Decentralized IoT Data Authentication with Signature Aggregation.

The rapid expansion of the Internet of Things (IoT) has introduced significant challenges in data authentication, necessitating a balance between scalability and security. Traditional approaches often rely on third parties, while blockchain-based solutions face computational and storage bottlenecks. Our novel framework employs edge aggregating servers and Ethereum Layer 2 rollups, offering a scalable and secure IoT data authentication solution that reduces the need for continuous, direct interaction between IoT devices and the blockchain.

Decentralized Machine Autonomy for Manufacturing Servitization.

Blockchain ecosystems are rapidly maturing and meeting the needs of business environments (e.g., industry, manufacturing, and robotics).

Approaching the Communication Constraints of Ethereum-Based Decentralized Applications.

Those working on Blockchain technologies have described several new innovative directions and novel services in the Internet of things (IoT), including decentralized trust, trusted and verifiable execution of smart contracts, and machine-to-machine communications and automation that reach beyond the mere exchange of data. However, applying blockchain principles in the IoT is a challenge due to the constraints of the end devices. Because of fierce cost pressure, the hardware resources in these devices are usually reduced to the minimum necessary for operation.

LDAF: Low-Bandwidth Distributed Applications Framework in a Use Case of Blockchain-Enabled IoT Devices.

In this paper, we present Low-Bandwidth Distributed Applications Framework (LDAF)-an application-aware gateway for communication-constrained Internet of things (IoT) devices. A modular approach facilitates connecting to existing cloud backend servers and managing message formats and APIs' native application logic to meet the communication constraints of resource-limited end devices. We investigated options for positioning the LDAF server in fog computing architectures.

A System for Multi-Domain Contextualization of Personal Health Data.

Current telehealth systems are used to improve the treatment of chronic diseases by collecting medical data at the patient and transferring them to a remote medical institution. Research shows that such medical practice can be substantially improved if the measured parameters are greater in number and of more diverse nature. Emerging consumer solutions for monitoring personal health and wellness, as well as various resources from domains like internet, telecommunications and smart living, can be used as possible sources for exploration of an individual's wider health context.