IoT Lecture Notes

ARI 202: Internet of Things

Introduction

The Internet of Things (IoT) is defined by the phrase: "Anything that can be connected, will be connected." IoT involves interrelated computing devices, mechanical and digital machines, objects, animals, or people provided with unique identifiers (UIDs) and the ability to transfer data over a network without requiring human-to-human or human-to-computer interaction (IoTAgenda).

A "thing" in IoT can be a person with a heart monitor, a farm animal with a biochip, an automobile with built-in tire pressure sensors, or any natural or man-made object assignable an IP address and capable of data transfer.

IoT consists of a sensor network comprised of billions of smart devices connecting people, systems, and applications to collect and share data.

IoT involves connecting any device with an on/off switch to the Internet and/or each other, including cellphones, coffee makers, washing machines, headphones, lamps, and wearable devices.

This also applies to machine components like a jet engine or oil rig drill (Forbes).

IoT as a Network

The IoT is a giant network of connected "things," including people, enabling relationships between people-people, people-things, and things-things.

Consumer IoT

The dominant consumer IoT device worldwide is the smart TV, owned by 25-35% of consumers with Internet connectivity (Deloitte research). Other IoT market areas are growing rapidly.

Why IoT?

Organizations across industries use IoT for:

• Efficient operation
• Better customer understanding for enhanced service
• Improved decision-making
• Increased business value

IoT Ecosystem

An IoT ecosystem comprises web-enabled smart devices using embedded processors, sensors, and communication hardware to collect, send, and act on data acquired from their environments.

IoT devices share sensor data by connecting to an IoT gateway or edge device where data is sent to the cloud for analysis or analyzed locally.

7 Components of an IoT Ecosystem

1. IoT Devices
2. Network
3. The Cloud
4. Gateway
5. Application
6. Security
7. Users

Top 10 Strategic IoT Technologies and Trends (Gartner)

1. Artificial Intelligence (AI): Data powers the IoT, and the ability to derive meaning from it determines long-term success.
2. Social, Legal, and Ethical IoT: Includes data ownership, algorithmic bias, privacy, and compliance with regulations like the General Data Protection Regulation. Social acceptability is crucial for successful IoT deployment.
3. Infonomics and Data Broking: Treats data monetization as a strategic business asset recorded in company accounts. The buying and selling of IoT data is projected to be an essential part of many IoT systems by 2023.
4. Shift from Intelligent Edge to Intelligent Mesh: The shift from centralized cloud to edge architectures is underway, enabling more flexible, intelligent, and responsive IoT systems, albeit with added complexities.
5. IoT Governance: A governance framework will be needed to ensure appropriate behavior in the creation, storage, use, and deletion of information related to IoT projects as IoT expands.
6. Sensor Innovation: The sensor market will evolve continuously through 2023, with new sensors enabling detection in a wider range of situations and events.
7. Trusted Hardware and Operating System: By 2023, expect to see hardware and software combinations creating more trustworthy and secure IoT systems.
8. Novel IoT User Experiences: User experience is driven by new sensors, algorithms, experience architectures, context, and socially aware experiences.
9. Silicon Chip Innovation: New special-purpose chips are expected to reduce the power consumption required to run IoT devices by 2023.
10. New Wireless Networking Technologies for IoT: IoT networking involves balancing competing requirements, particularly exploring 5G, low earth orbit satellites, and backscatter networks.

Benefits of IoT

IoT enables organizations to:

1. Monitor overall business processes
2. Improve customer experience
3. Save time and money
4. Enhance employee productivity
5. Integrate and adapt business models
6. Make better business decisions
7. Generate more revenue

IoT Pillars

• SCADA
• M2M
• RFID
• WSN

Technology Trends in IoT (2022)

1. IoT is developing into a crucial technology for sustainability.
2. The platform hype is moving from cloud to the edge.
3. IIoT initiatives are transforming manufacturing.
4. Cloud-native applications are on the rise.
5. Hyper-automation is transforming operations.
6. AI is increasingly found at the (Thin) Edge.
7. "Invisible AI" adoption is happening.
8. Immersive realities (VR/AR) are entering the enterprise environment.
9. 5G is becoming "IoT ready."
10. Secure remote access of assets is growing in importance.

Key Technologies Driving IoT Development

• Cloud Computing: IoT focuses on sharing real-time information, generating huge data amounts requiring cloud space for storage and processing. Cloud computing offers the potential to store and quickly process these vast datasets.
• Blockchain: Combining IoT solutions with blockchain ensures that data is reliable, authentic, and genuine. For example, in supply chains, assigning a digital ID to each product component aids in smooth movement and tamper-proof tracking.
• Sensors: Sensors are key elements in IoT solutions, enabling different day-to-day activities. Advanced IoT sensors facilitate remote activities.
• Artificial Intelligence: AI combined with IoT solutions helps businesses analyze the massive data collected by IoT apps and devices, generating important insights. During the global pandemic, IoT helped businesses across industries operate and grow simultaneously.

Business Drivers

Key business drivers for IoT development include:

• Developing the IoT product (value chain, developing connected features).
• Developing the business model (revenue model, pricing the IoT product).
• Commercializing the IoT product (time-to-market, market positioning).
• Driving adoption rates (measuring success).

How to create a successful IoT business model

IoT Development: Key Business Driver

• Increase productivity by optimizing processes and costs (e.g., connected machines harvesting data for predictive maintenance).
• Generate new revenue streams by creating new offers and business models (e.g., agriculture management combining sensor tech and scientific knowledge).
• Enhance regulation compliance by remote equipment monitoring (e.g., household smart metering of energy).
• Improve customer loyalty by enriching customer relationships (e.g., In-car connected devices for fleet tracking or premium concierge services).

IoT Connecting Technologies

Fast data is real-time data from streaming sources like IoT technologies and event-driven applications, analyzed quickly for rapid business decisions. Unlike big data, fast data provides real-time insights and quick analysis is crucial to the bottom line.

Consumer and Enterprise IoT Applications

• Smart city
• Smart car
• Wearables
• Smart health
• Smart appliances
• Smart farming
• Smart TV
• Smart home
• Smart buildings

Sample: Consumer IoT Products & Services

1. Helmet Concussion Sensor
2. Medical Alert Watch
3. Smart Fitness Clothing and Smart Running Shoes
4. One-Button Product Purchases: Amazon Dash buttons allow reordering products with a physical button press.
5. Garden Sensors
6. Smart Televisions

Kinsa Thermometer

Monitoring your temperature and can call your doctor as necessary

Connected Car

The connected car is equipped with internet connections and software that allow people to stream music, look up movie times, be alerted of traffic and weather conditions, and even power driving-assistance services such as self-parking.

Smart Farming: Use of IoT to Improve Agriculture

IoT-based smart farming involves monitoring crop fields with sensors (light, humidity, temperature, soil moisture) and automating irrigation systems, enabling farmers to monitor field conditions remotely. Benefits include:

• Better water usage
• Optimization of inputs and treatments
• Reduced waste
• Enhanced productivity

IoT applications include:

• Precision farming
• Agricultural drones
• Livestock monitoring
• Smart greenhouses

Industrial IoT (IIoT)

IIoT focuses on using cyber-physical systems to monitor physical factory processes and make data-based automated decisions.

Using IoT, physical systems become intelligent, and real-time communication is established between systems and humans via wireless web. 'A connected factory leads to a smart factory.'

IIoT in Manufacturing

1. Digital/connected factory: IoT-enabled machinery can transmit operational information to partners like original equipment manufacturers and field engineers.
2. Facility management: Use of IoT sensors in manufacturing equipment enables condition-based maintenance alerts.
3. Production flow monitoring: IoT in manufacturing can enable the monitoring of production lines starting from the refining process down to the packaging of final products.
4. Inventory management: IoT applications permit the monitoring of events across a supply chain.
5. Plant Safety and Security: IoT combined big data analysis can improve the overall workers’ safety and security in the plant.
6. Quality control: IoT sensors collect aggregate product data and other third-party syndicated data from various stages of a product cycle.
7. Packaging Optimization: By using IoT sensors in products and/or packaging, manufacturers can gain insights into the usage patterns and handling of product from multiple customers.
8. Logistics and Supply Chain Optimization: The Industrial IoT (IIoT) can provide access to real-time supply chain information by tracking materials, equipment, and products as they move through the supply chain.

Technologies Involved in IoT Development

IoT primarily exploits standard protocols and networking technologies. Major enabling technologies and protocols include RFID, NFC, low-energy Bluetooth, low-energy wireless, low-energy radio protocols, LTE-A, and WiFi-Direct.

• NFC and RFID

  RFID (radio-frequency identification) and NFC (near-field communication) provide simple, low-energy, and versatile options for identity and access tokens, connection bootstrapping, and payments.

  RFID technology employs 2-way radio transmitter-receivers to identify and track tags associated with objects.

  NFC consists of communication protocols for electronic devices, typically a mobile device and a standard device.

• Low-Energy Bluetooth

  This technology supports the low-power, long-use need of IoT function while exploiting a standard technology with native support across systems.

• Low-Energy Wireless

  This technology replaces the most power-hungry aspect of an IoT system. Though sensors and other elements can power down over long periods, communication links (i.e., wireless) must remain in listening mode. Low-energy wireless not only reduces consumption but also extends the life of the device through less use.

• Radio Protocols

  ZigBee, Z-Wave, and Thread are radio protocols for creating low-rate private area networks. These technologies are low-power but offer high throughput unlike many similar options. This increases the power of small local device networks without the typical costs.

• LTE-A

  LTE-A, or LTE Advanced, delivers an important upgrade to LTE technology by increasing not only its coverage but also reducing its latency and raising its throughput. It gives IoT a tremendous power through expanding its range, with its most significant applications being vehicle, UAV, and similar communication.

• WiFi-Direct

  WiFi-Direct eliminates the need for an access point. It allows P2P (peer-to-peer) connections with the speed of WiFi, but with lower latency. WiFi-Direct eliminates an element of a network that often bogs it down, and it does not compromise on speed or throughput.

IoT Challenges

• Security, privacy, and data sharing issues: Because IoT devices are closely connected, exploiting one vulnerability can compromise all data. Manufacturers who don't regularly update devices leave them vulnerable to cybercriminals.
• Privacy: Companies could use consumer IoT devices to obtain and sell users' personal data.
• Challenges with IIoT:
  • Security of data is paramount.
  • Reliability and stability of IIoT sensors is critical.
  • Connectivity of all the systems in IIoT setup must be ensured.
  • Blending legacy systems with IIoT, which is new, presents unique challenges.

Edge Technology

• Enhanced Data rates for GSM Evolution (EDGE) also known as Enhanced GPRS (EGPRS).
• Edge computing is an emerging computing paradigm which refers to a range of networks and devices at or near the user. Edge is about processing data closer to where it's being generated, enabling processing at greater speeds and volumes, leading to greater action-led results in real time.

Cloud Computing vs. Edge Computing

Cloud Computing: Computation takes place centrally.

Edge Computing: Computation takes place near the data source (Edge Server).

IoT Security Issues

1. Public Perception: A major problem that manufacturers should address. 52% of users are worried about the security vulnerabilities of smart home devices.
2. Vulnerability to Hacking: Researchers have been able to hack into real devices, meaning hackers could likely replicate their efforts. For example, a team of researchers found holes in the security of Samsung’s SmartThings platform.
3. Are Companies Ready?: 85% of enterprises are in the process of or intend to deploy IoT devices, but only 10% feel confident that they could secure those devices against hackers.
4. True Security: Securing IoT devices means more than simply securing the actual devices themselves. Companies also need to build security into software applications and network connections that link to those devices.

IoT Privacy Issues

1. Too Much Data: The amount of data that IoT devices can generate is staggering. Fewer than 10,000 households can generate 150 million discrete data points every day, creating more entry points for hackers and leaving sensitive information vulnerable.
2. Unwanted Public Profile: Companies could use collected data that consumers willingly offer to make employment decisions. For example, an insurance company might gather information about your driving habits through a connected car when calculating your insurance rate.
3. Eavesdropping: Manufacturers or hackers could actually use a connected device to virtually invade a person’s home. German researchers accomplished this by intercepting unencrypted data from a smart meter device to determine what television show someone was watching at that moment.
4. Consumer Confidence: Each of these problems could put a dent in consumers’ desire to purchase connected products, which would prevent the IoT from fulfilling its true potential.

Data Confidentiality

• Insufficient authentication/authorization
• Insecure interfaces (web, mobile, cloud, etc.)
• Lack of transport encryption
• Confidentiality preserving
• Access control

Privacy Issues

• Privacy, data protection and information.
• security risk management
• Privacy by design and privacy by default
• Data protection legislation
• Traceability/profiling/unlawful processing

Trust

• Identity management system
• Insecure software/firmware
• Ensuring continuity and availability of services
• Realization of malicious attacks against loT devices and system
• Loss of user control/difficult in making decision

Security Issues

• Confidentiality
• Integrity
• Privacy
• Authentication
• Identity
• Location
• Trajectory
• Report
• Query

Security Requirements in IoT

What Needs To Be Done?

1. Consumer education
2. Product reviews and comparisons
3. Vulnerability disclosure and vulnerability markets
4. Self-certification and voluntary codes of practice
5. Trust marks and labels like Internet Society’s Online Trust Alliance (OTA) IoT Trust Framework
6. Government initiatives
7. Mandated security requirements
8. Mandated certification
9. Liability reform
10. Etc.
11. No intervention!?

M2M Value Chain

Inputs -> Production/Manufacture -> Processing -> Distribution -> Packaging and Marketing

M2M to IoT Value Chain

Expands upon the M2M value chain by adding devices/sensors, asset information, open data sets, and various information components, incorporating OSS/BSS networks, corporate databases, and large-scale system integrators.

IoT Value Chain

Device (hardware) -> Connectivity -> Application

• Hardware: Device, Sensors, Comms hardware
• Connectivity: Connectivity Backend Software, Systems integration
• Application: Billing and support

Overview of Governance in IoT

An IoT governance framework should ensure data integrity and data security for information shared by all IoT devices in the enterprise network and should maintain the trusted source of information across the different layers of the IoT architecture.

An IoT governance model is an effective way to address data security and privacy concerns, as well as legal, ethical, and public relations matters. It establishes the policies, procedures, and practices that define how a company will design, build, deploy, and manage an IoT system.

IoT governance models should comply with industry, local, and global data security and privacy laws, defining how an IoT device should collect, store, manage, use, and discard data.

• Governance
• Stakeholders
• Risk Management
• Governance Mechanisms
• Principles, Policies and Standards
• Interested Parties

IoT Governance Model

Includes design, infrastructure, data operation, sensors-actuators, scales, scalability implementation, fog computing, security and communications, innovation devices, management and monitoring, integration and testbeds, dashboards and metrics, skills, Enterprise Culture, Tools, Apps and Analytics

The Future of IoT

• Bain & Company expects annual IoT revenue of hardware and software to exceed $450$ billion by 2020.
• McKinsey & Company estimates IoT will have an $11.1$ trillion impact by 2025.
• IHS Markit believes the number of connected IoT devices will increase 12% annually to reach $125$ billion in 2030.
• Gartner assesses that $20.8$ billion connected things will be in use by 2020, with total spend on IoT devices and services to reach $3.7$ trillion in 2021.
• By 2023, the average CIO will be responsible for more than three times as many endpoints as this year – Gartner
• Garter forecasts that worldwide IoT Security Spending will be $3.11$ billion by 2021 largely driven by regulatory compliance.
• Great improvements in the security of IoT devices driven by manufacturers’ own initiatives as well users’ demand for better secure devices.
• Global manufacturers will use analytics data recorded from connected devices to analyze processes and identify optimization possibilities, according to IDC and SAP.
• Business Insider forecasts that by 2020, 75 percent of new cars will come with built-in IoT connectivity.

IoT Hardware Platforms and Prototyping Kits

• Raspberry Pi
• Arduino
• Pycom
• Particle
• SODAQ
• Adafruit
• SparkFun
• Espressif

Internet of Things Uses by Industry

• HOME: Smart Temperature Control, Optimized Energy Use
• INDUSTRIAL: Machine-to-Machine Communication, Quality Control
• AUTOMOTIVE: Vehicle Auto-Diagnosis, Optimized Traffic Flow, Smart Parking
• AGRICULTURE: Offspring Care, Crop Management, Soil Analysis
• MILITARY: Situational Awareness, Threat Analysis
• MEDICAL: Optimized Patient Care, Wearable Fitness Devices, Quality Data Reporting
• ENVIRONMENTAL: Forest Fire Detection, Species Tracking, Weather Prediction
• RETAIL: Theft Protection, Inventory Control, Focused Marketing