This web map visualizes the prevalence of households in a given geography that do not own a computer, smartphone, or tablet. Data are shown by tract, county, and state boundaries -- zoom out to see data visualized for larger geographies. The map also displays the boundary lines for the jurisdiction of Rochester, NY (visible when viewing the tract level data), as this map was created for a Rochester audience.This web map draws from an Esri Demographics service that is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2014-2018ACS Table(s): B28001, B28002 (Not all lines of ACS table B28002 are available in this feature layer)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 19, 2019National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.
This map shows the population in households where a smartphone is the only computing device the household owns. Map is multi-scale, containing data for states, counties, and tracts. Pop-ups display total households that own a smartphone, households that own a smartphone and no other computing device, households that have a cellular data plan for internet, and households that have a cellular data plan and no other type of internet subscription. Cellular data plans might be cheaper and more accessible than a Broadband data plan, however cellular internet is less likely to be able to sustain remote learning, work from home, and telehealth.Data come from Census Bureau's American Community Survey Summary Tables: B28001 (used for symbology & pop-up) & B28002 (used for pop-up only). This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.
North America registered the highest mobile data consumption per connection in 2023, with the average connection consuming 29 gigabytes per month. This figure is set to triple by 2030, driven by the adoption of data intensive activities such as 4K streaming.
This layer shows computer ownership and type of internet subscription. This is shown by county boundaries. This service is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. There are also additional calculated attributes related to this topic, which can be mapped or used within analysis. This layer is symbolized to show the percentage of households that have no computer, smartphone, or tablet.
The global number of smartphone users in was forecast to continuously increase between 2024 and 2029 by in total 1.8 billion users (+42.62 percent). After the ninth consecutive increasing year, the smartphone user base is estimated to reach 6.1 billion users and therefore a new peak in 2029. Notably, the number of smartphone users of was continuously increasing over the past years.Smartphone users here are limited to internet users of any age using a smartphone. The shown figures have been derived from survey data that has been processed to estimate missing demographics.The shown data are an excerpt of Statista's Key Market Indicators (KMI). The KMI are a collection of primary and secondary indicators on the macro-economic, demographic and technological environment in up to 150 countries and regions worldwide. All indicators are sourced from international and national statistical offices, trade associations and the trade press and they are processed to generate comparable data sets (see supplementary notes under details for more information).Find more key insights for the number of smartphone users in countries like Australia & Oceania and Asia.
This map shows the population in households where a smartphone is the only computing device the household owns. Map is multi-scale, containing data for states, counties, and tracts. Pop-ups display total households that own a smartphone, households that own a smartphone and no other computing device, households that have a cellular data plan for internet, and households that have a cellular data plan and no other type of internet subscription. Cellular data plans might be cheaper and more accessible than a Broadband data plan, however it is less likely to be able to sustain remote learning, work from home, and telehealth.Data come from Census Bureau's American Community Survey Summary Tables: B28001 (used for symbology & pop-up) & B28002 (used for pop-up only). This map uses these hosted feature layers containing the most recent American Community Survey data. These layers are part of the ArcGIS Living Atlas, and are updated every year when the American Community Survey releases new estimates, so values in the map always reflect the newest data available.
Smartphone Market Size 2025-2029
The smartphone market size is forecast to increase by USD 99.8 million, at a CAGR of 4.1% between 2024 and 2029.
The market is experiencing significant growth, driven by several key trends. One major factor is the increasing adoption of artificial intelligence (AI) in smartphones, enhancing user experience through features like voice recognition and facial recognition. Sensor fusion technology is another trend, enabling devices to collect and analyze data from various sensors for improved functionality and accuracy. However, ongoing trade wars are posing challenges to market growth, with tariffs and import taxes affecting smartphone sales, particularly in key markets. These trends and challenges are shaping the future of the smartphone industry.
What will be the Size of the Smartphone Market During the Forecast Period?
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The market continues to evolve, driven by advancements in telecom infrastructure and the proliferation of affordable handsets. Mobile phone users increasingly seek devices capable of leveraging 5G network technologies, with chipmakers responding by producing 5G chips for integration into mobile handsets. Android and Windows Phone operating systems dominate the market, while third-party originators challenge the status quo. Improved hardware and software capabilities enable advanced digital functions such as web browsing, music, video, gaming, and camera capability. The integration of artificial intelligence enhances user experience. Governmental assistance and the transition from feature phones to smartphones further fuel market growth. Overall, the market remains dynamic, with a focus on affordable, high-performance devices that cater to the diverse needs of consumers.
How is this Smartphone Industry segmented and which is the largest segment?
The smartphone industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments.
Technology
Android
IOS
Others
Price Range
Between USD 150-USD 800
Greater than USD 800
Less than USD150
Screen Size
Greater than 6 inches
Between 5-6 inches
Less than 5 inches
Geography
APAC
China
India
Japan
South Korea
Europe
Germany
UK
France
North America
Canada
US
Middle East and Africa
South America
Brazil
By Technology Insights
The android segment is estimated to witness significant growth during the forecast period.
The Android operating system, provided by Alphabet Inc. (Google), is a globally popular choice for smartphones. With over 2.5 million apps available In the Google Play Store, users have access to a vast selection of applications catering to their diverse needs. Notable features of the Android OS include smart reply for messaging apps, focus mode options, Wi-Fi sharing via QR codes, and Google Assistant. Google offers essential web services such as Google Search, Google Maps, and YouTube free of charge. The Android OS's extensive feature set has contributed to its increasing popularity among consumers worldwide.
In addition, high-speed data connectivity and integration with Internet of Things (IoT) applications further enhance its appeal. Application developers create software for various lifestyle, social media, mobile utility, and other categories, ensuring a rich and diverse app ecosystem. The Android OS is written primarily in Java and C++, with support for in-app purchases and in-app course subscriptions.
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The android segment was valued at USD 203.60 million in 2019 and showed a gradual increase during the forecast period.
Regional Analysis
APAC is estimated to contribute 48% to the growth of the global market during the forecast period.
Technavio's analysts have elaborately explained the regional trends and drivers that shape the market during the forecast period.
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The market in APAC has experienced substantial growth, with China, Japan, India, South Korea, and Indonesia being the primary contributors to revenue generation. The expansion of urban populations and the subsequent increase in disposable income have fueled the demand for smartphones In the region. Key drivers of this market growth include the advancement of telecom infrastructure and the emergence of affordable smartphone options. Major global smartphone manufacturers have established manufacturing facilities in China, Taiwan, South Korea, Japan, and India to cater to the increasing demand.
Additionally, digital information consumption, human-computer interaction advancements, and t
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The global mobile phone data line market size was valued at approximately $5.4 billion in 2023 and is projected to reach $8.9 billion by 2032, registering a CAGR of 6.2% during the forecast period. The market growth is primarily driven by the rising smartphone penetration, increasing data transfer needs, and advancements in charging technology.
One of the most significant growth factors for the mobile phone data line market is the widespread adoption of smartphones and other mobile devices. With smartphone penetration nearing saturation in developed markets and continuing to rise in emerging economies, the demand for mobile phone data lines is expected to grow robustly. The increasing need for efficient and reliable connectivity for data transfer and charging purposes further propels the market. As mobile devices become more integral to daily activities, consumers are seeking data lines that offer higher speed, durability, and versatility.
Technological advancements in charging and data transfer technologies also contribute significantly to market growth. Innovations such as fast-charging capabilities, reversible connectors like USB Type-C, and enhanced data transfer speeds are attracting consumers to upgrade their existing data lines. Additionally, the growing trend of wireless charging has not completely eliminated the need for traditional data lines, as the latter still remain essential for certain applications such as data transfer, device management, and specific charging needs.
The surge in e-commerce and the proliferation of online shopping platforms have also played a crucial role in the market’s expansion. With the convenience of online stores, consumers now have access to a broader range of products and brands, including high-quality and specialized data lines. This shift towards online purchasing has opened new avenues for market growth, enabling manufacturers to reach a wider audience and offer competitive pricing.
Regionally, Asia Pacific dominates the mobile phone data line market, driven by the high smartphone penetration rates in countries like China and India. North America and Europe also represent significant markets, with steady demand supported by technological adoption and consumer awareness. The Middle East & Africa and Latin America are emerging markets, showing promising growth potential due to increasing smartphone usage and improving economic conditions.
The mobile phone data line market is segmented into several types, including USB Type-C, Micro USB, Lightning, and Others. Each type has distinct features and caters to various consumer needs and device compatibility. USB Type-C has been gaining significant traction due to its reversible design and high-speed data transfer capabilities. It supports faster charging and is compatible with a wide range of devices, making it a preferred choice among consumers and manufacturers alike.
Micro USB, although being an older technology compared to USB Type-C, still holds a substantial share of the market. Many budget and mid-range smartphones continue to use Micro USB ports, particularly in developing regions. This segment is characterized by its affordability and widespread availability, making it accessible to a large demographic. However, its market share is gradually declining as more devices transition to USB Type-C.
The Lightning connector, exclusive to Apple's ecosystem, remains a significant player in the market. Designed for iPhones, iPads, and other Apple devices, the Lightning cable is known for its durability and efficient data transfer speeds. Despite the speculation about Apple transitioning to USB Type-C, the Lightning connector continues to sustain a loyal customer base, contributing to steady demand in this segment.
Other types of mobile phone data lines include proprietary connectors used by specific brands or specialized cables designed for particular functionalities. These niche segments cater to specific consumer needs and device compatibility requirements, contributing to the overall diversity of the market. The continued innovation in this segment ensures that a wide range of consumer preferences and device specifications are met.
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Smart phone price index (CPPI) by North American Product Classification System (NAPCS). The table includes annual data for the most recent reference period and the last four periods. Data are available from January 2015. The base period for the index is (2015=100).
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SELECTED SOCIAL CHARACTERISTICS IN THE UNITED STATES COMPUTERS AND INTERNET USE - DP02 Universe - Total households Survey-Program - American Community Survey 5-year estimates Years - 2020, 2021, 2022 The 2008 Broadband Improvement Act mandated the collection of data about computer and internet use. As a result, three questions were added to the 2013 American Community Survey (ACS) to measure these topics. The computer use question asked if anyone in the household owned or used a computer and included four response categories for a desktop or laptop, a smartphone, a tablet or other portable wireless computer, and some other type of computer. Respondents selected a checkbox for “Yes” or “No” for each response category. Respondents could select all categories that applied. Question asked if any member of the household has access to the internet. “Access” refers to whether or not someone in the household uses or can connect to the internet, regardless of whether or not they pay for the service. If a respondent answers “Yes, by paying a cell phone company or Internet service provider”, they are asked to select the type of internet service.
Between 2015 and 2021, regardless of their age, the share of children owning a smartphone in the United States grew. During the 2021 survey, it was found that 31 percent of responding 8-year-olds owned a smartphone, up from only 11 percent in 2015.
Rugged Smartphone Market Size 2025-2029
The rugged smartphone market size is forecast to increase by USD 299.6 million, at a CAGR of 4.5% between 2024 and 2029.
The market is experiencing significant growth, driven by increasing demand from the defense sector and emerging applications in industries such as construction, healthcare, and field services. This trend is partly due to the convergence of consumer-grade smartphones with ruggedized features, making them more accessible and cost-effective alternatives to traditional rugged devices. However, this market is not without challenges. One major obstacle is the high cost of manufacturing rugged smartphones, which can limit their widespread adoption. Additionally, the durability and reliability of these devices must be consistently maintained to meet the demanding requirements of their users. To capitalize on this market's potential, companies should focus on developing cost-effective rugged smartphones with superior durability and advanced features to cater to the evolving needs of various industries. By addressing these challenges and leveraging the growing demand, businesses can effectively navigate this dynamic market and secure a competitive edge.
What will be the Size of the Rugged Smartphone Market during the forecast period?
Explore in-depth regional segment analysis with market size data - historical 2019-2023 and forecasts 2025-2029 - in the full report.
Request Free SampleThe market continues to evolve, with dynamic market activities unfolding across various sectors. Facial recognition technology and wireless charging are increasingly integrated into rugged devices, enhancing security and convenience. Rugged cases with IP68 ratings and sapphire glass offer superior water resistance and drop protection. Proximity sensors and battery life optimization ensure efficient use of resources. Storage capacity and mobile accessories cater to the needs of field service management and outdoor recreation applications. Telephoto lenses and push-to-talk (PTT) capabilities expand the functionality of these devices for public safety and construction applications. Augmented reality (AR) and ultra-wide lenses offer new possibilities for industrial inspections and healthcare diagnoses.
Biometric security and thermal management systems ensure optimal device performance and data protection. Protective films, screen size, and cellular connectivity cater to the diverse needs of this market. Rugged smartphones are increasingly being adopted for military applications, with features such as mil-std-810h certification, external antennas, and night mode enhancing their utility. The integration of touchscreen technology, ambient light sensors, and virtual reality (VR) capabilities further expands the potential applications of rugged smartphones. Fast charging and extended battery options cater to the demands of users in the field. Rugged smartphones continue to be a crucial tool for industries requiring robust and reliable devices, with ongoing advancements in technology shaping the market's future.
How is this Rugged Smartphone Industry segmented?
The rugged smartphone industry research report provides comprehensive data (region-wise segment analysis), with forecasts and estimates in 'USD million' for the period 2025-2029, as well as historical data from 2019-2023 for the following segments. TypeSemi-ruggedFully-ruggedUltra-ruggedEnd-userIndustrialCommercialMilitary and defenseGovernmentGeographyNorth AmericaUSCanadaEuropeFranceGermanyItalyUKAPACChinaIndiaJapanSouth KoreaRest of World (ROW)
By Type Insights
The semi-rugged segment is estimated to witness significant growth during the forecast period.Semi-rugged smartphones represent a category of devices that cater to the demands of professionals in diverse industries, offering a balance between consumer-grade features and rugged durability. These devices are engineered to endure harsh conditions and rough handling, without sacrificing the advanced functionalities of standard smartphones. Semi-rugged smartphones incorporate several enhanced features. For instance, they may include data encryption for heightened security, external antennas for improved connectivity, and image stabilization for superior photography. Military applications benefit from their ruggedness and GPS tracking capabilities, while field service management relies on their durability and touchscreen technology. Semi-rugged smartphones boast IP68 ratings for water resistance and shock resistance, ensuring they can withstand drops and extreme temperatures. They may also feature sapphire glass for unparalleled screen protection and Gorilla Glass for scratch resistance. Facial recognition and fingerprint sensors provide biometric security, while thermal management maintains optimal performance. Additional features include long battery life, extensive storage capacity, wireless ch
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Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, the decennial census is the official source of population totals for April 1st of each decennial year. In between censuses, the Census Bureau's Population Estimates Program produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units and the group quarters population for states and counties..Information about the American Community Survey (ACS) can be found on the ACS website. Supporting documentation including code lists, subject definitions, data accuracy, and statistical testing, and a full list of ACS tables and table shells (without estimates) can be found on the Technical Documentation section of the ACS website.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019-2023 American Community Survey 5-Year Estimates.ACS data generally reflect the geographic boundaries of legal and statistical areas as of January 1 of the estimate year. For more information, see Geography Boundaries by Year..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Users must consider potential differences in geographic boundaries, questionnaire content or coding, or other methodological issues when comparing ACS data from different years. Statistically significant differences shown in ACS Comparison Profiles, or in data users' own analysis, may be the result of these differences and thus might not necessarily reflect changes to the social, economic, housing, or demographic characteristics being compared. For more information, see Comparing ACS Data..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..The category "Has one or more types of computing devices" refers to those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer. The category "No computer" consists of those who said "No" to all of these types of computers.."Desktop or laptop" refers to those who selected that category regardless of whether or not they indicated they also had another type of computer. However, "Desktop or laptop with no other type of computing device" refers to those who said "Yes" to owning or using a desktop or laptop and "No" to smartphone, tablet or other wireless computer, and other computer. Similarly, the same holds true for "Smartphone" compared to "Smartphone with no other type of computing device", "Tablet or other portable wireless computer" compared to "Tablet or other portable wireless computer with no other type of computing device", and "Other computer" compared to "Other computer with no other type of computing device.".Caution should be used when comparing data for computer and Internet use before and after 2016. Changes in 2016 to the questions involving the wording as well as the response options resulted in changed response patterns in the data. Most noticeable are increases in overall computer ownership or use, the total of Internet subscriptions, satellite subscriptions, and cellular data plans for a smartphone or other mobile device. For more detailed information about these changes, see the 2016 American Community Survey Content Test Report for Computer and Internet Use located at https://www.census.gov/library/working-papers/2017/acs/2017_Lewis_01.html or the user note regarding changes in the 2016 questions located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes/2017-03.html..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on 2020 Census data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed becau...
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This data base shows the responses of medical students from 7 countries of Latin America, about academic use of smartphones.
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Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the .Technical Documentation.. section......Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the .Methodology.. section..Source: U.S. Census Bureau, 2018 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see .ACS Technical Documentation..). The effect of nonsampling error is not represented in these tables..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..The category "Has one or more types of computing devices" refers to those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer. The category "No computer" consists of those who said "No" to all of these types of computers.."Desktop or laptop" refers to those who selected that category regardless of whether or not they indicated they also had another type of computer. However, "Desktop or laptop with no other type of computing device" refers to those who said "Yes" to owning or using a desktop or laptop and "No" to smartphone, tablet or other wireless computer, and other computer. Similarly, the same holds true for "Smartphone" compared to "Smartphone with no other type of computing device", "Tablet or other portable wireless computer" compared to "Tablet or other portable wireless computer with no other type of computing device", and "Other computer" compared to "Other computer with no other type of computing device.".Caution should be used when comparing data for computer and Internet use before and after 2016. Changes in 2016 to the questions involving the wording as well as the response options resulted in changed response patterns in the data. Most noticeable are increases in overall computer ownership or use, the total of Internet subscriptions, satellite subscriptions, and cellular data plans for a smartphone or other mobile device. For more detailed information about these changes, see the 2016 American Community Survey Content Test Report for Computer and Internet Use located at .https://www.census.gov/programs-surveys/acs/methodology/content-test.htm.. or the user note regarding changes in the 2016 questions located at .https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes.html....While the 2018 American Community Survey (ACS) data generally reflect the July 2015 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas, in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:..An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median w...
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Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2019 American Community Survey 1-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..The category "Has one or more types of computing devices" refers to those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer. The category "No computer" consists of those who said "No" to all of these types of computers.."Desktop or laptop" refers to those who selected that category regardless of whether or not they indicated they also had another type of computer. However, "Desktop or laptop with no other type of computing device" refers to those who said "Yes" to owning or using a desktop or laptop and "No" to smartphone, tablet or other wireless computer, and other computer. Similarly, the same holds true for "Smartphone" compared to "Smartphone with no other type of computing device", "Tablet or other portable wireless computer" compared to "Tablet or other portable wireless computer with no other type of computing device", and "Other computer" compared to "Other computer with no other type of computing device.".Caution should be used when comparing data for computer and Internet use before and after 2016. Changes in 2016 to the questions involving the wording as well as the response options resulted in changed response patterns in the data. Most noticeable are increases in overall computer ownership or use, the total of Internet subscriptions, satellite subscriptions, and cellular data plans for a smartphone or other mobile device. For more detailed information about these changes, see the 2016 American Community Survey Content Test Report for Computer and Internet Use located at https://www.census.gov/library/working-papers/2017/acs/2017_Lewis_01.html or the user note regarding changes in the 2016 questions located at https://www.census.gov/programs-surveys/acs/technical-documentation/user-notes/2017-03.html..The 2019 American Community Survey (ACS) data generally reflect the September 2018 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineations due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:An "**" entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.An "-" entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution, or the margin of error associated with a median was larger than the med...
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The Smartphone Market Report is Segmented by Operating System (Android, IOS, and More), Price Band (Entry-Level [Less Than USD 200], Mid-Range [USD 200 – 499], and More), Technology (5G, 4G/LTE, and 3G and Below), Form Factor (Bar, Foldable/Flip, and Rugged/Industrial), Distribution Channel (Operator/Carrier Stores, Brand-Owned Retail, and More) and Geography. The Market Forecasts are Provided in Terms of Value (USD).
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Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau's Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities, and towns and estimates of housing units for states and counties..Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Technical Documentation section.Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Source: U.S. Census Bureau, 2017-2021 American Community Survey 5-Year Estimates.Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see ACS Technical Documentation). The effect of nonsampling error is not represented in these tables..Data about computer and Internet use were collected by asking respondents to select "Yes" or "No" to each type of computer and each type of Internet subscription. Therefore, respondents were able to select more than one type of computer and more than one type of Internet subscription..The category "Has one or more types of computing devices" refers to those who said "Yes" to at least one of the following types of computers: Desktop or laptop; smartphone; tablet or other portable wireless computer; or some other type of computer. The category "No computer" consists of those who said "No" to all of these types of computers..Desktop or laptop refers to those who selected that category regardless of whether or not they indicated they also had another type of computer. However, "Desktop or laptop with no other type of computing device" refers to those who said "Yes" to owning or using a desktop or laptop and "No" to smartphone, tablet or other wireless computer, and other computer. Similarly, the same holds true for "Smartphone" compared to "Smartphone with no other type of computing device", "Tablet or other portable wireless computer" compared to "Tablet or other portable wireless computer with no other type of computing device", and "Other computer" compared to "Other computer with no other type of computing device.".The 2017-2021 American Community Survey (ACS) data generally reflect the March 2020 Office of Management and Budget (OMB) delineations of metropolitan and micropolitan statistical areas. In certain instances, the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB delineation lists due to differences in the effective dates of the geographic entities..Estimates of urban and rural populations, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..Explanation of Symbols:- The estimate could not be computed because there were an insufficient number of sample observations. For a ratio of medians estimate, one or both of the median estimates falls in the lowest interval or highest interval of an open-ended distribution. For a 5-year median estimate, the margin of error associated with a median was larger than the median itself.N The estimate or margin of error cannot be displayed because there were an insufficient number of sample cases in the selected geographic area. (X) The estimate or margin of error is not applicable or not available.median- The median falls in the lowest interval of an open-ended distribution (for example "2,500-")median+ The median falls in the highest interval of an open-ended distribution (for example "250,000+").** The margin of error could not be computed because there were an insufficient number of sample observations.*** The margin of error could not be computed because the median falls in the lowest interval or highest interval of an open-ended distribution.***** A margin of error is not appropriate because the corresponding estimate is controlled to an independent population or housing estimate. Effectively, the corresponding estimate has no sampling error and the margin of error may be treated as zero.
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According to Cognitive Market Research, The Global NFC enabled Handsets market will grow at a compound annual growth rate (CAGR) of 20.50% from 2023 to 2030.
The demand for NFC enabled handsets is rising due to increasing demand for mobile payments.
Demand for feature phones remains higher in the NFC enabled handsets market.
The mobile payment category held the highest NFC enabled handsets market revenue share in 2023.
North America will continue to lead, whereas the Asia Pacific NFC enabled handsets market will experience the most robust growth until 2030.
Increasing Demand for Mobile Payments to Drive Market Growth
Mobile payments using NFC enabled handsets offer a faster and more convenient alternative to traditional payment methods. Users can complete transactions with a simple tap, reducing the time spent at the checkout. The increasing penetration of smartphones, including NFC enabled handsets, provides a larger user base for mobile payment solutions. As more people own smartphones, the potential for mobile payments grows.
Smartphone shipments from India reached 168 million units in 2021, and it is anticipated that they will reach 190 million units in 2022.
(Source: www.ibef.org/industry/electronics-system-design-manufacturing-esdm)
Mobile wallet applications like Apple Pay, Google Pay, and Samsung Pay have gained traction. These wallets rely on NFC technology and have become increasingly integrated into daily routines. Mobile payments extend beyond physical retail stores. Users can make online and in-app purchases using their NFC enabled handsets, broadening the scope of mobile payment applications.
Growing Adoption of Wearable Technology to Drive Market Growth
Wearable devices, especially smartwatches, are increasingly used for mobile ticketing applications. Users can store electronic tickets for public transportation, events, or flights on their wearables, simplifying ticketing. Some banks and financial institutions offer apps that are compatible with wearable devices. Users can check their account balances, receive transaction alerts, and even make mobile payments using NFC enabled wearables.
Exports of electronic goods increased by 50.52% from US$ 15.66 billion in FY22 to US$ 23.57 billion in FY23, a record high.
(Source: www.ibef.org/industry/electronics-system-design-manufacturing-esdm)
NFC enabled wearables are used for health and fitness applications. Users can tap their devices to collect data from fitness equipment, make payments for health services, or even access their medical records securely.
Market Dynamics Of the NFC enabled Handsets
Lack of Awareness and Education to Hinder Market Growth
The lack of education about the various applications of NFC technology can result in a limited understanding of its potential use cases beyond mobile payments. This can hinder the development of new NFC-based services. The lack of awareness about NFC security features can lead to unfounded concerns and reluctance to use NFC enabled handsets for secure transactions. Some individuals and businesses may perceive NFC technology as too complex or difficult to implement. This can discourage exploration and adoption.
Key Trends of the NFC enabled Handsets
The Rapid Increase in the Use of Contactless Payments and Digital Wallets
With the worldwide growth of mobile payment systems such as Google Pay, Apple Pay, and Samsung Pay, there is a significant demand for NFC-enabled smartphones. Consumers are favoring fast, secure, and touchless transactions, particularly in the aftermath of the pandemic, which has led to a rise in the incorporation of NFC chips in mid-range and entry-level devices across various markets.
Integration with IoT and Smart Ecosystems
NFC-enabled smartphones are being utilized increasingly for purposes beyond payments, including pairing with smart devices, access control, ticketing, and identity verification. As smart home technologies, wearables, and interconnected infrastructure expand, NFC devices act as a central hub, enhancing their importance in everyday digital interactions.
Impact of COVID-19 on the NFC enabled handsets market
COVID-19, both positive and negative, significantly impacted the market for NFC enabled smartphones. The pandemic accelerated the adoption of contactless payment methods due to concerns about the transmission of the virus through ...
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The global mobile data traffic market size was estimated at approximately USD 68 billion in 2023 and is projected to surge to about USD 320 billion by 2032, exhibiting a remarkable compound annual growth rate (CAGR) of 18.5% over the forecast period. This growth is driven by the increasing penetration of smartphones, advancements in network technologies, and the rising consumption of data-intensive applications and services.
One of the primary growth factors for the mobile data traffic market is the rapid expansion of the smartphone user base globally. As smartphones become more affordable and accessible, especially in emerging markets, the number of mobile internet users is skyrocketing. This trend is further amplified by the increasing availability of high-speed mobile networks, which make data-heavy applications such as video streaming and online gaming more feasible and attractive to users. The proliferation of affordable data plans is also encouraging users to consume more mobile data, thereby bolstering market growth.
Another significant driver of growth is the continuous evolution of network technologies. The transition from 3G to 4G, and now to 5G, has significantly enhanced data transmission speeds and network capabilities. 5G technology, in particular, promises ultra-low latency, higher capacity, and faster download and upload speeds, which are expected to revolutionize various sectors such as healthcare, automotive, and smart cities. The deployment and adoption of 5G networks are anticipated to boost mobile data traffic volumes exponentially, as it facilitates the seamless use of high-bandwidth applications, including augmented reality (AR), virtual reality (VR), and Internet of Things (IoT) devices.
The increase in video content consumption is also a major factor driving the market. Video traffic accounts for a substantial portion of mobile data usage, driven by platforms like YouTube, Netflix, and social media sites that prioritize video content. The trend of live streaming and video-on-demand services is creating a massive surge in data traffic, with users increasingly accessing high-definition (HD) and even 4K content. Moreover, the COVID-19 pandemic has accelerated the adoption of digital entertainment and online education, further increasing the demand for mobile data.
Regionally, the growth of mobile data traffic is witnessing variations with Asia Pacific leading the charge. The region's high population density, coupled with increasing urbanization and smartphone penetration, makes it a significant contributor to global data traffic. Countries like China and India are at the forefront, driven by government initiatives to promote digitalization and the rollout of advanced mobile networks. North America and Europe are also substantial markets due to their well-established network infrastructure and early adoption of new technologies. However, the growth rates in these regions are relatively moderate compared to the exponential growth seen in Asia Pacific and Latin America.
The mobile data traffic market can be segmented by traffic type into video, audio, data, and others. Video traffic is the most dominant segment, accounting for the largest share of mobile data usage worldwide. The proliferation of video streaming services, alongside user-generated video content on social media platforms, significantly contributes to this dominance. As more users switch to high-definition and 4K streaming, the demand for data-intensive video content continues to rise. Additionally, the growing popularity of live streaming and video calls, particularly in the context of remote work and online education, further propels this segment's growth.
Audio traffic also plays a significant role in the mobile data traffic market. The increasing usage of music streaming services such as Spotify, Apple Music, and various podcast platforms are driving the growth of this segment. The trend of consuming audio content on the go, facilitated by improved network speeds and unlimited data plans, is contributing to a steady rise in mobile data traffic from audio services. Furthermore, the adoption of smart speakers and voice assistant technologies is expected to continue bolstering this segment.
Data traffic, encompassing all forms of non-visual and non-audio data, is another crucial segment. This includes browsing, app usage, emails, and other types of data transmission over mobile networks. With the increasing reliance on mobile applications for a wide array of activities—ra
This web map visualizes the prevalence of households in a given geography that do not own a computer, smartphone, or tablet. Data are shown by tract, county, and state boundaries -- zoom out to see data visualized for larger geographies. The map also displays the boundary lines for the jurisdiction of Rochester, NY (visible when viewing the tract level data), as this map was created for a Rochester audience.This web map draws from an Esri Demographics service that is updated annually to contain the most currently released American Community Survey (ACS) 5-year data, and contains estimates and margins of error. To see the full list of attributes available in this service, go to the "Data" tab, and choose "Fields" at the top right. Current Vintage: 2014-2018ACS Table(s): B28001, B28002 (Not all lines of ACS table B28002 are available in this feature layer)Data downloaded from: Census Bureau's API for American Community Survey Date of API call: December 19, 2019National Figures: data.census.govThe United States Census Bureau's American Community Survey (ACS):About the SurveyGeography & ACSTechnical DocumentationNews & UpdatesThis ready-to-use layer can be used within ArcGIS Pro, ArcGIS Online, its configurable apps, dashboards, Story Maps, custom apps, and mobile apps. Data can also be exported for offline workflows. Please cite the Census and ACS when using this data.Data Note from the Census:Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables.Data Processing Notes:This layer is updated automatically when the most current vintage of ACS data is released each year, usually in December. The layer always contains the latest available ACS 5-year estimates. It is updated annually within days of the Census Bureau's release schedule. Click here to learn more about ACS data releases.Boundaries come from the US Census TIGER geodatabases. Boundaries are updated at the same time as the data updates (annually), and the boundary vintage appropriately matches the data vintage as specified by the Census. These are Census boundaries with water and/or coastlines clipped for cartographic purposes. For census tracts, the water cutouts are derived from a subset of the 2010 AWATER (Area Water) boundaries offered by TIGER. For state and county boundaries, the water and coastlines are derived from the coastlines of the 500k TIGER Cartographic Boundary Shapefiles. The original AWATER and ALAND fields are still available as attributes within the data table (units are square meters). The States layer contains 52 records - all US states, Washington D.C., and Puerto RicoCensus tracts with no population that occur in areas of water, such as oceans, are removed from this data service (Census Tracts beginning with 99).Percentages and derived counts, and associated margins of error, are calculated values (that can be identified by the "_calc_" stub in the field name), and abide by the specifications defined by the American Community Survey.Field alias names were created based on the Table Shells file available from the American Community Survey Summary File Documentation page.Negative values (e.g., -555555...) have been set to null. These negative values exist in the raw API data to indicate the following situations:The margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate.Either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution.The median falls in the lowest interval of an open-ended distribution, or in the upper interval of an open-ended distribution. A statistical test is not appropriate.The estimate is controlled. A statistical test for sampling variability is not appropriate.The data for this geographic area cannot be displayed because the number of sample cases is too small. NOTE: any calculated percentages or counts that contain estimates that have null margins of error yield null margins of error for the calculated fields.