Financial literacy and resilience in IoT-driven sustainable development using fuzzy cognitive algorithms

A country’s sustainable development is assessed by its financial improvements and literacy levels. Financial improvement is assessed using a country’s economic management and foreign exchange, and literacy levels must meet the country’s minimum educational criteria. These two factors are validated by statistics reference period and data modules over the years. However, prior research on economic knowledge and its effectiveness has been limited by insufficient data and methodological challenges. This article introduces a sustainability-focused cognitive fuzzification process (SCFP) to identify a country’s key indicators. This process relies on data from the reference period to the present day. These data were validated using fuzzy normalization and rational methods. Specifically, rational methods are used to ensure the accuracy, use of logical consistency checks, cross-variable correlation analysis, and temporal trend evaluation to verify the coherence between literacy and financial data over time. This systematic validation considers annual gaps in terms of literacy and financial inflation. The fuzzy process identifies gaps and inflations from their fall-off and hike values over time. In this process, the cognitive solutions of hikes and downfalls are gauged to provide development suggestions and grants for literacy improvements. Using fuzzy logic, data intensity improves financial assessment and literacy gap identification by 8.85 % and 8.23 %, respectively, reducing computational complexity and assessment time by 11.07 % and 11.01 %, respectively.