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Suspicious Behavior Detection near Vehicles in University Environment: An Approach using Object Detection and Body Angles

Published: 23 May 2024 Publication History

Abstract

Context: With the advancement of smart cities, the University environment demands surveillance camera systems to increase their monitoring capabilities to prevent malicious behaviors without prohibiting people’s circulation. Problem: Universities have large parking lots with many vehicles and face daily security problems, such as robberies and kidnappings, due to the lack of cameras capable of detecting suspicious behavior and alerting security personnel. Solution: Our approach enhances security in the university environment by developing a system capable of recognizing vehicles and individuals, assessing their proximity, and detecting gestures and actions labeled as suspicious behavior while interoperating with camera systems to alert the appropriate security authorities. Information systems theory: This work was conceived based on the General System Theory to interact with pre-existing heterogeneous systems. It relates to the Technological Frames of Reference theory, which involves the perception and interpretation of real-time object detection technology to monitor, alert, and ensure security. Method: Our research method is an experimental, descriptive investigation of collecting quantitative data, and our evaluation is conducted through the proof of concept. Results: Our artifact demonstrated its feasibility by exhibiting good performance, enabling the detection of pre-defined suspicious behaviors near vehicles with a precision of 94,25% and accuracy of 86,99%. Contributions and Impact in the area of information systems: Our contributions are two-fold: From the organization’s perspective, our security system interoperability, generating interoperable alerts; the artifact to detect suspicious behaviors, protecting people in the University environment. Our approach impacts the three pilars from IS area: People, Process and Technology. Additionally, we provide a dataset of security camera videos in university parking lots.

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SBSI '24: Proceedings of the 20th Brazilian Symposium on Information Systems
May 2024
708 pages
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

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Publication History

Published: 23 May 2024

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Author Tags

  1. abnormal hehavior
  2. activity recognition
  3. body angles
  4. parking lots
  5. pose detection
  6. public security

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SBSI '24
SBSI '24: XX Brazilian Symposium on Information Systems
May 20 - 23, 2024
Juiz de Fora, Brazil

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Overall Acceptance Rate 181 of 557 submissions, 32%

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