Bandwidth Measurement for Conference Call Data Usage

During the first half of 2020, the COVID-19 pandemic changed the social gathering lifestyle to online business and social interaction. The worldwide imposed travel bans and national lockdown prevented social gatherings, making learning institutions and businesses to adopt an online platform for learning and business transactions. This development led to the incorporation of video conferencing into daily activities. This data article presents broadband data usage measurement collected using Glasswire software on various conference calls made between July and August. The services considered in this work are Google Meet, Zoom, Mixir, and Hangout. The data were recorded in Microsoft Excel 2016, running on a personal computer. The data was cleaned and processed using google colaboratory, which runs Python scripts on the browser. Exploratory data analysis is conducted on the data set using linear regression to model a predictive model to assess the best performance model that offers the best quality of service for online video and voice conferencing. The data is necessary to learning institutions using online programs and to learners accessing online programs in a smart city and developing countries. The data is presented in tables and graphs.2020年上半年，新型冠状病毒肺炎 (COVID-19) 大流行促使线下社交聚会的生活方式转向线上商务与社交互动。全球范围内实施的旅行禁令与国家封控措施阻断了线下社交聚集，迫使教育机构与企业转而采用线上平台开展教学活动与商务交易。这一发展趋势使得视频会议成为日常活动的重要组成部分。本数据论文呈现了2020年7月至8月期间，通过Glasswire软件采集的各类电话会议宽带数据使用量测量结果。本研究涵盖的服务平台包括Google Meet、Zoom、Mixir以及Google Hangout。所有数据均通过运行于个人计算机上的Microsoft Excel 2016进行记录。数据的清洗与处理工作依托谷歌协作平台 (Google Colaboratory) 完成，该平台可在浏览器环境中运行Python脚本。本数据集已采用线性回归开展探索性数据分析 (Exploratory Data Analysis)，构建预测模型以评估性能最优、可提供最佳在线视频与语音会议服务质量的模型。该数据集对于智慧城市与发展中国家内采用线上教学项目的教育机构，以及参与线上学习的学习者均具有重要应用价值。本数据集以表格与图表形式呈现。