IOT Enabling Technologies :

IOT Enabling Technologies :

IOT enabled by several technologies including wireless sensor networks,cloud
computing ,Big Data analytics,embedded systems,security protocols and
architectures, communication protocols,web services,mobile internet,and
semantic search engines.

 Wireless Sensor Networks

A wireless sensor network (WSN)comprises of distributed devices with sensors which
are used tomonitor the environmental and physical conditions. A WSN
consists of a number of end-nodes and routers and a coordinator. End nodes
have several sensors attached to them.End nodes can also act as routers.
Routers are responsible for routing the data packets from end nodes to the
coordinator. The coordinator collects the data from all the
nodes.Coordinatoralso acts as gateway that connects the WSN to the internet.
EX: 1. Weather monitoring system use WSNs in which the nodes collect temperature,
humidity and other data, which is aggregated and analysed.
2. Indoor air quality monitoring systems use WSNs to collect data on the indoor
air quality and concentration of various gases.
3. Smart grids use WSNs for monitoring the grid at various points.
WSNs are enabled by wireless communication protocols such as IEEE 802.15.4. ZigBee
is one of the most popular wireless technologies used by WSNs. ZigBee
specifications are based on IEEE 802.15.4. ZigBee operates at 2.4GHz frequency and
offers data rates upto250 KB/s and range from 10 to 100 meters depending on the
power output and environmental conditions. The power of WSNs lies in their ability
to deploy large number of loe-cost and low-power sensing nodes for continuous
monitoring of environmental and physical conditions. WSNs are self-organizing
networks. Since WSNs have large number of nodes, manual configuration for each
node is not possible. The self-organizing capability of WSN makes the network
robust. In the event of failure of some nodes or addition of new nodes to the network,
the network can reconfigure itself.

Cloud Computing

Cloud Computig isa transformative computing paradigm that involves delivering
applications and services over the internet. Cloud computing involves provisioning of

computing, networking and storage resources on demand and providing these
resources as metered services to the users, in a “pay as you go” model.Cloud
computing services are offered to users in different forms:
(i).Infrastructure-as-a-services(IaaS):IaaS provides the users the ability to
provisioncomputing and storage resources. These resources are provided to the
users as virtual machine instance and virtual storage. Users can start ,stop,
configure and manage the virtual machine instances and virtual storage. Users
can deploy operating systems and appilicationsof their choice on the virtual
resources provisioned in the cloud. The cloud services provider manages the
underlying infrastructure. Virtual resources provisioned by the users are
billedbased on a pay-per-use paradigm.
(ii). Platform-as-a-Service(PaaS):
Paas provides the users the ability to develop and deploy applications in the cloud
using the Development tools, applications programming interfaces, software
libraries and services provided by the cloud service provider. The cloud
service provider manages the underlyingcloud infrastructure including
services, network, operating systems and storage. The users ,themselves,are
responsible for developing, deploying, configuring and managing applications
on the cloud infrastructure.
(iii).Software-as-a-Service(SaaS):
SaaS provides the users a complete software applications or the interface to the
applications itself. The cloud service provider manages the underlying cloud
infrastructure including servers, network, operating systems,storage and
applications software, and the user is unaware of the underlying architecture of
the cloud, Applications are provided to the user through a thin client interface.
SaaS applications are platform independent and can be accessed from various
client devices such as workstations, laptop, tablets and smart-phones running
different operating systems. Since the cloud services provider manages both
the applications and data, the users are able to access the applications from
anywhere.

 Big Data Analytics:

Big data is defined as collections of data sets whose volume, velocity or varity, is so
large that it is difficult to store, manage, process and analyse the data using
traditional database and data processing tools. Big data analytics involves
several steps starting From data cleansing,datamunging, data processing and
visualization.
EX: 1. Sensor data generated by IoT systems such as weather monitoring stations.

2. Data generated by IoT system for location and tracking of vehicles.
3. Data generated by retail inventory monitoring systems.

Characteristics:

1.volume: Through there is no fixed threshold for the volume of data to be
considered as big data, however , typically the term big data is used for
massive scale data that is difficult to store, manage and process using
traditional databases and data processing architectures. The volume of data
generated by modern IT, industrial, and health-care systems for example is
growing exponentially driven by the lowering costs of data storage and
processing architectures and the need to extract valuable insights from the data
to improve business processes, efficiency and service to consumers.
2.Velocity: Velocity is another important characteristic of big data and the primary
reason for exponential growth of data. Velocity of data refers to how fast the
data is generated and how frequency it varies. Modern IT , industrial and other
systems are generating data at increasingly higher speeds.
3.Variety:Varity refers to the forms of the data. Big data comes in different forms
such as structured or unstructured data, including text data, image, audio,
video and sensor data.

 Communication protocols:

Communication protocols form the backbone of IoT system and enable network
connectivity and coupling to applications. Communication protocols allow
device to exchange data over the network. In section 1.2.2 you learned about
various link, network, transport, and application layer protocols. These
protocols define the data exchange formats, data encoding, addressing
schemas for device and routing of packets from source to destination other
functions of the protocols include sequence control , flow control and
retransmission of lost packets.

 Embedded Systems :

An embedded system is a computer system that has computer hardware and software
embedded to perform specific tasks. In contrast to general purpose computers
or personal computers which can perform various types of tasks, embedded
systems are designed to perform a specific set of tasks . Key components of an
embedded system include microprocessor or microcontroller,memory,
networking units, input/output units and storage.
Some embedded system have specialized processors such as digital signal processors,

graphics processors and application specific processors. Embedded system run
embedded operating systems such as real-time operating system. Embedded system
range from low-cost miniaturized devices such ad digital watches to devices such as
digital cameras, point of scale terminals, vending machines, appliances, etc.