Human Tracking and Profiling for Risk Management

α
Ranjith K.H.V.S
Ranjith K.H.V.S
σ
Jayasekara A.S
Jayasekara A.S
ρ
Ratnasooriya K.A.L.L
Ratnasooriya K.A.L.L
Ѡ
J.L Thilini Randika
J.L Thilini Randika
¥
Dr. Lakmal Rupasinghe
Dr. Lakmal Rupasinghe
§
Ms. Chethana Liyanapathirana
Ms. Chethana Liyanapathirana
α Sri Lanka Institute of Information Technology

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Human Tracking and Profiling for Risk Management

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Abstract

Infectious viruses are conveyed via respiratory droplets produced by an infected person when they speak, sneeze, or cough. So, to combat virus transmission, the World Health Organization (WHO) has imposed severe regulations such as mandatory face mask use and social segregation in public spaces. The ‘Human Tracking and Profiling for Risk Management System (HTPRM)’ is an online application that identifies the risk associated with failing to follow proper health practices. This proposed approach, which is divided into four components, utilizes ‘You Only Live Once YOLO (V3)’ to detect facemask danger, which would be determined based on two factors: wearing the face mask properly and the type of mask (Surgical, k95, homemade, and bare). The second phase is to use Open CV and SSD-Mobilenet to evaluate the value of a one-meter space (Social Distance) between people. The system recognizes the maximum number of individuals that can be in the vicinity of the specific hall that uses YOLO( V3) and image processing as the third procedure. In the last processing, the system identifies each person’s behavior, classifies it as uncommon or not, and calculates the risk associated with each category. Finally, the system computes the overall risk and generates a warning alarm to notify the user that they are in a dangerous scenario.

References

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Ranjith K.H.V.S. 2026. \u201cHuman Tracking and Profiling for Risk Management\u201d. Global Journal of Computer Science and Technology - D: Neural & AI GJCST-D Volume 22 (GJCST Volume 22 Issue D1): .

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Advanced human tracking for AI research applications and cybersecurity.
Journal Specifications

Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

Keywords
Classification
GJCST-D Classification: H.3.4
Version of record

v1.2

Issue date

January 22, 2022

Language
en
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Infectious viruses are conveyed via respiratory droplets produced by an infected person when they speak, sneeze, or cough. So, to combat virus transmission, the World Health Organization (WHO) has imposed severe regulations such as mandatory face mask use and social segregation in public spaces. The ‘Human Tracking and Profiling for Risk Management System (HTPRM)’ is an online application that identifies the risk associated with failing to follow proper health practices. This proposed approach, which is divided into four components, utilizes ‘You Only Live Once YOLO (V3)’ to detect facemask danger, which would be determined based on two factors: wearing the face mask properly and the type of mask (Surgical, k95, homemade, and bare). The second phase is to use Open CV and SSD-Mobilenet to evaluate the value of a one-meter space (Social Distance) between people. The system recognizes the maximum number of individuals that can be in the vicinity of the specific hall that uses YOLO( V3) and image processing as the third procedure. In the last processing, the system identifies each person’s behavior, classifies it as uncommon or not, and calculates the risk associated with each category. Finally, the system computes the overall risk and generates a warning alarm to notify the user that they are in a dangerous scenario.

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Human Tracking and Profiling for Risk Management

Ranjith K.H.V.S
Ranjith K.H.V.S Sri Lanka Institute of Information Technology
Jayasekara A.S
Jayasekara A.S
Ratnasooriya K.A.L.L
Ratnasooriya K.A.L.L
J.L Thilini Randika
J.L Thilini Randika
Dr. Lakmal Rupasinghe
Dr. Lakmal Rupasinghe
Ms. Chethana Liyanapathirana
Ms. Chethana Liyanapathirana

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