Sensor journalism refers to the use of sensors to generate or collect data, then analyzing, visualizing, or using the data to support journalistic inquiry. This is related to but distinct from data journalism. Whereas data journalism relies on using historical or existing data, sensor journalism involves the creation of data with sensor tools. This also includes drone journalism.
Examples of sensor-based journalism (below) date back to the early 2000s and usually involve the use of sensor tools to generate or collect data to be reported on. The way in which the sensors are deployed varies. In some cases, a journalist will learn how to operate and deploy a sensor (see Houston Chronicle) while in others (see WNYC Cicada Tracker), the sensors are built and deployed by the general public. Journalists can also request data from existing sensor networks (see Sun Sentinel example) and remote sensors (see ProPublica example).
Sensor journalism modules have been taught at Emerson College (around water quality/contamination) and Florida International University (around sea-level rise). San Diego State University planned an air-quality sensor-journalism module for spring 2015.