IoT-Based Access Management Supported by AI and Blockchains

Internet-of-Things (IoT), Artificial Intelligence (AI), and Blockchains (BCs) are essential techniques that are heavily researched and investigated today. This work here specifies, implements, and evaluates an IoT architecture with integrated BC and AI functionality to manage access control based on facial detection and recognition by incorporating the most recent state-of-the-art techniques. The system developed uses IoT devices for video surveillance, AI for face recognition, and BCs for immutable permanent storage to provide excellent properties in terms of image quality, end-to-end delay, and energy efficiency

Scalable Transport Mechanisms for Blockchain IoT Applications

This paper studies various methods that improve the performance of Blockchain systems integrated with the Internet of Things (BIoT) using the LoRaWAN access method. Duty Cycle Enforcement (DCE) and Listen Before Talk (LBT) mechanisms as the channel access methods, Automatic Repeat reQuest (ARQ) on the Transport Layer, and transaction aggregation on the Application Layer are evaluated. The main focus is put on the system performance studying the maximal number of transactions submitted, reliability of transport schemes, and the energy efficiency of the BIoT system. The combination of LBT-based MAC, the ARQ-enabled Transport Layer, and transaction aggregation at the Application Layer provides a good trade-off between submitted transaction count, packet loss, and energy efficiency. The proposed scheme complies to the data integrity demands of BIoT applications by specifying a reliable data transmission scheme from IoT devices to the BC