Leveraging Artificial Intelligence and Distributed Ledger Technologies Toward Smart and Autonomous Buildings

Abstract

The increasing digitization of the built environment, along with the growing demand for sustainable, resilient, and intelligent infrastructure, has led to the emergence of smart buildings as a critical domain of innovation. These buildings leverage Internet of Things (IoT) devices, building automation systems, data analytics, and artificial intelligence (AI) to optimize operations, reduce energy consumption, and enhance occupant comfort. However, the conventional design of smart building systems remains largely centralized. The reliance on centralized communication protocols and data architectures exposes building systems to single points of failure and cybersecurity threats, where a malfunction can disrupt its operational processes. Moreover, traditional facility management processes often predominantly rely on the centralized organizational structure which restricts participation from the building's stakeholders in the governance and operation of the facility, resulting in inefficiencies, misalignment with user needs, and missed opportunities for community participation. Furthermore, while traditional AI models and machine learning approaches have enabled a degree of building automation, their dependence on predefined rules or narrowly scoped training data limits their ability to reason adaptively in complex environments which is crucial in enabling autonomous building operations. This dissertation introduces a novel interdisciplinary framework that integrates generative artificial intelligence, digital twins, and distributed ledger technologies (DLTs) such as blockchain and decentralized autonomous organizations (DAOs) to develop a secure, decentralized, and autonomous building cyber-physical systems framework for building infrastructure. The overarching objective of this research is to transform how buildings are governed, operated, and maintained by shifting from centralized, administrator-led systems to inclusive, data-driven, and self-governing infrastructure. The research is structured around three primary goals: to enhance the security and resilience of IoT and digital twin data using decentralized communication protocols; to establish democratic and decentralized governance mechanisms for facility management; and to develop a prototype of an autonomous building cyber-physical system that integrates generative AI, digital twins, blockchain, and decentralized governance of building operation. To fulfill these objectives, the dissertation is composed of four interconnected studies. The first study focuses on enhancing the cybersecurity and resilience of smart building systems by developing blockchain-based protocols for transmitting IoT and digital twin data and building operation automation. The second study introduces a decentralized governance platform that allows building stakeholders to collectively participate in facility management decisions. With the addition of a real-time digital building twin and an AI assistant powered by a large language model, the platform promotes transparent, data-driven decision-making and greater inclusivity in building operations. Building on this foundation, the third study adds a blockchain-based incentivization model to encourage community involvement in the collective improvement and upkeeping of building infrastructure. The final study integrates the technological and governance components into a prototype of a Decentralized Autonomous Building Cyber-Physical System. This system brings together blockchain governance, digital twins, and AI agents/assistants capable of smart building appliances through natural human interaction and autonomous control of building operations. It also creates a collectively governed building infrastructure that functions autonomously with self-sustaining operation through blockchain-based protocols includes. The prototype was evaluated across several simulated and real-world scenarios, validating its effectiveness in enabling autonomous, secure, and community-governed building systems. This dissertation contributes to the growing body of knowledge at the intersection of smart buildings, blockchain governance, Generative AI-driven automation, and human-building interaction. By combining decentralized ledger technologies, AI, and digital twins, it lays the groundwork for a new paradigm of autonomous, secure, and community-driven building infrastructure. The research not only offers theoretical advancements in decentralized facility management and AI integration but also provides practical blueprints and open-source prototypes for broader adoption in the built environment.