Introduction to Embedded Systems

• This resource is about embedded systems and the basics to understand them

Objectives of the Lesson

• Students will understand the fundamentals and basic concepts of embedded systems
• Students will learn the components of embedded systems
• Students will learn the different applications of embedded systems

Defining Embedded Systems

• An embedded system is a computer system designed to perform specific functions within a larger mechanical or electrical system
• They are integrated into larger devices or products to control and monitor the operation of the device or system
• Embedded systems combine hardware and software to perform specific function(s)
• Embedded systems are typically small, low-cost, and low-power
• Embedded systems are used in real-time applications.

Applications of Embedded Systems - Examples

• Digital Cameras
• Smart Phones
• Smart Televisions
• Washing Machines
• Microwave Ovens
• Garmin GPS
• Electrocardiogram (ECG) Monitor
• Pacemakers

Microcontrollers

• A microcontroller is a small computer on a single integrated circuit (IC) designed to perform specific tasks and control electronic systems
• Microcontrollers consist of a CPU, memory, and input/output peripherals, which are all integrated onto a single chip
• Microcontrollers are utilized in computer systems designed for specific applications or tasks
• They are used in a wide spectrum of devices, including consumer electronics, automotive systems, medical devices, and industrial control systems

Microcontrollers vs. Microprocessors

• A microcontroller has all the essential components of a computer system integrated onto a single chip
• A microprocessor is a CPU that requires external components such as memory and I/O devices to function

Comparing Microcontrollers (MCU) and Microprocessors (MPU)

• Integration: MCUs have CPU, memory, and peripherals integrated, whereas MPUs only have the CPU on the chip and require external memory and I/O
• Functionality: MCUs are designed for specific control tasks in embedded systems, while MPUs are designed for general-purpose computing
• Complexity: MCUs are simple, compact, and cost-effective, while MPUs are more complex and require additional components
• Power Consumption: MCUs have low power consumption, making them ideal for battery-powered devices, while MPUs have higher power consumption
• Speed and Performance: MCUs have lower speed and are optimized for real-time control, while MPUs have higher speed and are optimized for complex computations
• Memory: MCUs use limited internal RAM, ROM/Flash, whereas MPUs use external RAM, ROM, and external I/O
• Cost: MCUs have low cost due to integrated components, whereas MPUs have higher cost due to external components
• Applications: MCUs are used in embedded systems like washing machines, cameras, and IoT devices, and MPUs are used in computers, smartphones, servers, and tablets

Scenarios of Microcontrollers vs. Microprocessors

• Home Automation System: MCU is preferred for compact, low-power, and dedicated functionality
• Personal Computer: MPU is preferred for versatility, high performance, and support for complex tasks
• Wearable Health Monitor: MCU is preferred for long battery life, real-time control, and compact design
• Server Infrastructure: MPU is preferred for high processing power and multitasking capability
• Automotive Control Systems: MCU is preferred for reliability, low power, and design for specific tasks
• Gaming Console: MPU is preferred for high speed, complex computations, and large memory support
• Industrial Automation: MCU is preferred for being cost-effective and simple in design for specific applications.
• Cloud Computing: MPU is preferred for scalability, external memory support, and multitasking

Applications of Embedded Systems

• Traffic management
• Industrial Automation
• Location Mapping
• Medical Care
• Consumer Electronics
• Building Management Systems

Analog vs Digital Signals

• Analog signals transition smoothly over time, e.g. like a Sine wave
• Digital signals are square waves

Implications of Conversion on Signal Integrity

• Noise and Distortion: Analog signals can be affected by noise and distortion during transmission, so these issues can degrade the quality of the digital signal unless adequately filtered or conditioned before conversion.
• Quantization Error: The quantization process introduces errors because the continuous analog signal is approximated to discrete levels, affecting the accuracy and integrity of the digital signal

Implications on System Performance in Real-Time Applications

• Processing Speed: The efficiency of an embedded system in converting and processing signals can impact its performance; high-speed ADCs and optimized algorithms are necessary for real-time applications
• Latency: The conversion process can introduce latency, and delays can lead to performance degradation or system instability in applications requiring immediate feedback
• Resource Constraints: Embedded systems often operate under constraints such as limited processing power, memory, and energy resources, so efficient designs ensure the system performs optimally without these limits
• Reliability: The integrity of the signal used in decision-making is paramount in critical applications, and poor signal quality can lead to incorrect and dangerous outcomes

Block Diagram of Embedded Systems

• Sensor: The input to the embedded system is obtained from sensors that detect physical quantities, then convert into electrical / analog signals
• Analog-to-Digital Converter (ADC): Since electrical signals generated by the sensors are often in analog form, they need to be converted into digital format for digital systems to process
• Microcontroller: The microcontroller processes the digital data received from the ADC to perform computations, decision-making, and control algorithms based on programmed instructions
• Digital-to-Analog Converter (DAC): In certain applications, the output of the microcontroller needs to be converted back to analog form to drive analog devices or actuators
• Actuators: Actuators are the output devices that generate physical action or movement, so examples include motors, solenoids, and valves that convert electrical signals into mechanical motion

Definition of a Sensor

• Sensors detect physical quantity like pressure, force or electrical quantity like current or any other form of energy

Solenoids

• Actuators that use an electromagnet to create a force
• They typically open or close valves/move small objects
• They are often used in conjunction with electric motors to provide precise control of motion

Key Milestones and Developments in the History of Embedded System

• Early Development (1940-1960s):
  • The term "embedded system" was coined in the late 1960s by Jack Ganssle while working at IBM
  • Early systems developed to control specific tasks, such as radar systems (WWII)
  • ENIAC (Electronic Numerical Integrator and Computer), built during World War II, can be considered an early embedded system due to dedicated control system.
• Microcontrollers and the 8-bit Era (1970-1980s):
  • Microcontrollers integrate a microprocessor, memory, and I/O peripherals on a single chip to be smaller, cheaper, and more efficient
  • Intel's 4004 (1971) was one of the earliest microprocessors
  • Examples of 8-bit microcontrollers: Intel 8051 and Motorola 68HC11
• Rise of 16-bit and 32-bit Microcontrollers (1990-2000s):
  • This period witnessed more processing power capabilities with enhanced memory/ capabilities
  • Real-time operating systems (RTOS) adoption became more prevalent, enabling better multitasking, resource management, and improved system reliability
• Integration of Connectivity and Networking (2000s-Present):
  • Embedded systems began incorporating connectivity and networking features by using Wifi and ethernet
  • Internet of Things (IoT) gained traction: embedded systems connected and communicated with each other and the internet for smart homes, healthcare etc
• Advancements in Processing Power and AI (2010s-Present):
  • Embedded systems benefit from advancements in processing power via multicore processors and powerful GPUs
  • Artificial intelligence (AI) and machine learning (ML) techniques in embedded systems became more prevalent, enabling intelligent decision-making, computer vision, and natural language processing