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Title: :  Crowd Computing in Public Places
PaperId: :  24043
Published in:   International Journal Of Advance Research And Innovative Ideas In Education
Publisher:   IJARIIE
e-ISSN:   2395-4396
Volume/Issue:    Volume 10 Issue 3 2024
DUI:    16.0415/IJARIIE-24043
Licence: :   IJARIIE is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Author NameAuthor Institute
Kashish InamdarSanghvi College of Engineering
khushi GujrathiSanghvi College of Engineering
Gaytri SonawaneSanghvi College of Engineering
toshil sonawaneSanghvi College of Engineering

Abstract

Computer Engineering
Crowd counting, Public spaces, Automated surveillance, Video analytics, Surveillance systems, Convolutional neural networks (CNNs), Recurrent neural networks (RNNs), Deep learning, Security monitoring, Urban planning, Urban planning
Crowd counting in public places plays a pivotal role in various domains including urban planning, security management, and event organization. This paper provides a comprehensive review and analysis of automated crowd counting techniques applied in public spaces. The study encompasses a wide array of methodologies ranging from traditional to state-of-the-art deep learning approaches. The review begins with an overview of the significance of crowd counting in public places, highlighting its importance in ensuring public safety, optimizing resource allocation, and enhancing crowd management strategies. Subsequently, it delves into the evolution of crowd counting techniques, tracing the progression from classical methods such as background subtraction and feature-based approaches to more recent advancements leveraging convolutional neural networks (CNNs), recurrent neural networks (RNNs), and their variants. Furthermore, the paper discusses various challenges encountered in crowd counting tasks, including occlusions, scale variations, and lighting conditions, along with the corresponding solutions proposed in literature. Additionally, it examines datasets commonly used for crowd counting research and evaluates their suitability for different scenarios. Moreover, the review critically assesses the performance metrics utilized to evaluate crowd counting algorithms and identifies the limitations of existing evaluation protocols. It also discusses the emerging trends and future directions in crowd counting research, such as the integration of multimodal data and the adoption of explainable AI techniques. Overall, this paper serves as a valuable resource for researchers, practitioners, and policymakers interested in understanding the state-of-the-art techniques, challenges, and future prospects of automated crowd counting in public spaces.

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IJARIIE Kashish Inamdar, khushi Gujrathi, Gaytri Sonawane, and toshil sonawane. "Crowd Computing in Public Places" International Journal Of Advance Research And Innovative Ideas In Education Volume 10 Issue 3 2024 Page 2797-2800
MLA Kashish Inamdar, khushi Gujrathi, Gaytri Sonawane, and toshil sonawane. "Crowd Computing in Public Places." International Journal Of Advance Research And Innovative Ideas In Education 10.3(2024) : 2797-2800.
APA Kashish Inamdar, khushi Gujrathi, Gaytri Sonawane, & toshil sonawane. (2024). Crowd Computing in Public Places. International Journal Of Advance Research And Innovative Ideas In Education, 10(3), 2797-2800.
Chicago Kashish Inamdar, khushi Gujrathi, Gaytri Sonawane, and toshil sonawane. "Crowd Computing in Public Places." International Journal Of Advance Research And Innovative Ideas In Education 10, no. 3 (2024) : 2797-2800.
Oxford Kashish Inamdar, khushi Gujrathi, Gaytri Sonawane, and toshil sonawane. 'Crowd Computing in Public Places', International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 3, 2024, p. 2797-2800. Available from IJARIIE, https://ijariie.com/AdminUploadPdf/Crowd_Computing_in_Public_Places_ijariie24043.pdf (Accessed : ).
Harvard Kashish Inamdar, khushi Gujrathi, Gaytri Sonawane, and toshil sonawane. (2024) 'Crowd Computing in Public Places', International Journal Of Advance Research And Innovative Ideas In Education, 10(3), pp. 2797-2800IJARIIE [Online]. Available at: https://ijariie.com/AdminUploadPdf/Crowd_Computing_in_Public_Places_ijariie24043.pdf (Accessed : )
IEEE Kashish Inamdar, khushi Gujrathi, Gaytri Sonawane, and toshil sonawane, "Crowd Computing in Public Places," International Journal Of Advance Research And Innovative Ideas In Education, vol. 10, no. 3, pp. 2797-2800, May-Jun 2024. [Online]. Available: https://ijariie.com/AdminUploadPdf/Crowd_Computing_in_Public_Places_ijariie24043.pdf [Accessed : ].
Turabian Kashish Inamdar, khushi Gujrathi, Gaytri Sonawane, and toshil sonawane. "Crowd Computing in Public Places." International Journal Of Advance Research And Innovative Ideas In Education [Online]. volume 10 number 3 ().
Vancouver Kashish Inamdar, khushi Gujrathi, Gaytri Sonawane, and toshil sonawane. Crowd Computing in Public Places. International Journal Of Advance Research And Innovative Ideas In Education [Internet]. 2024 [Cited : ]; 10(3) : 2797-2800. Available from: https://ijariie.com/AdminUploadPdf/Crowd_Computing_in_Public_Places_ijariie24043.pdf
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