## 2 Methodology
### Systematic Literature Selection and Inclusion Criteria  
To ensure a systematic and reproducible analysis of the scientific literature on the application of AI and Digital Twins (DT) in sustainable waste management, an approach based on the principles of the PRISMA methodology (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) was adopted [18; 19].  
The bibliographic search was conducted using the Scopus database, employing an advanced search string constructed as shown in Figure 1:  
The search string was constructed to incorporate key synonyms and conceptually related terms frequently used within the field. Boolean operators (OR, AND) were employed to balance breadth and precision, allowing the retrieval of a wide yet thematically consistent set of documents. As such, a single, well-structured query was deemed adequate to encompass the diversity of existing research on the topic.  
The initial query, executed without any filters, returned a total of 873 documents. A temporal filter was then applied, restricting the selection to publications from 2015 to 2025 to ensure the currency and relevance of the contributions. This step did not alter the total, which remained at 873 documents.  
Next, to ensure the scientific rigor and reliability of the dataset, a document-type filter was applied, limiting the analysis to peer-reviewed journal articles and conference proceedings [22]. This reduced the dataset to 674 documents.  
Subsequently, a disciplinary filter was introduced, selecting only publications within the following subject areas: Engineering, Environmental Science, Computer Science, and Materials Science--identified as central to the objectives of this study. After applying this filter, the final dataset consisted of 570 documents.  
The selection procedure is summarized in the PRISMA flow diagram shown in Figure 2, which adopts the standard four-phase structure: Identification, Screening, Eligibility, and Inclusion. This framework ensures a transparent and systematic presentation of how the initial dataset was progressively filtered. A simplified overview of the applied criteria is provided in Table 2.  
Figure 1: Search query used in the Scopus database to identify relevant literature. Our elaboration.  
In the identification phase, records were collected through the application of a precisely defined Boolean query. During the screening phase, non-peer-reviewed materials were excluded. The eligibility step entailed a manual assessment of the disciplinary relevance of each document. Finally, in the inclusion phase, only those records that fully met both methodological and thematic requirements were retained for analysis [23; 24].  
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Phase** & **Inclusion Criteria** & **Exclusion Criteria** \\ \hline Identification & Publications indexed in Scopus database; English language; years 2015–2025 & Publications outside time window (pre-2015 or post-2025) _(n = 0)_ \\ \hline Screening & Peer-reviewed documents: journal articles, reviews, and conference papers & Non-peer-reviewed works: notes, editorials, book chapters, etc. _(n = 199)_ \\ \hline Eligibility & Belonging to subject areas: Computer Science (COMP), Engineering (ENGI), Environmental Science (ENVI) & Records from unrelated domains _(e.g., social sciences, business) (n = 104)_ \\ \hline Inclusion & Studies matching all previous filters and containing relevant thematic keywords & _—(Final records included: 570)_ \\ \hline \hline \end{tabular}
\end{table}
Table 2: Inclusion and exclusion criteria for document selection. Our elaboration.  
Figure 2: PRISMA diagram—document selection process. Our elaboration.