José de Jesus Rugeles

Guillermo Antonio Hernandez Ortiz, Edgar Santiago Quiroz Puentes, José de Jesús Rugeles

The integration of LoRa technologies with mesh topologies represents a robust alternative for off-grid communications in emergency scenarios within smart cities. Meshtastic firmware implements a decentralised mesh network over LoRa where each node acts simultaneously as end device and router, enabling communication via Bluetooth-connected mobile devices without reliance on conventional infrastructure. Within the Colombian context (915 MHz ISM band), this work establishes design and planning criteria through a controlled guided-link methodology that isolates the LoRa physical layer from propagation effects, enabling deterministic characterisation of all eight Meshtastic modem presets at three transmission power levels (42 datasets). The results reveal a performance partitioning governed primarily by Spreading Factor (SF): "Short" presets (SF7-SF8) fail at 110-120 dB of path attenuation, "Medium" presets (SF9-SF10) sustain links up to 135-150 dB, and "Long" presets (SF11-SF12) maximise coverage, with "Long Slow" reaching 180 dB before failure - a 60-70 dB advantage over the fastest profiles. The SNR analysis confirms sub-noise-floor demodulation down to -18 dB for SF12, with abrupt link failure occurring within 2-4 dB of the theoretical limit. Based on these thresholds, three operational regimes are defined (high-density IoT, balanced urban mesh, and maximum-range emergency), providing network designers with quantitative criteria to select the appropriate configuration and node density for smart city deployments.

Jose de Jesus Rugeles, Edward Paul Guillen, Leonardo S Cardoso

The increase of cyberattacks using IoT devices has exposed the vulnerabilities in the infrastructures that make up the IoT and have shown how small devices can affect networks and services functioning. This paper presents a review of the vulnerabilities of the wireless technologies that bear the IoT and assessing the experiences in implementing wireless attacks targeting the Internet of Things using Software-Defined Radio (SDR) technologies. A systematic literature review was conducted. The types of vulnerabilities and attacks that can affect the wireless technologies that stand the IoT ecosystem and SDR radio platforms were compared. On the IoT system model layer, perception layer was identified as the most vulnerable. Most attacks at this level occur due to limitations in hardware, physical exposure of devices, and heterogeneity of technologies. Future cybersecurity systems based on SDR radios have notable advantages due to their flexibility to adapt to new communication technologies and their potential for the development of advanced tools. However, cybersecurity challenges for the Internet of Things are so complex that it is needed to merge SDR hardware with cognitive techniques and intelligent techniques such as deep learning to adapt to rapid technological changes.