AL ARBA'IN

Steganography is a data security method that conceals information within a medium, ensuring no suspicion about a link between two parties. During the Arbaeen pilgrimage, a study used the least significant bit (LSB) concealment method, extracting letters from text within a coloured digital image, converting them into binary numbers, and embedding them within the image. This process resulted in an image containing textual information, allowing comparison with the original image to observe additive noise differences. The most significant noise effects were observed in homogenous areas and edge regions, with a pronounced impact of masking across all color packets. The study used statistical metrics like mean square error (MSE) and peak-to-noise ratio (PSNR) to analyze the quality and effectiveness of the outputs. The best stenographic effect occurs when the message size is small, the image size is large, and there are fewer bits to be hidden. The best reduction effect is achieved when the message size is small and the image size is large, with fewer bits to hide. The blue, red, and green bars exhibit the best steganography effects, ensuring the security of pilgrims in Karbala Governorate and elsewhere, and facilitating easy and secure data transmission.

In this paper ,we use one of mathematical crowd models to represent
the movement of crowds arriving for the Arbaeen pilgrimage Specifically,
we aim to understand the dynamics of crowds on the road between the two
holy mosques. Firstly, we introduce the proposed Mathematical crowd
motion. In this model, we define a spontaneous speed corresponding to
the speed each individual would like to reach in the absence of others. The
actual speed is then calculated as a projection of the spontaneous speed
onto a set of feasible speeds (i.e., speeds that do not violate the non-interference constraint). Secondly, the numerical computations are conducted
using finite difference method and projection techniques. We also perform numerical simulations using an (Open AI, 2025).The obtained results can assist in designing emergency exits, reducing congestion, and
improving crowd distribution.

The Arbaeen pilgrimage continuous to show increase in the size of the
crowed, emphasizing the essential demand for precise analytical system
to optimize crowed organization, service managing, and decision support.
The present work develops two frameworks that employ predictive statistical modeling combined with contemporary artificial intelligence based
solutions for managing this extensive religious occasion. In this regrad,
the first framework involves a thorough analysis on established and other types of forecasting methods such as Box–Jenkins time series models,
nonparametric regressions (Nadaraya–Watson and Epanechnikov kernels),
and so on. One-way ANOVA—combined with multilayer perceptron
models applied to forecast health indicators such as pilgrim birth rates.
Inspired by best practices in the classification of Arbaeen films; the second framework proposes Comparison Replicating best practices from the
Arbaeen film scene classification, the second strand, a video scene recognition method is proposed based on transfer learning from Inception V3
and VGG-16. These neural networks trained to recognize and distinguish
between images from the Arbaeen procession and other mass gatherings,
this system improves deeper machine-based understanding of context and
support the implementation of AI-driven surveillance systems.Using transfer learning results in ingesting and interpreting largescale pilgrimage data.
Engineered to suit Arbaeen’s distinct characteristics,this plan also provides
a flexible foundation for managing similar large-scale events such as other
eligious or public gatherings. To support real time monitoring we explore
visual scene recognition after presenting forecasting

Millions of Shia Muslims travel to Karbala, Iraq, for the Arbaeen Pilgrimage, one of the biggest religious gatherings in the world, which honors Imam
Hussein’s martyrdom (as). Despite the event’s great spiritual and cultural significance, the risks of diseases transmission, overcrowding, and poor sanitation present serious public health issues. Due to congestion, poor sanitation, and the possibility of infectious disease epidemics, the Arbaeen pilgrimage one of the biggest yearly religious mass gatherings brings millions of pilgrims to Iraq and presents serious public health issues. With an emphasis on monitoring tactics, patterns of antimicrobial resistance (AMR), and control approaches, this review summarizes the state of knowledge regarding microbial diseases linked to the Arbaeen pilgrimage. AMR is a growing threat, and respiratory and gastrointestinal bacteria are important pathogens. We draw attention to deficiencies in international cooperation, vaccine coverage, and real-time illness monitoring for efficient infection management. To reduce health risks, recommendations include multi-sectoral collaboration, pre-travel health education, and improved syndromic surveillance. Arbaeen is linked to epidemics of infectious diseases, such as meningococcal disease, respiratory infections, diarrheal ailments, and blood-borne pathogens, just like other large gatherings like the Hajj. Vaccination requirements, hygiene promotion, and real-time genomic surveillance are examples of current surveillance and preventative tactics that have been successful in reducing risks at similar events. Systematic research on the health effects unique to Arbaeen is still lacking, though. In order to address new dangers (such as antibiotic resistance and climate-sensitive diseases) and guarantee pilgrim safety, this assessment emphasizes the critical need for specialized interventions, global cooperation, and enhanced preparedness frameworks. To protect health during Arbaeen and in the future, lessons learned from international mass gatherings highlight the significance of comprehensive prevention, quick diagnosis, and cross-border collaboration

In this work explores the optimal placement of piezoelectric energy
harvesting systems in the holy city of Karbala, Iraq, using (RS) and (GIS)
Techniques. Piezoelectric technology, which converts mechanical energy
from foot traffic and vehicular movement into electricity, offers a sustainable energy solution for high-pilgrimage areas Case Study (Arbaeen anniversary). By integrating spatial data, including pedestrian density, road networks, and land use patterns derived from satellite imagery and GIS analysis, this research identifies the most suitable locations for piezoelectric installations to maximize energy generation. Multi-criteria decision
analysis (MCDA) techniques were applied to evaluate factors such as urban mobility, religious event schedules, and infrastructure suitability. The
results highlight key zones near holy shrines (Al-Abbasia and, Al-Hussinnaa) walkways, and major roads where piezoelectric tiles can efficiently harness energy from the constant movement of pilgrims. The Roads map results were extracted using the Arc-GIS Pro software

This paper presents the design of a new stream cipher cryptosystem
(CS) with a new Key Generator (KG). Firstly, we presented the mathematical model of the new CS, which is based on Linear Feedback Shift
Registers (LFSR) units with non-linear combined functions to increase
the complexity of the design CS. This cryptosystem can be used to protect
data transmitted (online or offline) during the Arbaeen pilgrimage commemorating Imam Hussein's martyrdom, peace be upon him, whether by
pilgrims or/and military protection units affiliated with the army or police.
To test the output key results, we apply Basic Efficiency Criteria (BEC) to
the suggested KG. The results of using BEC demonstrate the robustness
and efficiency of the new stream cipher CS.

This study presents a case study for extracting energy from the footsteps of participants during the Arbaeen pilgrimage in Karbala. It employ
piezoelectric energy-harvesting techniques in conjunction with cloud data
aggregation. A cost-efficient approach will be devised to capture energy
produced by foot pressure and transform it into electrical energy, employing recycled plastic materials incorporated into walkways. Rechargeable
batteries are employed to store gained energy. The energy management
system proficiently controls the stored energy to ensure effective and reliable charging. The method offers a clean, sustainable, and renewable energy source in high-traffic locations, such as during the Arbaeen pilgrimage. This project illustrates the transformation of commonplace human
movement into energy generation. This study facilitates the development
of improved, more sustainable urban systems by illustrating how quotidian human movement may be converted into usable energy, particularly in
vibrant, religious locations such as Karbala.

Objective: This research study focuses on understanding cybersecurity
threats of Internet of Things (IoT) devices with special attention towards
cyber attacks that relate to mega events such as Arbaeen Pilgrimage. With
an objective to guard the users and their equipment in a mega event scenario, this project would identify weaknesses of the IoT system, develop
means for cyber threat detection and also give recommendations for risk
neutralization in an efficient manner.
Methodology: A mixed-method strategy combining qualitative and
quantitative research methods is employed in this research. A thorough
review of the existing body of research on IoT security issues and attack
techniques is conducted. In addition to this, primary data from surveys
and expert interviews conducted with cybersecurity professionals are
utilized. In order to analyze actual vulnerabilities in IoT systems, a case
study on the Arbaeen Pilgrimage is studied. Cyber threat detection models
are created by applying machine learning methods, and simulation tools
are used to check how well the mitigation techniques work.
Key Findings: IoT devices are particularly vulnerable to all types of
cyberattacks, including DDoS, unauthorized access, and data breaches,
particularly during peak events like the Arbaeen Pilgrimage. Existing
IoT security measures often fail to detect and prevent these threats in real-time, putting both users and devices at risk. Nevertheless, the study
of suspicious activity patterns and anomalies can serve as a strong base
in which machine learning algorithms might be useful for the identification and mitigation of cyber threats. Strong security features, including
intrusion detection systems, regular firmware upgrades, and multi-factor
authentication, must be incorporated into IoT devices for general security
enhancement and protection against future cyber threats.Implications: This study is critical implications for the field of cybersecurity, especially in terms of safeguarding IoT devices in expansive,
real-time settings. It guides the development of stronger security frameworks by bringing new insights into the specific vulnerabilities of IoT systems during critical events. The results further underscore how important
proactive threat detection and mitigation strategies are to safeguarding
users’ devices and data.
Specific Contribution: This research contributes to the field of IoT cybersecurity through a model that strengthens the identification and mitigation
of threats during major events through an integration of cutting-edge techniques in machine learning. This study provides a case-specific framework
for the Arbaeen Pilgrimage that can be adapted to other large-scale events
and shows that integrated security mechanisms are crucial. This work improves the knowledge of IoT vulnerabilities and offers practical ways to
fortify the overall security framework of IoT systems in dynamic settings.

The importance of the Movement of Imam Hussein from Mecca to
Karbala played a great and effective role in accomplishment Imam’s mission. The authors focused on the Kufi Hajj Route (Zubaydah Trail in Arabic Darb Zubaydah) as a basis for this study due to the abundance of
sources through which they can learn the ancient and numerous names of
the houses and stations on the route. Famous to Zubaydah Trail, it is comprised of the sites and ponds along the road. A study made to designate
precisely the names of all the sites and ponds along the road. Benefiting of
the modern technologies as a strong and effective tool for well managing
and study we used space applications technologies and engineering such
as GIS and remote sensing, telecommunications, artificial intelligence,
informatics, mathematics, statistics, and so on.
A satellite or aerial image of each site and a judicial image from Google
Maps for each site with the geographical coordinates were used. Putting
the geographical coordinates accurately is important bias because all references do not put the coordinates and if they do, they are either incorrect
or inaccurate. Furthermore, a framework for using space radar imagery
for some locations provided a valuable addition to our work.
In this paper, the authors with background in space science and technologies, and telecommunications focus on and highlight effectiveness
and importance of these fundamental and infrastructural technologies.
Authors believe that the joint work and cooperation of the organizational
and independent experts from the relevant entities and sharing knowledge
and experience can lead to increment of the synergy of work for well managing and control of the event.Authors, who are from Iraq and Iran, worked for long term in their
relevant national space technology and communication organizations in
both managerial and specialized levels. They share the feasible and accessible potentials and possibilities for well managing and control of the
sites under study. Authors determine the steps of ideas in order of priority
and importance, which inevitably involve creativity. They believe that the
idea of ​​experimenting with collaboration and remote work will certainly
yield success.

This research paper addresses the design of a solar-powered freshwater
production system, aiming to provide sustainable solutions for desalination, especially in water-scarce regions that benefit from high solar radiation. The research addresses how solar energy can be converted into
electricity to power desalination technologies, such as reverse osmosis.
The design process includes assessing the installation location, solar radiation intensity, and water demand before determining energy needs and
selecting appropriate desalination methods. The system is environmentally friendly, has low operating costs, and is capable of operating independently from conventional electrical grids, making it ideal for remote areas, especially during major events such as the Arbaeen pilgrimage, where a reliable supply of clean water is required. The results indicate the system’s ability to provide clean water at low operating costs and with high efficiency under variable solar radiation levels, reducing reliance on conventional energy sources. The system can also operate for extended periods at night thanks to the high battery storage capacity. The results also showed that the quality of the water produced by the system is high, with a saline concentration of 0.1%, demonstrating excellent purity and
suitability for consumption. The system can be expanded by incorporating solar panels and larger-capacity batteries to meet increased demand,
making it a sustainable, long-term solution. In this way, the study demonstrates the system’s importance in addressing challenges associated with drinking water in water-scarce areas, especially during major events such as the Arbaeen pilgrimage

This plastic recycling project seeks to minimize environmental pollution resulting from the accumulation of plastic waste by collecting, sorting, and processing it for reuse in the production of new, usable products.
This project aimed to contribute preservation of natural resources, by accumulating plastic in landfills and oceans and reduces dependence on virgin raw materials, in addition to decreasing carbon emissions. Moreover,
it raises environmental awareness while also providing employment opportunities in recycling factories through fields of collection, processing,
and manufacturing. The project constitutes a crucial step toward achieving sustainable development and a circular economy.
Large quantities of plastic waste have been observed during the Arbaeen
pilgrimage in the holy city of Karbala, one of the world’s largest human
gatherings. This waste primarily consists of water bottles and plastic utensils utilized by pilgrims and Hussaini service processions. While a portion
of this waste is sorted and collected systematically by service and volunteer
entities, a large portion ends up in general waste without being utilized.
This creates a genuine opportunity to capitalize on these large quantities of plastic through more efficient organization of collection and sorting
processes, in collaboration with municipal authorities and environmental
initiatives. These materials can be directed toward recycling facilities to
be transformed into new, usable products such as household items, benches, storage boxes, or even eco-friendly construction material

Designing a system for recycling plastic bottles in our research enabled
us to address the problem of plastic waste accumulating during the Arbaeen pilgrimage due to the large number of visitors. There are numerous
ways to recycle materials, including manufacturing suitable materials at
a low cost by recycling plastics with good mechanical properties to manufacture spare parts using 3D printing. PET was used for plastic bottles
by recycling it into filaments with specific specifications and thicknesses,
as determined by the system designed during the research. A 3D printer
was then used to print the filaments after shaping them and printing a
new material with new specifications. These filaments were used as raw
material, and a 3D printer (Ender 3 S1 Pro) was used to produce a material with better strength and hardness specifications for the filling ratios
during printing with best30% infill ratio. This allows for the printing of
models and designs that can serve to commemorate the anniversary.

This research examines the spatiotemporal dynamics of air pollutant
concentrations across the Baghdad-Karbala-Najaf corridor, leveraging
Doppler-based satellite remote sensing data. The analysis focuses on five
critical atmospheric contaminants: sulfur dioxide (SO₂), nitrogen dioxide
(NO₂), carbon monoxide (CO), ozone (O₃), and fine particulate matter
(PM₂.₅). Findings reveal pronounced variability in pollution levels, attributable to synergistic interactions between meteorological parameters and anthropogenic factors, with peak exacerbations observed during the Arbaeen pilgrimage a mass religious gathering. Urban centers in Baghdad
exhibited the highest baseline pollution concentrations, driven by vehicular density and industrial emissions, while Karbala and Najaf demonstrated episodic spikes correlated with large-scale religious events. Precipitation emerged as a statistically significant mitigating factor, particularly in
scavenging SO₂ and NO₂ from the atmospheric column. The study proposes evidence-based scientific and policy interventions, advocating for integrated sustainable urban planning, deployment of real-time air quality surveillance systems, and ecological mitigation protocols for managing high-density human congregations.

In a time of rapid digital transformation, demographic crowd analysis has become a mainstay of innovative city applications, especially in
crowd management, crisis forecasting, and sustainable urban planning.
Traditional crowd analysis models lack integration, accumulate errors due
to the separation of detection and classification, exhibit poor performance
in crowded conditions or inadequate lighting, and pose difficulties for real-time operation on edge modules (Elbishlawi et al., 2022; Gao et al.,
2024).
The research problem: the absence of a unified model capable of operating efficiently in real time while maintaining high accuracy and specificity (Bai et al., 2022; Li et al., 2024).
The research aims to design an intelligent, field-deployable system for
monitoring and classifying individuals during a visit to the fortieth, and
predicting crowd behavior, within a framework that respects data privacy
via federated learning. It evaluates it via the digital twin in a Simulink
environment.Despite the rapid progress in computer vision technologies over the past decade, traditional systems are still unable to meet the requirements of practical operation in high-density environments or non-ideal contexts, due to three fundamental gaps:
− The structural separation between the detection and classification tasks leads to an accumulation of errors by up to 42%.
− Contextual fragility, where the classification accuracy drops to 64% in the
absence of faces or deterioration of image quality.
− The intractable trade-off between accuracy and time performance hinders the operation of real-time systems in resource-limited edge environments [10] In response to these challenges, this research proposes an intelligent
multitasking system that combines unified processing, high precision, and
superior performance, and is based on four principal axes:
1. a unified architecture that combines the detection of individuals (F1 =
95.7%) and demographic classification (93.8%) in one model.
2. flexible hierarchical classification maintains an accuracy of 87.2% in
complex conditions (absence of faces, density > 15 people/M2).
3. It outperforms in terms of time and power, with an execution speed of
32.4 FPS and a power consumption of no more than 8.3 Watts.
4. an adaptive data generation methodology that addresses demographic
bias using variable contextual scopes.
The system’s efficiency was verified through a pilot evaluation on
62,855 images representing 12 realistic scenarios. The model exceeded
10 modern reference systems across nine key performance metrics, making it eligible for deployment on edge devices without requiring enormous resources or cloud connectivit

Mapping religious sites will allow a better understanding of the religious landscape of the participating countries. Maps connect you to the
matter at hand. They are functional tools to compile, display and share information, and support spatial thinking and planning. The geographically
referenced information displayed provide context as they are visualized
at a large scale. This mapping effort is made possible thanks to the engagement of relevant networks of government and religious organizations
in-country and builds on existing information. UNAOC launched a global
Call to Action for Safe Worship to support the UN Plan of Action to Safeguard Religious Sites.
This paper explores the application of drone technology in accurately
determining and fixing GPS coordinates of the Holy shrines of Imam Hussein and Imam Abbas in Karbala, Iraq. With millions of visitors annually,
precise geospatial data is essential for security, navigation, urban planning, and crowd management. This study examines the use of advanced
drone mapping techniques, including RTK (Real-Time Kinematic) and
PPK (Post-Processed Kinematic) GPS, to enhance the accuracy of spatial
data. Case studies of successful drone-based mapping projects worldwide
are included to highlight best practices and potential applications in Karbala. By leveraging aerial photogrammetry and geospatial mapping, this
approach enhances precision in shrine documentation, facilitates pilgrimage planning, and contributes to heritage preservation. The paper outlines the methodology used, results obtained, and potential implications for urban planning, security, and tourism.

This study focuses on monitoring and analyzing crowd dynamics
during the Arbaeen Ziyarat in Karbala, one of the world’s largest religious
gatherings. The research employs high-resolution satellite imagery, specifically from Google Earth Pro, combined with advanced remote sensing
and geospatial analysis techniques to accurately classify crowd densities
and movement patterns. The classification achieved a spatial resolution of
0.1 meters with over 95% accuracy when validated against official visitor
data from the Al-Abbas Holy Shrine.
Results indicate that crowd density and pedestrian flow vary significantly throughout the pilgrimage period. From Safar 6 to Safar 13, pedestrian movement remained free-flowing with low density and high speeds.
However, from Safar 14 onwards, congestion intensified, peaking on Safar 19 with densities exceeding 2 persons per square meter and pedestrian speeds dropping to 0.11 m/s, well below the standard free pedestrian
speed of 1.25 m/s. This critical congestion level highlights the urgent need
for effective crowd management strategies. This integrated methodological framework offers a reliable, scalable, and non-invasive approach to
managing large-scale crowd dynamics, contributing valuable insights for
urban planners, event organizers, and public safety officials.
The study demonstrates the effectiveness of integrating satellite remote
sensing with geospatial modeling and official data for crowd monitoring
in highly sensitive religious contexts. Recommendations include the periodic use of high-resolution satellite imagery for real-time crowd monitoring, implementation of AI-based smart crowd control systems, real-time
visitor flow modeling with early warning systems, horizontal expansion
of the Bayn Al Haramayn zone via multi-level walkways or underground
corridors, and comprehensive emergency traffic management plans coordinated with local authorities to ensure visitor safety during peak periods

Reliance on renewable energy sources, particularly solar energy, is
a key component of achieving environmental sustainability, especially
in areas with intensive seasonal use, such as the pilgrims’ route linking
Baghdad and Karbala. This research aims to identify the optimal locations
for installing solar cells along this vital route, using remote sensing techniques and image processing algorithms. This ensures maximum energy
efficiency while minimizing interference with existing infrastructure and
services. The study relied on high-resolution satellite data, along with a
digital elevation model (DEM) and solar radiation data, to identify areas
with the greatest exposure to sunlight and optimal surface slope. Land
cover characteristics were also analyzed using spectral indices such as
NDVI and BSI, taking into account topographic factors, shade, and vegetation density, within a Geographic Information Systems (GIS) environment. To weight factors and prioritize impacts, the Analytical Hierarchy
Model (AHP) method was applied, producing a final map showing the
optimal installation locations. The results showed that approximately 23%
of the studied route is highly suitable for solar cell installation. Among
the most efficient areas are the outskirts of Yusufiyah, Latifiyah, Sadr
al-Yusufiyah, Rustamiyah, al-Radwaniyah, al-Haswa, Khan al-Nas, the
outskirts of Alexandria, and al-Hindiyah Dam, due to their gentle slopes,
direct solar exposure, and distance from urban and natural obstacles. This
study provides a practical framework for sustainable energy planning in
visitor service infrastructure projects. It also opens up future prospects
for expanding the model to include similar corridors or integrating it with
time-series data to monitor energy performance throughout the year