Overview of IoT Features

Internet of Things (IoT) is a technology of connected smart devices that has incremental use cases across industries. With the increasing use across various industries, it is becoming a necessity to define a common standard of IoT ecosystems. As a design standard, any IoT device comes with some common set of features like connectivity, analytics, endpoint management, etc. Let’s discuss the high-level feature maps of IoT devices.

Features of Internet of Things (IoT)

Any IoT device comes up with the following features:

All in One Data Science Bundle(360+ Courses, 50+ projects)

Price
View Courses

360+ Online Courses | 50+ projects | 1500+ Hours | Verifiable Certificates | Lifetime Access
4.7 (85,992 ratings)

1. Connectivity

In the case of IoT, the most important feature one can consider is connectivity. Without seamless communication among the interrelated components of the IoT ecosystems (i.e sensors, compute engines, data hubs, etc.) it is not possible to execute any proper business use case. IoT devices can be connected over Radio waves, Bluetooth, Wi-Fi, Li-Fi, etc. We can leverage various protocols of internet connectivity layers in order to maximize efficiency and establish generic connectivity across IoT ecosystems and Industry. There may be special cases where the IoT ecosystem is built on-premises or in an intranet.

2. Sensing

We humans can naturally understand and analyze our circumstances easily based on our past experiences with various things or situations. In the case of IoT in order to get the best of it, we need to read the analog signal, convert it in such a way that we can derive meaningful insights out of it. We use Electrochemical, gyroscope, pressure, light sensors, GPS, Electrochemical, pressure, RFID, etc. to gather data based on a particular problem. For example for automotive use cases, we use Light detection sensors along with pressure, velocity and imagery sensors. To make a use case successful we need to choose the proper sensing paradigm.

3. Active Engagements

IoT device connects various products, cross-platform technologies and services work together by establishing an active engagement between them. In general, we use cloud computing in blockchain to establish active engagements among IoT components. In the case of Industry grade, IoT solutions raw analog data need to be acquired, preprocessed and rescale as per business capacity. As per Google, only 50% of structured and 1% of unstructured data is used to make important business decisions. So while designing the IoT ecosystems carriers need to consider the future needs of manipulating such a huge scale of data to satisfy incremental business needs. One can confuse the need of active engagements with scale, practically it means your systems should be able to handle huge data across various technologies, platforms, products, and industries.

4. Scale

IoT devices should be designed in such a way that they can be scaled up or down easily on demand. In general, IoT is being used from smart home automation to automating large factories and work stations, so the use cases vary in scale. A carrier should design their IoT infrastructure depending upon their current and future engagement scale.

5. Dynamic Nature

For any IoT use case, the first and foremost step is to collecting and converting data in such a way that means business decisions can be made out of it. In this whole process, various components of IoT need to change their state dynamically. For example, the input of a temperature sensor will vary continuously based on weather conditions, locations, etc. IoT devices should be designed this keeping in mind.

6. Intelligence

In almost every IoT use cases in today’s world, the data is used to make important business insights and drive important business decisions. We develop machine learning/ deep learning models on top of this massive data to obtain valuable insights. The analog signals are preprocessed and converted to a format on which machine-learning models are trained. We need to keep in mind the proper data infrastructure based on business needs.

7. Energy

From end components to connectivity and analytics layers, the whole ecosystems demand a lot of energy. While designing an IoT ecosystem, we need to consider design methodology such that energy consumption is minimal.

8. Safety

One of the main features of the IoT ecosystem is security. In the whole flow of an IoT ecosystem, sensitive information is passed from endpoints to the analytics layer via connectivity components. While designing an IoT system we need to adhere to proper safety, security measures, and firewalls to keep the data away from misuse and manipulations. Compromising any component of an IoT ecosystem can eventually lead to failure of the whole pipeline.

9. Integration

IoT integrates various cross-domain models to enrich user experience. It also ensures proper trade-off between infrastructure and operational costs.

Conclusions

The expansion and design of optimal IoT systems are still an active area of research, so in practice, not all IoT products come up with these all set of features of the standard. It mainly depends on the use cases and industry where the ecosystem needs to be incorporated. Internet of Things (IoT) is a technology of connected smart devices that has incremental use cases across industries. With the increasing use across various industries, it is becoming a necessity to define a common standard of IoT ecosystems. As a design standard, any IoT device comes with some common set of features like connectivity, analytics, endpoint management, etc. Let’s discuss the high-level feature maps of IoT devices.

Quiz Result
Total Questions	Correct Answers	Wrong Answers	Percentage