Papers
12
Total Citations
332
H-Index
9
About
Fernando Seco is a leading researcher in indoor localization and positioning systems, with a career focused on advancing the accuracy and reliability of location technologies. His work spans acoustic positioning, ultra-wideband (UWB) radio systems, and sensor network optimization. Seco’s major contributions include developing advanced sensorial systems for acoustic LPS (65 citations) and algorithms for 3D-position estimation from ultrasonic time-delay data (31 citations). He has also pioneered methods for optimal sensor placement in trilateration networks (42 citations) and improved UWB location accuracy by accessing multiple ranges (35 citations). Notably, his research on comparing indoor localization systems through the EvAAL framework (82 citations) has provided a benchmark for the field. Seco has also contributed to competition datasets for IPIN, supporting community-wide evaluation of smartphone-based positioning. His work on autocalibration of wireless networks using FastSLAM (9 citations) and compensation of CDMA interference in acoustic positioning (14 citations) further demonstrates his innovative approach. With over 300 total citations, Seco’s research continues to shape the development of robust, high-accuracy indoor localization systems for robotics, IoT, and navigation applications.
Research Focus
Key Achievements
Top Papers
- 1
- 2Advanced sensorial system for an acoustic LPS65 citations · 2007
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- 7Fine-grained acoustic positioning with compensation of CDMA interference14 citations · 2015
- 8Datasets and Supporting Materials for the IPIN 2019 Competition Track 3 (Smartphone-based, off-site)13 citations · 2019
- 9
- 10Datasets and Supporting Materials for the IPIN 2018 Competition Track 3 (Smartphone-based, off-site)7 citations · 2018