arXiv subjects

Juan Palomeque-Gonzalez

Publications and source records attributed to Juan Palomeque-Gonzalez.

2 recordsLinked to original sources

arXiv2025

A Reproducible Workflow for Scraping, Structuring, and Segmenting Legacy Archaeological Artifact Images

This technical note presents a reproducible workflow for converting a legacy archaeological image collection into a structured and segmentation ready dataset. The case study focuses on the Lower Palaeolithic hand axe and biface collection curated by the Archaeology Data Service (ADS), a dataset that provides thousands of standardised photographs but no mechanism for bulk download or automated processing. To address this, two open source tools were developed: a web scraping script that retrieves all record pages, extracts associated metadata, and downloads the available images while respecting ADS Terms of Use and ethical scraping guidelines; and an image processing pipeline that renames files using UUIDs, generates binary masks and bounding boxes through classical computer vision, and stores all derived information in a COCO compatible Json file enriched with archaeological metadata. The original images are not redistributed, and only derived products such as masks, outlines, and annotations are shared. Together, these components provide a lightweight and reusable approach for transforming web based archaeological image collections into machine learning friendly formats, facilitating downstream analysis and contributing to more reproducible research practices in digital archaeology.

cs.CY↗

arXiv2025

A Modular, Low-Cost IoT System for Environmental and Behavioural Monitoring in Cultural Heritage Sites

The preservation of cultural heritage faces growing challenges from climate change, tourism pressure, and limited conservation resources. Existing monitoring solutions are often cost-prohibitive, proprietary, and inflexible, leaving many institutions, particularly in developing regions, without viable tools for proactive management. This study presents a modular, low-cost Internet of Things (IoT) system designed for real-time environmental and behavioural monitoring in heritage sites. Built with off-the-shelf components such as ESP32 microcontrollers and Raspberry Pi, the system integrates a wireless sensor network, edge computing, and cloud services (Microsoft Azure) to measure variables including temperature, humidity, sound, and visitor proximity. It also incorporates computer vision models to classify visitor behaviour, achieving up to 95% accuracy using fine-tuned Vision Transformers. The system's modularity, enabled via JSON configurations, allows for rapid reconfiguration without firmware changes. A simulated deployment demonstrated robust performance, low power consumption, and cost-efficiency (less than 200 GBP per node), validating the system's potential for scalable, sustainable heritage monitoring. This open-source framework offers a practical path forward for institutions seeking to balance accessibility with conservation needs.

cs.CY↗