Guidelines for a participatory Smart City model to address Amazon’s urban environmental problems
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Notice bibliographique
Résumé
Climate change is a global challenge, and the Brazilian Amazon Forest is a particular concern due to the possibility of reaching a tipping point that could amplify environmental crises. Despite many studies on the Amazon Forest, this research was conducted in Manaus, the capital of Amazonas state, to address five gaps, including the lack of local citizen consultation on urban environmental issues, Smart Cities, decarbonization, and disruptive technologies. This study holds significance for the academy community, government bodies, policymakers, and investors, as it offers novel insights into the Amazon region and proposes a model to engage citizens in Smart Cities. This model could also guide other municipalities aspiring for participatory sustainable development with a decarbonization focus, mitigating future risks, and protecting future generations. Basically, it is an explanatory and applied study that employs mixed methods, including literature, bibliometric and documentary reviews, two questionnaires, and descriptive statistical approaches, organized in four phases to reach the following goals: (a) provide information on the main challenges facing humanity, the Brazilian Amazon state, and the city of Manaus; (b) identify the best Smart City approaches for engaging citizens in solving urban problems; (c) contextualize and consult Manaus City Hall about the effectiveness of the Smart City project; (d) investigate the perceptions of citizens living in Manaus on the main city’s environmental problems, as well as their level of knowledge and interest on issues related to Smart Cities, decarbonization, and disruptive technologies; (e) propose a participatory Smart City model with recommendations. Among the result, the study found that the term “Smart City” dominates scholarly publications among nineteen urban-related terms, and the five main environmental problems in Manaus are an increase in stream pollution, garbage accumulation, insufficient urban afforestation, air pollution, and traffic congestion. Although citizens are willing to help, the majority lack knowledge on Smart City and Decarbonized City issues, but there is a considerable interest in training related to these issues, as well as disruptive technologies. It was found that Amsterdam, Melbourne, Montreal, San Francisco, Seoul, and Taipei all have a formal model to engage citizens in solving their urban problems. The main conclusion is that, after 6 years, the Smart City Project in Manaus is a political fallacy, as no model, especially with a citizen participatory approach, has been effectively adopted. In addition, after conducting a literature and documentary review and analyzing 25 benchmark Smart Cities, the P 5 model and the Citizen Engagement Kit model are proposed with 120 approaches and guidelines for addressing the main environmental problems by including Manaus’ citizens in the Smart City and/or decarbonization journey.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle