INTERNET OF THINGS
Chapter 2
IoT Paradigms
IOT PARADIGM
The Internet of Things (IoT) paradigm refers to a set of fundamental principles, concepts, and assumptions that helps
to design, development, and implementation of IoT systems. It is a new approach to computing that emphasizes the
integration of physical devices, sensors, networks, and software applications to enable the collection, processing, and
analysis of data in real-time.
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KEY PRINCIPLES OF IOT PARADIGMS
The IoT paradigm is based on five key principles:
1. Interconnectivity
2. Data collection
3. Data analytics
4. Automation
5. Security
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1. INTERCONNECTIVITY
Interconnectivity refers to the ability of IoT devices to communicate and exchange data with other devices
over a network. This allows devices to work together to achieve a common goal or provide a more
comprehensive services.
Examples of interconnectivity in IoT systems −
Smart Home Systems − Devices such as smart thermostats, smart lights, and smart locks can communicate
with each other to create an integrated system that can be controlled by a single app or voice command.
Industrial IoT Systems − In manufacturing plants, sensors on machines can communicate with each other
and with central control systems to optimize production and reduce downtime.
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2. DATA COLLECTION
Data collection involves the use of sensors, cameras, and other devices to gather
information from the environment or other sources. This data can be used in taking
right decisions, improve processes, or provide new services.
Examples of data collection in IoT systems −
Environmental Monitoring − Sensors can be used to monitor air quality, water
quality, and other environmental factors in real-time.
Healthcare − Wearable devices can collect data on heart rate, blood pressure, and
other health indicators to monitor patients and improve treatment.
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3. DATA ANALYTICS
Data analytics involves processing and analyzing data in real-time. Machine
learning algorithms or other analytical tools can be used to derive insights and
make informed decisions.
Examples of data analytics in IoT systems −
Predictive Maintenance − In industrial IoT systems, data analytics can predict
when machines need maintenance, reducing downtime and improving efficiency.
Smart Agriculture − Sensors can collect data on soil moisture, temperature, and
other factors, which can then be analysed to optimise crop yields and reduce
water usage.
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4. AUTOMATION
Automation involves the use of IoT devices to perform automated actions based on the
data collected and analyzed. This can include turning off lights when a room is empty,
adjusting the temperature based on occupancy, or automatically ordering supplies
when inventory runs low.
Examples of automation in IoT systems −
Smart Lighting − Lighting systems can be automated to turn off when a room is empty
or adjust brightness based on the time of day.
Inventory Management − IoT devices can be used to monitor inventory levels and
automatically reorder supplies when they run low.
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5. SECURITY
Security in IoT systems involves protecting devices, networks, and data from
unauthorized access or malicious attacks. This includes implementing encryption,
firewalls, and other security measures to prevent data breaches or other cyber
threats.
Examples of security measures in IoT systems −
Authentication − Devices can be configured to require authentication before
allowing access to sensitive data or settings.
Encryption − Data can be encrypted to prevent unauthorized access, even if it is
intercepted during transmission.
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FUTURE OF IOT PARADIGM
As technology continues to evolve, the IoT paradigm is also expected
to advance and bring about new opportunities and challenges.
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EMERGING TRENDS IN IOT PARADIGMS
Edge Computing − Edge computing involves processing data closer to the source, rather than sending
it to a centralized location. This reduces latency and allows for faster decision-making in IoT systems.
AI and Machine Learning − Artificial intelligence and machine learning will continue to play a crucial
role in IoT systems, enabling devices to learn and adapt to new situations and improve decision-
making.
Blockchain − Blockchain technology can be used to enhance security and privacy in IoT systems,
allowing for secure and transparent data sharing between devices.
5G Networks − The rollout of 5G networks will significantly enhance the capabilities of IoT systems,
allowing for faster data transfer, lower latency, and increased device connectivity.
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EXPECTED IMPACT OF IOT PARADIGMS IN THE FUTURE
As with any technology, there are challenges and risks associated
with implementing IoT. Here are some of the major ones −
Data Security and Privacy − With the large amount of data being
collected and transmitted in real-time, it is crucial to ensure that the
data is secured and privacy is maintained. Hackers can potentially
exploit vulnerabilities in IoT systems, compromising the safety and
security of IoT devices.
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Standardization − There is a lack of standardization in the IoT industry, with various
manufacturers using different protocols and standards. This can create
interoperability issues and make it difficult to integrate different systems.
Integration with Legacy Systems − Many airlines and banks are still using legacy
systems that are not designed to work with IoT technology. Integrating new IoT
systems with these older systems can be a challenge and requires careful planning
and execution.
Regulatory Compliance − Some industries are heavily regulated, and new
technologies must meet stringent safety and security standards. It is important for IoT
solutions to comply with these regulations and obtain necessary certifications before
they can be implemented. Failure to do so can result in serious consequences,
including fines and legal action.
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IMPORTANCE OF IOT PARADIGM
Since its conception, the Internet of Things has
been effectively employed by a variety of
sectors to manage their operations and provide
services to their customers. IoT has found
applications in a wide range of activities,
leading to the development of different
paradigms based on the type of data sources,
devices, and peripherals, as well as the
applications they support.
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1. INTERNET OF BATTLEFIELD THINGS (IOBT):
This category is in charge of linking troops to the Internet of Things.
IoBT researchers want to create a suite for soldiers that includes
implanted biometric and location sensors. The data from these
sensors helps soldiers to maintain track of their troops and exchange
information on enemies, putting the entire squad on the same page.
Furthermore, sophisticated analysis based on machine learning
algorithms allows for the development of superior tactics in real-
time. However, there are certain drawbacks to IoBT, most notably
energy restrictions and data rates. Soldiers must send large amounts
of data quickly, necessitating the efficient use of bandwidth and
battery power.
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2. INTERNET OF DRONES (IOD):
It aims to improve the user experience while reducing user
interaction. The deployment and management of unmanned aerial
vehicles fall within the IoD category. IoD is used by service providers
for a variety of purposes, including package delivery, animal
surveillance, rescue operations, agriculture, photography, and more.
Developers must, however, cope with operating drones in regulated
and uncontrolled airspace, as well as dictating navigation
coordinates. Developers must integrate air traffic control networks,
cellphone networks, automation, and the Internet to ensure that IoD
runs well.
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3. INTERNET OF PEOPLE (IOP):
The Internet has a variety of profiles that represent people. Peer-to-
peer networks are connected through the Internet of Things (IoT). Social
graphs are widely used in social computing research for representation
and inference. Direct device-to-device, person-to-person, and company-
to-person interactions are all made possible by IoP compatible apps.
IoP also expands the potential for crypto-currency to be used as a way
of transferring incentives/payments in exchange for services. Such
frameworks make it easier for service providers and customers to
communicate. IoP also provides a platform for making safe and
transparent payments.
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4. INTERNET OF SERVICES (IOS):
This category is for manufacturers and service providers. Manufacturers
may now combine hardware and software under the IoS umbrella. For
example, a car manufacturer may construct a vehicle with sensors
already installed. To improve the user experience, software updates are
delivered through the Internet. Furthermore, this approach provides the
door for crypto-currency to be used as a payment mechanism. Factory
monitoring, sensing, and actuation are all examples of IoS applications,
as well as the generation of remote alarms in the event of an
emergency.
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5. INTERNET OF SPACE (IOSPACE):
For providing seamless connectivity services over uneven
demographic areas, this category of IoT relies on low earth orbit
(LEO) satellites. However, such satellites have drawbacks in terms
of development and deployment costs, as well as loss due to
orbital failure. These satellites have the potential to significantly
reduce network latency.
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PILLARS OF IOT PARADISGM
1. Device
An IoT device is a form of hardware that is capable of transmitting data from one location to
another through the internet. This data is usually recorded by a sensor located within the device. A
wireless solution is needed to support many devices that run on a single network. IoT devices can
include mobile devices, medical devices, cars and electronic appliances.
2. Data
The major function of IoT is to gather vast amounts of data in order to improve application
functionality and process information. Several forms of data can be collected. For example, music
streaming services gather data on the music and artists that each individual listens to; and exercise
applications regularly utilize location trackers to track users’ movements and physical activities
throughout the day. Organizations often integrate IoT with their HVAC (heating, ventilation and air
conditioning) and security, allowing enterprises to control these systems from one centralized
location or even remotely.
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3. Analytics
It is essential that the gathered data can be analyzed correctly and processed efficiently. This pillar is what makes IoT
applications so powerful and useful in the everyday life of individuals and organizations. Analytics is performed through the
application of data analysis tools and procedures to the generated data types. Once this data is processed and understood,
it then becomes valuable information. Analytics helps to optimize and enhance the benefits of IoT for the user.
4. Connectivity
Connectivity enables the three previously mentioned pillars to work in conjunction with each other. It is essential that connection
is maintained so that data can be transferred and analyzed correctly. High-bandwidth connectivity with little to no issues is a
requirement in order to maintain this real-time data flow. Without this regular flow of data from the device, no analysis of
data could take place. Without this information, the optimization of systems could not occur. Any data that was collected may
also be inaccurate due to the loss of potentially valuable data through poor connection.
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