Aatab, S., & Freitag, F. (2023). Integrating a Neural Network Library in Embedded Federated Learning. Presented at the. https://doi.org/10.1109/CloudTech58737.2023.10366148

Vilchez, P., Jacques, S., Freitag, F., & Meseguer, R. (2023). LoRaTRUST: Blockchain-Enabled Trust and Accountability Service for IoT Data. Electronics, 12, 1996. https://doi.org/10.3390/electronics12091996

Freitag, F., Solé, J. M., & Meseguer, R. (2023). Position Paper: LoRa Mesh Networks for Enabling Distributed Intelligence on Tiny IoT Nodes. Presented at the. IOS Press. https://doi.org/10.3233/AISE230026

Roura, M., Navarro, L., & Meseguer, R. (2023). Property Rights in Servitisation: A Practical Assessment with Reused Computers (V. Wohlgemuth, S. Naumann, G. Behrens, H.-K. Arndt, & M. Höb, Eds.). Hamburg: Springer International Publishing. https://doi.org/https://doi.org/10.1007/978-3-031-18311-9_2 (Original work published 2022)

Cerdà-Alabern, L., Gemmi, G., & Maccari, L. (2023). Reliability Analysis in a Wireless ISP. Retrieved from https://www.ac.upc.edu/app/research-reports/public/html/research_center…

Freitag, F., Wei, L., Liu, C.-H., Selimi, M., & Veiga, L. (2023). Server-side Adaptive Federated Learning over Wireless Mesh Network. Presented at the. Cusco, Peru: Springer International Publishing. Retrieved from https://doi.org/10.1007/978-3-031-33261-6_25 (Original work published 2023)

Francisco, J., Coimbra, M. E., Neto, P. F. R., Freitag, F., & Veiga, L. (2023). Stateful Adaptive Streams with Approximate Computing and Elastic Scaling. Presented at the. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3555776.3577858

Gemmi, G., Cerdà-Alabern, L., Navarro, L., & Maccari, L. (2023). Toward Smart Community Networks. IEEE Network, 37, 128-134. https://doi.org/10.1109/MNET.003.2200371 (Original work published 2023)

Aatab, S., & Freitag, F. (2023). Towards a Library of Deep Neural Networks for Experimenting with on-Device Training on Microcontrollers. Presented at the. https://doi.org/10.1109/WF-IoT58464.2023.10539445

Aliagas, C., Pérez-Foguet, A., Meseguer, R., Millan, P., & Molina, C. (2022). A Low-Cost and Do-It-Yourself Device for Pumping Monitoring in Deep Aquifers. Electronics, 11, 3788. https://doi.org/10.3390/electronics11223788

Gemmi, G., Cerdà-Alabern, L., & Maccari, L. (2022). A Realistic Open-Data-based Cost Model for Wireless Backhaul Networks in Rural Areas. Presented at the. Thessaloniki, Greece: IEEE. https://doi.org/10.23919/CNSM55787.2022.9964562 (Original work published)

Finochietto, J. M., Micheletto, M., Eggly, G. M., Pueyo, R. C., Santos, R. M., Ochoa, S. F., … Orozco, J. (2022). An IoT-based infrastructure to enhance self-evacuations in natural hazardous events. Personal and Ubiquitous Computing, 26, 1461–1478. https://doi.org/10.1007/s00779-020-01506-z

Llisterri-Giménez, N., Freitag, F., Lee, J., & Vandierendonck, H. (2022). Comparison of Two Microcontroller Boards for On-Device Model Training in a Keyword Spotting Task. 1-4. https://doi.org/10.1109/MECO55406.2022.9797171

Cerdà-Alabern, L. (2022). Dataset for Anomaly Detection in a Production Wireless Mesh Community Network. https://doi.org/10.5281/zenodo.6169917

Freitag, F., Vilchez, P., Wei, L., Liu, C.-H., Selimi, M., & Koutsopoulos, I. (2022). Demo: An Experimental Environment Based On Mini-PCs For Federated Learning Research. Las Vegas: IEEE. Retrieved from https://personals.ac.upc.edu/felix/CR_2022_CCNC_Demo.pdf (Original work published 2022)

Solé, J. M., Nogués, S. M., Pueyo, R. C., & Freitag, F. (2022). Demonstration of a library prototype to build LoRa mesh networks for the IoT. Presented at the. https://doi.org/10.1109/ICDCS54860.2022.00150

Pino, D. L., Freitag, F., & Selimi, M. (2022). Designing a Double LoRa Connectivity for the Arduino Portenta H7. Presented at the. https://doi.org/10.1109/LANMAN54755.2022.9820092

Solé, J. M., Pueyo, R. C., Freitag, F., & Meseguer, R. (2022). Implementation of a LoRa Mesh Library. IEEE Access, 10, 113158-113171. https://doi.org/10.1109/ACCESS.2022.3217215

Harillo, E. C., & Freitag, F. (2022). LoRaCoin: Towards a blockchain-based platform for managing LoRa devices. 1-2. https://doi.org/10.1109/INFOCOMWKSHPS54753.2022.9798276

Llisterri-Giménez, N., Monfort_Grau, M., Pueyo, R. C., & Freitag, F. (2022). On-Device Training of Machine Learning Models on Microcontrollers with Federated Learning. Electronics, 11. https://doi.org/10.3390/electronics11040573 (Original work published 2022)

Freitag, F., Vilchez, P., Wei, L., Liu, C.-H., & Selimi, M. (2022). Performance Evaluation of Federated Learning Over Wireless Mesh Networks with Low-Capacity Devices. online: Springer International Publishing.

Finochietto, M., Santos, R. M., Ochoa, S. F., & Meseguer, R. (2022). Reducing Operational Expenses of LoRaWAN-Based Internet of Remote Things Applications. Sensors, 22, 7778. https://doi.org/10.3390/s22207778

Del Solar, A. J. C., Solé, J. M., & Freitag, F. (2022). Towards a Monitoring System for a LoRa Mesh Network. Presented at the. https://doi.org/10.1109/ICDCS54860.2022.00139

Pueyo, R. C., Freitag, F., Meseguer, R., & Navarro, L. (2021). A minimalistic distance-vector routing protocol for LoRa mesh networks. Retrieved from http://hdl.handle.net/2117/347444 (Original work published 2026)

Panadero, J., Selimi, M., Calvet, L., Marquès, J. M., & Freitag, F. (2021). A two-stage Multi-Criteria Optimization method for service placement in decentralized edge micro-clouds. Future Generation Computer Systems, Future Generation Computer Systems. https://doi.org/https://doi.org/10.1016/j.future.2021.03.013 (Original work published 1021)