Résumé
Raspberry Pi is a powerful, popular, low-cost minicomputer with the ability to collect physical environmental data from sensors and circuits, such as temperature, luminosity, gas concentration, images and infrared radiation level. Our new R package RaspberryPiR can store sensor data using sensor controlling modules on the Pi (GPIO pins) into shared memory. The data analysis can then be done in a streaming manner, using various streaming statistical and machine learning algorithms.In its current implementation, our package is compatible with the following sensors: DHT11 Temperature and Humidity Sensor, Photo Resistor, MQ2 Gas Sensor and Raspberry Pi Camera Module V2, which already allows for numerous streaming applications. We review and suggest implementation of a set of existing statistics tools for windowed data streams, such as Control Charts and Tukey Region. These can help visualizing data streams collected using our package.To summarize, our package simplifies the process of collecting data streams from surroundings using a Raspberry Pi. This permits scientists, statisticians, data scientists and practitioners to be in control of their environmental research and data project without the need of understanding complexity of data storage and electric circuits on the Raspberry Pi.https://github.com/alexzhu1998/RaspberryPiR