IoT-Lite: A Lightweight Semantic Model for the Internet of Things
IoT-Lite: A Lightweight Semantic Model
for the Internet of Things
Maria Bermudez-Edo (University of Granada),
Tarek Elsaleh, Payam Barnaghi (University of Surrey),
Kerry Taylor (The Australian National University/University of Surrey)
2P. Barnaghi et al., "Digital Technology Adoption in the Smart Built Environment", IET Sector Technical Briefing, The Institution of Engineering and Technology
(IET), I. Borthwick (editor), March 2015.
Sensor devices are becoming widely available
- Programmable devices
- Off-the-shelf gadgets/tools
Internet of Things: The story so far
Wireless Sensor and
, solutions for
efficiency, routing, …
vertical applications, early
concepts and demos, …
More products, more
solutions for control and
Future: Cloud, Big (IoT) Data
Enhanced Cellular/Wireless Com.
for IoT, Real-world operational
use-cases and Industry and B2B
Data in the IoT
− Data is collected by sensory devices and also crowd sensing
− It is time and location dependent.
− It can be noisy and the quality can vary.
− It is often continuous - streaming data.
− Data is gathered from various heterogeneous sources and in
various format and representations.
− Often the value is in integrating data from different sources
and in creating an ecosystem of systems.
The slide adapted from the IoT talk given by Jan Holler of Ericsson at IoT Week 2015 in Lisbon.
Heterogeneity, multi-modality and volume are
among the key issues.
We need interoperable and machine-interpretable
Semantic Sensor Web
“The semantic sensor Web enables
interoperability and advanced analytics
for situation awareness and other
advanced applications from
(Amit Sheth et al, 2008)
Some good existing models:
Ontology Link: http://www.w3.org/2005/Incubator/ssn/ssnx/ssn
M. Compton et al, "The SSN Ontology of the W3C Semantic Sensor Network Incubator Group", Journal of Web Semantics, 2012.
There are several good models and description
The problem is that having good models and
developing ontologies are not enough.
Semantic descriptions are intermediary
solutions, not the end product.
They should be transparent to the end-user and
probably to the data producer as well.
Source: The IET Technical Report, Digital Technology Adoption in the Smart Built Environment: Challenges and
opportunities of data driven systems for building, community and city-scale applications,
Design Rules (1)
−Design for large-scale.
−Think of who will use the semantics and design for
their needs (keep the minimum required tags).
−Provide means to update and change the semantic
annotations (not covered).
−Create tools for validation and interoperability
−Create taxonomies and vocabularies.
Design Rules (2)
− Re-use existing models.
− Link data and descriptions to other existing resources.
− Define rules and/or best practices for providing the values for
− Keep it simple.
− Create effective methods, tools and APIs to handle and
process the semantics.
Evaluations- data size
Comparison with the
Evaluations- Query Time
Query performed in the experiments
Evaluations- Query Time
Round Time Trip (RTT) of the queries required
to retrieve the endpoint.
− The IoT-Lite Ontology provides an extensible way to
describe devices acting as sensors, actuators or tags in terms
of their attributes and associated units of measure, as well as
the device's physical location and area of coverage.
- Semantic descriptions
solutions, not the end
- They, usually, should be
transparent to the end-
user and probably to the
data producer as well.
−IoT-Lite (or any other similar model) should be
−Tools for annotation (similar to SAOPY)
−Tools for validation (similar to the SSN validator)
−Sample code and sample datasets
The research leading to these results has received funding
from the European Commission’s in the Seventh Framework
Programme for the FIWARE project under grant agreement
no. 632893 and in the H2020 for FIESTA-IoT project under
grant agreement no. CNECT-ICT-643943.