TII operates and maintains a network of traffic counters on the national primary and secondary road network in Ireland. There are currently almost 300 of these counters active across the network. For an interactive view of the data they capture, go to the TII Traffic Counter Data Website nratrafficdata.ie

A complete list of live websites using the Traffic Counter Widget technology, compiled through global website indexing conducted by WebTechSurvey.

The NRA Traffic Data website presents data collected from the NRA traffic counters located on the National Road Network. The Website uses a dynamic mapping interface to allow the User to access data in a variety of report formats. Counter data includes multi-day volume, daily volume, weekly volume, average week, monthly volume, monthly summary, and hourly direction

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

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

This traffic-count data is provided by the City of Pittsburgh's Department of Mobility & Infrastructure (DOMI). Counters were deployed as part of traffic studies, including intersection studies, and studies covering where or whether to install speed humps. In some cases, data may have been collected by the Southwestern Pennsylvania Commission (SPC) or BikePGH.

Data is currently available for only the most-recent count at each location.

Traffic count data is important to the process for deciding where to install speed humps. According to DOMI, they may only be legally installed on streets where traffic counts fall below a minimum threshhold. Residents can request an evaluation of their street as part of DOMI's Neighborhood Traffic Calming Program. The City has also shared data on the impact of the Neighborhood Traffic Calming Program in reducing speeds.

Different studies may collect different data. Speed hump studies capture counts and speeds. SPC and BikePGH conduct counts of cyclists. Intersection studies included in this dataset may not include traffic counts, but reports of individual studies may be requested from the City. Despite the lack of count data, intersection studies are included to facilitate data requests.

Data captured by different types of counting devices are included in this data. StatTrak counters are in use by the City, and capture data on counts and speeds. More information about these devices may be found on the company's website. Data includes traffic counts and average speeds, and may also include separate counts of bicycles.

Tubes are deployed by both SPC and BikePGH and used to count cyclists. SPC may also deploy video counters to collect data.

NOTE: The data in this dataset has not updated since 2021 because of a broken data feed. We're working to fix it.

In 2024, most of the global website traffic was still generated by humans, but bot traffic is constantly growing. Fraudulent traffic through bad bot actors accounted for 37 percent of global web traffic in the most recently measured period, representing an increase of 12 percent from the previous year. Sophistication of Bad Bots on the rise The complexity of malicious bot activity has dramatically increased in recent years. Advanced bad bots have doubled in prevalence over the past 2 years, indicating a surge in the sophistication of cyber threats. Simultaneously, the share of simple bad bots drastically increased over the last years, suggesting a shift in the landscape of automated threats. Meanwhile, areas like food and groceries, sports, gambling, and entertainment faced the highest amount of advanced bad bots, with more than 70 percent of their bot traffic affected by evasive applications. Good and bad bots across industries The impact of bot traffic varies across different sectors. Bad bots accounted for over 50 percent of the telecom and ISPs, community and society, and computing and IT segments web traffic. However, not all bot traffic is considered bad. Some of these applications help index websites for search engines or monitor website performance, assisting users throughout their online search. Therefore, areas like entertainment, food and groceries, and even areas targeted by bad bots themselves experienced notable levels of good bot traffic, demonstrating the diverse applications of benign automated systems across different sectors.

Context

The data presented here was obtained in a Kali Machine from University of Cincinnati,Cincinnati,OHIO by carrying out packet captures for 1 hour during the evening on Oct 9th,2023 using Wireshark.This dataset consists of 394137 instances were obtained and stored in a CSV (Comma Separated Values) file.This large dataset could be used utilised for different machine learning applications for instance classification of Network traffic,Network performance monitoring,Network Security Management , Network Traffic Management ,network intrusion detection and anomaly detection.

The dataset can be used for a variety of machine learning tasks, such as network intrusion detection, traffic classification, and anomaly detection.

Content :

This network traffic dataset consists of 7 features.Each instance contains the information of source and destination IP addresses, The majority of the properties are numeric in nature, however there are also nominal and date kinds due to the Timestamp.

The network traffic flow statistics (No. Time Source Destination Protocol Length Info) were obtained using Wireshark (https://www.wireshark.org/).

Dataset Columns:

No : Number of Instance. Timestamp : Timestamp of instance of network traffic Source IP: IP address of Source Destination IP: IP address of Destination Portocol: Protocol used by the instance Length: Length of Instance Info: Information of Traffic Instance

Acknowledgements :

I would like thank University of Cincinnati for giving the infrastructure for generation of network traffic data set.

Ravikumar Gattu , Susmitha Choppadandi

Inspiration : This dataset goes beyond the majority of network traffic classification datasets, which only identify the type of application (WWW, DNS, ICMP,ARP,RARP) that an IP flow contains. Instead, it generates machine learning models that can identify specific applications (like Tiktok,Wikipedia,Instagram,Youtube,Websites,Blogs etc.) from IP flow statistics (there are currently 25 applications in total).

**Dataset License: ** CC0: Public Domain

Dataset Usages : This dataset can be used for different machine learning applications in the field of cybersecurity such as classification of Network traffic,Network performance monitoring,Network Security Management , Network Traffic Management ,network intrusion detection and anomaly detection.

ML techniques benefits from this Dataset :

This dataset is highly useful because it consists of 394137 instances of network traffic data obtained by using the 25 applications on a public,private and Enterprise networks.Also,the dataset consists of very important features that can be used for most of the applications of Machine learning in cybersecurity.Here are few of the potential machine learning applications that could be benefited from this dataset are :

1. Network Performance Monitoring : This large network traffic data set can be utilised for analysing the network traffic to identifying the network patterns in the network .This help in designing the network security algorithms for minimise the network probelms.

2. Anamoly Detection : Large network traffic dataset can be utilised training the machine learning models for finding the irregularitues in the traffic which could help identify the cyber attacks.

3.Network Intrusion Detection : This large dataset could be utilised for machine algorithms training and designing the models for detection of the traffic issues,Malicious traffic network attacks and DOS attacks as well.

For further information about traffic counters - see the City of York Council website

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.

This dataset contains the Department of Transport and Main Roads road location details (both spatial and through distance) as well as associated traffic data.

It allows users to locate themselves with respect to road section number and through distance using the spatial coordinates on the state-controlled road network.

Through distance – the distance in kilometres measured from the gazetted start point of the road section.

Note: "Road location and traffic data" resource has been updated as of June 2025.

The FDOT Annual Average Daily Traffic feature class provides spatial information on Annual Average Daily Traffic section breaks for the state of Florida. In addition, it provides affiliated traffic information like KFCTR, DFCTR and TFCTR among others. This dataset is maintained by the Transportation Data & Analytics office (TDA). The source spatial data for this hosted feature layer was created on: 07/12/2025.Download Data: Enter Guest as Username to download the source shapefile from here: https://ftp.fdot.gov/file/d/FTP/FDOT/co/planning/transtat/gis/shapefiles/aadt.zip

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

The global Network Traffic Monitor market was valued at USD 1.2 billion in 2025 and is expected to reach USD 2.4 billion by 2033, exhibiting a CAGR of 7.8% during the forecast period. The increasing demand for network visibility and performance monitoring, growing adoption of cloud computing, and the proliferation of IoT devices are the major factors driving the market growth. The market is segmented by application into IT services, telecommunication, banking, and others. The IT services segment held the largest market share in 2025 and is projected to continue its dominance throughout the forecast period. The growing demand for network monitoring services from IT service providers is attributed to the increasing complexity of IT infrastructures and the need to ensure optimal network performance. The telecommunication segment is also expected to witness significant growth, driven by the increasing deployment of 5G networks and the need to monitor network performance and security.

The data included in the GIS Traffic Stations Version database have been assimilated from station description files provided by FHWA for Weigh-in-Motion (WIM), and Automatic Traffic Counters (ATR). Location referencing information was derived from the National Highway Planning Network version 4.0.and State offices of Transportation.

The global Network Traffic Monitoring market is experiencing robust growth, driven by the increasing adoption of cloud computing, the proliferation of IoT devices, and the rising need for enhanced network security. The market, estimated at $15 billion in 2025, is projected to achieve a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching approximately $45 billion by 2033. Key drivers include the imperative for businesses to optimize network performance, ensure compliance with data regulations, and proactively mitigate cyber threats. The growing complexity of network infrastructures, fueled by digital transformation initiatives across various sectors—including IT services, telecommunications, and banking—is significantly contributing to this growth. Furthermore, the transition to hybrid and multi-cloud environments necessitates sophisticated network traffic monitoring solutions capable of providing comprehensive visibility and control across diverse network topologies. While the initial investment in network monitoring solutions can be a restraint for smaller organizations, the long-term cost savings in terms of improved network efficiency and reduced downtime often outweigh these initial costs. The market segmentation reveals a strong demand for both SaaS and PaaS solutions, with SaaS gaining popularity due to its ease of deployment and scalability. Geographically, North America currently holds the largest market share, followed by Europe and Asia Pacific. However, the Asia Pacific region is anticipated to demonstrate the fastest growth rate during the forecast period, driven by increasing digitalization and infrastructure development in countries like China and India. The competitive landscape is marked by a mix of established players like Cisco Systems and IBM, and emerging vendors offering innovative solutions. The market’s future growth will be significantly shaped by advancements in AI-powered analytics, the integration of network traffic monitoring with security information and event management (SIEM) systems, and the increasing demand for real-time network visibility and anomaly detection. The continued evolution of network technologies and the rise of 5G will further fuel the demand for advanced network traffic monitoring tools.

Network Traffic Analysis Solutions Market Outlook

The global network traffic analysis solutions market size was estimated at USD 3.5 billion in 2023 and is projected to reach USD 9.8 billion by 2032, reflecting a compound annual growth rate (CAGR) of 12.1%. This substantial growth is largely driven by the increasing demand for robust cybersecurity measures across various sectors. With an ever-growing volume of network traffic due to the proliferation of connected devices and the adoption of digital transformation initiatives, organizations are compelled to deploy sophisticated traffic analysis tools to effectively monitor, manage, and secure their networks. The expansion of cloud services, coupled with the rise in cyber threats, further accentuates the need for advanced traffic analysis capabilities.

The surge in cyber threats, including sophisticated hacking techniques and ransomware attacks, has become a pivotal growth factor for the network traffic analysis solutions market. As organizations strive to protect sensitive data and ensure the integrity of their networks, there is a heightened demand for solutions that can provide real-time visibility and control over network traffic. This growing emphasis on cybersecurity is not limited to large enterprises but is increasingly becoming a priority for small and medium enterprises (SMEs) as well. Consequently, the increasing cyber threat landscape is stimulating the adoption of network traffic analysis solutions across different organizational sizes, driving market growth.

Moreover, the rise of Internet of Things (IoT) devices is significantly contributing to the increased need for network traffic analysis. IoT devices generate vast amounts of data that need to be managed effectively to prevent network congestion and potential security breaches. By leveraging traffic analysis solutions, organizations can optimize IoT device performance and ensure seamless data flow while maintaining robust security protocols. As the IoT ecosystem continues to expand, it is expected to further fuel the demand for network traffic analysis solutions, facilitating better management and security of network resources.

In addition to cybersecurity concerns and IoT proliferation, regulatory compliance is another critical growth driver for the network traffic analysis solutions market. Organizations across various industries, such as BFSI, healthcare, and government sectors, are under increasing pressure to comply with stringent data protection regulations. Network traffic analysis solutions help these organizations monitor compliance effectively by providing detailed insights into network activity and data flows. As regulations continue to evolve and become more complex, the role of network traffic analysis solutions in ensuring compliance and mitigating risks is expected to become increasingly important, further bolstering market growth.

Network Telemetry Solutions are becoming increasingly essential in the realm of network traffic analysis. These solutions provide real-time data collection and analysis, enabling organizations to gain deeper insights into their network operations. By leveraging network telemetry, businesses can proactively identify and address potential issues before they escalate into significant problems. This capability is particularly valuable in today's fast-paced digital environment, where network performance and security are critical to maintaining operational efficiency. As the demand for more granular visibility into network activities grows, network telemetry solutions are poised to play a pivotal role in enhancing the capabilities of traffic analysis tools, offering a more comprehensive approach to network management and security.

From a regional perspective, North America is anticipated to maintain a dominant position in the network traffic analysis solutions market. This can be attributed to the presence of major technology companies, a high adoption rate of advanced technologies, and stringent cybersecurity regulations. The region's established digital infrastructure and focus on innovation also contribute to market growth. Meanwhile, the Asia Pacific region is projected to witness the highest growth rate due to rapid digitalization, increasing internet penetration, and growing investments in IT infrastructure. As businesses in this region continue to adopt digital technologies and face rising cyber threats, the demand for network traffic analysis solutions is expected to surge significantly.

Component Analysis</h2

In March 2025, ChatGPT.com received approximately *** billion visits from users worldwide. The most recent year under analysis has seen an increase in traffic to OpenAI's artificial intelligence chatbot. This is the highest traffic volume achieved by the site to date, with values for the most recent analyzed month exceeding twice the average monthly visits for the entire examined period between April 2023 and April 2024.

The global Network Traffic Monitoring market is experiencing robust growth, driven by the escalating demand for enhanced network visibility and security in an increasingly interconnected world. The market, currently valued at approximately $15 billion in 2025, is projected to witness a Compound Annual Growth Rate (CAGR) of 12% from 2025 to 2033, reaching an estimated market size of $45 billion by 2033. This expansion is fueled by several key factors, including the proliferation of cloud computing, the rise of the Internet of Things (IoT), and the increasing prevalence of sophisticated cyber threats. Businesses across various sectors, including IT services, telecommunications, and banking, are adopting network traffic monitoring solutions to optimize network performance, enhance security posture, and ensure regulatory compliance. The market is segmented by deployment model (SaaS and PaaS) and application (IT Services, Telecommunications, Banking, and Others), each contributing uniquely to the overall market growth. The increasing adoption of cloud-based solutions and the demand for advanced analytics are also major catalysts. The competitive landscape is characterized by the presence of established players like Cisco Systems, IBM, and SolarWinds, alongside emerging technology providers such as Auvik and ManageEngine. These companies are continually innovating to offer advanced features like AI-powered anomaly detection, real-time threat intelligence, and enhanced network visualization capabilities. The geographical distribution of the market shows strong growth across North America and Europe, driven by high technological adoption rates and stringent data security regulations. However, Asia-Pacific is expected to witness significant growth in the coming years, fueled by rapid digital transformation and infrastructure development in countries like India and China. Market restraints include the complexity of implementing and managing these solutions, along with the high initial investment costs. However, the long-term benefits of improved network efficiency and enhanced security are overriding these concerns, leading to a sustained and positive market trajectory.

The Annual Average Daily Traffic (AADT) for sections of roads for all vehicle types, including single and combination trucks, reported in the 2023 Highway Performance Monitoring System (HPMS) federal report.Annual Average Daily Traffic (AADT) is used to represent vehicle traffic on a typical day of the year and is important for planning purposes, such as defining the federal functional classification of a roadway. The values are calculated using data collected from traffic counter devices, such as Automatic Traffic Recorders (ATR), Weigh In Motion (WIM) devices, and short term counters using tubes. All available traffic data collected throughout the year are then summed and divided by 365 to calculate the annual average daily traffic.Single unit trucks are any trucks that meets the requirements established for the FHWA Truck Classification Method for Categories 4 through 7. Combination unit trucks are any trucks that meets the requirements established for the FHWA Truck Classification Method for Categories 8 through 13. Refer to the Federal Highway Administration website for more information about truck classifications.Reported Extent: State Highway System (i.e. all ADOT-owned roads), National Highway System (NHS), and all federal aid-eligible roads. Federal aid-eligible roads include urban roads classified as minor collectors or above (functional system 1-6) and rural roads classified as major collectors or above (function system 1-5). Roads where ATRs are available, counts are updated annually. For roads where short term counters must be used, traffic counts are collected every three years for all National Highway System (NHS) roads as well as interstates (functional system 1), principal arterials (functional systems 2-3), and sample panel sections. All other federal aid-eligible roads, including minor arterials and collectors, are collected every six years.For undivided highways, which do not have a physical barrier between the two directions of traffic, values are reported as the sum total for both directions of travel. On divided highways, AADT is reported separately on the cardinal and non-cardinal directions of the roadway. Note, the cardinal direction refers to the direction of increasing mileposts.