6533b832fe1ef96bd129aec5

RESEARCH PRODUCT

A Meta-Model for Intelligent Engineering Design of Complex City

Fabien PfaenderFabien PfaenderBin HeAlain-jérôme FougèresEgon Ostrosi

subject

0209 industrial biotechnologyProcess (engineering)Computer scienceInterpretation (philosophy)0211 other engineering and technologiesComplex system02 engineering and technologyObject (computer science)Data scienceField (computer science)Metamodeling[SHS]Humanities and Social Sciences020901 industrial engineering & automationSmart city11. SustainabilityEngineering design processComputingMilieux_MISCELLANEOUS021106 design practice & management

description

A city is a complex system, requiring the input of multiple disciplines for its (re)design. It shares some properties of two kinds of objects: empirical objects as well as theoretical objects. As city emerges as a complex object for multi-disciplinary studies, it is of the highest importance to adopt a systemic and global approach in order to bring new knowledge to this field. To master the growing complexity of cities and to consider in the same spot heterogeneous ways of thinking of city, we need intellectual tools and models. The goal of this paper is to propose a model for describing engineering modelling knowledge with relationships and transformations between four domains: (1) citizen, (2) functional, (3) physical and (4) process. The proposed model is structured on four levels of modelling: (1) conceptual (2) mathematical (3) computational and (4) experimental. These network of models should be necessary intelligent for managing the engineering design of a smart city. For overall city design, the paradigm should change from planner-centric to citizen-centric. However, while these models are potentially relevant, data that may feed these models is lacking most of the time. Moreover, filling and detailing each of the models, requires additional input from different experts and theories. In this chapter smart city engineering design will focus on three interrelated approaches: (a) data that should be gathered, (b) models that can be used by means of these data, and (c) interpretation methods and tools to elaborate knowledge and decision from the results these models can produce. The paper presents some findings from the application of the proposed meta-model.

10.1007/978-3-030-33312-6_9https://hal.archives-ouvertes.fr/hal-03175018