IoT-Integrated Bio-Impedance Monitoring for Enhanced Agricultural Applications

A non-invasive bio-impedance technique provides a quick response to small changes in the electrical impedance of a phantom or object, making it suitable for agriculture-based applications. This method generates high-frequency, low-current signals that vary with impedance changes in the phantom (e.g., papaya) detected through paired electrodes. The electrodes, positioned at either end of the cylindrical phantom, measure electrical impedance based on voltage changes in response to constant current insertion. Reconstruction algorithms designed in MATLAB generate electrical impedance images using initial conductivity and measured potentials. Electrical Impedance Tomography applies forward and inverse solutions to estimate conductivity distribution within an object, leveraging finite element meshes with triangular elements for computational accuracy. The forward problem involves determining current magnitude in a homogeneous conducting medium. This study developed a GUI-based reconstruction algorithm for the agricultural phantom model using MATLAB. Data acquisition integrates Internet of Things technology, connecting sensors to the GUI system and further to remote monitoring systems. This enables real-time parameter monitoring for agricultural phantom applications. The IoT-based approach demonstrates versatility for agriculture and medical applications, offering efficient, remote-access monitoring of critical parameters.