## 2 Existing Enumeration and Housing Population Census Methodology  
Conducting a national population and housing census demands substantial financial and human resources. The gathered data, crucial for policy-making and resource management globally, must be collected accurately by posing relevant questions and enumerating all individuals. Census methodology, therefore, plays a vital role and necessitates careful consideration to comprehensively represent a country's population. Historically, censuses like those in the United States have exhibited bias, neglecting people of color, slaves, and Native Americans, leading to the significant underrepresentation of these groups. This highlights the need for a standardized global methodology. The United Nations addressed this by developing the Principles and Recommendations for Population and Housing Censuses, serving as a guide for countries to achieve reliable population counts at specific points in time [1]. Traditionally, a census involves full-field enumeration, employing various methods to reach households and individuals. Data are condensed into questionnaires designed to capture comprehensive information without marginalization. Conducted through electronic media, mail, or interviews, a census offers an extensive view of a country's population and socio-economic domains. Despite its advantages, a traditional full-field census is complex, time-consuming, and resource-intensive and may lack optimal technological efficiency, leading to data redundancy. An alternative methodology, the register-based census, focuses on specific sub-groups rather than the entire population. It utilizes information from existing records to identify individuals and households in selected areas of employment, education, and tax brackets. Administrative registers, derived from crucial variables, are enumerated and compiled through the census process. Examples of administered variables include taxation, employment, education, social welfare, and businesses. The register-based census methodology is cost-effective, utilizing existing data sources and requiring less funding than the traditional full-field methods [7]. However, it faces challenges in defining variables, potentially leading to discrepancies and the overlooking of certain subgroups, like transient populations. Information may be outdated due to restricted access to registries, limiting this method's overall accuracy [1]. An integrated approach combines register-based and traditional census methods, improving data accuracy and population coverage. This method leverages administrative registers to define subgroups and incorporates field research for recent information. This integrated method enhances data accuracy and accessibility, whilst being cost-effective and not as resource-intensive as traditional methods [8]. Identifiers are essential in both register-based and field research-based methods to prevent overlaps and handle duplicates. Cross-referencing and probabilistic methods address missing entries. A rolling census, conducted annually, complements full-fledged censuses, providing up-to-date information and allowing flexibility for future surveys [1]. Blockchain technology can address the issue of outdated data by enabling regular and real-time updates through electronic sharing. Decentralized data collection from smart devices and IoT sensors directly contributes to the blockchain network, while smart contracts automate survey processes, reducing manual administration. Blockchain's interoperability and integration capabilities enable the consolidation of data from diverse sources, creating a comprehensive view of the population. By leveraging these blockchain features, national census authorities can establish a dynamic and responsive system that continuously updates and enriches census data. Artificial intelligence can enhance data profiling and analysis. Post-census activities, including data processing, storage, and maintenance, are crucial for preventing leaks and improving future planning.