AL ARBA'IN

The Arbaeen pilgrimage, one of the largest annual mass gatherings
globally, presents significant challenges in maintaining public safety due
to its immense scale, dynamic population movements, and vulnerability
to physical and cyber threats. This study introduces an AI-driven framework designed to simulate, monitor, and analyze security risks associat-ed with the pilgrimage, focusing on pedestrian and vehicular flow, drone surveillance, incident detection, and crowd sentiment. A synthetic data-set designed to approximate real-world conditions was generated using Python, integrating spatiotemporal features and environmental variables across key urban routes. Machine learning techniques—including Isolation Forest for anomaly detection and K-Means clustering for pattern recognition—were employed to uncover behavioural irregularities and high-risk crowd conditions. Additionally, visual analytics tools were used to map incidents, detect surveillance gaps, and identify relationships between crowd sentiment and security factors. The findings highlight the potential of advanced surveillance technologies, AI-enhanced analytical tools, and simulation modelling in informing early warning systems, optimizing emergency response, and enhancing situational awareness during the Arbaeen pilgrimage. This integrative approach offers a scalable and transferable solution for mass gathering security management in similarly complex contexts.

The Arbaeen Pilgrimage, one of the largest religious gatherings in the
world, attracts millions of people to Iraq annually. As global awareness
about climate change and environmental sustainability increases, it becomes essential to examine the environmental footprint of such largescale events. This paper explores the awareness of the concept of “Net Carbon Zero” among participants in the Arbaeen Pilgrimage, focusing by analysing data from interviews, as well as examining environmental initiatives, this paper aims to provide insights into how sustainable practices can be integrated into the pilgrimage, ensuring that religious devotion and environmental responsibility go hand in hand.
The Arbaeen Pilgrimage, held annually to commemorate the martyrdom of Imam Hussein, is a significant event for millions of Muslims
worldwide. It involves a mass gathering of pilgrims who travel to the
holy city of Karbala, Iraq, covering vast distances by foot, vehicle, and
other means of transportation. While this event holds immense religious
and cultural importance, its environmental impact specifically its carbon
footprint has raised concerns in recent years.
In response to global environmental challenges, the concept of “Net
Carbon Zero” has gained prominence to reduce or offset carbon emissions to point where the net result is zero. The objective of this paper is to assess the level of awareness of Net Carbon Zero among the people
participating in the Arbaeen Pilgrimage, understand their attitudes toward
environmental sustainability, and identify potential strategies for reducing
the pilgrimage’s carbon footprint.

Visiting the holy shrines is of great importance to Muslims in Islamic
countries in general and to Muslims in Iraq in particular. Visitors usually
try to visit as many holy shrines as possible in a single visit at the lowest
possible cost. In this research, visiting the Iraqi Holy Shrines Problem
(IHSP) was considered, which is in fact, a practical application of the symmetrical traveling salesman problem (TSP). The summary of this problem is that a visitor wants to visit all (or most) of the (14) holy shrines in Iraq. This visitor lives in a city that includes one of these shrines and wants to find the appropriate route to visit all of them at the lowest cost (cost here
means distance and/or time and/or financial cost) and then return to the
same city from which he started without repeating the route between any
two shrines. One of the most important results of this research is that the
optimal (shortest) distance path was found to help the visitor achieve the
minimum financial cost of fuel consumption using more than one accurate or approximate method to solve this problem.

The ziyarat Al-Arbaeen in Karbala, Iraq, is one of the largest annu-al gatherings of people in the world, attracting millions of visitors. This
poses significant challenges in crowd control, ensuring smooth flow of
traffic, and ensuring the safety of visitors. This research aims to develop
an intelligent people counting system using advanced computer vision
techniques, relying on convolutional neural networks (CNNs), to accurately and effectively detect individuals in video clips, without the use of facial recognition or identification techniques. The system analyzes the
input videos to calculate the total number of people appearing in each
frame. The results are displayed as a representation of the total number,
allowing for a more accurate understanding of the crowd distribution in
the studied locations. The system currently does not include real-time data
processing, but the possibility of developing this aspect and adding automatic alerts when crowd density increases is an important future endeavor that could enhance the system’s ability to effectively manage crowds. This research represents a first step towards employing artificial intelligence techniques to support crowd control during major religious events and highlights the potential of computer vision as an effective tool to help ensure the safety and security of visitors.

The Arbaeen pilgrimage in Karbala is one of the largest religious gatherings in the world, generating complex environmental challenges—most notably in urban waste management due to extreme crowd density and limited infrastructure.The problem addressed in this study lies in the inadequate adoption of artificial intelligence (AI) technologies in managing crowd-generated waste during the pilgrimage, which hampers the realization of a sustainable urban system responsive to mass events.
The research hypothesizes that the integration of AI tools can significantly enhance the efficiency, responsiveness, and environmental sustainability of waste management systems during mass religious occasions. The significance of this study stems from its contribution to proposing an AI-based smart waste management framework, tailored to the specific context of Karbala, and capable of addressing the challenges of both scale and religious spatial sensitivity.To achieve this, the study employed a mixed-methods approach combining analytical review, comparative case analysis, and a field survey conducted in eight neighborhoods within the historical center of Karbala during the 1445 AH Arbaeen season. Data were collected through structured observations, municipal records, and semi-structured interviews with local service providers.Temporal and spatial boundaries: Data were collected from field observations,
municipal records, and interviews with local service personnel. The sample
included municipal employees, representatives of the shrines, and workers in the Husseini service processions within the historic center of Karbala. The time period extended from Muharram to the end of Safar 1445 AH, with a special focus on the peak days of the Arbaeen pilgrimage.
The research proposes technical solutions including smart sorting robots,
sensor-enabled waste bins, drone monitoring, and predictive analytics platforms. Results revealed weak digital infrastructure, lack of coordinated governance, and minimal AI integration in existing practices.
The study recommends a national strategy for AI-based waste management, establishing real-time monitoring centers, community awareness cam-paigns, and encouraging applied research in environmental AI. These steps would transform current waste challenges into opportunities for smart, sustain-able urban management.

Green belts are an important environmental solution for combating desertification and mitigating the effects of climate change, especially in arid and semi-arid regions such as Iraq. This research aims to identify the optimal locations for establishing a sustainable green belt along the Baghdad-Karbala Road, using remote sensing, satellite, and geographic information systems (GIS) techniques. This road represents a vital axis witnessing rapid urban expansion and a major route for millions of pilgrims during the Arbaeen pilgrimage. This places significant pressure on the local environment and infrastructure, necessitating science-based planning interventions to ensure sustainable visitor services. Satellite imagery (such as Landsat 8 and Sentinel-2) from the recent period (2023–2024) was used, and a set of spectral indices, including the NDVI (Natural Color Vividness Index), the BSI (Aridity Index), and the NDMI (Natural Color Moisture Index), were applied to assess the environmental condition of the lands adjacent to the road. The terrain was also analyzed using a digital elevation model (DEM) to determine the appropriate slopes and levels for agriculture, taking into account factors such as wind direction and speed, the level of urban expansion, and nearby groundwater or surface water sources. A multi-criteria decision analysis (MCDA)
methodology was adopted within a GIS environment to identify the most
suitable areas, with each criterion weighted according to its environmental
and logistical importance using the Analytic Hierarchy Process (AHP) method. The analysis results showed that the areas located southwest of Latifiya city and north of Alexandria are among the environmentally promising areas for establishing a green belt. These areas recorded the highest values ​​in NDVI and the lowest in BSI, with flat terrain and relative proximity to water sources. The study also demonstrated that the areas within Babil Governorate.
adjacent to the road have a high potential for transformation into green spaces if properly managed, using drought-resistant plants and low-water-consumption agricultural methods. The study recommends integrating the results of this analysis into regional sustainable development plans, particularly in light of the importance of the Million Pilgrimage Route. It also proposes involving stakeholders and local communities in the design and implementation to en-sure the environmental and social sustainability of the project.

Religious events are held globally, where the Arbaeen pilgrimage is
considers one of the largest events. During this event, millions of visitors
arrive in Iraq from different countries, creating an urgent need to ensure
a safe and organized mass movement for people and vehicles. Therefore,
in this research an intelligent framework for crowd movement analysis
and anomaly detection was designed specifically for this event. Synthetic datasets were created to simulate the dynamics of the visit and test
the proposed framework. Six machine learning algorithms were applied
(Isolation Forest, Local Outlier Factor (LOF), Rolling Z-Score, ARIMA
Residuals, DBSCAN Clustering, and Kernel Density Estimation (KDE))
to analyze Data identify anomalies (such as sudden overcrowding or irregular movement patterns) which may indicate possible threats to safety, unusual stops, or irrational movements. In addition to calculating the ac_curacy of each algorithm by comparing its results with the majority vote results and measuring the execution time of each algorithm. Moreover, to maintain data privacy and integrity, with the results signed using a digital signature (SHA3-256) to ensure security and integrity. The system aims to support the shrine authorities by monitoring crowd behavior and enabling proactive measures to enhance the safety of visitors and the smooth execution of procedures

The Arbaeen pilgrimage is one of the largest human gatherings in the
world, posing significant challenges for traffic management and traffic
sign supervision due to extreme population density, frequent changes in
temporary traffic routes, and the physical and mental fatigue experienced
by organizational staff. These factors make it increasingly difficult to guide
visitors, particularly the elderly and those unfamiliar with the area. This
research aims to address these challenges by developing an intelligent,
automated system capable of instantly recognizing Arabic traffic signs and
providing audio alerts to drivers and traffic coordinators. A convolutional
neural network (CNN) model was employed, incorporating data analysis
techniques such as preprocessing, data augmentation (including rotation and zooming), and normalization. The system was trained and tested on a publicly available dataset (ArTS Dataset) containing Arabic traffic signs under diverse conditions (e.g., lighting, angle, clarity). An interactive graphical user interface (GUI) was designed, allowing users to upload images of traffic signs (simulating camera input) and receive real-time predictions accompanied by audio pronunciation in Arabic. The model achieved test accuracy exceeding 90% when evaluated on the designated test dataset, along with strong performance in additional metrics such as precision, recall, and F1-score. Although the data used does not originate from actual traffic signs in Karbala during the Arbaeen pilgrimage, it reflects similar real-world conditions. This work represents an initial step toward future field deployment, particularly in smart transportation systems, where such a system could support visitors in their native language and in real time, thereby enhancing public safety and mobility during large-scale religious events.

The Arbaeen pilgrimage is one of the most significant annual events in
Iraq, attracting millions of people from nearly every corner of the world
to visit the shrine of Imam Hussein (peace be upon him). Pilgrims travel
to the holy city of Karbala using various modern transportation methods, though many choose to walk on foot as an act of devotion. The holy
shrines in Karbala provide comprehensive services, including food, water,
accommodation, and transportation, to support pilgrims during their journey. This study aims to assess pilgrims’ satisfaction with these services and provide recommendations for their improvement. A multi-dimensional evaluation tool was developed, consisting of several key aspects, each measured through a set of questions in both paper and digital formats. The Instrument evaluated service quality to measure visitor satisfaction. The survey was distributed randomly to pilgrims at various main entry points of Karbala. Responses were analyzed using a data analysis software SPSS V3, and the findings, along with proposed recommendations, were presented and discussed. The study revealed that the majority of pilgrims were generally satisfied with the services provided. Additionally, the re-search included actionable recommendations to further enhance service quality and achieve optimal performance.

This study applies Speech Act Theory, particularly Searle’s taxonomy,
to explore how language is used pragmatically by Al-Mawakib organizers
during the Arba’een pilgrimage—an event rich in religious and cultural
meaning. While prior research has overlooked the linguistic analysis of
such expressions, this study addresses the gap by analyzing thirty commonly used statements gathered directly from Al-Mawakib organizers. These expressions, often emotionally and spiritually charged, aim to influence the recipient’s response positively.
Furthermore, the study employs a mixed-methods approach, primarily
qualitative descriptive analysis, supplemented by quantitative tools such
as frequency counts and percentage analysis to enhance the credibility
and robustness of the findings. It examines the frequency and function
of five categories of speech acts: Expressives, Directives, Commissives,
Assertives, and Declaratives.The study proposes three hypotheses: (1) the terminology used by AlMawakib organizers reflects core religious and social values, such as generosity and hospitality; (2) expressive speech acts are the most dominant, while declaratives are the least; and (3) context plays a vital role in shaping the interpretation and multifunctionality of these utterances.The findings of the analysis verified the three hypotheses as follows:
(1) the terminology used by Al-Mawakib organizers indeed reflects key
religious and social values, such as generosity and hospitality;
(2) among the speech acts, the expressive category is the most frequently employed in addition to directive one , while the declarative category is the least frequent; and (3) the social and religious context plays a significant role in shaping the interpretation and function of these expressions, enabling .
a single utterance to perform multiple speech acts simultaneously. More-over, utilizing various categories of speech acts fosters persuasive com-munication between organizers and pilgrims, highlighting the integral
role of language in such occasions.

This article explores the participation of elderly pilgrims in the Arbaeen
pilgrimage, highlighting their unwavering faith, resilience, and deep spiritual connection with Imam Hussein (AS). This article will also explore the historical significance of Jabir ibn Abdullah Ansari, who, despite his old
age, was the first to visit the grave of Imam Hussein (AS) on the day of
Arbaeen. His determination and deep devotion set a precedent for future
generations of pilgrims, illustrating that age is no barrier when it comes
to expressing unwavering loyalty and love for Imam Hussein. Jabir’s pilgrimage is a poignant reminder of the profound spiritual connection that
transcends physical limitations, further emphasizing the significance of
elderly participation in the Arbaeen pilgrimage today.
In the present article I will highlight the elderly pilgrim challenges
related to their financial assistance like visa, air fare, transportation expenditure and I will also try to understand health risks, mobility issues,
accommodation difficulties, overcrowding, and emotional distress during
Arbaeen pilgrimage. The article will also present practical measures to
improve their pilgrimage experience, such as enhanced medical support,
better accessibility, improved accommodations, guided assistance, and
psychological support. By addressing these challenges, the Arbaeen pilgrimage can become a more inclusive and comfortable experience for elderly pilgrims, allowing them to partake in this profound spiritual journey
with dignity and ease.

This research endeavored to examine the impact of participating in
Arbaeen pilgrimage on the development of authentic leadership within
a sample of Bahraini youth. Employing a mixed-methods design, the research adopted quantitative data obtained through a questionnaire, along with qualitative insights driven from focus group discussions. To measure the authentic leadership, the Authentic Leadership Questionnaire (ALQ) is administered, which comprises sixteen items, measuring the four established theoretical constructs of authentic leadership: self-awareness, internalized moral perspective, balanced processing, and relational transparency. The target population in this research consists of youths aged 15-20 years (N = 760), who reside within a local town in the Kingdom of Bahrain. Electronic administration of the ALQ in January 2025 yield a response rate of 66% (N = 500) consisting our random sample. Statistical analyses of the responses reveal a significant positive correlation, indicating participation in the Arbaeen pilgrimage as a predictor of the development of authentic leadership, with self-awareness construct exhibiting a particularly increase among the pilgrims. Consequently, the research posits a strategic importance of leveraging the Arbaeen pilgrimage as a potential opportunity for the development of Islamic authentic leadership among youth, thereby contributing to the formation of future leadership capital.

The paper looks into how the English media language frame of Arba’een pilgrimage of Imam Hussain can be used to expand the notion of
religious identity. This study uses Critical Discourse Analysis (CDA) by
adopting Fairclough’s three- dimensional model (1995) to analyse four
media texts in order to know how discourse practices have been used to
create the perceptions of Shia Islamic identity in the global spectrum.
The study aims to investigate the lexical, syntactic, and rhetorical devices
used in media to frame the Arba’een pilgrimage and to how the linguistic
framing of the Arba’een pilgrimage in English discourse influences public
perceptions of Shia Muslim identity, communal solidarity, or geopolitical
narratives. The analysis shows that media forms relying on the orientalist models tend to focus on spectacle and neglect spiritual meaning and
construct a number of antinomies between secular Western and religious
Eastern worldviews. The results have shown that language can play an
important role in protecting the picture of religious practices and personal
identity in the minds of people through the correct use of use of headlines text, descriptive language and framing the context of the language.
The paper concludes that the way power relations incorporated in media
discourse led to the marginalisation or legitimisation of religious communities. These results have impacts on examining the representation of religious minorities in the media and language, which is used to create otherness across the world.

This article examines the Arbaeen pilgrimage through the lens of sen-sory anthropology, highlighting how sensory perception—particularly
taste, touch, smell, sight, and hearing—plays a central role in shaping
the embodied religious experience of pilgrims. Drawing on ethnographic
fieldwork and in-depth interviews with pilgrims and service volunteers
(khādimīn) in Iraq, the study investigates how ritual food functions not
only as nourishment but as a powerful medium of spiritual, social, and
cultural significance. Through a multisensory approach, this research
shows that the sacred is not only represented in religious texts and spaces
but also felt, smelled, tasted, and heard in everyday ritual practices.
The article argues that the preparation, offering, and consumption of
votive food is a central ritual act that mediates intersubjective connections
among participants, rooted in deeply held beliefs about divine presence,
intercession, and sacred reciprocity. Sensory modalities become symbolic carriers of memory, meaning, and identity, rendering the pilgrimage
a site of both spiritual intensification and social cohesion. The analysis
is grounded in theoretical contributions from David Howes, Constance
Classen, Sarah Pink, and Éric Landowski, providing a robust interdisciplinary framework to understand how religious experiences are embodied, mediated, and communicated through the senses.

This study focuses on the Arbaeen March as a modern application of
Joseph Campbell’s Hero’s Journey. It studies the pilgrimage as an organized story of faith, resistance, and spiritual transformation. The study
fills the gap in academic attention to Arbaeen as a literary and mythic
genre. Using Campbell’s stages of departure, initiation, and return, the
study examines pilgrims’ experiences using qualitative methods such as
observations, interviews, and analysis of speeches and rituals during the
march to Karbala. Thematic analysis ties these real-life experiences to the
structure of the Hero’s Journey. The research uses Campbell’s theory, together with cultural and narrative theory, to explain how pilgrims exhibit
ideals like as sacrifice, moral growth, and solidarity. The study concludes
that the Arbaeen March is not only a spiritual event but also a powerful narrative journey. It mirrors classic heroic patterns and functions as a
living myth that deepens cultural identity, collective memory, and moral
purpose.