Available Wireless Sensor Network and Internet of Things testbed facilities: dataset

Open Res Eur. 2023 Nov 28:2:127. doi: 10.12688/openreseurope.15176.2. eCollection 2022.

Abstract

The availability of data is an important aspect of any research as it determines the likelihood of the study's commencement, completion, and success. The Internet of Things and Wireless Sensor Networks technologies have been attracting a huge amount of researchers for more than two decades, without having a consolidated or unified source that identifies and describes available Internet of Things and Wireless Sensor Network testbed facilities. In this paper, a dataset including 41 distinct testbed facilities is described. These testbed facilities are classified according to their key features such as Device Under Test (DUT) type, mobility, access level, facility count, connection/interaction interfaces, and other criteria. The systematic review process resulting in the gathered data set consisted of three filtering phases applied to relevant articles published between the years 2011 and 2021 as obtained from the Web of Science and SCOPUS databases.

Keywords: Testbed facility; Data set; Wireless Sensor Networks; WSN; Internet of Things; IoT.

Plain language summary

In this Data Note, we present data collected for the purpose of carrying out a systematic review of the available Wireless Sensor Network and Internet of Things testbed facilities. The data was collected through multiple stages and in each stage, the pre-defined criteria were applied. We provide a dataset describing the hardware and software aspects of Wireless Sensor Networks and Internet of Things testbed facilities available in the market and scientific community. The data were gathered through an extensive systematic review process of scientific articles published between the years 2011 and 2020. The review aims to obtain good-quality data for people who are actively researching the Internet of Things or Wireless sensor Network testbed facilities or anyone who is interested in that field.

Grants and funding

This research was financially supported by the European Union’s Horizon 2020 research and innovation programme under the grant agreement No 825196 (Digital Technologies, Advanced Robotics and increased Cyber-security for Agile Production in Future European Manufacturing Ecosystems [TRINITY]).