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Konum belirleme teknolojilerinde yenilikçi yaklaşımlar: LoRaWAN

Year 2025, Volume: 12 Issue: 2, 151 - 162, 04.11.2025
https://doi.org/10.9733/JGG.2025R0011.T

Abstract

Nesnelerin İnterneti (Internet of Things, IoT) kavramı içerisinde insanların ihtiyaçlarına cevap verebilecek birçok uygulama bulunmaktadır. Konum Tabanlı Hizmetler (Location-Based Services, LBS) ve bunlara bağlı olarak geliştirilen uygulamalar bu ihtiyaçlar içerisinde önemli bir yere sahiptir. Küresel anlamda konum hizmeti sağlayan en önemli teknoloji Küresel Navigasyon Uydu Sistemleri (Global Navigation Satellite Systems, GNSS) teknolojisidir. GNSS teknolojisi birçok alanda kullanılmakla birlikte aynı zamanda birçok sektörde vazgeçilmez bir durumdadır. GNSS teknolojisi, LBS uygulamalarının birçoğunda dolayısıyla IoT kavramı içerisinde de yer almaktadır. GNSS teknolojisinin sunduğu hizmetlerin sağladığı birçok avantaj olmasına rağmen bu teknolojinin bazı zayıf yönleri vardır. GNSS teknolojisinin özellikle IoT uygulamaları için maliyetli oluşuyla birlikte enerji verimliliğiyle ilgili problemler, kapalı alanlarda iyi performans verememesi gibi bazı dezavantajlı durumları görülmektedir. Bu durum ise GNSS’in dezavantajlı taraflarını giderebilecek yeni teknolojilerin gelişmesine olanak sağlamaktadır. Bu teknolojilerden biri de LoRaWAN teknolojisidir. Son yıllarda özellikle IoT uygulamaları için oldukça popüler olan ve tercih edilen, veri iletiminde uzun menzil avantajı, enerji verimliliği ve maliyetiyle ön planda olan bu teknoloji konum belirleme konusunda araştırmacıların dikkatini çekmektedir. Bu çalışmada GNSS dışında yenilikçi başkaca konum belirleme sistemleri içerisinde yer alabilme potansiyeli olan LoRaWAN teknolojisi araştırılmış, güçlü ve zayıf yönleri ortaya konulmuş ve bu teknolojinin geleceğiyle ilgili öneriler sunulmuştur.

References

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Innovative approaches in positioning technologies: LoRaWAN

Year 2025, Volume: 12 Issue: 2, 151 - 162, 04.11.2025
https://doi.org/10.9733/JGG.2025R0011.T

Abstract

The Internet of Things (IoT) is a concept with many potential applications that could address people’s needs. Location-Based Services (LBS) and applications developed based on them have an important place in meeting these needs. The most significant technology providing global location services is Global Navigation Satellite Systems (GNSS). GNSS technology has proven indispensable across numerous domains and sectors, having been incorporated into a variety of LBS applications and, consequently, within the broader context of the IoT. However, despite its numerous advantages, its inherent limitations, particularly in the context of IoT applications, include significant costs, energy efficiency issues, and suboptimal performance indoors. This situation enables the development of new technologies that can eliminate the disadvantages of GNSS. One such technology is LoRaWAN. This technology, which has become particularly popular and preferred in recent years, especially for IoT applications, is attracting the attention of researchers in the field of positioning due to its long-range data transmission advantages, energy efficiency, and cost-effectiveness. In this study, LoRaWAN technology, which has the potential to be included in other innovative positioning systems other than GNSS, was investigated, its strengths and weaknesses were revealed, and suggestions for the future of this technology were presented.

References

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  • Aernouts, M., Janssen, T., Berkvens, R., & Weyn, M. (2022). LoRa localization: With GNSS or without?. IEEE Internet of Things Magazine, 5(3), 152-157.
  • Ahmed, S. T., Ahmed, A. A., Annamalai, A., & Chouikha, M. F. (2024). A scalable and energy-efficient lorawan-based geofencing system for remote monitoring of vulnerable communities. IEEE Access, 12, 48540-48554.
  • Ait Mouha, R. A. R. (2021). Internet of things (IoT). Journal of Data Analysis and Information Processing, 9(02), 77.
  • Alkhayyal, M., & Mostafa, A. (2024). Recent Developments in AI and ML for IoT: A Systematic Literature Review on LoRaWAN Energy Efficiency and Performance Optimization. Sensors, 24(14), 4482.
  • Alwahedi, F., Aldhaheri, A., Ferrag, M. A., Battah, A., & Tihanyi, N. (2024). Machine learning techniques for IoT security: Current research and future vision with generative AI and large language models. Internet of Things and Cyber-Physical Systems, 4, 167-185.
  • Anjum, M., Khan, M. A., Hassan, S. A., Jung, H., & Dev, K. (2022). Analysis of time-weighted LoRa-based positioning using machine learning. Computer Communications, 193, 266-278.
  • Asad Ullah, M., Iqbal, J., Hoeller, A., Souza, R. D., & Alves, H. (2019). K-Means Spreading Factor Allocation for Large-Scale LoRa Networks. Sensors, 19(21), 4723.
  • Augustin, A., Yi, J., Clausen, T., & Townsley, W. M. (2016). A Study of LoRa: Long Range & Low Power Networks for the Internet of Things. Sensors, 16(9), 1466.
  • Bagherian, M. H., Tehrani, Y. H., & Atarodi, S. M. (2025). Enhancing LoRaWAN localization efficiency: Leveraging machine learning and optimized parameter tuning for a 60% improvement. Measurement, 242, 116064.
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  • Gonzalez-Palacio, M., Luna-delRisco, M., Garcia-Giraldo, J., Arrieta-Gonzalez, C., Gonzalez-Palacio, L., Roehrig, C., & Le, L. B. (2025). Novel RSSI-Based localization in LoRaWAN using probability density estimation similarity-based techniques. Internet of Things, 31, 101551.
  • Grenier, A., Lohan, E. S., Ometov, A., & Nurmi, J. (2023). A survey on low-power GNSS. IEEE Communications Surveys & Tutorials, 25(3), 1482-1509.
  • Hao, H., Xi, W., Kuster, A., Gamage, A., & Xia, X. (2025). MC-LoRa: Multi-node Concurrent Localization for LoRaWAN Indoors and Outdoors. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies, 9(1), 1-32.
  • Hayati, N., Arifanto, D., Purwanto, K., & Mardian, R. D. (2024, Ağustos). Developing IoT-LoRaWAn Ambulance Tracking System to Enhance Emergency Response. 2024 International Conference on Information Technology and Computing (ICITCOM) içinde, (s. 318-322). Yogyakarta, Endonezya.
  • Ingabire, W., Larijani, H., Gibson, R. M., & Qureshi, A.-U.-H. (2022). LoRaWAN Based Indoor Localization Using Random Neural Networks. Information, 13(6), 303.
  • Jalowiczor, J., Rozhon, J., & Voznak, M. (2021). Study of the Efficiency of Fog Computing in an Optimized LoRaWAN Cloud Architecture. Sensors, 21(9), 3159.
  • Janssen, T., Koppert, A., Berkvens, R., & Weyn, M. (2023). A survey on IoT positioning leveraging LPWAN, GNSS, and LEO-PNT. IEEE Internet of Things Journal, 10(13), 11135-11159.
  • Jouhari, M., Saeed, N., Alouini, M. S., & Amhoud, E. M. (2023). A survey on scalable LoRaWAN for massive IoT: Recent advances, potentials, and challenges. IEEE Communications Surveys & Tutorials, 25(3), 1841-1876.
  • Kaven, S., Bornholdt, L., & Skwarek, V. (2021, Haziran). Authentication by rssi-position based localization in a lora lpwan. 2020 6th IEEE Congress on Information Science and Technology (CiSt) içinde (s. 448-454). Agadir-Süveyr, Fas.
  • Kenan, M. (2021, Nisan). Comparative analysis of localization techniques used in lbs. 2021 5th International Conference on Computing Methodologies and Communication (ICCMC) içinde, (s. 300-304). Erode, Tamil Nadu, Hindistan.
  • Khaled, A. (2024, Mayıs). Smart Location-based Services (Smart-LBS): Platform for Smart Space-Independent LBS. 2024 IEEE International Conference on Electro Information Technology (eIT) içinde, (s. 643-650). Eau Claire, Wisconsin, ABD.
  • Khairullah, E. F., Alghamdi, A. M., Al mojamed, M. M., & Zeadally, S. (2025). LoRaWAN-based smart water management IoT applications: a review. Journal of Information and Telecommunication, 1–27.
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  • Li, Y., Barthelemy, J., Sun, S., Perez, P., & Moran, B. (2021). Urban vehicle localization in public LoRaWan network. IEEE Internet of Things Journal, 9(12), 10283-10294.
  • Li, C., Wang, J., Wang, S., & Zhang, Y. (2024). A review of IoT applications in healthcare. Neurocomputing, 565, 127017.
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There are 59 citations in total.

Details

Primary Language Turkish
Subjects Navigation and Position Fixing, Surveying (Incl. Hydrographic Surveying)
Journal Section Review
Authors

Recep Çakır 0000-0002-2395-4769

Publication Date November 4, 2025
Submission Date July 17, 2025
Acceptance Date September 9, 2025
Published in Issue Year 2025 Volume: 12 Issue: 2

Cite

APA Çakır, R. (2025). Konum belirleme teknolojilerinde yenilikçi yaklaşımlar: LoRaWAN. Jeodezi Ve Jeoinformasyon Dergisi, 12(2), 151-162. https://doi.org/10.9733/JGG.2025R0011.T
AMA Çakır R. Konum belirleme teknolojilerinde yenilikçi yaklaşımlar: LoRaWAN. Jeodezi ve Jeoinformasyon Dergisi. November 2025;12(2):151-162. doi:10.9733/JGG.2025R0011.T
Chicago Çakır, Recep. “Konum Belirleme Teknolojilerinde Yenilikçi Yaklaşımlar: LoRaWAN”. Jeodezi Ve Jeoinformasyon Dergisi 12, no. 2 (November 2025): 151-62. https://doi.org/10.9733/JGG.2025R0011.T.
EndNote Çakır R (November 1, 2025) Konum belirleme teknolojilerinde yenilikçi yaklaşımlar: LoRaWAN. Jeodezi ve Jeoinformasyon Dergisi 12 2 151–162.
IEEE R. Çakır, “Konum belirleme teknolojilerinde yenilikçi yaklaşımlar: LoRaWAN”, Jeodezi ve Jeoinformasyon Dergisi, vol. 12, no. 2, pp. 151–162, 2025, doi: 10.9733/JGG.2025R0011.T.
ISNAD Çakır, Recep. “Konum Belirleme Teknolojilerinde Yenilikçi Yaklaşımlar: LoRaWAN”. Jeodezi ve Jeoinformasyon Dergisi 12/2 (November2025), 151-162. https://doi.org/10.9733/JGG.2025R0011.T.
JAMA Çakır R. Konum belirleme teknolojilerinde yenilikçi yaklaşımlar: LoRaWAN. Jeodezi ve Jeoinformasyon Dergisi. 2025;12:151–162.
MLA Çakır, Recep. “Konum Belirleme Teknolojilerinde Yenilikçi Yaklaşımlar: LoRaWAN”. Jeodezi Ve Jeoinformasyon Dergisi, vol. 12, no. 2, 2025, pp. 151-62, doi:10.9733/JGG.2025R0011.T.
Vancouver Çakır R. Konum belirleme teknolojilerinde yenilikçi yaklaşımlar: LoRaWAN. Jeodezi ve Jeoinformasyon Dergisi. 2025;12(2):151-62.