Intcatch aquatic drone sensor dataset

Published: 24 January 2020| Version 1 | DOI: 10.17632/gtt7stf5x8.1
Contributors:
Alberto Castellini,
,
,
,

Description

This dataset contains sensor traces (multivariate time series) of six data acquisition campaigns performed by autonomous aquatic drones involved in water monitoring. A total of 5.6 hours of navigation are available, with data coming from both lakes and rivers, and from different locations in Italy and Spain. The monitored variables concern both the internal state of the drone (e.g., battery voltage, GPS position and signals to propellers) and the state of the water (e.g., temperature, dissolved oxygen and electrical conductivity). Data were collected in the context of the EU-funded Horizon 2020 project INTCATCH (http://www.intcatch.eu) which aims to develop a new paradigm in the monitoring of river and lake water quality. Both autonomous and manual drive is used in different parts of the navigation.

Files

Steps to reproduce

See paper in Data in Brief

Categories

Environmental Monitoring, Data Science, Machine Learning, Artificial Intelligence Applications, Data Analysis, Sensor, Water Monitoring

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