The rapid expansion of the Internet of Things (IoT) on a global scale has facilitated the convergence of revolutionary technologies such as artificial intelligence (AI), blockchain, and cloud computing. The integration of these technologies has paved the way for the development of intricate infrastructures, such as smart homes, smart cities, and smart industries, that are capable of delivering advanced solutions and enhancing human living standards. Nevertheless, IoT devices, while providing effective connectivity and convenience, often rely on traditional network interfaces that can be vulnerable to exploitation by adversaries. If not properly secured and updated, these legacy communication protocols and interfaces can expose potential vulnerabilities that attackers may exploit to gain unauthorized access, disrupt operations, or compromise sensitive data. To overcome the security challenges associated with smart home systems, we have devised a robust framework that leverages the capabilities of both AI and blockchain technology. The proposed framework employs a standard dataset for smart home systems, from which we first eliminated the anomalies using an isolation forest (IF) algorithm using random partitioning, path length, anomaly score calculation, and thresholding stages. Next, the dataset is utilized for training classification algorithms, such as K-nearest neighbors (KNN), support vector machine (SVM), linear discriminate analysis (LDA), and quadratic discriminant analysis (QDA) to classify the attack and non-attack data of the smart home system. Further, an interplanetary file system (IPFS) is utilized to store classified data (non-attack data) from classification algorithms to confront data-manipulation attacks. The IPFS acts as an onsite storage system, securely storing non-attack data, and its computed hash is forwarded to the blockchain’s immutable ledger. We evaluated the proposed framework with different performance parameters. These include training accuracy (99.53%) by the KNN classification algorithm and 99.27% by IF for anomaly detection. Further, we used the validation curve, lift curve, execution cost of blockchain transactions, and scalability (86.23%) to showcase the effectiveness of the proposed framework.

The most well-known and used evaluation system to determine the life cycle of a product, is the life cycle assessment (LCA). In Europe, the use of the life cycle assessment (LCA) to assess the environmental performance of products is becoming commonplace, which is why substantial efforts have been made in the last two decades to develop new life cycle assessment (LCA) methodologies and software. This paper evaluates the life cycle assessment (LCA) for the rehabilitation of a national road sector in Romania. The biggest ecological problem facing mankind is the effect of global warming and climate change associated with this phenomenon, due to the increase of the concentration of pollutants to the atmosphere, and this paper presents the results of the life cycle assessment (LCA) based on a cradle-to-gate approach. For this case study, were used three rehabilitation alternatives. These alternatives and the existing pavement structure were analysed using the GaBi software, Ganzheitlichen Bilanzierung (German for holistic balancing), to assess the environmental impact of global warming, the stratospheric impact of ozone, and the impact on human health. The results obtained in this study illustrate the importance of a life cycle assessment approach for evaluating the sustainability for different designs and for the construction of road rehabilitation options.

Human interference with the Earth’s climate cannot be ignored any longer. Renewable energy sources need utmost attention in all energy sectors. For buildings, geothermal energy for heating, cooling, and domestic hot water is a sustainable solution. Horizontal ground heat exchangers (HGHE) demonstrate promising results with low installation costs. Research is focused on increasing their thermal performances by structural improvements and ground thermal proprieties improvements, with little research on using auxiliary heat to increase their performances. A numerical model for an HGHE was established to investigate the effects of auxiliary heat sources on the performances of the HGHE. The results demonstrate that heat transfer into the HGHE increases the overall ground temperature at the end of the heating season by 138.50% compared with no heat transfer from auxiliary heat sources. The ground freezing period decreased by approximately 24.74% by having a heated basement, approximately 40.20% by transferring heat with solar thermal panels, and approximately 62.88% by using both auxiliary heat sources. The difference between the undisturbed ground temperature and the ground temperature with no auxiliary heat sources at the end of the season was 3.45 °C. The difference between the undisturbed ground temperature and the ground temperature with all auxiliary heat sources resulted in 0.92 °C.

Due to the intensive process of road construction or rehabilitation of pavement caused by an increase in traffic volume, in the field of rigid pavement design and research in Romania, we can say that there is a need to improve the design method. In the last decade, more and more researchers have been concerned about climate change and the increase in traffic volume; hence, there is a need for a renewal of the climatological, as well as traffic, databases because these are part of the input data for the design process. The design method currently used in Romania for jointed plain concrete pavement design is NP081/2002. The limitation of the data and the lack of lifetime estimation of structural and functional performance are the main aspects that need to be addressed in the new design procedure. The Mechanistic–Empirical Pavement Design (MEPDG) method offers the possibility of the design of pavement structures by estimating the structural and functional performances. This paper aims to obtain a comparative study of these two methods for the analysis of the input data collected from the field corresponding to the three failure criteria, while the symmetry of the characteristics of the material and their asymmetrical thicknesses are compared, thus contributing to the design of viable and long-lasting pavement structures using a rigid pavement with the specific characteristics of the mountainous area in northeastern Romania on the national road DN17 Suceava—Vatra Dornei. The novelty of this study consists of the implementation of the mechanistic–empirical method MEPDG instead of the old NP081/2002 method used in Romania.

Rapid urbanization and the widespread use of impervious materials have intensified the urban heat island (UHI) effect, raising surface temperatures and energy demands. Conventional concrete pavements contribute significantly due to their high thermal conductivity and low reflectivity. This study systematically investigates the development of thermally efficient concrete paver blocks using sustainable alternative fine aggregates to mitigate heat accumulation while retaining a minimum compressive strength of 35–45 MPa (recommended for medium traffic). Unlike prior isolated studies, this research offers a comprehensive comparative analysis of three sand replacements—Vermiculite powder (12.5–50%), Perlite powder (20–80%), and Crushed Glass (7.5–30%)—in M30-grade concrete. Fresh and hardened properties were evaluated through slump, density, and compressive strength tests at 7, 14, and 28 days, while infrared thermography quantified surface temperature variations under controlled heat exposure. Results showed significant thermal improvements, with optimal mixes Vermiculite 25% (VC-25), Perlite 40% (PR-40), and Crushed Glass 15% (CG-15) reducing surface temperatures by 25.1 °C, 22.2 °C, and 18.2 °C, respectively, while maintaining compressive strengths of 47.8 MPa, 38.8 MPa, and ~58 MPa. VC-25 proved superior, achieving the lowest surface temperature (26.3 °C) and 48.8% lower heat absorption than conventional concrete. The study establishes optimal replacement thresholds balancing insulation and strength, supporting SDGs 11, 12, and 13 through climate-responsive, resource-efficient construction materials.