Definition
The Internet of Things (IoT) is a system of interrelated computing devices, mechanical and digital machines, objects, animals or people that are provided with unique identifiers and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction.
1. A thing, in the Internet of Things, can be a person with a heart monitor implant, a farm animal with a biochip transponder, an automobile that has built-in sensors to alert the driver when tire pressure is low -- or any other natural or man-made object that can be assigned an IP address and provided with the ability to transfer data over a network.
2. Kevin Ashton, cofounder and executive director of the Auto-ID Center at MIT, first mentioned the Internet of Things in a presentation he made to Procter & Gamble in 1999. Here’s how Ashton explains the potential of the Internet of Things:“Today computers -- and, therefore, the internet -- are almost wholly dependent on human beings for information. Nearly all of the roughly 50 petabytes (a petabyte is 1,024 terabytes) of data available on the internet were first captured and created by human beings by typing, pressing a record button, taking a digital picture or scanning a bar code.
The problem is, people have limited time, attention and accuracy -- all of which means they are not very good at capturing data about things in the real world. If we had computers that knew everything there was to know about things -- using data they gathered without any help from us -- we would be able to track and count everything and greatly reduce waste, loss and cost. We would know when things needed replacing, repairing or recalling and whether they were fresh or past their best.”
3. Although the concept wasn't named until 1999, the Internet of Things has been in development for decades. The first internet appliance, for example, was a Coke machine at Carnegie Melon University in the early 1980s. The programmers could connect to the machine over the internet, check the status of the machine and determine whether or not there would be a cold drink awaiting them, should they decide to make the trip down to the machine.
4. Environmental monitoring
Infrastructure management
Manufacturing
Agriculture
Energy management
Medical and healthcare
Building and home automation
Transportation
Metropolitan scale deployments
Consumer application
1. In a computer, system understanding means being able to take in large volumes of both structured and unstructured data and derive meaning from it—that is, establish a model of concepts, entities and relationships. Reasoning means using that model to be able to derive answers or solve related problems without having the answers and solutions specifically programmed. And learning means being able to automatically infer new knowledge from data, which is a key component in understanding at scale.
What is cognitive IoT?
Cognition of course means thinking, and while computers are not yet capable of general human-like thought, they can now perform some of the same underlying functions that humans perceive as thinking. Cognition involves three key elements:
Understanding
Reasoning
Learning
Cognitive’s IoT potential
Build cognitive services that allow for a natural interaction over huge data sets
Voice input and image recognition as areas where cognitive services could make an impact in the IoT space.
How far can we go in mixing human interaction and technology when leveraging profiling and personalization
IoT is creating new opportunities and providing a competitive advantage for businesses in current and new markets. It touches everything—not just the data, but how, when, where and why you collect it. The technologies that have created the Internet of Things aren’t changing the internet only, but rather change the things connected to the internet—the devices and gateways on the edge of the network that are now able to request a service or start an action without human intervention at many levels.
Because the generation and analysis of data is so essential to the IoT, consideration must be given to protecting data throughout its life cycle. Managing information at all levels is complex because data will flow across many administrative boundaries with different policies and intents.
Given the various technological and physical components that truly make up an IoT ecosystem, it is good to consider the IoT as a system-of-systems. The architecting of these systems that provide business value to organizations will often be a complex undertaking, as enterprise architects work to design integrated solutions that include edge devices, applications, transports, protocols, and analytics capabilities that make up a fully functioning IoT system. This complexity introduces challenges to keeping the IoT secure, and ensuring that a particular instance of the IoT cannot be used as a jumping off point to attack other enterprise information technology (IT) systems.
The Problem with the Current Centralized Model
The current IoT ecosystems rely on centralized, brokered communication models, otherwise known as the server/client paradigm. All devices are identified, authenticated and connected through cloud servers that sport huge processing and storage capacities. Connection between devices will have to exclusively go through the internet, even if they happen to be a few feet apart.
IoT is creating new opportunities and providing a competitive advantage for businesses in current and new markets. It touches everything—not just the data, but how, when, where and why you collect it. The technologies that have created the Internet of Things aren’t changing the internet only, but rather change the things connected to the internet—the devices and gateways on the edge of the network that are now able to request a service or start an action without human intervention at many levels.
Because the generation and analysis of data is so essential to the IoT, consideration must be given to protecting data throughout its life cycle. Managing information at all levels is complex because data will flow across many administrative boundaries with different policies and intents.
Given the various technological and physical components that truly make up an IoT ecosystem, it is good to consider the IoT as a system-of-systems. The architecting of these systems that provide business value to organizations will often be a complex undertaking, as enterprise architects work to design integrated solutions that include edge devices, applications, transports, protocols, and analytics capabilities that make up a fully functioning IoT system. This complexity introduces challenges to keeping the IoT secure, and ensuring that a particular instance of the IoT cannot be used as a jumping off point to attack other enterprise information technology (IT) systems.
The Problem with the Current Centralized Model
The current IoT ecosystems rely on centralized, brokered communication models, otherwise known as the server/client paradigm. All devices are identified, authenticated and connected through cloud servers that sport huge processing and storage capacities. Connection between devices will have to exclusively go through the internet, even if they happen to be a few feet apart.
IoT is creating new opportunities and providing a competitive advantage for businesses in current and new markets. It touches everything—not just the data, but how, when, where and why you collect it. The technologies that have created the Internet of Things aren’t changing the internet only, but rather change the things connected to the internet—the devices and gateways on the edge of the network that are now able to request a service or start an action without human intervention at many levels.
Because the generation and analysis of data is so essential to the IoT, consideration must be given to protecting data throughout its life cycle. Managing information at all levels is complex because data will flow across many administrative boundaries with different policies and intents.
Given the various technological and physical components that truly make up an IoT ecosystem, it is good to consider the IoT as a system-of-systems. The architecting of these systems that provide business value to organizations will often be a complex undertaking, as enterprise architects work to design integrated solutions that include edge devices, applications, transports, protocols, and analytics capabilities that make up a fully functioning IoT system. This complexity introduces challenges to keeping the IoT secure, and ensuring that a particular instance of the IoT cannot be used as a jumping off point to attack other enterprise information technology (IT) systems.
The Problem with the Current Centralized Model
The current IoT ecosystems rely on centralized, brokered communication models, otherwise known as the server/client paradigm. All devices are identified, authenticated and connected through cloud servers that sport huge processing and storage capacities. Connection between devices will have to exclusively go through the internet, even if they happen to be a few feet apart.
To perform the functions of traditional IoT solutions without a centralized control, any decentralized approach must support three fundamental functions:
Peer-to-peer messaging
Distributed file sharing
Autonomous device coordination
Blockchain is promising for IoT security for the same reasons it works for cryptocurrency
It provides assurances that data is legitimate, and the process that introduces new data is well-defined
Blockchain is the missing link that will enable scalability, privacy andreliability of IoT transactions.
Concept in blockchain technology called an oracle. "An oracle is a system that reports on the world to the blockchain in a reliable fashion“.
High-powered block miner replaces the usual internet router or media center to manage all local network transactions. This device not only manages the internal blockchain but also controls communication between home-based IoT devices and the outside world.
Securely allowing IoT devices to communicate and autonomously trade in a secure way, which will eventually enable the Economy of Things
But blockchain isn’t a slam dunk. Bitcoin presents a simpler problem to solve than IoT security. With bitcoin, blockchain simply moves wallets of currency from one anonymous owner to another. Full-fledged device authentication, security and control layers are more complex
One potential limitation of blockchain as an IoT safeguard is the 51 percent attack problem.
And although IoT devices are miracles of engineering, they are still underpowered compared to the hardware powering successful blockchains. Blockchain processing tasks are computationally difficult and time-consuming.
Receiving the data could create incentives for outside agencies to participate in the blockchain, bringing additional CPU power to support the health of the system.