Blockchain-Based Secure and Robust Mechanism for Collaborative Manufacturing in Industry 4.0

This systematic review provides a comprehensive analysis of the advancements, challenges, and future directions of smart HVAC systems by examining 125 peer-reviewed articles following the PRISMA methodology. The study focuses on five critical areas: IoT-enabled HVAC systems, machine learning algorithms for predictive maintenance, renewable energy integration, data privacy and security concerns, and the economic feasibility of implementation. The findings highlight that IoT-enabled HVAC systems significantly enhance energy efficiency by leveraging real-time data from interconnected sensors, leading to energy savings between 20% and 40% through adaptive heating, cooling, and ventilation strategies. Additionally, machine learning algorithms in predictive maintenance play a crucial role in reducing system failures, cutting unscheduled maintenance costs by up to 40%, and improving energy efficiency by 15% to 25% through automated fault detection and optimized maintenance scheduling. Furthermore, renewable energy integration in HVAC systems, particularly hybrid solutions combining solar, geothermal, and wind energy, has demonstrated remarkable potential, with some systems achieving energy savings of up to 60%. However, challenges such as high upfront installation costs, the need for advanced energy storage solutions, and infrastructure limitations continue to hinder widespread adoption. The review also identifies data privacy and security vulnerabilities as a major concern in IoT and AI-powered HVAC systems. 20 reviewed articles highlight risks associated with data transmission, unauthorized access, and cyber threats, emphasizing the need for robust encryption techniques, blockchain-based security, and AI-driven authentication mechanisms to enhance protection and user trust. Moreover, the economic feasibility of smart HVAC solutions remains a key factor influencing adoption. While these systems require higher initial investments, findings from 15 reviewed studies indicate that the return on investment (ROI) typically falls within five to seven years, particularly for large-scale commercial applications where energy cost savings and predictive maintenance benefits accumulate more rapidly. Policy incentives, tax rebates, and government subsidies have also been recognized as crucial enablers for accelerating adoption, making smart HVAC technologies more accessible for residential and small business users. This review synthesizes existing knowledge, evaluates emerging trends, and identifies persistent barriers in smart HVAC technologies. The findings provide valuable insights for researchers, industry stakeholders, and policymakers to develop scalable, cost-effective, and energy-efficient HVAC solutions. Future research should focus on enhancing system interoperability, improving data security frameworks, and developing innovative financing models to facilitate the transition toward more sustainable and intelligent HVAC solutions in the built environment.

VABLOCK: A blockchain-based secure communication in V2V network using icn network support technology

The VANET has seen a boom in the distribution of significant source data,enabling connected vehicle communications to enhance roadway safety.Despite the potential for interesting applications invehicle networks,thereare still unresolved issues that have the potential to hinder bandwidth utilization once deployed. Specifically, insider assaults on VANET platforms such as Blackhole attemptscan completely stop vehicle-to-vehicle communications and impair the networks' performance level. In this study, we provide the blockchain-based decentralized trust scoring architecture for the participants in the network to identify existing and blacklisted insider adversaries in VANET. To address this concern, we suggest a two-level detection technique, in the first level neighboring nodes determine theirtrustworthiness and in the second level it aggregates trust scores for vehicle nodes using a consortium blockchain-based mechanism that uses authorized Road Side Units (RSUs) as consensus mechanism. The blacklisted node records are then periodically changed based on the trust scores supplied by the nearby nodes. In regards to the practical scope of the network, the experimental study demonstrates that the suggested solution is effective and sustainable. To improve packet delivery ratio and vehicle node security in the VANET, the blockchain-based Trust-LEACH routing technique has also been created. The performance analysis has been carried out for Computational cost analysis, Computational time for block creation, Network analysis, SecurityAnalysis, and MITM attack analysis. Additionally, we provide proof that the suggested approach enhances VANET reliability by thwarting and removing insider threat initiation nodes from its blacklist.

We will describe combining the concepts of Open Innovation (OI) and pre-competitive consortia to address industry specific issues. We will examine several pertinent topics such as finding alternatives to non-biodegradable packaging, finding alternative toner resins, or developing more environmentally friendly processes important to toner-based imaging.Regulating bodies at the federal, state and local level are continually expanding the list of harmful materials in products. This trend will likely continue and increase the focus on the electrophotographic printing industry.Open Innovation (OI) is an effective method for seeking expertise to solve technical challenges. Industry leaders, such as Nestle, 3M, GE, Goodyear, Xerox, and BP are successful leading practitioners of OI. We invite the toner-based imaging companies to join other corporations and NineSigma to benefit from the discovery of multiple industry-wide alternatives.Join your competitors, suppliers and customers in pre-competitive collaboration of multiple users and manufacturers in industry to use Open Innovation to seek alternatives to materials and processes subject to imminent regulation. Such collaborative use of Open Innovation can result in faster, more economical discovery of suitable alternatives that will benefit your company's stature, the industry, its customers, and the environment.

This paper reports on the experiences and lessons learned from the implementation of a Product Lifecycle Management (PLM) tool at MTU Aero Engines that addresses the increasing demand for richer and faster communication in product development and manufacturing both within one company and between different worldwide partners and locations in the aerospace industry. The requirements for the tool are outlined, the implementation approach is presented and the experiences and lessons learned are discussed from the collaborative engineering and manufacturing standpoints.

In the field of production automation, IO-Link Wireless (IOLW) offers energy-efficient and cost-effective solutions for networking wireless sensors and actuators close to the machines on the industrial shop-floor. In this paper, a concept is presented to enhance IOLW with security-for-safety and safety features in order to make safety critical systems in industrial environments with performance characteristics dedicated to demanding applications feasible. As data security is of paramount importance, security mechanisms already implemented in other wireless protocols are investigated and security-for-safety mechanisms for IOLW are introduced. Potential cryptographic algorithms are evaluated for IOLW with respect to energy consumption and timing. Taking performance parameters into account, which are crucial for industrial manufacturing processes, a safety protocol data unit (SPDU) is described and evaluated for different payload length and cycle times. Finally, an outlook towards the implementation of a demonstrator setup completes this work.

Autonomic provisioning of hosted applications in Enterprise Data Centers must be investigated as more and more business applications are executed in such an environment. In this scenario, the multiplicity and variability of software components and data to be dynamically deployed, interconnected and adjusted leads to more complex system management. In parallel, all customer requirements and constraints must be fulfilled. These requirements and constraints are specified in corresponding Service Level Agreements (SLA). Security aspects are one important part of such agreements, as in a shared, open infrastructure, perceived risks with respect to loss of information confidentiality, integrity and availability increase. Legislation and compensation mechanisms make it imperative for the Data Center to acknowledge these perceived risks. Therefore, robust application isolation mechanisms must be considered. However, potential drawbacks due to the used security mechanisms that might influence the overall system performance must be considered. In order to initialize an autonomic provisioning process, a concept for configuring the Data Center based on different Levels of Isolation is presented. Customers and Data Center providers can agree on the isolation guarantees they expect given their individual preferences specification between the perceived risks and the resulting costs associated with the chosen Level of Isolation.

Applications in Vehicular Networks : With the increase of Internet of Things (IoT) devices applications area, widespread deployment of and new markets for a variety of connected devices, robust security mechanisms are required to mitigate escalating cyber-attack scenarios. This is a brief summary of the full research paper on IoT secure techniques. The peculiar characteristic of IoT that connects everything with others everywhere, introduces many issues originated from the heterogeneous devices, different communication protocols and constrained deployment environment. This paper examines the current IoT security scenario and focuses on the highly crucial issue of ensuring data integrity. the current paper outlines a list of the security control tools that are used as elements of hardening IoT implementations with the purposes of malicious attack, unauthorized access, and data breaches. These types of security measures as the device authentication and secure communications protocols and encrypting algorithms are studied in detail depending on where they are used and their effectiveness in various IoT environments. Considering the evolution of IoT at present, we consider the state-of-the-art of secure mechanisms and security methods on a theoretical and practical basis. Based on an in-depth analysis of the issue of the looming cyber threats, the article is a part of the current discussion of strengthening the security stance of IoT systems.

The demand for cloud computing is increasing rapidly because of the advantages it provides to the customers like, pay as you use, self-serving, elastic, sharing of resources, ease of use, and accessibility. Due to the increase in the usage of the technology, there exists a high chance of compromising the security of the data being stored on the cloud. The major hindrance in the usage of the technology is the security concerns which accompany it. This increases the demand for a robust security mechanism to protect the data on the cloud. So as to overcome this drawback of cloud computing, encrypting the data to be stored on the cloud is one of the solutions. As part of this paper, a security mechanism to improve the security of data in cloud storage is suggested. The security mechanism used is inspired by the bio-inspired genetic algorithm. The inspiration behind the proposed security model is an amalgamation of genetic algorithm and attribute based encryption. As per the methodology proposed the data need to be encrypted before being stored on the cloud. This way the cloud service provider is unaware of the data being stored and even if the data is compromised to some third party, there is no information leakage.

Electronic voting systems have been increasingly adopted to improve the efficiency and accessibility of modern elections. However, traditional electronic voting platforms often suffer from several limitations, including security vulnerabilities, lack of transparency, centralized control, and potential risks of vote tampering. These challenges can undermine public trust in electoral processes and highlight the need for more secure and transparent voting mechanisms. Recent advancements in Block chain Technology provide a promising solution for addressing these issues by enabling decentralized, tamper-resistant, and verifiable systems. This study proposes a blockchain-based secure electronic voting framework designed to ensure data integrity, voter privacy, and transparent vote counting. The proposed system utilizes a distributed ledger to record votes as immutable transactions, making it nearly impossible for unauthorized parties to alter or manipulate the stored data. Each vote is encrypted using modern Cryptography techniques before being added to the block chain network, ensuring voter anonymity while maintaining the authenticity of the election process. In addition, smart contracts automate the voting procedures, including voter authentication, vote casting, and result tabulation, thereby reducing human intervention and potential errors. The system architecture integrates a voter registration module, authentication mechanism, block chain network, and secure voting interface. Through the use of decentralized consensus mechanisms, the proposed approach eliminates reliance on a central authority and enables transparent verification of election results by authorized participants. Performance evaluation of the system demonstrates improved security, reliability, and transparency compared with conventional Electronic Voting approaches. Furthermore, the system provides an auditable and tamper-proof record of all voting transactions, ensuring accountability throughout the electoral process.

The relevance of the research is caused by the need to form a high-quality concept of a system for management and forecasting of the socio-economic development of the sectoral and inter-sectoral complex of a region. The subject of the research is the methods for forecasting the economic security under conditions of uncertainty. The purpose of the research was to consider and evaluate a model of dynamic integration of economic security for a regional inter-sectoral complex under uncertainty conditions based on the institutional approach principles. The paper analyzes the vectors of structural changes in the regional inter-sectoral complex that includes the mining, manufacturing and construction industries. A methodology for predicting the impact of the digital economy on the economic security of the regional inter-sectoral complex is considered. A new model of forecasting the economic security of the above-mentioned complex was built to be used as a tool for regulating the socio-economic development at the regional level. A set of key conditions for the development of an institutional mechanism to ensure the economic security of the region in terms of its sustainable operation and withstanding internal and external threats and risks were formed. In turn, the institutional concept of the economic security mechanism involves constant selection, analysis and evaluation of judgments about the economic security of a region, country or economic entity. This task is achieved by comparing the numerous characteristics of economic activity. The paper concludes that the proposed method of forecasting using econometric models makes it possible to assess the economic security of a regional inter-sectoral complex and timely respond to negative performance indicators.

Currently, virtual/remotes laboratories are often being built to improve learning and researching capabilities in some areas of knowledge. Generally these virtual/remotes laboratories are built from scratch again and again, instead of reusing software and hardware infrastructures. This paper presents a new framework, RVLab, to help developers building flexible and robust server-side virtual and remotes laboratories quickly. RVLab affords support for the basic requirements of these systems such as the user management or the resources (instruments and devices) reservation. Unlike other lab systems, RVLab is adapted to devices and instruments of any real laboratory due to a secure and robust mechanism that allows the remote execution of lab programs. Moreover, it improves the user interaction with real labs, providing a real-time visualization of experiments and lab instruments by means of the control of video camera placed into lab, and the transmission of video streaming with different quality to users.

AR-assisted digital twin-enabled robot collaborative manufacturing system with human-in-the-loop

Introduction: The attacks on IoT systems are increasing as the devices and communication networks are progressively integrated. If no attacks are found in IoT for a long time, it will affect the availability of services that can result in data leaks and can create a significant impact on the associated costs and quality of services. Therefore, the attacks and security vulnerability in the IoT ecosystem must be detected to provide robust security and defensive mechanisms for real-time applications. Method: This paper proposes an analytical design of an intelligent attack detection framework using multiple machine learning techniques to provide cost-effective and efficient security analysis services in the IoT ecosystem. Result: The performance validation of the proposed framework is carried out by multiple performance indicators. Conclusion: The simulation outcome exhibits the effectiveness of the proposed system in terms of accuracy and F1-score for the detection of various types of attacking scenarios.

As the number of European Union (EU) visitors grows, implementing novel border control solutions, such as mobile devices for passenger identification for land and sea border control, becomes paramount to ensure the convenience and safety of passengers and officers. However, these devices, handling sensitive personal data, become attractive targets for malicious actors seeking to misuse or steal such data. Therefore, to increase the level of security of such devices without interrupting border control activities, robust user authentication mechanisms are essential. Toward this direction, we propose a risk-based adaptive user authentication mechanism for mobile passenger identification devices for land and sea border control, aiming to enhance device security without hindering usability. In this work, we present a comprehensive assessment of novelty and outlier detection algorithms and discern OneClassSVM, Local Outlier Factor (LOF), and Bayesian_GaussianMixtureModel (B_GMM) novelty detection algorithms as the most effective ones for risk estimation in the proposed mechanism. Furthermore, in this work, we develop the proposed risk-based adaptive user authentication mechanism as an application on a Raspberry Pi 4 Model B device (i.e., playing the role of the mobile device for passenger identification), where we evaluate the detection performance of the three best performing novelty detection algorithms (i.e., OneClassSVM, LOF, and B_GMM), with B_GMM surpassing the others in performance when deployed on the Raspberry Pi 4 device. Finally, we evaluate the risk estimation overhead of the proposed mechanism when the best performing B_GMM novelty detection algorithm is used for risk estimation, indicating efficient operation with minimal additional latency.