Acc.elerometer vs HCC2D Decoder

See how your device moves with Acc.elerometer. View live sensor readings, record an experiment and examine the results on your iPhone or iPad. Capture motion on Apple Watch and send recordings to your paired iPhone for charts and CSV export. EXPLORE SIX MEASUREMENTS - Acceleration, including gravity, in G - User acceleration, with gravity removed, in G - Rotation rate around three axes in rad/s - Magnetic field in microteslas - Device attitude: roll, pitch and yaw in radians - Gravity along each axis in G View individual axes and vector magnitude where supported. Follow changing values and review recorded measurements to explore movement, rotation and orientation. RECORD AND REVIEW Choose the measurements you want to capture, then start and stop a recording. On iPhone and iPad, set the measurement interval from 0.1 to 1 second. Open saved recordings to inspect charts, switch between individual axes and vector magnitude for supported measurements, and identify gaps in the data. EXPORT YOUR DATA Export each measurement from a recording as a CSV file with timestamps and axis values. Choose Unix time, spreadsheet serial dates or formatted date strings for your analysis workflow. CAPTURE MOTION ON APPLE WATCH View sensor readings and record selected measurements on your wrist. Send saved recordings to the paired iPhone and follow transfer progress. Add watch face complications to see saved sensor maxima or recording status, and open the app to start a recording from the recording widget. FOR EXPERIMENTS AND EVERYDAY CURIOSITY Explore device motion for a physics demonstration, a development project or your own experiments. Measurements and recordings are stored on your devices. No account is required. Available readings and actual sampling intervals depend on the device and its sensors. Apple Watch recording duration is subject to watchOS background runtime limits. Watch complications show saved values from the app, rather than a continuous live sensor feed.

This app allows you to scan and decode HCC2D and QR code symbols using your mobile camera. It is based on advanced research in high-capacity barcode technologies and provides reliable decoding. Key features: * Decode HCC2D color codes. * Full support for standard QR codes. * Real-time scanning using the camera. * Robust detection and error correction. * No ads and no registration required. HCC2D is a color two-dimensional code format that increases data capacity compared to traditional QR codes while preserving their structure. By using multiple colors, each module can encode more information, enabling higher data density in a compact symbol. The app captures images, detects barcode regions, corrects perspective distortions, and analyzes color or intensity patterns to reconstruct the encoded data. To transfer files from a desktop computer to your smartphone via a stream of HCC2D codes, use HCC2D Decoder together with the HCC2D Streamer desktop companion app. Notes: HCC2D codes can be created using the official online generator at hcc2d.com, the HCC2D Encoder application, the open-source CLI encoder, or the Debian/Ubuntu packages provided through the official HCC2D APT repository. * Low-quality color printing may reduce decoding performance * Best results are achieved with screen-displayed or high-quality printed codes and a high-resolution autofocus camera. * One-dimensional barcodes are intentionally not supported. References: * Querini, M. (2026). HCC2D Code Specification — Version 0.9.0. Zenodo. https://doi.org/10.5281/zenodo.22206528. Licensed under the Creative Commons Attribution-NoDerivatives 4.0 International License (CC BY-ND 4.0). * Querini, M. and Italiano, G. F. (2014). Reliability and Data Density in High Capacity Color Barcodes. Computer Science and Information Systems, 11(4), 1595-1615. * Querini, M., Grillo, A., Lentini, A., and Italiano, G. F. (2011). 2D Color Barcodes for Mobile Phones. IJCSA, 8(1), 136-155. * Querini, M. (2010). Analysis and Design of High-Capacity Two-Dimensional Codes. Development of the Reader for Desktop and Mobile Environments (Bilingual Digital Edition 2026, Version 1.0). Zenodo. https://doi.org/10.5281/zenodo.22206722 Notice: This application is an independent personal project and is not affiliated with any organization or institution.