Abstract

This work surveys Internet of Things (IoT) experimental research published since 2015. We summarize the IoT state of the art during the last 2 years and extract important data that we apply to enhance the analysis of IoT solutions. The IoT scenario presents a promising universe to data analysis. This raises a number of questions: which are its most popular applications? What is the definition of scale in an IoT application? What sensors are more often used and for what IoT applications? How can a researcher compare IoT scenarios? To investigate these concerns, this survey analyzes 2 years’ worth of contributions made in three main scientific publishers. We focus on IoT experiments that were actually implemented using real equipment within one or more scenarios. Our first contribution is the classification of those IoT scenarios into seven main aspects. Each analyzed research study presents a specific configuration of a scenario’s variables and sensors. Our second main contribution takes place after the scenario mapping phase. We identify as many as 19 common categories of data types in use. The interrelation among the scenarios and the data types from sensors should assist data researchers in understanding current IoT dynamics.

Highlights

  • This work surveys Internet of Things (IoT) experimental research published since 2015

  • We provide the reader with details of the most common emerging IoT scenarios currently found

  • The last part of the analysis offers the classification of the use of sensors, within a characterized scenario

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Summary

Introduction

This work surveys Internet of Things (IoT) experimental research published since 2015. While the main IoT architecture(s) is still under definition, their underlying paradigm offers the means to gather one or more “things” (sensors, interactive devices, or even complex ones) using well-defined communication interfaces These can share data and communicate with the outside world through some specially designed network gateways [4, 5]. The IoT paradigm creates new opportunities for specialized small devices (sensors and actuators) while it introduces new challenges for the storage and retrieval of large amounts of data and its meaningful visualization [6] Such hyper-connected information sources often provide a large-scale data offering. Some works classify the IoT objects (as in [13, 14]), but this strategy has not been applied to IoT scenarios so far

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