The Internet of Things (IoT) is a network of physical objects—"things"—embedded with sensors, software, and other technologies to connect and exchange data with other devices and systems over the internet. These devices range in complexity from common household items to sophisticated industrial instruments. Experts predict that by 2025, there will be 22 billion connected IoT devices.
What is the significance of the Internet of Things (IoT)?
IoT has emerged as one of the most important technologies of the twenty-first century in recent years. Now that we can connect everyday objects to the internet via embedded devices, including as kitchen appliances, vehicles, thermostats, and baby monitors, seamless communication between people, processes, and things is conceivable.
Physical things can share and collect data with minimal human interaction thanks to low-cost computers, the cloud, big data, analytics, and mobile technologies. Digital systems can record, monitor, and alter each interaction between connected things in today's hyperconnected environment. The physical and digital worlds collide, but they work together.
What technologies have made IoT possible?
While the concept of the Internet of Things has been around for a long time, recent developments in a variety of technologies have made it a reality.
Low-cost, low-power sensor technology is available. IoT technology is becoming increasingly accessible to more manufacturers thanks to the availability of low-cost, high-reliability sensors.
Connectivity. A slew of internet network protocols have made it simple to link sensors to the cloud and other "things" for fast data transfer.
Platforms for cloud computing. Cloud platforms are becoming more widely available, allowing organisations and consumers to gain access to the infrastructure they need to grow up without having to handle it all themselves.
Analytics and machine learning. Businesses can acquire insights faster and more simply thanks to developments in machine learning and analytics, as well as access to diverse and large volumes of data stored in the cloud. The advent of these linked technologies continues to push the frontiers of IoT, and IoT data feeds these technologies as well.
Artificial intelligence that converses (AI). Natural-language processing (NLP) has been brought to IoT devices (such as digital personal assistants Alexa, Cortana, and Siri) thanks to advances in neural networks, making them more appealing, inexpensive, and feasible for home usage.
What is industrial IoT?
Industrial IoT (IIoT) refers to the use of IoT technology in industrial settings, particularly in terms of sensor and device instrumentation and control using cloud technologies. For a nice example of IIoT, look at this Titan use case PDF. Machine-to-machine communication (M2M) has recently been employed in industries to achieve wireless automation and control. However, with the rise of cloud and related technologies (such as analytics and machine learning), businesses can attain a new level of automation and, with it, new income and business models. The Internet of Things, often known as Industry 4.0, is the fourth phase of the industrial revolution. The IIoT is commonly used for the following purposes:
Preventive and predictive maintenance, as well as connected assets
Smart power grids
Smart digital supply chains
IoT unlocks business value
Companies are capitalising on the immense business value that IoT may offer as it gets more widely used in the marketplace. These advantages include:
Increasing the efficiency and productivity of company operations
Using data-driven insights from IoT data to improve business management
Developing new revenue streams and business models
Connecting the real and digital worlds in a simple and seamless manner to accelerate time to value
What are IoT applications?
Machine learning techniques are used in IoT applications to analyse enormous volumes of linked sensor data in the cloud. You may see important performance indicators, statistics for mean time between failures, and other data using real-time IoT dashboards and alerts. Machine learning algorithms can detect irregularities in equipment and deliver notifications to users, as well as trigger automated fixes or proactive countermeasures.
Business users may easily improve existing supply chains, customer service, human resources, and financial services operations using cloud-based IoT apps. There's no need to start from scratch with your business operations.