Human Tracking and Profiling for Risk Management

Article ID

Q8B8T

Advanced human tracking for AI research applications and cybersecurity.

Human Tracking and Profiling for Risk Management

Ranjith K.H.V.S
Ranjith K.H.V.S Sri Lanka Institute of Information Technology (SLIIT)
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
DOI

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 SSDMobilenet 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.

Human Tracking and Profiling for Risk Management

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 SSDMobilenet 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.

Ranjith K.H.V.S
Ranjith K.H.V.S Sri Lanka Institute of Information Technology (SLIIT)
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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Ranjith K.H.V.S. 2026. “. Global Journal of Computer Science and Technology – D: Neural & AI GJCST-D Volume 22 (GJCST Volume 22 Issue D1): .

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Crossref Journal DOI 10.17406/gjcst

Print ISSN 0975-4350

e-ISSN 0975-4172

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GJCST-D Classification: H.3.4
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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 (SLIIT)
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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