A Low-Cost Soil Moisture Monitoring Method by Using Walabot and Machine Learning Algorithms

This chapter introduces an economical soil moisture monitoring method utilizing Walabot technology and machine learning algorithms. The chapter initiates with an introduction, emphasizing the importance of cost-effective solutions for soil moisture assessment in digital agriculture. The Materials and Methods section provides an overview of the study site, the utilization of the proximate sensor, and the experimental setup, along with details on data collection and processing. The chapter emphasizes the affordability and accessibility of the Walabot-based approach. The Results and Discussion section presents the outcomes of the experiments, showcasing the performance of linear discriminant analysis and principal component analysis in soil moisture estimation. The chapter concludes with a summary, underlining the potential of this low-cost method for widespread soil moisture monitoring. References are provided for further exploration of the methodologies and technologies discussed in this chapter.