Blockchain as an Enabler for Transfer Learning in Smart Environments

Abstract

The knowledge, embodied in machine learning models for intelligent systems, is commonly associated with time-consuming and costly processes such as large-scale data collection, data labelling, network training, and fine-tuning of models. Sharing and reuse of these elaborated models between intelligent systems deployed in a different environment, which is known as transfer learning, would facilitate the adoption of services for the users and accelerates the uptake of intelligent systems in environments such as smart building and smart city applications. In this context, the communication and knowledge exchange between AI-enabled environments depend on complicated networks of systems, system of systems, digital assets, and their chain of dependencies that hardly follows the centralized schema of traditional information systems. Rather, it requires an adaptive decentralized system architecture that is empowered by features such as data provenance, workflow transparency, and validation of process participants. In this research, we propose a decentralized and adaptive software framework based on blockchain and knowledge graph technologies that supports the knowledge exchange and interoperability between IoT-enabled environments, in a transparent and trustworthy way.

Exploring the Role of HRM in Facilitating Collaboration and Knowledge Sharing in Decentralized Organizational Structures

“…In the context of organizational culture, structure, and technological infrastructure, knowledge sharing acts as a mediator that influences process improvement, emphasizing the interconnectedness of these factors in knowledge management within enterprises (Chión et al, 2019). Furthermore, the use of technology, such as blockchain-based systems, has been proposed to govern trust and facilitate knowledge transfer in decentralized environments Anjomshoaa & Curry, 2022).…”

“…Additionally, the emergence of informal interpersonal networks facilitated by technology plays a vital role in providing access to expertise in highly decentralized systems (Binz-Scharf et al, 2011). The use of technology, such as blockchain and knowledge graph frameworks, enables reliable and transparent transfer of digital assets, fostering knowledge sharing in smart environments (Anjomshoaa & Curry, 2022).…”

Ethical Knowledge Sharing Leveraging Blockchain: An Overview

“…ENIR is an edge network routing approach that uses deep reinforcement learning for generating knowledge related to routing, where network knowledge and routing optimizations are shared securely using blockchain [76]. To achieve transfer learning in smart environments, knowledge graphs are stored in the blockchain, and such knowledge is exchanged in a decentralized manner [77]. Attribute based access control is implemented using SCs on the blockchain for providing trans-organizational access control, and an ontological model is used in the blockchain for representing and exchanging knowledge inside the blockchain in order to facilitate knowledgebased inferences without a trusted third party [78].…”

Applied Machine Learning for IIoT and Smart Production—Methods to Improve Production Quality, Safety and Sustainability

“…Blockchains play an important role in IIoT systems security; they are applied for various purposes, e.g., for distributed secure databases. The authentication of users to access blockchain is often integrated with a deep learning method that is taught by transfer learning [ 50 , 51 ]. Interestingly, authentication can be performed in the physical layer alone.…”