Autonomous Building Cyber-Physical Systems Using Decentralized Autonomous Organizations, Digital Twins, and Large Language Model

• URL: http://arxiv.org/abs/2410.19262v1
• Date: Fri, 25 Oct 2024 02:34:54 GMT
• Title: Autonomous Building Cyber-Physical Systems Using Decentralized Autonomous Organizations, Digital Twins, and Large Language Model
• Authors: Reachsak Ly, Alireza Shojaei,
• Abstract summary: This paper introduces a novel Decentralized Autonomous Building Cyber-Physical System framework. It integrates Decentralized Autonomous Organizations, Large Language Models, and digital twins to create a smart, self-managed, operational, and financially autonomous building infrastructure. An artificial intelligence assistant is developed to provide intuitive human-building interaction for blockchain and building operation management-related tasks.
• Score: 0.0
• License:
• Abstract: Current autonomous building research primarily focuses on energy efficiency and automation. While traditional artificial intelligence has advanced autonomous building research, it often relies on predefined rules and struggles to adapt to complex, evolving building operations. Moreover, the centralized organizational structures of facilities management hinder transparency in decision-making, limiting true building autonomy. Research on decentralized governance and adaptive building infrastructure, which could overcome these challenges, remains relatively unexplored. This paper addresses these limitations by introducing a novel Decentralized Autonomous Building Cyber-Physical System framework that integrates Decentralized Autonomous Organizations, Large Language Models, and digital twins to create a smart, self-managed, operational, and financially autonomous building infrastructure. This study develops a full-stack decentralized application to facilitate decentralized governance of building infrastructure. An LLM-based artificial intelligence assistant is developed to provide intuitive human-building interaction for blockchain and building operation management-related tasks and enable autonomous building operation. Six real-world scenarios were tested to evaluate the autonomous building system's workability, including building revenue and expense management, AI-assisted facility control, and autonomous adjustment of building systems. Results indicate that the prototype successfully executes these operations, confirming the framework's suitability for developing building infrastructure with decentralized governance and autonomous operation.

Related papers

• Fundamentals of legislation for autonomous artificial intelligence systems [0.0]
  The article proposes a method for forming a dedicated operational context for autonomous corporate management systems. The significant part of the operational context is the regulatory and legal environment within which corporations operate.
  arXiv  Detail & Related papers  (2024-09-17T09:50:23Z)
• Decentralised Governance for Autonomous Cyber-Physical Systems [0.24578723416255752]
  This paper examines the potential for Cyber-Physical Systems to be governed in a decentralised manner. By highlighting the considerations and challenges of decentralised governance in managing autonomous physical spaces, the study reveals that autonomy in the governance of autonomous CPS is not merely a technological feat but also involves a complex mesh of functional and social dynamics.
  arXiv  Detail & Related papers  (2024-07-18T14:40:06Z)
• Elements Of Legislation For Artificial Intelligence Systems [0.0]
  A dedicated operational context for autonomous artificial intelligence systems is created. The wording of local regulatory documents can be presented in two versions: for use by people and for use by autonomous systems. Local regulations that provide basis for the joint work of individuals and autonomous artificial intelligence systems can form the grounds for the relevant legislation.
  arXiv  Detail & Related papers  (2024-05-05T11:01:31Z)
• Computing Power and the Governance of Artificial Intelligence [51.967584623262674]
  Governments and companies have started to leverage compute as a means to govern AI. compute-based policies and technologies have the potential to assist in these areas, but there is significant variation in their readiness for implementation. naive or poorly scoped approaches to compute governance carry significant risks in areas like privacy, economic impacts, and centralization of power.
  arXiv  Detail & Related papers  (2024-02-13T21:10:21Z)
• Autonomous Open-Ended Learning of Tasks with Non-Stationary Interdependencies [64.0476282000118]
  Intrinsic motivations have proven to generate a task-agnostic signal to properly allocate the training time amongst goals. While the majority of works in the field of intrinsically motivated open-ended learning focus on scenarios where goals are independent from each other, only few of them studied the autonomous acquisition of interdependent tasks. In particular, we first deepen the analysis of a previous system, showing the importance of incorporating information about the relationships between tasks at a higher level of the architecture. Then we introduce H-GRAIL, a new system that extends the previous one by adding a new learning layer to store the autonomously acquired sequences
  arXiv  Detail & Related papers  (2022-05-16T10:43:01Z)
• A Decentralized Approach Towards Responsible AI in Social Ecosystems [0.0]
  We present a framework that provides computational facilities for parties in a social ecosystem to produce the desired AI behaviors. We analyze AI systems at the architecture level and propose two cryptographic mechanisms for an AI system architecture. We argue the case that a decentralized approach is the most promising path towards Responsible AI from both the computer science and social science perspectives.
  arXiv  Detail & Related papers  (2021-02-12T06:33:42Z)
• Decentralized Control with Graph Neural Networks [147.84766857793247]
  We propose a novel framework using graph neural networks (GNNs) to learn decentralized controllers. GNNs are well-suited for the task since they are naturally distributed architectures and exhibit good scalability and transferability properties. The problems of flocking and multi-agent path planning are explored to illustrate the potential of GNNs in learning decentralized controllers.
  arXiv  Detail & Related papers  (2020-12-29T18:59:14Z)
• Decentralized Reinforcement Learning: Global Decision-Making via Local Economic Transactions [80.49176924360499]
  We establish a framework for directing a society of simple, specialized, self-interested agents to solve sequential decision problems. We derive a class of decentralized reinforcement learning algorithms. We demonstrate the potential advantages of a society's inherent modular structure for more efficient transfer learning.
  arXiv  Detail & Related papers  (2020-07-05T16:41:09Z)
• Graph Neural Networks for Decentralized Controllers [171.6642679604005]
  Dynamical systems comprised of autonomous agents arise in many relevant problems such as robotics, smart grids, or smart cities. Optimal centralized controllers are readily available but face limitations in terms of scalability and practical implementation. We propose a framework using graph neural networks (GNNs) to learn decentralized controllers from data.
  arXiv  Detail & Related papers  (2020-03-23T13:51:18Z)
• Distributed and Democratized Learning: Philosophy and Research Challenges [80.39805582015133]
  We propose a novel design philosophy called democratized learning (Dem-AI) Inspired by the societal groups of humans, the specialized groups of learning agents in the proposed Dem-AI system are self-organized in a hierarchical structure to collectively perform learning tasks more efficiently. We present a reference design as a guideline to realize future Dem-AI systems, inspired by various interdisciplinary fields.
  arXiv  Detail & Related papers  (2020-03-18T08:45:10Z)
• A Self-Integration Testbed for Decentralized Socio-technical Systems [2.8360662552057323]
  This paper introduces a novel testbed architecture for decentralized socio-technical systems running on the Internet of Things. It is designed for a seamless reusability of application-independent decentralized services by an IoT application, and different IoT applications by the same decentralized service. Pressure and crash tests during continuous operations of several weeks, with more than 80K network joining and leaving of agents, 2.4M parameter changes, and 100M communicated messages, confirm the robustness and practicality of the testbed architecture.
  arXiv  Detail & Related papers  (2020-02-06T12:18:28Z)

This list is automatically generated from the titles and abstracts of the papers in this site.

This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.