The Industrial Internet of Things (IIoT) has the potential to improve the production and business processes by enabling the extraction of valuable information from industrial processes. The mining industry, however, is rather traditional and somewhat slow to change due to infrastructural limitations in communication, data management, storage, and exchange of information. Most research efforts so far on applying IIoT in the mining industry focus on specific concerns such as ventilation monitoring, accident analysis, fleet and personnel management, tailing dam monitoring, and pre-alarm system while an overall IIoT architecture suitable for the general conditions in the mining industry is still missing. This article analyzes the current state of Information Technology in the mining sector and identifies a major challenge of vertical fragmentation due to the technological variety of various systems and devices offered by different vendors, preventing interoperability, data distribution, and the exchange of information securely between devices and systems. Based on guidelines and practices from the major IIoT standards, a high-level IIoT architecture suitable for the mining industry is then synthesized and presented, addressing the identified challenges and enabling smart mines by automation, interoperable systems, data distribution, and real-time visibility of the mining status. Remote controlling, data processing, and interoperability techniques of the architecture evolve all stages of mining from prospecting to reclamation. The adoption of such IIoT architecture in the mining industry offers safer mine site for workers, predictable mining operations, interoperable environment for both traditional and modern systems and devices, automation to reduce human intervention, and enables underground surveillance by converging operational technology (OT) and information technology (IT). Significant open research challenges and directions are also studied and identified in this paper, such as mobility management, scalability, virtualization at the IIoT edge, and digital twins.

Modern cities are deploying smart, safe, and sustainable smart city services. However, such services are largely fragmented across cities because they are being developed based on proprietary IoT solutions or using different IoT standards. This creates a strong need to develop an approach to bridge disconnected smart cities and provide interoperability. Therefore, the aim of this article is to provide a guideline to mayors and other city officials for interconnecting their smart cities with other smart cities for interoperability. For this purpose, we propose three interworking models that can be selected based on the status of the cities to be connected with each other. All these models enable the continuity of IoT services between cities using different technologies, that is, a standardized interface, interworking proxy, and semantics. As only one model cannot be adapted to all the connected city cases, we thoroughly compare and analyze the models followed by introducing the pros and cons of each model.

As the Internet of Things (IoT) is evolving rapidly in various verticals, such as smart cities and smart industries, the number of IoT applications is growing exponentially. Standardized conformance testing mechanisms are widely used to test software applications, including IoT applications. However, current conformance testing mechanisms require continuous human intervention and additional software to be embedded into a target device being tested, which is time consuming, costly, and requires additional memory on the target device. Therefore, there is a considerable need to enhance and optimize existing conformance testing so that it is adequate for automatically testing highly distributed constraint IoT applications. In this paper, we propose a novel mechanism for automated and scalable conformance testing for IoT applications by introducing a test triggering mechanism based on a standardized test interface. This triggering mechanism is based on several new logical components in a testing environment that exchange messages between a testing system and a target IoT device. This technique of automatic conformance testing can lessen the cost and human intercession to decrease the number of missteps and accelerate the IoT market by certifying IoT applications.

In the realm of Industrial Internet of Things (IoT) and Industrial Cyber-Physical Systems (ICPS), Digital Twins (DTs) have revolutionized the management of physical entities. However, existing implementations often face constraints due to hardware-centric approaches and limited flexibility. This article introduces a transformative paradigm that harnesses the potential of distributed Digital Twins as proxies, enabling software-centricity and unlocking composability and flexibility for purpose-oriented digital twin development and deployment. The proposed microservices-based architecture, rooted in service-oriented architecture (SOA) and microservices principles, emphasizes reusability, modularity, and scalability. Leveraging the Lean Digital Twin Methodology and packaged business capabilities expedites digital twin creation and deployment, facilitating dynamic responses to evolving industrial demands. This architecture segments the industrial realm into physical and virtual spaces, where core components are responsible for digital twin management, deployment, and secure interactions. By abstracting and virtualizing physical entities into individual digital twins, this approach establishes the groundwork for purpose-oriented composite digital twin creation. Our key contributions involve a comprehensive exposition of the architecture, a practical proof-of-concept (PoC) implementation, and the application of the architecture in a use-case scenario. Additionally, we provide an analysis, including a quantitative evaluation of the proxy aspect and a qualitative comparison with traditional approaches. This assessment emphasizes key properties such as reusability, modularity, abstraction, discoverability, and security, transcending the limitations of contemporary industrial systems and enabling agile, adaptable digital proxies to meet modern industrial demands.

As a major utility system in industry, boilers consume a large portion of the total energy and costs. Significant reduction of boiler cost operation can be gained through improvements in efficiency. In accomplishing such a goal, an adequate dynamic model that comprehensively reflects boiler characteristics is required. This paper outlines the idea of developing a mathematical model of a water-tube industrial boiler based on first principles guided by the bond graph method in its derivation. The model describes the temperature dynamics of the boiler subsystems such as economizer, steam drum, desuperheater, and superheater. The mathematical model was examined using industrial boiler performance test data.It can be used to build a boiler simulator or help operators run a boiler effectively