Smart Cities and Sustainability: A Set of Vertical Solutions for Managing Resources
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Smart City vision can be viewed as a “system of systems”, where all systems within it are interconnected, in constant communication with each other in real time, exchanging information, and making smart decisions all in a sustainable and highly efficient model. Two decades ago, the Smart City concept was born to address emerging city sustainability issues and was mainly focused on energy efficiency and greenhouse gas emissions reduction. More recently the term was attached to the role of ICT infrastructure. This paper aims to clarify interrelations between the Smart City concept and fostering the sustainable development of cities. The paper is based on an analytical study of the main characteristics and systems of a Smart City, emphasizing the significant role of Future Internet in the development of Smart Cities. The first section is a short introduction to challenges and drivers for a Smart City. Sections two and three discuss the technological context of Future Internet and the expected impact of Internet-of-Things, sensors, tags, and cloud computing on Smart Cities. The next two sections analyze the main Smart City Systems and approaches for managing them. Moreover, sections six and seven analyze two of the top performing Smart Cities in Europe and also address the UAE 2021 Vision in order to assert the environmental impacts that occur as a result of transforming into a Smart City. This paper concludes with a common framework for transforming cities into smart ones, which depends on the nature, circumstances, and resources of each city.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it