Between December 2022 and January 2024, ******** was the online learning platform reporting the highest traffic, with a peak of *** million visits to its websites in December 2023. ******** ranked second, with the platform reaching a peak of ** million visits in the examined period. The website ******* (which stands for technology, entertainment, design) saw a peak of over ** million visits in March 2023.

Internet traffic volume measures global IP traffic, or the amount of data being sent and received over the internet globally each month. Data and forecasts are sourced from Cisco Systems Inc.

This dataset consists of 24-hour traffic volumes which are collected by the City of Tempe high (arterial) and low (collector) volume streets. Data located in the tabular section shares with its users total volume of vehicles passing through the intersection selected along with the direction of flow.Historical data from this feature layer extends from 2016 to present day.Contact: Sue TaaffeContact E-Mail: sue_taaffe@tempe.govContact Phone: 480-350-8663Link to embedded web map:http://www.tempe.gov/city-hall/public-works/transportation/traffic-countsLink to site containing historical traffic counts by node: https://gis.tempe.gov/trafficcounts/Folders/Data Source: SQL Server/ArcGIS ServerData Source Type: GeospatialPreparation Method: N/APublish Frequency: As information changesPublish Method: AutomaticData Dictionary

This statistic shows the total business internet data traffic in the United States from 2016 to 2023. In 2017, total business internet traffic volume amounted to 56.7 billion gigabytes in the United States.

A collection of historic traffic count data and guidelines for how to collect new data for Massachusetts Department of Transportation (MassDOT) projects.

Annual average daily traffic is the total volume for the year divided by 365 days. The traffic count year is from October 1st through September 30th. Very few locations in California are actually counted continuously. Traffic Counting is generally performed by electronic counting instruments moved from location throughout the State in a program of continuous traffic count sampling. The resulting counts are adjusted to an estimate of annual average daily traffic by compensating for seasonal influence, weekly variation and other variables which may be present. Annual ADT is necessary for presenting a statewide picture of traffic flow, evaluating traffic trends, computing accident rates. planning and designing highways and other purposes.Traffic Census Program Page

Traffic Volumes from SCATS Traffic Management System Jan-Jun 2025 DCC. Published by Dublin City Council. Available under the license cc-by (CC-BY-4.0).Traffic volumes data across Dublin City from the SCATS traffic management system. The Sydney Coordinated Adaptive Traffic System (SCATS) is an intelligent transportation system used to manage timing of signal phases at traffic signals. SCATS uses sensors at each traffic signal to detect vehicle presence in each lane and pedestrians waiting to cross at the local site. The vehicle sensors are generally inductive loops installed within the road.

3 resources are provided:

SCATS Traffic Volumes Data (Monthly) Contained in this report are traffic counts taken from the SCATS traffic detectors located at junctions. The primary function for these traffic detectors is for traffic signal control. Such devices can also count general traffic volumes at defined locations on approach to a junction. These devices are set at specific locations on approaches to the junction but may not be on all approaches to a junction. As there are multiple junctions on any one route, it could be expected that a vehicle would be counted multiple times as it progress along the route. Thus the traffic volume counts here are best used to represent trends in vehicle movement by selecting a specific junction on the route which best represents the overall traffic flows.

Information provided:

End Time: time that one hour count period finishes.

Region: location of the detector site (e.g. North City, West City, etc).

Site: this can be matched with the SCATS Sites file to show location

Detector: the detectors/ sensors at each site are numbered

Sum volume: total traffic volumes in preceding hour

Avg volume: average traffic volumes per 5 minute interval in preceding hour

All Dates Traffic Volumes Data

This file contains daily totals of traffic flow at each site location.

SCATS Site Location Data Contained in this report, the location data for the SCATS sites is provided. The meta data provided includes the following;

Site id – This is a unique identifier for each junction on SCATS

Site description( CAP) – Descriptive location of the junction containing street name(s) intersecting streets

Site description (lower) - – Descriptive location of the junction containing street name(s) intersecting streets

Region – The area of the city, adjoining local authority, region that the site is located

LAT/LONG – Coordinates

Disclaimer: the location files are regularly updated to represent the locations of SCATS sites under the control of Dublin City Council. However site accuracy is not absolute. Information for LAT/LONG and region may not be available for all sites contained. It is at the discretion of the user to link the files for analysis and to create further data. Furthermore, detector communication issues or faulty detectors could also result in an inaccurate result for a given period, so values should not be taken as absolute but can be used to indicate trends....

Abstract: The task for this dataset is to forecast the spatio-temporal traffic volume based on the historical traffic volume and other features in neighboring locations.

Source: Liang Zhao, liang.zhao '@' emory.edu, Emory University.

Data Set Information: The task for this dataset is to forecast the spatio-temporal traffic volume based on the historical traffic volume and other features in neighboring locations. Specifically, the traffic volume is measured every 15 minutes at 36 sensor locations along two major highways in Northern Virginia/Washington D.C. capital region. The 47 features include: 1) the historical sequence of traffic volume sensed during the 10 most recent sample points (10 features), 2) week day (7 features), 3) hour of day (24 features), 4) road direction (4 features), 5) number of lanes (1 feature), and 6) name of the road (1 feature). The goal is to predict the traffic volume 15 minutes into the future for all sensor locations. With a given road network, we know the spatial connectivity between sensor locations. For the detailed data information, please refer to the file README.docx.

Attribute Information: The 47 features include: (1) the historical sequence of traffic volume sensed during the 10 most recent sample points (10 features), (2) week day (7 features), (3) hour of day (24 features), (4) road direction (4 features), (5) number of lanes (1 feature), and (6) name of the road (1 feature).

Relevant Papers: Liang Zhao, Olga Gkountouna, and Dieter Pfoser. 2019. Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. ACM Trans. Spatial Algorithms Syst. 5, 3, Article 19 (August 2019), 28 pages. DOI:[Web Link]

Citation Request: To use these datasets, please cite the papers:

Liang Zhao, Olga Gkountouna, and Dieter Pfoser. 2019. Spatial Auto-regressive Dependency Interpretable Learning Based on Spatial Topological Constraints. ACM Trans. Spatial Algorithms Syst. 5, 3, Article 19 (August 2019), 28 pages. DOI:[Web Link]

Annualized, Hourly and Classification count data for the TPB modeled region. Data are collected from state DOTs and processed by TPB staff.Layers IncludedAnnualized Traffic Volumes Historic AADT by Count Station This database contains the Annual Average Daily Traffic (AADT) estimates reported at permanent and short term counting stations in the TPB modeled region. Please note: Interstates in Virginia are typically represented by two stations (one in each direction) while Interstates in the other states are represented by one station. Therefore, the AADT estimates displayed for the stations on Virginia Intestates will be around half of the total for the directional roadway. The AADT estimates for recent years in this file are based on counts taken at the actual count station locations that are indicated by the station points. The AADT estimates for earlier years are based on volumes reported along roadway segments that the station points currently represent. Specific data sources for each state are listed below:District of ColumbiaAADT estimates since 2006 are based on counts taken at the station locations in the file for purpose of Federal HPMS reporting.AADT estimates prior to 2006 are based on Traffic Volume maps produced by DDOT (Formerly DC DPW).MarylandAADT estimates since 2000 are based on counts taken at the station locations in the file and reported by MD SHA.AADT estimates prior to 2000 are based on volumes reported by MD SHA in the Highway Location Reference documents and matched to links in the COG/TPB highway network. The volumes are shown at the count locations that currently represent those network links.VirginiaAADT estimates since 1997 are based on counts taken at the station locations in the file and reported by VDOT.AADT estimates prior to 1997 are based on volumes reported by VDOT in the Average Daily Traffic Volumes documents and matched to links in the COG/TPB highway network. The volumes are shown at the count locations that currently represent those network links.West VirginiaAADT estimates since 1999 are based on counts taken at the station locations in the file and reported by WV DOT.Traffic Counts by Network LinkThis layer was created by assigning the state DOT traffic counting station locations to their corresponding COG/TPB network links. Facility names and route numbers were added to the network. AADT Average Annual Daily Traffic (2010 - 2021), AAWDT Average Annual Weekday Daily Traffic (2010 - 2021) and Count Type (2010 - 2021) are included as well as Count Year (last year the link was counted). Count Type denotes the source of the count. Please note: for bi-directional roads, the AADT and AAWDT values for each location were divided in two and assigned to both network links that represent the Anode-Bnode direction and the Bnode-Anode direction. Therefore, in most cases the AADT/AAWDT values associated with an individual link in this network will be half of the AADT/AAWDT values reported at the associated individual count station point. Traffic Counts by External StationThis layer was created by placing points where major facilities cross the TPB Modeled Area boundary. In some cases, the external station represents more than one facility. The facility field indicates which road or roads the station represents. AADT and AAWDT estimates at external stations are provided for 2007 through 2023. Each external station is assigned to a state DOT traffic counting station(s). An effort was made to assign stations or combinations of stations that would come closest to measuring the traffic volume on each facility as it enters/exits the region. In some cases, these volumes are measured just inside the modeled area; in other cases, the volumes are measured just outside the modeled area. The external stations around the Baltimore Beltway are exceptions to this rule. These stations all measure the traffic just south of the Baltimore Beltway in order lessen the influence of traffic specific to Baltimore. AADT Average Annual Daily Traffic (2007 – 2023) and AAWDT Average Annual Weekday Daily Traffic (2007 – 2023) are included. Count Type denotes when the location was last counted. West Virginia does not report AAWDT, so the AADT values were increased by 5% to arrive at AAWDT estimates in West Virginia.

This data set features a hyperlink to the New York State Department of Transportation’s (NYSDOT) Traffic Data (TD) Viewer web page, which includes a link to the Traffic Data interactive map. The Traffic Data Viewer is a geospatially based Geographic Information System (GIS) application for displaying data contained in the roadway inventory database. The interactive map has five viewable data categories or ‘layers’. The five layers include: Average Daily Traffic (ADT); Continuous Counts; Short Counts; Bridges; and Grade Crossings throughout New York State.

Average Annual Daily Traffic data for use with GIS mapping software, databases, and web applications are from Caliper Corporation and contain data on the total volume of vehicle traffic on a highway or road for a year divided by 365 days.

Click Web Traffic Combined with Transaction Data: A New Dimension of Shopper Insights

Consumer Edge is a leader in alternative consumer data for public and private investors and corporate clients. Click enhances the unparalleled accuracy of CE Transact by allowing investors to delve deeper and browse further into global online web traffic for CE Transact companies and more. Leverage the unique fusion of web traffic and transaction datasets to understand the addressable market and understand spending behavior on consumer and B2B websites. See the impact of changes in marketing spend, search engine algorithms, and social media awareness on visits to a merchant’s website, and discover the extent to which product mix and pricing drive or hinder visits and dwell time. Plus, Click uncovers a more global view of traffic trends in geographies not covered by Transact. Doubleclick into better forecasting, with Click.

Consumer Edge’s Click is available in machine-readable file delivery and enables: • Comprehensive Global Coverage: Insights across 620+ brands and 59 countries, including key markets in the US, Europe, Asia, and Latin America. • Integrated Data Ecosystem: Click seamlessly maps web traffic data to CE entities and stock tickers, enabling a unified view across various business intelligence tools. • Near Real-Time Insights: Daily data delivery with a 5-day lag ensures timely, actionable insights for agile decision-making. • Enhanced Forecasting Capabilities: Combining web traffic indicators with transaction data helps identify patterns and predict revenue performance.

Use Case: Analyze Year Over Year Growth Rate by Region

Problem A public investor wants to understand how a company’s year-over-year growth differs by region.

Solution The firm leveraged Consumer Edge Click data to: • Gain visibility into key metrics like views, bounce rate, visits, and addressable spend • Analyze year-over-year growth rates for a time period • Breakout data by geographic region to see growth trends

Metrics Include: • Spend • Items • Volume • Transactions • Price Per Volume

Inquire about a Click subscription to perform more complex, near real-time analyses on public tickers and private brands as well as for industries beyond CPG like: • Monitor web traffic as a leading indicator of stock performance and consumer demand • Analyze customer interest and sentiment at the brand and sub-brand levels

Consumer Edge offers a variety of datasets covering the US, Europe (UK, Austria, France, Germany, Italy, Spain), and across the globe, with subscription options serving a wide range of business needs.

Consumer Edge is the Leader in Data-Driven Insights Focused on the Global Consumer

The Traffic Volume Trends montly report is a natinal data report that provides quality controlled vehicle miles traveled data for each State for all roadways

The census count of vehicles on city streets is normally reported in the form of Average Daily Traffic (ADT) counts. These counts provide a good estimate for the actual number of vehicles on an average weekday at select street segments. Specific block segments are selected for a count because they are deemed as representative of a larger segment on the same roadway. ADT counts are used by transportation engineers, economists, real estate agents, planners, and others professionals for planning and operational analysis. The frequency for each count varies depending on City staff’s needs for analysis in any given area. This report covers the counts taken in our City during the past 12 years approximately.

TERMS OF USE 1. Restriction on the use of Material on this websiteUsage and/or downloading this data indicates Your acceptance of the terms and conditions below.The data here controlled and operated by the Corporation of the County of Lennox and Addington (referred to the “County” herein) and is protected by copyright. No part of the information herein may be sold, copied, distributed, or transmitted in any form without the prior written consent of the County. All rights reserved. Copyright 2018 by the Corporation of the County of Lennox and Addington.2. DisclaimerThe County makes no representation, warranty or guarantee as to the content, accuracy, currency or completeness of any of the information provided on this website. The County explicitly disclaims any representations, warranties and guarantees, including, without limitation, the implied warranties of merchantability and fitness for a particular purpose.3. Limitation of LiabilityThe County is not responsible for any special, indirect, incidental or consequential damages that may arise from the use of or the inability to use, any web pages and/or the materials contained on the web page whether the materials are provided by the County or by a third party. Without limiting the generality of the foregoing, the County assumes no responsibility whatsoever for: any errors omissions, or inaccuracies in the information provided, regardless of how caused; or any decision made or action taken or not taken by the reader or other third party in reliance upon any information or data furnished on any web page.The Data is provided "as is" without warranty or any representation of accuracy, timeliness or completeness. The burden for determining accuracy, completeness, timeliness, merchantability and fitness for or the appropriateness for use rests solely on the requester. Lennox and Addington County makes no warranties, express or implied, as to the use of the Data. There are no implied warranties of merchantability or fitness for a particular purpose. The requester acknowledges and accepts the limitations of the Data, including the fact that the Data is dynamic and is in a constant state of maintenance, corrections and update.

This dataset is historical. For recent data, we recommend using https://chicagotraffictracker.com. -- Average Daily Traffic (ADT) counts are analogous to a census count of vehicles on city streets. These counts provide a close approximation to the actual number of vehicles passing through a given location on an average weekday. Since it is not possible to count every vehicle on every city street, sample counts are taken along larger streets to get an estimate of traffic on half-mile or one-mile street segments. ADT counts are used by city planners, transportation engineers, real-estate developers, marketers and many others for myriad planning and operational purposes. Data Owner: Transportation. Time Period: 2006. Frequency: A citywide count is taken approximately every 10 years. A limited number of traffic counts will be taken and added to the list periodically. Related Applications: Traffic Information Interactive Map (http://webapps.cityofchicago.org/traffic/).

This traffic volumes feature class containing Traffic Volumes (also known as Traffic Counts) on California state highway network created from AADT excel spreadsheet file maintained by Caltrans, Division of Traffic Operations.Annual average daily traffic is the total volume for the year divided by 365 days. The traffic count year is from October 1st through September 30th. Very few locations in California are actually counted continuously. Traffic Counting is generally performed by electronic counting instruments moved from location throughout the State in a program of continuous traffic count sampling. The resulting counts are adjusted to an estimate of annual average daily traffic by compensating for seasonal influence, weekly variation and other variables which may be present. Annual ADT is necessary for presenting a statewide picture of traffic flow, evaluating traffic trends, computing accident rates, planning and designing highways and other purposes.

January 2024, Netflix.com generated over 412 million visits in the United States. Traffic to the SVoD platform increased by seven percent compared to the previous month. Overall, Netflix was the leading subscription video-on-demand service in terms of traffic during the examined period. Between the second half of 2022 and the beginning of 2023, search and visit volume trends on streaming sites in the market appeared to have normalized after the usage increase brought by the COVID-19 pandemic in 2020 and 2021.

Pride month is celebrated in the United States annually in June as an occasion to honor LGBTQ+ communities and identities. In April 2021, the majority of the web traffic derived by the keyword "Pride month" came from health websites, accounting for a 54.5 percent share. Government sites ranked second, with 23.7 percent of paid and organic traffic combined. E-commerce websites accounted for ten percent of total traffic for the keyword.

A detailed listing outlining the 23 year history (1988-2010) of traffic volumes on Provincial Highways (King's, Secondary, Tertiary Roads and the 7000 series highways). The highway network is divided into approximately 1600 sections for reporting purposes. Seasonal traffic volume variations are estimated for each section. Although local conditions cause variations, the volumes shown are considered to adequately represent the section. On highways that overlap one another (e.g. Highway 35 and Highway 115) the volume information is referenced to the lower number highway. When an overlap occurs between a freeway and non-freeway, reference is made to the freeway route number. The freeways are Highway 400 to Highway 427 and the Queen Elizabeth Way. *[e.g.]: for example