Design and validation of IoT based smart classroom


YAĞANOĞLU M., BOZKURT F., GÜNAY F. B., KUL S., Şimşek E., ÖZTÜRK G., ...Daha Fazla

MULTIMEDIA TOOLS AND APPLICATIONS, cilt.83, sa.22, ss.62019-62043, 2023 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 83 Sayı: 22
  • Basım Tarihi: 2023
  • Doi Numarası: 10.1007/s11042-023-15872-2
  • Dergi Adı: MULTIMEDIA TOOLS AND APPLICATIONS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus, FRANCIS, ABI/INFORM, Applied Science & Technology Source, Compendex, Computer & Applied Sciences, INSPEC, zbMATH
  • Sayfa Sayıları: ss.62019-62043
  • Anahtar Kelimeler: Anomaly detection, IoT, New generation classroom, Smart classroom
  • Atatürk Üniversitesi Adresli: Evet

Özet

The smart campus is an educational campus concept that uses innovative technologies such as the Internet of Things (IoT), cloud computing, with integrated information systems to support learning, teaching and administrative activities. It is one of the important outputs of smart campus applications that these technologies support students, lecturers, and administrators by performing multi-tasking in multi-functional buildings. It is an important step to create smart classrooms with intelligent systems with the aim of developing a smart campus. For this reason, it is necessary to create smart classrooms for a smart campus and to expand it throughout the campus. In this study, it is aimed to monitor the environmental parameters in the classroom environments in real time and to develop a smart classroom concept that provides energy savings and air conditioning based on the analysis of these data. It is expected that an educational effect will occur on the attention span of the students through the automatic improvement of physical conditions as well as administrative convenience in terms of ensuring security and increasing savings in company with an efficient and applicable system architecture. In this study, tests were performed for 7 different scenarios and the best accuracy and sensitivity were calculated as 98%, and the best specifity as 100%.