Large Geographical Area Aerial Surveillance Systems Data Network Infrastructure Managed by Artificial Intelligence and Certified over Blockchain: A Review

Autor: Nelson Batista, Rui Melicio, Luis Filipe Santos
Jazyk: angličtina
Rok vydání: 2021
Předmět:
Zdroj: Network, Vol 1, Iss 3, Pp 335-353 (2021)
Druh dokumentu: article
ISSN: 2673-8732
DOI: 10.3390/network1030019
Popis: This paper proposes an aerial data network infrastructure for Large Geographical Area Surveillance Systems. The work presents a review of previous works from the authors, existing technologies in the market, and other scientific work, with the goal of creating a data network supported by Autonomous Tethered Aerostat Airships used for sensor fixing, a drones deployment base, and meshed data network nodes installation. The proposed approach for data network infrastructure supports several independent and heterogeneous services from independent, private, and public companies. The presented solution employs Edge Artificial Intelligence (AI) systems for autonomous infrastructure management. The Edge AI used in the presented solution enables the AI management solution to work without the need for a permanent connection to cloud services and is constantly fed by the locally generated sensor data. These systems interact with other network AI services to accomplish coordinated tasks. Blockchain technology services are deployed to ensure secure and auditable decisions and operations, which are validated by the different involved ledgers.
Databáze: Directory of Open Access Journals