Multi-layered design strategies to adopt smart districts as urban regeneration enablers
Bibliographic record
Abstract
Smart City emerged as a reference concept to shape the city of the future, mainly by strengthening the connections between grids, Information and Communication Technology (ICT) tools, governance and people.'Smart' refers to the potential benefit that is derived by adopting ICT to face the increasing complexity of city growth, which involves multiple urban scales, a number of different players and a variety of regulatory frameworks, as shown by several experiences worldwide in the past few decades.Compared to the potential that is expected to be fuelled by hyper-connected devices in delivering an efficient and optimized configuration of the urban eco-system, the architecture of the city seems to have been relegated to the background.Facilitating an integrated management of the urban dynamics on both a large and a small scale is a key challenge.This means that the cross-related effects of decisions and behaviours must be identified, mapped and analysed considering their relations, reciprocal influences and conflicts.Although an effective ICT infrastructure should facilitate this purpose, the number of variables to consider is enormous, due to both top-down and bottom-up strains, which can act simultaneously on a large palette of fields, with multiple and combined issues as well.In order to design a model on which a tool for management can be built, a simplified scale of analysis is needed: the 'district' seems to represent an acceptable intermediate portion of the whole city where local and global phenomena can be observed from a perspective of their interferences and potential synergies.It often also corresponds to an administrative entity as well as to a structured place recognized by citizens and inhabitants.This article reports on a study conducted in the city of Bologna by a team of researchers of the University of Bologna -Department of Architecture.The study aimed at supporting the municipality in defining effective strategies to implement the Smart City Vision by a set of coordinated actions of regeneration at district level.The research aimed at coupling holistic design principles and the typical ICT platform architecture into an inter-operable tool that could enable the management of the key features of a district in separate layers, supplemented by different data sets.A significant part of the research has been devoted to identifying the variables involved and defining the methodology to process them, according to the most up-to-date shared definitions and indicators.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.011 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".