ItemConference Paper

Smart People Counting System by Enhancing Accuracy and Affordability with YOLOv5 and Cloud-Based Integration

Title
Smart People Counting System by Enhancing Accuracy and Affordability with YOLOv5 and Cloud-Based Integration
Creator
Maharajan, M.S.; Abirami, T.; Jayadharshini, P.; Krishnasamy, Lalitha; Priyanka, S.; Aravinth, S.
Description
Considering that all moving objects are humans, much of the work in data is based on recognizing and tracking moving objects. In this work, we present a method for counting peoples faces. Even though we use the face mask, the deep learning-based YOLOv5 algorithm and Faster R-CNN allow us to recognize the face. We do a very good job of counting people. To make the calculation more accurate, we introduced a new type of intelligent small scale computing system consisting of cheaper hardware and user-friendly cloud computing software. These findings show that intelligent computing systems can realize human vision. Additionally, by combining inexpensive hardware with cloud-based software, the planning process becomes more transparent and cost-effective. Finally, the web application allows users to view the number of authorized and unauthorized users. Based on the results obtained from this method, the deep learning YOLOv5 algorithm is used to identify and match human images to increase security, and thanks to cloud storage, users can easily view all calculated results, increasing the accuracy by 98.53%. Owing to the truth that most of the secure watches cannot be able to check each and each individual The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
Source
Lecture Notes in Networks and Systems;Volume;1314 LNNS;pp.115-125
Date
01-01-2025
Publisher
Springer Science and Business Media Deutschland GmbH
Coverage
Maharajan M.S., Department of Artificial Intelligence and Data Science, Panimalar Engineering College, Tamilnadu, Chennai, India; Abirami T., Department of Information Technology, Kongu Engineering College, Tamil Nadu, Perundurai, India; Jayadharshini P., Department of Artificial Intelligence, Kongu Engineering College, Tamil Nadu, Perundurai, India; Krishnasamy L., Department of CSE, School of Engineering and Technology, CHRIST University, Bangalore, Kengeri, India; Priyanka S., Department of Artificial Intelligence, Kongu Engineering College, Tamil Nadu, Perundurai, India; Aravinth S., Department of Information Technology, Kongu Engineering College, Tamil Nadu, Perundurai, India
Rights
Restricted Access; Hardcopy may be available in the library
Relation
ISSN: 23673370; ISBN: 978-981963796-6;
Format
online
Language
English
Type
Conference paper

Citation

Maharajan, M.S.; Abirami, T.; Jayadharshini, P.; Krishnasamy, Lalitha; Priyanka, S.; Aravinth, S., “Smart People Counting System by Enhancing Accuracy and Affordability with YOLOv5 and Cloud-Based Integration,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 19, 2026, https://archives.christuniversity.in/items/show/25516.

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