Applied Technology Review : News

In the apparel industry, platforms provide brands with a different choice; as ecommerce websites fully integrate resale capabilities, the technology platform enables enterprises to access the market. The trendiest section of the global fashion market is secondhand resale. The garment resale market is projected to increase more than three times faster than the primary market over the next five years, from $96 billion in 2021 to $218 billion in 2026, according to the most authoritative assessment of fashion resale, the Thredup Resale Report. Within the secondhand fashion business, internet resale is projected to reach over fifty percent of the market by 2024 and nearly quadruple in size by 2026. Third-party marketplaces, like Poshmark, Vestiaire Collective, eBay, The RealReal, and Thredup, have reaped the majority of the benefits to date. The platforms in the apparel industry offer brand an additional option. Technology platform enables businesses to enter the market with their fully-integrated resale capabilities on their ecommerce websites. In addition to apparel, accessories, and footwear, the service is also available to electronics, outdoor gear, and equipment-branded enterprises. It utilizes to streamline brand integration, improve data analytics capabilities, find methods for businesses to resell unsold inventory and product returns and investigate auctions and other upcycling prospects. The platform should effortlessly and elegantly integrate resale into every commerce experience, enhancing companies' sustainability, customer loyalty, and revenue. The ease of purchasing and listing goods through brand sites will attract many new customers, assist brands in retaining existing customers, and ultimately bring millions of customers to the circular economy. It facilitates peer-to-peer resale, as opposed to buy-back schemes where the brand gets merchandise from sellers, processes, and warehouses and finally distributes it to the next buyer. In the peer-to-peer concept, Poshmark or eBay, the vendor lists and ships their things directly to the buyer. The strategy is the most scalable for a brand with minimal up-front and continuing costs and enables merchants to maximize the value of their product. Authentication is one of the drawbacks of the peer-to-peer approach, and it verifies each listing and gives digital ID verification. The customer support service addresses inquiries and complaints. Peer-to-peer models significantly benefit brands, such as increased customer connection and engagement. Customers urge to visit the brand's website to make a new purchase and refer a friend. It redefines the conventional meaning of the circular economy. In the branded resale model, there are many chances to strengthen the link between the brand and the customer story and establish a community. The platform should be the inevitable progression of the resale market from third-party platforms to brands with an ownership position in the product lifecycle. And it should allow brands to provide customers with additional perks due to their continued connections with them, essentially enhancing brand loyalty. ...Read more

City officials and planners optimize digital twin applications to make effective decisions based on real-time information. Surveillance cameras integrated with specific software can transmit data to digital twin platforms. City data provide digital twin applications with the capability to map city activities like traffic flow, optimal routes, congestion rates, response times, and air quality can influence planning decisions. Digital-twin-enabled smart surveillance is integral to smart city goals, which aim to reduce crime rates, free up roadways, improve sustainable lifestyles, and reduce infrastructural response times. Smart cities can optimize infrastructural efficiency through digital twin applications. Data optimization: Manufacturing and logistic companies rely on digital twin platforms' real-time information to make the best decision. They can effectively view and map assets. Other city planning aspects rely on digital twins. It provides officials with virtual representations based on real-time data collected through the internet of things (IoT). City authorities can access data on air pollution levels, noise levels, weather conditions, and the movement of vehicles, bikes, and pedestrians through certain city areas. Officials can make decisions based on specific traffic movements, behaviors, and events. Planning: Surveillance systems track the daily movements of traffic around the city, while digital twin applications map and trace activities. Vehicle numbers, types, and patterns, such as how many cars, trucks, and bicycles are on the road in certain areas, are some of the information collected in this area. The digital twin platform can enable advanced analytics, such as multidimensional AI, as data is collected from multiple sources. Analyzing different datasets using AI can produce greater insights that can be applied to a macro level. It is possible to review the impact and outcome of an action by going through replicas and models of different scenarios. City officials can anticipate challenges and plan in advance. Surveillance cameras: Sensor data input plays a key role in the strength of digital twin platforms. The software will build accurate virtual representations using this information, which will feed into the models. A network camera with real-time visual feedback is crucial to this process, as it not only provides surveillance but also captures high-quality images that serve as the basis for analytical insights. Due to many network cameras already installed in crucial locations, data collection is enhanced by utilizing the existing install base rather than installing new cameras wherever necessary. ...Read more

Market analysts are hard at forecasting AI's economic impact on the garment sector and manufacturing in general .  The expansion of the human population and its need for clothes is unavoidable, but manufacturers' capacity to satisfy expectations without overextending themselves is not. Like every other business, clothing and textiles must learn to service a rising population while staying mindful of the planet's limited resources. Using artificial intelligence (AI) to fulfill demand without exceeding the available supply is not a novel concept. How does it apply to the garment industry? • Improving material grading The human eye is a magnificent device, yet it has flaws. Grading yarn and many other basic materials are one aspect of clothing production where AI helps quality control (QC). The application of artificial intelligence in this sector leads to cost savings and more exact gradings of the basic materials used in clothing manufacture. In other words, AI can maintain a better and more consistent material standard than humans, increasing the average quality of final clothing. • Reducing errors in final product inspection Machine learning & computer vision have advanced to the point where they can tell whether a piece of fruit has been damaged beneath its skin. Textile and clothing production applications are equally enthralling. Algorithms combined with specialized lighting systems can assess the quality and resale value of newly created and previously used clothing. Measuring the amount of transmitted and reflected light allows AI to determine if the density of a fabric piece or a finished garment matches current quality requirements in a single glance. • Tailor-made for the apparel industry This only touches the surface of what artificial intelligence offers textile and garment manufacturers. Another area where AI is poised to thrive is sustainable and customized manufacturing. Modern imaging technology enables end users to create 3D representations of their bodies, allowing for less expensive and less resource-intensive personalized apparel manufacture. Another technology making headlines in the garment business is generative design. Designers and engineers choose material and performance limits using an AI algorithm, then tell an AI to develop product designs that fulfill those criteria. As a result, there is a greater diversity of feasible designs and a significant decrease in time and material waste. Market analysts are hard at forecasting AI's economic impact on the garment sector and manufacturing in general.   ...Read more