Project Description

Problem

In order to excavate sites with as little disruption as possible, archaeologists have a need for technology which can extract and analyze data from a site to determine where they should dig. A variety of tools, including pXRF spectrometers and GPS mapping, serve to collect data from sites. However, there exists no straightforward way of integrating and analyzing these different forms of data to draw conclusions about a site. Moreover, another issue is the difficulty posed by transferring data from pXRF devices to the devices used by archaeologists for quick, real-time analysis due to the lack of a stable Internet connection in the field.

Project Aim

The goal of our project is to develop and deploy a multi-lingual mobile application for the use of archaeologists working in the field. This application will run data from pXRF spectrometers, GPS, and site imagery through machine learning models in order to predict locations where anthropogenic activity is likely present. Our project will build upon its previous iteration, ArchaeoSight 1.0, by developing a strong user interface for the app, improving upon the machine learning models employed, enabling the app to be deployed on different types of devices, and providing support for multiple languages.

Project Proposal

This project was proposed by our client, Dr. Kayeleigh Sharp, director of NAU's Digital Archaeology Laboratory. The original proposal can be found here.