Modern technology is built from layers that continuously interact with one another. At the physical level, electronic devices transform electrical signals into digital information. Digital logic turns that information into computation, while processors, memory and communication interfaces provide the machinery needed to execute instructions and move data. As these components become part of embedded systems, they begin to interact with the physical world through sensors, controllers, actuators and real-time software.
But computation does not exist in isolation. Operating systems coordinate hardware and software, firmware gives specialized machines their behaviour, and communication protocols allow independent systems to exchange information. At the same time, machine learning is moving beyond the cloud into edge and on-device systems, where models must operate within real constraints such as memory, processing power, latency and energy consumption.
PrajnaEdge explores these connections as one continuous technology landscape — and takes them beyond explanation. From computing foundations and embedded systems to intelligent machines and edge AI, ideas can be understood, experimented with, and eventually turned into technology that can be experienced in the real world.
Experiment with intelligence beyond the cloud.
Explore how neural networks learn representations from data before compression and deployment. Future experiments will allow adjusting learning parameters—such as learning rate, epoch counts, and batch sizes—to observe loss trajectories and decision boundaries.
Can this image classifier maintain its intelligence while becoming small enough for the edge?
Run a fully quantized INT8 image-classification model directly on embedded hardware.
Can this image classifier maintain its intelligence while becoming small enough for the edge?
Run a fully quantized INT8 image-classification model directly on embedded hardware.
This experiment investigates preparing a compact INT8 TensorFlow Lite model for direct inference on resource-constrained embedded hardware. The model uses the same CNN architecture as the Edge AI exploration, converted to a full INT8 representation to classify three classes: Apple, Banana, and Orange.
Explore the ideas, systems and connections that shape technology — choose any node to begin your journey.
Practical guides to embedded systems and engineering.
Deploying neural networks and intelligent decision loops on raw silicon targets.
The first software architecture of embedded systems.
We have spent chapters assembling the physical machine. We designed the silicon gates, configured the system clocks, wired up communication buses, and added watchdog monitors to protect the device from itself. The hardware is ready. But at this moment, the processor is silent. At power-on, it simply loads the reset vector, initializes the stack pointer, and waits.
Without software to orchestrate its behavior, a microcontroller is nothing more than expensive sand. The hardware provides the capability, but software must provide the purpose. How do we organize the instructions that bring this silicon to life?
When personal computers run software, they do so under the supervision of a massive operating system. But in early embedded systems, there were no operating systems. The software had to run directly on the 'bare metal' of the hardware.
The simplest possible software architecture is a sequence of direct instructions. We fetch a sensor value, perform a calculation, and write the output to a pin. But an embedded system cannot simply execute these instructions once and shut down; it must monitor and control its environment indefinitely. To achieve this, the entire program is wrapped in a loop that never ends:
This simple infinite loop — the super-loop — became the heartbeat of early embedded systems. It runs as fast as the processor can fetch instructions, executing the same sequence of tasks over and over.
In a basic device, the super-loop is elegant and short. But as products grow, the loop becomes the repository for every new feature. A single loop must now handle a multitude of tasks:
* Inputs: Check if a button is pressed; sample the ADC channel for temperature. * Logic: Run a filter on the ADC readings; calculate the next motor velocity. * Outputs: Write a new duty cycle value to the PWM timer; toggle status LEDs. * Communications: Check if a byte has arrived in the UART buffer; parse a CAN frame. * Diagnostics: Feed the watchdog timer; monitor the battery voltage.
Every single one of these tasks is placed inside the same while(1) block, executed sequentially, one after another.
It is tempting to view Bare Metal as a primitive, outdated architecture. But in engineering, simplicity is a feature, not a bug. Bare Metal was, and remains, an exceptionally powerful design choice for several reasons:
* Zero Overhead: There is no operating system scheduler taking up CPU cycles. Every clock cycle is dedicated to your application code. * Tiny Memory Footprint: A super-loop does not need task control blocks, stacks for each thread, or message queues. It runs entirely on a single system stack, preserving precious SRAM. * Total Predictability: Because tasks run in a fixed sequence, there are no unpredictable context switches or priority inversions. The path of execution is completely deterministic. * Easy Debugging: If the system halts, the call stack tells you exactly which instruction inside the loop caused the failure.
For millions of successful products — from digital thermometers and microwave ovens to automotive sensors — Bare Metal is not a compromise; it is the optimal engineering solution.
The vulnerability of a sequential loop is that it assumes every task is fast. In a super-loop, a delay in one task becomes a delay for the entire system. This is the 'Timing Wall'.
Consider what happens if we add a slow task, like reading an external temperature sensor over I2C. The sensor takes 10 milliseconds to perform a conversion. If the CPU spins in a blocking while-loop waiting for the I2C transfer to complete, the entire loop stops. During those 10 milliseconds, the buttons are not polled, the motor PWM is not updated, and serial bytes are missed. If a user presses a button during that window, the press is completely lost. The tasks are cooperatively linked: if one misbehaves, the timing of the entire device is destroyed.
Bare Metal is not simply 'no operating system.' It is a active architectural choice that forces the developer to become the scheduler. To keep the loop running smoothly, the engineer must write non-blocking code. Instead of waiting for a timer to expire, they poll a hardware flag. Instead of waiting for a UART transmission to finish, they write bytes to a software buffer and let interrupts handle the hardware registers.
This approach teaches fundamental embedded systems thinking. It forces the developer to understand the timing budget of every line of code, the bandwidth of the bus, and the cooperative relationship between hardware peripherals and CPU cycles.
We can observe Bare Metal super-loops running reliably in many everyday systems:
* Simple Sensor Nodes: A remote temperature transmitter reads an SPI sensor, formats a packet, transmits it via a sub-GHz radio, and enters a low-power sleep mode, repeating this sequence once per minute. * Digital Thermometers: The loop continuously samples an ADC channel connected to a thermistor, converts the readings to a temperature value using a lookup table, and updates a segment LCD driver. * Brushless Motor Controllers: A high-speed super-loop runs the field-oriented control (FOC) mathematical algorithms to adjust motor phase voltages at 20 kHz. Because the math must be completed in under 50 microseconds, there is no room for operating system overhead. * Battery Chargers: The controller loops continuously to check battery voltage, current, and temperature, adjusting the output buck converter's PWM duty cycle to maintain a safe charging curve.
For years, one loop was enough.
But as embedded products grew, communication requirements multiplied, displays became graphical, networking appeared, and diagnostics expanded.
One processor core now carried dozens of independent responsibilities. The challenge was no longer writing code for a peripheral; it was organizing the execution of independent, parallel activities without letting one delay the other.
That challenge eventually led to the development of Operating Systems.
PrajnaEdge is a technology company exploring the space between understanding technology, experimenting with ideas, and turning them into things that can be experienced.
PrajnaEdge began with Embedded Systems — exploring the foundations that connect hardware, software and intelligent computation.
The first technology universe is built around that foundation. The journey will expand as new ideas, experiments and products emerge.
PrajnaEdge is a technology company created by Devaharsha Meesarapu.
I am the engineer behind the design, development, and content of PrajnaEdge. I build low-level systems where code directly controls hardware, bridging the gap between register-level silicon behavior and intelligent edge decision loops.
I am an Embedded Firmware Engineer focused on developing software for resource-constrained systems. My experience spans bare-metal firmware, device drivers, microcontroller peripherals, and communication protocols, working across the boundary between hardware and software.
My work has involved microcontroller-based systems, real-time behaviour, hardware interfaces, and communication technologies such as CAN, CAN FD, UART, SPI, and I²C. I am particularly interested in understanding systems from the lowest level upward—from registers and peripherals to intelligent edge systems.
Engineering is not just about writing code; it is about managing constraints, timings, and physical hardware characteristics. True mastery of complex systems comes from understanding the interactions across different layers of the stack.
This conviction is why I built PrajnaEdge—to bridge the gap between conceptual theory and direct, register-level physical reality.
Software that runs directly on hardware without an operating system.
"Every embedded application begins long before main()."
An Operating System manages hardware and software resources so complex applications can work efficiently.
"When one loop is no longer enough to carry the burden."
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