How do QR codes work? (I built one myself to find out)

Initially dismissed as unattractive and meaningless, QR codes have proven to be incredibly useful and are now widely adopted in various applications such as tickets, restaurant menus, advertising, and even money transfers in some countries. Their evolution reflects a significant shift from being mere machine-readable symbols to becoming an integral part of everyday human interaction with technology. The history of QR codes traces back to early attempts at digitizing information.

In 1825, painter Samuel Morse received a significant opportunity to paint the Marquis de Lafayette but tragically lost his wife during his absence. This personal loss motivated him to develop faster long-distance communication methods. By 1836, he created an electric telegraph system with Joseph Henry and Alfred Vail that utilized simple dots and dashes for encoding letters based on their frequency of use. The ability to recognize these sounds allowed operators to transmit messages quickly, leading Morse code to become an international standard in various fields including military and maritime communications.

The Birth of Barcodes: Revolutionizing Checkout Processes In the late 1940s, Bernard Silver and Norman Joseph Woodland created the first barcode to streamline supermarket checkouts. Inspired by Morse code, they developed a system using narrow and wide lines that could store 12 digits. This universal product code (UPC) is read by lasers reflecting light off black and white patterns, with specific arrangements ensuring accurate scanning from any angle. Each unique combination of numbers identifies products globally while manufacturers pay for exclusive number ranges.

Evolving Beyond Barcodes: The Quest for More Information As barcodes became limited in information capacity, alternatives were sought after incidents like mad cow disease highlighted tracking needs in food safety. David Allais attempted to stack multiple barcodes but achieved minimal data increase until two-dimensional codes emerged as a solution—specifically Data Matrix technology used by NASA for space shuttle parts identification. Masahiro Hara also innovated an efficient alternative due to frustrations with traditional scanning methods at his auto parts company.

Encoding Information in Binary Form QR codes store information using a grid system where black and white squares represent binary data. Each character in the encoded message is converted into ASCII, then to binary form, creating a string of ones and zeros. The QR code's design includes position markers for orientation detection and alignment patterns that help with rescaling when scanned from different angles.

Understanding QR Code Structure The structure of a QR code consists of various elements including timing strips that indicate its version size, format rules for scanning, and reserved spaces for error correction. Data storage begins at the bottom right corner with bits specifying data formats followed by bytes arranged in zigzag patterns across the grid while avoiding fixed regions like alignment squares.

Enhancing Functionality Through Redundancy Redundancy within QR codes allows recovery of lost information if damaged; this feature enables logos or designs to be incorporated without losing scannability. A practical application involves setting up e-SIMs through services like Saily which simplifies mobile connectivity abroad without incurring high roaming fees—demonstrating how technology can enhance user experience globally.

Error Correction in QR Codes QR codes utilize four levels of error correction, allowing them to remain readable even with significant damage—up to 30% missing for high-level corrections. The format strip indicates the level of error correction and contains duplicated information for reliability. This redundancy ensures that if part of a QR code is damaged, it can still be reconstructed using the remaining data.

Reed-Solomon Coding Explained To ensure accurate transmission despite potential errors, Reed-Solomon coding employs polynomial mathematics where additional coefficients help verify message integrity. By evaluating these polynomials at specific points (syndromes), one can detect and correct any discrepancies in transmitted numbers without excessive data increase. This method has been crucial not only for QR codes but also in preserving signals from spacecraft like Voyager against noise interference.

Masking Techniques and Public Adoption The appearance of a QR code must avoid uniform patterns that could confuse scanners; thus masking techniques are applied to shuffle pixel arrangements while maintaining functional elements intact. Eight different masks exist within the standard, each evaluated based on readability efficiency before selection during generation processes. Initially designed for industrial use, public demand surged after events like mad cow disease highlighted their utility in tracking food sources effectively through scannable codes.

QR codes gained popularity due to DENSO Wave's decision not to enforce patent rights, allowing widespread use. The integration of QR code readers into smartphone camera apps in 2017 significantly boosted their adoption. The COVID-19 pandemic further accelerated this trend as businesses sought contactless solutions for menus and payments, particularly in countries like India and China where transactions soared. Additionally, QR codes became essential for storing vaccine records and health information on mobile devices.

QR codes have become a tool for scammers looking to defraud unsuspecting users. It's crucial to remain vigilant when scanning QR codes, as they can lead to malicious websites or phishing attempts. Always verify the destination of a scanned code before clicking on any links.

The future of QR codes is promising, with an almost limitless number of unique configurations available. Unlike UPC barcodes, which may eventually run out, the potential for new QR codes remains vast due to their complex structure—approximately 2 to the power of 152 unique versions exist. This immense variety ensures that random patterns in a QR code do not convey meaningful information unless specifically designed as such. As users continue scanning and interacting with these codes, they gain deeper insights into their functionality and applications.