Performance analysis of in situ ion selective electrodes with estimation filter

• Main Author: Lai, Francis P.
• Format: text
• Published: Animo Repository 2011
• Subjects: Multisensor data fusion; Data logging; Kalman filtering; Computer Sciences
• Online Access: https://animorepository.dlsu.edu.ph/faculty_research/7573
• Institution: De La Salle University

In situ environmental sensors for agriculture are still under development and have been proven to be quite expensive for most agricultural applications. Low-cost sensors exists however, they are much more sensitive to drift and other ex­ternal interferences thus producing erroneous results. Very few researchers have used Estimation Filters to address these sensor limitations and to improve the accuracy. The experiments were done under laboratory conditions however with varying environmental conditions the results may differ. This study aims to use estimation filters, such as a Bayes or a Kalman filters, to improve on low-cost in situ environmental sensors such as Ion-Selective Electrodes (ISE).