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A spatiotemporal data acquisition toolkit for volume estimation tools in precision agriculture
Author(s) -
Lee SeongHun,
Park Jaehwa
Publication year - 2019
Publication title -
concurrency and computation: practice and experience
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.309
H-Index - 67
eISSN - 1532-0634
pISSN - 1532-0626
DOI - 10.1002/cpe.5258
Subject(s) - data acquisition , computer science , volume (thermodynamics) , projection (relational algebra) , precision agriculture , range (aeronautics) , software , noise (video) , data processing , data mining , computer vision , algorithm , database , engineering , agriculture , geography , physics , archaeology , quantum mechanics , operating system , programming language , aerospace engineering , image (mathematics)
Summary A data acquisition system for precision agriculture is presented. The system can collects various time‐series data on target plants and their environmental facts. The designed system consists of a server and multiple intra‐networked stations and includes a software toolkit that has two independent but synchronized data acquisition processes. The one is for measurements on environmental facts around a target plant and the other is for volume estimation of the target plant adopting multi‐view stereo techniques. An analysis on sampling rate and data acquisition experiments for testing purposes were performed. A data filtering method based on the fast Fourier transform is applied to analyze the noise immunity of the collected data. For the volume estimation, three different methods, ie, method‐I using 2‐D projection on slices, method‐II using polyhedrons on voxels, and method‐III using enclosed surfaces, were devised to handle various plant types and examined for three different type of target plants. The volume estimation errors were measured in range of 6 ∼ 30% in the experiments.