INTERNET OF THINGS
Module-1:
1. Define IOT:

The Internet of Things (IoT) describes the network of physical objects—“things”—that are
embedded with sensors, software, and other technologies for the purpose of connecting and
exchanging data with other devices and systems over the internet. These devices range from
ordinary household objects to sophisticated industrial tools.
2. Define m2m:

Machine
to
machine (M2M)
is
direct
communication
between
devices
using
any communications channel, including wired and wireless.

It is technology to interconnect two or more divices all machines to connect with each other.

M2m technology available in ore homes, ofices, shopping malls and other places.

For example controlling electrical appliances like bulbs and fans using radio frequency or
Bluetooth from your smartphones
Introduction to Internet of Things (IoT)
Internet of Things (IoT) is the networking of physical objects that contain electronics embedded within their
architecture in order to communicate and sense interactions amongst each other or with respect to the external
environment. In the upcoming years, IoT-based technology will offer advanced levels of services and practically
change the way people lead their daily lives. Advancements in medicine, power, gene therapies, agriculture,
smart cities, and smart homes are just a very few of the categorical examples where IoT is strongly established.
There are four main components used in IoT:
1. Low-power embedded systems – Less battery consumption, high performance are the inverse factors play a
significant role during the design of electronic systems.
2. Cloud computing – Data collected through IoT devices is massive and this data has to be stored on a reliable
storage server. This is where cloud computing comes into play. The data is processed and learned, giving more
room for us to discover where things like electrical faults/errors are within the system.
3. Availability of big data – We know that IoT relies heavily on sensors, especially real-time. As these
electronic devices spread throughout every field, their usage is going to trigger a massive flux of big data.
4. Networking connection – In order to communicate, internet connectivity is a must where each physical
object is represented by an IP address. However, there are only a limited number of addresses available
according to the IP naming. Due to the growing number of devices, this naming system will not be feasible
anymore. Therefore, researchers are looking for another alternative naming system to represent each physical
object.
There are two ways of building IoT:
1. Form a separate internetwork including only physical objects.
2. Make the Internet ever more expansive, but this requires hard-core technologies such as rigorous cloud
computing and rapid big data storage (expensive).
IoT Enablers –
 RFIDs: uses radio waves in order to electronically track the tags attached to each physical object.
 Sensors: devices that are able to detect changes in an environment (ex: motion detectors).
 Nanotechnology: as the name suggests, these are extremely small devices with dimensions usually less
than a hundred nanometers.
 Smart networks: (ex: mesh topology).
Characteristics of IoT:




Massively scalable and efficient
IP-based addressing will no longer be suitable in the upcoming future.
An abundance of physical objects is present that does not use IP, so IoT is made possible.
Devices typically consume less power. When not in use, they should be automatically programmed to
sleep.
 A device that is connected to another device right now may not be connected in another instant of time.
 Intermittent connectivity – IoT devices aren’t always connected. In order to save bandwidth and battery
consumption, devices will be powered off periodically when not in use. Otherwise, connections might
turn unreliable and thus prove to be inefficient.
Application Domains: IoT is currently found in four different popular domains:
1) Manufacturing/Industrial business - 40.2%
2) Healthcare - 30.3%
3) Security - 7.7%
4) Retail - 8.3%
Modern Applications:
1. Smart Grids
2. Smart cities
3. Smart homes
4. Healthcare
5. Earthquake detection
6. Radiation detection/hazardous gas detection
7. Smartphone detection
8. Water flow monitoring
A USE CASE EXAMPLE: Human stress management
 Measures are heart rate & GSR(Galvanic skin Response)
Let’s See About Human Stress Management
Refer Note Page no: 14 & 15
Define IOT Value Chain?
Looking at the IOT value chains as a pyramid, at the base us all the connected devices:
 Phones,
 Fitness bands,
 Connecterd Cars,
 Smart homes, and
 Other Devices
On the consumer side in industry, you have things like building sensors, smart cities and connected
factories.
M2M TOWARDS IOT – The Global Context:
M2M solutions have been around for decades and are quite common in many different scenarios. While
the need to remotely monitor and control assests – Personal, enterprise or other is not new, a number of
concurrent things are now converging to create drivers for change not just within the technology industry, but
within the wider global economy and society.
Our planet is facing massive challenges – environmental, social, and economic. The changes that
humanity needs to deal with in the coming decades are unprecedented, not because similar things have not
happened before during our common history on this planet, but because on natural them are happening at the
same time. From constraints on naturals resources to a reconfiguration of the world’s economy many people are
looking to technology to assists with this issues.
Essentialy, therefore, a set of megatrends are coming to create needs and capabilities, which in
turn produce a set of IOT technology and business Drivers.
A megatrends is a pattern or trend that will have a fundamental and global impact on society at a
macro level over several generations. It is somethings that will Have a significant impact on the
world in the foreseeable future.
We here imply both game changers as challenges, as well as technology and science to meet these
challenges. A full description of megatrends is beyond the scope of this book, and interested readers are directed
to the many excellent books and reports available on this topic, including publications from the national
intelligence commercial (NIC 2012), European internet foundation(EIF 2009), Frost & Sullivan Following
section, we focus on the megatrends that have implications for IOT.
M2M VALUE CHAIN:
M2M Value chain are internal to one company or organization and gives a solution to one problem. The
following are the main functions processed by M2M Value Chain.
i.
ii.
iii.
iv.
v.
INPUT:
The input are raw material are ingrediance to make a product.
PRODUCTION MANUFACTURE:
`
It refers to the process through which the raw inputs became part of value chain.
PROCESSING:
It refers to the process by which the product is prefer for sale.
Packaging:
It is a process by which the product can be branded
DISTRIBUTION MARKETING:
It is refers to the channels to market the product.
DIFFERING CHARACTERISTICS IN M2M AND IOT:
SL.NO
1
2
3
4
5
M2M
IOT
It is a direct communication betweend the
machines
It is support point-to-point communication
Devices do not rely on internet connection
Hardware based technique
Machine normally communicate with a simple
That IOT is about sensor automated and internet
platform
It Support cloud communication
Devices drely on Internet connection
Hardware and Software Based Technique
Many users can access at one time over the internet
6
machine at a time
Devices can connected to mobile (or) other Devices can be connected to internet protocol (IP)
network
through the Internet
Internet Big
7
Data
Module-2:
A MARKET PERSPECTIVE:
Definition of M2M
Machine to machine refers to technology that allowed both wireless and wired systems to communicate
with other devices of the same type.
Machine to Machine (M2M) technology allows organization to gather data from the edge of the
enterprise and apply it in way that positively impact the business.
exchange the information between machine that is established between central control system (server)
and any type of equipment, through one or several communication networks.
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
Analyzing an industry from a global value chain (GVC) perspective permits understanding of the context of
globalization on the activities contained within them by “focusing on the sequences of tangible and intangible
value-adding activities, from conception and production to end use. GVC analysis therefore provides a holistic
view of global industries both from the top down and from the bottom up”.
M2M value chain
IoT value chains
The Information-Driven Global Value Chain(I-GVC)








Fundamental roles within the I-GVC
Inputs:
Sensors, RFID, and other devices.
End-Users.
Data Factories.
Service Providers/Data Wholesalers.
Intermediaries.
Resellers.
The Information-Driven Global Value Chain.
Inputs to the information-driven global commodity chain


Sensors and other devices (e.g. RFID and NFC).
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
from
value
chain.
-> As a result, sensor devices and networks, RFIDs, mobile and consumer devices, Wi-Fi hotspots, and
end-users all form part of a network of “subcontractors” in the value chain, all contributing to the
increased value of the information products
Sensors and radio frequency identification





Sensors and RFID devices are working as inputs to the I-GVC through the capture and transmission of
data necessary for the development of information products.
Smart phones have also been developed that allow mobile devices to interact with sensors and RFID.
This allows for a two-way interaction between a mobile terminal and the sensor technology.
The data is used as one part of the input to the commodity chain, which uses it to create the information
products that are eventually exchanged.
In this sense, the sensor networks, and NFC and RFID technologies may be viewed as subcontractors
Resellers Intermediaries Data Factories Service Providers/ Data Wholesalers End User Information
Domestic and overseas input from human and sensor-based ‘subcontractors’ to the I-GVC, workers that
constantly gather data for further processing and sale.
End-users




End-users that choose to use and participate within the digital world are now deeply embedded into the
very process of production.
Every human that enters a search query into a search engine,
Every human that agrees to allow the mobile broadband platform to inform a service of their location,
Every human that uses NFC to allow a bank to establish and confirm their identity are also functioning as
subcontractors to the global information systems that form the basis of the I-GVC.
Production processes of the information – driven global value chain





Data factories
Data factories are those entities that produce data in digital forms for use in other parts of the I-GVC.
Service providers/data wholesaler:
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.
Example: Twitter, Facebook, Google
M2M TO IOT- An architectural overview:
i.
ii.
iii.
iv.
European Telecommunication standard institute(ETS1) M2M
International Telecommunication union (ITU)
Internet Engineering Task Force Architecture fragments
Open geospatial consortium architecture
NETWORK DOMAIN
M2M
M2M Application
Management
M2M service capabilities
Function
<
Core Network
Network
Management
Access Network
Function
Devices & Gateway Domain
M2M Service capabilities
<
M2M Application
<
M2M gateway
<
M2M Devices
M2M Service gateway
<
M2M Application
<
M2M gateway
<
ETS1 M2M Reference Architecture:
He is a combination of both functional and topological view and give some functional group.(FG)
The device and gateway domain contains the following entities.
M2M Device:
M2M device contains M2M application and M2M service capabilities
M2M device connects to the networks domain either directly or through and M2M gateway
M2M Area Network:
 This is typically a LAN or PAN which provides connectively between M2M devices and M2M gateways.
Eg,
IEEE 802.15.1 (Bluetooth), IEEE 802.15.4 (Zig Bee)
M2M Gateway:
1. Network Domain Entities:
 This contains M2M Applications and M2M services capabilities. It also provides services to other
devices that are not visible to the network domain.
i.
Access Network:
This network allows the devices in the devices and gateway domain to communicate with
the core network.
Eg,
 Wireless LAN
 W-LAN, WIMAX, XDLS, HFC
ii.
2.
Core Network:
This network is used to provide the following function namely – IP connectivity Service
and Network control, Interconnection with other network and Roming.
iii. M2M Service Capabilities
iv. M2M Service Application
v. M2M Management Function
ETS1 M2M Service Capabilities:
i. Application Enablement (XAE)
ii. Generic Communication (XGC)
iii. Reachability, Addressing & Repository(XRAR)
iv. Communication Selection (XCS)
v. Remote Entity Management (XREM)
vi. Security (XSEC)
vii. History and Data Retention(XHDR)
viii.
ix.
x.
xi.
3.
Transaction Management (XTM)
Compensation broker (XCB)
Telco Operator Exposure (NTOE)
Internetworking Proxy (XIP)
ETS1,M2M Interfaces :
The following are the three main interfaces:
 mIa
 dIa
 mId
ETS1,M2M Resource Management :
ETS!,M2M Architecture assumes that application structures devices application(DA), Gateway
Application(GA), Neytwork Application (NA), Exchange information by performing CRVD operation
4.
(Create Read Update Delete) on a number of Resources by using REST full Architecture
(Representational State Transfer)
Main design Principles and needed capabilities:
i.
ii.
iii.
iv.
v.
vi.
vii.
The architecture relies on the separation of resources providing sensing and actuation from the actual
devices, a set of contextual and real world entity centric services, and the users of the services.
SENSEI further relies on open – ended constellation of providers and users, and also provides a reference
model for different business roles.
A number of design principles and guidelines are identified, and so is a set of requirements
Finally, the architecture itself contains a set of key functional capabilities
IOT – A refers to as the Architectural reference model(ARM)
The Vision of IOT – A is, via the ARM, to establish a means to achieve a high degree of interoperability
between different IOT solutions at the different system levels of communication, service and information.
IOT – A provides a set of different architectural views, establishes a proposed terminology and a set of
unified Requirements.
An IOT Architectural outline:
Functional layer and capabilities of and IOT solution
Business Layer
Data and Information Layer
Security
Management
IOT Data and Services
Application Layer
Service Support Layer
Communication Layer
Resource Layer
Asset Layer
ASSET LAYER:



Real-world objects and entities that are subject to being monitored and controlled, as well as
having digital representations and identities.
For example:
1. Vehicles
2. Home
3. Human
4. Buildings etc.
Assets can also be of a more virtual character, being subjective representations of parts of the real
world.
For example: Latterroutestrickslogisticsinformationtraffic intensityroadworkroad
conditionsweather situation.
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.
For examples:
1. Tags: RFID
2. Optical Codes: barcodes
3. QR (Quick Response) code.
COMMUNICATION LAYER:
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
DATA AND INFORMATION LAYER:
MANAGEMENT:
SECURITY:
DATA AND SERVICES:
Standards Considerations:
 There are a number of standardization organizations and bodies, both proper standards Development
Organization (SDO) as well as special interest groups and alliances that develop standards specifications.
CONSIDERATION
1
INTEREST
 Different national and international
bodies ratify standards by SDOs,
whereas standards specifications
developed by special interest group
and alliances are normally agreedupon and adopted by market actors
such as technology manufactures
EXAMPLE
 International Telecommunications
Union(ITU)
 International organization for
standardization(ISO)
 European Telecommunication standards
institute(ETSI)
 The European committee for electro
2
3
 System standards can address 3G
mobile communication network as
defined within the 3rd generation
partnership project (3GPP) or
standards towards the smart grid as
done by the national Institute of
standards and technology(NIST)
 Standards are emerging as a result of
collaborative research involving both
academia and industry
technical standardization(CENELEC)
 System standards rely on the enabling
technology components as the foundation,
but as there generally are many competing
technology components (eg., Protocol
stacks), the adoption into a system
standard is not a straightforward route
 Technology are selection for
standardization can happen as part of
requlatory or legislative process
Module-3:
M2M AND IOT TECHNOLOGY FUNDAMENTALS:
Four fundamental components of an IoT system:
1) Sensors/Devices: Sensors or devices are a key component that helps you to collect live data from the
surrounding environment. All this data may have various levels of complexities. It could be a simple temperature
monitoring sensor, or it may be in the form of the video feed.
A device may have various types of sensors which performs multiple tasks apart from sensing. Example, A
mobile phone is a device which has multiple sensors like GPS, camera but your smartphone is not able to sense
these things.
2) Connectivity: All the collected data is sent to a cloud infrastructure. The sensors should be connected to the
cloud using various mediums of communications. These communication mediums include mobile or satellite
networks, Bluetooth, WI-FI, WAN, etc.
3) Data Processing: Once that data is collected, and it gets to the cloud, the software performs processing on the
gathered data. This process can be just checking the temperature, reading on devices like AC or heaters.
However, it can sometimes also be very complex like identifying objects, using computer vision on video.
4)User Interface: The information needs to be available to the end-user in some way which can be achieved by
triggering alarms on their phones or sending them notification through email or text message. The user
sometimes might need an interface which actively checks their IOT system. For example, the user has a camera
installed in his home. He wants to access video recording and all the feeds with the help of a web server.
However, it's not always one-way communication. Depending on the IoT application and complexity of the
system, the user may also be able to perform an action which may create cascading effects.
 For example, if a user detects any changes in the temperature of the refrigerator, with the help of IOT
technology the user should able to adjust the temperature with the help of their mobile phone.
DEVICES AND GATEWAYS:
Devices:
Introduction:
A device can be characterized as having several properties, including:
• Microcontroller: 8-, 16-, or 32-bit working memory and storage.
• Power Source: Fixed, battery, energy harvesting, or hybrid.
• Sensors and Actuators: Onboard sensors and actuators, or circuitry that allows them to be connected,
sampled, conditioned, and controlled.
• Communication: Cellular, wireless, or wired for LAN and WAN communication.
• Operating System (OS): Main-loop, event-based, real-time, or fullfeatured OS.
• Applications: Simple sensor sampling or more advanced applications.
• User Interface: Display, buttons, or other functions for user interaction.
• Device Management (DM): Provisioning, firmware, bootstrapping,and monitoring.
• Execution Environment (EE): Application lifecycle management and Application Programming Interface
(API).
Device type
Device types they are classified into two types.They are,


Basic Device
Advanced Device
Basic Devices: Devices that only provide the basic services of sensor readings and/or actuation tasks, and in
some cases limited support for user interaction. LAN communication is supported via wired or wireless
technology, thus a gateway is needed to provide the WAN connection.
Advanced Devices: In this case the devices also host the application logic and a WAN connection. They may
also feature device management and an execution environment for hosting multiple applications. Gateway
devices are most likely to fall into this category.
Deployment scenarios for devices:
Deployment can differ for basic and advanced deployment scenarios. Example deployment scenarios for basic
devices include:
• Home Alarms: Such devices typically include motion detectors, magnetic sensors, and smoke detectors. A
central unit takes care of the application logic that calls security and sounds an alarm if a sensor is activated
when the alarm is armed. The central unit also handles the WAN connection towards the alarm central. These
systems are currently often based on proprietary radio protocols.
• Smart Meters: The meters are installed in the households and measure consumption of, for example,
electricity and gas. A concentrator gateway collects data from the meters, performs aggregation, and periodically
transmits the aggregated data to an application server over a cellular connection.
• Building Automation Systems (BASs): Such devices include thermostats, fans, motion detectors, and boilers,
which are controlled by local facilities, but can also be remotely operated.
• Standalone Smart Thermostats: These use Wi-Fi to communicate with web services. Examples for advanced
devices, meanwhile, include:
• Onboard units in cars that perform remote monitoring and configuration over a cellular connection.
• Robots and autonomous vehicles such as unmanned aerial vehicles that can work both autonomously or by
remote control using a cellular connection.
• Video cameras for remote monitoring over 3G and LTE.
• Oil well monitoring and collection of data points from remote devices.
• Connected printers that can be upgraded and serviced remotely.
Basic devices:
These devices are often intended for a single purpose, such as measuring air pressure or closing a valve. In some
cases several functions are deployed on the same device, such as monitoring humidity, temperature, and light
level
Advanced devices
As mentioned earlier, the distinction between basic devices, gateways, and advanced devices is not cut in stone,
but some features that can characterize an advanced device are the following:
• A powerful CPU or microcontroller with enough memory and storage to host advanced applications, such as a
printer offering functions for copying, faxing, printing, and remote management.
• A more advanced user interface with, for example, display and advanced user input in the form of a keypad or
touch screen.
• Video or other high bandwidth functionsIt’s not unusual for the advanced device to also function as a gateway
for local devices on the same LAN.
GATEWAYS
A gateway serves as a translator between different protocols, e.g. between IEEE 802.15.4 or IEEE 802.11, to
Ethernet or cellular.
There are many different types of gateways, which can work on different levels in the protocol layers. Most often
a gateway refers to a device that performs translation of the physical and link layer, but application layer
gateways (ALGs) are also common. The latter is preferably avoided because it adds complexity and is a common
source of error in deployments.
Some examples of ALGs include the ZigBee Gateway Device (ZigBee Alliance 2011), which translates from
ZigBee to SOAP and IP, or gateways that translate from Constrained Application Protocol (CoAP) to HyperText
Transfer Protocol/Representational State Transfer (HTTP/REST).
For some LAN technologies, such as 802.11 and Z-Wave, the gateway is used for inclusion and exclusion of
devices. This typically works by activating the gateway into inclusion or exclusion mode and by pressing a
button on the device to be added or removed from the network.
For very basic gateways, the hardware is typically focused on simplicity and low cost, but frequently the
gateway device is also used for many other tasks, such as data management, device management, and local
applications. In these cases, more powerful hardware with GNU/Linux is commonly use
Local and wide area networking:
Local Area Networks (LAN)
Local Area Network (LAN) is a computer network, which is limited to a small office, single building, multiple
buildings inside a campus etc. Typically, a Local Area Network (LAN) is a private network owned and
maintained by a single organization.
Below image shows a small Local Area Network (LAN) connected together using a Network Switch.
The terms Local Area Network (LAN), broadcast domain and subnet are used interchangeably throughout
omnisecu.com website. Do remember that a Local Area Network (LAN) is comprised of one or more broadcast
domains. A Local Area Network (LAN) may contain one or more subnets also.
Wide Area Networks (WAN)
A Wide Area Network (WAN) spans over multiple geographic locations, which is composed of multiple LANs.
It is nearly impossible for a small to medium organization (except Network Service Providers) to pull network
cables between their two offices in two different countries located 1000s of kilometers away. Network Service
Providers (also called as ISPs) provide the connectivity solutions for Wide Area Networks (WAN).
Below image shows two Local Area Networks (LANs), located at two different geographical locations
connected via Internet to create a Wide Area Network (WAN). LAN 1 is located in Chennai, India and LAN 2 is
located in Manila, Philippines. The aerial distance between Chennai and Manila is about 4,400 kilometers. It is
almost impossible for a small to medium business to draw cables between Chennai and Manila. We normally
avail the services of an Internet Service Provider for connectivity between these two offices.
Differences between LAN and WAN
• A Local Area Network (LAN) is a private computer network that connects computers in small physical areas.
Example: A small office, A Single building, Multiple buildings inside a campus etc. Wide Area Networks
(WAN) is type of computer network to connect offices which are located in different geographical locations.
Wide Area Network (WAN) depends mainly on Internet Service Providers (ISPs) for connection solutions.
•
Local Area Network (LAN) has higher bandwidth rates. Current Local Area Networks (LANs) runs at
bandwidth speeds of 100 Mbps, 1 Gbps or 10 Gbps. Wide Area Networks (WAN) has lower bandwidth rates
compared with Local Area Network (LAN). Current Wide Area Networks runs on bandwidths of 20 Mbps, 50
Mbps or 100 Mbps.
• Local Area Network (LAN) bandwidth rates are almost constant. Local Area Network (LAN) bandwidth rates
are dependent on characteristics of the LAN technology in use (Normally FastEthernet or Gigabit Ethernet).
Since most of Wide Area Networks (WAN) connectivity solutions are dependent on Internet Service Providers
(ISPs), budget related constraints affect the quality of WAN.
• Most of the current Local Area Networks (LANs) use Ethernet as the LAN Standard (FastEthernet 100 Mbps,
or Gigabit Ethernet 1/10 Gbps). Normally for WAN connectivity, technologies like VPN (Virtual Private
Network) over Internet, or MPLS (Multi-Protocol Label Switching) are used.
• Since Local Area Networks (LANs) are private networks, managed by dedicated local network administrators,
Local Area Networks (LANs) are more reliable and secure than Wide Area Networks (WANs). Since Wide Area
Networks (WANs) involve third-party service providers, WAN networks are less reliable and secure.
• Initial set-up costs for Local Area Networks (LANs) are low as the devices required to set up the networks are
cheap. Initial set-up costs for Wide Area Networks (WANs) are high, because of the devices (Routers, Firewalls
etc.), cables and manpower required.
• Local Area Networks (LANs) running costs are less Wide Area Networks (WANs) running costs are high.
Wide Area Networks (WANs) normally have recurring monthly cost as Service Provider access fees.
DATA MANAGEMENT:
When customers embark on the journey to address IoT and IIoT use cases, the first hurdle they face is how to
retrieve the data from the IoT systems and make it available for the analytics systems and for decision making.
The ability to ingest the data from IoT systems into the data lake or into messaging systems like Apache Kafka is
a key first step. In most scenarios, organizations also want to enrich and cleanse the data to ensure that bad data
doesn’t get into the lake and the analysts have enriched data for their analytics. In some cases, customers want to
operationalize actions in real-time on IoT-enabled devices. For example, they may want to automatically stop a
painting machine if factory conditions get too warm for optimal paint adhesion—a situation that could cause
major quality and warranty issues if not corrected during manufacturing.
5 must-have capabilities for IoT data management
Managing data from IoT devices is an important aspect of a real-time analytics journey. To be sure your
data management solution can handle IoT data demands, look for these five key capabilities:
Versatile connectivity and ability to handle data variety: IoT systems have a variety of standards and IoT
data adheres to a wide range of protocols (MQTT, OPC, AMQP, and so on). Also, most IoT data exists in semistructured or unstructured formats. Therefore, your data management system must be able to connect to all of
those systems and adhere to the various protocols so you can ingest data from those systems. It is equally
important that the solution support both structured and unstructured data.
Edge processing and enrichments: A good data management solution will be able to filter out erroneous
records coming from the IoT systems—such as negative temperature readings—before ingesting it into the data
lake. It should also be able to enrich the data with metadata (such as timestamp or static text) to support better
analytics.
Big data processing and machine learning: Because IoT data comes in very large volumes, performing
real-time analytics requires the ability to run enrichments and ingestion in sub-second latency so that the data is
ready to be consumed in real time. Also, many customers want to operationalize ML models such as anomaly
detection in real time so that they can take preventive steps before it is too late.
M2M AND IOT ANALYTICS
The value of big data stems from its ability to surface relevant and actionable insights at the micro level.
The proliferation of Internet-connected devices presents a framework for analytics to become much more
granular in nature and an opportunity to better align the frequency of reporting to the pace of business
operations.
While today the biggest challenge lies in managing the variety–rather than the volume or velocity–of IoT data,
the general shift from batch- to event-based processing signals a growing interest in real-time / streaming
analytics as a lever for IoT value creation. The need to harmonize these components without creating or simply
shifting the bottlenecks that come with the management of high-velocity variable data puts pressure on
connectivity providers, edge analytics platform players, and system integrators (SIs) to stand up new and
distributed architectures to not only support, but also add value to data at any level.
In this research analysis, ABI Research analyzes what it considers to be the most significant trends and
developments related to the IoT analytics industry. The first section includes the conceptual framework
supporting the research, as well as a wrap-up of recent activity. The second section consists of the updated and
refined forecasts on the market’s revenues, broken down by application, region, value chain component, and
analytic phase (descriptive, predictive, prescriptive). A high-level revenue projection for the overall big data and
analytics market is also included at the end of the section for a view of IoT analytics in a broader industry
context. The final section provides a high-level assessment of a number of relevant vendors to exemplify the
different parts of the value chain.
Address data drift: Data coming from IoT systems can change over time due to events such as firmware
upgrades. This is called data drift or schema drift. It is important that your data management solution can
automatically address data drift without interrupting the data management process.
Real-time monitoring and alerting: IoT data ingestion and processing never stops. Therefore, your data
management solution should provide real-time monitoring with flow visualizations to show the status of the
process at any time with respect to performance and throughput. The data management solution should also
provide alerts in case any issues arise during the process.
KNOWLEDGE MANAGEMENT:
Knowledge management (KM) systems would have to be geared more and more for real time knowledge
updation. Customers buying patterns and the usage trends of equipments will come together to provide new
insights for marketing and product development teams and KM specialists have the opportunity to synthesise
both the data and arrive at new knowledge. Internet of Things and SMAC (social media, mobility, analytics and
cloud) are forcing businesses to rethink their goals and how value is created. Businesses have to balance their
goal of ‘reliability’ and move towards becoming ‘agile’ and value creation is no longer through price
performance alone but will happen by focussing on revenue generation by customer experience and brand
building.
Sensors and embedded technology enabling transmission of real time data through wireless networks will lead to
co creation of new real time knowledge with customers and vendors on a regular basis. The moot point all the
commonly owned data is likely to be accessible by all the stakeholders but the advantage would go the firm
which has the ability to interpret the data and convert it into real time knowledge which can be put to use for
competitive advantage. Opportunities for innovation by better understanding of product usage, performance and
customer experience will help create opportunities for creating and leveraging collaborative innovation platforms
with customers and vendors to spot, nurture and fructify innovation ideas.
In the changing world led by Internet of Things and Big Data, knowledge needs of individuals will get redefined.
L&D functions have to get equipped with capabilities to deal with data, machine interface and the threats of the
possibilities of machine intelligence surpassing human intelligence by rethinking methods and tools for making
the talent pool get to interpret system intelligence such that human intelligence becomes even more sharper.
Thus L&D teams will see a shift in their roles from being facilitators to coaches to data based interpretation of
training needs and profiling of employees.
Module - 4
IoT Architecture -State of the Art
A reference model is a model that describes the main conceptual entities and how they are related to each other,
while the reference architecture aims at describing the main functional components of a system as well as how
the system works, how the system is deployed, what information the system processes, etc.
An ARM is useful as a tool that establishes a common language of an M2M or IoT system.
State of the art
European Telecommunications Standards Institute M2M/oneM2M.
The European Telecommunications Standards Institute (ETSI) in 2009 formed a Technical Committee (TC) on
M2M topics aimed at producing a set of standards for communication among machines from an end-to-end
viewpoint.
ETSI M2M high-level architecture
1.1 )
ETSI M2M high-level architecture
M2M Device:


An M2M device connects to the Network Domain either directly or through an M2M Gateway
Direct connection:
 The M2M Device is capable of performing registration, authentication, authorization, management, and
provisioning to the Network Domain.
 Direct connection also means that the M2M device contains the appropriate physical layer to be able to
communicate with the Access Network.
M2M Gateway:


This is the case when the M2M device does not have the appropriate physical layer, compatible with the
Access Network technology, and therefore it needs a network domain proxy.
The M2M Gateway acts as a proxy for the Network Domain and performs the procedures of
authentication, authorization, management, and provisioning. An M2M Device could connect through
multiple M2M Gateways.
M2M Area Network:

This is typically a local area network (LAN) or a Personal Area Network (PAN) and provides
connectivity between M2M Devices and M2M Gateways
M2M Gateway:



The M2M Gateway contains M2M Applications and M2M Service Capabilities.
The M2M Gateway may also provide services to other legacy devices that are not visible to the Network
Domain.
The device that provides connectivity for M2M Devices in an M2M Area Network towards the Network
Domain.
Access Network:
The network that allows the devices in the Device and Gateway Domain to communicate with the Core Network.
Core Network:




IP connectivity.
• Service and Network control.
• Interconnection with other networks.
• Roaming.
M2M Service Capabilities:

Functions use underlying Core Network functions, and their objective is to abstract the network functions
for simpler applications.
M2M Applications:

M2M applications (e.g. smart metering) that utilize the M2M Service Capabilities through the open
interfaces.
Network Management Functions:

functions to manage the Access and Core Network
M2M Management Functions:




Functions required to manage the M2M Service Capabilities on the Network Domain while the
management of an M2M Device or Gateway is performed by specific M2M Service Capabilities.
There are two M2M Management functions:
M2M Service Bootstrap Function (MSBF).
M2M Authentication Server (MAS):
IOT ARCHITECTURE AND REFERENCE MODEL
The Internet of Things (IoT) is defined as a paradigm in which objects outfitted with sensors, actuators, and
processors interact with each other to serve a significant purpose.
THE BASIC IOT ARCHITECTURE IS DEFINED IN FOUR STAGES.SENSOR NODES <==>
GATEWAYS <==> INTERNET + CLOUD(SERVER) <==> VISUALIZATION AND CONTROL
ENDPOINTS.



Sensor Nodes: These are the physical things that carry sensors and actuators with it. Sensors that can
record environmental conditions and transmit them over the network. Actuators can respond to
commands from the network and show some mechanical response.
Gateway: A noticeable predicament in connecting the thing to the internet is that not all sensor nodes can
connect to the internet directly. And it is also not a good idea to connect each device directly to the
internet because of the restrictions of IP address and efficiency reduction. The answer for this problem is
an IoT Gateway. Which can handle interoperability of the communication protocols and can connect to
various devices and the internet at the same time.
note: this is not same as the Network
Gateway.
A Server operating on the Cloud: The gateway connects to the cloud through the internet. The Server
manages all the data coming from the Gateways and all the requests coming of the Visualization and
Control Endpoints. The data arriving in is also processed at the server depending on the deployment of
analytics algorithms and methods at the server. The clouds serve a Web UI and API endpoints for the rest
of the world to interact with it.

Visualization and Control Endpoints: The are devices with input and output devices built in, such as
mobile phones, remote controllers and PCs. The Web UI served and API endpoints on the cloud can be
consumed by these devices to read the data, do some operations on it or to send some commands to the
sensor nodes through the gateways over the internet.
IOT reference model:
1. Physical Devices and Controllers: These are similar to the sensor nodes discussed earlier. The actual
things in the Internet of Things.
2. Connectivity: The nodes in sensor nodes discussed earlier can be related to this. The basic device that
has some connectivity radios and contains the sensors. The Network devices also fall in the same
segment.
3. Edge Computing: The small level data processing at the gateway and sensor nodes is known as edge
computing. Some small tasks and actuator handling can also be done here.
4. Data Accumulation: The data that is sent over the internet via gateways by the sensor nodes are
acquired and stored in a database on the Cloud.
5. Data Abstraction: Normalization, filtering, expansion, aggregation of the data is done at the
cloud mainly.The main aim is ti get the required and significant data out of all the data that
is collected.Some small operations can be done at the Edge also.
6. Application: Analytics over the data and responding according to the data to control the actuators at the
sensor nodes is one of the main applications of the IoT Architecture.
7. Collaboration and Processing: This is the final level of the IoT Reference model. The human
interaction and involvement in the IoT scenario are seen as the most neglected parts. Not only the device
should be smart enough to perform certain tasks but they should also have some intuitive interactions
with the human. The iinvolment of People and Business processes is an essential prt of developping an
interesting IoT application.
MODULE-5
INTRODUCTION:
1. Functional View: Description of what the system does, and its main functions.
2. Information View: Description of the data and information that the system handles.
3. Deployment and Operational View: Description of the main real world components of the system such
as devices, network routers, servers, etc.
IOT FUNCTIONAL VIEW:
IOT functional view contains eight types, they are:
1.
2.
3.
4.
5.
6.
7.
8.
Device and Application functional group
Communication functional group
IOT Service functional group
Virtual entity functional group
Process management functional group
Service Organization functional group
Security functional group
Management functional group
1.1. Devices and application functional group:
Devices are like phone, machines.
1.2. Communication functional group:
The Hop-by-Hop Communication is applicable in the case that devices and messages
have to traverse the mesh from node-to-node (hop-by-hop) until they reach a gateway
node which forwards the message (if needed) further to the Internet.
This FC has two main interfaces:
 one “southbound” to/from the actual radio on the device, and
 one “northbound” to/from the Network FC in the Communication FG.
1.2 . IOT Service functional group:
The IoT Service FC is a collection of service implementations, which interface the related and
associated Resources.
For a Sensor type of a Resource, the IoT Service FC includes Services that receive requests from
a User and returns the Sensor Resource value in synchronous or asynchronous (e.g.
subscription/notification) fashion.
The IoT Service Resolution FC contains the necessary functions to realize a directory of IoT
Services that allows dynamic management of IoT Service descriptions and
discovery/lookup/resolution of IoT Services by other Active Digital Artifacts.
1.3 . Virtual entity functional group:
The Virtual Entity FG contains functions that support the interactions between Users and
Physical Things through Virtual Entity services.
An example of such an interaction is the query to an IoT system of the form
1.4 . Process management functional group:
It consists of two FCs:
 The Process Modelling FC provides that right tools for modelling a business process that
utilises IoT-related services.
 The Process Execution FC contains the execution environment of the process models
created by the Process Modelling FC and executes the created processes by utilising the
Service Organisation FG in order to resolve high-level application requirements to specific
IoT services
1.5 Service Organization functional group:
The Service Composition FC manages the descriptions and execution environment of
complex services consisting of simpler dependent services.
An example of a complex composed service is a service offering the average of the values
coming from a number of simple Sensor Services
1.6 Security Functional group
The Identity Management FC manages the different identities of the involved Services or
Users in an IoT system
The The Authentication FC verifies the identity of a User and creates an assertion upon
successful verification. verifies the identity of a User and creates an assertion upon successful
verification.
The Authorization FC manages and enforces access control policies. It provides services to
manage policies (CUD), as well as taking decisions and enforcing them regarding access
rights of restricted resources.
The Key Exchange & Management is used for setting up the necessary security keys
between two communicating entities in an IoT system.
1.7 Management functional group
The Configuration FC maintains the configuration of the FCs and the Devices in an IoT
system. The component collects the current configuration of all the FCs and devices, stores
it in a historical database, and compares current and historical configurations.
The Fault FC detects, logs, isolates, and corrects system-wide faults if possible. This means
that individual component fault reporting triggers fault diagnosis and fault recovery
procedures in the Fault FC.The component collects the current configuration of all the FCs
and devices, stores it in a historical database, and compares current and historical
configurations.
The Member FC manages membership information about the relevant entities in an IoT
system.
The State FC is similar to the Configuration FC, and collects and logs state information from
the current FCs,
IOT INFORMATION VIEW:
The pieces of information handled by an IoT system









Virtual Entity context information, i.e. the attributes (simple or complex) as represented by parts of the
IoT Information model.
IoT Service output itself is another important part of information generated by an IoT system. For
example, Sensor or a Tag Service.
Virtual Entity descriptions in general, which contain not only the attributes coming from IoT Devices
(e.g. ownership information).
Virtual Entity Associations with other Virtual Entities (e.g. Room #12 is on floor#7)
Resource Descriptions –> type of resource (e.g. sensor), identity, associated Services, and Devices.
Device Descriptions –> device capabilities (e.g. sensors, radios).
Descriptions of Composed Services –> the model of how a complex service is composed of simpler
services.
IoT Business Process Model describes –> the steps of a business process utilizing other IoT-related
services.
Management information such as state information from operational FCs used for fault/performance
purposes, configuration snapshots, reports, membership information, etc.
IOT DEPLOYMENT AND OPERATIONAL VIEW:
ARCHITECTURE OF IOT:
Overall technological advances have contributed to the fact that electronic and other devices become smarter
with the ability to produce a large amount of data. In addition, the networking of computers and the Internet has
enabled data exchange in both local and Geo-global environments.
From the real-world perspective, including elements of use by ordinary observers such as vehicles, trains, planes,
lights, clocks, parking garages … appears a common denominator in the world of smart devices and it’s called
the Internet of Things (IoT). It keeps the basic idea of connecting all devices to each other. Internet of things can
be understood as the natural evolution of the web because it connects information technology and many other
operational technologies. This technology connects more than ordinary devices – it connects all devices that
contain such a collection of sensors or any device that generates digital data including humans as an overall data
producer. By connecting and networking on a shared thread, the Internet of Things is becoming a based machine
that uses data streams as its fuel to build a novel ecosystem based on a few elements.
Things include all sorts of existing devices that are able to produce data directly or by transforming an analog
device signal into useful digital data from. Furthermore, within the ecosystem, things are actually virtual copies
of objects made up of different forms of data.
Data are digital representation of the various physical forms, objects and even minds thus enabled to be
exchangeable, processed by machines and converted into useful information used by human beings as intelligent
decisions.
Humans as end node data producers and connected to the Internet become an active actor of the IoT ecosystem
by leveraging process of data producing, transforming and sharing.
Processes as a common connectivity and communication descriptor lead us to the overall IoT ecosystem which is
able to ingest data autonomously and act as much as self-configured structure.
By representing physical objects and processes by its virtual copies, the IoT ecosystem is limited by a level of
fragmentation. Since this is an anomaly, even the ecosystem must be overcome in some way. It is also necessary
to allow unhindered data flow and, therefore, the evaluation of the events in the system of independent decisionmaking. For this, it is necessary to define the structure, i.e. the rules of behavior and functioning of the elements
within the IoT ecosystem. Since all of this already coincides and is functionally expressed through already
existing technological postulates, it is easiest to define all this through a unique, i.e. the reference architecture of
the IoT ecosystem.
The process of forming the reference architecture of the IoT ecosystem is not at all simple. The reason for this is
the high dynamism of the elements inside the system, as well as the rapid conglomeration of new solutions in
terms of data processing throughout the entire cycle.
In addition, the integration of artificial intelligence into building elements leads to a greater degree of activity
and the occurrence of events that can be independently triggered and controlled within the system. This increases
the need for efficient scaling of processes and the participation of all other information-science actors within the
ecosystem.
In the professional literature and also in practice, there is a more diverse review of the reference architecture of
the IoT ecosystem. Starting from those proposed by various equipment manufacturers, IoT elements, platforms
of both conventional IoT systems and industrial IoT, there are also references architectures proposed by various
consortia and official technical-scientific bodies within governments and intergovernmental organizations.
From this perspective, considering the transformation of existing business processes into the active IoT
ecosystem, only some views and perspectives will be discussed without a deeper analysis of all the reference
architecture and below are some simplified views of the reference architecture reviews from the software
development perspective within the IoT ecosystem.
The Layers of the IoT Architecture
Conventional Architecture
One of the basic and simplified models of the reference architecture is the so-called Conventional IoT
architectural model – Three layer IoT Architecture.
Perception layer belongs to the world of sensors, actuators and smart devices. At this level, data production is
done. In addition to the active and passive components in this layer, the so-called “edge elements” which, along
with “Things” are data producers of the IoT ecosystem. Also, communication from this Layer to the outside
world is directed to the cloud environment and is managed using standard network infrastructure as well as
localized RF – radio frequency networks.
Network layer covered the area of gateways and routers. Here are most elements of the IoT ecosystem – physical
devices or software program between clouds and controllers, sensors and smart devices. Their role is also to
discover, i.e. detects intelligent devices in the perception layer and translates them into the network and establish
coordination with the applications. If they are hardware devices, they are mostly Plug & Run devices with a
simple configuration via a web interface. In some descriptions this layer is also called a Transport layer.
Application layer is a part of the cloud and servers. Functionally, it’s usually some of Cloud services like AVS or
Google Cloud, server farms, or even a local remote server company (on premise). The application layer also
includes powerful servers and databases that allow large IoT applications to easily integrate, use spanking data
storage services with high-speed data processing. The data thus available are easy to filter, build analytics, and
API’s user-friendliness. The benefit of this is reflected in an improved and more advanced business logic. In
addition, the security of the IoT ecosystem itself with advanced warning systems and real-time monitoring
increases.
Support layer was added to the list later as a necessity to give more effective and transparent communication
between the application layer and networking layer as contains the services by using APIs.
Five layer IoT Architecture
Another IoT architectural model, is built as an extension of three layer approach. Two more layers are added: a
Business and a Processing layer.
With two new layers, IoT architecture still belongs to cloud-centric based architectural model. It turns out that
most of the operations or data transfer and processing are performed on cloud or remote servers.
The introduction of a business layer as a top layer is justified by the multifaceted user requirements. The
complexity of the business logic in the process of creating the IoT system has sidelined the process of data
management in the application layer so that the coordination of business logic is shifted to the new layer. This
has led to more stable architecture in terms of the sustainability in perception of connecting different
technologies and diverse business areas.
An important element of improving the IoT ecosystem at the architectural level was achieved by introducing the
processing layer. As data production increased, IoT systems became cumbersome and difficult to filter data. The
layer is often processed, i.e. filtering mass sets of data and data from the Big Data category, in such a way that
the processing layer can be found at more than one point within the IoT ecosystem, which leads to resource
optimization and more efficient processing and filtering of large amounts of data which is very important for
realizing real-time processing as an important factor of efficiency.
Seven layer IoT architecture
Seven layers of IoT architecture is the one most commonly used by users (referred by) when attempting to
explain IoT ecosystem appearance and its structure.
The things – in order to realize one IoT environment, i.e. the ecosystem needs to have a variety of devices,
sensors and controllers that enable their interconnection. This also means that the end point of an IoT system
must have connected devices – besides standard sensors, the actuators also include smartphones, microcontrollers, computers, etc.
Layer two – Connectivity/Edge represents the environment and the place where all connections are made before
the exchange of data within the IoT ecosystem. It defines all communication protocols, and establishes a network
for Edge computing. Therefore, this type of architecture tells us that this is a distributed architecture and that data
are processed on the edge of the network.
The third layer, global infrastructure, is usually a layer that relies on cloud infrastructure. This is because most
IoT solutions rely on the integration of cloud services. Observed from the business perspective, this is an
inevitable solution in recent times because the cloud provides a complete upgrade to the customer’s perspective.
The fourth layer, the data ingestion, the data entry layer. This is inevitably thought of Big Data, as well as the
cleansing and data store. Also, data streaming processes are present in this layer as a building element of data
ingestion.
Layer five belongs to the data analysis. This is of course related to the processing of data in order to prepare the
report, data mining, the implementation of machine learning, etc.
In the sixth layer, the so-called application layer, user applications is stored depends on the purpose and needs of
the user. Different context-elements are also thing-specific and it is therefore necessary to have a defined
application layer, otherwise they cannot be standardized within the IoT ecosystem. On the other hand, this means
that this layer is where the integration of users and objects from the lowest layer of architecture takes place. In
some studies on the IoT architecture, this layer is also called application integration layer where the same layer
can be viewed as a service layer with the implementation of the UI at the top.
The seventh layer is represented by people and processes. This includes all business entities as consortium of IoT
ecosystems and, at the same time, the actors involved in decision making on the basis of data obtained from the
IoT ecosystem, with the help of all the structures that were previously mentioned in architecture.
Real-World Design Constraints
Devices and Networks:
 The devices that form networks in the M2M Area Network domain must be selected, or designed, with certain
functionality suitable to IoT applications.
 The devices must have an energy source (e.g. batteries), computational capability (e.g. an MCU), appropriate
communications interface (e.g. a Radio Frequency Integrated Circuit (RFIC) and front end RF circuitry),
memory (program and data), and sensing (and/or actuation) capability.
 These must be integrated in such a way that the functional requirements of the desired application can be
satisfied with additional nonfunctional requirements
Functional Requirements:
1. Specific sensing and actuating capabilities
2. Sensing principle and data requirements: Sometimes continuous sampling of sensing data is required. For
some applications, sampling after specific intervals is required.
3. The parameters like higher network throughput, data loss, energy use, etc are decided based on sensing
principle.
Sensing and communications field:
 The sensing field is to be considered for sensing in local area or distributed sensing. The distance between
sensing points is also important factor to be considered.
 The physical environment has an implication on the communications technologies selected and the reliability
of the system in operation thereafter.
 Devices must be placed in close enough proximity to communicate. Where the distance is too great, routing
devices may be necessary.
Programming and embedded intelligence:
 Devices in the IoT are heterogeneous such as various computational architectures, including MCUs (8-, 16-,32bit, ARM, 8051, RISC, Intel, etc.), signal conditioning (e.g. ADC), and memory (ROM, S/F/D) RAM, etc.),
communications media, peripheral components (sensors, actuators, buttons, screens, LEDs), etc.
 In every case, an application programmer must consider the hardware selected or designed, and its capabilities.
 Application-level logic decides the sampling rate of the sensor, the local processing performed on sensor
readings, the transmission schedule (or reporting rate), and the management of the communications protocol
stack, among other things.
 The programmers have to reconfigure and reprogram devices in case of change in devices in IoT application.
Power:
 Power is essential for any embedded or IoT device.
 Depending on the application, power may be provided by the mains, batteries, or hybrid power sources.
 Power requirements of the application are modeled prior to deployment. This allows the designer to estimate
the cost of maintenance over time.
Gateway:
 Gateway devices or proxies are selected according to need of data transitions.
Nonfunctional requirements:
The non-functional requirements are technical and non-technical.
1. Regulations:
• For applications that require placing nodes in public places, prior permissions are important.
• Radio Frequency (RF) regulations limit the power with which transmitters can broadcast.
2. Ease of use, installation, maintenance, accessibility:
• This relates to positioning, placement, site surveying, programming, and physical accessibility of
devices for maintenance purposes.
3. Physical constraints:
• Integration of additional electronics into existing system
• Suitable packaging
• Kind and size of antenna
• Type of power supply
Financial cost:
Financial cost considerations are as follows:
• Component Selection: Typically, the use of these devices in the M2M Area Network domain is to
reduce the overall cost burden. However, there are research and development costs likely to be incurred for each
individual application in the IoT that requires device development or integration. Developing devices in small
quantities is expensive.
• Integrated Device Design: Once the energy, sensors, actuators, computation, memory, power,
connectivity, physical, and other functional and nonfunctional requirements are considered, it is likely that an
integrated device must be produced.
Data representation and visualization:
Each IoT application has an optimal visual representation of the data and the system. Data that is
generated from heterogeneous systems has heterogeneous visualization requirements. There are currently no
satisfactory standard data representation and storage methods that satisfy all of the potential IoT applications.
IoT on Industrial Automation
Internet of things is proving to be a game changer for many automation companies. Industrial automation
companies utilize IoT solutions can realize new advantages. The Internet of Things (IoT) assists to generate new
technologies to resolve problems, improve operations and enhance productivity. The IoT can be described as the
connection of only known electronic devices using Internet ‘data plumbing’ involving Internet Protocol (IP),
web services and cloud computing. Impact of IoT on Industrial Automation is very high and it empowers us to
utilize tablet computers, smart phones, realistic systems and cloud storage of data and so on.
Let us see the effect of Internet of Things (IoT) on Industrial Automation:
• Internet of Things (IoT)
• Internet of things products
• Internet of things devices
• IoT Gateway Devices
• Industrial IoT Development Kits
Internet of Things (IoT)
The Internet of Things (IoT) plays an important role in the industrial automation as it is begining to explore and
apply IoT concepts and technology. IoT helps to make system well organized and system architectures that are
essential, reasonable and flexible. The main aim is to generate cooperative communications and interaction from
manufacturing field input or output involving actuators, robotics, analyzers etc to improve flexibility and
enhanced manufacturing. Using IoT, the industrial automation has leveraged commercial technologies in
extensive applications and these examples involve PLCs replacing edges of relays.
Internet of things products
Internet of Things is the next large technology turn and it is simply internet connected devices that are able to
collect data. Many Internet of Things products are good enough smooth into the patterns of daily life by
clarifying routine tasks. IoT products are available in different ways and they can be utilized in various verticals.
Using IoT products, business and consumer lives can be more absolute than ever.
Internet of things devices
Internet of things devices can be utilized in different fields and they may deviate from home automation and
functionality of your house. IoT Devices such as smoke detectors, thermostats, smart music systems, smart light
bulbs come under this category. On another side, IoT devices are also present in the association with the human
body, where we can talk about fitness trackers, smart body scales etc.
IoT Gateway Devices
IoT Gateway devices behave as a connection bridge between IoT Sensor Network and Cloud Server. IoT
Gateway devices are appearing as essential elements in bringing next-generation devices to the IoT. They assist
to merge protocols for networking, helps to analyze storage and edge analytics on the data and make possible
data flow safely between edge devices and the cloud.
Industrial IoT Development Kits
Industrial IoT Development Kits produces a complete, high quality design environment for engineers and
solution architects to dramatically speed up the growth and delivery of IoT applications. Using these kits, any
development/industrial environment can be rapidly revolved into a production set unit.
The IoT Development Kit targets a variety of IoT application requirements by supplying a range of various
hardware platforms, spanning from very dense, low-power ARM-based designs to strong multi-core, new
generation gateways.
Machinery Automation
In easy terms Machinery automation has been into reality since more than 70 years. The concept is to analyze,
activate and control different machineries in various industries. It includes industries such as automobile, textile,
agriculture, chemical food and beverages, cement and other infrastructure evolution, manufacturing, shipping,
pharmaceutical, transportation and many more.
The concept is constantly fulfilling large number of real world use-cases, controlling various levels of challenges
and continuously benefiting this generation.
Fundamental building blocks of Machinery Automation with IoT are as follows:
– Wireless network with ideal connectivity
– Cloud storage
– Operation center
– Data processing
– Inventive hardware
– Improved sensors network
Success calculating criteria’s of machinery automation with IoT arrangement are as follows:
– Security
– Performance
– Efficiency
– Scalability and Customization
– Renewability
– Intelligence and Add-Value
– Predictive measurement and analysis
– Contribution towards Eco system
Advantages
– Real time data can save time and money!
– It’s Cloud! – Acquire anywhere, anytime and it’s safer!
– Develops standardization!
– Minimizes downtime
– Data integration is secure and visibility is higher
– Helps to realize your production processes better > supply better > increase performance > minimizes cost >
improve efficiency > scale higher!