Project Hub /Artificial Intelligence & Edge ML/Object Detection & Tracking/Retrieval Of Data Using Image Analytic

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RASPBERRY PI

₹5,000 – ₹15,000

6 – 12 Hours

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Retrieval Of Data Using Image Analytic

An image analytics project that uses a camera and Python OCR to extract data from an older SCADA display screen where direct data connection is impossible.

Originally published on ElectronicsForU

View original tutorial

Parts You'll Need

This project is sourced from another site, not written by us — this list is our best match of their components against what we stock, not a verified bill of materials. Always check the original blog (linked above) for the actual parts list before buying.

Raspberry Pi 3 - Model B+ 1.4Ghz 64-bit quad-core Processor with 1 GB Ram (Original) Rs. 9,810.00
ESP32 CAM WiFi Module Bluetooth with OV2640 Camera Rs. 1,483.00
400 Points Mini Solderless Prototype PCB Breadboard High Quality Rs. 89.00
MB102 Adjustable Breadboard Power Supply Module (3.3V & 5V) for Arduino & Raspberry Pi Rs. 139.00
Jumper Wire 10 Pin Male To Male 20cm Rs. 45.00
Jumper Wire 10 Pin Male To Female 20cm Rs. 45.00

Selected: Rs. 0.00

We don't carry yet: LCD (generic / unspecified)
SS Transceiver

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How It Works

The Retrieval Of Data Using Image Analytic project functions by optically capturing visual data from a display monitor running SCADA software, bypassing the need for a direct digital data connection. At the core of the system is a moderate quality USB camera connected to a Raspberry Pi 4 Model B, which continuously or periodically captures images of the SCADA interface screen. Once an image frame is acquired, the Raspberry Pi executes a Python-based script utilizing the EAST text database and OCR (Optical Character Recognition) software. The EAST model efficiently detects text regions within the complex layout of the SCADA display, while the OCR engine translates those visual pixel patterns into machine-readable alphanumeric text strings. This extracted telemetry data is then processed locally or packaged for transmission via an SS Transceiver, allowing operational metrics to be logged or monitored remotely without ever interfacing directly with the legacy control computer network.

Why Build This

Bridge the gap between modern analytics platforms and legacy industrial control systems without violating warranty or stability constraints.

Gain practical undergraduate-level experience deploying computer vision pipelines and OCR frameworks on edge computing hardware like the Raspberry Pi.

Implement an un-intrusive data extraction technique suitable for hazardous or strictly locked-down operational environments.

Real-World Application

Extracting operational telemetry data from legacy industrial SCADA systems without modifying or interfering with the primary control computers.

Skills You'll Learn

Optical Character Recognition

Python programming

Edge machine learning deployment

Image preprocessing

Wireless data transmission

Computer vision integration

Safety Precautions

No specific precautions noted for this build — always follow general electronics safety practices.

Technology Tags

PYTHON

IMAGE PROCESSING

OCR

COMPUTER VISION

RASPBERRY PI

SCADA

DATA EXTRACTION

UART TRANSCEIVER

Frequently Asked Questions

Why use a camera instead of connecting directly to the SCADA computer via network or serial cable?

Direct connections to legacy industrial control systems can introduce security risks, software instability, or violate strict compliance regulations. An optical approach is entirely non-invasive and eliminates any risk of interfering with primary control operations.

What is the role of the EAST text database in this setup?

EAST (Efficient and Accurate Scene Text Detector) is used to rapidly and accurately locate text areas within the captured image frames from the SCADA screen, preparing the regions for successful optical character recognition.

Can this system transmit the extracted data to a remote location?

Yes, the system incorporates an SS Transceiver, which allows the Raspberry Pi to wirelessly transmit the processed text data over designated radio frequencies to a remote monitoring station or receiver.

Gallery

This page is part of Kitkraft's Project Hub — a curated collection of electronics & robotics projects gathered from the maker community to help students and hobbyists discover and learn to build. Kitkraft does not claim authorship of the original project, and makes no representation as to the accuracy, completeness or safety of third-party source material. The summary and "How It Works" explanation above are AI-generated, rewritten with reference to the original tutorial — not a reproduction of it. Full credit and a direct link to the original source are provided above. If you're the original creator and have a concern about how your work is represented here, please contact us and we'll address it promptly.

Kitkraft Project Hub — curated from the maker community, credited at the source.

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