Fundamentals of IoT

Brief Bio of Instructor

• Vidya NL holds a B.E. and M.Tech in Computer Science and Engineering
• They teaches at NIE, Mysore with 5 years of teaching experience
• Expertise includes IoT systems, Operating Systems, and Big-data analytics
• Research papers have been published on IoT, AI, ML, Teaching, and Learning

Learning Objectives

• Understand the fundamentals of IoT
• Analyze the role of data, data analytics, and IoT endpoints in IT and OT
• Assess the impact of IoT in the real world

Course Outcomes

• Understand IoT concepts, physical/logical design, enabling tech, and deployment strategies
• Outline the role of smart objects, sensors, actuators, M2M communication, and IoT system management
• Apply IoT platform design methodology using Python for data processing and automation
• Apply IoT physical device knowledge, such as Arduino and Raspberry Pi, for real-world application design in home automation, smart cities, and agriculture
• Analyze IoT data analytics techniques, challenges, and security measures 

Introduction to IoT

• IoT comprises unique things connected to the internet
• Limited to connecting devices, appliances, and machines to allow communication and data exchange
• A vast global network of connected servers, computers, tablets, and mobiles is governed by standard protocols

Thing

• A physical entity or device, such as sensors, actuators, computing devices, routers, gateways, PCs, laptops, or mobiles
• Dynamic, and self-adapting
• Self-configuring to allow devices to work together to provide functionality
• Able to use communication protocols for interconnectivity
• Having a unique identity with a unique identifier like an IP address
• Integrates into an information network to enable communication and data exchange

Definitions of IoT

• Self-configuring global network with communication protocols for physical and virtual items to have identities
• Attributes and personalities use interfaces integrated into a network for user and environmental data communication
• A system of interrelated computing devices with unique identifiers able to transfer data over a network without human interaction

IoT Architectures

• Architectural standards and frameworks have faced challenges in designing massive IoT networks
• Architectures support data, processes, and endpoint device functions
• Well-known architectures are oneM2M and IoT World Forum (IoTWF)
• The rapid growth of machine-to-machine (M2M) prompted ETSI to create the M2M Technical Committee in 2008, releasing the oneM2M IoT Standardized Architecture in 2012
• The IoTWF architectural committee released a seven-layer IoT model with edge computing, data storage, and access in 2014

OneM2M Standardized Architecture Layers

• Major attention is given to connectivity between them
• Horizontal framework of applications includes the physical network, management protocols, and hardware
• A communications domain for devices and endpoints, with wireless technologies (IEEE 802.15.4) and wireless point-to-multipoint systems (IEEE 801.11ah)

IoT World Forum (IoTWF) Standardized Architecture

• Levels with control from a central location to the edge (sensors, devices, machines)
• Data travels up the stack from the edge to the center
• The IoT model decomposes into parts, identifies different technologies at each layer, and defines a system that can be provided by different vendors
• Has interfaces that lead to interoperability
• Has a tiered security model that is enforced at transition points between levels
• Layer 1 is the physical devices and controllers layer for sensors and various endpoints
• "Things" range from microscopic sensors to giant machines
• Generates data that is queried or controlled over a network. 
• Layer 2 is Connectivity for communications between devices
• The 2nd Connectivity Layer gives reliable information delivery across the network and switching
• Layer 3 is Edge Computing layer for filtration of data to reduce processing traffic

Upper Layers 4-7 of IoTWF Model

• Deals with data handling and processing
• Layer 4, the Data Accumulation Layer, captures data, stores data, converts data, and stores for applications
• Layer 5, the Data Abstraction Layer, ensures semantics consistency, confirms data completeness and consolidates sources
• Layer 6, Application Layer, interprets data via software supporting monitoring, control, and reports
• Layer 7, the Collaboration and Processes Layer, consumes and shares application information, enabling useful process changes

Simplified IoT architecture Framework

• Interconnection of IoT endpoint devices to a network transporting data for use by applications in data centers, clouds, or management points
• It separates IoT core, data management into segments for studying functions in complex IoT systems

Sensors

• Measures physical quantity and converts that measurement reading into a digital representation
• The reading is transferred to another device for transformation

Classification Based on Input

• Passive sensors cannot independently sense the input
• Active sensors independently sense the input
• Examples of passive sensors: Accelerometer, Soil moisture, Water level and Temperature sensor. 
• Examples of active sensors: Radar, sounder and Laser altimeter Sensor.

Classification Based on Output

• Analog sensors have output a continuous function of input parameters
• Digital sensors have output in a binary nature, also comprising bit conversion electronics
• Example of analog sensor: Temperature sensor, LDR, analog pressure sensor.
• Example of digital sensors: Passive Infrared Sensor and Digital Temperature Sensor (DS1620).

Classification Based on Data Type

• Vector sensors response depends on the magnitude of the direction and orientation of input parameters
• Scalar sensors detects the input only based on its magnitude
• Example of vector sensor: Accelerometer, gyroscope, magnetic field, motion detector sensors
• Example of scarlor sensors: Temperature, gas, strain, color and smoke sensor

Sensor Grouping

• Active sensors produce an output of energy
• Passive sensors receive energy only
• Invasive sensors are part of the environment measured
• Non-invasive sensors are external to the measured environment
• Contact sensors require contact, while no-contact sensors do not require contact
• Absolute sensors measure on an absolute scale
• Relative sensors measure based on a fixed or variable reference value
• Sensors are categorized based on their specific industry/vertical application

Additional Methods of Categorization

• Physical mechanisms used by sensors
• Applications and measured physical variables

Types of Sensors: Proximity

• Detects presence/absence of objects using inductive, capacitive, ultrasonic, or infrared tech
• Inductive detects objects with metal
• Capacitive detects objects of metal, liquids, water, resin and other non-metallics
• Ultrasonic measures distance, liquid levels using sound waves
• Infrared detects heat radiation

Examples of Proximity Sensors

• Omron E2E-X3D1 with inductive Detection for metal detection in conveyor systems
• Baumer IFRM 08P15A3/S35L capacitive for liquid level detection
• HC-SR04 ultrasonic for car parking assistance
• Sharp GP2Y0A21YK Infrared for touchless hand sanitizer
• Ensure components are correctly positioned before the assembly process begins

Proximity Sensor Applications

• Inductive sensors detect position of metal parts in automated robotic arms
• Proximity sensors start/stop conveyor belts when luggage is present
• Capacitive sensors verify liquid levels
• Proximity sensors count/verify sealing of products
• Detection of animals or obstacles in path of irrigation systems

Types of Sensors: Photoelectric

• Light is detected or its absence
• Uses a light transmitter and a photoelectric receiver

Types of Photoelectric Sensors

• Through-beam: Light goes directly to receiver
• Retro-reflective: Light is reflected from an object back to the receiver
• Diffuse: Object reflects light
• In industrial automation, they can be used to detect positions of item

Applications of Photoelectric Sensors

• Detect object orientation on prodution line
• Used in automotive, food, transport and material handling industries
• Detects a wide array of materials, including glass, plastics and metal

Classification of Temperature Sensors

• Contact temperature sensors measure hotness/coolness through direct contact (thermocouples, thermistors, RTD)
• Non-contact temperature sensors measure hotness/coolness through emitted radiation (infrared temperature sensor)

Temperature Sensor Applications

• Instrumentation measures heat with thermocouples
• Industrial furnaces/boilers, automotive exhaust, food processing and appliances
• Digital thermometers, HVAC systems
• Measure temps with thermistors-Medical devices plus battery monitoring

Resistance Temperature Detectors

• Made of pure metals like platinum with predictable resistance
• As temperature increases, the resistance increases predictably with PT100 RTDs with base resistance of 100 ohms at 0°C
• Used in industrial applications (chemical and pharmaceutical) and precision measurement

Infrared Temperature Sensors

• Identify infrared radiation
• Every item over zero emits radiation
• Radiation strength is key
• Used in night vision and screening

Position Sensors

• Detects an object's location with relative positioning, linear travel, and/or rotational angle in mind
• Linear Variable Differential Transformer (LVDT) measures linear displacement with a primary coil and two secondary coils and consists of movable ferromagnetic core
• Rotary encoders converts the angular position or motion of a shaft/axle to analog/digital output
• Absolute rotary encoder indicate the current shaft position
• Incremental encoder provides information about the motion of the shaft
• Rotary encoders are used in robotics and input devices
• Potentiometer measures position in lines, rotary
• A three-terminal resistor with a sliding or rotating contact that forms an adjustable voltage divider
• Used as volume controls or in joysticks

Pressure Sensors

• Measures pressure of liquid and gases using transducers
• A strain gauge pressure sensor applies pressure through use of a strain gauge to an item
• Piezoelectric Pressure Sensor measures highly dynamic pressure with materials such as quartz
• Capacitive Pressure sensors measures pressure using ceramic, metal or silicon diaphragms

Smart Sensors

• Has interfaces of electrical output with a ranging function
• Can be programmed/calibrated
• Sensors and Actuators used as intelligent components for systems
• Self-identifying

Smart Sensor Functions

• Measure various environment in electrical form such as temperature
• Monitors industrial applications
• Allows configuration

Smart Sensor Features

• Detects Position
• Non-top supervision
• Transmits data/converse to other electronics

Smart Sensor Block Diagram Components

• Sensing unit detects changes
• Has a conditioning unit for maintaining a signal
• Utilizes an Analog to Digital converter signal
• All functions and devices are built for constant use

Applications for Smart Sensors

• Monitor processes or environment: water, sound, and traffic
• Able to be measured, collected and transmited in industrial computing
• Can be simply monitored at all times

Essential Static Characteristics of Sensors

• Range: Minimum to maximum value that a sensor can measure
• Span: Difference between minimum and maximum values
• Error: Difference between the measurement result and the true value
• Accuracy: Measuring instrument's ability to provide results close to the true value

Static Characteristics Continued

• Sensitivity: Ratio of change in output to change in input
• Resolution: Smallest change in input that can be detected
• Hysteresis: Difference in sensor output when approaching the same value from different directions
• Linearity: How well the sensor's output follows a straight line
• Repeatability: Measurement is made with same input
• Reproducibility: Measurement made at the same and different places

Dynamic Characteristics

• The relation between output and input changes
• Differential equations express the system's response as differential equations
• If measured in a rapid way the value/relation will be different
• If measured gradually things change such as settling time, response time and fidelity
• Lag can occur when the data is slightly delayed or disrupted

Sensor Selection: Step 1

• Define application requirements and data to measure
• Environmental - temp, CO2, Weather
• Healthcare - Motion heart
• Industrial - Pressure
• Smart Home - Motion security

Sensor Selection: Steps 2, 3 and

• Identify all environmental and operational Factors
• What protocols need to be supported
• Does the instrument need to be wired
• Power Consumtion - does this have a major role

Further Compatibility Check

• Confirm compatability with the desired sensor libraries and cloud platforms

Sensor Selection: Final

• Consider all cost factors when building a project
• Build projects starting with use cases like DHT then scale industrial
• Is the sensor the right choice
• Build around and test with the right sensor

Scenario

• A homeowner needs unauthorized entry and monitors indoor air quality.
• Identify proper sensors for communication and qualitys