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Icwe2016 CRS4 Lugano
1. Middleware Mediated Semantic Sensor Networks
ICWE 2016
Cristian LAI
cristian.lai@crs4.it
Antonio Pintus
antonio.pintus@crs4.it
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2. Context
IoT
Semantics
G Things are active participants in information processes.
G Things are active parts of heterogeneous networks.
G IoT can take advantage of Semantic Technologies.
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3. Semantic Sensor Networks
Ritesh Jagzape, Internet of Things1
1https://riteshjagzape.wordpress.com/.
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4. Issues
G How to consider and manage
H networks’ elements, devices and, in general, smart connected things,
H information obtained from raw dataSensor’s raw data
{10, 5.5, 12, ...}
G How to benefit from an IoT middleware platform to enrich and transform
data into interconnected Information entities.
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5. Methodology
G Sensors and observations data annotation
H semantic annotations are embedded within sensing stations
Annotation: temperature sensor
{"whois":"sensor_Temperature_1",
"observes":"cf-property:air_temperature"}
G Enriched semantic descriptions
H Paraimpu, rules transform semantic annotations to semantic descriptions
Description: temperature sensor
{"@id": ":sensor_Temperature_1",
"@type": "ssn:Sensor",
"dbpedia-owl:thumbnail": { "@id": "http://mydomain.com/images/img10.jpg" },
"rdfs:label": [
{ "@language": "it", "@value": "Temperatura" },
{ "@language": "en", "@value": "Temperature" }
],
"ssn:observes": { "@id": "cf-property:air_temperature" },
"ssn:onPlatform": { "@id": ":station_1" } }
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7. Case Study
SEMANTIC
DATA
ENRICHMENT
RULES
Paraimpu IoT Platform
Arduino stations, Sensors
City Traffic Open Data
City Weather Data
Triplestore
SPARQL engine
API
API
1
2
3
Web App4
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9. Conclusion
G We discussed how to benefit from Semantic Web technologies in SSN.
G Data originating from devices will be part of the world of Linked Sensor
Data, through distributed RDF Knowledge Bases.
G Future works
H How to avoid duplication of rules in connections sharing the same goal?
H How to (semi)automate rules definition?
H Novel approaches of sensor analysis that infers semantic properties such as
the type of observed property, using the raw sensor observations as input.
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10. Q & A
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