Enhancing Decision-Making in Piezoelectric Energy  Harvesting Systems through Neutrosophic Logic

A. A. Salam; Mohamed A. Mohamed; Hanan M. Amer; Musallam Matar Jeailan Hzam AlZubi; Huda  E. Khalid; Ahmed K. Essa

Authors

A. A. Salam Dept. of Math and Computer Sci., Faculty of Science, Port Said Univ., Egypt
Mohamed A. Mohamed Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt;
Hanan M. Amer Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt;
Musallam Matar Jeailan Hzam AlZubi Electronics and Communications Engineering Department, Faculty of Engineering, Mansoura University, Mansoura, Egypt;
Huda E. Khalid University of Telafer, The Administration Assistant for the President of the Telafer University, Telafer, Iraq;
Ahmed K. Essa University of Telafer, The Administration Assistant for the President of the Telafer University, Telafer, Iraq;

Keywords:

Neutrosophic Logic; Piezoelectric Energy Harvesting (PEH); Uncertainty Modeling; Smart Sensing; Arduino-Based Control; Energy Optimization; Internet of Things (IoT); Vibration Analysis

Abstract

in this paper, we introduce a novel decision-making approach of inducing neutrosophic
logic in the piezoelectric energy harvesting (PEH) systems to address uncertainty available in the
environment. The traditional PEH configurations, in particular the Arduino-controlled ones,
generally struggle to provide a constant energy output, which is mainly due to the non-deterministic
character of stimuli of the environment and to noisy sensor signals. The proposed approach follows
a three-valued neutrosophic logic models with truth, indeterminacy, and falsity, that is used for
sensor data classification and energy control i.e., to determine the energy to save in desktop
environment and to reinforce fault diagnosis ability. Performance characteristics are examined in our
experiments and reveal that the proposed approach gains an energy conversion rate rise up to 12
18% using the statistical nondeterministic models, including the phenomena of varying frequency
excitation, the same optimistic efficiency performance is observed. Its improved reliability and
versatility make it an applicable solution for the field of real-life IoT devices and self-powered
wearable electronics with uncertainty.

DOI: 10.5281/zenodo.15648350