The increase in yearly particulate matter concentrations has been a constant issue since 2017 in the Aburrá Valley, located in Antioquia, Colombia. Although local certified air quality monitors provide high accuracy, they are limited in spatial coverage, limiting chemical transport and pollution dynamic studies in this mountainous environment. In this work, a local, Low-Cost Sensor network is proposed as an alternative and has been installed around the valley in representative locations and heights. To calibrate PM2.5 and O3 sensors used by the network, temporal delays were analyzed with Dynamic Time Warping and the linear scale was corrected with a Single Linear Regression model. As a result, the correlation coefficient R2 of the sensor reached values of 0.8 and 0.9 after calibration. For all network stations, rescaled data agrees with official historical reports on the behavior of pollutant concentrations and meteorological variables. The ability to compare the network results with certified data confirms the success of the calibration/validation method employed and contributes to the growing field of low-cost air quality sensors in Latin America.