What is Internet of Things?

The internet of things (IoT) is a catch-all term for the growing number of electronics that aren't traditional computing devices, but are connected to the internet to send data, receive instructions or both. There's an incredibly broad range of things that fall under that umbrella: Internet-connected "smart" versions of traditional appliances like refrigerators, fan and light bulbs; gadgets that could only exist in an internet-enabled world like Alexa-style digital assistants; internet-enabled sensors that are transforming factories, healthcare, transportation, distribution centers and farms. The IoT brings the power of the internet, data processing and analytics to the real world of physical objects. For consumers, this means interacting with the global information network without the intermediary of a keyboard and screen; many of their everyday objects and appliances can take instructions from that network with minimal human intervention.

How Does the Internet of Things Work?

The Internet of Things requires three elements:

1] A way for devices to connect to other devices

2] A way for devices to gather data from other devices

3] A method for devices to process that data and make decisions

Individual devices with integrated sensors can connect and deliver information about their status to one another, creating a network of integrated things. While these IoT devices usually take some human setting up, once they're up and running, the process of collecting and sending data is autonomous and has a vast range of uses. IoT devices can piggyback on our existing internet connections using Wi-Fi (though there are plenty of wired IoT devices!), or they can use Bluetooth for closer-range direct connectivity without a middleman. Other options exist too, such as smart home protocols like ZigBee and Z-Wave.

But even after connecting, devices can only communicate with each other if they can "speak the same language" (i.e., they need to be able to decode the data sent to them). With so many potential "languages," it's impossible for one device to support them all. That's why many IoT platforms rely on an "interpreter" device, typically known as a smart home hub (if you're using it at home, of course).

For example, SmartThings products communicate with each other by passing data through a SmartThings Hub. This means each device only needs to know the Hub's language, while the Hub knows how to speak to each device. This relay allows the devices to indirectly communicate with ease. Now that the IoT and other smart devices are commonplace, more industry-wide IoT protocol standardization has taken place. As a result, you'll often find smart home hubs support Wi-Fi, Bluetooth, Z-Wave, Matter, and ZigBee (or a combination of) out of the box, making sure you can connect all of your IoT and smart devices with ease.

What Is an IoT Platform?

An IoT platform is a set of tools that allows various devices to connect and communicate. We already talked about IoT and smart home hubs above, but they're only one part. An IoT platform is more like the overall building blocks of the process, and the hub is just one building block.

So, when someone talks about an IoT platform, they're typically talking about the hub (also called a gateway device), plus the communication protocol used by the platform (such as Wi-Fi, ZigBee, or Z-Wave), plus the underlying software that processes and transmits the network data. It also includes user-facing applications that allow humans to interact with the devices on the platform. But, although that sounds like a lot of different things you have to learn to begin using IoT devices, you won't always have to dig into every aspect of the IoT platform.

For example, SmartThings has its Hub as the gateway device. It also supports any device that can "speak" Wi-Fi, ZigBee, Z-Wave, or Matter. These devices communicate through the Hub (e.g., a motion sensor detects movement and notifies the Hub, which turns on connected lightbulbs).

Advantages & Drawback of IoT

The IoT ensures that communication between Internet-enabled devices works. Data is constantly being captured, collected, sent, and analyzed in order to further optimize communication and connectivity. This presents tremendous opportunities in professional and private environments, but also risks.

Advantages:-

Drawbacks:-

What Security Aspects Must Be Taken into Account for IoT Solutions?

Billions of devices exchange immense amounts of data via the Internet of Things. This information, the respective applications and processes, and the IoT systems themselves must be protected against unauthorized access and manipulation. This requires, for example, effective identity and access management. In addition, all data transmitted over the public Internet should be encrypted, and all relevant systems should be effectively hardened and secured by protective measures such as firewalls. Also important is continuous software and patch management throughout the entire system operating period to close potential security gaps.

What are the benefits of IoT?

The potential uses of the IoT are virtually limitless, and it is already being used in a wide range of applications. Some of the key industries that are adopting the IoT include:

Healthcare: The IoT is being used to monitor the health of patients remotely and to improve the efficiency of healthcare delivery.

Transportation: The IoT is being used to optimize the delivery of goods and to improve the safety and efficiency of transportation systems.

Manufacturing: The IoT is being used to improve the efficiency of manufacturing processes and to reduce waste and defects.

Agriculture: The IoT is being used to optimize crop yields and to improve the efficiency of farming operations.

In addition to collecting and analyzing data, the IoT also enables the automation of processes and tasks. For example, a smart thermostat can be programmed to adjust the temperature of a home based on the time of day and the occupants’ schedules, while a smart irrigation system can be set to water a lawn only when necessary, based on weather data.

The concept of the IoT has been around for decades, but it has only recently become a reality due to advances in technology such as the widespread adoption of the Internet, the proliferation of mobile devices, and the development of low-cost sensors and other hardware.

There are many different types of devices that can be connected to the IoT, including smartphones, tablets, laptops, wearable devices, home appliances, and industrial machinery. These devices can be connected to the Internet using a variety of technologies, including Wi-Fi, cellular networks, and Bluetooth.

The IoT is expected to continue to grow and evolve in the coming years, as more and more devices become connected to the Internet and the capabilities of these devices continue to improve. It is likely that the IoT will become an integral part of our daily lives, making many tasks and processes more convenient, efficient, and secure.

How can India utilize IoT?

IoT is also expected to play a key role in improving energy efficiency and sustainability in Indian smart cities. Smart energy management systems can use IoT sensors to monitor and optimize the use of energy in buildings and other infrastructure, helping to reduce energy consumption and greenhouse gas emissions. In addition, IoT can be used to improve the delivery of essential services such as water, waste management, and healthcare. Smart water systems can use IoT sensors to monitor water levels, quality, and leaks in real-time, helping to ensure an adequate and reliable supply of clean water. Smart waste management systems can use IoT sensors to optimize the collection and processing of waste, reducing pollution and improving public health. And smart healthcare systems can use IoT sensors to monitor the health of patients remotely, allowing for more timely and effective treatment.

IoT standards and frameworks

There are several emerging IoT standards, including the following:

IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN) is an open standard defined by the Internet Engineering Task Force (IETF). The 6LoWPAN standard enables any low-power radio to communicate to the internet, including 804.15.4, Bluetooth Low Energy (BLE) and Z-Wave (for home automation).

ZigBee is a low-power, low-data rate wireless network used mainly in industrial settings. ZigBee is based on the Institute of Electrical and Electronics Engineers (IEEE) 802.15.4 standard. The ZigBee Alliance created Dotdot, the universal language for IoT that enables smart objects to work securely on any network and understand each other.

LiteOS is a Unix-like operating system (OS) for wireless sensor networks. LiteOS supports smartphones, wearables, intelligent manufacturing applications, smart homes and the internet of vehicles (IoV). The OS also serves as a smart device development platform.

OneM2M is a machine-to-machine service layer that can be embedded in software and hardware to connect devices. The global standardization body, OneM2M, was created to develop reusable standards to enable IoT applications across different verticals to communicate.

Data Distribution Service (DDS) was developed by the Object Management Group (OMG) and is an IoT standard for real-time, scalable and high-performance M2M communication.

Advanced Message Queuing Protocol (AMQP) is an open-source published standard for asynchronous messaging by wire. AMQP enables encrypted and interoperable messaging between organizations and applications. The protocol is used in client-server messaging and in IoT device management.

Constrained Application Protocol (CoAP) is a protocol designed by the IETF that specifies how low-power, compute-constrained devices can operate in the Internet of Things.

Long Range Wide Area Network (LoRaWAN) is a protocol for WANs designed to support huge networks, such as smart cities, with millions of low-power devices.

IoT frameworks include the following:

Amazon Web Services (AWS) IoT is a cloud computing platform for IoT released by Amazon. This framework is designed to enable smart devices to easily connect and securely interact with the AWS cloud and other connected devices.

Arm Mbed IoT is a platform to develop apps for IoT based on Arm microcontrollers. The goal of the Arm Mbed IoT platform is to provide a scalable, connected and secure environment for IoT devices by integrating Mbed tools and services.

Microsoft's Azure IoT Suite is a platform that consists of a set of services that enables users to interact with and receive data from their IoT devices, as well as perform various operations over data, such as multidimensional analysis, transformation and aggregation, and visualize those operations in a way that's suitable for business.

Google's Brillo/Weave is a platform for the rapid implementation of IoT applications. The platform consists of two main backbones: Brillo, an Android-based OS for the development of embedded low-power devices, and Weave, an IoT-oriented communication protocol that serves as the communication language between the device and the cloud.

Calvin is an open source IoT platform released by Ericsson designed for building and managing distributed applications that enable devices to talk to each other. Calvin includes a development framework for application developers, as well as a runtime environment for handling the running application.

What IoT data protocols are available?

Wi-Fi is rapidly becoming the personal-area network strategy of choice for devices like thermostats and doorbells. There's increased interest in Bluetooth as a location-oriented IoT model for tasks including asset tracking, warehouse goods movement and in-building navigation. Zigbee is defined by IEEE 802.15.4 and controlled by the Zigbee alliance. Zigbee is the legacy protocol and architectural model most likely to fit an IoT deployment. JupiterMesh, another Zigbee Alliance protocol, is designed for mesh applications in industrial networks.

How Artificial Intelligence Works?

It's even more amazing, perhaps, that our existence is quietly being transformed by a technology that many of us barely understand, if at all — something so complex that even scientists have a tricky time explaining it.

"AI is a family of technologies that perform tasks that are thought to require intelligence if performed by humans," explains Vasant Honavar, a professor and director of the Artificial Intelligence Research Laboratory at Penn State University. "I say 'thought,' because nobody is really quite sure what intelligence is."

Honavar describes two main categories of intelligence. There's narrow intelligence, which is achieving competence in a narrowly defined domain, such as analyzing images from X-rays and MRI scans in radiology. General intelligence, in contrast, is a more human-like ability to learn about anything and to talk about it. "A machine might be good at some diagnoses in radiology, but if you ask it about baseball, it would be clueless," Honavar explains. Humans' intellectual versatility "is still beyond the reach of AI at this point."

According to Honavar, there are two key pieces to AI. One of them is the engineering part — that is, building tools that utilize intelligence in some way. The other is the science of intelligence, or rather, how to enable a machine to come up with a result comparable to what a human brain would come up with, even if the machine achieves it through a very different process. To use an analogy, "birds fly and airplanes fly, but they fly in completely different ways," Honavar. "Even so, they both make use of aerodynamics and physics. In the same way, artificial intelligence is based upon the notion that there are general principles about how intelligent systems behave."

AI is "basically the results of our attempting to understand and emulate the way that the brain works and the application of this to giving brain-like functions to otherwise autonomous systems (e.g., drones, robots and agents)," Kurt Cagle, a writer, data scientist and futurist who's the founder of consulting firm Semantical, writes in an email. He's also editor of The Cagle Report, a daily information technology newsletter.

And while humans don't really think like computers, which utilize circuits, semi-conductors and magnetic media instead of biological cells to store information, there are some intriguing parallels. "One thing we're beginning to discover is that graph networks are really interesting when you start talking about billions of nodes, and the brain is essentially a graph network, albeit one where you can control the strengths of processes by varying the resistance of neurons before a capacitive spark fires," Cagle explains. "A single neuron by itself gives you a very limited amount of information, but fire enough neurons of varying strengths together, and you end up with a pattern that gets fired only in response to certain kinds of stimuli, typically modulated electrical signals through the DSPs [that is digital signal processing] that we call our retina and cochlea."

"Most applications of AI have been in domains with large amounts of data," Honavar says. To use the radiology example again, the existence of large databases of X-rays and MRI scans that have been evaluated by human radiologists, makes it possible to train a machine to emulate that activity.

AI works by combining large amounts of data with intelligent algorithms — series of instructions — that allow the software to learn from patterns and features of the data, as this SAS primer on artificial intelligence explains.

In simulating the way a brain works, AI utilizes a bunch of different subfields, as the SAS primer notes.

Machine learning automates analytical model building, to find hidden insights in data without being programmed to look for something in particular or draw a certain conclusion.

Neural networks imitate the brain's array of interconnected neurons, and relay information between various units to find connections and derive meaning from data.

Deep learning utilizes really big neural networks and a lot of computing power to find complex patterns in data, for applications such as image and speech recognition.

Cognitive computing is about creating a "natural, human-like interaction," as SAS puts it, including using the ability to interpret speech and respond to it.

Computer vision employs pattern recognition and deep learning to understand the content of pictures and videos, and to enable machines to use real-time images to make sense of what's around them.

Natural language processing involves analyzing and understanding human language and responding to it.

What Is the Industrial Internet of Things (IIoT)?

IoT applications in industry are also referred to as the Industrial Internet of Things (IIoT) or Industry 4.0. This primarily involves digitally networked machines or systems. A key area of application is intelligent manufacturing: Individual stations in a production line communicate with each other without human intervention. Machines independently retrieve the information they need to work efficiently and continuously regulate or optimize themselves, including predictive maintenance. This allows production processes to be accelerated, saving costs and time. Thanks to order-based just-in-time production, less storage space is required. The entire supply chain management, including supplier selection, can also be fully automated. Other IIoT application areas include intelligent power grids, smart cities, and networked and intelligent logistics.

What is Smart Home?

A smart home means your home has a smart system that connects with your appliances to semi-automate, automate specific tasks and is typically remotely controlled. You can use a smart system to program your sprinklers, set and monitor your home security system and cameras, or control appliances like your fan, lights, refrigerator or air conditioning and heating.

Why is IoT important?

The internet of Things helps people live and work smarter, as well as gain complete control over their daily lifestyle. In addition to offering smart devices to automate equipment used at home, IoT is essential to business. IoT provides businesses with a real-time look into how their systems really work, delivering insights into everything from the performance of machines to supply chain and logistics operations. IoT enables companies to automate processes, analytics and reduce labor costs. It also cuts down on waste and improves service delivery, making it less expensive to manufacture and deliver goods, as well as offering transparency into customer transactions. As such, IoT is one of the most important technologies of everyday life, and it will continue to pick up steam as more businesses realize the potential of connected devices to keep them competitive.