An MBZUAI team won the Cisco Sustainability Challenge with 'Energy for the People,' an AI-powered solution to improve the national energy grid. The system uses an AI-based rewarding system to motivate energy efficiency among residential energy consumers. The winning team received a six-month mentorship from Cisco experts to develop the project further. Why it matters: The solution addresses the UAE's Energy Strategy 2050 goals to reduce carbon footprint by 70% and increase clean energy consumption by 50% by leveraging AI for sustainable solutions.
A team of MBZUAI students won the Pioneers 4.0 Hackathon by developing an AI-based predictive maintenance solution using sensor data. The solution uses data preprocessing techniques and the Prophet model to identify anomalies in manufacturing, leading to energy savings and preventing sensor outages. The hackathon, organized by MoIAT and EDGE, involved 15 students from UAE universities. Why it matters: This highlights the practical application of AI skills being cultivated at UAE universities and their potential to address industrial challenges in line with the UAE's 4IR strategy.
Professor Mérouane Debbah, Chief Researcher at AIDRC, and his co-authors received the 2022 IEEE TAOS TC Best GCSN Paper Award for their work on federated quantized neural networks. The paper, presented at IEEE ICC 2022, explores the tradeoff between energy, precision, and accuracy in these networks. The research proposes an optimal quantization level to minimize energy consumption during training, making it less prohibitive for mobile devices. Why it matters: The award recognizes work that reduces the carbon footprint of large-scale AI systems, a key challenge for sustainable AI deployment in the region and globally.
MBZUAI students achieved top honors at the 2022 Dubai Roads and Transport Authority’s (RTA) Transport Hackathon. Sultan Abu Ghazal and his team developed Scooty, an app for scooter safety monitoring that rewards users for rule adherence. Muhammad Uzair Khattak led a team that created Salem, a mobile application to monitor motorcycle delivery drivers' safety and reduce traffic infractions by using computer vision and mobile sensors. Why it matters: The hackathon win highlights the practical AI skills being developed at MBZUAI and their application to real-world transportation challenges in the UAE.
This paper explores the use of deep learning for anomaly detection in sports facilities, with the goal of optimizing energy management. The researchers propose a method using Deep Feedforward Neural Networks (DFNN) and threshold estimation techniques to identify anomalies and reduce false alarms. They tested their approach on an aquatic center dataset at Qatar University, achieving 94.33% accuracy and 92.92% F1-score. Why it matters: The research demonstrates the potential of AI to improve energy efficiency and operational effectiveness in sports facilities within the GCC region.