Qatar Football World Cup: Doha Municipality adopts plan to address public hygiene violations during

Qatar Football World Cup: Doha Municipality adopts plan to address public hygiene violations during FIFA World Cup 2022 Doha Municipality has adopted a plan to deal with any violation of the Public Sanitation Act No. 18 of 2017 during the FIFA World Cup 2022 later this year, which includes reports of dumping of garbage, discarded vehicles, advertising violations, and violations of public squares, among others.

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Speaking to the local Arabic newspaper Arrayah, Hamad Sultan al-Shahwani, director of the Doha Municipality's general management unit, said inspectors in this section would focus on key areas of Doha as there are two stadiums under municipal control, Al Thumama Stadium and Stadium 974.

He emphasized that the Doha Municipality was committed to fully preparing and upgrading these facilities for tourists, while also looking at all other areas within the municipality. Al-Shahwani noted that the inspectors of this section will work two shifts, from 12 noon to 10 pm and from 10 pm to 5 am, in addition to having several dedicated inspectors assigned to receive any complaints or reports related.

In addition, management staff will continue to work during the morning shift. Al-Shahwani pointed out that the general regulatory body has conducted intensive surveillance campaigns to emphasize the need for shopkeepers to obtain a legal license for their advertisements and advertisements in the municipality. This has been instrumental in reducing the number of related offenses by more than 60%.

The Department warns against copying the FIFA World Cup logo on vehicle numbers The Qatar Interior Ministry said that the number of vehicles with the FIFA World Cup logo was a special version sold by it and could not be copied or pasted into all vehicles. It warned that action would be taken against anyone who copied a FIFA World Cup logo with car numbers.

In the announcement of the Terms and Conditions of the Qatar World Cup 2022 logo on car numbers, he added that special number plate plates with the Qatar Football World Cup logo are being sold at auction following certain terms and conditions in collaboration with the International Football Association FIFA, for new cars only registered and special plate auction numbers only.

It went on, too, that it is not allowed to copy and mark the FIFA World Cup on car plates. Anyone who violates this will be subject to legal action and will be brought before the authorities for legal action. For more to know about Qatar World Cup tickets Click here.

Qatar University develops a crowd management program during the FIFA World Cup In collaboration with the Executive Committee of Inheritance (SC), Qatar University (QU) College of Engineering has developed intelligent crowd management and control systems, which include multiple components of census counting, face recognition, and special event detection (AED).

A team of QU researchers, led by Prof. Sumaya Al Maadeed as the lead investigator in the study, includes Dr. Noor Al Maadeed, Associate Dean of Graduate Studies for Academic Affairs, and Professor of Computer Engineering, Dr. Khalid Abualsaud, Lecturer in Computer Engineering.

Prof. Amr Mohamed, Professor of Computer Engineering, Prof. Tamer Khattab, Professor of Electrical Engineering and Acting Executive Director at the teaching and learning center, Drs. Yassine Himeur, Postgraduate Researcher, and Drs. Omar Elharrouss. Post-doctoral researcher, Najmath Ottakath, Master's student.

The safety and security of the players, spectators, and others related to the FIFA World Cup 2022 is among the attention of the organizing committee. In general, security risks increase several times over, considering the size of the event and the significant number of fans expected to attend over 1.5 million fans.

Therefore, the security of the Qatar World Cup 2022 is a challenge due to the increasing number of potential threats and the use of technology. Managing crowds at FIFA World Cup stadiums and borders is important to ensure safety and smoothness at Football World Cup events due to the natural closure and overcrowding inside and outside the stadiums.

Qatar World Cup 2022 will rely on the use of state-of-the-art technology, such as surveillance drones, ICT, and AI, to improve crowd management. In this case, a team of QU researchers first developed a system to calculate masses from drone data, using expanded neural networks to extract relevant features and demographics.

Additionally, a new set of census data for sports facilities called Football Supporters Crowd Dataset FSCSet was introduced. It includes 6,000 hand-painted images of various scenes, featuring thousands of people assembling in or near theaters. The efforts of the research team also focused on developing a facial recognition system, processing faces less than pose variations using a multitask convolutional neural network CNN. For more to know about Football World Cup tickets Click here.

Specifically, cascade formations were used to integrate the positioning system and the face recognition module. The CNN-based measurement method is trained in three categories of facial images, which include left-facing, front, and right-side photography. Going forward, three CNN buildings, namely VGG16 + PReLU on the left, VGG-16 + PReLU on the front, and VGG-16 + PReLU on the right, have been planted to identify the face based on a limited area.

Additionally, a skin-based face recognition system, based on architecture and color definition, has been introduced to remove useless facial information e.g., background content. Powerful testing was performed on four popular face recognition data sets, in which the proposed system overworked the related high-level related schemes.

To that end, a team of researchers, led by Prof. Al Maadeed, developed the novel AED, which aims to learn unusual actions using both common and unusual parts. It allows you to avoid the annotation of unusual events in video sequencing training to reduce computational costs and thus be easier to use on drones. Thus, rare cases are studied using an in-depth system, which uses a series of training videos with weak annotations. Simply put, training annotations are included in full videos instead of specific clips.

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