Project Section

A.B.C. — AI Bridging Cultural Heritage

A 36-month Erasmus+ KA220-SCH cooperation partnership uniting six European nations to pioneer artificial intelligence, 3D photogrammetry, and interdisciplinary STEAM education in cultural heritage preservation.

Relevance & Vision

Why AI and Cultural Heritage?

European cultural heritage represents a shared wealth of identity, artistry, and history. Yet across our continent, countless historic sites face risks from environmental erosion, climate stress, and a growing disconnect among youth. Traditional textbook education often portrays history as static, lacking experiential and modern technological connection.

The Erasmus+ project “A.B.C. — AI Bridging Cultural Heritage” transforms students from passive observers into active digital guardians. Secondary school learners in Estonia, Italy, Poland, Greece, and Portugal use everyday smartphones to create high-precision 3D scans of local monuments, train neural vision models to classify architecture, and build interactive digital archives.

Funded under Erasmus+ Key Action KA220-SCH (Cooperation Partnerships in School Education), the project bridges the humanities and STEAM disciplines to inspire long-term digital literacy and cross-border European solidarity.

Aims & Objectives

What We Aim to Achieve by 2027

Six concrete intellectual and educational outcomes that drive every stage of consortium work.

Open Heritage AI Toolkit

A comprehensive open-source pedagogical toolkit with guides, annotated image datasets, and 3D workflows adapted for classroom use across European schools.

Living Transnational Exchange

Regular coordinator meetings (TPM) and international student learning mobilities (LTT) where multicultural teams test tools and solve local heritage challenges.

Student-Led 3D Digital Archive

Empowering students as primary researchers to capture and publish over 30 interactive 3D digital models of regional monuments and museum artifacts.

Computer Vision Architecture Models

Training accessible neural networks to recognize Gothic, Renaissance, Baroque and Modernist styles, giving students hands-on artificial intelligence literacy.

Local Heritage Adaptation

Each partner school applies the methodology to its own historic reality — from medieval Tallinn gates to Portuguese Manueline architecture and ancient Minoan ruins.

Long-Term Post-2027 Sustainability

Ensuring all resources remain free, open-source, and permanently hosted for schools and museums throughout Europe after project completion.

Methodology & Tech

Practical Technologies Built and Tested by Students

How artificial intelligence and photogrammetry come together in school classrooms.

Neural Vision Classification

Students gather and label thousands of photos of arches, capitals, and facades. Using transfer learning, they train lightweight vision models capable of real-time style identification on mobile devices.

Smartphone 3D Photogrammetry

By taking overlapping photos around sculptures and facade details, students process point clouds into textured polygon meshes, producing web-ready 3D models viewable in AR and VR.

Conversational Heritage AI Bot

Using Retrieval-Augmented Generation (RAG) and curated historical databases, teams create interactive conversational assistants that answer visitor questions in multiple languages.

Target Groups

Who Benefits From This Initiative

Direct Group

Students aged 13–18

More than 350 learners gain technical AI competence, creative digital skills, and an international perspective on European heritage.

Direct Group

Teachers & School Teams

Educators in history, computer science, arts and languages receive interdisciplinary training and ready-to-use lesson packages.

Indirect Group

Museums & Conservators

Regional cultural institutions gain free 3D digital assets, educational museum apps, and increased engagement with youth.

Indirect Group

Schools Across Europe

Open-access materials allow any European school to replicate and adapt our heritage AI modules free of charge.

Project Phases

Three Years · Four Implementation Phases

A structured roadmap ensuring rigorous development, testing, and dissemination.

Phase 1 · Autumn 2024

Kick-Off & Methodological Framework

Consortium setup, first Transnational Project Meeting (TPM 1) in Tallinn, ethical AI guidelines for secondary schools, and hardware baseline setup.

Phase 2 · 2025

Tool Development & Photogrammetry Mobilities

Teacher training and student learning mobility (LTT 1) in Braga on 3D scanning, pilot creation of 15 models, and interim evaluation meeting in Florence (TPM 2).

Phase 3 · 2026

Computer Vision Hackathons & Scaled Piloting

Virtual reconstruction workshop and AI hackathon in Kraków (LTT 2), and pilot classroom testing across all partner schools.

Phase 4 · 2027

Public Launch & European Dissemination Conference

Open release of the 3D model repository, launch of the multilingual Heritage AI Toolkit, and final dissemination conference in Heraklion, Greece.

Project Passport

Official Grant Details

Official registration data under the Erasmus+ Programme of the European Union for reporting, academic citations, and administrative verification.

Project No.
2024-1-EE01-KA220-SCH-000000000
Action
KA220-SCH · Cooperation partnerships in school education
Coordinator
Narva Pähklimäe Kool, Estonia
Partners
Italy, Poland, Greece, Portugal, Turkey
Duration
01.09.2024 – 31.08.2027 (36 months)
Funding
Erasmus+ Programme, European Union

Explore Our Transnational Mobilities

Follow the chronological journey of our student exchanges and coordinator meetings across Europe.

View Mobilities Timeline → Meet Partner Schools