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Middleware Mediated Semantic Sensor Networks
ICWE 2016
Cristian LAI
cristian.lai@crs4.it
Antonio Pintus
antonio.pintus@crs4.it
Lugano 7 June 2016, USI Lugano, Switzerland 1 / 10
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.
Lugano 7 June 2016, USI Lugano, Switzerland 2 / 10
Semantic Sensor Networks
Ritesh Jagzape, Internet of Things1
1https://riteshjagzape.wordpress.com/.
Lugano 7 June 2016, USI Lugano, Switzerland 3 / 10
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.
Lugano 7 June 2016, USI Lugano, Switzerland 4 / 10
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" } }
Lugano 7 June 2016, USI Lugano, Switzerland 5 / 10
The Paraimpu Middleware
Lugano 7 June 2016, USI Lugano, Switzerland 6 / 10
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
Lugano 7 June 2016, USI Lugano, Switzerland 7 / 10
Paraimpu Transformation Rules
Lugano 7 June 2016, USI Lugano, Switzerland 8 / 10
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.
Lugano 7 June 2016, USI Lugano, Switzerland 9 / 10
Q & A
Lugano 7 June 2016, USI Lugano, Switzerland 10 / 10

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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 Lugano 7 June 2016, USI Lugano, Switzerland 1 / 10
  • 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. Lugano 7 June 2016, USI Lugano, Switzerland 2 / 10
  • 3. Semantic Sensor Networks Ritesh Jagzape, Internet of Things1 1https://riteshjagzape.wordpress.com/. Lugano 7 June 2016, USI Lugano, Switzerland 3 / 10
  • 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. Lugano 7 June 2016, USI Lugano, Switzerland 4 / 10
  • 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" } } Lugano 7 June 2016, USI Lugano, Switzerland 5 / 10
  • 6. The Paraimpu Middleware Lugano 7 June 2016, USI Lugano, Switzerland 6 / 10
  • 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 Lugano 7 June 2016, USI Lugano, Switzerland 7 / 10
  • 8. Paraimpu Transformation Rules Lugano 7 June 2016, USI Lugano, Switzerland 8 / 10
  • 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. Lugano 7 June 2016, USI Lugano, Switzerland 9 / 10
  • 10. Q & A Lugano 7 June 2016, USI Lugano, Switzerland 10 / 10