IoT: An Overview of the Internet of Things

Imagine a World Connected: The Internet of Things (IoT)

• IoT envisions a world where everyday objects are online, communicating to enhance our lives.
• Examples include self-driving drones and health-monitoring clothing.
• IoT aims to "connect the unconnected," linking objects to the internet for interaction.
• It facilitates sensing and controlling the physical world, making objects smarter through intelligent networks.
• Remote sensing and control enable tighter integration between the physical world and computers.
• This integration improves efficiency, accuracy, automation, and advanced applications.
• IoT comprises various concepts, protocols, and technologies dependent on specific industries.
• Benefits include increased productivity and automation, but challenges involve scaling devices and data processing.

Understanding IoT: Key Elements

• This chapter defines IoT and its elements for a foundation in subsequent chapters.
• Topics include:
  • Genesis of IoT: IoT's place in the Internet's evolution.
  • IoT and Digitization: Distinguishing IoT from digitization.
  • IoT Impact: Scenarios demonstrating IoT's influence.
  • Convergence of IT and OT: How IoT merges information technology (IT) and operational technology (OT).
  • IoT Challenges: Difficulties in transitioning to an IoT-enabled world.

Genesis of IoT: The Rise of Connected Devices

• The age of IoT began around 2008-2009 when connected devices exceeded the world population.
• Kevin Ashton coined the term "Internet of Things" in 1999 while at Procter & Gamble.
• He used it to link the company's supply chain to the Internet.
• Ashton explains IoT as adding senses to computers.
• In the 20th century, computers lacked senses and relied on human input.
• IoT changes this by enabling computers to sense things independently.
• IoT is a major technology shift, fitting into the Internet's evolution across four phases.
• Each phase profoundly impacts society and lives.

Phases of the Internet's Evolution

The evolution of the internet is categorized into four phases:

• Connectivity (Digitize access)
  • Connected people to email, web services, and search for easy information access.
• Networked Economy (Digitize business)
  • Enabled e-commerce, supply chain enhancements, and collaboration for business process efficiency.
• Immersive Experiences (Digitize interactions)
  • Extended Internet to video, social media, and mobility, with applications moving to the cloud.
• Internet of Things (Digitize the world)
  • Adds connectivity to objects and machines to enable new services and experiences.
  • Connects the unconnected.

Each phase builds on the previous, increasing value for businesses, governments, and society.

Connectivity Phase: Early Internet Access

• The Connectivity phase began in the mid-1990s.
• Email and Internet access were initially luxuries for universities and corporations.
• Dial-up modems were used for basic connectivity.

Networked Economy Phase: Leveraging Connectivity for Profit

• Connectivity improvements led to a focus on efficiency and profit.
• E-commerce and digitally connected supply chains emerged.
• This caused major disruptions, with vendors, suppliers, and consumers becoming more connected.
• Traditional brick-and-mortar retailers suffered.

Immersive Experiences Phase: Social Media and Mobility

• Social media, collaboration, and widespread mobility characterized this phase.
• Connectivity became pervasive across multiple platforms.
• Person-to-person interactions became digitized.

Internet of Things Phase: Connecting Machines and Objects

• Despite media coverage, IoT is still in its early stages.
• 99% of "things" remain unconnected.
• Machines and objects connect with each other and humans.
• This leads to data, knowledge, insights, automation, and process efficiencies.
• IoT is poised to change the world like previous Internet phases.

IoT and Digitization: Defining the Terms

• IoT and digitization are often used interchangeably, but have key differences.
• IoT focuses on connecting "things" to computer networks like the Internet.
• Digitization encompasses connecting "things" with data and business insights.
• Wi-Fi location tracking in shopping malls illustrates digitization.
• "Things" are the Wi-Fi devices.
• Tracking Wi-Fi clients provides business benefits to mall and shop owners.
• Analysis of location data helps optimize product displays, advertising, shop placement, and security.

Internet of Everything (IoE) and Digitization

• The term Internet of Everything (IoE) has been replaced by digitization.
• IoE and digitization have roughly the same definition.
• IoT is a subset of both IoE and digitization.
• Digitization is the conversion of information into a digital format.
• This has been happening for decades across various industries.

Examples of Digitization: Photography, Video, and Transportation

• Photography: Shift to digital cameras.
• Video Rental: Streaming and downloadable files replaced physical media.
• Transportation: Uber and Lyft use mobile apps to connect riders and drivers.

IoT's Role in Digitization and Enhanced Connections

• In the context of IoT, digitization brings together things, data, and business processes.
• Home automation products like Nest exemplify this.
• Nest integrates sensors, climate settings, smoke alarms, cameras, and third-party devices.
• These functions were previously managed separately.
• Digitization and IoT increase the relevancy and value of networked, intelligent connections.
• Companies view digitization as a differentiator, with IoT as a key enabler.
• Smart objects and increased connectivity drive digitization.

IoT Impact: Impressive Projections and Benefits

• Projections on the potential impact of IoT are impressive.
• Currently, about 14 billion "things" are connected to the Internet.
• Cisco Systems predicts 50 billion connections by 2020.
• A UK government report speculates 100 billion connected objects.
• Cisco estimates $19 trillion in profits and cost savings from new connections.
• IoT will fundamentally shift how people and businesses interact with their surroundings.
  Managing and monitoring smart objects using real-time connectivity enables a whole new level of data-driven decision making.
  This in turn results in the optimization of systems and processes and delivers new services that save time for both people and businesses while improving the overall quality of life.
  The future include connected roadways, connected factories, smart connected buildings, and smart creatures (animals).

Connected Roadways: The Future of Transportation

Connected roadways is the term associated with both the driver and driverless cars fully integrating with the surrounding transportation infrastructure.

• IoT will allow self-driving vehicles to better interact with the transportation system.
• It enables bidirectional data exchanges while providing data to riders.
• Self-driving cars require reliable communications and data from sensors.
• Connected roadways integrate driver and driverless cars with transportation infrastructure.

Current Challenges Being Addressed by Connected Roadways

• Safety: IoT and connected vehicle technologies will empower drivers with the tools they need to anticipate potential crashes and significantly reduce the number of lives lost each year.
• Mobility: Connected vehicle mobility applications can enable system operators and drivers to make more informed decisions, which can, in turn, reduce travel delays.
• Environment: Connected vehicle environmental applications will give all travelers the real-time information they need to make “green” transportation choices.

By addressing safety, mobility, and environmental challenges, connected roadways will bring many benefits to society. These benefits include reduced traffic jams and urban congestion, decreased casualties and fatalities, increased response time for emergency vehicles, and reduced vehicle emissions.

Intersection Movement Assist (IMA)

• With IoT-connected roadways, a concept known as Intersection Movement Assist (IMA) is possible.
• This application warns a driver (or triggers the appropriate response in a self-driving car) when it is not safe to enter an intersection due to a high probability of a collision—perhaps because another car has run a stop sign or strayed into the wrong lane.
• Thanks to the communications system between the vehicles and the infrastructure, this sort of scenario can be handled quickly and safely.

Automated Vehicle Tracking

• With automated vehicle tracking, a vehicle’s location is used for notification of arrival times, theft prevention, or highway assistance.

Cargo Management

• Cargo management provides precise positioning of cargo as it is en route so that notification alerts can be sent to a dispatcher and routes can be optimized for congestion and weather.

Road Weather Communications

• Road weather communications use sensors and data from satellites, roads, and bridges to warn vehicles of dangerous conditions or inclement weather on the current route.

Amount of data from connected cars in the future

• A fully connected car will generate more than 25 gigabytes of data per hour, much of which will be sent to the cloud.
• To put this in perspective, that’s equivalent to a dozen HD movies sent to the cloud every hour—by your car!
• Multiply that by the number of hours a car is driven per year and again by the number of cars on the road, and you see that the amount of connected car data generated, transmitted, and stored in the cloud will be in the zettabytes range per year (more than a billion petabytes per year).

Automobile data uses

The data generated by your car needs to be handled in a secure and reliable way, which means the network needs to be secure, it must provide authentication and verification of the driver and car, and it needs to be highly available.

• Tire companies can collect data related to use and durability of their products in a range of environments in real time.
• Automobile manufacturers can collect information from sensors to better understand how the cars are being driven, when parts are starting to fail, or whether the car has broken down—details that will help them build better cars in the future.
• Car sensors will be able to interact with third-party applications, such as GPS/maps, to enable dynamic rerouting to avoid traffic, accidents, and other hazards.

The IoT data broker

• Imagine the many different types of data generated by an automobile and the plethora of different parties interested in this data. This poses a significant business opportunity.
• In a very real sense, the data generated by the car and driver becomes a valuable commodity that can be bought and sold.
  • Tire companies will pay for information from sensors related to your tires, but they won’t get anything else.

The Connected Factory: Revolutionizing Manufacturing

• Traditional factories face disadvantages due to disconnected production environments.
• Managers lack visibility into operations, which are composed of plant floors, front offices, and suppliers operating in independent silos.
• The main challenges facing manufacturing in a factory environment today include the following:
  • Accelerating new product and service introductions to meet customer and market opportunities
  • Increasing plant production, quality, and uptime while decreasing cost
  • Mitigating unplanned downtime (which wastes, on average, at least 5% of production)
  • Securing factories from cyber threats
  • Decreasing high cabling and re-cabling costs (up to 60% of deployment costs)
  • Improving worker productivity and safety

Retoolind factories

• Industrial enterprises around the world are retooling their factories with advanced technologies and architectures to resolve these problems and boost manufacturing flexibility and speed.
• These improvements help them achieve new levels of overall equipment effectiveness, supply chain responsiveness, and customer satisfaction.

Basic sensors in Connected Factories

• Just as the IoT solutions for the connected roadways previously discussed, there are already large numbers of basic sensors on factory floors.
• However, with IoT, these sensors not only become more advanced but also attain a new level of connectivity.
• They are smarter and gain the ability to communicate, mainly using the Internet Protocol (IP) over an Ethernet infrastructure.
• In addition to sensors, the devices on the plant floor are becoming smarter in their ability to transmit and receive large quantities of real-time informational and diagnostic data

Machine-to-people connections

• With IoT and a connected factory solution, true “machine-to-people” connections are implemented to bring sensor data directly to operators on the floor via mobile devices.
• Time is no longer wasted moving back and forth between the control rooms and the plant floor.
• In addition, because the operators now receive data in real time, decisions can be made immediately to improve production and fix any quality problems.

fourth Industrial Revolution.

• The IoT wave of Industry 4.0 takes manufacturing from a purely automated assembly line model of production to a model where the machines are intelligent and communicate with one another.
• IoT in manufacturing brings with it the opportunity for insertingintelligence into factories.
• This starts with creating smart objects, which involves embedding sensors, actuators, and controllers into just about everything related to production.

Smart Connected Buildings: Management

• IoT makes them easier and cheaper to manage.
• Managers are interested in making buildings more efficient and cheaper to manage.
• Smart building sensors and occupancy detection are combined with the power of data analytics, it becomes easy to demonstrate floor plan usage and prove your case.

Building automation (BAS)

• In an attempt to connect these systems into a single framework, the building automation system (BAS) has been developed to provide a single management system for the HVAC, lighting, fire alarm, and detection systems, as well as access control. All these systems may support different types of sensors and connections to the BAS. How do you connect them together so the building can be managed in a coherent way?
  • Biggest challenges in IoT: the heterogeneity of IoT systems.
  • BACnet (Building Automation and Control Network).defines a set of services that allow Ethernet-based communication between building devices such as HVAC, lighting, access control, and fire detection systems.

Digital ceiling

• Another promising IoT technology: the “digital ceiling.”
  • Encompasses several of the building’s different networks—including lighting, HVAC, blinds, CCTV (closed-circuit television), and security systems—and combines them into a single IP network.
• Central to digital ceiling technology is the lighting system (LEDs).

Smart Creatures: Connecting Living Things

• IoT connects living things to the Internet.
• Sensors can be placed on animals and insects.

Connected Cow Example.

• Sparked, a Dutch company, developed a sensor that is placed in a cow’s ear.
• The sensor monitors various health aspects of the cow as well as its location and transmits the data wirelessly for analysis by the farmer.
• Enables early detection of disease as cows tend to eat less days before they show symptoms

Sensors on roaches.

• Researchers at North Carolina State University are working with Madagascar hissing cockroaches in the hopes of helping emergency personnel rescue survivors after a disaster.
• The electronic backpack uses wireless communication to a controller and can be “driven” remotely.
• The electronic backpack is equipped with directional microphones that allow for the detection of certain sounds and the direction from which they are coming.

Convergence of IT and OT: Bridging the Divide

• Information technology (IT) and operational technology (OT) have traditionally been separate.
• IT supports Internet connections, data, and technology systems, focusing on secure data flow.
• OT monitors and controls devices and processes on physical operational systems.
• OT environments include assembly lines, utility distribution networks, factories, and roadway systems.
• IT typically did not involve itself with OT production and logistics.

IT vs OT responsibilities

• IT organization is responsible for the information systems of a business, such as email, file and print services, databases, and so on.
• OT is responsible for the devices and processes acting on industrial equipment, such as factory machines, meters, actuators, electrical distribution automation devices, SCADA (supervisory control and data acquisition) systems, and so on.
• Traditionally, OT has used dedicated networks with specialized communications protocols to connect these devices, and these networks have run completely separately from the IT networks.

Compare IT and OT:

• With the rise of IoT and standards-based protocols, such as IPv6, the IT and OT worlds are converging or, more accurately, OT is beginning to adopt the network protocols, technology, transport, and methods of the IT organization, and the IT organization is beginning to support the operational requirements used by OT.
• When IT and OT begin using the same networks, protocols, and processes, there are clear economies of scale.
• IoT is forcing these groups to work together, when in the past they have operated rather autonomously
• Overall benefit: a more efficient and profitable business due to reduced downtime, lower costs through economy of scale, reduced inventory, and improved delivery times.

IoT Challenges: Overcoming Obstacles

• An IoT-enabled future faces significant challenges.

Challenge 1: Scale

• OT scale can be orders of magnitude larger than IT networks.

Challenge 2: Security

• Security is an increasingly complex issue due to more connected "things."
• A compromised device can attack other devices and systems.
• IoT security is pervasive across facets of IoT.

Challenge 3: Privacy

• Sensors gather data specific to individuals and activities.
• There are discussions about data ownership and control.

Challenge 4: Big Data and Data Analytics

• IoT triggers a deluge of data that must be efficiently handled.

Challenge 5: Interoperability

• Various protocols and architectures compete within IoT.

IoT Network Architecture and Design

• Key is to carefully architect a network according to sound design principles

Network Architecture Is Gaining Influence in IT

• protect information technology (IT) systems need to be designed to withstand “network earthquakes,” such as distributed denial of service (DDoS) attacks, future growth requirements, network outages, and even human error.
• Chief enterprise architect (CEA) has gained so much traction in recent years that the position is often equated to the responsibilities of a CTO, and in many instances, the CEA reports directly to the CEO.

IT and IoT Network Architecture Are Different

• Enterprise IT network architecture has matured significantly over the past two decades and is generally well understood; however, the discipline of IoT network architecture is
  new and requires a fresh perspective.
• for the most part, the challenges and requirements of IoT systems are radically different from those of traditional IT networks
• IoT networks are often under the umbrella of OT, which is responsible for the management and state of operational systems. In contrast, IT networks are primarily concerned with the infrastructure that transports flows of data, regardless of the data type.

Key Items to Consider

• Drivers Behind New Network Architectures: OT networks drive core industrial business operations. They have unique characteristics and constraints that are not
  easily supported by traditional IT network architectures.
• Comparing IoT Architectures: Several architectures have been published for IoT, including those by ETSI and the IoT World Forum. This section discusses and compares these architectures.
• A Simplified IoT Architecture: While several IoT architectures exist, a simplified model is presented in this section to lay a foundation for rest of the material discussed in this book.
• The Core IoT Functional Stack: The IoT network must be designed to support its unique requirements and constraints. This section provides an overview of the full networking stack, from sensors all the way to the applications layer.
• IoT Data Management and Compute Stack: This section introduces data management, including storage and compute resource models for IoT, and involves edge, fog, and cloud computing.

The key difference between IT and IoT is the data.

• IT systems are mostly concerned with reliable and continuous support of business applications such as email, web, databases, CRM systems, and so on, IoT is all about the data generated by sensors and how that data is used.
• The essence of IoT architectures thus involves how the data is transported, collected, analyzed, and ultimately acted upon.

IT vs IoT

• IOT Architectural Change Required
  • The massive scale of IoT end-points (sensors) is far beyond that of typical IT networks
    • scale can be met only by using IPv6.
  • Security is required at every level of the IoT network. Every IoT endpoint node on the network must be part of the overall security strategy and must support device-level authentication and link encryption.
  • New last-mile wireless technologies are needed to support constrained IoT devices over long distances. The network is also constrained, meaning modifications need to be made to traditional network-layer transport mechanisms.
  • Data analytics capabilities need to be distributed throughout the IoT network, from the edge to the cloud. In traditional IT networks, analytics and applications typically run only in the cloud.

Security Consideration to keep in mind

• Most IoT sensors are designed for a single job, and they are typically small and inexpensive. This
  means they often have limited power, CPU, and memory, and they transmit only
  when there is something important. Because of the massive scale of these devices and the
  large, uncontrolled environments where they are usually deployed, the networks that
  provide connectivity also tend to be very lossy and support very low data rates. This is a completely different situation from IT networks, which enjoy multi-gigabit connection
  speeds and endpoints with powerful CPUs.
• IoT requires a new breed of connectivity technologies that meet both the scale and constraint limitations.
• Unlike IT networks, IoT systems are designed to stagger data consumption throughout the architecture, both to filter and reduce unnecessary data going
  upstream and to provide the fastest possible response to devices when necessary.
• Industrial compute systems often transmit their state or receive inputs from external devices through an alarm channel. These may drive an indicator light (stack lights) to display the status of a process element from afar. This same element can also receive inputs to initiate actions within the system itself.

Security Requirement for IoT

• Be able to identify and authenticate all entities involved in the IoT service (that is, gateways, endpoint devices, home networks, roaming networks, service platforms)
• Ensure that all user data shared between the endpoint device and back-end applications is encrypted
• Comply with local data protection legislation so that all data is protected and stored correctly
• Utilize an IoT connectivity management platform and establish rules-based security policies so immediate action can be taken if anomalous behavior is detected from connected devices
• Take a holistic, network-level approach to security

Legacy device Considerations for IoT

• Supporting legacy devices in an IT organization is not usually a big problem. If someone’s computer or operating system is outdated, she simply upgrades. If someone is using a mobile device with an outdated Wi-Fi standard, such as 802.11b or 802.11g, you can simply deny him access to the wireless network, and he will be forced to upgrade.
• In OT systems, end devices are likely to be on the network for a very long time—sometimes decades. As IoT networks are deployed, they need to support the older devices already present on the network, as well as devices with new capabilities. In many cases, legacy devices are so old that they don’t even support IP. For example, a factory may replace machines only once every 20 years—or perhaps even longer!
• In this case, the IoT network must either be capable of some type of protocol translation or use a gateway device to connect these legacy endpoints to the IoT network.

IoT Architectures

Architecture 1: oneM2M IoT Standardized Architecture

To standardize the rapidly growing field of machine-to-machine (M2M) communications, the European Telecommunications Standards Institute (ETSI) created the M2M Technical Committee in 2008. The goal of this committee was to create a
common architecture that would help accelerate the adoption of M2M applications and devices. Over time, the scope has expanded to include the Internet of Things. The goal of oneM2M is to create a common ser-vices layer, which can be readily embedded in field devices to allow communication with application servers.

This divides into three major domains
* the application layer,
* the services layer,
* the network layer.

oneM2M’s horizontal framework and RESTful APIs allow the LoRaWAN system to interface with the building management system over an IoT network,
thus promoting end-to- end IoT communications in a consistent way, no matter how heterogeneous the networks.

Architecture 2: IoT World Forum (IoTWF) Standardized Architecture

• In 2014 the IoTWF architectural committee (led by Cisco, IBM, Rockwell Automation, and others) published a seven-layer IoT architectural reference model. While various IoT
  reference models exists, the one put forth by the IoT World Forum offers a clean, simplified perspective on IoT and includes edge computing, data storage, and access. It provides a succinct way of visualizing IoT from a technical perspective. Each of the seven
  layers is broken down into specific functions, and security encompasses the entire model.

Each of the seven layers:
* Layer 1: Physical Devices and Controllers Layer
* Layer 2: Connectivity Layer
* Layer 3: Edge Computing Layer
* Upper Layers: Layers 4–7

Edge Computing vs Fog Computing

One of the basic principles of this reference model is that information processing is initiated as early and as close to the edge of the network as possible.

IoT Responsibilities and Boundary

IoT systems have to cross several boundaries beyond just the functional layers. The bottom of the stack is generally in the domain of OT.
Then this will cross into IT and requires different groups to communicate.

Simplified IoT Architecture

For this book and its layout, it presents the IoT framework two parallel stacks:
* The IoT Data Management and Compute Stack and the Core IoT Functional Stack.
These are meant to simply the understand of an IoT architecture.
The Core IoT Functional Stack includes core layers similar to those shown on the left side of Figure 2-6, including “things,” a communications network, and applications.
Each layer of the two stack will have security considerations to to keep in mind

The Core IoT Functional Stack

Elements:

• Communications network layer
  • Sublayers
    • Access network sublayer (last mile)
    • Gateways and backhaul network sublayer
    • Transport sublayer
    • App management sublayer
• Application and analytics layer
  • The goal is to give intelligent decision make and instruct accordingly.

In the next chapters those will be expanded upon

Classifying the things

• the sensors:
  • Battery-powered or power-connected: This classification is based on whether the object carries its own energy supply or receives continuous power from an external power source
  • Mobile or static: This classification is based on whether the “thing” should move or always stay at the same location.
  • Low or high reporting frequency: This classification is based on how often the object should report monitored parameters.
  • Simple or rich data:
    • This classification is based on the quantity of data exchanged at each report cycle. Higher frequencies drive higher energy consumption, which may create constraints
      on the possible power source (and therefore the object mobility) and the transmission range.
  • Report range: This classification is based on the distance at which the gateway is located.
  • Object density per cell:
    • This classification is based on the number of smart objects (with a similar need to communicate) over a given area, connected to the same gate- way.

The IoT communications.

• the physical environment in which the devices are deployed.
• Temperature variances.
• Humidity fluctuations
• Operating extremes related to kinetic forces. Shock and vibration

Access Network and Distance

• Distance can range from personal to wide range:
  • PAN (personal area network)
  • HAN (home area network)
  • NAN (neighborhood area network)
  • FAN (field area network
  • LAN (local area network)
    MAN (metropolitan area network

Important to factor topology when deciding on your system:

• Point-to-point topologies
• Point-to-multipoint topologies:
• Mesh topologies

Sublayer Backhaul

Used to connect the smart medium used to collect and get the data to another one.
With wireless example being:

• WiMAX
• Cellular (for example, LTE)

Transport Sublayer

Data can be flow in different ways:
Vertical , mesh, from a given place
Need IP to do this, since it is open and has great scalability

IoT sublayer Management

• the sensor reports at a regular interval or based on a
  local trigger
• Also protocols:
  • web-derived protocols have been suggested for the IoT space. One example is WebSocket.
  • Constrained Application Protocol (CoAP).
  • Message Queue Telemetry Transport (MQTT)

Application vs Control Applications:

• Analytics application (process for information display) vs
• Control application (controls objects behavior)

Analytics vs Business is something to consider.
Also whether or not to give a system open ability.

Then comes smart services. From sensor to communication there are many different options that comes with efficiency.

IoT Data Management and Compute Stack

Traditional it data is general from communications with servers with high bandwidth.
IoT generates such an abundant amount that creates new challenges. As the data has some limit data.

challenges

• Volume gets high but data might now be very needed.
• Limited bandwidth.
• Big Data gets bigger
• Network connection may be unreliable.

To address is to make the processing point closer

Fog Computing

Local servers the data and processing center to analyze the data at location.
This is different than the traditional IT computing model.
An advantage of this structure is that the fog node allows intelligence gathering (such as
analytics) and control from the closest possible point, and in doing so, it allows better
performance over constrained networks.
Not meant to replace cloud but help work together
Therefore this creates a distributed computing network, all work together.
But has ractistics of Edge Computing
Contextual location awareness and low latency
Geographic area is very wide
Communicate close to the end target.
Mostly used in real time interaction,

The hierarchy has these steps:
*Data comes in.
*Gets collectd,analyzed,responded.

• Gets send to cloud to analyze over long period of times.
  The heterogeous can come up again in edge as well. Abstraction layer will expose a common set of APIs for these so it can work.