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.
Submarine pipelines have been extensively employed to transport oil or gas from offshore petroleum exploitation activities. To ensure an efficient and expedited pipeline project, a computational tool based on Evolutionary Algorithms is employed to optimize submarine pipeline routes. Different evolutionary optimization methods could be applied, but this study focuses on the Genetic Algorithm (GA). In this tool, each candidate route is evaluated with several criteria incorporated in an objective function, obeying the relevant aspects to be considered in the route design such as: pipeline length, bathymetric data, obstacles, etc. Slope stability verification is also important in landslide risk areas in the pipeline route design context. Thus, this study evaluates the influence of these factors on a representative scenario route configuration. The case study results indicated the slope stability importance in the best route selection. Moreover, the computational tool provides more accurate results, avoids route interpretation mistakes, and ultimately minimizes the huge costs associated with submarine pipeline instalation and operation. Additionally, the slope stability assessment computational costs are low, which indicates the feasibility to incorporate them in the optimization tool.
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