IoT has the potential to transform the way we think about information and communication technology. IoT has been studied extensively across many disciplines such as the networking, communication, security, business, and management communities. However, many unsolved challenges, especially in managing heterogeneous IoTs, remain to be discussed. Recent studies propose using blockchain, an emerging technology that enables decentralized coordination, to address inherent challenges in IoT. This article presents a preliminary study on an architecture that implements blockchain in managing heterogeneous IoT systems. We start by pointing out the limitations of prior IoT systems and the difficulties of integrating IoT and blockchain. Then we outline an architecture to manage a large-scale heterogeneous IoT system. Our main goal is to stimulate further effort and cross-disciplinary collaboration by providing guidance and reference for future studies.

Through the digitization of essential functional processes, Industry 4.0 aims to build knowledgeable, networked, and stable value chains. Network trustworthiness is a critical component of network security that is built on positive interactions, guarantees, transparency, and accountability. Blockchain technology has drawn the attention of researchers in various fields of data science as a safe and low-cost platform to track a large number of eventual transactions. Such a technique is adaptable to the renewable energy-trade sector, which suffers from security and trustworthy issues. Having a decentralized energy infrastructure, that is supported by blockchain and artificial intelligence, enables smart and secure microgrid energy trading. The new age of industrial production will be highly versatile in terms of production volume and customization. As such a robust collaboration solution between consumers, businesses, and suppliers must be both secure and sustainable. In this article, we introduce a cooperative and distributed framework that relies on computing, communication, and intelligence capabilities of edge and end devices to enable secure energy trading, remote monitoring, and network trustworthiness. The blockchain and federated learning-enabled solution provide secure energy trading between different critical entities. Such a technique, coupled with 5G and beyond networks, would enable mass surveillance, monitoring, and analysis to occur at the edge. Performance evaluations are conducted to test the effectiveness of the proposed solution in terms of reliability and responsiveness in a vehicular network energy-trade scenario.