Many people in the United States are disconnected from their environment: urban residents spend 90% of their time indoors inside confined climate-controlled spaces. In addition to being physically separated from the natural environment, much of human understanding of the world's environment is inferred from data collected by satellites orbiting 22,000 miles away. In contrast, in-situ environmental sensor systems are physically accessible, location specific, and essential for correcting and validating weather measurements. However, present options for in-situ systems are mostly limited to expensive, proprietary commercial data loggers with inflexible data access protocols. WeatherChimes is an open-source Arduino-programmable, low-cost hardware and software suite that enables near real-time access to in-situ environmental sensor data (including light, temperature, relative humidity, and soil moisture) anywhere with a WiFi internet connection. Scientists, educators, and artists alike can use this tool to obtain and interact with environmental data in new and innovative ways, as well as collaborate remotely. Transforming data collection processes of environmental sensors into Internet of Things (IoT) compatible formats opens new doors into accessing, understanding, and interacting with natural phenomena. WeatherChimes not only enables users to observe data online, but can also transform data into auditory signals and soundscapes through sonification processes or creative animations using newly-created computer applications. Lab and field tests have confirmed the sensor and online data logging performance of the system. We describe the application of WeatherChimes in an undergraduate Honors College classroom and STEM (Science, Technology, Engineering, and Math) education workshop series in Sitka Alaska, which was used to not only teach about environmental sensors, but to explore how different aspects of our environment are interrelated (e.g. temperature and humidity) through sonification.
Keywords: Arduino; Data Logging; Data Sonification; Environmental Observation; MQTT; Max8; MongoDB; Near real-time Data.
© 2023 The Author(s).