Abstract
With the raising of environmental concerns regarding pollution, interest in monitoring air quality is increasing. However, air pollution data is mostly originated from a limited number of government-owned sensors, which can only capture a small fraction of reality. Improving air quality coverage in-volves reducing the cost of sensors and making data widely available to the public. To this end, the NanoSen-AQM project proposes the usage of low-cost nano-sensors as the basis for an air quality monitoring platform, capa-ble of collecting, aggregating, processing, storing, and displaying air quality data. Being an end-to-end system, the platform allows sensor owners to manage their sensors, as well as define calibration functions, that can im-prove data reliability. The public can visualize sensor data in a map, define specific clusters (groups of sensors) as favorites and set alerts in the event of bad air quality in certain sensors. The NanoSen-AQM platform provides easy access to air quality data, with the aim of improving public health.
Highlights
Since the industrial revolution, human activity is responsible for multiple kinds of pollution that have negative consequences to the environment [1]
This article provides an overall description of the platform, which includes: the main requirements of the platform, which guided the development; a list of the technologies used by the NanoSen-AQM platform, along with a small description of each one; the architecture of the system, coupled with an explanation of each module; and an overview of the client applications, which allow users to access air quality data and manage sensors
Users can interact with the NanoSen-AQM platform through the client applications, web and mobile, both created with Ionic from a single codebase
Summary
Human activity is responsible for multiple kinds of pollution that have negative consequences to the environment [1]. While low-cost sensors could improve the coverage of air quality monitoring, their data is often unreliable Performance of such sensors can be degraded by external and internal factors: temperature, relative humidity, cross-sensitivity (i.e., other pollutants that affect the measurements of the one being measured) and sensor drift (i.e., hardware decay). To deal with these issues, we intend to develop adjusting functions for compensating low-cost sensor output data accuracy, according to historic comparisons against reference sensors ( known as an adjustment of a measuring system [4]). This article provides an overall description of the platform, which includes: the main requirements of the platform, which guided the development; a list of the technologies used by the NanoSen-AQM platform, along with a small description of each one; the architecture of the system, coupled with an explanation of each module; and an overview of the client applications, which allow users to access air quality data and manage sensors
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