COSC111 Midterm Reviewer PDF

**COSC111 Midterm Reviewer** **Lesson 1: Introduction to IoT** **Internet of Things (IoT)** \- network of physical objects or \"things\" embedded with sensors, software, and other technologies \- network of interconnected devices that communicate with each other over the internet **Components o...

**COSC111 Midterm Reviewer** **Lesson 1: Introduction to IoT** **Internet of Things (IoT)** \- network of physical objects or \"things\" embedded with sensors, software, and other technologies \- network of interconnected devices that communicate with each other over the internet **Components of IoT** **1. Sensors/Devices** \- collect data from environment \- ex: temperature sensors, cameras, GPS trackers **2. Connectivity** \- transmits data to cloud services \- Wi-Fi, Bluetooth, cellular networks **3. Data Processing** \- analyzes collected data to extract meaningful information **4. User Interface** \- allows users to interact with the IoT system **Architecture of IoT:** **Perception Layer**: Comprises sensors and actuators that collect data. **Network Layer**: Responsible for transferring data from the perception layer to processing systems. **Processing Layer**: AKA the middleware layer; processes the data and makes decisions based on analysis. **Application Layer**: Provides the specific application-oriented services to users. **Communication Protocols** \- used in IoT systems to facilitate interaction between devices and the internet \- examples: - **MQTT** (Message Queuing Telemetry Transport) - **HTTP/HTTPS** - **CoAP** (Constrained Application Protocol) - **Zigbee** **History and Evolution of IoT** **Early Beginnings** \- early 1980s \- modified Coca-Cola vending machine at Carnegie Mellon University, which reported its inventory and whether drinks were cold. **1990s** \- the term \"Internet of Things\" was coined by Kevin Ashton in 1999; described a system where the internet would be connected to the physical world via ubiquitous sensors. **2000s** \- advancements in wireless communication technologies \- ex: Wi-Fi and RFID (Radio-Frequency Identification) **2010s and Beyond** \- rapid growth of smartphone usage and cloud computing \- smart home devices like Amazon Echo and Google Home **IoT Applications and Market Trends** **1. Smart Homes** \- smart thermostats (ex: Nest), smart lights (ex: Philips Hue), smart security cameras (ex: Ring), and voice-activated assistants (ex: Amazon Alexa, Google Assistant) **2. Healthcare** \- wearable fitness trackers (ex: Fitbit), smart medical devices (ex: connected inhalers, heart monitors), and remote patient monitoring systems **3. Industrial IoT (IIoT)** \- predictive maintenance of machinery, real-time monitoring of industrial processes, supply chain optimization, and inventory management **4. Agriculture** \- precision farming, including soil moisture sensors, automated irrigation systems, and livestock monitoring. **5. Smart Cities** \- enhance urban infrastructure \- smart traffic management systems, smart parking solutions, waste management, and energy-efficient buildings **6. Market Trends** \- key trends include integration of AI and machine learning with IoT, edge computing for faster data processing **Benefits of IoT** Improved Efficiency Enhanced Data Collection Convenience Improved Safety and Security Innovation **Challenges of IoT** Security Risks Privacy Concerns Interoperability Scalability Cost **Lesson 2: IoT Architecture and Design Principles** **Basic Architecture of IoT Systems** \- typically divided into three layers: **1. Perception Layer (Device Layer)** \- includes all physical devices such as sensors and actuators that interact with the environment **2. Network Layer** \- responsible for transmitting data from the perception layer to the processing systems and back to the devices \- ex: Wi-Fi or cellular networks that transmit data from the sensor to the cloud **3. Application Layer** \- where the data is processed and utilized to perform specific tasks \- ex: a mobile app that allows users to control the smart thermostat remotely **IoT Reference Models (4-layer, 7-layer models)** **A. Four Layer Model** 1. **Perception Layer** - sensing and actuating components 2. **Network Layer** - communication protocols and network hardware 3. **Middleware Layer** - data management, storage, and processing 4. **Application Layer** - end-user applications and services **B. Seven Layer Model (Based on the OSI Model)** 1. **Perception Layer** - sensing and actuating components 2. **Network Layer** - communication protocols (e.g., TCP/IP) 3. **Data Link Layer** - manages data transfer and error detection 4. **Transport Layer** - ensures reliable data transmission 5. **Session Layer** -- manages sessions and data exchange 6. **Presentation Layer** - data formatting and encryption 7. **Application Layer** - user-facing applications and services **Key Components in IoT Systems** **1. Sensors** \- devices that detect and measure physical phenomena \- ex: pressure sensor in a smart irrigation system that measures soil moisture levels **2. Actuators** \- devices that perform actions based on commands received from system \- ex: valve in the smart irrigation system that opens or closes based on the moisture level **3. Microcontrollers** \- small computing devices that process sensor data and control actuators \- ex: Arduino board **4. Communication Protocols** \- standards and rules that define how data is transmitted between devices \- ex: **MQTT (Message Queuing Telemetry Transport)** - a lightweight protocol used in IoT for efficient data transmission, especially in environments with low bandwidth **Example Smart Agriculture System** **Perception Layer** - Soil moisture sensors and temperature sensors measure environmental data. **Network Layer** - LoRaWAN (Long Range Wide Area Network) transmits sensor data to a central hub. **Middleware Layer** - A cloud platform processes the data, storing historical trends and triggering actions. **Application Layer** - A mobile app displays real-time soil moisture levels and allows farmers to automate irrigation. **Lesson 3: Sensors and Actuators** **Sensors** \- devices that detect and measure physical properties from the environment **Types of Sensors** **1. Temperature Sensors** \- measure temperature using thermocouples, thermistors, or resistance temperature detectors (RTDs) \- ex: **DS18B20**, a digital temperature sensor - use a thermistor to measure temperature - the thermistor changes its resistance with temperature **2. Humidity Sensors** \- detect amount of water vapor in the air \- capacitive or resistive methods are often used \- ex: **DHT11**, a sensor that measures both humidity and temperature - based on changes in electrical capacitance when humidity levels fluctuate - contains moisture-absorbing substrate that changes capacitance based on water vapor **3. Motion Sensors** \- detect movement with technologies like infrared, ultrasonic, or accelerometers \- ex: **PIR (Passive Infrared) sensors** detect human movement by sensing changes in infrared radiation - detect changes in infrared radiation in their surroundings - when a warm object (like a human) passes, the sensor detects this change and triggers an output **4. Light Sensors** \- measure intensity of light using photodiodes or **light-dependent resistors (LDRs)** \- ex: LDR changes its resistance based on the intensity of light falling on it - resistance of an LDR decreases as light intensity increases **5. Proximity Sensors** \- detect nearby objects without physical contact using ultrasonic or infrared. \- ex: **HC-SR04**, an ultrasonic sensor **Actuators** \- convert electrical signals into physical actions (motion, heat, etc.) \- enable system to interact with the physical world. **Types of Actuators** **1. Motors (DC/Stepper Motors)** \- convert electrical energy into mechanical motion. \- ex: **DC motor** rotates when voltage is applied to it - current passes through a wire coil inside the motor, generating a magnetic field. **2. Servos** \- offer precise control of angular position, commonly used in robotics and automation \- ex: **Servo motor** is controlled by Pulse Width Modulation (PWM), allowing it to move to a specific angle - uses an electromagnetic coil to move a plunger inside, creating linear motion **3. Solenoids** \- electromagnetic devices that convert electrical signals into linear motion \- often used for pushing or pulling actions in locks - controlled by sending a PWM signal to rotate the motor to a specific angle **Lesson 4: Microcontrollers and IoT Platforms** **Microcontrollers** \- small computing devices designed to perform specific tasks in embedded systems \- can interface with sensors, control actuators, and communicate with other devices via the internet. **Popular Microcontrollers Used in IoT** **Arduino** \- widely used open-source microcontroller platform; known for its simplicity and ease of use **Raspberry Pi** \- often used as a microcontroller in IoT applications; technically a single-board computer \- more powerful than typical microcontrollers \- runs a full operating system like Linux **ESP8266** \- low-cost microcontroller with built-in Wi-Fi capability \- widely used in IoT projects where internet connectivity is essential **ESP32** \- successor to the ESP8266 \- offers more power, dual-core processors, Bluetooth, and additional GPIO pins \- ideal for IoT projects that require both Wi-Fi and Bluetooth communication **Lesson 5: IoT Communication Protocols** **IoT communication protocols** \- essential for connecting devices and enabling data exchange between them and the cloud or other IoT systems \- different protocols are used based on the requirements like power consumption, bandwidth, and range. **Widely Used IoT Communication Protocols** **1. MQTT (Message Queuing Telemetry Transport)** \- lightweight publish/subscribe messaging protocol; ideal for low-bandwidth and high-latency networks \- commonly used in remote monitoring applications **2. CoAP (Constrained Application Protocol)** \- specialized web transfer protocol designed for resource-constrained devices in IoT systems \- similar to HTTP but optimized for low-power devices; supports methods like GET, POST, PUT, and DELETE **3. HTTP (HyperText Transfer Protocol)** \- widely used application layer protocol for sending data over the web **4. WebSockets** \- provide full-duplex communication between a client and server; enables real-time data exchange \- ideal for IoT systems requiring continuous communication **Wireless Communication Technologies** \- enable devices to connect without physical cables **1. WiFi** - high-speed communication for devices that are near a WiFi router **2. Bluetooth** - short-range, low-power communication protocol; often used for personal devices like wearables and smart home appliances. **3. Zigbee** - low-power, low-data-rate **4. LoRa (Long Range)** - long-range, low-power technology; used for IoT systems that require communication over large distances **Lesson 6: Networking Technologies for IoT** **Network topology** \- the arrangement of different elements (links, nodes, etc.) in a network. **Network Topologies in IoT** **Star Topology** - each node connects to a central hub; often used in home automation systems where all devices connect to a WiFi router **Mesh Topology** - each node connects to multiple other nodes, allowing for redundancy and extended range; useful in larger areas **IPv6** \- latest version of the Internet Protocol \- crucial for IoT due to its vast address space, which can support billions of devices **Low-Power WAN (LPWAN)** \- designed for long-range communication with low power consumption \- ideal for IoT devices that require long battery life **Lesson 7: IoT Data Management and Storage** **IoT Data Management and Storage** \- processes and technologies involved in collecting, storing, processing, and analyzing the vast amounts of data generated by IoT devices **Data Generation** - occurs when devices collect data from their environment or from user interactions; can include metrics like temperature, humidity, location, or user activity **Data Collection Process** - involves transmitting the information to a central system for further analysis or action **Examples:** **Smart Home Devices** - A smart thermostat collects temperature and humidity data to optimize heating and cooling based on user preferences and external weather conditions. **Wearable Health Monitors** - Fitness trackers generate data on heart rate, steps taken, and sleep patterns, which is then collected and sent to a mobile app for user insights. **Industrial IoT Sensors** - In a manufacturing environment, sensors on machinery monitor performance, wear and tear, and environmental conditions, generating data that can be used for predictive maintenance. **Cloud Storage Solutions** \- provide scalable and flexible environments for storing and managing IoT data \- can handle large volumes of data generated by numerous devices; support advanced analytics and machine learning **Examples of Cloud Storage** **Amazon Web Services (AWS) IoT Core** \- enables the connection of IoT devices to the cloud, allowing secure data transmission and storage in Amazon S3 (Simple Storage Service) for later analysis **Microsoft Azure IoT Hub** \- provides cloud storage and management capabilities for IoT data, allowing developers to build, connect, and manage IoT applications effectively **Google Cloud IoT** \- offers tools for ingesting, processing, and analyzing IoT data **Edge Computing** \- processing data near the source of generation (i.e., at the \"edge\" of the network) rather than relying on a centralized cloud \- reduces latency, conserves bandwidth, and allows for real-time data processing **Cloud Computing** \- sending data to centralized servers for processing and storage \- can be beneficial for extensive data analytics and historical data storage but may introduce delays due to network latency **Lesson 8: IoT Analytics and Data Processing** **IoT Analytics** \- techniques and methods used to analyze data generated from IoT devices. \- ex: - **Smart Homes**: Analyzing energy consumption data from smart thermostats to optimize heating and cooling, thus reducing energy costs. - **Wearable Devices**: Collecting and analyzing health metrics (like heart rate and activity levels) to provide personalized health recommendations. - **Smart Cities**: Analyzing traffic data from connected vehicles and sensors to improve traffic management and reduce congestion. **Data Processing Techniques for IoT** \- manage and analyze the large volumes of data generated \- **key techniques** include: **Data Filtering** - removing unnecessary data points before analysis **Data Aggregation** - combining data from multiple sources to provide a unified view **Data Transformation** - modifying data into a format suitable for analysis **Machine Learning** - applying algorithms to discover patterns and make predictions based on IoT data **Real-time Processing** \- analyzing data as it is generated, allowing for immediate insights and actions \- for applications requiring instant responses. **Batch Processing** \- collecting data over a period, then processing it all at once \- for applications where immediate responses are not necessary **Lesson 9: IoT Security and Privacy** **IoT Security** \- focuses on protecting IoT devices and their networks from malicious attacks, unauthorized access, and data breaches **Privacy** \- ensuring that personal data collected by IoT devices is protected and handled according to relevant laws and user consent **Security Challenges in IoT** Lack of standardization Resource constraints Connectivity Lifecycle management Data management **Common Threats and Vulnerabilities** **1. Unauthorized access** \- hackers can gain control over IoT devices, often due to weak authentication mechanisms, leading to data breaches or device manipulation **2. Distributed Denial-of-Service (DDoS) attacks** \- malicious actors can target IoT devices to launch DDoS attacks, overloading systems and causing network outages \- ex: **Mirai botnet**, which used IoT devices like security cameras to perform large-scale DDoS attacks **3. Data interception and leakage** \- sensitive data transferred between IoT devices and servers can be intercepted if not properly encrypted **4. Malware and botnets** \- vulnerable IoT devices can be infected with malware, turning them into part of a botnet to execute malicious actions **5. Firmware vulnerabilities** \- exploiting weaknesses in IoT firmware can allow attackers to execute arbitrary code, gaining control over devices **Security Protocols and Best Practices** **Encryption** \- encrypting data at rest and in transit ensures that even if intercepted, the data remains unreadable \- ex: using **TLS (Transport Layer Security)** for encrypting communication between IoT devices and servers **Authentication and Access Control** \- strong authentication mechanisms, such as **multi-factor authentication (MFA)**, help prevent unauthorized access to IoT devices and networks **Regular Updates and Patching** \- IoT devices should receive frequent software and firmware updates to patch known vulnerabilities **Network Segmentation** \- isolating IoT devices from other critical parts of a network reduces the risk of lateral movement if one device is compromised **Secure Booting** \- ensuring that IoT devices only run authenticated and trusted code during startup **Device Hardening** \- deactivating unused features, changing default credentials, and applying minimal necessary configurations reduce vulnerabilities **Data Anonymization** \- if personal data is collected, it should be anonymized or pseudonymized to protect user privacy **Addtl:** **Components of Arduino Kit** **Arduino Board** \- the core of the kit \- microcontroller board (often an Arduino Uno) used to control electronic components \- can be programmed to read inputs and control outputs by executing the code uploaded to it  **1**. Power USB **2**. Power (Barrel Jack) **3**. Voltage Regulator - controls voltage given to the Arduino board; stabilizes the DC voltages **4**. Crystal Oscillator - helps Arduino in dealing with time issues **5, 17**. Arduino Reset **6, 7, 8, 9**. Pins (3.3, 5, GND, Vin) Vin - used to power the Arduino board from an external power source **10**. Analog pins **11**. Main microcontroller **12**. ICSP pin - AKA SPI (Serial Peripheral Interface); programming header for the Arduino **13**. Power LED indicator **14**. TX and RX LEDs **15**. Digital I/O **16**. AREF - Analog Reference; used to set an external reference voltage for the analog input pins