Danilo Pena

Profile

Signal processing & AI.
Passionate about systems grounded in theory and designed with purpose.

Projects

Audio Effects

Audio Effects using PortAudio

Real-Time Audio Effects Processor (RT-AEP) using PortAudio API.

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ESC CNN

Sound Classification on STM32

Environmental Sound Classification (ESC) CNN implemented on the STM32.

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AFX

Audio Features

Audio Feature Extraction (AFX) module in Python.

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TDOA Methods

TDOA Methods

A variety of TDOA methods, including angle of arrival (AoA) and robust algorithms.

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MSP430 Course

Course on MSP430

Short course on the MSP430 microcontroller and its applications.

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Selected Publications

Investigation of Feature Selection and Pooling Methods for Environmental Sound Classification

P Dehaghani, D Pena, A P Aguiar

2025 14th International Symposium on Image and Signal Processing and Analysis (ISPA)

This paper explores the impact of dimensionality reduction and pooling methods for Environmental Sound Classification (ESC) using lightweight CNNs.

PDF → arXiv →

Smart Plant Growth Device with Digital Twin Modeling for Precision Agriculture

D Pena, AP Aguiar, F Lobo Pereira, O Hadj-Abdelkader, H Bouzebiba, P Dehaghani

EP Patent EP4483706A1, 2025

A portable compact device for growing plants.

Espacenet →

Energy-Efficient IoT-based Light Control System in Smart Indoor Agriculture

O Hadj Abdelkader, H Bouzebiba, D Pena, AP Aguiar

MDPI Sensors, 2023

Control light system in growth chambers while monitoring the plant factory through wireless communication devices.

PDF → DOI →

A Simulation Tool for the Analysis of TDOA Methods

ABF Diniz, DS Pena, VA de Sousa Jr

IPIN 2021 (11th International Conference on Indoor Positioning and Indoor Navigation)

A simulation tool for evaluation and analysis of TDOA methods.

PDF →

Characterization of Noise Level Inside a Vehicle Under Different Conditions

D Flor, D Pena, L Pena, V A. de Sousa Jr, A Martins

MDPI Sensors, 2020

Evaluation of noise level inside a vehicle using statistical tools.

PDF → DOI →

Acoustic Impulsive Noise Based on Non-Gaussian Models: An Experimental Evaluation

D Pena, C Lima, M Dória, L Pena, A Martins, V Sousa

MDPI Sensors, 2019

Analysis of audio signal corrupted by impulsive noise using non-Gaussian models.

PDF → DOI →

View the full list on Google Scholar →