Wireless communications in times of crisis: a systematic approach to enhancing disaster relief networks

Abstract

This research evaluates the performance and optimisation of IoT-enabled communication systems for disaster response through five experimental studies. BLE 5.0 in fire-exposed environments showed minimal signal attenuation, with a maximum RSSI variance of 2 dBm, indicating resilience under high-temperature and obstructed conditions. Network topology comparisons revealed that point-to-point (P2P) links provided stronger RSSI, while mesh networks enabled self-healing, with average losses of 6–7 dBm and maximum losses up to 18 dBm between nodes. User orientation and transmission power effects were assessed for BLE 4.0 and 5.0, showing orientation can alter RSSI by up to 13 dBm, while enhanced power improved short-range signals (up to 10 m) by 0.08–10.42 dBm but occasionally reduced performance at longer distances. RSSI-based localisation was evaluated using two distance estimation models: The Friis transmission equation provided accurate estimates up to 1 m, whereas a power regression model extended reliable localisation to 40 m, with maximum offset errors of 3.31 m for distances up to 18 m and 6–20 m for longer ranges.

UAV deployments as aerial nodes were investigated for BLE and 5G links. RSSI analysis showed optimal BLE performance at 5 m (–88.57 dBm, standard power) and 15 m (–87.73 dBm, enhanced power). Channel characterisation of mid-5G UAV links indicated that UAV vibrations and onboard electronics had negligible impact on received wideband power (mean RWP differences ≤0.2 dB), delay spread (τ mean and τ RMS), and statistical distributions, best modelled by the Rician distribution across all heights and user modes.

Methods included laboratory BLE testing, mesh network simulations, UAV field trials, and statistical analysis of 5G channels. Collectively, these findings demonstrate that combining BLE, mesh networking, UAV relays, and careful power/orientation management can yield robust, resilient IoT-based emergency communication systems, supporting accurate localisation, stable signal transmission, and enhanced situational awareness in disaster scenarios.

Date of Award	Oct 2025
Original language	English
Supervisor	Jose Santos (Supervisor) & Joseph Rafferty (Supervisor)