PublicVision: A Secure Smart Surveillance System for Crowd Behavior Recognition
<p dir="ltr">Crowd behavior recognition plays a critical role in various domains, including public safety, event management, and urban planning. Understanding crowd dynamics and detecting behaviors based on violence levels are crucial for preventing incidents and maintaining order in...
محفوظ في:
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| مؤلفون آخرون: | , , , , , , |
| منشور في: |
2024
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| الموضوعات: | |
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إضافة وسم
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| _version_ | 1864513510331908096 |
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| author | Marwa Qaraqe (10135172) |
| author2 | Almiqdad Elzein (13141038) Emrah Basaran (19160743) Yin Yang (35103) Elizabeth B. Varghese (19198018) Wisam Costandi (19198021) Jack Rizk (19198024) Nasim Alam (19198027) |
| author2_role | author author author author author author author |
| author_facet | Marwa Qaraqe (10135172) Almiqdad Elzein (13141038) Emrah Basaran (19160743) Yin Yang (35103) Elizabeth B. Varghese (19198018) Wisam Costandi (19198021) Jack Rizk (19198024) Nasim Alam (19198027) |
| author_role | author |
| dc.creator.none.fl_str_mv | Marwa Qaraqe (10135172) Almiqdad Elzein (13141038) Emrah Basaran (19160743) Yin Yang (35103) Elizabeth B. Varghese (19198018) Wisam Costandi (19198021) Jack Rizk (19198024) Nasim Alam (19198027) |
| dc.date.none.fl_str_mv | 2024-02-23T12:00:00Z |
| dc.identifier.none.fl_str_mv | 10.1109/access.2024.3366693 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/PublicVision_A_Secure_Smart_Surveillance_System_for_Crowd_Behavior_Recognition/26355070 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Human society Criminology Information and computing sciences Computer vision and multimedia computation Cybersecurity and privacy Data management and data science Human-centred computing Machine learning Crowd behavior recognition deep learning public safety secure data transmission smart surveillance system design Surveillance Behavioral sciences Cameras Streaming media Security Real-time systems Transformers Crowdsensing Public security Data security System analysis and design Smart devices |
| dc.title.none.fl_str_mv | PublicVision: A Secure Smart Surveillance System for Crowd Behavior Recognition |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">Crowd behavior recognition plays a critical role in various domains, including public safety, event management, and urban planning. Understanding crowd dynamics and detecting behaviors based on violence levels are crucial for preventing incidents and maintaining order in crowded environments. However, traditional surveillance methods fall short of providing comprehensive and real-time insights into complex crowd behavior patterns and fail to distinguish different violence levels within crowds that affect proactive decision-making. Moreover, most of the current systems do not provide reliable secure data transmission and are not viable in protecting the privacy of individuals. This paper designs an end-to-end secure and smart surveillance system, namely PublicVision, that transmits CCTV data securely to a remote central hub where a deep learning (DL) model based on Swin Transformer is utilized to identify and analyze crowd behaviors. A novel video dataset was created to train the DL model that identifies crowds based on size and violence level. The proposed system incorporates end-to-end security by creating a Dynamic Multipoint Virtual Private Network (DMVPN) and leverages the property of IP Security (IPSec) and Firewall for confidentiality and integrity during transmission and storage. Experiment analysis and real-time inference using DeepStream Software Development Kit (SDK) proved that the proposed system has significant implications for public safety, security, and crowd management in various contexts, including public spaces, transportation hubs, and large-scale events.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2024.3366693" target="_blank">https://dx.doi.org/10.1109/access.2024.3366693</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_0d3d2fbd3095e8c58514e91ca629440f |
| identifier_str_mv | 10.1109/access.2024.3366693 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/26355070 |
| publishDate | 2024 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | PublicVision: A Secure Smart Surveillance System for Crowd Behavior RecognitionMarwa Qaraqe (10135172)Almiqdad Elzein (13141038)Emrah Basaran (19160743)Yin Yang (35103)Elizabeth B. Varghese (19198018)Wisam Costandi (19198021)Jack Rizk (19198024)Nasim Alam (19198027)Human societyCriminologyInformation and computing sciencesComputer vision and multimedia computationCybersecurity and privacyData management and data scienceHuman-centred computingMachine learningCrowd behavior recognitiondeep learningpublic safetysecure data transmissionsmart surveillancesystem designSurveillanceBehavioral sciencesCamerasStreaming mediaSecurityReal-time systemsTransformersCrowdsensingPublic securityData securitySystem analysis and designSmart devices<p dir="ltr">Crowd behavior recognition plays a critical role in various domains, including public safety, event management, and urban planning. Understanding crowd dynamics and detecting behaviors based on violence levels are crucial for preventing incidents and maintaining order in crowded environments. However, traditional surveillance methods fall short of providing comprehensive and real-time insights into complex crowd behavior patterns and fail to distinguish different violence levels within crowds that affect proactive decision-making. Moreover, most of the current systems do not provide reliable secure data transmission and are not viable in protecting the privacy of individuals. This paper designs an end-to-end secure and smart surveillance system, namely PublicVision, that transmits CCTV data securely to a remote central hub where a deep learning (DL) model based on Swin Transformer is utilized to identify and analyze crowd behaviors. A novel video dataset was created to train the DL model that identifies crowds based on size and violence level. The proposed system incorporates end-to-end security by creating a Dynamic Multipoint Virtual Private Network (DMVPN) and leverages the property of IP Security (IPSec) and Firewall for confidentiality and integrity during transmission and storage. Experiment analysis and real-time inference using DeepStream Software Development Kit (SDK) proved that the proposed system has significant implications for public safety, security, and crowd management in various contexts, including public spaces, transportation hubs, and large-scale events.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2024.3366693" target="_blank">https://dx.doi.org/10.1109/access.2024.3366693</a></p>2024-02-23T12:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2024.3366693https://figshare.com/articles/journal_contribution/PublicVision_A_Secure_Smart_Surveillance_System_for_Crowd_Behavior_Recognition/26355070CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/263550702024-02-23T12:00:00Z |
| spellingShingle | PublicVision: A Secure Smart Surveillance System for Crowd Behavior Recognition Marwa Qaraqe (10135172) Human society Criminology Information and computing sciences Computer vision and multimedia computation Cybersecurity and privacy Data management and data science Human-centred computing Machine learning Crowd behavior recognition deep learning public safety secure data transmission smart surveillance system design Surveillance Behavioral sciences Cameras Streaming media Security Real-time systems Transformers Crowdsensing Public security Data security System analysis and design Smart devices |
| status_str | publishedVersion |
| title | PublicVision: A Secure Smart Surveillance System for Crowd Behavior Recognition |
| title_full | PublicVision: A Secure Smart Surveillance System for Crowd Behavior Recognition |
| title_fullStr | PublicVision: A Secure Smart Surveillance System for Crowd Behavior Recognition |
| title_full_unstemmed | PublicVision: A Secure Smart Surveillance System for Crowd Behavior Recognition |
| title_short | PublicVision: A Secure Smart Surveillance System for Crowd Behavior Recognition |
| title_sort | PublicVision: A Secure Smart Surveillance System for Crowd Behavior Recognition |
| topic | Human society Criminology Information and computing sciences Computer vision and multimedia computation Cybersecurity and privacy Data management and data science Human-centred computing Machine learning Crowd behavior recognition deep learning public safety secure data transmission smart surveillance system design Surveillance Behavioral sciences Cameras Streaming media Security Real-time systems Transformers Crowdsensing Public security Data security System analysis and design Smart devices |