This dataset contains about 140,000 Tweets related to exoskeletons. that were mined for a period of 5-years from May 21, 2017, to May 21, 2022. The tweets contain diverse forms of communications and conversations which communicate user interests, user perspectives, public opinion, reviews, feedback, suggestions, etc., related to exoskeletons.
The dataset contains only tweet identifiers (Tweet IDs) due to the terms and conditions of Twitter to re-distribute Twitter data ONLY for research purposes. They need to be hydrated to be used. The process of retrieving a tweet's complete information (such as the text of the tweet, username, user ID, date and time, etc.) using its ID is known as the hydration of a tweet ID. For hydrating this dataset the Hydrator application (link to download and a step-by-step tutorial on how to use Hydrator) may be used.
This dataset consists of 7 .txt files. The following shows the number of Tweet IDs and the date range (of the associated tweets) in each of these files.
Number of Tweet IDs – 22945, Date Range of Tweets - July 20, 2021 – May 21, 2022
Number of Tweet IDs – 19416, Date Range of Tweets - Dec 1, 2020 – July 19, 2021
Number of Tweet IDs – 16673, Date Range of Tweets - April 29, 2020 - Nov 30, 2020
Number of Tweet IDs – 16208, Date Range of Tweets - Oct 5, 2019 - Apr 28, 2020
Number of Tweet IDs – 17983, Date Range of Tweets - Feb 13, 2019 - Oct 4, 2019
Number of Tweet IDs – 34009, Date Range of Tweets - Nov 9, 2017 - Feb 12, 2019
Number of Tweet IDs – 11351, Date Range of Tweets - May 21, 2017 - Nov 8, 2017
For any questions related to the dataset, please contact Nirmalya Thakur at firstname.lastname@example.org
Abstract—In the 2021 and later we know that the technology
will have key participation of to help us in all kind of tasks
mainly using internet connection, due the new normality.
Industry 4.0 has been one of the most relevant field. IoT as part
of it. This Systematic Literature Review (SLR) we will cover
the South America countries and their development status,
addressing the development categories and the Hardware that
has been cited on papers on the last 5 years.
We elaborate on the dataset collected from our testbed developed at Washington University in St. Louis, to perform real-world IIoT operations, carrying out attacks that are more prelevant against IIoT systems. This dataset is to be utilized in the research of AI/ML based security solutions to tackle the intrusion problem.
Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems
Resource Efficient Real-Time Reliability Model for Multi-Agent IoT Systems is called ERT-CORE. It defines specific input parameters, i.e., system's workload, average request processing time and availability. Defined parameters reflect system's state and react on its changes. Based on these parameters system reliability evaluation is performed.
The Bluetooth 5.1 Core Specification brought Angle of Arrival (AoA) based Indoor Localization to the Bluetooth Standard. This dataset is the result of one of the first comprehensive studies of static Bluetooth AoA-based Indoor Localization in a real-world testbed using commercial off-the-shelf Bluetooth chipsets.
The positioning experiments were carried out on a 100 m² test area using four stationary Bluetooth sensor devices each equipped with eight antennas. With this setup, a median localization accuracy of up to 18 cm was achieved.
There are two data files, named 'Data1.mdb' and 'Data2.mdb'. A total of 87,272 pieces of data, including 43,607 pieces of data in file 'Data1.mdb' and 43,665 pieces of data in file 'Data2.mdb'. Please open them with ACCESS software.
The research were incorporated an extended cohort monitoring campaign, validation of an existing exposure model and development of a predictive model for COPD exacerbations evaluated against historical electronic health records.A miniature personal sensor unit were manufactured for the study from a prototype developed at the University of Cambridge. The units monitored GPS position, temperature, humidity, CO, NO, NO2, O3, PM10 and PM2.5.Three 6-month cohort monitoring campaigns were carried out, each including of 65 COPD patients.
Dataset for An-ontology-integrating-the-open-standards-of-city-models-and-internet-of-things-for-smart-city-main research paper.
For the innovation challenge for unmanned aerial vehicle (UAV) communications, we propose to demonstrate a two-tier Low Power Wide Area Network (LP-WAN) based on UAV base stations suitable for dynamic deployment and reconfiguration in deep rural areas. The proposed UAV-based LP-WAN network augments the existing macro-cellular NB-IoT network (Tier 1) with either an additional layer of mobile NB-IoT base stations or an additionaly layer of mobile LoRa base stations (Tier2).