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Low-cost real-time environmental noise monitoring system design and implementation

International Journal of Environmental Studies 2024年第3期81卷 1045-1057页

作者： Hamamcı, Samet Feyyaz Doğru, Ahmet Özgür Graduate School Geographical Information Technologies PhD Program Istanbul Technical University Istanbul Turkey Faculty of Civil Engineering Department of Geomatics Engineering Istanbul Technical University Istanbul Turkey

Environmental noise has a negative impact on human health and well-being. Real-time noise monitoring for effective noise control and management helps to identify noise sources and areas with high noise pollution, and potential mitigation strategies in urban planning. This paper reports work with a pilot scale system that can continuously collect noise data to assess noise levels accurately for real-time monitoring of environmental noise, focusing on hardware and software aspects and potential applications. The system permits the transfer of measurement data to the central server computer, with storage and display there, with the code written using Python. This system includes Web integration, with open source technologies to provide data access, and is based on Wi-Fi communication and a Control Card with Wi-Fi technology. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Noise pollution

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Smart Parking System with IoT-Enabled using NodeMCU for Car Reservation in Public Areas 2

Smart Parking System with IoT-Enabled using NodeMCU for Car ...

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2nd IEEE International Conference on electrical engineering, Computer and Information Technology, ICEECIT 2024

作者： Simatupang, Joni Welman Alfarizi, Yosep Salman Electrical Engineering Study Program Faculty of Engineering President University Cikarang Indonesia

ISBN: (纸本)9798331504373

This paper presents the smart parking system using NodeMCU ESP8266 for web-based car reservation in public areas. Conventional parking system made car users take a long time to find the parking in public areas like shopping centers or malls. Therefore, its necessary to overcome this problem by implementing the smart parking system of car reservation. The system prototype integrates the Internet of Things (IoT) technology, NodeMCU ESP8266 (microcontroller), Ultrasonic Sensor HC-SR04 (vehicle detector sensor in parking area), IR obstacle sensor (entry and exit), SG90 Servo (at the entry and exit gate) and Firebase to create a real-time database connected to a web platform. The system provides real-time slot availability information via the web platform and LCD as information at the entrance gate. Users can easily make and cancel reservations with additional features such as OTP verification, and automatic booking cancellation have been successfully implemented. The prototype test method consist of calibration test, sending OTP test, automatic booking cancellation test and manual booking cancellation test. The result of calibration test on 10 cm range have a 80% success rate for ultrasonic sensor 1 as well as the result of ultrasonic sensor 2. While, additional features test result such as sending OTP, automatic booking cancellation, and manual booking cancellation having 100% success rate. It can be concluded that this prototype is successfully implemented and reach the goals with minimum error can be tolerated. The authors suggest to adding a keypad and payment system to this prototype for improvement in the future. © 2024 IEEE.

关键词： Ultrasonic sensors

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Ant Colony Optimization-Based Path Planning for Autonomous Vehicle Navigation Systems 4

Ant Colony Optimization-Based Path Planning for Autonomous V...

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4th International Conference on electrical engineering and Computer Science, ICECOS 2024

作者： Sari, Desi Windi Dwijayanti, Suci Suprapto, Bhakti Yudho Universitas Sriwijaya Faculty of Engineering Department of Electrical Engineering Doctoral Program in Engineering Science Palembang Indonesia Universitas Sriwijaya Faculty of Engineering Department of Electrical Engineering Palembang Indonesia

ISBN: (纸本)9798350368253

A crucial aspect of autonomous vehicles is path planning, which involves using various algorithms to determine the most efficient routes. This study investigates the application of the Ant Colony Optimization (ACO) algorithm to create a system for identifying the shortest path. The process includes collecting coordinate data from specific test locations on the Universitas Sriwijaya Indralaya campus to generate a graph-based map for analysis. The study begins with gathering route data through the Google Maps application, which includes 182 routes. In simulation tests, the routes generated by ACO differ from those suggested by Google Maps;sometimes, the ACO route is longer and sometimes shorter, due to the probabilistic nature of the ACO algorithm in finding optimal routes. The average error compared to Google Maps is 11.7 meters. Additional tests introduce obstacles on the road, requiring the system to find alternative routes. For instance, the initial route from the auditorium to the faculty of Science and Math is 38-39-11-53-110-54-111 with a route length of 670 m. After adding a roadblock in front of the faculty of engineering, the route changes to 38-39-116-40-70-69-56-111, with a route length of 730 meters. These tests demonstrate that the ACO algorithm effectively identifies the best routes for autonomous vehicles, both under normal conditions and when obstacles are present. © 2024 IEEE.

关键词： Ant colony optimization

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Design and Analysis of an Optical Fiber Network for Vehicles Sensing System

Design and Analysis of an Optical Fiber Network for Vehicles...

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2024 International Conference on electrical and Information Technology, IEIT 2024

作者： Adriansyah, Muhammad Athallah Natali, Yus Apriono, Catur Universitas Indonesia Faculty of Engineering Department of Electrical Engineering Depok Indonesia Telkom University Telecommunication Engineering Program Faculty of Engineering Jakarta Indonesia

ISBN: (纸本)9798331516888

The increasing number of accidents on toll roads, predominantly caused by human error, underscores the critical need for enhanced vehicular safety systems. This research introduces a novel optical fiber network design that utilizes polymer optical fiber (POF) as both a sensor and communication medium to significantly improve the reliability and response time of vehicle safety mechanisms. The system was carefully developed and simulated using OptiSystem software, incorporating key components such as a continuous-wave laser operating at 1310 nm, NRZ encoding, and a Mach-Zehnder modulator, all chosen for their ability to optimize data transmission and minimize signal degradation. Comprehensive simulations were conducted to evaluate the system's performance, focusing on parameters like bit error rate (BER), signal integrity, and response time. The results demonstrate that the proposed design achieves a Q factor of 5.2628, an output power of -14.049 dBm, and a rise time of 0.07 ns. Additionally, the system's power margin of 13.951 dB confirms its robustness and suitability for real-world implementation with the potential to be a viable solution for advancing vehicular safety technologies. © 2024 IEEE.

关键词： Continuous wave lasers

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Deep Convolutional Neural Networks for Accurate Solar Module Classification in Thermal Images 12

Deep Convolutional Neural Networks for Accurate Solar Module...

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12th International electrical engineering Congress, iEECON 2024

作者： Phungket, Chutinun Nangthin, Prasit Pathumwan Institute Of Technology The Graduate Program Faculty Of Engineering Faculty Of Engineering Bangkok Thailand Pathumwan Institute Of Technology Faculty Of Engineering Department Of Electrical Engineering Bangkok Thailand

ISBN: (纸本)9798350383591

The rapid and continuous technological advancements in computer and internet technologies, combined with data management techniques, find applications in various domains. For example, they aid in predictive maintenance systems, evaluate the performance of solar modules, and differentiate efficiently performing solar modules from less efficient ones using thermal imagery. The accuracy of solar module classification significantly impacts the subsequent assessment. In this study, we employ advanced techniques, particularly deep learning through Convolutional Neural Networks (CNN), to classify thermal images of solar modules. The practical aspects of applying CNN to the dataset of thermal images are explored, including transfer learning from pretrained CNN architectures and custom CNN architecture training. Experiments are conducted with three prominent types of solar module conditions: normal, cracked, and dusty. The results reveal that the most effective approach involves learning and fine-tuning pre-trained architectures on detailed studies, achieving a classification accuracy of up to 94.5% © 2024 IEEE.

关键词： Convolutional neural networks

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Variable Length Multi-Objective Whale Optimization for Trust Aware Data Gathering in Wireless Sensor Network

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IEEE Access 2025年 13卷 32100-32121页

作者： Saad, Mohammed Ayad Jaafar, Rosmina Chellappan, Kalaivani Faculty of Engineering and Built Environment Department of Electrical Electronics and System Engineering Selangor Bangi43600 Malaysia Al-Kitab University Department of Medical Instrumentations Technique Engineering Kirkuk36001 Iraq Universitas Airlangga Biomedical Engineering Study Program Faculty of Science and Technology Surabaya60115 Indonesia

Efficient data collection in wireless sensor networks (WSNs) is crucial. While traditional approaches rely on stationary data sinks, the use of mobile sinks, like unmanned aerial vehicles (UAVs), has shown promise in enhancing data-gathering capabilities. However, existing methods often overlook the importance of trust, leaving the network susceptible to malicious or faulty nodes. To address this issue, we propose a novel trust-aware data-gathering algorithm, Variable Length Multi-Objective Whale Optimization Data Gathering (VLMOWO-DG). Our algorithm simultaneously optimizes energy consumption, delay, and trust while employing mobile sinks to collect data from sensor nodes. By considering trust as a key performance metric, we improve data reliability and security. The VLMOWO-DG algorithm introduces flexibility through variable-length solution representation and application-oriented operators, allowing for efficient exploration of the solution space. Simulation results demonstrate that our proposed algorithm significantly outperforms established benchmarks, NSGA-II and NSGA-III, in terms of domination and hypervolume. This leads to a remarkable improvement of 200% in data gathering performance. © 2015 The Authors.

关键词： Data collection

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Speech Recognition for Intelligent System in Service Robots: A Review 4

Speech Recognition for Intelligent System in Service Robots:...

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4th International Conference on electrical engineering and Computer Science, ICECOS 2024

作者： Atika, Ratna Dwijayanti, Suci Yudho Suprapto, Bhakti Doctoral Program in Engineering Science Universitas Sriwijaya Department of Electrical Engineering Polytechnic of Sriwijaya Palembang Indonesia Faculty of Engineering Universitas Sriwijaya Department of Electrical Engineering Palembang Indonesia Faculty of Engineering Palembang Universitas Department of Electrical Engineering Sriwijaya Indonesia

ISBN: (纸本)9798350368253

Speech recognition and response system technology in service robot research continues to evolve alongside technical advances and the increasing demand for intelligent automation across industries. The development of machine learning, digital signal processing, and artificial neural networks has brought significant advancements to speech recognition systems. While speech recognition has been implemented in various systems, there is limited discussion on categorizing these systems by examining four aspects: speech recognition applications, datasets used, emotional speech recognition, and automatic speech recognition. In this study, a review of these four aspects is conducted, focusing on the algorithms and methods used, along with their advantages and disadvantages, particularly in the context of implementing them in service robots using the Indonesian language. This study involves a literature review of 100 research papers from the last five years. The review concludes that the use of the transformer method combined with other techniques and Indonesian language datasets is still very limited. Therefore, future research will focus on developing and implementing these methods in humanoid service robots. © 2024 IEEE.

关键词： Intelligent systems

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Design Implementation of Flood Early Warning System for Residential Monitoring

Design Implementation of Flood Early Warning System for Resi...

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2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, ICRAMET 2023

作者： Simatupang, Joni Welman Arrazaq, Thariq Auliya Faculty of Engineering President University Electrical Engineering Study Program Cikarang Indonesia

ISBN: (纸本)9798350343892

The efforts to mitigate floods are necessary. One of the tools that can contribute to flood mitigation is the Flood Early Warning System (FEWS). The main goal of this study is to design a prototype of FEWS that can be easily used anywhere, anytime, and provide accurate water level readings. The prototype system is designed using an Ultrasonic Sensor for water level detection, an alarm system, and Blynk as a web and mobile dashboard. The prototype consists of four main components: Ultrasonic Sensor HC-SR04, Arduino Nano, NodeMCU, and HC-12. It comprises two units: a transmitter unit and a receiver unit. To determine the accuracy and consistency of the Ultrasonic Sensor, the author conducted testing using calibration, non-continuous, and continuous methods. The accuracy obtained was 99.71%. Additionally, the author observed high consistency in the readings of the ultrasonic sensor, as evident from continuous sensor reading test results. Furthermore, the receiver unit successfully displayed output according to the water level threshold for each condition. Additionally, the Blynk web and mobile dashboard were able to display output as per the design. However, we suggest adding data logging features and also solar panels as a renewable power source to support the improved prototype system. © 2023 IEEE.

关键词： Floods

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Novel Hybrid Algorithm for Investigation of Dissolved Gas Analysis for Alternate Dielectric Fluids of Power Transformer 1

Novel Hybrid Algorithm for Investigation of Dissolved Gas An...

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1st IEEE International Conference on Smart and Sustainable Developments in electrical engineering, SSDEE 2025

作者： Soni, Rahul Raj, Raymon Antony Silwal, Bishal Prasojo, Rahman Azis Darwish, M.M.F. Bakar, Norazhar Abu Electrical and Electronics Engineering Program Navrachana University Gujarat Vadodara India Kongu Engineering College Perundurai Department of Electrical and Electronics Engineering Tamil Nadu Erode India Pulchowk Department of Electrical Engineering Lalitpur Nepal Politeknik Negeri Malang Department of Electrical Engineering Malang Indonesia Shoubra Benha University Faculty of Engineering Department of Electrical Engineering Cairo Egypt Universiti Teknologi PETRONAS Faculty of Engineering Department of Electrical Engineering Perak Malaysia

ISBN: (纸本)9798331542108

The power transformer is the most important element of equipment in an electrical transmission and distribution network. The power and voltage levels that these transformers can manage determine their size, and as the transformer's volume increases, internal isolation and cooling become more challenging. The most popular insulating fluid used in transformers for insulation and cooling is mineral-based oil, which has demonstrated exceptional dielectric and thermal qualities. However, alternative oil technologies have been sought to replace mineral-based oils in recent years because to concerns about safety, cost, and environmental impact. In this context, extensive research efforts have emerged on biological oils for use in transformers. This paper examines the sustainability, safety, and electrical performance of bio-based ester oil in transformer applications with respect to dissolved gas analysis (DGA). AI-based Fuzzy logic controller (FLC) with Duval's triangle (DT) and Duval's pentagon (DP), IEC, CIGRE reports are used in a hybrid manner to identify the possible incipient faults inside the oil-immersed transformers. The graphical analysis of various fuzzy logic plots along with DT and DP are utilized to critically analyze the possible incipient faults arrayed due to DGA. The proposed work proficient compared to previously published results. Highest efficiency of DT and DP based FLC (92%), followed by furan analysis (82.3%). Lastly, recommendations are made on potential fixes for the problems raised and the future course of study for alternate dielectric fluids-based power transformers. The suggested techniques in this research offer a higher diagnostic accuracy than the present approach. © 2025 IEEE.

关键词： Power transformers

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Extracorporeal membrane oxygenation versus conventional therapy in patients with acute respiratory failure: systematic review with meta-analysis

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Research on Biomedical engineering 2024年第3-4期40卷 835-849页

作者： de Souza, Daniel Baldoino Barreto, Cassiana Gabriela Lima Milagre, Selma Terezinha Pereira, Adriano Alves University Hospital of the Federal University of Santa Catarina Florianópolis Brazil Centre for Innovation and Technology Assessment in Health Faculty of Electrical Engineering Postgraduate Program in Electrical and Biomedical Engineering Federal University of Uberlândia Uberlândia Brazil

Background: Acute respiratory distress syndrome (ARDS) is a severe condition where lung alveoli fill with fluid, depriving organs of oxygen and risking death. Mechanical ventilation is conventional for oxygen therapy, but extracorporeal membrane oxygenation (ECMO) may be needed for refractory ARDS cases. This study aims to compare ECMO's impact on mortality and hospital stay versus conventional treatment for patients aged 12 or older with moderate or severe ARDS in intensive care units (ICUs). Methodology: Four independent reviewers followed the PRISMA-P method for the review. The key question used the PICOS tool. Databases searched included Cochrane Library, Bireme, MEDLINE, EMBASE, Web of Science, Scielo, LILACS, and grey literature to minimize publication bias. Selected papers were randomized controlled trials (RCTs) without language restrictions, meeting predefined inclusion and exclusion criteria. RoB-2 assessed bias risk, and GRADE evaluated evidence quality. Mortality was analyzed using a fixed-effect PETO method (odds ratio), and hospital stay was treated as a continuous variable using inverse variance and standardized mean difference (SMD). Results: We found 3,774 articles and selected 6 studies with 1,050 participants. Of these, 519 were allocated to the intervention group (ECMO) and 531 to the conventional treatment group (MV). The risk of bias for 3 studies was "some concerns," and 3 were "high risk of bias," mainly due to "deviations from intended/planned interventions" and "selection of reported outcomes." The primary outcomes for 30-day, 60-day, 90-day, and 180-day mortality showed odds ratios of 0.90 (95% CI: 0.66–1.21), 0.78 (95% CI: 0.50–1.21), 0.90 (95% CI: 0.66–1.21), and 0.62 (95% CI: 0.36–1.06) respectively, with low heterogeneity (I2 0.10). The secondary outcomes for a total length of stay and ICU stay showed standardized mean differences of 0.39 (95% CI: 0.13–0.65) and 0.33 (95% CI: 0.05–0.60) respectively, with substantial heterogeneity (I2

关键词： Risk assessment

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