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1.
Sensors (Basel) ; 23(16)2023 Aug 16.
Artigo em Inglês | MEDLINE | ID: mdl-37631747

RESUMO

Developing a low-cost wireless energy meter with power quality measurements for smart grid applications represents a significant advance in efficient and accurate electric energy monitoring. In increasingly complex and interconnected electric systems, this device will be essential for a wide range of applications, such as smart grids, by introducing a real-time energy monitoring system. In light of this, smart meters can offer greater opportunities for sustainable and efficient energy use and improve the utilization of energy sources, especially those that are nonrenewable. According to the 2020 International Energy Agency (IEA) report, nonrenewable energy sources represent 65% of the global supply chain. The smart meter developed in this work is based on the ESP32 microcontroller and easily accessible components since it includes a user-friendly development platform that offers a cost-effective solution while ensuring reliable performance. The main objective of developing the smart meters was to enhance the software and simplify the hardware. Unlike traditional meters that calculate electrical parameters by means of complex circuits in hardware, this project performed the calculations directly on the microcontroller. This procedure reduced the complexity of the hardware by simplifying the meter design. Owing to the high-performance processing capability of the microcontroller, efficient and accurate calculations of electrical parameters could be achieved without the need for additional circuits. This software-driven approach with simplified hardware led to benefits, such as reduced production costs, lower energy consumption, and a meter with improved accuracy, as well as updates on flexibility. Furthermore, the integrated wireless connectivity in the microcontroller enables the collected data to be transmitted to remote monitoring systems for later analysis. The innovative feature of this smart meter lies in the fact that it has readily available components, along with the ESP32 chip, which results in a low-cost smart meter with performance that is comparable to other meters available on the market. Moreover, it is has the capacity to incorporate IoT and artificial intelligence applications. The developed smart meter is cost effective and energy efficient, and offers benefits with regard to flexibility, and thus represents an innovative, efficient, and versatile solution for smart grid applications.

2.
Micromachines (Basel) ; 12(10)2021 Sep 30.
Artigo em Inglês | MEDLINE | ID: mdl-34683246

RESUMO

Network-on-Chip is a good approach to working on intra-chip communication. Networks with irregular topologies may be better suited for specific applications because of their architectural nature. A good design space exploration can help the design of the network to obtain more optimized topologies. This paper proposes a way of optimizing networks with irregular topologies through the use of a genetic algorithm. The network proposed here has heterogeneous routers that aim to optimize the network and support applications with real-time tasks. The goal is to find networks that are optimized for average latency and percentage of real-time packets delivered within the deadline. The results show that we have been able to find networks that can deliver all the real-time packets, obtain acceptable latency values, and shrink the chip area.

3.
Data Brief ; 27: 104725, 2019 Dec.
Artigo em Inglês | MEDLINE | ID: mdl-31737764

RESUMO

This article presents data from an extensive set of simulation-based experiments to compare the performance of on-chip communication architectures. These experiments were performed using the RedScarf simulation environment [1], which is described in the article entitled 'RedScarf: an open-source multi-platform simulation environment for performance evaluation of Networks-on-Chip' [2]. In the experiments presented here, several intra-chip communication architectures were compared under different traffic patterns. Latency, jitter, and throughput metrics were collected. Data is useful for researchers investigating on-chip communication architectures who need baseline data for comparison.

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