Lizandro de Souza Oliveira

@ucpel.edu.br

Professor - Master’s degree program in Electronics and Computer Engineering – MEEC
Catholic University of Pelotas

Lizandro de Souza Oliveira


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https://researchid.co/lizandro

RESEARCH, TEACHING, or OTHER INTERESTS

Computer Science, Artificial Intelligence, Electrical and Electronic Engineering, Computer Science Applications
13

Scopus Publications

Scopus Publications

  • AquOculus: A Cost-effective Advanced Metering Infrastructure for Urban Water Distribution Systems
    Matheus Pilotto Figueiredo, Lizandro de Souza Oliveira
    IEEE Latin America Transactions, 2026
    Water consumption Automated Meter Reading (AMR) devices are fundamental to achieving sustainable management in Water Distribution Systems (WDS). However, available solutions are still relatively expensive, and don't feature adequate and synchronized network throughput to attain Leakage Detection and Localization (LDL). As a consequence, AMR installation isn't extended in most cities. As an alternative, we propose the so-called AquOculus Advanced Metering Infrastructure (AMI) system, intended to be a cost-effective solution. This article presents the first results obtained while developing the embryonic AquOculus AMR prototype, consistent with Technology Readiness Level (TRL) 3. It was based on an ESP32 microcontroller and communicated the correct consumed water volume to a remote application via Wi-Fi. An ordinary water meter was leveraged as the main reading instrument, coupled with the developed optoelectronic pulse counter. It doesn't require specific color, metallic, or magnetic parts on the monitored indicator, applying to a wider variety of water meter models. As the water volume counting is indirect, the measurement relies on the factory-calibrated water meter; so the initial validation setup was very simple, using a hairdryer to move the water meter mechanism. Sunlight sensitivity was observed, and the sensor positioning process was demanding. These issues were figured out and discussed for future work. Despite the TRL achieved, this article also addresses the main steps towards the complete AquOculus system. The cost-effective characteristics are expected to boost further studies to allow massive installations by water distribution companies. The developed software repository link was provided for reproducibility.
  • A New Dataset for Analyzing Battery Failures in Wheelchairs
    William M. Manzolli, Tiago B. Rickes, Giancarlo Lucca, Lizandro de Souza Oliveira, Adenauer Correa Yamin
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2025
  • LeakG3PD: A Python Generator and Simulated Water Distribution System Dataset
    Matheus Pilotto Figueiredo, Lizandro de Souza Oliveira, Giancarlo Lucca, Adenauer Correa Yamin, Wesley Huckembeck dos Santos, Tiago da Rosa Lopes
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2025
  • Intf-HybridMem: ωA-IvE Entropy Analysis via Median and Arithmetic Mean Fuzzy Aggregations
    Lidiane C. Silva, Lizandro Oliveira, Helida Santos, Giancarlo Lucca, Benjamin Bedregal, Adenauer Yamin, Renata Reiser
    Lecture Notes in Networks and Systems, 2025
  • Analysis of Bitcoin Trends Through the Integration of On-Chain Financial Indicators and Machine Learning
    Arthur G. Bubolz, Giancarlo Lucca, Lizandro de S. Oliveira, Thiago Teixeira, Rafael A. Berri, Eduardo N. Borges, Bruno L. Dalmazo
    Lecture Notes in Computer Science, 2025
  • IBM-Qiskit Simulations for Quantum-Fuzzy Interpretations of X(N)or-Connectives using Overlapping and Grouping Aggregations
    Juliano S. Buss, Bruna Novack, Helida S. Santos, Giancarlo Lucca, Lizandro Oliveira, Adenauer C. Yamin, Anderson P. Cruz, Renata H. Reiser
    IEEE International Conference on Fuzzy Systems, 2025
    This study aims to contribute to the broader dissemination of knowledge concerning quantum fuzzy computing. Combining characteristics and exploring fusion information by Fuzzy Logic and Quantum Computing, this work extends the quantum interpretation in the class of fuzzy Xor-connectives. Firstly, the X(N)or-connective is defined using aggregation functions. Additionally, the results are validated in the Qfuzzy-Analyser, a computational component providing methodologies for algebraic analysis and logical interpretation of flexible systems via quantum circuit modeling. This study considers the well-known IBM Qiskit simulator, which enables execution and graphical representations for fuzzy X(N)or-connectives, including quantum circuits and many tools to observe the evolution of flexible systems and quantum-fuzzy interpretations.
  • A Ubiquitous Learning Approach on Robotics
    Fernanda P. Mota, Rebeca B. Kalbermatter, Lizandro De S. Oliveira, José Lima
    Proceedings 2023 Latin American Robotics Symposium 2023 Brazilian Symposium on Robotics and 2023 Workshop of Robotics in Education LARS Sbr Wre 2023, 2023
    Ubiquitous learning refers to the integration of learning processes with everyday environments and activities using technology. By leveraging ubiquitous learning principles in the field of robotics, we can foster an immersive and interactive learning environment that promotes continuous learning and knowledge acquisition. This paper presents an in-depth exploration of a ubiquitous learning approach for robotics with the aim to enhance the educational experiences and capabilities of robotic systems. Furthermore, it explores the potential benefits and challenges of ubiquitous learning in the field of robotics, such as increased adaptability, personalized learning experiences, and the development of lifelong learning skills. The results indicate that a ubiquitous learning approach can significantly enhance the learning capabilities of students.
  • Exploring fuzzy set consensus analysis in IoT resource ranking
    Lizandro de Souza Oliveira, Amanda Argou, Renato Dilli, Adenauer Yamin, Renata Reiser, Benjamín Bedregal
    Engineering Applications of Artificial Intelligence, 2022
  • Toward a Fuzzy Logic-Based Consensus Analysis in Hybrid Memory Management
    Lizandro De Souza Oliveira, Rodrigo Costa De Moura, Guilherme Bayer Schneider, Mauricio Lima Pilla, Adenauer Correa Yamin, Renata Hax Sander Reiser, Benjamin Rene Callejas Bedregal
    IEEE International Conference on Fuzzy Systems, 2021
    This paper explores fuzzy logic-based consensus analysis as support to the decision making problem related to page migrations in hybrid memories. The proposed interval fuzzy approach considers the uncertainties on data access profiles in hybrid memories and its main characteristics. The fuzzy set consensus analysis, in its turn, is proposed using arithmetic and exponential extended aggregations. Aiming to evaluate the proposal, a case study was developed in the Intf-HybridMem memory management architecture.
  • Intf-HybridMem: Page migration in hybrid memories considering cost efficiency
    Rodrigo Costa de Moura, Lizandro de Souza Oliveira, Guilherme Bayer Schneider, Mauricio Lima Pilla, Adenauer Correa Yamin, Renata Hax Sander Reiser
    Sustainable Computing Informatics and Systems, 2021
  • A Proposal for Hybrid Memories Management Exploring Fuzzy-Based Page Migration Policy
    Lizandro de Souza Oliveira, Rodrigo Costa de Moura, Guilherme Bayer Schneider, Adenauer Correa Yamin, Renata Hax Sander Reiser
    Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics, 2021
  • F-HybridMem: A fuzzy-based approach for decision support in hybrid memory management
    Rodrigo Costa de Moura, Guilherme Bayer Schneider, Lizandro de Souza Oliveira, Mauricio Lima Pilla, Adenauer Correa Yamin, Renata Hax Sander Reiser
    IEEE International Conference on Fuzzy Systems, 2020
  • Survey of memory optimization techniques for embedded systems
    Lizandro Oliveira, Julio C. B. Mattos, Lisane Brisolara
    Brazilian Symposium on Computing System Engineering Sbesc, 2013