The security of Internet of Things (IoT)–Low-Power and Lossy Networks (LLNs) is crucial for their widespread adoption in various applications. The standard routing protocol for IoT-LLNs, IPv6 Routing Protocol over Low-Power and Lossy Networks (RPL), is susceptible to insider attacks, such as the version number attack (VNA), decreased rank attack (DRA), and increased rank attack (IRA). These attacks can significantly impact network performance and resource consumption. To address these security concerns, we propose the IbiboRPLChain Solution, a secure blockchain-based authentication method for RPL nodes. The proposed solution introduces an additional blockchain layer to the RPL architecture, enabling secure authentication of communication links between the routing layer and the sensor layer. The IbiboRPLChain Solution utilises smart contracts to trigger immediate authentication upon detecting routing attacks initiated by malicious nodes in an IoT-LLN environment. The evaluation of the proposed solution demonstrates its superior performance in mitigating insider attacks and enhancing IoT-LLN security compared to existing methods. The proposed solution effectively mitigates insider attacks by employing blockchain technology to authenticate communication links between routing and sensor nodes. This prevents malicious nodes from manipulating routing information and disrupting network operations. Additionally, the solution enhances IoT-LLN security by utilising smart contracts to trigger immediate authentication upon detecting suspicious activity, ensuring prompt action against potential threats. The findings of this research have significant implications for the development and deployment of secure IoT-LLNs.

The security of Internet of Things (IoT)-Low Power and Lossy Networks (LLNs) is crucial for their widespread adoption in various applications. The standard routing protocol for IoT-LLNs, IPv6 Routing Protocol over Low Power and Lossy Networks (RPL), is susceptible to insider attacks, such as the version number attack (VNA), decreased rank attack (DRA), and increased rank attack (IRA). These attacks can significantly impact network performance and resource consumption. To address these security concerns, we propose IbiboRPLChain Solution, a secure blockchain-based authentication method for RPL nodes. The proposed solution introduces an additional blockchain layer to the RPL architecture, enabling secure authentication of communication links between the routing layer and the sensors layer. IbiboRPLChain Solution utilises smart contracts to trigger immediate authentication upon detecting routing attacks initiated by malicious nodes in an IoT-LLN environment. The evaluation of the proposed solution demonstrates its superior performance in mitigating insider attacks and enhancing IoT-LLN security compared to existing methods. The proposed solution effectively mitigates insider attacks by employing blockchain technology to authenticate communication links between routing and sensor nodes. This prevents malicious nodes from manipulating routing information and disrupting network operations. Additionally, the solution enhances IoT-LLN security by utilising smart contracts to trigger immediate authentication upon detecting suspicious activity, ensuring prompt action against potential threats. The findings of this research have significant implications for the development and deployment of secure IoT-LLNs.

The Internet of Things (IoT) continues to expand rapidly, with the Routing Protocol for Low-Power and Lossy Networks (RPL) serving as its core communication backbone. However, RPL remains vulnerable to a range of insider routing attacks such as the Version Number Attack (VNA) and Hello Flooding Attack (HFA), particularly in constrained IoT environments. In our previous work, IbiboRPLChain, we proposed a blockchain-based authentication mechanism to secure communication between routing and sensor nodes. This paper presents an evolved framework, IbiboRPLChain II, which integrates smart contracts, decentralised authentication nodes, and composite blockchain mechanisms to improve network resilience, scalability, and security. Our experiments, conducted using Cooja and Contiki OS, evaluate the system across multiple simulation seeds, demonstrating significant gains in Packet Delivery Ratio (PDR), energy efficiency, and delay mitigation. IbiboRPLChain II proves to be a robust solution for secure, lightweight, and scalable RPL-based IoT environments.

This paper evaluates a Sustainable Energy Efficiency Business Model (SEEBM) for small and medium sized enterprises (SMEs) in the European industrial sector. The sustainability-oriented model, developed by the authors, combines Energy Performance Contracting (EPC), Energy Supply Contracting (ESC), and Energy Saving Insurance (ESI) within a unified framework to support industrial decarbonisation. The study identifies key performance indicators and translates them into a System Dynamics model using a Design-Based Research approach. The model is built from secondary data drawn from 45 SME case studies in the European SMEmPower project and is validated through extreme condition testing and behavioural sensitivity analysis. Results indicate that the integrated model significantly enhances financial performance, reducing the average payback period from average 36 months to 10 months. Sensitivity analysis highlights the influence of contract duration, energy saving rates, and energy prices on both payback and emissions reduction outcomes. This research introduces a novel dynamic framework integrating EPC, ESC, and ESI, enabling time-based evaluation of investment viability and environmental impact. It offers a replicable decision support tool for policymakers and market actors seeking scalable, low risk pathways to SME decarbonisation. Overall, the model provides practical insights for improving investment decisions while accelerating the transition toward sustainable industrial systems across Europe.

The importance of wind turbine reliability for the performance and cost-effectiveness of wind power systems cannot be overstated, and advanced wind turbine condition monitoring is crucial to the solution. Providing effective condition monitoring for wind turbines is still difficult, as there is not a lot of insight in real time, nor is there any integrated sustainability assessment. While some solutions can be offered by digital twins, most existing solutions are not immersive, and do not merge performance information with environmental information. In this paper, an integrated VR-based Digital Twin framework for real-time simulation and condition monitoring as well as deterministic fault-risk assessment of wind turbines is presented. The model is developed in MATLAB using historical UK wind data and includes a reduced-order physics-based turbine model, aerodynamic behaviour, rotor dynamics, thermal modelling, controlled fault injection, and a healthy-reference/fault-exposed dual-turbine configuration. The temperature and vibration results are aggregated into a Fault-Risk Score (FRS) using predefined warning and fault thresholds, while a Health Index (HI), energy production and consequence metrics related to CO₂ are complementary indicators of turbine condition and performance. The results indicate that there is a significant difference between the healthy turbine and the fault-exposed turbine, where the fault-exposed turbine has a higher health-index degradation, lower energy production, and higher fault-risk score. By the end of the simulation period, the turbine’s health index was reduced from >80% to 38% under fault conditions, leading to a 5% penalty in energy generation and a 5.1% elevation in the environmental ${\mathrm{CO}}_2$ impact metric. Additionally, the implementation using MATLAB–Unity showed real-time telemetry transmission and immersive visualisation at 72–90 FPS from the communication response time of less than 50 milliseconds. The system therefore provides an integrated platform for physics-based condition monitoring, controlled fault-risk assessment, sustainability consequence evaluation, and immersive operator visualisation, while offering a basis for future individual components and hardware-oriented validation.