The number of smartphone users in the United States was forecast to continuously increase between 2024 and 2029 by in total 17.4 million users (+5.61 percent). After the fifteenth consecutive increasing year, the smartphone user base is estimated to reach 327.54 million 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 Mexico and Canada.

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 fifteenth 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 the Americas and Asia.

Percentage of smartphone users by selected smartphone use habits in a typical day.

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.

Percentage of Canadians using a smartphone for personal use and selected habits of use during a typical day.

The number of smartphone users in Ireland was forecast to continuously increase between 2024 and 2029 by in total 0.3 million users (+6.15 percent). After the seventh consecutive increasing year, the smartphone user base is estimated to reach 5.22 million users and therefore a new peak in 2029. 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 information concerning Serbia and Sweden.

In 2022, smartphone vendors sold around 1.39 billion smartphones were sold worldwide, with this number forecast to drop to 1.34 billion in 2023.

Smartphone penetration rate still on the rise

Less than half of the world’s total population owned a smart device in 2016, but the smartphone penetration rate has continued climbing, reaching 78.05 percent in 2020. By 2025, it is forecast that almost 87 percent of all mobile users in the United States will own a smartphone, an increase from the 27 percent of mobile users in 2010.

Smartphone end user sales

In the United States alone, sales of smartphones were projected to be worth around 73 billion U.S. dollars in 2021, an increase from 18 billion dollars in 2010. Global sales of smartphones are expected to increase from 2020 to 2021 in every major region, as the market starts to recover from the initial impact of the coronavirus (COVID-19) pandemic.

Dataset from Singapore Department of Statistics. For more information, visit https://data.gov.sg/datasets/d_65567444c3df02aceb795897bbd183c9/view

China is leading the ranking by number of smartphone users, recording ****** million users. Following closely behind is India with ****** million users, while Seychelles is trailing the ranking with **** million users, resulting in a difference of ****** million users to the ranking leader, China. 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).

The S3 dataset contains the behavior (sensors, statistics of applications, and voice) of 21 volunteers interacting with their smartphones for more than 60 days. The type of users is diverse, males and females in the age range from 18 until 70 have been considered in the dataset generation. The wide range of age is a key aspect, due to the impact of age in terms of smartphone usage. To generate the dataset the volunteers installed a prototype of the smartphone application in on their Android mobile phones.
All attributes of the different kinds of data are writed in a vector. The dataset contains the fellow vectors:
Sensors:
This type of vector contains data belonging to smartphone sensors (accelerometer and gyroscope) that has been acquired in a given windows of time. Each vector is obtained every 20 seconds, and the monitored features are:- Average of accelerometer and gyroscope values.- Maximum and minimum of accelerometer and gyroscope values.- Variance of accelerometer and gyroscope values.- Peak-to-peak (max-min) of X, Y, Z coordinates.- Magnitude for gyroscope and accelerometer.

Statistics:
These vectors contain data about the different applications used by the user recently. Each vector of statistics is calculated every 60 seconds and contains : - Foreground application counters (number of different and total apps) for the last minute and the last day.- Most common app ID and the number of usages in the last minute and the last day. - ID of the currently active app. - ID of the last active app prior to the current one.- ID of the application most frequently utilized prior to the current application. - Bytes transmitted and received through the network interfaces.

Voice:
This kind of vector is generated when the microphone is active in a call o voice note. The speaker vector is an embedding, extracted from the audio, and it contains information about the user's identity. This vector, is usually named "x-vector" in the Speaker Recognition field, and it is calculated following the steps detailed in "egs/sitw/v2" for the Kaldi library, with the models available for the extraction of the embedding.


A summary of the details of the collected database.
- Users: 21 - Sensors vectors: 417.128 - Statistics app's usage vectors: 151.034 - Speaker vectors: 2.720 - Call recordings: 629 - Voice messages: 2.091

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).

There are a total of 17 questions in the survey, addressing the following categories:Internet useMobile phone use (smartphones & basic voice/SMS phones)Awareness and use of WikipediaGeneral demographicsThe survey collected 2500 total responses, representing populations in 5 geographical regions served by 3 mobile Iraqi operators. 3 language choices (Arabic, English, Kurdish) were provided.Here are the main questions this survey was designed to answer. However, analyzing the full data set allows you to conduct more in-depth data explorations and gain meaningful insights beyond the points presented here.What is the actual number of people who use the internet?(Real-world behavior makes this difficult to measure from industry reports, since people might have access to the internet through school, friends, internet cafés, public Wifi, etc.)For internet users: What do people mostly use the internet for?For non-internet users: Why not use the internet?How many people use smartphones?Do people with smartphones use the internet from just Wifi? Or just cellular service?How many people think that they don’t use the internet, but still use Facebook or WhatsApp?How many people have heard of Wikipedia? What do they use it for? How often?If they have heard of Wikipedia, but aren’t using it, why not?Compared to previous phone surveys in other countries, the 2017 Iraq phone survey presented new questions.What are people’s awareness of other major internet brands in comparison to Wikipedia?Can people find online content in their preferred language?How does data cost impact internet use?

Apple is one of the most influential and recognisable brands in the world, responsible for the rise of the smartphone with the iPhone. Valued at over $2 trillion in 2021, it is also the most valuable...

Percentage of Internet users by selected Internet service and technology, such as; home Internet access, use of smart home devices, use of smartphones, use of social networking accounts, use or purchase of streaming services, use of government services online and online shopping.

Italian(Italy) Scripted Monologue Smartphone speech dataset, collected from monologue based on given common-used sentences, with balanced gender distribution. Transcribed with text content and other attributes. Our dataset was collected from extensive and diversify speakers(800 people), geographicly speaking, enhancing model performance in real and complex tasks.Quality tested by various AI companies. We strictly adhere to data protection regulations and privacy standards, ensuring the maintenance of user privacy and legal rights throughout the data collection, storage, and usage processes, our datasets are all GDPR, CCPA, PIPL complied.

The dataset provides temporary migration estimates at the (origin*destination*time)-level in Senegal derived from mobile phone data for the period 2013-2015. Origin and destination locations are comprised of 39 cities and 112 rural areas of third-level administrative units (i.e., districts), defining the spatial resolution of the dataset. Estimates are provided for each half-month period, defining the temporal resolution of the dataset.

Kazakhstan Number of Mobile Phone Subscribers data was reported at 25,521,600.000 Person in 2023. This records an increase from the previous number of 25,171,800.000 Person for 2022. Kazakhstan Number of Mobile Phone Subscribers data is updated yearly, averaging 19,402,600.000 Person from Dec 1997 (Median) to 2023, with 27 observations. The data reached an all-time high of 30,373,000.000 Person in 2013 and a record low of 11,240.000 Person in 1997. Kazakhstan Number of Mobile Phone Subscribers data remains active status in CEIC and is reported by Bureau of National Statistics of the Agency for Strategic Planning and Reforms of the Republic of Kazakhstan. The data is categorized under Global Database’s Kazakhstan – Table KZ.TB001: Communication Statistics.

Mobile Phone Company Description:

A mobile phone company is a business organization that designs, manufactures, markets, and/or sells mobile phones and related services. These companies may operate as hardware manufacturers producing smartphones and accessories, or as service providers offering cellular network connectivity, mobile internet, and value-added services.

Mobile phone companies play a key role in the telecommunications industry by connecting people globally through voice, messaging, and data services. They often offer a range of products and services, including prepaid and postpaid plans, 4G/5G network access, mobile applications, customer support, and device financing options.

Digitally semi-literate means those people who face challenges in digital enablement and are not too familiar with using smartphones for text message communication. Any progress to reduce the difficulty of their smartphone usage can help these people. These people are over one billion worldwide. The dataset contains text messages in English (some of these are translations of local text messages) from semi-literate Indian users. The dataset has been derived from face to face surveys primarily. Only 10% by online surveys since these people are not comfortable in doing online surveys.

This dataset contains transcribed fieldnotes from a “methodological assemblage” and technological prototype connecting autoethnography to the practices of self-research in personal science. As an experimental process of personal data gathering, the author used a low-tech device for the active registration of events and their perception, in a case study on disengaging from his smartphone.

The dataset contains 267 data points (timestamp and intensity/duration of perceived events) with alternative classification and subclassification categories through thematic analysis, as well as 112 "on spot" fieldnotes and 112 related retrospective interpretation notes (with corresponding references where indicated) from a focused autoethnography intervention, tracking the authors' experience of living without constant access to a smartphone for a month (during May 2021).

For more info on the process and the main results of this personal experiment, here's the derived publication: Senabre Hidalgo, E., & Greshake Tzovaras, B. (2023). “One button in my pocket instead of the smartphone”: A methodological assemblage connecting self-research and autoethnography in a digital disengagement study. Methodological Innovations. https://doi.org/10.1177/20597991231161093

As described in the paper, this dataset contains a classification of events based on two complementary approaches:

Initial categories (May 2021): Positive - Negative - Reflection

Retrospective categories and subcategories (November 2021):

Response to habit:

Basic impulse: looking for smartphone in pocket / “If I had it now…”

Abstinence reaction: attempts to reconnect to “the cloud”

Fear of missing out (FOMO) after long periods of time

Disruption in basic routine: perception of altered habits

Social context:

Feelings of embarrassment: in relation to others due to feature phone

Observing others: people using smartphones around me

Meta level: how to share process afterwards (in community, academically)

User experience (UX) practicalities:

Moving around solo: orientation when commuting without GPS

Parasitic use of other smartphones (in case of urgent need)

Capturing things on the spot (pictures, information, feelings)

Local stored culture (music and reading away from screens)

Communication problems: dysfunctions in everyday coordination

Reconnection need: whenever ending up using the smartphone again

Self-reinforcing / awareness:

Succeeding in intended detox: satisfaction for achievement

Full attention to moment / stimulus: mindfulness and concentration

Relevant changes in routine: positive reinforcement by new habit