information from a plethora of different stakeholders (i.e., citizens, utilities, policy makers, and energy providers) and sensors. Current modeling approaches for this context address each level and domain separately, thus preventing a structured and comprehensive approach to a unified energy representation. Moreover, current approaches make difficult to keep the consistency between the energetic data through levels, sub-domains and across stakeholders. Starting from an analysis of ontologies at the state-of-the-art, this paper shows how DogOnt can be used as a foundation towards a shared and unified model for such a context. DogOnt was firstly developed in 2008 and withstand over 8 years of usage without major failures and shortcomings. We discuss successful design choices and adaptations, which kept the model up-to-date and increasingly adopted in domains ranging from home automation to energy representation in Smart Cities.

DogOnt as a viable seed for semantic modeling of AEC/FM