Smarttag: An Indoor Positioning System Based on Smart Transmit Power Scheme Using Active Tags


ŞAHİN S., ÖZCAN H., KÜÇÜK K.

IEEE ACCESS, cilt.6, ss.23500-23510, 2018 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 6
  • Basım Tarihi: 2018
  • Doi Numarası: 10.1109/access.2018.2824538
  • Dergi Adı: IEEE ACCESS
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.23500-23510
  • Anahtar Kelimeler: Indoor localization, Monte Carlo methods, NRF24L radio modules, path loss model, smart tags, trilateration
  • Kocaeli Üniversitesi Adresli: Evet

Özet

There are no large-scale deployments to navigate the people indoor environments as the GPS for outdoor environments. For this reason, the development of high-performance systems of indoor localization has been considered the potential research areas by both academia and industry in last decade. These indoor localization research studies are divided into two groups in the literature which are reader-based and tag-based systems. Most of these studies are reader-based. These readers and tags can determine the received signal strength levels of the signal using the radio frequency technology. We present a tag-based and cost-effective indoor localization system using NRF24L series radio modules. Different from the available tag-based systems, we propose a smart transmit power scheme run in the tags called SmartTag. The SmartTag provides communication with the nearest reader using different power levels. However, the existing tag-based methods require the received signal strength indicator (RSSI) information to achieve high localization accuracy. Our proposed system eliminates RSSI information with the SmartTag. We have developed a simulation of the prototype system, and we used Monte Carlo simulations in many different scenarios. We have also implemented the system prototype and conducted in an actual indoor environment to demonstrate the performance of the SmartTag by comparing with the Monte Carlo simulations. From the indoor experimental results, we confirm that the detections of room and objects are accurate and positioning accuracy is improved thanks to the SmartTag localization. If we briefly summarize our work, we have determined the position in indoor environments by communicating with the nearest reader in the medium thanks to the scheme on the SmartTag.