Abstract

Wireless Sensor Networks (WSNs) are a technology that is becoming very popular for many applications, and environmental monitoring is one of its most important application areas. This technology solves the lack of flexibility of wired sensor installations and, at the same time, reduces the deployment costs. To demonstrate the advantages of WSN technology, for the last five years we have been deploying some prototypes in the Doñana Biological Reserve, which is an important protected area in Southern Spain. These prototypes not only evaluate the technology, but also solve some of the monitoring problems that have been raised by biologists working in Doñana. This paper presents a review of the work that has been developed during these five years. Here, we demonstrate the enormous potential of using machine learning in wireless sensor networks for environmental and animal monitoring because this approach increases the amount of useful information and reduces the effort that is required by biologists in an environmental monitoring task.

Highlights

  • A wireless sensor network (WSN) is composed of many small devices that are deployed in a physical environment

  • The technical requirements of a WSN applied to environmental monitoring include: (1) Autonomy: Batteries must be able to power the nodes during the whole network lifetime

  • All of the proposed WSNs have been designed to be applied in the Doñana Biological Reserve (DBR)

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Summary

Introduction

A wireless sensor network (WSN) is composed of many small devices that are deployed in a physical environment. Sensor networks have many applications [2], environmental monitoring is an area in which the potential impact is extremely large, as described in [3] These devices permit monitoring an area at a low cost and with little need for human presence, which is very important in these types of applications [4]. These networks are normally used in environmental monitoring to collect information via sensors that are incorporated into each node, and they pool this information in a special device called a Base Station [5].

Description of the Environment to Monitor
Description of the Research Facilities in Doñana
Current WSNs Designed for Doñana
ARTICA 1 Network
ARTICA 2 Network
ICARO 1 Network
Animal Localization Project
Forest Fire Detection Project
HORUS Project
ICARO and Networks
SENDA Network
Chronological Evolution of the Prototypes
Design year
Future WSN Projects in Doñana
Video Processing of Smart-Nest Boxes
Sound Monitoring in Natural Areas
Findings
Conclusions
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