## 3 Materials and Methods
### Data Synthesis  
The synthesis techniques for this comprehensive literature review of IoT-based transformer condition monitoring were established to enable a solid, clear, and repeatable aggregate of outcomes from the chosen papers. The method of choosing which papers were deemed appropriate for consideration in each synthesis was undertaken in a structured and a diligent manner, assuring conformity with the review's targets, which concentrate on the significance of IoT technology in revolutionizing condition monitoring of transformers. Excel spreadsheets were developed and utilized to consolidate the data collected from the research problems' answers. The Excel spreadsheet played a vital role in facilitating and ensuring that a valid data extraction process took place. During the synthesis stage, the most popular keywords were used, and the terms that described the study subject were standardized. These data were extracted from the 120 papers that met the minimum of 75% in the quality assessment checklist. The Excel spreadsheet incorporated the following data: (a) year of publication (b) research type (e.g., conference paper, journal, article, review), (c) online repository, (d) country, (e) transformer type or physical object, (f) investigated transformer aspect, (g), microprocessor (h) communication channel, and (i) IoT Cloud. From all 120 of the publications that made up this review, the data listed in Table 2 were \begin{table}
\begin{tabular}{l l l} \hline \hline \multicolumn{1}{c}{**Criteria**} & \multicolumn{1}{c}{**Description**} & \multicolumn{1}{c}{**Details**} \\ \hline Risk of bias assessment tool & Develop MMAT risk of bias tool for qualitative and quantitative data. & MMAT technique, tailored for IoT-based transformer monitoring studies \\ Methodological quality criteria for bias & Refer to the five methodological quality criteria questions listed in Table 5 & Refer to Table 5 \\ Methodological quality criteria questions & Answer methodological quality criteria questions. & Yes, No, Can’t tell \\ Agreement protocol & Address divergences through interactions. & Consensus decision through scoring \\ Results & Guarantee an exhaustive, accurate assessment of risk among every research study. & Defining the influence of the Internet of Things in transformer condition monitoring \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Risk bias process. \begin{table}
\begin{tabular}{l l} \hline \hline \multicolumn{1}{c}{**Category of Study Design**} & \multicolumn{1}{c}{**Methodological Quality Criteria**} \\ \hline  & Is there an appropriate justification for utilizing a mixed methods strategy to answer the research question? & \\ Mixed Methods & Are the study’s components adequately combined to address the study’s question? & \\ Mixed Methods & Are the results of the combination of qualitative and quantitative components & \\  & appropriately determined? & \\  & Are the differences and discrepancies between quantitative and qualitative outcomes & \\  & De the study’s components meet the quality criteria of each methodological approach concerned? & \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Mixed Methods Appraisal Tool criteria. used to extract the relevant information. Using this approach, a clear picture was developed of the most favored microcontrollers for IoT-based transformer condition monitoring, communication channels, IoT clouds, transformer types, and investigated aspects. The process of data synthesis eligibility entailed meticulously choosing papers that were relevant to transformer condition monitoring, used IoT technology, and aligned with the predefined objectives of the author. A regulated assessment with established requirements guaranteed that only relevant papers were included in the analysis, reducing biases and improving the evaluators' thoroughness. Information across numerous research papers was eventually harmonized to enable logical comparisons.