MicroDiff: Embedded Text Analysis Engine 🚀

📖 Overview

MicroDiff is a lightweight, hardware-integrated text analysis engine designed specifically for memory-constrained embedded systems. It performs real-time comparison of text strings (such as system configuration plans) using a highly optimized Longest Common Subsequence (LCS) algorithm.

Bridging the gap between theoretical computer science and bare-metal mechatronics, this system processes data with extreme memory efficiency and makes physical actuation decisions based on textual similarity percentages.

📺 Live Demo & Output

Here is the execution of the optimized engine running inside the Wokwi simulation environment, successfully analyzing file differences and triggering a mechatronic lock response:

🧠 Engineering Analysis: Space Optimization

The standard dynamic programming implementation of the LCS algorithm requires a 2D matrix, resulting in a space complexity of O(m * n). On a standard microcontroller with severely limited SRAM (e.g., 2KB), this approach immediately results in a stack overflow for large texts.

The Solution: MicroDiff implements a bitwise space-optimized approach. By recognizing that the calculation only ever requires the current and previous rows of the DP matrix, the algorithm continuously toggles between two rows using bitwise AND (i & 1).

• Time Complexity: O(m * n)
• Space Complexity: O(min(m, n))

Read the full mathematical breakdown in our Algorithm Notes.

⚙️ Hardware Architecture

The system architecture relies on minimal GPIO usage by leveraging serial communication protocols.

• Processing Unit: Arduino Uno (ATmega328P) showcasing aggressive memory management.
• Display Output: 16x2 LCD operating over the I2C protocol to display analysis progress and match percentage.
• Physical Actuator: PWM-controlled Servo Motor acting as a mechatronic gate/lock that physically reacts if the file variance exceeds a defined safety threshold.

📂 Repository Structure

• src/: Contains the core C++ logic (main.ino) featuring the optimized algorithm.
• simulation/: Includes the diagram.json mapping for rapid reproduction in Wokwi.
• data/: Sample text targets utilized for difference analysis (plan5_en.txt, plan6_en.txt).
• docs/: Project documentation, algorithmic notes, and architecture details.

🚀 How to Run (Simulation Environment)

You can deploy and test this system entirely in the cloud without physical hardware:

1. Clone this repository.
2. Open the Wokwi Simulator and create a new Arduino project.
3. Replace the default code with the contents of src/main.ino.
4. Replace the environment mapping with simulation/diagram.json.
5. Add the LiquidCrystal I2C library via the Wokwi Library Manager.
6. Run the simulation to observe the text analysis, percentage calculation, and automated servo actuation.

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Developed as part of academic coursework and research at Amirkabir University of Technology.