Environmental sensing in cities

Resumen

The environmental condition has been a main concern in the last decades. Global governments and organizations warn about the possible harm in humans and in the environment. In this context, the current cost of sensors, embedded platforms and cloud solutions allow the IoT to help in environmental monitoring. This enables better awareness and better action plans in dangerous situations. This project consists of the development of an end-to-end prototype for environmental monitoring with a low-cost approach. It has been successfully developed and tested. It has been used a Raspberry Pi 3 Model B+ with the operating system Raspbian with full capabilities. With the sensors BME680, PMS5003, ADXL343 and MT3339 it has been measured the ambient conditions, particulate matter, acceleration and location. That hardware has been controlled with Python and CircuitPython with a multi-thread process. The Raspberry has internet access through WiFi and allows the commanding via MQTT. Onesait CloudLab is the cloud platform, it stores, process and presents the measured data. It generates alarms if the particulate matter overcomes the WHO recommendation. Moreover, Node-RED tool is used for the integration between the end-device and the cloud platform. It is adopted a multi-cloud approach; the data is sent to the Azure IoT Hub and to Onesait through HTTP. The resultant prototype has been tested in a fixed place, indoors and outdoors. The data variability along the day is small, so there is no necessity to send constant data. The particulate matter augments considerably outdoors. As far as concerned the validity of the measurements there are some differences in the obtained results comparing with nearest reference stations. Nevertheless, it cannot be determined if it is due to the spatial variability of the parameter. This document includes the state-of-the-art of environmental monitoring solutions. In addition, it is explained the used materials and the development of the prototype with the obtained results. Finally, a global evaluation of the project and future steps are presented.