Efficient Soil Moisture Monitoring without In-Situ Probes: LSTM-Based Bluetooth Signal Strengths Analysis

Selçuk Yazar; Deniz Taşkın; Erdem Bahar

doi:10.59314/tujes.1464575

EN TR

Efficient Soil Moisture Monitoring without In-Situ Probes: LSTM-Based Bluetooth Signal Strengths Analysis

Abstract

Soil moisture measurement without damaging soil structure is important in agriculture. Electrical conductivity and microwaves are commonly used for this purpose. Recently, there has been growing interest in using artificial neural networks and time series forecasting to determine soil moisture content. Bluetooth signals, similar to microwave devices, are utilized in these measurements. However, Bluetooth signals have low transmission power compared to dedicated soil moisture measurement devices. This study investigates the possibility of determining soil moisture content using Long Short-Term Memory (LSTM) neural network architecture and Bluetooth signal strengths with 0.001 Watt transmission power, specifically for soil samples with varying pH values. The objective was to assess soil moisture change status directly using Bluetooth signal levels without an in-situ probe. In an experimental study, soil moisture content changing was predicted with a root-mean-square error (RMSE) value of 15% using an artificial learning model based on Bluetooth signal strengths obtained from alkali soil samples. This method eliminates the need for a dedicated sensor, as soil moisture can be reliably measured by tracking signal level changes over time.

Keywords

Bluetooth Low Energy , Deep learning , Long Short-Term Memory , Active microwaves , Soil moisture

Yerinde Problar Olmadan Etkili Toprak Nemi İzleme: LSTM Tabanlı Bluetooth Sinyal Gücü Analizi

Öz

Toprak yapısına zarar vermeden toprak nemi ölçümü tarımda önemlidir. Elektriksel iletkenlik ve mikrodalgalar bu amaçla yaygın olarak kullanılmaktadır. Son zamanlarda, toprak nem içeriğini belirlemek için yapay sinir ağları ve zaman serisi tahminlerinin kullanılmasına olan ilgi artmaktadır. Bu ölçümlerde mikrodalga cihazlara benzer şekilde Bluetooth sinyallerinden yararlanılmaktadır. Ancak Bluetooth sinyalleri, özel toprak nemi ölçüm cihazlarına kıyasla düşük iletim gücüne sahiptir. Bu çalışmada, Uzun Kısa Süreli Bellek (LSTM) sinir ağı mimarisi ve 0,001 Watt iletim gücüne sahip Bluetooth sinyal güçleri kullanılarak, özellikle farklı pH değerlerine sahip toprak örnekleri için toprak nem içeriğinin belirlenme olasılığı araştırılmaktadır. Amaç, toprak nem değişim durumunu yerinde bir prob olmadan doğrudan Bluetooth sinyal seviyelerini kullanarak değerlendirmekti. Deneysel bir çalışmada, alkali toprak örneklerinden elde edilen Bluetooth sinyal güçlerine dayalı bir yapay öğrenme modeli kullanılarak toprak nem içeriği değişimi %15'lik bir kök-ortalama-kare hata (RMSE) değeri ile tahmin edilmiştir. Bu yöntem, toprak nemi zaman içindeki sinyal seviyesi değişiklikleri izlenerek güvenilir bir şekilde ölçülebildiğinden, özel bir sensör ihtiyacını ortadan kaldırmaktadır.

Anahtar Kelimeler

Bluetooth Düşük Enerji , Derin öğrenme , Uzun-Kısa Süreli Bellek , Aktif mikrodalgalar , Toprak nemi

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Details

Primary Language

English

Subjects

Information Systems Development Methodologies and Practice , Information Systems (Other)

Journal Section

Research Article

Authors

Selçuk Yazar ^*
0000-0001-6567-4995
Türkiye

Deniz Taşkın
0000-0001-7374-8165
Türkiye

Erdem Bahar
0000-0002-2579-5060
Türkiye

Early Pub Date

June 29, 2024

Publication Date

June 30, 2024

Submission Date

April 3, 2024

Acceptance Date

June 24, 2024

Published in Issue

Year 2024 Volume: 25 Number: 1

DOI

https://doi.org/10.59314/tujes.1464575

IZ

https://izlik.org/JA49PN53KX

IEEE

[1]S. Yazar, D. Taşkın, and E. Bahar, “Efficient Soil Moisture Monitoring without In-Situ Probes: LSTM-Based Bluetooth Signal Strengths Analysis”, TUJES, vol. 25, no. 1, pp. 21–38, June 2024, doi: 10.59314/tujes.1464575.

Efficient Soil Moisture Monitoring without In-Situ Probes: LSTM-Based Bluetooth Signal Strengths Analysis

Abstract

Keywords

Yerinde Problar Olmadan Etkili Toprak Nemi İzleme: LSTM Tabanlı Bluetooth Sinyal Gücü Analizi

Öz

Anahtar Kelimeler

References

Details

Primary Language

Subjects

Journal Section

Authors

Early Pub Date

Publication Date

Submission Date

Acceptance Date

Published in Issue

DOI

IZ

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