Sensing Real-time Observatories in Marine Sites

A Proof-of-Concept

Alessandro Oggioni

, Mauro Bastianini

, Paola Carrara

, Tiziano Minuzzo

and Fabio Pavesi

Institute for Electromagnetic Sensing of the Environment, CNR - IREA UOS Milano, Via Bassini 15, 20133, Milano, Italy

Institute of Marine Science, CNR - ISMAR Venezia, Castello 2737/F, 30122, Venezia, Italy

Keywords: Sensor Web, Interoperability, Marine Observations, Real Time Measurements.

Abstract: Managing real time data collected by a network of heterogeneous sensors from marine sites needs to face

challenges such heterogeneity, quality check, harmonization, description of sensors, etc. This is the purpose

of the proof-of-concept described in this paper; it tests the suitability of OGC Sensor Web Enablement

services, exploiting in particular the Sensor Observation Service (SOS) and the associated SensorML and

O&M standards. Two Italian marine observatories have been included in the proof, both belonging to CNR

ISMAR; they are the oceanographic Platform “Acqua Alta” and a weather station in Venice (Italy). They

measure multiple real time parameters and distribute them by OGC SOS.

The multilayer architecture and the service approach adopted enable decoupling of components; in

particular, the proof shows that each Institution hosting a sensor station is allowed to store observations and

deliver them to multiple independent clients, in a standard, interoperable way, well recognized and accepted

at European and global scale. The proof has been implemented and tested in three scenarios to retrieve and

display descriptions of stations, sensors and measurements available; to retrieve and display observations of

one parameter selected from multiple sensors; to retrieve observations of all parameters collected from

sensors of a specific station.

1 INTRODUCTION

Miniaturization of electronics components, and

decrease in prices of sensors and devices led to a

shift from traditional monitoring to

sensor/processing networks, in particular in

environmental disciplines (Papp & Hakkesteegt

2008). Environmental Sensor Networks allow

increasing the number of observations and

measurements, in order to facilitate studying and

understanding of complex theories or fundamental

ecological processes.

In a review of 50 Sensor Networks, Hart &

Martinez (2006) total integration of distributed,

mobile, fixed, and asynchronous sensors from

different networks. Integration is the first step to

allow monitoring the environment at different scales,

but the real ability of diverse systems to work

together has been realized only in recent years

(Barnaghia, Ganza, & Abangara, 2011; Havlik et al.

2011). Concepts like interoperability are

fundamental in realizing a linkup among data using

spatial (e.g. depth, geographical projection or

location, relative position), temporal (e.g. time zone)

and thematic (e.g. quality, domain, unit of

measurement) attributes.

Some research frameworks, such as the LIFE+

Project EnvEurope (http://www.enveurope.eu) and

the Italian flagship Project RITMARE

(http://www.ritmare.it), underlined the necessity to

exploit the interoperable access to observations from

marine sensors, which is more and more necessary

as symptoms of climate change have to be detected

and monitoring of sudden anomalies is a priority for

early warning systems. Following the approach of

Hart & Martinez (2006), we would analyse the

challenges of real-time sensing, in particular from

marine Italian observatories. Issues to be faced are:

 Heterogeneity of sites - The Italian marine

observational network is heterogeneous and offers

excellence in the type of sensor used. Managing

authorities are numerous and have different skills,

resources and IT expertise. Network nodes

technologies are not homogeneous in the

collection, frequency and distribution of the

measured parameters (e.g. different temporal and

spatial resolution, units, identifiers).

111

Oggioni A., Bastianini M., Carrara P., Minuzzo T. and Pavesi F..

Sensing Real-time Observatories in Marine Sites - A Proof-of-Concept.

DOI: 10.5220/0004713401110118

In Proceedings of the 3rd International Conference on Sensor Networks (SENSORNETS-2014), pages 111-118

ISBN: 978-989-758-001-7

 2014 SCITEPRESS (Science and Technology Publications, Lda.)

 Quality check and harmonization - Allow for a

comparison between measurements coming from

sensors in the network, quality check of data is a

priority. Exclusion of outliers, comparisons among

nearby stations, and trend analysis at different

temporal granularity are operations that must be

carried out at different levels of the data processing

workflow; they would allow an effective and

meaningful comparison. Another important action

is the harmonization of collection and storing

practices in order to improve the overall quality of

the observations collected from the network.

 Description and history of sensor - Information on

sensors in the network like their description,

searching keywords, identification, classification,

characterization of physical properties or electrical

requirements, capability, contacts of manufacturer,

owner or operator, input, output and components

of the system, and especially history log to track

any changes or calibration must be collected and

made available in order to assess their quality,

capacity, features and to compare the sensors in

the network.

To study how to cope with the above issues a proof-

of-concept has been created whose objective is to

test how distributed, heterogeneous, asynchronous

sensors connected to the Web are able to

interoperate and to share observations and

measurements to the purpose of studying marine

ecosystem.

This paper describes the proof, in particular the

demonstration sites that simulate the network and

the approach adopted to face the problems of real-

time observatories in Mediterranean marine sites

from the user prospective, exploiting Service

Oriented Architecture (SOA) approach, Sensor Web

Enablement (SWE) technology based on Open

Geospatial Consortium (OGC) standards.

The next section briefly describes the technological

solution adopted; section 3 depicts the sites included

in the proof. The architecture adopted is illustrated

in section 4, while conclusions and lessons learned

close the contribution.

2 SENSOR WEB ENABLEMENT

AND OCG WEB SERVICES

In the domain of standards for the web, the Open

Geospatial Consortium (OGC) is the organization

that provides the main standardization of services for

geospatial data. It is a non-profit organization

founded in 1994; it consists of 440 companies,

governmental agencies and partner universities and

develops standards to address the lack of

interoperability between systems that process geo-

referenced data. Several geographic Web services

have been developed by OGC for exchanging

different type of geographic data; among them, the

most popular are: Web Map Service (WMS), Web

Feature Service (WFS) and Web Coverage Service

(WCS) for maps, features and coverages

exchanging, respectively; Catalog Service of

Metadata (CSW) for metadata catalogue

management.

Table 1: Requests carried out in SOS service divided by

type (modify by Bermudez et al. 2009). For more

information about operation descriptions see Na & Priest,

2007.

Core Operations

GetCapabilities

DescribeSensor

GetObservation

Transactional Operations

RegisterSensor

InsertObservation

Enhanced Operations

GetObservationById

GetResult

GetFeatureOfInterest

GetFeatureOfInterstTime

DescribeFeatureType

DescribeObservationType

DescribeResultModel

To the purpose of sensor management a framework

of standards have been proposed and supported by

OGC under the common umbrella of Sensor Web

Enablement (SWE) (Botts et al. 2013), which

includes: SWE Common Data Model, Sensor Model

Language (SensorML), Sensor Event Service (SES),

Sensor Planning Service (SPS), Sensor Observation

Service (SOS) for observations collected by sensors.

In this paper we focus on the SOS service (Na &

Priest 2007) that has been adopted in the proof-of-

concept. The objective of SOS is to specify

interoperability interfaces and metadata encodings

that enable the integration of heterogeneous sensors

on the Web. SOS has been developed for

discovering, binding and querying individual sensors

or sensors platforms in real-time (RT), near real-

time (NRT) or delay mode (DM) (Bermudez et al.

2009). With SOS, two more specifications work

together: SensorML for describing characteristics

and capability of the sensors and Observations and

Measurements (O&M) for encoding observations

and measurements. SOS specifies a standard Web

service interface for requesting, filtering, and

SENSORNETS2014-InternationalConferenceonSensorNetworks

112

retrieving observations and sensor system

information (see available requests categorized into

core, transactional and enhanced in Table 1). This is

the intermediary between a client and an observation

repository or near real-time sensor channel. Clients

can also access SOS to obtain metadata information

that describes the associated sensors, platforms,

procedures and other metadata associated with

observations.

3 THE DEMONSTRATION SITES

The proof-of-concept was performed by exploiting

two Italian marine observatories belonging to CNR

ISMAR (Figure 1). Both are nodes of the European

LTER (Long Term Ecological Research) network

(http://www.lter-europe.net/) and are involved in

EnvEurope (Figure 4).

They are the oceanographic Platform “Acqua

Alta” and a weather station in Venice (Italy). The

parameters measured and included in the proof are

described in Table 2.

The Platform “Acqua Alta” is a tower located 15

km offshore in the Northern Adriatic Sea, on 16

meters depth (Figure 1 left). It is the only scientific

structure in Italy, and one of the very few in Europe,

that allows people on board for long periods for

intensive campaigns in the middle of the sea. The

capability of having a structure in the open sea, large

enough to withstand the worst storms, but small

enough not to interfere with the surrounding

environment, allows highly accurate measurements

also in heavily difficult conditions. The tower has

three floors plus the terrace at 12 meters above the

mean sea level. It is fully energetically self-

sufficient, being powered by solar panels, wind

generators and power generators. “Acqua Alta” is

fully equipped with a very large set of instruments,

devoted to meteorological, oceanographic and

chemical parameters’ collection. Measurements go

back to the early ‘70s, so that some time series

provide sufficient information to detect climate

changes. The site is part of the European LTER

(Long Term Ecological Research) network

(http://www.lter-europe.net/).

Table 2: Parameters collected at “Acqua Alta” Oceanography Tower and weather station. The table specifies also

depth/altitude above/below average sea level, frequency of sampling observation, and manufacturer of the sensors used.

“Acqua Alta” Oceanographic Platform Weather station

Parameters

Level Frequency

Sensor

Manufacturer

and Model

Level Frequency

Sensor

Manufacture

r and Model

Air temperature

+18 m asl

average

30’’

Davis

Vantage Pro2

+24 m asl

average

30’’

Davis

Vantage Pro2

Humidity

Wind speed

Wind direction

Irradiance

Precipitation

Wave height

0 m asl

average

30’

Nortek

Awac

Wave period

Wave direction

Tide

Current speed

-1,-2,-3,-4,-5,-

6,-7,-8,-9,-

10,-11,-12,-

13,-14,-15 (m

bsl average)

Current direction

Water temperature

-2,-6,-12,-16

(m bsl

average)

CTD Seabird

SBE37

Oxygen concentration

-2,-12 (m bsl

average)

Salinity

-2,-6,-12 (m

bsl average)

Chlorophyll a

-12 m bsl

average

SensingReal-timeObservatoriesinMarineSites-AProof-of-Concept

113

Figure 1: Images of the Platform “Acqua Alta” (left) and

of the CNR ISMAR historical building hosting the

weather station included in the proof (right).

They are the oceanographic Platform “Acqua Alta”

and a weather station in Venice (Italy). The

parameters measured and included in the proof are

described in Table 2.

The Platform “Acqua Alta” is a tower located 15

km offshore in the Northern Adriatic Sea, on 16

meters depth (Figure 1 left). It is the only scientific

structure in Italy, and one of the very few in Europe,

that allows people on board for long periods for

intensive campaigns in the middle of the sea. The

capability of having a structure in the open sea, large

enough to withstand the worst storms, but small

enough not to interfere with the surrounding

environment, allows highly accurate measurements

also in heavily difficult conditions. The tower has

three floors plus the terrace at 12 meters above the

mean sea level. It is fully energetically self-

sufficient, being powered by solar panels, wind

generators and power generators. “Acqua Alta” is

fully equipped with a very large set of instruments,

devoted to meteorological, oceanographic and

chemical parameters’ collection. Measurements go

back to the early ‘70s, so that some time series

provide sufficient information to detect climate

changes. The site is part of the European LTER

(Long Term Ecological Research) network

(http://www.lter-europe.net/).

The weather station included in the proof hosts

the meteorological station at +24 m and is located in

the city centre of Venice nearby the historical

building of the ISMAR Institute (Figure 1 right).

From the Platform, observations flow through a

wireless link based on affordable radio equipment

allowing the tower to be a permanent node of the

Institute LAN. To this aim a wireless link on “free

license” frequencies has been installed with two

hops in order to overcome geographical barriers.

The bandwidth is minimum 10 Mbps with QoS. In

each segment two ALCOMA AL17FMP wireless

devices are installed operating in “license free”

17GHz, with a power of 20dBm and reduced power

requirements (25W).

4 THE PROOF-OF-CONCEPT

In the Environmental domain the need of designing

Service Oriented Architectures (SOA) is a challenge

to be won (Havlik et al. 2011). SOAs allow their

services to be published, discovered, and finally

invoked by clients in the network dynamically (Jiang

et al. 2013). Many authors (Chen et al. 2009; Woolf

2008; Voigt et al. 2008; Di 2007) have demonstrated

how distributed services can be coupled and

interoperate, but in this moment only few examples

seem to be really implemented.

In the architecture of the proof-of-concept

proposed here both services and repositories are

distributed, “… to ensure that spatial data are stored,

made available and maintained at the most

appropriate level …” (see Art. 6 - INSPIRE

Directive 2007/2/EC). This aspect is very important

in the marine context, where different institutions

need to manage and keep the data collected from

their equipment.

Table 3 describes the proposed architecture with

the meaning of its five different layers and the

components of the proof in each layer.

The observation flow among different

components of the architecture is ruled by the

standard SOS interface. Observations collected by

sensors are stored in the repositories by the SOS

InsertObservation() request. Also the dialogue

between application layer and service/data layer

occurs through different standard requests, e.g.

GetObservations(), GetFeatureOf-Interest(),

DescribeSensor().

The dialogue between the presentation and

application layers takes advantage of the portal

controller’s mediation, to organize and dispatch the

operations required by the proof’s users. The portal

controller's main purpose is to encapsulate a number

of features so that they are transparent to the

Presentation layer, such as unit of measurement and

parameter harmonization, quality control (QC),

cross-server querying or the auditing of server

availabilities.

It is worth noticing that the Application layer can

host different tools aimed at facing the quality

check, harmonization and analysis issues cited in the

Introduction. The proof allows to perform these

actions on either all or selected observations

delivered by their respective Web services.

SENSORNETS2014-InternationalConferenceonSensorNetworks

114

Table 3: Meaning of the five layers of the architecture adopted and components of the proof.

Layers Meaning Content in the proof-of-concept

Sensor layer

the layer of sensors, distributed in space and of different types, either

mobile or fixed, collecting data in real-time or in delay-mode. It is

different from the data layer as the sensors do not act as repositories

of the observations but simply pick them up or store them temporarily

In the proof this layer contains two

distributed, fixed stations of sensors (see

Table 2) connected with the Web and

collecting Real Time data

Data layer

the level contains the repositories of the observations gathered by the

sensors

In the proof-of-concept this layer consists

of two separate and distributed databases,

each of them storing data from the

respective observatories sensors

(PostgreSQL v9.2.and PostGIS v2.0 tool)

Service layer

it consists of the Web services that enable the distribution of

observations through the network; standard Web services allow to act

in an interoperable way

In the proof-of-concept the services

adopted are a couple of OGC SOS (one for

each station) with related SensorML and

O&M specifications (52°North SOS v3.2.1

implementation)

Application

layer

this level hosts tools designed to process, transform, harmonize,

analyse, etc. the observations coming from different Web services (e.g.

elaboration, quality check, geographic transformation, unit of

measure harmonization, etc.)

In the proof it contains a tool to harmonize

parameters’ names and also a portal

controller that dispatches the requests and

allows to process the operations that are

required by the presentation layer (JBoss

Application Server v7, Tomcat v7)

Presentation

layer

this layer contains the clients to access and retrieve the observations

and their elaborations; user interfaces are included here

In the proof there is here the interface with

the proof’s user; it offers forms to perform

selections and searching and exhibits

observations in the most appropriate way

to the user needs (OpenLayers v2.13.1)

Figure 2: Unique Model Languages (UML) sequence

diagram of SOS with main requests. In different colours

preferential requests using by different proposed users

(red, blue and green).

4.1 Use Cases

As already mentioned above, the Presentation layer

of the proof contains a client in the form of a user

interface.

This subsection is devoted to briefly describe the

main requirements of the proof interface in terms of

tasks and data, listing services coping with them and

the solutions adopted in our experiment. The

potential users of our application are different

operators involved in marine monitoring. The main

actions they would perform to assess sea-water

quality through a network of heterogeneous,

distributed stations of sensors can be summarized in

the following three use cases:

a) to retrieve and display a description of the

station, of the sensors available, and of the

measurement processes (e.g. calibration, gain,

accuracy, offset, etc.) which could include

quality control procedure of all sensors of a

station;

b) to retrieve and comparatively display

observations of one selected parameter (e.g. air

temperature, wind direction, wind speed, etc.)

collected from multiple, distributed sensors;

c) to retrieve observations of all parameters

collected from all sensors from a specific station.

The three sub-sections below describe, with real

examples, how the three use cases are realised in the

proof-of-concept.

4.1.1 Use Case A)

The user may want to know the features of the

thermometer of the “Acqua Alta” Platform.

Actions are highlighted in green in Figure 2;

SensingReal-timeObservatoriesinMarineSites-AProof-of-Concept

115

after a GetCapabilities() request in order to know if

the related Web service provides data on air

temperature, the proof system performs a

DescribeSensor() request. This allows to display the

SensorML description of the air temperature sensor

with general description, keywords, identification,

classification, characterization of physical

properties, electrical requirements, capability,

contacts of manufacturer, owner or operator, input,

output and components of the system, and moreover

its history log to track any changes or calibration.

4.1.2 Use Case B)

The user in this case may want to retrieve the air

temperature in the whole North Adriatic Sea during

August 2012, and to know also the geographic

position of sensors. Actions are highlighted in red in

Figure 2. The proof system performs a

GetCapabilities() request, in order to know if the

Web services available in the area provide data on

air temperature and if observations cover the period

requested by the user. In fact, the response to this

request contains, among other, information about:

parameters measured in each observatories, time

period covered by different sensors, and geographic

position. Both “Acqua Alta” tower and the weather

station have thermometers for measuring air

temperature (Table 2).

The second step is to get observations and display

them both in a chart. The request GetObservation()

with time period filtering can be used to get

observations from both services.

For the user may be also important to display on a

map the location of different air temperature sensors

(thermometer). In this case the Enhanced Operations

GetFeatureOfInterest() (Table 1) can be used to

obtain the coordinates of both stations hosting the

sensors collecting the observations (Figure 3).

4.1.3 Use Case C)

The user in this case may want to retrieve all data

collected by all sensors in the “Acqua Alta” tower.

Actions are highlighted in blue in Figure 2. To this

aim the proof system simply exploits

GetCapabilities() and GetObservation() requests to

list the parameters and the corresponding values,

respectively. The SOS that serves observations from

“Acqua Alta” tower can be queried independently

and it lists all observed properties present in the

response capabilities.

5 CONCLUSIONS

This paper has presented a proof-of-concept created

to test the suitability of OGC SWE services as core

of spatial data infrastructures for managing real time

data collected by a network of heterogeneous marine

sensors.

The architecture, components and

implementation solutions proposed in the proof-of-

concept revealed to be able to cope with all the

requirements of a community of users wishing to

retrieve and display observations coming from

heterogeneous sensors on distributed stations, stored

in distributed repositories connected to the Web and

delivered via standard OGC Web services in the

Figure 3: Presentation layer interface for displaying sensors’ positions.

SENSORNETS2014-InternationalConferenceonSensorNetworks

116

SWE framework.

The multilayer structure and the service approach

enable decoupling of components; in particular, each

Institution hosting and maintaining a sensor station

is allowed to store observations and deliver them to

multiple independent clients, in a standard,

interoperable way, well recognized and accepted at

European and global scale.

The success and reliability of the solution is

proved by the number of SOS services, which is

increased in the last few years (Tamayo et al. 2011).

Using advanced search in Google engine (e.g.

inurl:service=SOS inurl:request=GetCapabilities)

913 different SOS services are found, 456 of them

referred to the aquatic environment. They and their

observations are all potentially interoperable with

the observations distributed by our proof-of-concept.

If we consider the challenges defined in the

introduction, the proof-of-concept proposed is able

to cope with technological heterogeneity of the sites

and sensors since it is based on the use of OGC

standards, able to describe sites and sensors

characteristics but offering a uniform ways to

communicate among the implementation

components.

Quality check and harmonization are fostered by

the multi-layered approach that allows to include

components and tools aimed at those purposes at

different level; by example a fast-track quality

control can be performed before the storage of

observations in the repositories, while a spatially-

extended cross validation process can be included in

the Application layer, where values from multiple

sites are available.

Uniform metadata and a shared

sensor/observation model are also a way to describe,

search and compare quality.

But they are even more useful in facing the need

to provide descriptions of sensors and their status,

information necessary e.g. to maintain the network

and to compare the sensors’ performance.

Authors do not hide that the job to be done is

great: in particular the technological development of

the tools to implement SWE components (and in

particular SOS) is still overwhelming for the

community of marine researchers; the success of the

approach is linked to the development and

availability of easy to define, ready to use tools,

enabling site managers to friendly create their own

repositories and services. Cloud providers can also

offer a solution to the security issues linked to

service distribution in small institutions.

Another development is related to the syntactic

and semantic harmonization, which requires

intelligent applications that integrate the current

technological solutions and standards with

knowledge coming from the domain experts.

ACKNOWLEDGEMENTS

The activities described in this paper have been

partially funded by the LIFE+ Project EnvEurope

(http://www.enveurope.eu) and the Italian flagship

Project RITMARE (http://www.ritmare.it).

REFERENCES

Barnaghia, P., Ganza, F. & Abangara, H. 2011,

Sense2Web: A Linked Data Platform for Semantic

Sensor Networks. Semantic Web – Interoperability,

Usability, Applicability an IOS Press Journa, vol. 2,

no.1, pp. 1-11.

Bermudez, L., Cook, T., Forrest, D., Bogden, P.,

Galvarino, C., Bridger, E., Creager, G. & Graybeal, J.

2009, Web feature service (WFS) and sensor

observation service (SOS) comparison to publish time

series data in Collaborative Technologies and

Systems, 2009. CTS ’09. International Symposium

on. pp. 36-43.

Botts, M., Percivall, G., Reed, C., Davidson, J. 2013, OGC

Sensor Web Enablement: Overview and High Level

Architecture in GeoSensor networks, eds S Nittel, A

Labrinidis & A Stefanidis, Springer, Berlin

Heidelberg, pp. 175-190.

Chen, N., Di, L., Yu, G. & Min, M. 2009, A flexible

geospatial sensor observation service for diverse

sensor data based on Web service. ISPRS Journal of

Photogrammetry and Remote Sensing, vol. 64, no. 2,

pp. 234-242.

Di, L. 2007, (GMU): A General Framework and System

Prototypes for the Self-Adaptive Earth Predictive

Systems (SEPS). Paper presented at the Dynamically

Coupling Sensor Web with Earth System Models

(AIST-05-0064), ESTO-AIST Sensor Web PI Meeting,

San Diego.

Goodchild, M. F., Guo, H., Annoni, A., Bian, L., de Bie,

K., Campbell, F., Craglia, M., Ehlers, M., van

Genderen, J., Jackson, D., Lewis, A. J., Pesaresi, M.,

Remetey-Fülöpp, G, Simpson, R, Skidmore, A, Wang,

C & Woodgate, P 2012, Next-generation Digital

Earth. Proceedings of the National Academy of

Sciences of the United States of America, vol. 109, no.

28, pp. 11088-11094.

Hart, J. K. & Martinez, K. 2006, Environmental Sensor

Networks: A revolution in the earth system science?

Earth-Science Reviews, vol. 78, no. 3-4, pp. 177-191.

Havlik, D., Bleier, T. & Schimak, G. 2011, From Sensor

to Observation Web with environmental enablers in

the Future Internet, Sensors, vol. 11, no. 4, pp. 3874-

3907.

SensingReal-timeObservatoriesinMarineSites-AProof-of-Concept

117

Jiang, Y., Jiang, Y., Guo, Z., Hu, K., Shen, F. & Hong, F.

2013, Using Sensor Web to Sharing Data of Ocean

Observing Systems, in Advances in Wireless Sensor

Networks, eds R Wang & F Xiao, Berlin Heideberg:

Springer-Verlag Berlin Heidelberg, pp. 137-156.

Na, A. & Priest, M. 2007, Sensor Observation Service,

OGC 06-009r6, p. 104.

Papp, Z. & Hakkesteegt, H. 2008, Sensor Web, Sensor

Networks: New possibilities and new challenges in M.

Grothe & J. Kooijman, eds. Sensor Web Enablement.

Delft: NCG, Nederlandse Commissie voor Geodesie,

Netherlands Geodetic Commission, Delft, The

Netherlands, pp. 21-39.

Tamayo, A., Viciano, P., Granell, C. & Huerta, J 2011,

Empirical study of sensor observation services server

instances, CoRR, vol. abs/1109.4.

Voigt, T., Tsiftes, N. & He, Z. 2008, Remote Water

Monitoring With Sensor Networking Technology.

Ercim News, vol. 76, pp. 39-40.

Woolf, A. 2008 Building the Sensor Web - Standard by

Standard. Ercim News, vol. 76, pp. 24-25.

SENSORNETS2014-InternationalConferenceonSensorNetworks

118