This thesis introduces a groundbreaking blockchain-based framework that reimagines the national population census process. Its core objective is to transform census-taking by embedding principles of transparency, accountability, privacy, and security, offering a scalable and reliable alternative to traditional methods. The proposed system directly addresses the persistent issue of undercounted populations, particularly among marginalised groups. By integrating community-level datasets from non-state actors such as NGOs, the framework enables robust verification of individuals’ living conditions and residential status. This multi-source approach yields a more accurate and inclusive demographic representation, overcoming limitations inherent in centralised, government-led census models. Unlike conventional systems—often susceptible to political influence and data manipulation—this decentralised model fosters trust and resilience. It also opens pathways for interdisciplinary collaboration, leveraging blockchain’s synergy with emerging technologies to support equitable and data-driven governance. Traditional census methodologies, characterised by occasional data updates and inefficiencies, often fail to protect the rights of minorities and marginalised communities. The thesis addresses these shortcomings by ensuring data transparency, quality, and accuracy, particularly safeguarding personally identifiable information. It is especially relevant in contexts of external migration and internal displacements, where data privacy and accuracy are critical yet challenging. By implementing the census on a blockchain platform, the inherent benefits of security, transparency, and immutability are enhanced. It enables a more effective recording, 3 monitoring, forecasting, and analysis of demographic and socioeconomic trends. The project intersects various disciplines, including computer science, surveying, and government data collection, with blockchain technology, encouraging innovative solutions and applications. The development of a blockchain-based population census involved a systematic literature review that identified key challenges in traditional census methods and a use case in Pakistan to address specific issues, such as non-immutability and authorisation problems. The result is a blockchainbased architecture that enhances security, accountability, and transparency, effectively tackling the problem of uncounted individuals in census data. Subsequently, a prototype was designed, developed, and implemented within a specified geography block covering 267 houses and homeless individuals. Engaging three NGOs, 76 homeless individuals were approached. The findings revealed significant undercounting issues, indicating that up to 29% of the population, including marginalised groups and non-ID card holders, may have been overlooked. The system underwent evaluation across four stages, encompassing coverage and inclusion validation, software usability and accessibility, system performance and scalability, and data integrity and trust. Notably, the results of the software usability experience and blockchain network performance were highly satisfactory. Throughout the study, our primary contributions to the knowledge include i). establishing a knowledge bank on the existing challenges of the national population census, ii). proposing a blockchain-based system architecture to mitigate the problem of missing persons and marginalised communities, iii). implementing a proof-of-concept and conducting simulation testing, and iv). showcasing how blockchain technology can be used for the betterment of humanity and v). opening new research frontiers on how blockchain-based systems for census can be used for self-sovereign identity mechanisms.
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Full text Description: PhD Thesis_Sana_Rasheed.pdf (pdf)
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