Agile Technology of Information Data Engineering for Intelligent Analysis of the Happiness Index and Life Satisfaction in Known World Cities

This paper presents the development of an intelligent information system for analysing the happiness index and life satisfaction based on sociological survey data from various countries. The research addresses the need to improve the accuracy and efficiency of social research by integrating data mining and machine learning methods – specifically K-means clustering and multiple regression analysis – into the system design. The proposed module enables automated classification of countries and cities by life satisfaction levels, allowing stakeholders to make informed decisions on urban planning and social policy. The system also facilitates the identification of favourable living environments, providing valuable insights into the social, economic, and environmental factors affecting well-being. The experimental results on real-world datasets confirm the module’s effectiveness and predictive capabilities.