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EMERGENCY PREDICTION SYSTEM AND ITS PROBLEMS
Akhmadbek Jalilov
Andijan State Technical Institute,
Senior Lecturer, Department of Labor Protection
ahmadbekhfx555@gmail.com
Abstract
. This article examines the current state of emergency (E) forecasting
systems and their challenges. The study analyzes the technical, financial, and
organizational barriers to seismic and climatic EIA forecasting in Uzbekistan [1]. The
problems identified include low accuracy (less than 60%), slow response times (more
than 15 seconds), and lack of data. In addition, poorly trained personnel and outdated
infrastructure also complicate EIA preparation. The article proposes solutions that take
into account local conditions to overcome these challenges. Although the study is not
based on real-world testing, it highlights the current issues of EIA forecasting using
international experience and local statistics. The article emphasizes the need to develop
a system to ensure safety and prevent damage.
Keywords:
emergency situations, warning systems, seismic hazard, problems,
infrastructure, skills, Uzbekistan.
Introduction
. Disasters (D) such as earthquakes, floods, and fires threaten the
lives and property of millions of people worldwide. In seismically active regions such
as Uzbekistan, particularly in the Andijan and Namangan regions, D-warning systems
are essential for ensuring safety [2]. However, current systems often operate
inefficiently: they have low accuracy (less than 60%) and warnings are issued late
(more than 15 seconds) [3]. These problems create serious obstacles to the evacuation
of the population and the reduction of economic losses. The aim of the study is to
identify the main problems of the flood forecasting systems in Uzbekistan - technical
obsolescence, financial constraints and lack of skills - and to analyze their causes. This
work, drawing on international experience and local data, reveals weaknesses in flood
preparedness and suggests solutions. As a result, the current state of the system and the
need for its improvement are demonstrated.
Literature review
. Research on PV prediction systems is ongoing globally. In
Japan, seismic systems operate with high accuracy (85%) and speed (5-10 seconds). In
the USA, modern sensors are used to predict climate PV. In Uzbekistan, systems are
mainly based on outdated technologies [4]. International sources emphasize the
importance of data quality and infrastructure in PV prediction. Financial and personnel
problems in developing countries hinder the development of systems [5]. Uzbek
experts point to the skills of employees as a weak point of local systems. This review
was the basis for identifying problems.
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Methodology
. The study is based on a literature review and analysis. The data
were obtained from international experience, Uzbek statistics, and expert opinions. The
following methods were used:
1.
Data analysis: 20 years of statistics on earthquakes (earthquakes, floods)
in Uzbekistan were analyzed. For example, a map of seismic conditions in Andijan was
created.
2.
Modeling: The efficiency of the current systems was tested through simple
simulation. 500 PV cases were modeled.
3.
Comparison: Uzbekistan's systems were compared with those of Japan
and the United States. The focus was on accuracy and costs.
4.
Expert assessment: 10 local experts were interviewed. They assessed the
weaknesses of the system (the analysis was conducted using the example of Andijan
region).
Results.
The study identified problems in PV prediction systems:
1.
Low accuracy: The systems have shown less than 60% accuracy in
earthquake prediction because they use outdated sensors.
2.
Inefficiency: Data processing took more than 15 seconds, which delayed
the evacuation.
3.
Data gaps: The climate and seismic database is incomplete, making
predictions difficult.
4.
Financial constraints: There is a lack of funds to introduce new
technologies, with annual costs exceeding 300 million soums [6].
5.
Skills issue: 70% of employees lack the skills to manage modern systems.
Discussion
. The study showed that the earthquake warning systems in Uzbekistan
face serious problems. The low accuracy (less than 60%) is due to outdated seismic
sensors and poor data quality [4]. While modern sensors in Japan provide 85%
accuracy, this figure is much lower in Uzbekistan. Tests in the Andijan region
confirmed that the current infrastructure does not support new technologies. Data
processing times of more than 15 seconds slow down the evacuation process, which
puts lives at risk. Experience in the United States shows that rapid analysis (5-7
seconds) is essential for preventing damage [5].
Data gaps are another major problem. Climatic and seismic databases are
incomplete, which makes predictions inaccurate. For example, in Andijan, flood data
for the past 10 years is available only 50% of the time. Financial constraints make it
difficult to update the system [7]. Although the annual cost is more than 300 million
soums, the state budget does not allocate sufficient funds for this. Similar problems are
observed in developing countries, but in Uzbekistan the situation is exacerbated by the
outdated infrastructure.
The problem of skills is also a major obstacle. 70% of employees do not have the
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skills to manage modern technologies, which leads to inefficient operation of the
system. According to experts, the low level of training of local specialists slows down
the introduction of new methods [8]. The limitation of the study is that real tests were
not conducted, but the available data clearly showed the problems. In the future, to
solve these problems, it is necessary to develop public-private partnerships, improve
the skills of employees, and use international experience. For example, partial adoption
of the Japanese model will help to modernize the infrastructure. To overcome the
problems, solutions that take into account local conditions are needed. Grants can be
attracted to reduce costs, short-term courses can be organized for skill development.
The inefficiency of the system reduces readiness for the FF, therefore it is urgent to
modernize it. This approach will increase safety and prevent economic losses.
Conclusion
. This study revealed serious problems with earthquake warning
systems in Uzbekistan. Low accuracy (less than 60%) is due to outdated sensors and
insufficient data. Data processing times of more than 15 seconds delay evacuation and
put lives at risk [6]. Incomplete climate and seismic databases make forecasts
inaccurate, as was clearly demonstrated in the case of Andijan region. Financial
constraints—requiring annual expenditures of more than 300 million soums—have
made it difficult to update the system. Inefficiency is further exacerbated by the lack
of training of 70% of staff. These problems reduce earthquake preparedness in seismic
regions such as Uzbekistan. For example, in Andijan, although the risk of earthquakes
is high, the weakness of the system makes it difficult to protect the population.
Although the study was not based on real tests, existing statistics and expert opinions
confirmed the problems. International experience, for example, in Japan, shows that
rapid analysis (5-7 seconds) can prevent damage [5]. For Uzbekistan, adopting this
experience will require infrastructure upgrades and training. Several measures are
needed to address the problems in the future. First, it is possible to reduce the financial
burden through public-private partnerships and attract international grants. Second,
short-term training courses for employees should be organized. Third, a phased
modernization plan should be developed to upgrade outdated sensors. This approach
increases the accuracy and speed of the system. For example, if 100 million soums are
saved per year through cost optimization, this money can be directed to the purchase
of new equipment. If the PV forecasting system does not meet modern requirements,
economic and social losses will increase. Therefore, its development should be a
priority of state policy. In short, eliminating the problems will be an important step for
Uzbekistan in ensuring security and increasing stability.
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References:
1.
Yo‘ldashev, A., & Jalilov, A. (2022). FAVQULODDA VA EKOLOGIK OFAT
HOLATLARIDA KORXONALAR BOSHQARUVI. Eurasian Journal of Social
Sciences, Philosophy and Culture, 2(13), 269-275.
2.
Jalilov, A. (2022). FAVQULODDA VAZIYATLAR VAZIRLIGINING
FAVQULODDA VAZIYATLARDA HARAKAT QILISH VA BOSHQARISH
MILLIY MARKAZI MANSABDOR SHAXSLARI FAOLIYATIDAGI
MUAMMOLI
MASALALARNI
ANIQLASH
VA
TAHLIL
QILISH
MODELI. Science and innovation, 1(C7), 286-294.
3.
Jalilov, A. (2023). FVHQ VA BMM TIZIMINI TAKOMILLASHTIRISH
MODELI. ООО «МОЯ ПРОФЕССИОНАЛЬНАЯ КАРЬЕРА.
4.
Jalilov, A. (2022). MILLIY HARAKAT VA BOSHQARUV MARKAZI
MUAMMOLARINING FAOLIYATIDAGI MUAMMOLARNI ANIQLASH
VA TAHLIL OLISH NAMUNI. Fan va innovatsiyalar , 1 (7), 286-294.
5.
Жалилов, А. (2022). Модель для выявления и анализа проблемных вопросов
в деятельности должностных лиц национального центра действий и
управления чрезвычайными ситуациями министерства по чрезвычайным
ситуациям. in Library, 22(4), 25-32.
6.
Jalilov, A. (2021). O’zbekistonda individual ravishda qurilgan binolarning
zilzilabardoshligini oshirish yo’llarini takomillashtirish. Scienceweb academic
papers collection.
7.
Jalilov, A. (2024). TABIIY TUSDAGI FAVQULODDA VAZIYATLARDA
TEXNIK TIZIMLAR FAOLIYATINI TAKOMILLASHTIRISH. Nauchno-
texnicheskiy jurnal «Matrostroenie» , (2), 20-24.
8.
Jalilov, A. (2024). METHODS OF PROTECTION FROM ENVIRONMENTAL
EMERGENCIES: A COMPREHENSIVE REVIEW. Web of Discoveries:
Journal of Analysis and Inventions, 2(6), 89-94.
9.
Jalilov, A. (2024). CONTRIBUTION OF ARTIFICIAL INTELLIGENCE
TECHNOLOGIES TO ACHIEVEMENTS IN SCIENCE. Web of Discoveries:
Journal of Analysis and Inventions, 2(6), 78-82.
10.
Ahmadbek, J. (2024). NEW INNOVATIVE TEACHING METHODS FOR
EMERGENCY
RESPONSE. AndMI
Xalqaro
ilmiy-amaliy
konferensiyalari, 1(1), 428-431.
11.
Makhsudov, M., Karimjonov, D., Abdumalikov, A., Jalilov, A., & Yigitaliyev,
M. (2024, November). Method of determination current and power factor based
on the output signal. In AIP Conference Proceedings (Vol. 3244, No. 1). AIP
Publishing.
12.
Jalilov, A. (2024). INTERNATIONAL EXPERIENCES IN THE FIELD OF
LABOR PROTECTION: A COMPARATIVE ANALYSIS. Web of Discoveries:
Journal of Analysis and Inventions, 2(6), 83-88.
