UAV

COEfoodsecurity

AI-enabled UAVs and Multimodal Monitoring for Protected and Controlled Environment (PACE)

This project aims to utilize advanced technologies for UAVs to enhance the efficiency, accuracy, and responsiveness of crop monitoring and management within the diverse PACE settings. The primary objectives revolve around employing a fleet of micro-UAVs equipped with cameras and LiDAR sensors to capture high-resolution images and 3D point clouds and perform multi-layered AI analysis. While cameras offer visual insights into surface-level plant health and characteristics, LiDAR provides deeper insights about plant physical attributes for a more comprehensive crop assessment. This project is

Sim-to-Real Transfer for Autonomous Navigation

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B2 L5 R5220

This work investigates the problem of transfer from simulation to the real world in the context of autonomous navigation. To this end, we first present a photo-realistic training and evaluation simulator Sim4CV which enables several applications across various fields of computer vision. Built on top of the Unreal Engine, the simulator features cars and unmanned aerial vehicles (UAVs) with a realistic physics simulation and diverse urban and suburban 3D environments. We demonstrate the versatility of the simulator with two case studies: autonomous UAV-based tracking of moving objects and autonomous driving using supervised learning.

Data assimilation and optimal control in the context of UAV-based flash flood monitoring

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B5 L5 R5209

Flash floods are one of the most common natural disasters worldwide, causing thousands of casualties every year. The emergence of Unmanned Aerial Vehicles (UAVs) gives the possibility to monitor these events over large geographical areas. In this talk, we focus on the problem of trajectory planning for a swarm of unmanned aerial vehicles sensing flooding conditions.

Civil drones traffic management: Wireless communication for safe UAV

Prof. Sofie Pollin, KU Leuven

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KAUST

UAV

In this webinar, we describe the common terminology for these two communities. First, the traffic management system architecture, requirements, terminology, and services are discussed. A quick overview of existing technologies that can be useful for aerial deconfliction. Next, the focus will shift to wireless technologies used for the tactical (while flying) deconfliction: ADS-B, p2p LoRa, WiFi, FLARM.

Flying LoRA IoT Gateway for Agricultural Applications

Prof. Samsuzana Abd Aziz, Department of Biological and Agricultural Engineering, Universiti Putra Malaysia

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B18 Fellowship Hall

Featured Sessions
Abstract Low-Power Wide Area Network (LPWAN) technologies like LoRa have become prominent for IoT deployments in large agricultural areas due to their low-power and long-range transmission. However, data transmission in large farms with diverse landscapes suffers from obstructions or occlusions, and wired gateways are still difficult to cover the whole agricultural areas without proper network or power infrastructures. This study integrates LoRa gateways with a flying drone to enhance the connectivity to sensor nodes deployed in an oil palm plantation. The LoRa gateway was mounted on a multi

Computer vision: Teaching computers how to see the world

1 min read ·
Ghanem works in the Visual Computing Center (VCC) and is interested in computer vision, image processing, and machine learning.

Lokman Sboui successfully defended his PhD thesis - Congratulations!

1 min read ·

UAV MIMO

On November 26, 2017, Lokman Sboui successfully defended his Ph.D. thesis on "Towards Reliable, Scalable, and Energy Efficient Cognitive Radio Systems" under the supervision of Prof. Mohamed-Slim Alouini. We congratulate Dr. Sboui for his achievement​! Everyone at CTL wishes him all the best for the future.​ Committee Chairperson: Prof. Mohamed-Slim Alouini. Committee Members: Prof. Georgios Giannakis (University of Minnesota) Prof. Ahmed Kamal Sultan (KAUST) Prof. Basem Shihada (KAUST) Prof.​ Tareq Al-Naffouri (KAUST) Prof. Zouheir Rezki (University of Idaho). ​ Thesis Abstract: The current

Robots learn by checking in on team members

1 min read ·
Innovative drone designs and software enables a team of drones to work together in a coordinated approach.

Teaching algorithms to see

1 min read ·
Four hundred hours of video are uploaded to YouTube every minute. Other than using text to search the title, description or tags associated with a video, video content search is limited. In addition to helping users find content more quickly and accurately, the ability to search video content is of paramount importance to video platforms and advertisers. Last year, YouTube was embroiled in controversy after rolling video ads for Coca-Cola and Amazon, among others, were shown before racist and extremist content. Advertising content is a major revenue stream for video platforms like YouTube

KAUST Ph.D. student Matthias Mueller wins award for drone research

1 min read ·

UAV

KAUST Ph.D. student Matthias Mueller, who works in the Image and Video Understanding Lab under the supervision of KAUST Associate Professor Bernard Ghanem, won the Best Paper/Presentation Award at the 2nd International Workshop on Computer Vision for Unmanned Aerial Vehicles (UAVs). UAVs are commonly known as drones. The workshop was held in September 2018 in Germany in the post-proceedings of the 15th European Conference on Computer Vision workshops. Müller's paper entitled "Teaching UAVs to Race: End to End Regression of Agile Controls in Simulation" outlines the research of Müller and his

Beyond self-driving simulations: teaching machines to learn

1 min read ·
Teaching has the power to test the limits of one's knowledge. Teaching algorithms to learn using machine learning is making it possible for cars to do away with human drivers in the near future, but this has also opened up new questions about the limits of our knowledge of the brain and learning. Bernard Ghanem, KAUST associate professor of electrical engineering from the University's Visual Computing Center and principal investigator of the Image and Video Understanding Lab, applies machine learning techniques to computer vision for automated navigation (for example, self-driving cars and

ISL PhD Student Osama Bushnaq does Internship at UBC

1 min read ·

UAV IoT

ISL PhD Student Osama Bushnaq did an internship at the University of British Coloumbia in Canada. His internship was focused on UAV-IoT. Every year, an average of 2.5 million hectares (ha) is burnt only in Canadian forests, which costs around 500 million to 1 billion Canadian dollars per year. The current forest fire detection methods such as satellite imaging and infrared cameras are not reliable. In order to detect forest fires before getting out of control, a new fire detection method based on Unmanned Aerial Vehicle Internet of Things (UAV-IoT) network was studied during this internship. A

Global access to the internet for all (GAIA): A great opportunity for the 5G/6G era

1 min read ·

5G UAV MIMO

The CTL alumni Dr. Qurrat-Ul-Ain Nadeem has published the article "The Fourth Use Case for 5G: Internet for All" in the Marconi Society blog. Read the full article from the Marconi Society website

Unleashing the potential of networked tethered flying platforms (NTFPs)

1 min read ·
The Sixth Generation (6G) of mobile networks is expected to be a game-changer in the telecom industry with applications and services such as enhanced mobile communications, increased indoor positioning accuracy, holographic telepresence, tactile communications, extended reality, and worldwide connectivity. 6G will rely on terrestrial networks such as tower masts and Non-Terrestrial Networks (NTNs) such as satellites, High-Altitude Platforms (HAPs), and Unmanned Aerial Vehicles (UAVs). To complement this communication ecosystem and cope with the shortcoming of these platforms another type of

Neil Smith

Research Scientist, Computer Science
Neil Smith is a Research Scientist in the Computational Imaging Group (VCCIMAGING) working with Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Neil joined University of California in San Diego (UCSD) at the start his academic journey. He obtained his bachelor degree in Anthropology with Concentration in Archaeology in 2001. After that in 2003, he received his master degree in Anthropology. He has a doctoral in Anthropology since 2009. Dr. Smith started his career life as a Geographic Information Systems (GIS) Specialist at

Mohammed Aldosari

Ph.D. Student, Mechanical Engineering
Education 2021.08 - Present Ph.D. Student in Mechanical Engineering, KAUST, KSA 2018.08 - 2020.06 M.S. in Mechanical Engineering, KAUST, KSA 2011.08 - 2016.05 B.Sc. in Aerospace Engineering, KFUPM, KSA Professional Profile 2022.01 - 2022.05 Teaching Assistant, CEMSE, KAUST, KSA 2017.07 - Present Researcher, Center of Excellence for Aeronautics & Astronautics, King Abdulaziz City for Science and Technology, KSA 2017.04 - 2017.07 Maintenance Planning Engineer, SaudiGulf Airlines, KSA Selected Publications M.N.Aldosari, K.K.Yalamanchi, X. Gao, S.M. Sarathy, "Predicting entropy and heat capacity

Kuat Telegenov

An experienced Robotics Research Engineer and Laboratory Manager.

Hajar El Hammouti

Postdoctoral Research Fellow, Electrical and Computer Engineering
Publications dblp Scopus LinkedIn Education Profile Ph.D. in Telecommunications and Computer Science, National Institute of Posts and Telecommunications (INPT), Rabat, Morocco, Jan. 2013- May. 2017. 3rd year of engineering studies at ENSEEIHT, Toulouse, France, 2011-2012. Engineering studies at INPT, Rabat, Morocco, 2009 - 2011. Awards and Distinctions Best Paper Award, UNet 2018. Best Student Paper Award, WINCOM 2015. Best Student Paper Award, NETYS 2015.

Bernard Ghanem

Professor Ghanem's research focuses on computer vision and machine learning, emphasizing large-scale video understanding, vision for automated navigation and theoretical foundations.