The 𝐀𝐮𝐭𝐨𝐦𝐚𝐭𝐢𝐜 𝐈𝐝𝐞𝐧𝐭𝐢𝐟𝐢𝐜𝐚𝐭𝐢𝐨𝐧 𝐚𝐧𝐝 𝐃𝐚𝐭𝐚 𝐂𝐚𝐩𝐭𝐮𝐫𝐞 𝐌𝐚𝐫𝐤𝐞𝐭 report provides a detailed analysis of changing market dynamics, top segments, value chain, key investment pockets, regional scenario, and competitive landscape. Rise in adoption of AIDC solutions drives the growth of the global automatic identification and data capture market. However, high costs associated with installation of automatic identification and data capture system paired with the rise in concerns about malware attacks and security breaches restrain the market to some extent. On the other hand, surge in government regulations for the adoption of AIDC solutions forecasts presents new opportunities in the upcoming years. The global automatic identification and data capture market size was valued at $37,189 million in 2020, and is projected to reach $121,072 million by 2030, registering a CAGR of 12.5% from 2021 to 2030.
𝐃𝐨𝐰𝐧𝐥𝐨𝐚𝐝 𝐒𝐚𝐦𝐩𝐥𝐞 𝐑𝐞𝐩𝐨𝐫𝐭 (𝐆𝐞𝐭 𝐅𝐮𝐥𝐥 𝐈𝐧𝐬𝐢𝐠𝐡𝐭𝐬 𝐢𝐧 𝐏𝐃𝐅 – 300 𝐏𝐚𝐠𝐞𝐬) 𝐚𝐭: https://www.alliedmarketresearch.com/request-sample/A13147
Automatic identification and data capture is an innovative technology that automatically identifies the asset, collects the related information, and directly store the data into the computer system. Further, the information stored by automatic identification and data capture in the form of video, image, and biometric is known as identification data. However, the high risk of cybersecurity is impacting the growth of automatic identification and data capture system across government and private sectors. In addition, automatic identification and data capture convert the object data into a digital file by using a transducer before storing the data into the computer system. Moreover, rise in e-commerce industry is expected to offer significant growth opportunities for the market in the coming years.
Based on offering, the hardware segment held the highest market share in 2020, holding nearly three-fifths of the total market share, and is expected to continue its leadership status during the forecast period. However, the service segment is estimated to register the highest CAGR of 15.2% from 2021 to 2030.
𝐁𝐮𝐲 𝐍𝐨𝐰 & 𝐆𝐞𝐭 𝐄𝐱𝐜𝐥𝐮𝐬𝐢𝐯𝐞 𝐃𝐢𝐬𝐜𝐨𝐮𝐧𝐭 𝐨𝐧 𝐭𝐡𝐢𝐬 𝐑𝐞𝐩𝐨𝐫𝐭 : https://www.alliedmarketresearch.com/automatic-identification-and-data-capture-market/purchase-options
Surge in the e-commerce industry paired with rise in utilization of smartphones based QR codes and image recognition technology is driving the market growth. However, high cost associated with the automatic identification and data capture coupled with the high risk of concerns of malware attacks and security breaches is anticipated to restrain the automatic identification and data capture market share. Further, surge in adoption of AIDC solutions to address human error coupled with government regulations for the adoption of AIDC solutions is expected to drive the need for automatic identification and data capture during the forecast period.
𝐓𝐡𝐞 𝐤𝐞𝐲 𝐩𝐥𝐚𝐲𝐞𝐫𝐬 𝐩𝐫𝐨𝐟𝐢𝐥𝐞𝐝 𝐢𝐧 𝐭𝐡𝐢𝐬 𝐫𝐞𝐩𝐨𝐫𝐭 𝐢𝐧𝐜𝐥𝐮𝐝𝐞
Leading players of the global automatic identification and data capture market analyzed in the research include Cognex Corporation, Datalogic S.p.A., Honeywell, NXP Semiconductors N.V., Panasonic Corporation, SICK AG, Synaptics Incorporated, Thales, Toshiba, and Zebra Technologies.
𝐆𝐞𝐭 𝐂𝐮𝐬𝐭𝐨𝐦𝐢𝐳𝐞𝐝 𝐑𝐞𝐩𝐨𝐫𝐭𝐬 𝐰𝐢𝐭𝐡 𝐲𝐨𝐮’𝐫𝐞 𝐑𝐞𝐪𝐮𝐢𝐫𝐞𝐦𝐞𝐧𝐭𝐬: https://www.alliedmarketresearch.com/request-for-customization/A13147
Based on technology, the radio frequency identification segment held the largest market share in 2020, holding more than one-third of the total market share, and is expected to continue its leadership status during the forecast period. However, the smart cards segment is projected to register the highest CAGR of 16.2% from 2021 to 2030.
According to technology, the radio frequency identification (RFID) segment was the highest contributor to the market in 2020. Rise in automation across healthcare and government sector is driving the automatic identification and data capture growth during the forecast period.
𝐈𝐧𝐪𝐮𝐢𝐫𝐲 𝐁𝐞𝐟𝐨𝐫𝐞 𝐁𝐮𝐲𝐢𝐧𝐠: https://www.alliedmarketresearch.com/purchase-enquiry/A13147
The report offers detailed segmentation of the global automatic identification and data capture market based on offering, product, technology, industry vertical, and region.
𝐑𝐞𝐠𝐢𝐨𝐧𝐚𝐥 𝐀𝐧𝐚𝐥𝐲𝐬𝐢𝐬:
Based on region, North America contributed to the highest share in terms of revenue in 2020, holding one-third of the global automatic identification and data capture market share, and is estimated to continue its dominant share by 2030. However, Asia-Pacific is projected to manifest the fastest CAGR of 14.10% during the forecast period.
𝐂𝐨𝐧𝐭𝐚𝐜𝐭:
David Correa
5933 NE Win Sivers Drive
#205, Portland, OR 97220
United States
Toll-Free: 1-800-792-5285
UK: +44-845-528-1300
Hong Kong: +852-301-84916
India (Pune): +91-20-66346060
Fax: +1-855-550-5975
help@alliedmarketresearch.com
Web: https://www.alliedmarketresearch.com
Follow Us on: LinkedIn Twitter
𝐀𝐛𝐨𝐮𝐭 𝐔𝐬
Allied Market Research (AMR) is a full-service market research and business-consulting wing of Allied Analytics LLP based in Portland, Oregon. Allied Market Research provides global enterprises as well as medium and small businesses with unmatched quality of “Market Research Reports” and “Business Intelligence Solutions.” AMR has a targeted view to provide business insights and consulting to assist its clients to make strategic business decisions and achieve sustainable growth in their respective market domain.
Pawan Kumar, the CEO of Allied Market Research, is leading the organization toward providing high-quality data and insights. We are in professional corporate relations with various companies and this helps us in digging out market data that helps us generate accurate research data tables and confirms utmost accuracy in our market forecasting. Each and every data presented in the reports published by us is extracted through primary interviews with top officials from leading companies of domain concerned. Our secondary data procurement methodology includes deep online and offline research and discussion with knowledgeable professionals and analysts in the industry.
This release was published on openPR.