Unit 6: IoT Applications for Value Creations

ECE128 — Introduction To Iot Networking Protocols 11 min read

I. Orientation

IoT applications create value by connecting physical objects, communication networks, data platforms, and intelligent services. Early IoT focused on identification and remote monitoring; modern systems increasingly support automation, prediction, safety, sustainability, and industrial decision-making. Industrial IoT, agriculture, healthcare, and smart environments depend on devices that can sense conditions, communicate efficiently, and act within application requirements.

Connected environment: Sensors, actuators, gateways, networks, cloud services, and users operate as one system.
Value creation: Benefits include reduced cost, improved productivity, better safety, lower energy use, and more informed decisions.
Constrained operation: Many devices have limited battery power, memory, processing capacity, bandwidth, and physical size.
Layered architecture: A typical system includes sensing, connectivity, data processing, application, and management layers.
Interoperability: Devices using different vendors or networks require common protocols, data formats, APIs, and security mechanisms.
Cyber-physical behavior: IoT systems monitor physical processes and may influence them through actuators.

II. Future factory concepts — Intelligent and connected production

A. Future factory concepts

Future factories combine automation, industrial data, artificial intelligence, robotics, and connected machinery to create flexible production systems. The aim is to move from fixed, reactive manufacturing toward adaptive and predictive operations.

Cyber-physical production: Machines, sensors, software, and human operators exchange real-time information about production status.
Digital twin: A virtual representation of a machine or process is updated using sensor data; it can support simulation, maintenance, and optimization.
Flexible manufacturing: Networked robots and programmable equipment can switch between products with limited reconfiguration.
Predictive maintenance: Vibration, temperature, and current measurements help estimate failure before breakdown. A rising motor vibration trend can trigger planned maintenance.
Human-machine collaboration: Operators work with collaborative robots, wearable displays, and decision-support systems rather than being fully removed from production.
Key limitation: Connectivity increases the attack surface, so authentication, segmentation, patching, and safety controls are essential.

III. Smart objects — Physical things with digital behavior

A. Smart objects

A smart object is a physical entity enhanced with sensing, processing, communication, identification, and sometimes actuation capabilities. Its intelligence arises from the combination of hardware, software, and network access.

Identification: An RFID tag, MAC address, serial number, or IPv6 address distinguishes the object.
Sensing: Temperature, light, pressure, location, motion, or chemical sensors convert physical conditions into data.
Processing: A microcontroller filters readings, applies thresholds, or executes local control logic.
Communication: Technologies such as Bluetooth Low Energy, Wi-Fi, NFC, or LPWAN carry data to another device or service.
Actuation: A relay, motor, valve, or display enables the object to affect its environment.
Context awareness: A smart object interprets data in relation to time, location, or surrounding devices; a thermostat can adjust heating when occupancy and temperature conditions coincide.

IV. Smart applications — Services built from connected data

A. Smart applications

Smart applications use data from connected objects to deliver automated, context-sensitive, and user-oriented services. They generally combine device data, analytics, rules, and an interface.

Observation: Dashboards present measurements such as room temperature, machine status, or patient heart rate.
Automation: Rules convert events into actions: “if soil moisture is below a threshold, activate irrigation.”
Analytics: Historical data can reveal trends, anomalies, correlations, and predicted outcomes.
Service integration: APIs connect IoT data with enterprise systems such as inventory, billing, hospital records, or logistics.
User value: A smart application should reduce effort or improve decisions, not merely display raw sensor readings.
Design requirement: Applications must handle missing data, false readings, latency, privacy, and different user permissions.

V. A protocol for constrained session initiation — CoAP-based interaction

A. A protocol for constrained session initiation

Constrained Application Protocol (CoAP) is a lightweight web-style protocol designed for constrained devices and low-power networks. It provides request-response communication similar to HTTP while reducing overhead.

Message model: CoAP commonly uses methods such as GET, POST, PUT, and DELETE to access resources.
Transport: It normally runs over UDP, reducing connection-management overhead; reliability can be requested with confirmable messages.
Resource addressing: A device may expose a resource such as /temperature or /valve.
Constrained session initiation: A client can discover a device, request a resource, and establish communication with minimal signaling.

Example exchange:

TEXT

  Client -> GET coap://sensor.local/temperature
  Server -> 2.05 Content: 24.6 C

Security: Datagram Transport Layer Security (DTLS) or newer object-security approaches protect confidentiality and authentication.
Limitation: UDP-based communication may require proxies or gateways when interacting with conventional HTTP services.

VI. Near-field communication — Very short-range interaction

A. Near-field communication

Near-field communication (NFC) is a short-range wireless technology operating at 13.56 MHz, generally over a distance of a few centimeters. It is useful when intentional proximity is part of the interaction.

Operating modes: NFC supports reader/writer communication, card emulation, and peer-to-peer exchange.
Passive tags: A tag can obtain power from the reader’s electromagnetic field, allowing inexpensive objects without batteries.
Applications: Contactless payments, access badges, product authentication, device pairing, and medical identification use NFC.
Security advantage: The short range makes accidental remote interception more difficult, although it does not guarantee security.
Data format: NFC Data Exchange Format (NDEF) stores records such as URLs, text, or application-specific data.
Limitation: NFC is unsuitable for continuous long-distance monitoring because range and data rate are limited.

VII. Narrowband IoT — Licensed cellular connectivity

A. Narrowband IoT

Narrowband IoT (NB-IoT) is a 3GPP cellular technology for low-power wide-area communication. It uses narrow bandwidth, strong coverage mechanisms, and operator-managed infrastructure for massive numbers of devices.

Coverage: Repetition and narrowband operation improve indoor and underground reach, often described through enhanced coverage levels.
Energy use: Devices can use Power Saving Mode (PSM) and extended Discontinuous Reception (eDRX) to remain unreachable or inactive for long periods.
Traffic pattern: NB-IoT suits small, infrequent messages such as meter readings, alarms, and status updates.
Deployment: It operates in licensed cellular spectrum, providing managed interference and SIM/eSIM-based authentication.
Limitations: Latency can be high for sleeping devices, and mobility support is more limited than in ordinary broadband cellular services.
Example: A water meter may transmit daily consumption and immediately send an exception alert when leakage is detected.

VIII. Sigfox — Ultra-narrowband low-power networking

A. Sigfox

Sigfox is a low-power wide-area network approach designed for very small, infrequent IoT messages. It uses ultra-narrowband radio and a public operator network.

Message size: Traditional Sigfox uplink messages are limited to 12 bytes, while downlink capacity is more restricted.
Energy model: Short transmissions and long sleep periods support multi-year battery operation in suitable deployments.
Applications: Asset tracking, environmental sensing, utility monitoring, and simple alarms fit its low-data-rate model.
Coverage principle: End devices transmit to nearby base stations, which forward messages to a cloud backend.
Comparison: NB-IoT offers stronger two-way cellular integration and larger capability; Sigfox can be simpler and highly economical for tiny payloads.
Limitation: Small payloads, restricted downlink, operator dependence, and limited real-time control make Sigfox unsuitable for video, voice, or complex actuation.

IX. Introduction to Industrial IoT — IoT for operational systems

A. Introduction to Industrial IoT

Industrial Internet of Things (IIoT) applies IoT technologies to factories, energy systems, transportation, utilities, and other operational environments. It connects industrial assets to improve performance, safety, quality, and resilience.

Operational focus: IIoT measures production variables such as pressure, flow, speed, energy consumption, and equipment health.
Business outcomes: Common outcomes include reduced unplanned downtime, improved output quality, and optimized energy consumption.
Edge computing: Data may be processed near the machine to reduce latency and preserve operation during cloud disconnection.
IT-OT convergence: Information technology systems manage data and business processes, while operational technology controls physical equipment.
Critical requirement: Availability, deterministic timing, safety, and integrity may be more important than simple data volume.

X. History of Industrial IoT — From automation to connected intelligence

A. History of Industrial IoT

The history of IIoT reflects the gradual integration of industrial control, networking, computing, and cloud analytics. Each stage increased connectivity and the amount of usable operational data.

First industrial control: Mechanical systems and relay logic provided local automation before widespread digital computing.
Programmable control: Programmable Logic Controllers (PLCs), introduced in the late 1960s, replaced extensive hard-wired relay systems.
Supervisory systems: SCADA systems enabled centralized monitoring and control of geographically distributed assets.
Networked automation: Industrial Ethernet, fieldbuses, and protocols such as Modbus connected controllers, instruments, and supervisory systems.
Modern IIoT: Cloud platforms, edge computing, machine learning, IPv6, and mobile access expanded industrial data use during the 2010s and afterward.
Historical tension: Legacy equipment prioritizes reliability and long service life, whereas modern systems demand openness, remote access, and rapid analytics.

XI. Components of Industrial IoT — The operational architecture

A. Components of Industrial IoT

An IIoT system consists of physical assets, data acquisition, communication, computing, applications, and security controls. Reliable value depends on coordination across all components.

Devices and sensors: Transmitters, cameras, encoders, and vibration sensors measure process conditions.
Actuators and controllers: Motors, valves, PLCs, and Distributed Control Systems convert decisions into physical action.
Gateways: Industrial gateways translate protocols, aggregate data, buffer messages, and enforce local security.
Networks: Ethernet, Wi-Fi, private cellular, industrial fieldbus, and LPWAN provide different latency, range, and reliability characteristics.
Platforms: Edge and cloud platforms store time-series data, manage devices, and run analytics.
Applications: Maintenance, quality control, asset tracking, digital twins, and energy management consume processed data.
Security layer: Identity management, encryption, network segmentation, logging, and secure updates protect both information and physical processes.

XII. Brownfield Internet of Things — Connecting existing infrastructure

A. Brownfield Internet of Things

Brownfield IoT modernizes existing plants, machines, and infrastructure rather than replacing them with new connected equipment. It is valuable because industrial assets may remain productive for decades.

Retrofitting: External sensors, gateway modules, or protocol adapters collect data from older machinery.
Non-invasive monitoring: A vibration sensor can be attached to a motor without changing its original controller.
Protocol conversion: Gateways may translate Modbus, OPC UA, CAN, or proprietary formats into MQTT or an industrial data platform.
Economic advantage: Existing capital equipment is preserved while maintenance and monitoring improve.
Integration risk: Old systems may lack encryption, authentication, documentation, or processing capacity.
Implementation principle: Begin with a measurable use case, isolate legacy networks, validate sensor accuracy, and expand after operational benefits are demonstrated.

XIII. Internet of Things in agriculture — Data-driven farming

A. Internet of Things in agriculture

IoT in agriculture uses connected sensors, equipment, satellites, and analytics to manage crops, livestock, water, and farm operations with greater precision.

Field sensing: Soil-moisture probes, weather stations, leaf-wetness sensors, and nutrient monitors provide localized measurements.
Precision irrigation: A controller can compare soil moisture with a configured threshold and operate a valve only where water is needed.
Livestock monitoring: Wearables and location devices help identify movement changes, illness, estrus, or animals outside a permitted area.
Equipment management: GPS, fuel sensors, and telemetry support route planning, machine utilization, and predictive maintenance.
Connectivity challenge: Rural locations may require LoRaWAN, NB-IoT, satellite, or store-and-forward gateways.
Value and limitation: IoT can reduce water and chemical use, but sensor calibration, harsh weather, battery life, and fragmented connectivity affect results.

XIV. Internet of Things in healthcare — Connected care and monitoring

A. Internet of Things in healthcare

IoT in healthcare connects medical devices, patients, clinicians, facilities, and information systems to support monitoring, diagnosis, treatment, and resource management.

Remote patient monitoring: Wearables and home devices measure blood pressure, glucose, oxygen saturation, temperature, or heart rate.
Clinical alerts: A system can compare a measurement with an individualized threshold and notify clinical staff when intervention may be required.
Medical asset tracking: RFID, Bluetooth beacons, and gateways locate infusion pumps, wheelchairs, or ventilators and reduce search time.
Smart facilities: Connected beds, temperature sensors, and environmental monitors improve occupancy management, infection control, and equipment conditions.
Interoperability: Healthcare devices must exchange usable information with Electronic Health Record systems through suitable standards and interfaces.
Safety and privacy: Patient identity, consent, encryption, access control, audit trails, and dependable fail-safe behavior are essential because incorrect data or delayed alerts can directly harm patients.