Energy and Spectral Efficiency Analysis for UAV-to-UAV Communication in Dynamic Networks for Smart Cities DOI Creative Commons
Mfonobong Uko, Sunday Ekpo, Ubong Ukommi

et al.

Smart Cities, Journal Year: 2025, Volume and Issue: 8(2), P. 54 - 54

Published: March 22, 2025

Unmanned Aerial Vehicles (UAVs) are integral to the development of smart city infrastructures, enabling essential services such as real-time surveillance, urban traffic regulation, and cooperative environmental monitoring. UAV-to-UAV communication networks, despite their adaptability, have significant limits stemming from onboard battery constraints, inclement weather, variable flight trajectories. This work presents a thorough examination energy spectral efficiency in over four frequency bands: 2.4 GHz, 5.8 28 60 GHz. Our MATLAB R2023a simulations include classical free-space path loss, Rayleigh/Rician fading, mobility profiles, accommodating varied heights (up 500 m), velocities (reaching 15 m/s), fluctuations loss exponent. Low-frequency bands (e.g., GHz) exhibit up 50% reduced compared higher mmWave for distances exceeding several hundred meters. Energy (ηe) is evaluated by contrasting throughput with total power consumption, indicating that GHz initiates at around 0.15 bits/Joule (decreasing 0.02 after 10 s), whereas demonstrate markedly worse ηe (as low 10−3–10−4bits/Joule), resulting increased oxygen absorption. Similarly, sub-6 can attain 4×10−12bps/Hz near-line-of-sight scenarios, lines encounter attenuation above 200–300 m without sophisticated beamforming techniques. Polynomial-fitting methods indicate projected diverges actual performance less than 5% s flight, highlighting feasibility machine-learning-based techniques beam steering, or multi-band switching. While UAV provide capacity enhancements (100–500 MHz bandwidth), deteriorates meticulous planning adaptive protocols. We thus advocate using radios, modulation, trajectory optimisation equilibrate ensure connection stability, meet high data-rate requirements densely populated, dynamic settings.

Language: Английский

Unmanned Aerial Vehicles and Low-Cost Sensors for Air Quality Monitoring: A Comprehensive Review of Applications Across Diverse Emission Sources DOI

Vishal Choudhary,

Manuj Sharma, Suresh Jain

et al.

Sustainable Cities and Society, Journal Year: 2025, Volume and Issue: unknown, P. 106409 - 106409

Published: April 1, 2025

Language: Английский

Citations

0
When the Wind Blows: Exposing the Constraints of Drone‐Based Environmental Mapping DOI Creative Commons
Jan Komárek

Natural Sciences, Journal Year: 2025, Volume and Issue: unknown

Published: April 28, 2025

ABSTRACT Drones have become indispensable for high‐resolution, on‐demand remote sensing, yet their valid operational window is far narrower than often portrayed. Using meteorological data from 31 locations in the Czech Republic since 2016, we demonstrate that weather constraints—including precipitation, wind and temperature extremes—collectively limit feasible flight days to roughly 25% per year. Although an overall 0.8°C rise average 2019 has slightly reduced cold‐weather issues, it introduced more frequent heatwaves increased variability, offsetting potential gains. High gusts, precipitation can degrade sensor accuracy distort imagery even when conditions permit flight. Radiometric collection—often conducted near solar noon—can be disrupted by clouds, haze or complicating efforts obtain consistent, high‐quality measurements. Despite these pervasive effects, many drone‐based studies lack detailed documentation, hindering reproducibility comparisons. Weather nowcasting adaptive mission planning offer ways mitigate gaps, but questions remain about ensuring sustained, coverage variable climates. By acknowledging addressing inherent constraints, sensing community realistically harness drones’ refine guidelines long‐term environmental monitoring. Highlights: Meteorological constraints are a strong reality check. Climate trends alter don't solve drone limitations. Future improvements must go beyond hardware enhancements.

Language: Английский

Citations

0
Energy and Spectral Efficiency Analysis for UAV-to-UAV Communication in Dynamic Networks for Smart Cities DOI Creative Commons
Mfonobong Uko, Sunday Ekpo, Ubong Ukommi

et al.

Smart Cities, Journal Year: 2025, Volume and Issue: 8(2), P. 54 - 54

Published: March 22, 2025

Unmanned Aerial Vehicles (UAVs) are integral to the development of smart city infrastructures, enabling essential services such as real-time surveillance, urban traffic regulation, and cooperative environmental monitoring. UAV-to-UAV communication networks, despite their adaptability, have significant limits stemming from onboard battery constraints, inclement weather, variable flight trajectories. This work presents a thorough examination energy spectral efficiency in over four frequency bands: 2.4 GHz, 5.8 28 60 GHz. Our MATLAB R2023a simulations include classical free-space path loss, Rayleigh/Rician fading, mobility profiles, accommodating varied heights (up 500 m), velocities (reaching 15 m/s), fluctuations loss exponent. Low-frequency bands (e.g., GHz) exhibit up 50% reduced compared higher mmWave for distances exceeding several hundred meters. Energy (ηe) is evaluated by contrasting throughput with total power consumption, indicating that GHz initiates at around 0.15 bits/Joule (decreasing 0.02 after 10 s), whereas demonstrate markedly worse ηe (as low 10−3–10−4bits/Joule), resulting increased oxygen absorption. Similarly, sub-6 can attain 4×10−12bps/Hz near-line-of-sight scenarios, lines encounter attenuation above 200–300 m without sophisticated beamforming techniques. Polynomial-fitting methods indicate projected diverges actual performance less than 5% s flight, highlighting feasibility machine-learning-based techniques beam steering, or multi-band switching. While UAV provide capacity enhancements (100–500 MHz bandwidth), deteriorates meticulous planning adaptive protocols. We thus advocate using radios, modulation, trajectory optimisation equilibrate ensure connection stability, meet high data-rate requirements densely populated, dynamic settings.

Language: Английский

Citations

0