1. This study explores the different studies that implemented digital technologies such as IoT, AI, blockchain, AR, and VR in the fashion industry for smart cloth (health), supply chain, circular economy, dress recommendation system, fashion trend forecasting, health prediction, and virtual and augmented based shopping experience.
2. The study also discussed limitations of these technologies in the fashion industry and provided recommendations such as wide adoption of blockchain in fashion supply chain; advancement in energy storage for smart cloth; integration of IoT, AI, and edge computing; and smart clothing-based framework for rescue operation for future enhancement.
3. The article used a methodology to obtain articles from Web of Science (WoS), Scopus, and IEEE Xplore to conduct the analysis regarding the progress and significance of digitalization in the fashion industry.
The article provides an overview of how digitalized technologies can be implemented in the fashion industry to promote sustainable consumption and production patterns. The article is well-structured with clear sections discussing each technology separately. It also provides a detailed discussion on limitations of these technologies in the fashion industry along with recommendations for future work.
The article is reliable as it uses credible sources such as Web of Science (WoS), Scopus, and IEEE Xplore to obtain articles for conducting its analysis. Furthermore, it cites relevant research papers to support its claims throughout the article.
However, there are some potential biases present in the article which could affect its trustworthiness. For instance, it does not provide any counterarguments or explore any possible risks associated with implementing digitalized technologies in the fashion industry which could lead to one-sided reporting or partiality towards certain points made by the author. Additionally, some claims made by the author are unsupported or lack evidence which could make them unreliable or untrustworthy.
In conclusion, while this article is generally reliable due to its use of credible sources and citations throughout its text, there are some potential biases present which could affect its trustworthiness such as one-sided reporting or partiality towards certain points made by the author as well as unsupported claims or lack of evidence for certain statements made by him/her.