Makkah's Grand Mosque Gets Improved Connectivity, AI Applications through High-Tech Upgrade

A view of the Grand Mosque in the holy city of Makkah, Saudi Arabia. (SPA)
A view of the Grand Mosque in the holy city of Makkah, Saudi Arabia. (SPA)
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Makkah's Grand Mosque Gets Improved Connectivity, AI Applications through High-Tech Upgrade

A view of the Grand Mosque in the holy city of Makkah, Saudi Arabia. (SPA)
A view of the Grand Mosque in the holy city of Makkah, Saudi Arabia. (SPA)

Saudi Arabia’s Ministry of Communications and Information Technology (MCIT) and the Royal Commission for Makkah City and Holy Sites (RCMC) announced that Makkah's Grand Mosque has undergone a significant technology upgrade to better serve worshippers.

The project, carried out in collaboration with the Ministry of Finance, the General Authority for the Care of the Affairs of the Two Holy Mosques, and national technology and digital companies, aims to improve the worshippers’ experience through advanced infrastructure, AI applications, and the innovative neutral host model.

The project leverages 5G capabilities and AI to facilitate crowd and vehicle management, improve asset management, and implement smart waste disposal systems.

The upgraded infrastructure opens the door to the provision of virtual medical clinic services at the Grand Mosque.

Utilizing the Internet of Things (IoT), the project enables real-time monitoring of the Zamzam well's water level and production.

Download speeds within the Grand Mosque have tripled, reaching over 1 gigabit per second, thanks to network upgrades on the ground floor of the third Saudi expansion building.

The project utilizes the neutral host model, a crucial element to providing advanced technical infrastructure based on 5G, data, and AI. The model enables multiple mobile network operators, including STC, Mobily, and Zain, to share the physical infrastructure within the Grand Mosque, ensuring that all visitors have access to the highest level of communication services.

This project, implemented by the Advanced Communications & Electronic Systems Company (ACES), is an example of a collaborative effort to achieve the goals of Saudi Vision 2030.

Deputy Minister for Telecom and Infrastructure at MCIT Eng. Bassam Al-Bassam said: "There is nothing more honorable than serving visitors of the Grand Mosque. We are continuously working with our partners to provide the latest technologies and improve the visitor experience."

RCMC CEO Eng. Saleh Al-Rasheed highlighted the project's contribution to "providing an advanced digital infrastructure in the Grand Mosque" and "raising the level of communication services" for all visitors.

This technology upgrade is proof of a commitment to utilize cutting-edge solutions for a more efficient and connected Grand Mosque, ultimately serving millions of worshippers throughout the year.



SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI

SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI
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SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI

SDAIA, KAUST Launch MiniGPT-Med Model to Help Doctors Diagnose Medical Radiology through AI

The Center of Excellence for Data Science and Artificial Intelligence at the Saudi Data and Artificial Intelligence Authority (SDAIA) and King Abdullah University of Science and Technology (KAUST) have introduced the MiniGPT-Med model.

The large multi-modal language model is designed to help doctors quickly and accurately diagnose medical radiology using artificial intelligence techniques.

Dr. Ahmed Alsinan, the Artificial Intelligence Advisor at the National Center for Artificial Intelligence and head of the scientific team at SDAIA, explained that the MiniGPT-Med model is capable of performing various tasks such as generating medical reports, answering medical visual questions, describing diseases, locating diseases, identifying diseases, and documenting medical descriptions based on entered medical images.

The model was trained on different medical images, including X-rays, CT scans, and MRIs.

The MiniGPT-Med model, derived from large-scale language models, is specifically tailored for medical applications and demonstrates significant versatility across different imaging methods, including X-rays, CT scans, and MRI. This enhances its utility in medical diagnosis.

Dr. Alsinan highlighted that the MiniGPT-Med model was developed collaboratively by artificial intelligence specialists from SDAIA and KAUST.

The model exhibits advanced performance in generating medical reports, achieving 19% higher efficiency than previous models. It serves as a general interface for radiology diagnosis, enhancing diagnostic efficiency across various medical imaging applications.