ARABIA-WIND: Autonomous Remote Aerial Bot for Integrated Atmospheric Wind and Weather INtelligence Detection in Eastern Saudi Arabia

ARABIA-WIND (Autonomous Remote Aerial Bot for Integrated Atmospheric Wind and Weather Intelligence Detection) is a purpose-built, IoT-enabled Unmanned Aerial Vehicle (UAV) developed for environmental sensing. This paper presents the design and implementation of ARABIA-WIND, with a par-ticular emphasis on its environmental sensing capabilities for detecting temperature, humidity, and rainfall. The UAV enables continuous data streaming and analysis via real-time internet connectivity with a ground station and supports cloud-based IoT integration for remote access and monitoring. Integrated GPS modules enhance navigational accuracy, ensuring precise mission execution across varied and complex terrains. This technology is especially vital in the Eastern Province of Saudi Arabia, a region characterized by rapid urbanization, frequent sandstorms, and variable microclimates. These conditions demand responsive and localized meteorological data to support infrastructure planning, public safety, and disaster preparedness efforts. This paper offers a comprehensive overview of the development stages of ARABIA-WIND, including its system design, hardware-software integration, intelligent features, and the challenges encountered throughout its implementation.

Authors

Institutions

Publication Details

Published
2025-08-22
DOI
https://doi.org/10.1109/iccsce65566.2025.11182677
Primary Topic
Flood Risk Assessment and Management
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

ARABIA-WIND: Autonomous Remote Aerial Bot for Integrated Atmospheric Wind and Weather INtelligence Detection in Eastern Saudi Arabia

Ghulam E Mustafa Abro, Asif M. Khan, Mohammed Altheeb, AbdulAziz Al Ruqi
Flood Risk Assessment and Management
article

ARABIA-WIND: Autonomous Remote Aerial Bot for Integrated Atmospheric Wind and Weather INtelligence Detection in Eastern Saudi Arabia

Ghulam E Mustafa Abro, Asif M. Khan, Mohammed Altheeb, AbdulAziz Al Ruqi
article en

Abstract

ARABIA-WIND (Autonomous Remote Aerial Bot for Integrated Atmospheric Wind and Weather Intelligence Detection) is a purpose-built, IoT-enabled Unmanned Aerial Vehicle (UAV) developed for environmental sensing. This paper presents the design and implementation of ARABIA-WIND, with a par-ticular emphasis on its environmental sensing capabilities for detecting temperature, humidity, and rainfall. The UAV enables continuous data streaming and analysis via real-time internet connectivity with a ground station and supports cloud-based IoT integration for remote access and monitoring. Integrated GPS modules enhance navigational accuracy, ensuring precise mission execution across varied and complex terrains. This technology is especially vital in the Eastern Province of Saudi Arabia, a region characterized by rapid urbanization, frequent sandstorms, and variable microclimates. These conditions demand responsive and localized meteorological data to support infrastructure planning, public safety, and disaster preparedness efforts. This paper offers a comprehensive overview of the development stages of ARABIA-WIND, including its system design, hardware-software integration, intelligent features, and the challenges encountered throughout its implementation.

King Fahd University of Petroleum and Minerals (SA), King Fahd Military Medical Complex (SA), Coventry University (GB)
Openalex Percentile: Top 74%
Flood Risk Assessment and Management
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.