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

Gimenez, N. L., 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-Centelles, R., & 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-Centelles, R., Freitag, F., & Meseguer, R. (2022). Implementation of a LoRa Mesh Library. IEEE Access, 10, 113158-113171. https://doi.org/10.1109/ACCESS.2022.3217215

Finochietto, J. M., Micheletto, M., Eggly, G. M., Pueyo-Centelles, R., 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

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

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

Llisterri_Giménez, N., Monfort_Grau, M., Pueyo-Centelles, R., & 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.

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, 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

Cerdà-Alabern, L., & Iuhasz, G. (2021). Anomaly Detection in Wireless Community Networks using PCA. Presented at the. Barcelona, Spain. Retrieved from https://jcsd2020.ac.upc.edu/blog

Ibraimi, L., Selimi, M., & Freitag, F. (2021). BePOCH: Improving Federated Learning Performance in Resource-Constrained Computing Devices. Presented at the. Madrid: IEEE. https://doi.org/10.1109/GLOBECOM46510.2021.9685095 (Original work published 2021)

Pueyo-Centelles, R., Freitag, F., Meseguer, R., & Navarro, L. (2021). Beyond the Star of Stars: An Introduction to Multihop and Mesh for LoRa and LoRaWAN. IEEE Pervasive Computing, 20, 63-72. https://doi.org/10.1109/MPRV.2021.3063443

Manco-Sanchez, A., & Navarro, L. (2021). Blockchain-based system for subscription payments in circular economy model. Retrieved from /sites/default/files/dsg/Memoria%20-%20adrian.manco.pdf (Original work published 2021)

Roura, M., Franquesa, D., Navarro, L., & Meseguer, R. (2021). Circular digital devices: lessons about the social and planetary boundaries. Presented at the. New York: ACM. Retrieved from https://people.ac.upc.edu/leandro/p/limits2021-roura.pdf (Original work published 2021)