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.
How open-drain logic and addressing solved the pin inflation crisis of SPI.
SPI unlocked extreme communication speeds by sharing a clock, but it introduced a severe hardware bottleneck: pin inflation. Because SPI has no addressing system, the master must use a dedicated Chip Select (CS) pin for every single peripheral on the bus. If you connect five sensors, you need five separate CS pins. If you scale to ten devices, your microcontroller's GPIO lines are consumed entirely by chip selection.
This physical routing nightmare forced engineers to re-evaluate the bus architecture. They needed a protocol that preserved the benefits of a synchronous clock but allowed dozens of devices to share the exact same physical wires without a forest of chip select lines. The solution was the Inter-Integrated Circuit (I2C) protocol.
I2C makes a radical design trade-off. It discards the four-wire, point-to-point architecture of SPI in favor of a strictly shared, two-wire bus: SDA (Serial Data) and SCL (Serial Clock). Every device on the bus connects to these same two traces.
By shrinking the bus to two wires, I2C eliminates the physical pin bottleneck. A master can communicate with over a hundred devices using the exact same two pins. However, this simplicity introduces a complex electrical challenge: if multiple devices share the same data and clock lines, how do we prevent them from colliding and burning out their output drivers when one tries to transmit a 1 while another transmits a 0?

In standard push-pull output stages (used in UART and SPI), a device actively drives the line HIGH (connecting it to VCC) or actively drives it LOW (connecting it to GND). If Device A drives HIGH while Device B drives LOW on a shared wire, a low-resistance path is created directly from VCC to GND. This causes a short circuit, excessive current draw, heating, and physical damage to the silicon.
To prevent this, I2C uses open-drain (or open-collector) output buffers combined with physical pull-up resistors on both SCL and SDA. In an open-drain buffer, a device can only actively pull the line LOW (turning on an internal NMOS transistor connected to GND). It cannot actively drive the line HIGH; instead, to send a 1, it simply turns off the transistor and lets the line float. The external pull-up resistor then pulls the line HIGH.
This creates a 'wired-AND' logic bus. If any single device pulls the line LOW, the entire line goes LOW. The line only returns HIGH when every single device releases it. Electrical collisions are resolved safely: if two devices write conflicting states, the line simply resolves to LOW, drawing only a safe, limited current through the pull-up resistor.

Because I2C lacks physical Chip Select lines, the protocol must establish starting boundaries and address routing directly within the two-wire interface. Under normal operation, the SDA line is only allowed to change state when the SCL clock line is LOW. When SCL is HIGH, the data on SDA must remain stable to be sampled.
I2C exploits this stability rule to define START and STOP conditions. A START condition is signaled when SDA transitions from HIGH to LOW while SCL is HIGH. A STOP condition is signaled when SDA transitions from LOW to HIGH while SCL is HIGH. These transitions act as start-of-frame and end-of-frame markers that every peripheral monitors on the bus, resetting their internal receivers to listen for addressing.

Immediately following a START condition, the master transmits a 9-bit address frame. The first 7 bits represent the unique target address of the slave. The 8th bit indicates the transaction direction: Write (0) or Read (1).
The 9th clock cycle is reserved for a hardware handshake: the Acknowledge (ACK) bit. During the 9th clock tick, the master releases the SDA line (letting it float HIGH). The slave device matching the address must actively pull the SDA line LOW. If the slave pulls SDA LOW, it is an ACK—the transaction continues. If the slave is missing, busy, or has crashed, the line remains HIGH (a Not-Acknowledge, or NACK), signaling the master to stop.
SPI is a 'blind' protocol: the master drives SCLK regardless of whether the slave has processed the data. If the slave lags behind, data is lost. I2C solves this flow-control problem using clock stretching.
Although the master normally controls SCL, the open-drain architecture allows a slave to take control. If a slave needs more time to process a byte or fetch sensor readings, it can actively hold the SCL line LOW after the master releases it. The master monitors the SCL line: as long as it senses SCL is LOW, its internal clock generator pauses, freezing the transaction. Only when the slave releases SCL does it float HIGH and the master continues.
In complex systems, multiple master devices may share the same bus. If two masters assert a START condition simultaneously, I2C uses bus arbitration to resolve conflicts without corrupting data or causing electrical shorts.
Because of the open-drain wired-AND structure, both masters can drive SCL and SDA. As they transmit data bits, each master monitors the actual state of the SDA line. As long as the bus matches the bits they write, they proceed. However, if Master A writes a 1 (releasing SDA) but Master B writes a 0 (pulling SDA LOW), the bus resolves to LOW. Master A, sensing a LOW when it expected a HIGH, realizes another master is active, immediately halts its transmission, releases the bus, and falls back to receiver mode. Master B continues its transaction completely uninterrupted, unaware of the silent victory.

Let's review the journey: UART taught us to align clock phases through a timing contract between two nodes. SPI showed us that sharing a physical clock yields speeds orders of magnitude higher at the cost of dedicated wiring. I2C showed us that by using addressing and open-drain physics, we can share the clock and data wires completely, scaling to dozens of devices using only two pins.
Yet I2C has limits. The pull-up resistors create an RC time constant with the parasitic capacitance of the wires: as the bus gets longer or more devices are added, the rising edge of SCL/SDA becomes slow and rounded, limiting speeds (typically 400 kHz to 3.4 MHz) and distances to a few meters. Furthermore, in high-noise environments like automotive engines or industrial floors, common-mode noise can easily flip single-ended logic levels.
When we need to scale to longer distances, high noise immunity, and multi-master robustness without master-slave dependencies, we must look beyond single-ended voltage sharing to differential, arbitrated networks—leading us to the design of the Controller Area Network (CAN).
I2C stands as a monument to cooperation in hardware. By shifting the selection burden from dedicated copper wires (SPI's CS) to software protocol syntax and open-drain physics, it enables complex inter-chip ecosystems using minimum resources.
It reminds us that communication is not just about driving voltages, but agreeing on when to listen and when to step aside.
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."
PrajnaEdge is an independent education platform built to make knowledge freely accessible.
If you find PrajnaEdge useful, you can support its continued development.
Your support helps fund the time, tools, infrastructure, and experimentation that go into building and maintaining PrajnaEdge.
Welcome to PrajnaEdge (prajnaedge.dev), an independent engineering and technology platform created and maintained by Devaharsha Meesarapu. By using this website, you agree to these terms.
Educational & Research Focus: PrajnaEdge publishes interactive technical explorations, architectural models, and simulation walk-throughs covering embedded systems, computer architecture, operating systems, and edge artificial intelligence. All materials, interactive tools, and code demonstrations are provided solely for educational and conceptual understanding.
Hardware & Firmware Disclaimer: Embedded programming interacts directly with hardware registers, physical voltages, and precise timing. While all writeups and code demonstrations are prepared with care, they are provided "as is" without warranty of any kind. You are responsible for reviewing component datasheets, circuit schematics, and electrical ratings before deploying code to physical microcontrollers or custom hardware.
Intellectual Property: All original articles, custom SVG architectures, interactive simulators, curriculum sequences, and source code are the intellectual property of Devaharsha Meesarapu (© 2026 PrajnaEdge. All rights reserved). Non-commercial educational study and citation are welcome with proper attribution. Direct republication, unauthorized mirroring, or mass scraping of content is not permitted.
PrajnaEdge is committed to user privacy and minimal data collection. We do not sell, rent, or monetize your personal information.
localStorage purely to remember your interface preferences on your device (such as sound preferences for animations and tutorial display states). No personal identity data is stored in localStorage.
To help support platform operation and hosting, PrajnaEdge displays advertisements served by third-party advertising partners, including Google AdSense.
We use Google Analytics (measurement tag: G-6Y8ZVQB1V0) to evaluate anonymous, aggregate usage trends across our technical writeups.
Depending on your jurisdiction (including rights under GDPR, CCPA/CPRA, and applicable privacy laws), you have the right to request access to, correction of, or deletion of any personal communications you have submitted. We do not sell personal data.
For any questions regarding these terms, privacy practices, or data inquiries, contact the creator directly: