0 or 1 credit
Summer 2026 Laboratory Upper Division
This class is the last course (of four) within the Digital Data Acquisition Camp, a 3 week-long intensive, in-person program. Students will learn: the operating principles behind common environmental sensors, how to configure and deploy sensors, and practices for cleaning, processing, and analyzing sensor time series data. Learners will gain hands-on experience collecting data with environmental sensors. Students will work with large datasets to learn best practices for quality control. After processing their datasets, students will use common data processing and modeling techniques to extract meaningful information from sensor data streams. This course emphasizes both in situ and remote sensing techniques for analyzing soil, water, and air chemistry and physical properties and forestry and wildlife applications. Permission from the Department is required.
Learning Outcomes1Understand and evaluate different sensor technology platforms and networks.
2Deploy, calibrate and maintain sensor networks.
3Process, clean and manage data collected from sensor networks.
4Analyze simple data streams from sensor networks.
Prerequisites
Restrictions
made by Purdue students.