Towards Efficient Detection and Crowd Management for Law Enforcing Agencies

Habib, Shaban; Hussain, Altaf; Islam, Muhammad Mobaidul; Khan, Sheroz; Albattah, Waleed

doi:10.1109/caida51941.2021.9425076

Cited by 13 publications

(19 citation statements)

References 30 publications

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“…We evaluated the proposed framework using UCF [ 22 ], ShanghaiTech [ 39 ], and Surveillance fight [ 57 ] datasets. It is important to note that these datasets are large-scale and challenging in terms of detecting anomalies and violence.…”

Section: Resultsmentioning

confidence: 99%

“…From 15 to nearly one minute long, the video clips range in length. Akti et al [ 57 ] have introduced a surveillance fight dataset that includes all types of fight videos, including both violent and non-violent ones. As a part of this dataset, we have comprised equal numbers of videos in each study group and in total there are 300 videos with a variety of resolutions.…”

Section: Resultsmentioning

confidence: 99%

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An IoT Enable Anomaly Detection System for Smart City Surveillance

Islam¹,

Dukyil²,

Alyahya³

et al. 2023

Sensors

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Since the advent of visual sensors, smart cities have generated massive surveillance video data, which can be intelligently inspected to detect anomalies. Computer vision-based automated anomaly detection techniques replace human intervention to secure video surveillance applications in place from traditional video surveillance systems that rely on human involvement for anomaly detection, which is tedious and inaccurate. Due to the diverse nature of anomalous events and their complexity, it is however, very challenging to detect them automatically in a real-world scenario. By using Artificial Intelligence of Things (AIoT), this research work presents an efficient and robust framework for detecting anomalies in surveillance large video data. A hybrid model integrating 2D-CNN and ESN are proposed in this research study for smart surveillance, which is an important application of AIoT. The CNN is used as feature extractor from input videos which are then inputted to autoencoder for feature refinement followed by ESN for sequence learning and anomalous events detection. The proposed model is lightweight and implemented over edge devices to ensure their capability and applicability over AIoT environments in a smart city. The proposed model significantly enhanced performance using challenging surveillance datasets compared to other methods.

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Section: Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

An IoT Enable Anomaly Detection System for Smart City Surveillance

Islam¹,

Dukyil²,

Alyahya³

et al. 2023

Sensors

Self Cite

View full text Add to dashboard Cite

show abstract

“…Using R-CNN, it is possible now not only to count the number of pilgrims in the crowd, but also to determine their gender and estimate their age [230]. Likewise, Habib et al suggested using Faster Region CNN to achieve accurate computer vision-based crowd management [231]. CNN was also used for crowd density estimation at Al-Masjid Al-Haram in Makkah with 70% accuracy [232].…”

Section: G Crowd Managementmentioning

confidence: 99%

Solving Hajj and Umrah Challenges Using Information and Communication Technology: A Survey

Showail

2022

IEEE Access

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Hajj and Umrah are Muslims' religious pilgrimages to Makkah, Saudi Arabia. Hajj is considered the largest annual gathering in the world. In Islam, each and every able-bodied adult is obligated to go for Hajj at least once in his/her lifetime. Hajj takes place between the 8 th and the 13 th day of Dhul Hijjah, which is the last month of the Islamic year while Umrah, the minor pilgrimage, could be done any time of the year. In Hajj, pilgrims, also known as Hajjis, travel around 15 km and pilgrims have the choice to do it by foot, bus or by train. The Hajj journey starts from Mina, which is considered the largest tent city in the world because it hosts more than 10,000 fire resistant tents, and includes various religious rituals. Around 3 million Muslims from more than 183 countries make Hajj every year and the Kingdom of Saudi Arabia is working on increasing this number. Since 1989, researchers in various ICT domains have tried leveraging their expertise in solving challenges and issues related to Hajj and Umrah. Although several papers have surveyed efforts using technology in Hajj and Umrah research, none of them was comprehensive. In this paper, I classified research efforts that used information and communication technologies for solving Hajj and Umrah challenges over the past 33 years based on their applications in 10 categories. I also identified more than 30 technologies used by researchers all over the world to address Hajj and Umrah issues and group research efforts based on these technologies for ease of access. Furthermore, open challenges were discussed and new technologies that could be used to address these challenges were proposed.

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“…Taha et al also employed convolutional neural networks for detecting the geographic location of pilgrims and helping in crowd management by identifying hotspots [50]. Habib et al proposed an improved solution using Faster-RCNN (region-based convolutional neural networks) with an Inception V2 feature extractor [51]. Feldman et al have provided an excellent review of the latest research in crowd management during Islamic pilgrimage [5].…”

Section: Related Workmentioning

confidence: 99%

Analyzing the Impact of Social Distancing on the Stoning Ritual of the Islamic Pilgrimage

2022

KSII TIIS

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The COVID-19 pandemic has resulted in a profound impact on large-scale gatherings throughout the world. Social distancing has become one of the most common measures to restrict the spread of the novel Coronavirus. Islamic pilgrimage attracts millions of pilgrims to Saudi Arabia annually. One of the mandatory rituals of pilgrimage is the symbolic stoning of the devil. Every pilgrim is required to perform this ritual within a specified time on three days of pilgrimage. This ritual is prone to congestion due to strict spatiotemporal requirements. We propose a pedestrian simulation model for implementing social distancing in the stoning ritual. An agent-based simulation is designed to analyze the impact of inter-queue and intra-queue spacing between adjacent pilgrims on the throughput and congestion during the stoning ritual. After analyzing several combinations of intra-queue and inter-queue spacings, we conclude that 25 queues with 1.5 meters of intra-queue spacing result in an optimal combination of throughput and congestion. The Ministry of Hajj in Saudi Arabia may benefit from these findings to manage and plan pilgrimage more effectively.

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Towards Efficient Detection and Crowd Management for Law Enforcing Agencies

Cited by 13 publications

References 30 publications

An IoT Enable Anomaly Detection System for Smart City Surveillance

An IoT Enable Anomaly Detection System for Smart City Surveillance

Solving Hajj and Umrah Challenges Using Information and Communication Technology: A Survey

Analyzing the Impact of Social Distancing on the Stoning Ritual of the Islamic Pilgrimage

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