Journals / Journal of Artificial Intelligence and Data Science / 2026 / Cilt: 1 Sayı: 1

Social Distancing Automation Software Based on Cloud

Ali Şahin Demir(MANISA CELAL BAYAR UNIVERSITY)
Sevcan Emek(MANISA CELAL BAYAR UNIVERSITY)
Pages
59–62
Publication Date
2021-08-30
DOI
—
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Both employees and employers will be able to observe social distance tracking by providing access to the cloud.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This study aims to follow the social distance between people working together in a workplace.
📊
Key Findings & Data:It is extremely important to provide a healthy workplace by both employers and employees during the pandemic.
💡
Conclusion & Impact:Both employees and employers will be able to observe social distance tracking by providing access to the cloud.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Cloud · IoT · social distancing automation

Abstract

This study aims to follow the social distance between people working together in a workplace. It is extremely important to provide a healthy workplace by both employers and employees during the pandemic. One of the measures taken during the pandemic is to ensure social distance. In this study, an IoT (Internet of Things) based circuit design is created that measure the distance between people working together. Social distancing automation software has been developed that stores information of employees such as name, surname, identity id, and the department they work in the cloud. Measurements taken from the circuit, which will track the distance of the employees, can be transferred to the cloud with this automation application. Both employees and employers will be able to observe social distance tracking by providing access to the cloud.

🔖

Cite This Article

Demir, A. Ş., Emek, S. (2021). Social Distancing Automation Software Based on Cloud. Journal of Artificial Intelligence and Data Science, Cilt: 1 Sayı: 1, 59–62. https://ajindex.com/articles/1618351

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (5)

  1. T.C. Aile Çalışma ve Sosyal Hizmetler Bakanlığı, “Yeni Koronavirüs Salgini Kapsaminda İş Sağlığı ve Güvenliği Profesyonellerinin İşyerlerinde Aldıracağı Tedbirler,” [Online]. Available: https://ailevecalisma.gov.tr/media/42183/yenikoronavirus-salgini-kapsaminda-is-sagligi-ve-guvenligi-profesyonellerinin-isyerlerinde-aldiracagi-tedbirler.pdf [Accessed July 16, 2021].
  2. A. Gad, G. ElBary, M. Alkhedher, and M. Ghazal, “Vision-based approach for automated social distance violators detection,” 2020 International Conference on Innovation and Intelligence for Informatics, Computing and Technologies (3ICT), ‘2020, pp. 1-5, doi: 10.1109/3ICT51146.2020.9311969.
  3. S. Siddiqui, M. Z. Shakir, A. A. Khan, and I. Day, “Internet of things (IoT) enabled architecture for social distancing during pandemic”, Frontiers in Communications and Networks, vol. 2, 2021. https://doi.org/10.3389/frcmn.2021.614166
  4. X. V. Wang, and L. Wang, “A literature survey of the robotic technologies during the COVID-19 pandemic”, Journal of Manufacturing Systems, 2021. https://doi.org/10.1016/j.jmsy.2021.02.005
  5. Ainstein, “5 IoT implementations for social distancing management,” [Online]. Available: https://ainstein.ai/ebook-5-iotimplementations-for-social-distancing-management/ [Accessed July 16, 2021]