--- title: A.B.C. - A.I. Book Cataloguer: from concept to working prototype language: en date: 2026-02-28 modified: 2026-06-18 canonical: https://denovo.srl/en/a-b-c-a-i-book-cataloguer-from-concept-to-working-prototype/ source: https://denovo.srl/en/a-b-c-a-i-book-cataloguer-from-concept-to-working-prototype/ --- # A.B.C. - A.I. Book Cataloguer: from concept to working prototype *This article follows up on our previous post: [Axelera AI Smarter Spaces Project Challenge](https://denovo.srl/en/axelera-ai-smarter-spaces-project-challenge-3/), where we announced our participation in the challenge.* **From concept to working prototype: our journey through the Axelera Project Challenge.** ### The project **A.B.C.** (“A.I. Book Cataloguer”) is an edge-AI system for the automatic cataloguing of books, developed by us at [Denovo](https://denovo.srl), an Italian startup, as part of the **Axelera Project Challenge 27**. The project was first announced on the Axelera community on **December 3, 2025**, and reached a fully working prototype on **February 25, 2026**, with final documentation published on February 28, 2026. The core idea is straightforward but powerful: eliminate the manual work of book cataloguing – slow, repetitive and error-prone – by replacing it with a **smart tabletop station** that automatically scans a book cover and extracts title, author and publisher in real time, with no cloud connectivity required. ### The team We are an **innovative startup in the field of AI-driven mechatronics**, a small international team made up of: - **Two Italian engineers** - **One Polish project manager** More information about the team is available on the [Team](https://denovo.srl/en/team/) page. A.B.C. is our **first real edge-AI project**, brought to life thanks to the hardware kit provided by Axelera as part of the challenge. ### The problem A.B.C. aims to solve The digitisation of book collections has historically been a slow and labour-intensive process. Operators must read each book, enter data by hand and correct any mistakes – a workflow that significantly slows down operations and undermines metadata quality. A.B.C. aims to **eliminate this bottleneck** by automating information extraction and introducing a natural gesture-based correction mechanism, making the entire process faster, more accurate and remarkably intuitive. Potential applications range from libraries and second-hand bookshops to comic book stores, where the continuous cataloguing of ever-changing stock is a concrete and costly challenge. ### The hardware The system is built around the kit provided by Axelera, which arrived from the Netherlands in late December 2025. The components used in the final setup are: - **SBC:** Orange Pi 5 Plus - **NPU accelerator:** Axelera Metis M.2 - **Camera:** Sonoff CAM S2 - **Local network:** TP-Link router with direct Ethernet connection - **Camera mount:** ring light with adjustable arm - **Levelling:** dual-bubble level attached to the camera - **Storage:** SD card - **Display:** monitor ### Software and AI pipeline After several iterations we adopted the final solution based on **PP-OCR (PaddleOCR v3 Latin)** in hybrid mode, after discarding EasyOCR, Tesseract and several LLMs (which turned out to be too “creative”, fabricating data instead of correcting it). The complete pipeline involves: 1. RTSP camera acquisition and loading-area crop via OpenCV 2. Book detection with YOLOv8l running on the Metis NPU 3. Hybrid OCR sub-pipeline: text-block detection on Metis and actual OCR acquisition on CPU with a newer, more accurate model 4. Fuzzy matching against a local database (12 GB **Open Library** dump) 5. On-screen result and wait for the operator’s gesture ### Operator interaction and UX ▶Load the video from YouTubeBy loading the video you accept YouTube (Google) cookies and policy. [Privacy policy](https://denovo.srl/en/privacy-policy-3/) The operator interacts with the system in a completely **hands-free, gesture-based** way: - **Placing a book** in the loading area automatically starts the process - **Sliding the book away** confirms the acquisition – a large green check is shown and data is saved to a local CSV file - **Showing crossed fingers** (an X shape) under the camera triggers a discard – a large red X is shown - Both actions feature a **time bar**, giving the operator a window to interrupt the action In the final phase, a **QR code command system** was added, allowing the operator to re-trigger calibration, toggle diagnostics and handle a clean shutdown of the Orange Pi. ### Project timeline - **Dec 3, 2025:** first post published on the Axelera community - **Dec 20, 2025:** hardware kit received from the Netherlands - **Jan 12, 2026:** full unboxing, Voyager SDK installation, first test with “inference.py” - **Feb 1, 2026:** physical setup, Open Library DB integration, code published on GitHub - **Feb 23, 2026:** complete pipeline, switch to PaddleOCR v3, final debugging - **Feb 25, 2026:** working prototype completed - **Feb 28, 2026:** final documentation and verified physical setup ### Axelera features the project On **April 10, 2026** Axelera publicly featured our project on their LinkedIn profile: [see the post](https://www.linkedin.com/feed/update/urn:li:activity:7448055915393568768/). ### Results and outlook The system was completed successfully within the challenge timeframe. The final prototype operates **entirely offline** (with the sole exception of the Wi-Fi link between camera and local access point) and demonstrates the viability of an automatic cataloguing system running on low-cost edge hardware. All code, documentation, instructions, QR codes, images and the Orange Pi “.stl” support bracket are **freely available** in the project’s GitHub repository: [github.com/denovo-it/abc](https://github.com/denovo-it/abc). *Project developed by us at [Denovo](https://denovo.srl) as part of the Axelera Project Challenge 27 – December 2025 / March 2026.* ABC (AI Book Cataloguer) is one of the public projects from our [artificial intelligence](/en/artificial-intelligence/) stream, developed in‑house alongside [mechatronics Terni, Central Italy](/en/mechatronics/), [blockchain Terni, Central Italy](/en/blockchain-rd/) and [cybersecurity Terni, Central Italy](/en/cybersecurity-rd/).