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Results for "Brightskies"

KAUST, Intel, and Brightskies collaborate to develop self-driving mobility platform

KAUST ·

KAUST, Intel, and Brightskies have launched REDD, a collaborative self-driving mobility platform, converting a conventional car into a self-driving vehicle with integrated AI software. Brightskies developed the self-driving system, powered by Intel® NUC platforms, utilizing their BrightDrive system. KAUST researchers will use the vehicle to test new techniques, leveraging real-world data to improve self-driving technologies. Why it matters: This partnership advances autonomous vehicle research in Saudi Arabia, aligning with the Kingdom's Vision 2030 by creating a platform for innovation and testing in a real-world environment.

Pursuing blue skies research

KAUST ·

KAUST researchers presented their work on stabilizing nanoparticle catalysts at the 252nd American Chemical Society Meeting & Exposition. The team devised a "molecular Scotch tape" using a silica gel support coated with a single molecule layer of soft material containing sulfur. This approach allows nanoparticles to stick to one side while leaving the other side free for catalysis, preventing aggregation without killing the catalyst. Why it matters: This innovation in catalyst stabilization could lead to more efficient and sustainable chemical processes, impacting various industries.

Supporting malaria solutions

MBZUAI ·

Malaria No More, the Crown Prince Court of Abu Dhabi, and the Reaching the Last Mile program launched the Institute for Malaria and Climate Solutions (IMACS) to combat malaria amidst climate change. Mohamed Bin Zayed University for Artificial Intelligence (MBZUAI) joined as a technical partner, providing research support leveraging AI and data science. The initiative aims to develop and implement AI-driven strategies to address the impact of climate change on malaria transmission. Why it matters: This partnership highlights the UAE's commitment to using AI for global health challenges, particularly in combating climate-sensitive diseases like malaria.

Learned Optics — Improving Computational Imaging Systems through Deep Learning and Optimization

MBZUAI ·

KAUST Professor Wolfgang Heidrich is researching computational imaging systems that jointly design optics and image reconstruction algorithms. He focuses on hardware-software co-design for imaging systems with applications in HDR, compact cameras, and hyperspectral imaging. Heidrich's work on HDR displays was the basis for Brightside Technologies, acquired by Dolby in 2007. Why it matters: This research aims to advance imaging technology through AI-driven design, potentially impacting various fields from consumer electronics to scientific research within the region and globally.

Inspirational solar research

KAUST ·

KAUST hosted the Emerging Concepts and Materials in Solar Energy Conversion research conference from October 31 to November 2. The conference gathered scientists to discuss solar energy research, including perovskite solar cells, quantum dot solar cells, and photocatalysis. Rawabi Holding's chairman expressed pride in KAUST's solar research and its potential to address global challenges. Why it matters: By bringing together global experts and fostering discussions on innovative solar technologies, KAUST is contributing to advancements in renewable energy and sustainable solutions for the region.

The sky's the limit for FalconViz

KAUST ·

FalconViz is a startup originating from KAUST that specializes in scanning and documenting the world. The company aims to provide new methods for documenting environments, benefitting cities and countries. Co-founder Neil Smith highlights the company's success as a demonstration of KAUST's original vision for startups. Why it matters: FalconViz represents a successful commercial venture emerging from Saudi Arabia's KAUST, showcasing the potential for technology and innovation within the Kingdom.

Reinforcement learning-based dynamic cleaning scheduling framework for solar energy system

arXiv ·

This study introduces a reinforcement learning (RL) framework using Proximal Policy Optimization (PPO) and Soft Actor-Critic (SAC) to optimize the cleaning schedules of photovoltaic panels in arid regions. Applied to a case study in Abu Dhabi, the PPO-based framework demonstrated up to 13% cost savings compared to simulation optimization methods by dynamically adjusting cleaning intervals based on environmental conditions. The research highlights the potential of RL in enhancing the efficiency and reducing the operational costs of solar power generation.

Future food security with algorithms and drones

MBZUAI ·

MBZUAI students Mugariya Farooq and Sarah Al Barri created a machine learning framework that classifies plant diseases from images and predicts yield using data inputs. Their project won second place at the Agritech Hackathon organized by the Abu Dhabi Agriculture and Food Security Authority (ADAFSA). The algorithm boasts accuracy above 99% when tested against agricultural scientists. Why it matters: This work showcases AI's potential to revolutionize agriculture in the UAE and the broader MENA region by improving food security, reducing waste, and optimizing resource allocation.