Smart Textile Market buoyed with the sharp rise of business in Europe

Published By: IndustryARC Published On : 19-Feb-2018

Smart Textile Market deals with the development of smart fabric technology. Smart textiles are fabrics that enable digital components and electronics to be embedded in them. These components have the ability to monitor different parameters and transmit this data to other components for further interpretation. Sensors can embed in smart fabrics to monitor temperature, heart beat, blood pressure and some other parameters. Smart textiles are also known as smart clothes or smart garments or smart fabrics or electronic textiles. These are used across various applications such as fashion, military, medical, automotive, sports and fitness.

Increasing demand for smart textile products because of their expanding base of applications in end user industries. Most of the demand for smart textile industry comes from end use industries such as military and defense and healthcare. Both developed and developing countries, will witness the increase in demand with innovative trends. Use of nanotechnology in textiles, integration of smart textiles and wearables, applications in smart-phones are the key growth factors for the Smart Textile Market.

Increasing usage in applications such as military, defense and sports sector are the major factors that drives significant growth for the market. Increasing R & D activities and rising demand in emerging economies such as India and China are creating new growth opportunities for the market of smart textiles. However, high production costs and lack of standards are acting as the key growth restraints for the Smart Textile Market.

North America is leading the Smart Textile Market and is expected to maintain its dominance till the end of the forecast period. Europe is leading with the second position followed by Asia-Pacific. Asia-Pacific is projected to have the fastest growth due to growing demand for smart textiles in emerging economies like India and China, during the forecast period.

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