While introducing new technology has completely transformed the textile production process, the rapid pace of massive industrialization has increased the volume of wastewater, which is highly hazardous. Even though the textile industry is essential to our economy, the textile industry is harmful to the environment because of the production of wastewater, solid wastes, air pollutants, noise, etc. Recycling textile wastewater is crucial, and oxidation, physical, biological, and physicochemical methods can be used to treat textile wastewater. Based on statistics and visualization tools, bibliometric analysis has evolved to demonstrate a given topic’s knowledge structures and developmental tendencies. Here we provide a bibliometric analysis focused on textile wastewater treatment from 1990 to 2022. Raw data was retrieved from the Web of Science (WoS) database and mapped using VOSviewer and biblioshiny. Textile, wastewater, and treatment were keywords. We retrieved 8,170 documents, 1,138 sources published these documents, a 22.7% annual increase, where 21458 authors published these documents with an average citation rate of 33.2%, and there were 6,680 research articles and 462 review articles. DESALINATION AND WATER TREATMENT stayed on top with 422 publications. We discovered that DONGHUA UNIVERSITY ranks first with 330 publications. Though China took first place with a total of 43961 citations, followed by India with a total of 33953 citations, from a total of 120 countries participating in this research, the research work of CRINI G and coworkers was most cited globally. The most common term was wastewater, which occurred 3,144 times, followed by textile, which appeared 2,669 times. We expect this research to be a significant resource for scholars by comprehensively describing the current state and future directions of textile wastewater treatment.

Generally, comprehensive documents are needed to provide the research community with relevant details of any research direction. This study conducted the first descriptive bibliometric analysis to examine the most influential journals, institutions, and countries in the field of artificial intelligence in textiles. Furthermore, bibliometric mapping analysis was also used to examine diverse research topics of artificial intelligence in textiles. VOSviewer was used to process 996 articles retrieved from Web of Science—Core Collection from 2007 to 2020. The results show that China and the United States have the largest number of publications, while Donghua University and Jiangnan University have the highest output. These three themes have also appeared in textile artificial intelligence publications and played a significant role in the textile structure, textile inspection, and textile clothing production. The authors believe that this research will unfold new research domains for researchers in computer science, electronics, material science, imaging science, and optics and will benefit academic and industrial circles.

Scientists worldwide are always interested in making new discoveries; thus, the scientific literature has been growing exponentially. Keeping abreast of the body of literature at a rapidly advancing pace poses significant challenges to active researchers and society. Although numerous data resources have been made openly available, effectively navigating the vast amount of information with heightened levels of uncertainty remains a significant bottleneck. Here, we searched and analyzed the literature regarding antibacterial treatments in the textile industry. The Web of Science, the most extensive database for scientific literature, was targeted to extract the data. We extracted the raw data from the Web of Science Core Collection. The documents were published from 1998 to 2022, from a total of 878 sources. A total of 3625 documents were found, 2898 of which were articles. A total of 11,192 authors contributed to the topic during this period. We used the Bibliometrix sub-tool Biblioshiny and extracted the basic information about the documents. With an annual growth rate of 26.27%, there was a boost in the literature during the period under study.