An Alert System: Using Fuzzy Logic for Controlling Crowd Movement by Detecting Critical Density Spots

Edris, Alaa; Alajlan, Abdullah; Sheldon, Frederick T.; Soule, Terence; Heckendorn, Robert B.

doi:10.1109/csci51800.2020.00112

Cited by 2 publications

(1 citation statement)

References 12 publications

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“…Moreover, fuzzy logic was used to control the crowd. It enabled researchers to create an alert system to keep the crowd safe in case of emergency [234]. The same group also used Long Short Term Memory (LSTM) to predict the direction of dense crowds [235].…”

Section: G Crowd Managementmentioning

confidence: 99%

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

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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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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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Meticulously Intelligent Identification System for Smart Grid Network Stability to Optimize Risk Management

2021

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The heterogeneous and interoperable nature of the cyber-physical system (CPS) has enabled the smart grid (SG) to operate near the stability limits with an inconsiderable accuracy margin. This has imposed the need for more intelligent, predictive, fast, and accurate algorithms that are able to operate the grid autonomously to avoid cascading failures and/or blackouts. In this paper, a new comprehensive identification system is proposed that employs various machine learning architectures for classifying stability records in smart grid networks. Specifically, seven machine learning architectures are investigated, including optimizable support vector machine (SVM), decision trees classifier (DTC), logistic regression classifier (LRC), naïve Bayes classifier (NBC), linear discriminant classifier (LDC), k-nearest neighbor (kNN), and ensemble boosted classifier (EBC). The developed models are evaluated and contrasted in terms of various performance evaluation metrics such as accuracy, precision, recall, harmonic mean, prediction overhead, and others. Moreover, the system performance was evaluated on a recent and significant dataset for smart grid network stability (SGN_Stab2018), scoring a high identification accuracy (99.90%) with low identification overhead (4.17 μSec) for the optimizable SVM architecture. We also provide an in-depth description of our implementation in conjunction with an extensive experimental evaluation as well as a comparison with state-of-the-art models. The comparison outcomes obtained indicate that the optimized model provides a compact and efficient model that can successfully and accurately predict the voltage stability margin (VSM) considering different operating conditions, employing the fewest possible input features. Eventually, the results revealed the competency and superiority of the proposed optimized model over the other available models. The technique also speeds up the training process by reducing the number of simulations on a detailed power system model around operating points where correct predictions are made.

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An Alert System: Using Fuzzy Logic for Controlling Crowd Movement by Detecting Critical Density Spots

Cited by 2 publications

References 12 publications

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

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

Meticulously Intelligent Identification System for Smart Grid Network Stability to Optimize Risk Management

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