Dataset Overview

This dataset was collected between September 2023 and September 2024 and focuses solely on Wi-Fi network performance for AT&T customers. The data includes critical network performance metrics such as download speeds, upload speeds, and the status of the internet connection (connected/disconnected) at various times of day. The dataset provides valuable insights into the performance of Wi-Fi networks across different environments, although the specific locations or device types are not specified.

Features:

Time: The exact timestamp (in UTC) when the measurement was taken. Download_Mbps: The download speed, measured in Megabits per second (Mbps), representing the speed at which data is received. Upload_Mbps: The upload speed, also in Megabits per second (Mbps), indicating the speed at which data is sent. Connected: A binary indicator (0 or 1) that shows whether the Wi-Fi was connected at the time of the test (1 = connected, 0 = disconnected).

Data Context:

This dataset is limited to Wi-Fi connections, representing the experiences of users across various environments such as homes, offices, or public spaces. Although the data lacks specific details about the geographic locations or device types, it can still provide meaningful insights into how Wi-Fi network performance fluctuates based on time and potential external factors. The absence of detailed source information suggests the data may have been gathered through an automated network monitoring tool, possibly as part of a routine diagnostic or performance test process within a specific set of environments using AT&T's services.

Possible Data Collection Scenario (Assumed):

The data could have been collected by Wi-Fi-enabled devices (such as laptops, smartphones, or routers) periodically running speed tests to measure both download and upload performance. These measurements likely occurred across a variety of settings, though no explicit details are provided about whether the environment is residential, commercial, or public. Given that the dataset focuses exclusively on Wi-Fi, it's reasonable to assume that this data could have been gathered either by end-users manually running tests or via automated diagnostics by a network monitoring system designed to track connectivity performance.

Limitations and Assumptions:

No Geographic Data: While the dataset includes performance metrics, it does not provide any information about the geographic locations or regions where the data was collected. Wi-Fi Focus: The data is solely related to Wi-Fi connections, and no other connection types (such as Ethernet or mobile data) are included. Unspecified Source: The source of the data is not clearly documented, which means the scope of the environments (home, public, or enterprise) and the methods of collection are unknown.

Potential Use Cases:

Wi-Fi Performance Analysis: This dataset can be used to analyze how download and upload speeds vary over time, which may reflect broader network trends such as congestion, interference, or router quality. Connectivity Prediction: Machine learning models can be developed to predict the likelihood of disconnections based on patterns in speed fluctuations. Time-Based Network Optimization: Telecom companies or network administrators can use the dataset to understand peak hours of usage and optimize network performance accordingly.

Insights to Explore:

Time of Day Analysis: Investigate whether certain times of day exhibit higher speeds or more frequent disconnections, potentially revealing periods of peak demand. Download vs. Upload Discrepancies: Explore how download and upload speeds differ and what this might imply for different types of internet usage (e.g., video streaming vs. video conferencing).

Network Reliability: Examine the proportion of time users were disconnected from the Wi-Fi and look for patterns that might suggest technical issues or environmental interference.

Routes, Stops, Park & Rides for Project Connect. This data is for informational purposes only and are subject to change.

This dataset includes the number of service connections, categorized by type and metering status, as submitted by public water systems via the electronic annual report (eAR) in sections 3 or 4 for calendar years 2013 through 2023 reporting year. It also includes facility public information details from the SDWIS database as metadata associated to the dataset. “Service connection” means the point of connection between the customer’s piping or constructed conveyance, and the water system’s meter, service pipe, or constructed conveyance. “Public water system” means a system for the provision of water for human consumption through pipes or other constructed conveyances that has 15 or more service connections or regularly serves at least 25 individuals daily at least 60 days out of the year. Public water systems submit critical water system information intended to assess the status of compliance with specific regulatory requirements such as source water capacity, provides updated contact and inventory information (such as population and number of service connections) to the to the Division of Drinking Water using the electronic Annual Report (eAR) submission process. The data in the datasets below are electronically reported annually by public water systems to the State Water Resources Control Board - Division of Drinking Water. The data contained herein are public water system reported data and do not include a determination of accuracy or validity by regulatory staff. For data validated by regulatory staff, refer to the public water system inventory dataset from the Safe Drinking Water Information System (SDWIS), available at: https://data.ca.gov/dataset/drinking-water-public-water-system-information. For more information about the eAR, visit the eAR Home Page: https://www.waterboards.ca.gov/drinking_water/certlic/drinkingwater/ear.html

This statistic presents the monthly number of mobile data connections in Spain from January 2016 to September 2022. The number of data connections decreased from **** million in January 2016 to **** million as of September 2022.

The Road and Path Networks are not topologically structured together. Connecting Links have been introduced to enable a connection between the Road Network and the Path Network without splitting the Road Network. A Connecting Link feature is a linear spatial object which represents a logical connection between the Path Network and the Road Network, and they do represent a feature in the real world. A Connecting Link will always reference a Path Node and a Connecting Node.

This dataset contains the number of low carbon technology connections to the National Grid Electricity Distribution network aggregated by primary substation, low carbon technology type and month for the period from April 2017

Connect Chicago was a loose network of more than 250 places in the city where internet and computer access, digital skills training, and online learning resources are available—for free.

This data set represents all the available details for every location. The content is updated regularly by site administrators and location managers.

This dataset contains an open and curated scholarly graph we built as a training and test set for data discovery, data connection, author disambiguation, and link prediction tasks. This graph represents the European Marine Science community included in the OpenAIRE Graph. The nodes of the graph we release represent publications, datasets, software, and authors respectively; edges interconnecting research products always have the publication as source, and the dataset/software as target. In addition, edges are labeled with semantics that outline whether the publication is referencing, citing, documenting, or supplementing the related outcome. To curate and enrich nodes metadata and edges semantics, we relied on the information extracted from the PDF of the publications and the datasets/software webpages respectively. We curated the authors so to remove duplicated nodes representing the same person. The resource we release counts 4,047 publications, 5,488 datasets, 22 software, 21,561 authors, and 9,692 edges connect publications to datasets/software. This graph is in the curated_MES folder. We provide this resource as: a property graph: we provide the dump that can be imported in neo4j 5 jsonl files containing publications, datasets, software, authors, and relationships respectively. Each line of a jsonl file contains a JSON object representing a node and contains the metadata of that node (or a relationship). We provide two additional scholarly graphs: The curated MES graph with the removed edges. During the curation we removed some edges since they were labeled with an inconsistent or imprecise semantics. This graph includes the same nodes and edges as the previous one, and, in addition, it contains the edges removed during the curation pipeline; these edges are marked as Removed. This graph is in the curated_MES_with_removed_semantics folder. The original MES community of OpenAIRE. It represents the MES community extracted from the OpenAIRE Research Graph. This graph has not been curated, and the metadata and semantics are those of the OpenAIRE Research Graph. This graph is in the original_MES_community folder.

The Smart Cities and Communities Task Force, a body under the NITRD Cyber-Physical Systems Interagency Working Group, developed Connecting and Securing Communities to provide Federal agencies with guidance in supporting research, development, demonstration, and deployment (RDD&D) of technology to enable U.S. cities and communities to build “smart” infrastructure, systems, and services. Five high-level recommended practices are provided to inform Federal agencies in supporting smart city and community efforts. Four effective approaches, illustrated by case studies from current and past Federal programs and projects, are provided to assist agencies in facilitating job growth and economic prosperity through Federally funded RDD&D in smart cities and communities. Connecting and Securing Communities envisions Federal agencies working with industry, local leaders, civil society, academia, and other key stakeholders to accelerate the development and implementation of new discoveries and innovations that enable cities and communities to achieve their local goals and address their most important challenges.

In 2022, the average data volume per broadband connection amounted to roughly ***** gigabytes per month. This statistic shows the average monthly data volume per broadband internet connection in Germany from 2001 to 2022, with an estimate for 2023.

Comprehensive dataset containing 19 verified Connect locations in United States with complete contact information, ratings, reviews, and location data.

Are there computers in the classroom? Does it matter? Students, Computers and Learning: Making the Connection examines how students’ access to and use of information and communication technology (ICT) devices has evolved in recent years, and explores how education systems and schools are integrating ICT into students’ learning experiences. Based on results from PISA 2012, the report discusses differences in access to and use of ICT – what are collectively known as the “digital divide” – that are related to students’ socio-economic status, gender, geographic location, and the school a child attends. The report highlights the importance of bolstering students’ ability to navigate through digital texts. It also examines the relationship among computer access in schools, computer use in classrooms, and performance in the PISA assessment. As the report makes clear, all students first need to be equipped with basic literacy and numeracy skills so that they can participate fully in the hyper-connected, digitised societies of the 21st century.

A survey conducted in October 2024 shows that ***percent of the respondents saw no improvement of data connection when switching their mobile network from ** and ** to **. While ***percent of respondents declared that the ** network quality was significantly faster in comparison to their previous mobile services.

Local authority ESB Connections do not include second-hand houses acquired by them. New units acquired under Part V, Planning & Development Acts 2000-2008 for local authority rental purposes are included. Voluntary & co-operative housing consists of housing provided under the capital loan & subsidy and capital assistance schemes. Data on this variable was not available until 1993. ESB Connections data series are based on the number of new dwellings connected by ESB Networks to the electricity supply and may not accord precisely with local authority boundaries. These represent the number of homes completed and available, and do not reflect any work-in progress. For 2005Q1, direct comparisons cannot be made with 2006, as those figures included some units built in 2005. ESB Networks have indicated that there was a higher backlog in work-in-progress in 2005 than usual ( estimated as being in the region of 5,000 units). This backlog was cleared through the connection of an additional 2,000 houses in Quarter 1 2006 and 3,000 houses in Quarter 2 2006. Due to circumstances beyond the Department's control it has not been possible to obtain a separate set of figures for the first two quarters of 2005. Direct comparisons cannot be made between pre 2009 and post 2010 data onwards. Up to 2010, completions relating to long term voids and demountables were included as new build completions. For 2009Q1, 2011Q1 and 2011 Q3, discrepencies in these quarters is explained in the Qtrly hse compls-sector county tab The most current data is published on these sheets. Previously published data may be subject to revision. Any change from the originally published data will be highlighted by a comment on the cell in question. These comments will be maintained for at least a year after the date of the value change. 2010 Q4 figure for Social Housing-Voluntary & Co-operative Housing; Malcolm Hillis - (DECLG): changed from 258 to 270 as 12 units ommitted from original 2010 figures 18/11/15 2015 Q3 figure for Social Housing – LA Housing; This was previously 8. It was changed on the 27-4-16 when revised data was received by the Department. .hidden { display: none }

Licensed under: Creative Commons Attribution 4.0

The statistic shows estimated data traffic per mobile connection in the United States from 2016 to 2020. In 2016, mobile data traffic per connection was estimated to amount to ***** megabytes per month.

The connection securing process (L4) between a digital word terminal (PDA2) and local information network (WLAN2) coupled to a mobile telephone network with an authentication center (AU2) has a relay (L3) between a digital word terminal (PDA2) and the mobile telephone terminal (T2). There is a card to process the radio connection (SIM3). The same procedure is applied at the mobile telephone terminal, and the result transferred to the digital word terminal.

This dataset provides information about the number of properties, residents, and average property values for Connecting Road cross streets in Islandia, NY.

Comprehensive dataset containing 33 verified The Connection locations in United States with complete contact information, ratings, reviews, and location data.