Sensing Real-time Observatories in Marine Sites
A Proof-of-Concept
Alessandro Oggioni
1
, Mauro Bastianini
2
, Paola Carrara
1
, Tiziano Minuzzo
2
and Fabio Pavesi
1
1
Institute for Electromagnetic Sensing of the Environment, CNR - IREA UOS Milano, Via Bassini 15, 20133, Milano, Italy
2
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
Copyright
c
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
UV
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