The Muggy Weather Robotics Duo

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 The Muggy Weather Robotics Duo A C++ System That Thinks, Feels (Sensors!), and Acts Humidity is like the quiet character in the weather story that actually runs the show. On muggy days, everything feels heavier—breathing, drying laundry, running machines, even keeping a data center cool. For people, it’s about comfort and health; for machines, it’s about performance and reliability; for plants and buildings, it’s about moisture balance and mold risk. In robotics and automation, muggy weather isn’t just a nuisance—it’s a signal . It tells your systems when to ventilate, when to dehumidify, when to throttle physically demanding tasks, and when to take preventative maintenance actions. Today, we’ll build a two-program C++ system that “understands” muggy weather: Program A — sensor_hub.cpp A sensor-side program that generates (or ingests) a live stream of environmental data (temperature, relative humidity, pressure, CO₂, VOCs). Think of it as your robotic nose and skin , con...
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C++ Smart Document Summarizer and Analyzer

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C++ Smart Document Summarizer and Analyzer

This project consists of two integrated programs that work together to extract, format, analyze, and summarize documents.

Program 1: Document Text Formatter and Extractor

This component is responsible for extracting text from scanned documents or handwritten notes and formatting it into a readable structure.

Features:

  • Uses OCR (Optical Character Recognition) to extract text from images, including scanned PDFs and handwritten notes.
  • Formats extracted text into structured documents with proper paragraphs, headings, and formatting.
  • Saves the formatted text into a MySQL database for further processing.

Program 2: AI-Powered Document Summarizer

This component analyzes and summarizes extracted text using Natural Language Processing (NLP).

Features:

  • Categorizes documents into types such as academic, legal, business, etc.
  • Extracts key points to generate a concise summary.

Tech Stack

  • C++ (Main logic and GUI using a lightweight library like Qt)
  • Tesseract OCR (For text extraction from images)
  • MySQL (For storing extracted and summarized text)
  • Pre-trained NLP model (For text summarization)

How They Work Together

  1. Document Extraction – The text extractor scans documents and extracts text.
  2. Data Storage – The extracted text is stored in a MySQL database.
  3. Summarization & Analysis – The AI summarizer fetches the text from the database, processes it using NLP, and generates a summary.

This system enables efficient document processing, making it useful for various industries, including academia, legal, and business sectors.

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