On March 31th, Darwin Quezada defended his PhD thesis entitled “Cloud-based Indoor Positioning Platform for Context adaptivity in GNSS-denied Scenarios” under the supervision of Prof. Joaquín Huerta, Dr. Joaquín Torres, Prof. Jari Nurmi, and Prof. Yevgeni Koucheryavy. 

This dissertation has a core focus on improving computing efficiency, data pre-processing, and software architecture for Indoor Positioning Systems, without throwing out position and location accuracy. One of the key contributions is on the field of data optimisation techniques, in which data cleansing algorithm is proposed to considerably reducing the number of outliers fingerprints in radio maps and, therefore, reducing the error in position estimation. Another set of contributions focused on two algorithms which group similar fingerprints into clusters, by proposing a new post-processing algorithm for Density-based Spatial Clustering of Applications with Noise (DBSCAN) clustering to redistribute noisy fingerprints to the formed clusters, enhancing the mean positioning accuracy.

Darwin’s thesis is one of the successful doctoral thesis developed in the context of the A-WEAR project. More will come shortly!

Congratulations to Dr. Darwin to reach that important milestone and all the best in his successful academic career! GEOTEC forever!