challenges in IOT

1. Vishal Choudhary
vishalhim@yahoo.com
Challenges in IoT

2. Internet of Things (IoT) designs mesh together several
design domains in order to successfully develop a
product. Individually, these design domains are
challenging. Bringing them all together to create an IoT
product can place extreme pressure on design teams.
IOT Technologies are facing many challenges , including interoperability and
scalability, as billions of heterogeneous devices will be connected, deciding on
how to invest in the IoT is a challenge for business, and there are also major
social, legal and ethical challenges, including security and privacy of data
collection, which must be resolved

3. Scalability
Billions of internet-enabled devices get connected in a huge network, large
volumes of data are needed to be processed. The system that stores, analyses
the data from these IoT devices needs to be scalable. In present, the era of
IoT evolution everyday objects are connected with each other via Internet.
The raw data obtained from these devices need big data analytics and cloud
storage for interpretation of useful data.

4. Interoperability
Technological standards in most areas are still fragmented. These
technologies need to be converged. Which would help us in establishing a
common framework and the standard for the IoT devices. As the
standardization process is still lacking, interoperability of IoT with legacy
devices should be considered critical. This lack of interoperability is
preventing us to move towards the vision of truly connected everyday
interoperable smart objects.

5. Security And Privacy:
 There has been no research in security
vulnerabilities and its improvements. It should
ensure Confidentiality, Integrity and Availability of
personal data.

6. Design Based Challenge
With the development in technology design challenges are increasing at
a faster rate. There have been issues regarding design like limited
computation power, limited energy and limited memory which need to
be sorted out.

7. Standards
 Lack of standards and documented best practices have a greater impact than just
legislating the potential of IoT devices. Without standards to guide
manufacturers, developers sometimes design products that operate in distracting
ways on the Internet without much regard to their impact. If poorly designed
and configured, such devices can have incorrect consequences for the
networking resources they connect to and the broader Internet.
 A lot of this comes down to cost constraints and the need to develop a product
to release quicker than competitors. Add to this the toughness with managing
and configuring larger numbers of IoT devices, the need for thoughtful design
and standardization of configuration tools, methods, and interfaces, coupled
with the adoption of IPv6, will be essential in the future.

8. Regulation
there is an enormous range of regulatory and legal questions surrounding the
IoT, which need thoughtful consideration. Legal issues with IoT devices
include cross border data flow; a conflict between law enforcement
surveillance and civil rights; data retention and destruction policies; and
legal liability for unintended uses, security breaches or privacy lapses.
Further, technology is awaiting much more rapidly than the associated
policy and regulatory environments.

9. Compatibility
When IoT devices that have to talk to each other
are running different software versions, all kinds of
performance issues and security vulnerabilities can
result. That’s a big part of why it’s so important that
IoT consumers keep their devices patched and up to
date.

10. Technological Challenges
 This part is covering all technologies needed to make IoT systems
function smoothly as a standalone solution or part of existing systems
and that’s not an easy mission, there are many technological challenges,
including Security, Connectivity, Compatibility & Longevity, Standards
and Intelligent Analysis & Actions

11. Security
IoT has already turned into a serious security concern that has drawn the
attention of prominent tech firms and government agencies across the
world. The hacking of baby monitors, smart fridges, thermostats, drug
infusion pumps, cameras and even the radio in your car are signifying a
security nightmare being caused by the future of IoT. So many new nodes
being added to networks and the internet will provide malicious actors with
innumerable attack vectors and possibilities to carry out their evil deeds,
especially since a considerable number of them suffer from security holes.

12.  Insufficient testing and updating
Main problems with tech companies building these devices is that they are too careless
when it comes to handling of device-related security risks.
Most of these devices and IoT products don’t get enough updates while, some don’t
get updates at all.
This means that a device that was once thought of as secure when the customers
first bought it becomes insecure and eventually prone to hackers and other security
issues.
 Brute-forcing and the issue of default passwords
IoT devices that come with default (read, hackable) credentials such as using
“admin” as username and/or passwords. Weak credentials and login details
leave nearly all IoT devices vulnerable to password hacking and brute-forcing
in particular. any company that used factory default credentials on their
devices is placing both their business and its assets and the customers and
their valuable information at risk of being susceptible to a brute-force attack

13.  Data security and privacy concerns (mobile, web,
cloud)
Data is constantly being harnessed, transmitted, stored and processed
by large companies using a wide array of IoT devices, such as smart TVs,
speakers and lighting systems, all this user-data is shared between or
even sold to various companies, violating our rights for privacy and Data
security and further driving public distrust.

14. Connectivity
 Connecting so many devices will be one of the biggest challenges of the
future of IoT, and it will defy the very structure of current communication
models and the underlying technologies . At present we rely on the
centralized, server/client paradigm to authenticate, authorize and connect
different nodes in a network.This model is sufficient for current IoT
ecosystems, where tens, hundreds or even thousands of devices are
involved. But when networks grow to join billions and hundreds of billions
of devices, centralized systems will turn into a bottleneck. Such systems
will require huge investments and spending in maintaining cloud servers
that can handle such large amounts of information exchange, and entire
systems can go down if the server becomes unavailable.

15. The future of IoT will very much have to depend on decentralizing IoT
networks. Part of it can become possible by moving some of the tasks to the
edge, such as using fog computing models where smart devices such as IoT
hubs take charge of mission-critical operations and cloud servers take on
data gathering and analytical responsibilities.

16. Bandwidth
Connectivity is a bigger challenge to the IoT than
you might expect. As the size of the IoT market grows
exponentially, some experts are concerned that
bandwidth-intensive IoT applications such as video
streaming will soon struggle for space on the IoT’s
current server-client model.

17. Compatibility and Longevity
 IoT is growing in many different directions, with
many different technologies competing to become
the standard. This will cause difficulties and require
the deployment of extra hardware and software
when connecting devices.
 Other compatibility issues stem from non-unified
cloud services, lack of standardized M2M protocols
and diversities in firmware and operating systems
among IoT devices.

18. Some of these technologies will eventually become obsolete in the next few
years, effectively rendering the devices implementing them useless. This is
especially important, since in contrast to generic computing devices which
have a lifespan of a few years, IoT appliances (such as smart fridges or
TVs) tend to remain in service for much longer, and should be able to
function even if their manufacturer goes out of service.

19. Standards
 Standard for handling unstructured data: Structured data are stored in
relational databases and queried through SQL for example. Unstructured
data are stored in different types of NoSQL databases without a standard
querying approach.
 Technical skills to leverage newer aggregation tools: Companies that are
keen on leveraging big-data tools often face a shortage of talent to plan,
execute, and maintain systems.

20. Intelligent Analysis & Actions
 Inaccurate analysis due to flaws in the data and/or model: A lack of data or presence of
outliers may lead to false positives or false negatives, thus exposing various algorithmic
limitations
 Legacy systems’ ability to analyze unstructured data: Legacy systems are well suited to
handle structured data; unfortunately, most IoT/business interactions generate
unstructured data
 Legacy systems’ ability to manage real- time data: Traditional analytics software
generally works on batch-oriented processing, wherein all the data are loaded in a batch
and then analyzed