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The article examines the methodology for assessing the public safety in the Smart City project. The content of the city IQ subindex “Intelligent public safety systems”, indicators, criteria and mathematical formulas by which this subindex is evaluated are considered. Using the example of the city of Ufa, the study analyses the dynamics of changes in the subindex from 2018 to 2020, as well as the factors influencing the achieved indicators and their final impact on the Ufa IQ index. The research aims to develop a mathematical model for improving the IQ of Ufa according to the subindex “Intelligent public safety systems” based on the available mathematical formulas for evaluating individual indicators of the smart city, choosing priority areas for improving the Ufa IQ. Using the algorithm and methodology for deriving the final formula for subindex No. 3, the same functions for other subindexes were simulated in a similar way. On their basis, the final model for increasing the total IQ of any city can be simulated. Статья посвящена изучению методики оценки безопасности жизни населения в проекте «Умный город». Рассмотрено содержание субиндекса IQ города «Интеллектуальные системы общественной безопасности», показатели, критерии и математические формулы, по которым производится оценка этого субиндекса. На примере города Уфа проанализирована динамика изменения субиндекса с 2018 г. по 2020 г., изучены факторы, повлиявшие на достигнутые показатели и их итоговое влияние на индекс IQ Уфы. Основная цель статьи: разработка математической модели повышения IQ Уфы по субиндексу «Интеллектуальные системы общественной безопасности» на основе имеющихся математических формул для оценки отдельных индикаторов «умного города», выбор приоритетных направлений повышения IQ Уфы. Используя алгоритм и методику выведения итоговой формулы для субиндекса № 3, можно аналогичным путем смоделировать такие же функции для других субиндексов и на их основе смоделировать итоговую модель для повышения суммарного IQ любого города.

In this paper we present an integrated system for intelligent video surveillance, control and alarm generation in security applications related to protection of public buildings (e.g. various financial institutions). By using only two networked cameras, video information is collected, dispatched via network and processed on-line with a group of integrated image processing algorithms able to detect humans in motion, track their motion, and check the visibility of their faces while entering the building. In addition, the developed system counts peoplepsilas traffic and keeps the record of a number of people in the protected area. The integration of given algorithms is made in order to raise the reliability of the threat recognition. The emphasis is on the fast detection of the invisible (masked) face of the approaching person. Based on the outputs of the algorithms, either alarm generation or adequate control actions may take place.

In this paper we present an integrated system for intelligent video surveillance, control and alarm generation in the security applications related to protection of public buildings (e.g. various financial institutions). By using only two networked cameras, video information is collected, dispatched via network and processed on-line with a group of integrated image processing algorithms able to detect humans in motion, track their motion, and check the visibility of their faces while approaching the building. In addition, the developed system counts people’ s traffic and keeps the record of a number of people in the protected area. The integration of given algorithms is made in order to raise the reliability of the threat recognition. The emphasis is on the fast detection of the invisible (masked) face of the approaching person. Based on the outputs of the algorithms, either alarm generation or adequate control actions may take place.