Internet of things , future technology

1. IoT
IoT product development life cycle

2. The IoT Product life cycle
• There are four stages to the IoT product life
cycle. These are
• Design,
• Deployment,
• ongoing Management, and
• Decommissioning.

4. Design
• Design is the first stage of the life cycle but likely the most
important one.
• In this stage, the developers have to consider requirements from
the next three stages of the product life cycle to ensure that the
product can easily support each stage.
• In many cases, the product is not brand new, and instead is an
enhancement to a previous generation product.
• Therefore, developers have to consider how to best bridge new
functionalities and the existing code base without compromising
performance and security.
• Developers have to also carefully weigh “make versus buy”
considerations.
• While many OEMs are starting to lean towards the “buy” scenario
to speed up time to market, this path isn’t without its own set of
challenges.
• In a noisy IoT marketplace filled with many options for both
hardware and software solutions, OEMs must be discerning when it
comes to selecting the right partners.

5. Deployment
• Deployment is the second stage of the product life cycle, and itself
can come in a few phases such as
• proof-of-concepts, pilots, and commercial roll out.
• Deployments of IoT solutions are much more complex than
traditional products, as there are many more stakeholders involved.
• For example, a deployment at an electric utility may involve the
OEM, the utility provider, a systems integrator, an independent
software vendor (ISV), and the public utility commission.
• They may all have the need to have access to the product at the
various phases of deployment; as such,
• the right level of user authorization needs to be provided.
• Initial provisioning and configuration of the platform in the field
needs to be quick and seamless.
• Modelling the deployment and activation after smartphones and
other consumer products can ensure ease of use and deployment
at scale.

6. Ongoing Management
• Ongoing Management is the third stage of the
product life cycle, and likely the longest one.
• During this stage, multiple stakeholders may need
to access the device to be able to monitor its
status, provide maintenance, provide updates,
and optimize its performance – all without
sending someone on site.
• In fact, for many industrial customers, one of the
most critical drivers of the value in IoT is the
ability to use a device’s data to make decisions
regarding its performance.

7. Decommissioning
• Finally, the last stage of the product life cycle is Decommissioning.
• This stage is typically overlooked in many product designs.
• OEMs need to carefully consider and plan for the product’s end-of-
life at the design stage.
• End users and other stakeholders have to be able to quickly and
securely remove a device from service and onboard a new one.
• While it may seem counterintuitive for an OEM to develop a design
for making it easier for an end user to decommission their product
and move into a newer model, this has been done very intelligently
by companies like Samsung and Apple.
• By making it easier for their customers to transition from one
product model to another, they have created another reason for
their customers to continue to invest in their products time and
time again.

8. IoT(internet of things) enabling
technologies
• IoT(internet of things) enabling technologies
are
• Wireless Sensor Network
• Cloud Computing
• Big Data Analytics
• Communications Protocols
• Embedded System

10. 1. Wireless Sensor Network(WSN) :
A WSN comprises distributed devices with sensors
which are used to monitor the environmental and
physical conditions. A wireless sensor network consists
of end nodes, routers and coordinators. End nodes
have several sensors attached to them where the data
is passed to a coordinator with the help of routers. The
coordinator also acts as the gateway that connects
WSN to the internet.
Example –
• Weather monitoring system
• Indoor air quality monitoring system
• Soil moisture monitoring system
• Surveillance system
• Health monitoring system

12. 2. Cloud Computing :
It provides us the means by which we can access
applications as utilities over the internet. Cloud means
something which is present in remote locations.
With Cloud computing, users can access any resources
from anywhere like databases, webservers, storage,
any device, and any software over the internet.
Characteristics –
• Broad network access
• On demand self-services
• Rapid scalability
• Measured service
• Pay-per-use

13. • Provides different services, such as –
• IaaS (Infrastructure as a service)
Infrastructure as a service provides online services such as physical
machines, virtual machines, servers, networking, storage and data center
space on a pay per use basis. Major IaaS providers are Google Compute
Engine, Amazon Web Services and Microsoft Azure etc.
Ex : Web Hosting, Virtual Machine etc.
• PaaS (Platform as a service)
Provides a cloud-based environment with a very thing required to support
the complete life cycle of building and delivering West web based (cloud)
applications – without the cost and complexity of buying and managing
underlying hardware, software provisioning and hosting. Computing
platforms such as hardware, operating systems and libraries etc. Basically,
it provides a platform to develop applications.
Ex : App Cloud, Google app engine
• SaaS (Software as a service)
It is a way of delivering applications over the internet as a service. Instead
of installing and maintaining software, you simply access it via the
internet, freeing yourself from complex software and hardware
management.
SaaS Applications are sometimes called web-based software on demand
software or hosted software.
SaaS applications run on a SaaS provider’s service and they manage
security availability and performance.
Ex : Google Docs, Gmail, office etc.

15. • Cloud computing supports four basic
deployment models. These models differ in
the way how the cloud is built and who are
using the resources in the cloud. The four
cloud deployment models are:
• Public cloud
• Private cloud
• Community cloud
• Hybrid cloud

17. • In a public cloud the resources are shared
between several users.
• Public cloud is generally maintained by the cloud
service provider.
• The management of the resources is taken care
by the cloud service provider.
• In a private cloud all the resources are used by a
single organization.
• Such organization has the complete control on
the cloud and can follow all the necessary
regulations.
• Private cloud offers greater flexibility when
compared to the public cloud.

18. • A community cloud is one whose resources
are shared by two or more companies having
shared goals.
• Such clouds are generally used for conducting
collaborated research.
• A combination of the previous three clouds is
a hybrid cloud.
• Big companies generally use hybrid cloud. The
companies generally store the sensitive data
in the private cloud and other non-sensitive
data in the public cloud.

19. 3. Big Data Analytics :
It refers to the method of studying massive volumes of data or big data.
• Collection of data whose volume, velocity or variety is simply too massive
and tough to store, control, process and examine the data using traditional
databases.
• Big data is gathered from a variety of sources including social network
videos, digital images, sensors and sales transaction records.
• Several steps involved in analyzing big data –
• Data cleaning (Data cleaning is the process of fixing or removing incorrect,
corrupted, incorrectly formatted, duplicate, or incomplete data within a
dataset)
• Munging (Data munging is the initial process of refining raw data into
content or formats better-suited for consumption by downstream systems
and users)
• Processing
• Visualization
Examples –
• Bank transactions
• Data generated by IoT systems for location and tracking of vehicles
• E-commerce and in Big-Basket
• Health and fitness data generated by IoT system such as a fitness bands

20. • The data analytics framework consists of six
steps namely: collection, cleaning, integration,
analysis, visualization and alerting.

21. 4. Communications Protocols :
They are the backbone of IoT systems and enable
network connectivity and linking to applications.
Communication protocols allow devices to
exchange data over the network.
• Multiple protocols often describe different
aspects of a single communication. A group of
protocols designed to work together is known as
a protocol suite; when implemented in software
they are a protocol stack.
They are used in
• Data encoding
• Addressing schemes

22. 5. Embedded Systems :
It is a combination of hardware and software used to
perform special tasks.
It includes microcontroller and microprocessor
memory, networking units (Ethernet Wi-Fi adapters),
input output units (display keyword etc. ) and storage
devices (flash memory).
It collects the data and sends it to the internet.
Embedded systems used in
Examples –
• Digital camera
• DVD player, music player
• Industrial robots
• Wireless Routers etc.

23. Internet of Things - Technology and Protocols
• IoT primarily exploits standard protocols and
networking technologies.
• However, the major enabling technologies and
protocols of IoT are RFID, NFC, low-energy
Bluetooth, low-energy wireless, low-energy
radio protocols, LTE-A, and WiFi-Direct.
• These technologies support the specific
networking functionality needed in an IoT
system in contrast to a standard uniform
network of common systems.

24. NFC and RFID
• RFID (radio-frequency identification) and NFC
(near-field communication) provide simple,
lowenergy, and versatile options for identity and
access tokens, connection bootstrapping, and
payments.
• RFID technology employs 2-way radio
transmitter-receivers to identify and track tags
associated with objects.
• NFC consists of communication protocols for
electronic devices, typically a mobile device and a
standard device.

25. • Low-Energy Bluetooth (BLE)
• This technology supports the low-power, long-use
need of IoT function while exploiting a standard
technology with native support across systems.
• Low-Energy Wireless (LoRaWAN)
• This technology replaces the most power hungry
aspect of an IoT system. Though sensors and
other elements can power down over long
periods, communication links (i.e., wireless) must
remain in listening mode. Low-energy wireless
not only reduces consumption, but also extends
the life of the device through less use.

26. • Radio Protocols
• ZigBee, Z-Wave, and Thread are radio protocols for creating low-
rate private area networks. These technologies are low-power,
but offer high throughput unlike many similar options. This
increases the power of small local device networks without the
typical costs.
• LTE-A
• LTE-A, or LTE Advanced, delivers an important upgrade to LTE
technology by increasing not only its coverage, but also reducing
its latency and raising its throughput. It gives IoT a tremendous
power through expanding its range, with its most significant
applications being vehicle, UAV, and similar communication.
• WiFi-Direct
• WiFi-Direct eliminates the need for an access point. It allows P2P
(peer-to-peer) connections with the speed of WiFi, but with
lower latency.
• WiFi-Direct eliminates an element of a network that often bogs
it down, and it does not compromise on speed or throughput.