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.

Mobile Phone Dataset | Smartphone & Feature Phone

Crowdsourced original images of a wide variety of mobile phones

About Dataset

This dataset is collected by* DataCluster Labs*, India. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

This dataset is an extremely challenging set of over 3000+ original Mobile Phone images captured and crowdsourced from over 1000+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at ****DC Labs.

Dataset Features 1. Dataset size : 3000+ 2. Captured by : Over 1000+ crowdsource contributors 3. Resolution : 99% images HD and above (1920x1080 and above) 4. Location : Captured with 600+ cities accross India 5. Diversity : Various lighting conditions like day, night, varied distances, view points etc. 6. Device used : Captured using mobile phones in 2020-2021 7. Applications : Mobile Phone detection, cracked screen detection, etc.

Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai

Visit www.datacluster.ai to know more.

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.

This is a complementary dataset for DOI: 10.1007/978-3-030-22335-9_6

Following an open data policy as supported by the European Union (https://www.openaire.eu/), this is the dataset used for the following conference paper: Zimmermann R., Auinger A., Riedl R. (2019) Smartphones as an Opportunity to Increase Sales in Brick-and-Mortar Stores: Identifying Sales Influencers Based on a Literature Review. In: Nah FH., Siau K. (eds) HCI in Business, Government and Organizations. eCommerce and Consumer Behavior. HCII 2019. Lecture Notes in Computer Science, vol 11588. Springer, Cham

The present work was conducted within the Innovative Training Network project PERFORM funded by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 765395. The EU Research Executive Agency is not responsible for any use that may be made of the information it contains.

In 2020, more smartphones were sold in Greater China than any other region in the world at over 368 million units. The annual global smartphone sales plateaued at around 1.5 billion units in the previous years, but dropped in 2020 to 1.38 billion units, due to the coronavirus pandemic. Before 2020, only China and other emerging countries in Asia were still showing growth. The potential for growth in China is reflected in the country's smartphone penetration rate, as currently, only around half of the population is using a smartphone.

Americas and Europe stagnating
Sales in the Americas region and Europe are predicted to decrease compared to pre-pandemic sales, with the largest drop in smartphone sales in 2021 predicted for North America, where smartphone sales are expected to decrease by around 8 million units in 2021 compared to 2019.

Africa and Middle East with modest growth

In contrast to the decreasing markets in Europa and the Americas, smartphone sales are expected to increase in Sub-Saharan countries and North Africa as well as the Middle East from 2019 to 2021. Shipments to the Middle East and Africa have been steadily growing since 2013. Drivers for the growth in these markets are the still low smartphone penetration and the average selling price for smartphones that is only half of the average price in North America.

This is a dataset obtained from an online survey conducted in August 2020.

In the survey, participants were introduced to the concept of a smartphone-based shopping assistant application with the help of pictures and videos when shopping with and without the application. Participants were presented with three different shopping scenarios. In each scenario, we showed products on a shelf (groceries, luxury chocolate, shoes, books). The first shopping scenario was a regular shopping scenario (RSS), the second was an augmented reality shopping scenario (ARSS), and the third was an augmented reality shopping scenario with explainable AI features (XARSS). For each scenario participants had to answer questions about how they perceived the scenario and how it influenced their overall purchase intention.

The present work was conducted within the Innovative Training Network project PERFORM funded by the European Union’s Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreement No. 765395. The EU Research Executive Agency is not responsible for any use that may be made of the information it contains.

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.

In the fourth quarter of 2024, Samsung shipped around 52 million smartphones, a decrease from the both the previous quarter and the same quarter of the previous year. Samsung’s sales consistently place the smartphone giant among the top three smartphone vendors in the world, alongside Xiaomi and Apple. Samsung smartphone sales – how many phones does Samsung sell? Global smartphone sales reached over 1.2 billion units during 2024. While the global smartphone market is led by Samsung and Apple, Xiaomi has gained ground following the decline of Huawei. Together, these three companies hold more than 50 percent of the global smartphone market share.

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...

The population share with mobile internet access in North America was forecast to increase between 2024 and 2029 by in total 2.9 percentage points. This overall increase does not happen continuously, notably not in 2028 and 2029. The mobile internet penetration is estimated to amount to 84.21 percent in 2029. Notably, the population share with mobile internet access of was continuously increasing over the past years.The penetration rate refers to the share of the total population having access to the internet via a mobile broadband connection.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 population share with mobile internet access in countries like Caribbean and Europe.

Deluxe is an online retailer based in UK that deals in a wide range of products in the following categories: 1. Clothing 2. Games 3. Appliances 4. Electronics 5. Books 6. Beauty products 7. Smartphones 8. Outdoors products 9. Accessories 10. Other Basic household products are classified as 'Other' in the category column since they have small value to the business.

Data Description: dates: sale date order_value_EUR : sale price in EUR cost: cost of goods sold in EUR category: item category country: customers' country at the time of purchase customer_name: name of customer device_type: The gadget used by customer to access our online store(PC, mobile, tablet) sales_manager: name of the sales manager for each sale sales_representative: name of the sales rep for each sale order_id: unique identifier of an order

The data was recorded for the period 1/2/2019 and 12/30/2020 with an aim to generate business insights to guide business direction. We would like to see what interesting insights the Kaggle community members can produce from this data.

Domestic Trash / Garbage Dataset

Dataset for trash detection

About Dataset

This dataset is collected by DataCluster Labs, India. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

This dataset is an extremely challenging set of over 9000+ original Trash/Garbage images captured and crowdsourced from over 2000+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at ****DC Labs.

Dataset Features 1. Dataset size : 9000+ 2. Captured by : Over 2000+ crowdsource contributors 3. Resolution : 99.9% images HD and above (1920x1080 and above) 4. Location : Captured across 500+ cities 5. Diversity : Various lighting conditions like day, night, varied distances, different material view points etc. 6. Device used : Captured using mobile phones in 2020-2022 7. Usage : Trash detection, Material classification, Garbage segregation, Trash segregation, etc.

Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

This dataset is collected by Datacluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

This dataset is an extremely challenging set of over 2000+ original Indian Traffic Sign images captured and crowdsourced from over 400+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at DC Labs.

Optimized for Generative AI, Visual Question Answering, Image Classification, and LMM development, this dataset provides a strong basis for achieving robust model performance.

Dataset Features

• Dataset size : 2000+
• Captured by : Over 400+ crowdsource contributors
• Resolution : 100% of images HD and above (1920x1080 and above)
• Location : Captured with 400+ cities accross India
• Diversity : Various lighting conditions like day, night, varied distances, view points etc.
• Device used : Captured using mobile phones in 2020-2021
• Usage : Traffic sign detection, Self-driving systems, traffic detection, sign detection, etc.

Available Annotation formats

COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

This dataset is collected by DataCluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

This dataset is an extremely challenging set of over 7000+ original Fire and Smoke images captured and crowdsourced from over 400+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs.

Optimized for Generative AI, Visual Question Answering, Image Classification, and LMM development, this dataset provides a strong basis for achieving robust model performance.

Dataset Features

• Dataset size : 7000+
• Captured by : Over 1000+ crowdsource contributors
• Resolution : 98% images HD and above (1920x1080 and above)
• Location : Captured with 400+ cities accross India
• Diversity : Various lighting conditions like day, night, varied distances, view points etc.
• Device used : Captured using mobile phones in 2020-2021
• Usage : Fire and Smoke detection, Smart cameras, Fire and Smoke alarming system, etc.

Available Annotation formats

COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

Vehicle Color Detection Dataset

Vehicle Color Detection Dataset

About Dataset

This dataset is collected by DataCluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

This dataset is an extremely challenging set of over 6,000+ images of Vehicle Colour Detection from multiple locations. These images are captured and crowdsourced from over 2000+ different locations, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs. It contains a wide variety of of vehicles such as trucks. cars, bikes,scooty, tempo,bus etc.

Dataset Features 1. Dataset size : 6000+ images 2. Captured by : Over 2000+ crowdsource contributors 3. Resolution : HD and above 4. Location : Captured with 2000+ locations 5. Diversity : Various lighting conditions like day, night, varied distances, view points etc. 6. Device used : Captured using mobile phones in 2020-2022 7. Usage : Wheel Detection, Wheel Counting, Object detection

Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record

**The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

This dataset is an extremely challenging set of over 3000+ originally Stair images captured and crowdsourced from over 500+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs.

Dataset Features

Dataset size : 3000+ Captured by : Over 500+ crowdsource contributors Resolution : 100% images HD and above (1920x1080 and above) Location : Captured with 500+ cities accross India Diversity : Various lighting conditions like day, night, varied distances, view points etc. Device used : Captured using mobile phones in 2020-2022 Usage : Stair detection , Stair Edge detection , Computer Vision , etc.

Available Annotation formats COCO, YOLO, PASCAL-VOC, Tf-Record

To download full datasets or to submit a request for your dataset needs, please ping us at sales@datacluster.ai Visit www.datacluster.ai to know more.

Note: All the images are manually captured and verified by a large contributor base on DataCluster platform

This dataset contains images of various plastic objects commonly found in everyday life. Each image is annotated with bounding boxes around the plastic items, allowing for object detection tasks in computer vision applications. With a diverse range of items such as milk packets, ketchup pouches, pens, plastic bottles, polythene bags, shampoo bottles and pouches, chips packets, cleaning spray bottles, handwash bottles, and more, this dataset offers rich training material for developing object detection models.

This dataset is collected by DataCluster Labs, India. To download the full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

The dataset is an extremely challenging set of over 4000+ original Plastic object images captured and crowdsourced from over 1000+ urban and rural areas, where each image is ** manually reviewed and verified** by computer vision professionals at Datacluster Labs.

Optimized for Generative AI, Visual Question Answering, Image Classification, and LMM development, this dataset provides a strong basis for achieving robust model performance.

Dataset Features

• Dataset size: 4000+
• Captured by: Over 1000+ crowdsource contributors
• Resolution: 99.9% images HD and above (1920x1080 and above)
• Location: Captured across 500+ cities
• Diversity: Various lighting conditions like day, night, varied distances, different material view points etc.
• Device used: Captured using mobile phones in 2020-2022
• Usage: Plastic object detection, Recycling and waste management, Garbage segregation, Trash segregation, etc.

Available Annotation formats

COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

This dataset is collected by DataCluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

This dataset is an extremely challenging set of over 5000+ images of people wearing gloves, which are captured and crowdsourced from over 2000+ urban and rural locations, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs. It contains a wide variety of gloves in various colors and textures.

Optimized for Generative AI, Visual Question Answering, Image Classification, and LMM development, this dataset provides a strong basis for achieving robust model performance.

Dataset Features

• Dataset size : 5000+ images
• Captured by : Over 2000+ crowdsource contributors
• Resolution : HD and above (1920x1080 and above)
• Location : Captured with 100+ locations across India
• Diversity : Various lighting conditions like day, night, varied distances, view points etc.
• Device used : Captured using mobile phones in 2020-2022
• Usage : Gloves Detection, Body Accessories Detection, PPE Detection, Covid Safety Items, Object Detection, Computer Vision, etc.

Available Annotation formats

COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

This dataset is collected by DataCluster Labs. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

This dataset is an extremely challenging set of over 1,000+ images of underpass images from multiple cities. These images captured and crowdsourced from over 200+ different locations, where each image is manually reviewed and verified by computer vision professionals at Datacluster Labs. It contains a wide variety of Kitchen images. This dataset can be used scene classification and domestic object detection.

Optimized for Generative AI, Visual Question Answering, Image Classification, and LMM development, this dataset provides a strong basis for achieving robust model performance.

Dataset Features

• Dataset size : 1000+ images
• Captured by : Over 200+ crowdsource contributors
• Resolution : HD and above (1920x1080 and above)
• Location : Captured with 200+ locations
• Diversity : Various lighting conditions like day, night, varied distances, view points etc.
• Device used : Captured using mobile phones in 2020-2022
• Usage : Identifying underpass on the roads, scene understanding and for autonomous driving vehicles.

Available Annotation formats

COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.

This dataset is collected by DataCluster Labs, India. To download full dataset or to submit a request for your new data collection needs, please drop a mail to: sales@datacluster.ai

This dataset is an extremely challenging set of over 500+ original Car Dashoard images captured and crowdsourced from over 700+ urban and rural areas, where each image is manually reviewed and verified by computer vision professionals at ****DC Labs.

Optimized for Generative AI, Visual Question Answering, Image Classification, and LMM development, this dataset provides a strong basis for achieving robust model performance.

Dataset Features

• Dataset size : 500+
• Captured by : Over 1000+ crowdsource contributors
• Resolution : 99% images HD and above (1920x1080 and above)
• Location : Captured with 700+ cities accross India
• Diversity : Various lighting conditions like day, night, varied distances, view points etc.
• Device used : Captured using mobile phones in 2020-2021
• Applications : Car Insurance, Odometer Reading, , etc.

Available Annotation formats

COCO, YOLO, PASCAL-VOC, Tf-Record

The images in this dataset are exclusively owned by Data Cluster Labs and were not downloaded from the internet. To access a larger portion of the training dataset for research and commercial purposes, a license can be purchased. Contact us at sales@datacluster.ai Visit www.datacluster.ai to know more.