Steganalysis of Digital Images Using a Deep Fractal Network Approach

This paper presents the design of an automated system for detecting and cleaning dust on photovoltaic (PV) modules. Dust accumulation significantly reduces the efficiency of PV systems by blocking sunlight from reaching the panel surface. The proposed system monitors the voltage and current output from the PV module to calculate power, helping identify any drop in performance due to dust. The circuit design and simulation were carried out using Proteus 8 Professional. The simulation results confirmed that the system could detect a decrease in power output caused by dust buildup. In response, the motor-driven cleaning mechanism was automatically activated. Development is ongoing, and a working prototype is planned to validate the system’s functionality in real-world conditions.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-06-06
DOI
https://doi.org/10.5281/zenodo.15607403
Primary Topic
Currency Recognition and Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Steganalysis of Digital Images Using a Deep Fractal Network Approach

Zenodo (CERN European Organization for Nuclear Research)
Currency Recognition and Detection
article

Steganalysis of Digital Images Using a Deep Fractal Network Approach

article en

Abstract

This paper presents the design of an automated system for detecting and cleaning dust on photovoltaic (PV) modules. Dust accumulation significantly reduces the efficiency of PV systems by blocking sunlight from reaching the panel surface. The proposed system monitors the voltage and current output from the PV module to calculate power, helping identify any drop in performance due to dust. The circuit design and simulation were carried out using Proteus 8 Professional. The simulation results confirmed that the system could detect a decrease in power output caused by dust buildup. In response, the motor-driven cleaning mechanism was automatically activated. Development is ongoing, and a working prototype is planned to validate the system’s functionality in real-world conditions.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 56%
Currency Recognition and Detection
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