The document discusses several challenges and opportunities related to connecting devices in the Internet of Things (IoT) to internet services and applications. It notes that while billions of devices have been connected, more can be done to utilize the data. Specifically, it addresses the need for semantic interfaces and data mining/machine learning techniques to overcome heterogeneity in integrating IoT devices with internet services and applications. Additionally, it discusses approaches for storing the large amounts of data produced and developing middleware platforms to enable new service creation and deployment on top of collected IoT information.

1. Internet of Things
Applications/Services
Diogo Gomes <dgomes@ua.pt>
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2. source GSMA, 2011
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3. source GSMA, 2011
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4. Information is produced 24/7
Technology Challenges for the Internet of
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Things 2011 – Winterhttp://embedded-computing.com/current-trends-cyber-attacks-mobile-embedded-systems
Source: School

5. What have we achieved so far…
• We have connected billions of devices to the
Internet, but…
– What are we doing with it ?
• We are following a 1 sensor 1 application model
– We have create vertical silos of information
• Energy information is kept by the Energy Company
• Home automation is a self-contained application
– We have over engineered our solutions
• e.g. wireless mesh networks in well served locations
• e.g. using generic sensing platforms to monitor limited amount of
variables
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6. Technology Challenges for the InternetSource:
of 2011, Gartner Hype Cycle
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7. … what are we targeting?
• What is done with all this information?
• Who gathers this information?
• Who stores this information?
• Potential for new IoT Applications and Services
– New players who do not own or operate any IoT
devices
– New players who are in charge of managing
Information and providing new applications and
services to users
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8. M2M vs IoT
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9. M2M vs IoT
New
Service
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10. IoT Services
• The vision of an Internet of Things has changed the
concept of a service from traditional notion of web
services.
• In the Internet of Things domain, the term ‘service’
refers to enhancing real world resources with
interaction support.
• These so-called “real world services” are provided by
resources that are linked directly to the physical world.
• The resources have sensing, processing or actuating
devices that provide information on entities in the real
world, provide interactions or generate events about
them.
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11. IoT and the IoS
• IoT is about connecting “things” to
the Internet.
• IoS will be about what we do with
the information provided by those Data Information
“things”
– IoT can gather data, but it is up to the
IoS to process that data into
Information and Knowledge.
IoT IoS
• IoS will enable the control and
management of real world resources Actions Information
and devices
– IoT will provide the actuators, by
which the Virtual/Service world will
interact with the real world.
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12. IoT deployment
Internet
Data Information Knowledge
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13. IoS - Internet of Services
• IoS is about the software fabric that will connect
service providers and consumers
• IoS will enable the exchange of information and
knowledge between internet users (both human
and machines)
• In order to achieve this goal, IoS requires data
• IoT will enable data to flow
Anytime, Anyplace, with Anything and
Anyone, ideally using Any path/network and Any
service
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14. How to connect the IoT to the IoS
• The IoT must export interfaces to the IoS
• Connecting devices to the Internet
– Directly: e.g. 6lowpan
– Indirectly: through service gateways
• IoT is very heterogeneous
– Multiple Technologies, Multiple Information Sources
• How to overcome such heterogeneity ?
– Through Semantic Interfaces
– Through Data Mining
– Through Machine Learning Techniques
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15. Semantic Interfaces
• Semantic interoperability can be achieved between
heterogeneous information systems (service providers
and service requestors) in a multitude of ways.
– development of comprehensive shared information
models can facilitate semantic interoperability among the
participant applications and businesses
• Problem: it is rigid and inflexible when it comes to business
processes
– appropriate semantic mediators (translators) at each
participant’s end, to facilitate the conversion to the
information format which the participant understands
• Problem: add’s complexity to all participants (many IoT devices to
not have enough resources for these semantic mediators)
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16. Data Mining
• An alternative and/or complementary approach is to
use Data Mining techniques to extract information
from the raw data collected by IoT devices.
– Through processes such as:
• Classification
• Cluster Analysis
• Regression Analysis
• Structured Data Analysis
– Each IoT device can have their own interface and data
representation format.
– The IoS Application/Service will take the task to sort out
relationships between collect data.
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17. Machine Learning
• At a higher level we will find machine learning
techniques that will assist us at creating
relationships between the collected
information, and at extracting knowledge
from the IoT.
– Relevant Machine Learning techniques include
• Sparse Dictionary Learning
• Representation learning
• Artificial neural networks
• Support Vector Machines
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18. How to store IoT Data
?
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19. What to do with all the collect
Information?
• When we consider that we have billions of
connected devices all publishing information
we are faced with data gathering and storage
issues:
– We require a distributed network capable of
aggregating and processing information on the
network before it reaches the storage servers
– We require a highly efficient storage architecture
that efficiently store and process all data collected
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20. Storing Information
• There are currently two main solutions to store
information
– Relational Databases (traditionally referred to as SQL-
based), which are based on the relational model in
which information is stored in rows and grouped into
tables
– NoSQL Databases, a more recent technology that tries
to overcome some of the relational databases
problems related to performance and scalability at the
expense of some of the ACID properties of relational
databases.
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21. NoSQL Solutions
• NoSQL is not a class by itself, but a set a different
technologies that do not adhere to the traditional
relational model.
– Key/Value Store
– Wide Column Store
– Document Oriented
• Most NoSQL storage systems are also
schemaless, or schema-free, where no schema is
configured or enforced when using the database.
– This is an important aspect when considering the
heterogeneity of IoT
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22. We collect and properly store
information
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23. Creating IoT Services and Applications
• How to develop and execute applications on
top of the collect information and knowledge?
• A middleware architecture approach is of
importance in the IoT domain due to its role in
simplifying the development of new services
and integration of legacy technologies into
new ones
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24. IoT middleware platforms
B2B / B2C Web Portais Applications API’s
Service Delivery Platform
OSS
Information/Knowledge Management
Smart Objects Management
WAN : 2G/3G/LTE, xDSL, GPON
Sensor/Device Networks
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25. Service Creation and Deployment
• Most middleware architectures follow SOA
approaches, and adhere to it’s
principals, providing:
– service composition environment.
– abstracting the devices’ functionalities and
communication capabilities,
– provision of a common set of services
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26. Examples of middleware’s
• Several research projects have proposed
middleware platforms
– FP7 PERSIST: proposed a P2P middleware
– FP7 ICT m:Ciudad project: middleware as a mobile
application (Service Creation Kit)
– FP7 SENSEI: Service creation and composition is
handled by a Task Plan
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27. Pachube
• Pachube is a web service that enables a user
to store, share and discover real time data
from objects.
• It is a generalized real time data brokerage
platform, that facilitate interaction between
remote environments, both physical and
virtual
• It is based on the concept of feeds and
datastreams,
– Feed corresponds to a single location (for
example a house),
– Datastream is the information associated to a
given sensor with that location (for example
temperatures, power consumption).
• Pachube provides two modes for data
capture:
– pull method (automatic feed type), where
data is collected from an http server;
– push method (manual feed type) where data
is written to Pachube using an http client.
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28. Evrythng
• Evrythng provides an unique
online identity and profile for any
physical object
– allows users to create an active
digital presence for any sort of
physical object and to share
information about these real things
in real time
– allows sharing active information
about objects to enable others to
build services and applications
around those objects.
• A Thng is a unique identity and
profile for an object in Evrythng
– accessed through a globally unique
URI on the Web and through the
Evrythng API toolkit
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29. XCoA
• XCoA is a Broker-based Context
Management Architecture built
around the XMPP protocol
– It is built on top of the results of
EU FP7 project C-Cast
– Built on Federation principals
– Provided as an adaptation and
control layer independent of
Context Sources and Applications
• Context is described through XML
documents exchanged between
parties
• CxB PubSub stores context
information into a NoSQL db.
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30. Standards
• Mostly focused on M2M
• ETSI
– Proposes an Horizontal Architecture for M2M service
deployment
– Standardizing IT friendly API’s based on HTTP/REST
• 3GPP
– Still focused on communication aspects
• OMA
– BBF TR069 & OMA DM – data models for ETSI M2M
device management
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31. Standards
• W3C Semantic Sensor Networks Incubator Group (SSN-XG)
– has developed an ontology for describing sensors.
– models the sensor from device, process and system point of views.
– It includes different operational, device related and quality of
information attributes that are related to sensing devices.
– describes the operational range, battery and power and
environmental ranges that are specified for sensor devices.
– Information gathered by a sensor is out of scope of SSN-XG
• W3C Ubiquitous Web Applications Group
– Follow on to former Device Independence WG
– Plus broadened focus on Ubiquitous Web Applications
– Looking for people interested in working on
• device abstraction layer for web applications
• enabling applications across multiple devices
• content adaptation for multi-channel delivery
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32. IoT Applications/Services
Business Opportunities
• Added Value Services
with clear value
proposition for users
• Supplement low profit
margins on devices with
services
• Built upon tested models
– Service contracts
– Pay as you go
– Advertisements
– Freemium
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33. Conclusion
• IoT is of no value without an interconnection with the
IoS through service API’s
• IoT poses several important requirements on:
– Scalability
– Heterogeneous Interfaces
– Storage
– Middleware platforms
• There are several commercial and academic endeavors
in the area of IoT Applications and Services, but not
enough standardization.
• I’ve intentionally left Security, Privacy and Ethical issues
out of this presentation 
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34. “The most profound technologies are those that
disappear. They weave themselves into the
fabric of everyday life until they are
indistinguishable from it”.
– (Mark Weiser in The Computer for the 21st Century)
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35. Thank you for your attention…
…Questions?
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