Sustainable development of smart cities through municipal waste incinerators: the examples of artificial intelligence in technological entrepreneurship

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26510%2F24%3APU155246" target="_blank" >RIV/00216305:26510/24:PU155246 - isvavai.cz</a>

Výsledek na webu

<a href="https://sciendo.com/article/10.2478/emj-2024-0037" target="_blank" >https://sciendo.com/article/10.2478/emj-2024-0037</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.2478/emj-2024-0037" target="_blank" >10.2478/emj-2024-0037</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Sustainable development of smart cities through municipal waste incinerators: the examples of artificial intelligence in technological entrepreneurship

Popis výsledku v původním jazyce

The article aims to analyse AI’s use for optimising management processes in urban waste incineration plants, making them consistent with the implementation of the sustainable development goals SDG #11 and SDG #12. The triangulation of research methods was chosen to achieve the most reliable research outcomes. The case study was the selected qualitative method. Among the available techniques, two were selected: Computer-Assisted Web Interviewing (CAWI) and in-depth interviews, both of which were employed to gather the necessary data. Scientific research analysed the AI-based technologies used by individual incinerators. The analysis encompassed trends in waste incineration plants utilising AI for sustainable development in smart cities, particularly for achieving SDG#11 and SDG#12, focusing on leveraging AI to enhance environmental outcomes. The effect of using AI in municipal waste incineration plants for SDG#11 and SDG#12 can be applied to other entities implementing the principles of sustainable development in smart cities. The identified trends underscore the importance of adopting and implementing integrated policies and plans that address inclusion, resource efficiency, climate change mitigation and adaptation.

Název v anglickém jazyce

Sustainable development of smart cities through municipal waste incinerators: the examples of artificial intelligence in technological entrepreneurship

Popis výsledku anglicky

The article aims to analyse AI’s use for optimising management processes in urban waste incineration plants, making them consistent with the implementation of the sustainable development goals SDG #11 and SDG #12. The triangulation of research methods was chosen to achieve the most reliable research outcomes. The case study was the selected qualitative method. Among the available techniques, two were selected: Computer-Assisted Web Interviewing (CAWI) and in-depth interviews, both of which were employed to gather the necessary data. Scientific research analysed the AI-based technologies used by individual incinerators. The analysis encompassed trends in waste incineration plants utilising AI for sustainable development in smart cities, particularly for achieving SDG#11 and SDG#12, focusing on leveraging AI to enhance environmental outcomes. The effect of using AI in municipal waste incineration plants for SDG#11 and SDG#12 can be applied to other entities implementing the principles of sustainable development in smart cities. The identified trends underscore the importance of adopting and implementing integrated policies and plans that address inclusion, resource efficiency, climate change mitigation and adaptation.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

—

OECD FORD obor

50704 - Environmental sciences (social aspects)

Projekt

—

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2024

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Engineering Management in Production and Services

ISSN

2543-6597

e-ISSN

—

Svazek periodika

16

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

PL - Polská republika

Počet stran výsledku

12

Strana od-do

127-138

Kód UT WoS článku

—

EID výsledku v databázi Scopus

2-s2.0-85211771371