Life cycle thinking and machine learning for urban metabolism assessment and prediction

Peponi, Angeliki; Morgado, Paulo; Kumble, Peter

doi:10.1016/j.scs.2022.103754

Cited by 15 publications

(10 citation statements)

References 40 publications

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“…However, an ambivalent impact is observed on SDG 7.3.1 dedicated to energy intensity (primary energy) which merits further analysis since the related net effect remains unclear. AI for land management can support efficient use of resources leading to lower energy consumption and intensity of the economy [174,175]. However, potential rebound effects [176] may arise along with growing energy demand from the DL algorithms [177,178], which might outweigh the benefits.…”

Section: Group 3: Ai As a DImentioning

confidence: 99%

Operationalizing Digitainability: Encouraging mindfulness to harness the power of digitalization for sustainable development

Gupta¹,

Zeballos²,

Castro³

et al. 2022

Preprint

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Digitalization is globally transforming the world with profound implications. It has enormous potential to foster progress toward sustainability. However, in its current form, digitalization also continues to enable and encourage practices with numerous unsustainable impacts affecting our environment, ingraining inequality, and degrading quality of life. There is an urgent need to identify such multifaceted impacts holistically. Impact assessment of digital interventions (DIs) leading to digitalization is important specifically for Sustainable Development Goals(SDGs). Action is required to understand the pursuit of short-term gains toward achieving long-term value-driven sustainable development. We need to understand the impact of DIs on various actors and in diverse contexts. A holistic understanding of the impact it creates will help us align it with visions of sustainable development and identify potential measures to mitigate negative short and long-term impacts. The recently developed Digitainability Assessment Framework (DAF) unveils the impact of DIs with an in-depth context-aware assessment and offers an evidence-based impact profile of SDGs at the indicator level. We performed the impact assessment of diverse technologies using DAF. This paper summarizes the insights from the Digitainable Spring School 2022 on "Sustainability with Digitalization and Artificial Intelligence," one of whose goals was to operationalize the DAF as a tool in the action learning process with diverse professionals in the field of digitalization and sustainability. The DAF guides a holistic context-aware process formulation for a given DI. An evidence-based evaluation within the DAF protocol benchmarks a specific DI’s impact against the SDG indicators framework. The operationalization of the DAF was carried out by looking at four different DIs: smart home technologies (SHT) for energy efficiency, blockchain for food security, artificial intelligence for land use cover and changes (LUCC), and big data for international law. Each of the four studies addresses different DIs for digitainability assessment using different techniques for a diverse group of indicators, demonstrating the potential of the DAF but also outlining the existing data gaps that limit a comprehensive analysis.

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Section: Group 3: Ai As a DImentioning

confidence: 99%

Operationalizing Digitainability: Encouraging mindfulness to harness the power of digitalization for sustainable development

Gupta¹,

Zeballos²,

Castro³

et al. 2022

Preprint

View full text Add to dashboard Cite

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“…The introduction of indicators has benn discussions by scholars, scientists, and experts, i.e. (Peponi, et al 2022) evaluated a multidimensional analysis in the perspective of urban ecosystem services with several indicators helpful for assessing the functioning of urban neighborhoods.…”

Section: Indicatorsmentioning

confidence: 99%

Renovation programs in old and inefficient neighborhoods of cities with case studies

Shahraki¹

2022

City Territ Archit

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This article concerns urban renovation’s background, necessity, goals, methods, and outcomes. The addressed question is how shall renew and rehabilitate old and non-functional urban neighborhoods.The aim is to build a model for cities’ renovation respecting general standards of town-building, local characteristics, requirements of inhabitants, and strategic development plans.The applied research methods are theoretical and experimental, which analyze the situation of worn-out neighborhoods of the case study cities in housing, physical, socioeconomic, and environmental perspectives.A problem-oriented, systematic, and step-by-step model evaluates the average magnitudes of damages caused by the nonfunctioning neighborhoods in 31 metropolitans of Iran. Certain indicators will introduce neighborhoods to renew them through a mother renovation program, which includes several projects. Simulating the program in the cities lead them to the best possible results in the renovation.The renovation program is applicable in every other city, which faces inefficiently and nonfunctioning because of oldness.

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“…Обзор научных трудов, исследуемой области показал, что отдельные исследователи [12,13] посвящают исследования жизненному циклу информационной модели здания, другие [14] предлагают рассматривать жизненный цикл строительного сектора с учетом воздействия глобальных выбросов CO 2 в окружающую среду и утверждают, что, в жизненном цикле строительного сектора, воздействия возникают не только на одной стадии (т. е. стадии использования), но и на каждой стадии ее жизненного цикла, третьи [15] заявляют, что поддержание городских экосистемных услуг является ключом к устойчивости городских территорий, повышению устойчивости системы, обеспечению здоровья и благополучия населения, четвертые [6] рассматривают вопросы устойчивости городов и жизненного цикла для отображения текущей ситуации и выявления пробелов для дальнейших исследований и т.п. Авторы поднимают и обозначают разноплановые вопросы, касающиеся проблемных ситуаций в городах, или сосредотачивают свои исследования на отдельных проблемах жизненного цикла города и его территорий.…”

Section: рис 1 рейтинг стран с наибольшим количеством исследований в ...unclassified

Life Cycle of Urban Planning System

Proshunina

Khomenko

2022

Inž.-stroit. vestn. Prikaspiâ

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Градостроительные системы являются сложными образованиями, характеризующиеся ресурсными мощностями и взаимосвязанными процессами. Для пролонгированной жизнеспособности градостроительной системы, отвечающей своевременному эволюционному развитию, необходимы взвешенные решения и ориентирующие алгоритмы на каждом этапе жизненного цикла системы. Жизненный цикл градостроительной системы многими исследователями раскрывается с разных подходов, тем не менее, отдельные составляющие многокомпонентной и полиориентированной градостроительной системы являются плохо изученными и требуют более детального рассмотрения. В статье анализируется современный взгляд на градостроительную систему с точки зрения жизненного цикла системы. Формируются представления о становлении стадийности цепи жизненного цикла и определяется место исследования в общей структуре жизненного цикла градостроительной системы.

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Life cycle thinking and machine learning for urban metabolism assessment and prediction

Cited by 15 publications

References 40 publications

Operationalizing Digitainability: Encouraging mindfulness to harness the power of digitalization for sustainable development

Operationalizing Digitainability: Encouraging mindfulness to harness the power of digitalization for sustainable development

Renovation programs in old and inefficient neighborhoods of cities with case studies

Life Cycle of Urban Planning System

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