MBICT

M2M to IOT
2180709
Prof.Dharmesh G Patel
Difference Between IoT and M2M
Global value chains
A value chain describes the full range of activities that firms and workers
perform to bring a product from its conception to end use and beyond,
including design, production, marketing, distribution, and support to the
final consumer

A value chain is a useful model to explain how markets create value

and how they evolve over time
M2M value chains
 Inputs:
data from an M2M device that will be turned into a
piece of information.
 Production/Manufacture:
Production/Manufacture refers to the process that the
raw inputs are put through to become part of a value
chain.
For example, cocoa beans may be dried and separated
before being transported to overseas markets. Data
from an M2M solution, meanwhile, needs to be
verified and tagged for provenance.
 Processing:
Processing refers to the process whereby a product is
prepared for sale. cocoa beans may now be made into
cocoa powder, ready for use in chocolate bars.
For an M2M solution, this refers to the aggregation of
multiple data sources to create an information
component something that is ready to be combined
with other data sets.
 Packaging:
Packaging refers to the process whereby a product can
be branded as would be recognizable to end-user
consumers.
 Distribution/Marketing:
This process refers to the channels to market for
products.

M2M value chains are internal to one company and

cover one solution.
IOT value chains
Inputs
 Devices/Sensors:
 Open Data:
city maps, provided by organizations such as Ordinance Survey
in the United Kingdom. Open data requires a license stating that
it is open data.
 OSS/BSS:
The Operational Support Systems and Business Support Systems
of mobile operator networks are also important inputs.
 Corporate Databases:
Companies of a certain size generally have multiple corporate
databases covering various functions, including supply chain
management, payroll, accounting, etc. ... Over the last
Production/Manufacture
 Asset Information:
Asset information may include data such as
temperature over time of container during transit or air
quality during a particular month.
 Open Data Sets: Open data sets may include maps, rail
timetables, or demographics about a certain area in a
country or city.
 Network Information: Network information relates to
information such as GPS data, services accessed via the
mobile network, etc. ...
 Corporate Information: Corporate information may be, for
example, the current state of demand for a particular
product in the supply chain at a particular moment in time.
Processing
 The data from the various inputs from the production
and manufacture stage are combined together to
create infor-mation.
Packaging
 Packaging:
After the data from various inputs has been combined
together, the packaging section of the information
value chain creates information components.
 These components could be produced as charts or
other traditional methods of communicating
information to end-users.
Distribution/Marketing
 The final stage of the Information Value Chain is the
creation of an Information Product.

 Two main categories:

 Information products for improving internal decision-
making:
 Information products for resale to other economic
actors:
Information-Driven Value Chain for
Retail
The information-driven global
value chain
 There are five fundamental roles within the I-GVC
 Inputs:
 Sensors, RFID, and other devices.
 End-Users.
 Data Factories.
 Service Providers/Data Wholesalers.
 Intermediaries.
 Resellers.
I-GVC
Inputs to the information-driven
global chain

 Sensors, RFID, and other devices.

 End-Users.

 Both of these information sources input tiny amounts

of data into the I-GVC chain, which are then
aggregated, analyzed, repackaged, and exchanged
between the different economic actors that form the
value chain.
Production processes of I-GVC
 Data Factories.
 Service Providers/Data Wholesalers.
 Intermediaries.
 Resellers.
Data Factories.
 Data factories are those entities that produce data in
digital forms for use in other parts of the I-GVC. Many
of these companies existed in the pre-digital era.
 for example, Ordnance Survey (OS) in the UK has
always collected map information from the field, and
collated and produced maps for purchase.
 Previously, such data factories would create paper-
based products and sell them to end-users via retailers.
 With the move to the digital era, however, these
companies now also provide this data via digital
means.
Service Providers/Data
Wholesalers
 Service Providers and Data wholesalers are those
entities that collect data from various sources
worldwide, and through the creation of massive
databases, use it to either improve their own
information products or sell information products in
various forms.
 examples exist; several well-known ones are Twitter,
Facebook, Google, etc....
Intermediaries
 In the emerging industrial structure of the I-GVC,
there is a need for intermediaries that handle several
aspects of the production of information products.
 There are many privacy and regional issues associated
with the collection of personal information.
 These corporations will provide protection for the
consumer that their data is being used in an
appropriate manner.
Resellers
 Resellers are those entities that combine inputs from
several different intermediaries, combine it together,
analyze, and sell it to either end-users or to corporate
entities.
 One example is BlueKai, which tracks the online
shopping behavior of Internet users and mines the
data gathered for “purchasing intent” in order
to allow advertisers to target buyers more accurately.
 BlueKai combines data from several sources, including
Amazon, Ebay, and Alibaba.
An Architectural Overview
Cont.
Main design principles
 Design for reuse of deployed IoT resources across
application domains.
 Design for different abstraction levels that hide
underlying complexities and heterogeneities.
 Design for ensuring trust, security, and privacy.
 Design for scalability, performance, and effectiveness.
 Design for simplicity of management.
 Design for lifecycle support.
Functional layers and capabilities
of an IoT solution
Cont.
 Assets are instrumented with embedded technologies that
bridge the digital realm with the physical world, and that
provide the capabilities to monitor and control the assets as
well as providing identities to the assets.
 The Resource Layer provides the main functional
capabilities of sensing, actuation, and embedded identities.
 The purpose of the Communication Layer is to provide the
means for connectivity between the resources on one end
and the different computing infrastructures that host and
execute service support logic and application logic on the
other end.
Service Support Layer
 These support services are provided by the Service Support
Layer and are typically executing in data centers or server
farms inside organizations or in a cloud environment.
 These support services can provide uniform handling
of the underlying devices and networks, thus hiding
complexities in the communications and resource layers.
 Examples include remote device management that can do
remote software upgrades, remote diagnostics or recovery,
and dynamically reconfigure application processing such as
setting event filters.
Data and Information Layer
 Data and Information Layer provides a more abstract
set of functions as its main purposes are to capture
knowledge and provide advanced control logic
support.
 Key concepts here include data and information
models and knowledge representation in general,and
the focus is on the organization of information.
 We refer to a Knowledge Management Framework
(KMF) as a collective term to include data,
information, domain-specific knowledge.
The Application Layer
 The Application Layer in turn provides the specific
IoT applications.
 There is an open-ended array of different applications,
and typical examples include smart metering in the
Smart Grid, vehicle tracking, building automation, or
participatory sensing (PS).
Business Layer
 The final layer in our architecture outline is the Business
Layer, which focuses on supporting the core business or
operations of any enterprise,organization, or individual
that is interested in IoT applications.
 This is where any integration of the IoT applications into
business processes and enterprise systems takes place.
 The enterprise systems can, for example,be Customer
Relationship Management (CRM), Enterprise Resource
Planning (ERP), or other Business Support Systems (BSS).
Management
 This includes management of devices,
communications networks, and the general
Information Technology (IT) infrastructure as well as
configuration and provisioning data, performance of
services delivered.
Security
 Security is about protection of the system, its
information and services, from external threats or any
other harm.
 Security measures are usually required across all
layers, for instance, providing communication security
and information security.
 Trust and identity management, and authentication
and authorization, are key capabilities.
Data and Services
 This functional group thus represents the vertical flow
of data into knowledge.
 provide the abstraction of data and services in
different levels, and the process steps of extracting
knowledge.
Standards considerations
 The primary objective of any technology oriented
standardization activity is to provide a set of agreed-
upon specifications that typically address issues like
achieving interoperability in a market with many
actors and suppliers.
 The first consideration is that standards are
developed across a number of different industries.
 There are a number of standardization organizations
and bodies.
 Standards Development Organizations (SDO)as
well as special interest groups that develop
standards specifications.
 Different national and international bodies approve
standards by by SDOs, whereas standard specifications
developed by special interest groups.
 Examples of international SDOs are the International
Telecommunications Union (ITU) and the
International Organization for Standardization (ISO),
 European Telecommunications Standards Institute
(ETSI) and the European Committee for Electro
technical Standardization (CENELEC) are examples of
regional SDOs.
 Other independent international standardization
organizations include the World Wide Web
Consortium (W3C) and the Internet Engineering Task
Force (IETF).
 one can make a distinction between standards
developed within the Information and
Communications Technology (ICT) industry, and
standards that are developed within a specific industry
segment, such as the Health, Transportation, or
Electricity industry segments.
 The applied IoT industry segments make use of the
ICT standards to varying degrees in developing their
standards.
 The second consideration is that some
Standardization activities define entire systems or
parts of systems.
 System standards can address a 3G mobile
communication network as defined within the 3rd
Generation Partnership Project (3GPP).
 Organizations like the IETF, on the other hand, focus
on developing the protocol suite of the Internet
without any effort to specify a system standard.
 The third and final consideration is about the
lifecycle process of standards.
 Many times, standards are emerging as a result of
collaborative research involving both academia and
industry.