SemIoT is a project funded by The Ministry of Education and Science of Russian Federation which aims to provide an access to sensor networks using unified data models and interfaces that hide heterogeneity of the network and facilitate effective data access, interoperability, resource search and discovery

1. SemIoT
Semantic technologies
for Internet of Things
semiot.ru

2. About
Start and end dates: 24.11.2014 - 31.12.2016
Government funding*
: 11.76M
Industrial funding: 2.94M
*Funded by The Ministry of Education and Science of Russian Federation, Grant RFMEFI57514X0101
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3. Goal
provide an access to sensor networks using
unified data models and interfaces that hide
heterogeneity of the network and facilitate
effective data access, interoperability,
resource search and discovery
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4. Expected results
■ SemIoT Gateway - a device connecting physical
objects with our middleware platform
■ SemIoT Platform - a middleware that collects, stores,
analyses and publishes the sensor data
■ Ontology Framework - a set of OWL-ontologies
providing unified models
■ several domain specific applications for the working
use cases
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5. SemIoT Platform | Workflow
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6. SemIoT Platform | Data Collection
Implements a plug-in architecture based
on OSGi specification1
which allows to:
■ support any type of connected devices
■ provide an easy way to implement a
new plug-in
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http://www.osgi.org

7. SemIoT Platform | Semantic Annotation
Facilitates semantic interoperability
meaning that different stakeholders can
access and interpret the data
unambiguously.
■ Semantic Sensor Networks (SSN)2
as
an upper ontology
■ A web app to generate the RDF
descriptions of connected devices
(http://semdesc.semiot.ru)
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http://purl.oclc.org/NET/ssnx/ssn#

8. SemIoT Platform | Archiving
Stores metadata about connected
devices and their readings in RDF.
■ A triplestore is used for metadata
■ A TSDB3
is used for the readings
There’s a plan to make them accessible
through a SPARQL endpoint and/or TPF4
server.
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3
https://en.wikipedia.org/wiki/Time_series_database
4
http://www.hydra-cg.com/spec/latest/triple-pattern-fragments/

9. SemIoT Platform | Real-time analysing
Identifies the events of interest based on
static and streaming data of connected
devices.
■ Uses an RDF Stream processing5
approach
■ Allows to use external datasources,
e.g. LinkedGeoData.org, DBPedia.org
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https://www.w3.org/community/rsp/

10. SemIoT Platform | Publishing
Provides an access to the data of
connected devices using:
■ A hypermedia-driven Web API6
■ A Triple Pattern Fragments API
■ A SPARQL endpoint
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http://www.hydra-cg.com/

11. SemIoT Gateway | Overview
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12. SemIoT Gateway | Scenario
■ Gets readings from devices which:
○ can’t communicate their data over (Intra)Internet
○ use popular protocols, e.g. MQTT, CoAP and etc
■ Annotates the data with semantic metadata
■ Gives access to the data using CoAP and RDF/EXI that
facilitates interoperability, resource search and
discovery
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13. Ontology Framework
Semantic Sensor Networks ontology as an upper ontology
and basis.
Domain specific ontologies (under development):
■ Electric Meters ontology
■ Heat Meters ontology
■ Machine Tools ontology
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14. Applications
■ Advanced electric meter management
■ Advanced heat meter management
■ Environmental monitoring
■ Machine Tool Monitoring
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15. Applications | Adv. Electric Meter Manag.
A simulator of electric meters7
is used. It
allows to simulate a network of thousands
of electric meters.
Goal is to detect different emergency
situations, such as too high voltage or
broken meter and etc.
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https://github.com/semiotproject/simulator-electric-meters

16. Applications | Adv. Heat Meter Manag.
A simulator of heat meters8
is used. It
allows to simulate heat meters in
residential buildings.
Goal is to detect overheating of the
building based on indoor and outdoor
temperature, and readings of the meter.
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https://github.com/semiotproject/simulator-heat-meters

17. Applications | Environmental Monitoring
Goal is to re-publish
environmental data
(outdoor temperature,
humidity, etc.) from
narodmon.ru web site
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18. Applications | Machine Tool Monitoring
In cooperation with Winghouse Ltd.
(http://winghouse.ru)
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A machine tool should work 24/7,
without any interruption
Goal is to detect “unfounded delays”
and minimize the downtime

19. Our team
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20. semiot.ru
@semiotproject
github.com/semiotproject
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