Introduction

In light of the critical role that remote sensing technology plays in the local community, there is an urgent demand for the establishment of a remote sensing chair. This chair is considered a pivotal element in fostering community partnerships between individuals, community institutions, and universities, serving as scientific hubs dedicated to conducting rigorous research and in-depth studies in the field. The chair aims to address community challenges and raise awareness about the significance of scientific research based on a sense of social and national responsibility.

Furthermore, the remote sensing chair is a crucial applied tool for analyzing scientific studies, offering innovative methods and technologies to support various scientific disciplines. It integrates modern technologies such as artificial intelligence, the Internet of Things, and cybersecurity, enhancing the efficiency and effectiveness of scientific endeavors. Through this interdisciplinary approach, the chair strives to optimize scientific applications, gaining a competitive edge at the national level and fostering the growth of the knowledge economy in remote sensing.

Moreover, the remote sensing chair aims to stimulate creativity and excellence by translating research innovations into practical solutions that benefit scientific institutions and the local community. This synergy enhances collaboration between academia and society, driving comprehensive sustainable development in alignment with the Kingdom's Vision 2030.

Vision:

 Establishing a knowledge base in remote sensing research and applications to link the university with the local community and achieve excellence and leadership locally, regionally, and globally.

 

Mission:

 Providing the appropriate research infrastructure and employing it for researchers, students, and society and providing a mechanism for cooperation between them and developing their capabilities in the field of remote sensing to reach knowledge products that contribute to the national economy and participate in achieving comprehensive sustainable development.

 

Objectives:

1. Develop technical proficiency to deliver the best solutions through remote sensing while upholding the highest quality standards.

2. Foster a culture of teamwork and knowledge-sharing to maximize efficiency and effectiveness in remote sensing applications.

3. Commitment to strong ethical principles in scientific research and development within remote sensing systems.

4. Offer support, expertise, and infrastructure to ensure society reaps the benefits of remote sensing applications in aligning with Vision 2030.

Chair Supervisor

Dr. Ali Hamdan Alenezi is an Associate Professor in the Department of Electrical Engineering at Northern Border University. He earned his Ph.D. in Electrical Engineering from the New Jersey Institute of Technology (NJIT), USA, with a dissertation on acoustic communication in drill strings. His academic and research expertise spans over a decade, strongly emphasizing wireless communication systems, mainly using intelligent UAVs, visible light communication, and signal processing.

Dr. Alenezi has published many impact factor journal articles in his field, exploring applications of artificial intelligence, machine learning, and deep learning in wireless and acoustic communications. His technical skills include programming in Python and C++ and working with MATLAB, LaTeX, and VERILOG hardware description language. Additionally, he co-founded the Remote Sensing Unit at Northern Border University, where he contributes to research and development in innovative communication technologies and teaches advanced courses in signal processing and wireless communications.

 

Email: Ali.Hamdan@nbu.edu.sa 

Teamwork

Researchers

 

Dr. Mohannad Almutairi is an Associate Professor in the Department of Electrical Engineering at Northern Border University. He holds a Ph.D. from the University of Dayton, Ohio, and has dedicated his career to advancing the fields of radar, remote sensing, and signal processing. He has served as Dean of Admissions and Registration and Head of the Remote Sensing Research Unit. One of Dr. Almutairi’s notable contributions includes co-founding SARsatX, a space-focused startup specializing in Earth monitoring through synthetic aperture radar (SAR) imaging. His expertise spans UAV detection, radar imaging, and electronic warfare, with a strong presence in publications and a U.S. patent in tomography imaging.

Email: Muhannad.Almutiry@nbu.edu.sa

 

 

 

 

 

 

Dr. Ahmad Salih Azzahrani received his B.S. degree in Electrical Engineering from Umm Al-Qura University in 2009 and his M.S. and Ph.D. in Electrical Engineering from Florida Institute of Technology, Florida, USA, in 2014 and 2020, respectively. He worked at Saudi Electricity Company for two years before joining Northern Border University’s faculty staff in 2011. During his PhD studies, he worked as a Teaching Assistant at the Florida Institute of Technology. In addition to his role at NBU as a vice dean of admission and registration, he teaches several courses, including Electronics, Object-Oriented Programming, Structured Computer Programming, and Digital Design. His research areas of interest are renewable energy, photonics, photodetectors, remote sensing, artificial intelligence, and the Internet of Things.

Email: Ahmad.Azzahrani@nbu.edu.sa 

 

 

 

 

 

 

Dr. Mohammad Abdulmannan Barr is an Associate Professor in the Department of Electrical Engineering at the College of Engineering, Northern Border University. He holds a Ph.D. from De Montfort University, UK. His research interests focus on artificial intelligence applications in engineering fields, including computer vision and image classification. His work includes aerial image classification for desertification detection, and he contributes to scientific projects to develop intelligent technologies for analyzing data related to environmental and renewable energy fields.

Email: Mohammed.Barr@nbu.edu.sa

 

 

 

Dr. Yahia Said has acquired a PhD in Electronics from the University of Monastir - Tunisia. He is an Associate Professor at the Electrical Engineering Department at the College of Engineering, Northern Border University, Saudi Arabia. 

Dr. Said has published several papers in top-ranked scientific journals and participated in many national and international conferences. He is an Editorial Board Member and regular reviewer of several well-known indexed journals. He is researching STEM-related topics, such as intelligent embedded systems, artificial intelligence, embedded vision, desertification detection, solar energy forecasting, intelligent traffic management systems in smart cities, advanced driver assistance systems, and crowd management.

Dr. Said's applied research portfolio showcases a deep engagement with developing AI-driven technologies for real-world applications. He focuses on enhancing assistive devices for the visually impaired through advanced computer vision and deep learning techniques to facilitate navigation and scene recognition. His work also extends to innovative city solutions, like traffic management, intelligent parking systems, and public safety during events like Hajj. He contributes to solar forecasting for smart grids in the renewable energy sector. His environmental efforts include using AI for desertification monitoring. Much of his work involves embedding these intelligent systems into hardware, using FPGAs and GPUs for real-time, efficient processing critical for edge computing. His interdisciplinary research spans AI and engineering, targeting societal benefits and technological advancements in autonomous vehicles and embedded intelligence.

 

Email: Yahia.Said@nbu.edu.sa 

 

Published research

 

Paper Title

Journal Name

Year

1

Cell on Wheels-Unmanned Aerial Vehicle System for Providing Wireless Coverage in Emergency SituationsComplexity2021

2

3d deployment of unmanned aerial vehicle-base station assisting ground-base stationWireless Communications and Mobile Computing2021

3

PSO-Based UAV Deployment and Dynamic Power Allocation for UAV-Enabled Uplink NOMA NetworkWireless Communications and Mobile Computing2021

4

Efficient placement of an aerial relay drone for throughput maximizationJournal of Green Engineering2021

5

Modeling ground-to-air paths loss for millimeter wave UAV networksIEEE Sensors Council2021

6

A Novel Method for Pattern Recognition based on Radar Tomographic Images

IJCSNS2021

7

Portable UWB RADAR Sensing System for Transforming Subtle Chest Movement into Actionable Micro-Doppler Signatures

IEEE Sensors Council2021

8

Novel Ensemble Algorithm for Multiple Activity Recognition in Elderly People Exploiting Ubiquitous Sensing Devices

IEEE Sensors Council2021

9

Discrete Human Activity Recognition and Fall Detection by Combining FMCW RADAR Data of Heterogeneous Environments

Electronics2021

10

Balancer Genetic Algorithm—A Novel Task Scheduling Optimization Approach in Cloud ComputingApplied Science2021

11

Uniform Magnetic Field Characteristics Based UHF RFID Tag for Internet of Things ApplicationsElectronics2021

12

On the Use of Deep Learning for Imaging-Based COVID-19 Detection Using Chest X-raysSensors2021

13

A Transfer Learning Approach for Indoor Object IdentificationSN Computer Science2021

14

Understanding Traffic Signs by an Intelligent Advanced Driving Assistance System for Smart VehiclesJournal of Artificial Intelligence and Big Data2021

15

Deep learning-based application for indoor wayfinding assistance navigationMultimedia Tools and Applications2021

16

Human emotion recognition based on facial expressions via deep learning on high-resolution images

Multimedia Tools and Applications2021

17

Real-time implementation of traffic signs detection and identification algorithm on graphics processing units

International Journal of Pattern Recognition and Artificial Intelligence2021

18

Countries flags detection based on local context network and color featuresMultimedia Tools and Applications2021

19

Indoor sign Detection System for Indoor Assistance Navigation

2021 18th International Multi-Conference on Systems2021

20

Drivers Fatigue Detection Using EfficientDet in Advanced Driver Assistance Systems2021 18th International Multi-Conference on Systems2021

21

A convolutional neural network to perform object detection and identification in visual large-scale data

Big Data2021

22

Optimizing Neural Networks for Efficient FPGA Implementation: A SurveyArchives of Computational Methods in Engineering2021

23

UAVs-assisted passive source localization using robust TDOA ranging for search and rescueICT Express2021

24

Interference aware cooperative routing for edge computing-enabled 5G networksIEEE Sensors Journal2022

25

Bayesian Multidimensional Scaling for Location Awareness in Hybrid Internet of Underwater ThingsIEEE/CAA Journal of Automatica Sinica2022

26

Investigating the Factors Impacting Aggregators and Datasets Performances in Federated LearningIEEE Transactions on Engineering Management2022

27

A Novel Mining Approach for Data Analysis and Processing Using Unmanned Aerial VehiclesComplexity2022

28

Adversarial Machine Learning in Text Processing: A Literature SurveyIEEE Access2022

29

Power-Efficient Wireless Coverage Using Minimum Number of UAVsSensors2022

30

A survey on spectrum management for unmanned aerial vehicles (UAVs)

IEEE Access2022

31

Distributed Destination Search Routing for 5G and beyond NetworksSensors2022

32

An Adaptive Black-box Defense against Trojan Attacks on Text Data2021 Eighth International Conference on Social Networks Analysis, Management, and Security (SNAMS)2022

34

Co-Circularly Polarized Planar Antenna With Highly Decoupled Ports for S-band Full Duplex ApplicationsIEEE Access2022

35

Multiple Participants' Discrete Activity Recognition in a Well-Controlled Environment using Universal Software Radio Peripheral Wireless

Sensors2022

36

Novel Privacy Preserving Non-Invasive Sensing-Based Diagnosis of Pneumonia Disease Leveraging Deep Network Model

Sensors2022

37

An evaluation of EfficientDet for object detection used for indoor robots assistance navigation

Journal of Real-Time Image Processing2022

38

An efficient implementation of a traffic sign detection system for advanced driver Assistance Systems

International Journal of Intelligent Robotics and Applications2022

39

An efficient object detection system for indoor assistance navigation using deep learning techniques

Multimedia Tools and Applications2022

40

Traffic Sign Detection for Green Smart Public Transportation Vehicles Based on Light Neural Network ModelComputational Intelligence Techniques for Green Smart Cities2022

41

An Embedded Implementation of a Traffic Light Detection System for Advanced Driver Assistance Systems

Industrial Transformation2022

42

Traffic Sign Detection Using Convolutional Neural Network for Navigation of Driver Assistance Systems

Computers, Materials & Continua2022

43

Human Faces Detection and Tracking for Crowd Management in Hajj and Umrah

Multimedia Tools and Applications2022

44

Desertification Detection in Makkah Region based on Aerial Images Classification

Computer Systems Science and Engineering2022

45

Embedded implementation of an obstacle detection system for blind and visually impaired persons’ assistance navigation

Computers and Electrical Engineering2023

46

Obstacle Detection System for Navigation Assistance of Visually Impaired People Based on Deep Learning Techniques

Sensors2023

47

Lightweight Cryptography for Connected Vehicles Communication Security on Edge Devices

Electronics2023

48

Scene Recognition for Visually-Impaired People’s Navigation Assistance Based on Vision Transformer with Dual Multiscale Attention

Mathematics2023

49

Indoor Signs Detection for Visually Impaired People: Navigation Assistance Based on a Lightweight Anchor-Free Object Detector

International Journal of Environmental Research and Public Health2023

50

Traffic flow management by detecting and estimating vehicles density based on object detection model

Neural Computing and Applications2024

51

AI-based outdoor moving object detection for smart city surveillance

AIMS Mathematics2024