European Journal of Molecular & Clinical Medicine

Abstract

Sensing in forest area is the most widely used application concerning investigation studies
of climate change. Wireless sensor networks with spatially scattered sensors enable the
application to record climate change disturbance detecting condition changes in
temperature, humidity, sound, wind, etc. The highly automated method herein can pass the
observed information bi-directionally to the system sink, empowering sensor activity
control. It is common knowledge that a multisensor environment has hundreds or
thousands of sensor nodes connected. With recent innovations, the remarkable challenge
faced in a multisensor climate is to rapidly acquire specific information from a reliable
route exhibiting high data accuracy. This proposed ADKF-DT-MF algorithm for
multisensor data fusion combines sensor information in-continuous time, providing a
rapid information exchange on climate change for environmental awareness. The findings
significantly show a better RMSE of 0.85 than the previous results reported in the
literature MHT-EnKF. The quality of estimation was explored, calculating the best costs,
ensuring an increase in data fusion accuracy for active awareness. The tests on simulated
data applying fuzzy membership optimization function show improvement in the ADKFDT-
MF multisensor fusion system's performance.