BAIoT-EMS: Consortium network for small-medium enterprises management system with blockchain and augmented intelligence of things
Article
Khan, Abdullah Ayub, Yang, Jing, Laghari, Asif Ali, Baqasah, Abdullah M., Alroobaea, Roobaea, Ku, Chin Soon, Alizadehsani, Roohallah, Acharya, U. Rajendra and Por, Lip Yee. 2025. "BAIoT-EMS: Consortium network for small-medium enterprises management system with blockchain and augmented intelligence of things." Engineering Applications of Artificial Intelligence. 141. https://doi.org/10.1016/j.engappai.2024.109838
Article Title | BAIoT-EMS: Consortium network for small-medium enterprises management system with blockchain and augmented intelligence of things |
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ERA Journal ID | 32032 |
Article Category | Article |
Authors | Khan, Abdullah Ayub, Yang, Jing, Laghari, Asif Ali, Baqasah, Abdullah M., Alroobaea, Roobaea, Ku, Chin Soon, Alizadehsani, Roohallah, Acharya, U. Rajendra and Por, Lip Yee |
Journal Title | Engineering Applications of Artificial Intelligence |
Journal Citation | 141 |
Article Number | 109838 |
Number of Pages | 14 |
Year | 2025 |
Publisher | Elsevier |
Place of Publication | United Kingdom |
ISSN | 0952-1976 |
1873-6769 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.engappai.2024.109838 |
Web Address (URL) | https://www.sciencedirect.com/science/article/abs/pii/S0952197624019973 |
Abstract | The rapid adoption of Augmented Intelligence of Things (AIoT) in enterprise management (EM) presents significant challenges in securely managing and exchanging information. This study introduces a blockchain-based platform, BAIoT-EMS, designed to enhance security and efficiency in AIoT-enabled EM systems. The platform leverages a consortium network and InterPlanetary File Storage (IPFS) for secure storage and transaction management, supported by smart contracts to automate and safeguard processes like device registration. A novel multi-proof-of-work consensus mechanism is implemented to analyze, validate, and verify AIoT transactions while minimizing resource consumption. Simulation results demonstrate a 63.51% improvement in performance and an 11.75% reduction in computational power usage, highlighting the effectiveness of the proposed framework. |
Keywords | Augmented intelligence of things (AIoT); Internet of things (IoT); Blockchain; Enterprise management system (EMS); Smart contract |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 4602. Artificial intelligence |
Public Notes | Files associated with this item cannot be displayed due to copyright restrictions. |
Byline Affiliations | Bahria University, Pakistan |
University of Malaya, Malaysia | |
Shenyang Normal University, China | |
Taif University, Saudi Arabia | |
University Tunku Abdul Rahman, Malaysia | |
Deakin University | |
School of Mathematics, Physics and Computing |
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