Using SWE Standards for Ubiquitous Environmental Sensing: A Performance Analysis

Alain Tamayo,Joaquín Huerta,Carlos Granell

doi:10.3390/s120912026

Alain Tamayo, Joaquín Huerta + Show 1 more

Open Access

https://doi.org/10.3390/s120912026

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Abstract

Although smartphone applications represent the most typical data consumer tool from the citizen perspective in environmental applications, they can also be used for in-situ data collection and production in varied scenarios, such as geological sciences and biodiversity. The use of standard protocols, such as SWE, to exchange information between smartphones and sensor infrastructures brings benefits such as interoperability and scalability, but their reliance on XML is a potential problem when large volumes of data are transferred, due to limited bandwidth and processing capabilities on mobile phones. In this article we present a performance analysis about the use of SWE standards in smartphone applications to consume and produce environmental sensor data, analysing to what extent the performance problems related to XML can be alleviated by using alternative uncompressed and compressed formats.

Highlights

Changes in environmental conditions affect the environment itself and put pressure on human society [1]
Because of the extension of the results, we present in detail those for CAPS, OBS and Insert Observations (IO) datasets
In this article we have presented a performance analysis of using Sensor Web Enablement (SWE) standards as data communication protocols in smartphone applications to consume and produce environmental sensor data

Summary

Introduction

Changes in environmental conditions affect the environment itself and put pressure on human society [1]. Smartphones are being used for in-situ data acquisition in varied scenarios such as geological sciences [11,12], epidemiology [13], biodiversity [14], and noise pollution monitoring [8,9] In these examples smartphones play either a consumer or producer role as typical clients in a client-server architecture. In low-connectivity situations, a mobile application may consume and process data from nearby in-situ sensors and upload aggregated datasets to the corresponding servers when network links are restored [15,16,17] In this particular case, smartphones may potentially collect large quantities of data to be further uploaded to remote servers, which may be a serious impediment in terms of performance.

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