The old fibers that make up heritage textiles displayed in museums are degraded by the aging process, environmental conditions (microclimates, particulate matter, pollutants, sunlight) and the action of microorganisms. In order to counteract these processes and keep the textile exhibits in good condition for as long as possible, both reactive and preventive interventions on them are necessary. Based on these ideas, the present study aims to test a natural and non-invasive method of cleaning historic textiles, which includes the use of a natural substance with a known antifungal effect (being traditionally used in various rural communities)—lye. The design of the study was aimed at examining a traditional women’s shirt that is aged between 80–100 years, using artificial intelligence techniques for Scanning Electron Microscopy (SEM) imagery analysis and X-ray powder diffraction technique in order to achieve a complex and accurate investigation and monitoring of the object’s realities. The determinations were performed both before and after washing the material with lye. SEM microscopy investigations of the ecologically washed textile specimens showed that the number of microorganism colonies, as well as the amount of dust, decreased. It was also observed that the surface cellulose fibers lost their integrity, eventually being loosened on cellulose fibers of cotton threads. This could better visualize the presence of microfibrils that connect the cellulose fibers in cotton textiles. The results obtained could be of real value both for the restorers, the textile collections of the different museums, and for the researchers in the field of cultural heritage. By applying such a methodology, cotton tests can be effectively cleaned without compromising the integrity of the material.

With the constant availability of new designs at extremely low prices, the production and disposal of clothing have increased significantly, leading to the need for the sustainable management of processes. The implementation of established craft practices in modern sustainable mass production requires the development and application of software and hardware computer tools as well as production machinery. Although the management of textile waste for interior design articles is addressed in the scientific literature by various techniques, there is still limited data and strategies based on the use of specific algorithms. Therefore, in this research, an algorithm is proposed, with the help of which textile waste resulting from upholstery production can be reused in the creation of interior decoration parts. The algorithm is implemented in the GNU Octave 6.4 programming environment, which makes it easily redistributable and accessible. The algorithm consists of a total of six stages, offering an option for arranging the textile elements and analyzing their color characteristics. The arrangement is performed with a Voronoi diagram, and the colors are represented by a four-color circle. Moreover, data on waste textile fabrics are presented, as well as their application in the conception of interior design elements. The proposed algorithm allows designers to focus on the visual design rather than compatibility checks and constraints. The present paper provides an algorithm for reusing textile wastes, which come in a variety of shapes and colors and are produced throughout the fabric cutting phase of upholstery manufacturing, in order to identify the most optimal combinations in matching irregular waste shapes and combinations of colors, create a suitable pattern for new interior design items, and contribute to improving the sustainable management of textile waste that is produced in considerable amounts.

This study focused on the mechanical and morphological properties of lignocellulosic heritage textiles (cotton and hemp) made using eco-friendly salvia and thyme microencapsulated essential oils, characterized by low toxicity for humans and the environment. A morphological evaluation of the tested fabrics was performed using scanning electron microscopy. The ATR–FTIR spectra of the untreated and treated fabric samples were tested using Perkin Elmer, Spectrum 3. A tensile test of the samples was conducted based on the ISO 13934-1 using a MESDAN-Lab tensile strength tester. According to the analysis, the salvia improved the tensile strength of the fabric by 20% and 39% in the warp and weft directions, respectively. The data for the untreated cotton, untreated hemp, and fabrics treated with salvia and thyme were processed using the kernel PCA method. From the principal component analysis it was found that the textile fabrics treated with salvia coalesced close to the untreated ones. This shows that treatment with essential oils from the indicated plant does not significantly affect the tensile properties of textile fabrics. The thymol-treated textile fabrics were significantly distant from those of the control sample. In cotton textile fabrics, thymol treatment was found to have a significant effect on their tensile properties. In hemp fabrics, two types of thymol and salvia treatments were found to have a very significant effect on the tensile strength performance of the textile fabrics. The results obtained can be used in museums, universities, and ethnographic studies that own or maintain collections of heritage textiles.

Air pollution and travel comfort in public transport is a significant problem as it can cause health problems for passengers. There are no sufficiently developed and researched monitoring systems for measuring the quality of the environment in public transport, which makes it difficult to assess the extent of the problem and implement effective solutions. This study presents the results of measurements made with a developed system for assessing air pollution and environmental quality in urban transport. Two time periods were defined based on air pollution and traffic levels, and informational features were selected for bus stops and buses. Noise was found not to be an informative feature, but vehicle acceleration should be considered in environmental quality monitoring. A quadratic discriminant classifier combined with principal components was shown to accurately classify high and low pollution time periods. Further research is planned to investigate the relationship between air pollution and travel discomfort and to develop effective strategies to improve air quality in urban public transport.

Building modern Internet of Things (IoT) systems is associated with a number of challenges. One of the most significant among them is the need for wireless technology, which will serve to build connectivity between the individual components of this technology. In the larger cities of Bulgaria, measures to ensure low levels of harmful emissions, reduce noise levels, and ensure comfort in urban environments have been taken. LoRa technology shows more advantages in transmission distance and low energy consumption compared to other technologies. That is why this technology was chosen for the design of wireless sensor networks (WSN) for six cities in Bulgaria. These networks have the potential to be used in IoT configurations. Appropriate modules and devices for building WSN for cities in Bulgaria have been selected. It has been found that the greater number of nodes in the WSN leads to an increase in the average power consumed in the network. On the other hand, depending on the location of these nodes, the energy consumed may decrease. The performance of wireless sensor networks can be optimized by applying appropriate routing protocols, which are proposed in the available literature. The methodology for energy efficiency analysis of WSN can be used in the design of wireless sensor networks to determine the parameters of the environment, with the possibility of application in IoT.

Applications of 3D printing in the fashion industry have continued to attract interest from academia and industry in order to improve and add functionalities to products. Among these applications, an interesting one is 3D printing on textile fabric. Composite structures created by 3D printing and textile fabric change a drape by improving or worsening its appearance. The scope of this work is to evaluate the effect of various 3D printed geometries on textile fabric regarding fabric drapes. The drape coefficient of the created composite structure is evaluated using a drape tester built according to EN ISO 9073-9. The results taken are compared with an algorithm developed for determining drape parameters and 3D form representation using color digital images and their image histograms. The measured values of the drape coefficient are close, with a minimal difference, up to 4%. The 3D printed patterns show a significant effect on the drape coefficient of textile fabrics by depicting another way to modify fabric drapes and create complex shapes by using less material. This can be seen as an advantage in the fashion industry where complex geometries can be added to textile fabrics, while changing fabric drape and product personalization and adding functionalities for garments and technical textiles.