Article
Chemistry, Analytical
Hikmat Yar, Ali Shariq Imran, Zulfiqar Ahmad Khan, Muhammad Sajjad, Zenun Kastrati
Summary: Smart home applications have become popular due to IoT technology, making homes more convenient, efficient, and secure. Our research proposes a cost-effective solution for smart home automation using Raspberry Pi, allowing remote and automatic control of home appliances while ensuring customer privacy.
Article
Computer Science, Theory & Methods
Yaru Liu, Jia Yu, Ming Yang, Wenqiang Hou, Huaqun Wang
Summary: With the deep integration of cloud computing and Internet of Things, privacy preserving keyword search techniques have gained importance. Forward security and verifiability are two important security properties for privacy preserving keyword search. This study proposes a scheme that simultaneously achieves forward security and full verification in protecting privacy for keyword search.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Theory & Methods
Shivananda R. Poojara, Chinmaya Kumar Dehury, Pelle Jakovits, Satish Narayana Srirama
Summary: With the growth of IoT devices, the need for efficient data processing and analytics is increasing. This study explores the benefits of using Serverless data pipelines for IoT data analytics and evaluates different approaches for designing such pipelines. The results reveal the suitability of different design methods for different types of applications.
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE
(2022)
Article
Computer Science, Hardware & Architecture
Malek Belouda, Abdelkader Mami
Summary: This article presents a solution for acquiring environmental data and managing energy in a remote area using a hybrid photovoltaic-wind system and electrochemical storage system. The authors propose an innovative data acquisition and intelligent management system based on Raspberry PI. The results and suitability of the embedded solution are discussed.
MICROPROCESSORS AND MICROSYSTEMS
(2022)
Article
Computer Science, Information Systems
Redowan Mahmud, Adel N. Toosi
Summary: Edge and Fog computing paradigms offer computing resources closer to data sources, overcoming the limitations of cloud-centric execution. Small single-board computers like Raspberry Pis are widely used in these paradigms, making them suitable for IoT-driven operations. However, these devices are constrained in facilitating multitenancy and resource sharing. To address this, a fully distributed framework named Con-Pi is proposed, which utilizes containerization and Docker containers to manage resources in Edge and Fog environments. Experimental results demonstrate that Con-Pi outperforms other frameworks in terms of response time, energy usage management, and computing resource allocation. Additionally, Con-Pi has been successfully applied to develop a practical pest bird deterrent system for IoT-enabled applications, such as smart agriculture.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Hardware & Architecture
Ye Liu, Dong Li, Bangsong Du, Lei Shu, Guangjie Han
Summary: The Agricultural Internet of Things is expected to address challenges in the agriculture industry, but the problem of sustainability needs to be addressed. This article proposes a versatile power supply paradigm, called PowerEdge, to achieve sustainable smart agricultural operations through ambient energy harvesting, distributed energy storage, wireless power transfer, and intelligent reflecting surface techniques. Experimental studies and open research issues are discussed.
IEEE WIRELESS COMMUNICATIONS
(2022)
Article
Computer Science, Information Systems
Xinrui Ge, Jia Yu, Fei Chen, Fanyu Kong, Huaqun Wang
Summary: This article explores how to achieve verifiable phrase search over encrypted cloud-based IoT data by designing novel look-up tables and adopting a two-phase query strategy, aiming to solve the problem of existing phrase search encryption schemes not achieving complete verification for search results. The proposed scheme is proven to have high security and efficiency through security analysis and extensive experiments.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Chemistry, Analytical
Luqman Ahsan, Mirza Jabbar Aziz Baig, Mohmmad Tariq Iqbal
Summary: This article describes a low-cost SCADA system for a PV plant with local data logging. It uses open-source hardware and software solutions to process, log, and visualize PV and environmental data. With the cooperation of remote terminal units and Raspberry Pi, data collection and storage are achieved, while providing a user-friendly dashboard.
Article
Computer Science, Information Systems
Albert M. M. Villarreal III, Robin Kumar Verma, Oren Upton, Nicole Lang Beebe
Summary: The smart speaker with an AI-powered voice assistant is commonly found in modern households. Researchers have been exploring methods to extract data from these IoT devices, specifically in the case of Amazon Echo Dot. However, traditional methods alter the device or its data, which is undesired in digital forensics. This study focuses on developing a nondestructive methodology using CT scan imagery to extract data from IoT devices, exemplified by Amazon Echo Dot version 2 with eMMC/eMCP chips, using a 3-D fixture and an eMMC reader.
IEEE INTERNET OF THINGS JOURNAL
(2023)
Article
Construction & Building Technology
Sheik Murad Hassan Anik, Xinghua Gao, Na R. Meng, Philip P. Agee, Andrew McCoy
Summary: The authors developed a cost-effective indoor environmental data collection system called Building Data Lite (BDL) using Raspberry Pi computers and various sensors. Through a case study in a housing community, they proved the system's functionality, cost effectiveness, scalability, and portability.
JOURNAL OF BUILDING ENGINEERING
(2022)
Article
Computer Science, Information Systems
Gaofei Sun, Xiaoshuang Xing, Zhenjiang Qian, Wei (Lisa) Li
Summary: The paper discusses the allocation of computation loads between IoT devices and edge computing servers to balance energy efficiency and data privacy. By analyzing the direct transmission and relay transmission scenarios, corresponding optimization algorithms are introduced.
COMPUTER COMMUNICATIONS
(2021)
Article
Computer Science, Information Systems
Changhee Hahn, Jongkil Kim
Summary: This article investigates two state-of-the-art schemes for verifiable outsourced decryption of encrypted data and identifies their vulnerabilities. It then proposes a securitywise enhanced encoding scheme and conducts a rigorous security analysis. Experimental results show that the proposed method outperforms the other two schemes in terms of encoding computation cost.
IEEE INTERNET OF THINGS JOURNAL
(2022)
Article
Computer Science, Information Systems
Yulei Wu
Summary: The Internet of Things is widely utilized in various critical sectors, requiring efficient data processing. AI-powered cloud-edge orchestration provides crucial computing support for IoT applications.
IEEE INTERNET OF THINGS JOURNAL
(2021)
Article
Computer Science, Information Systems
Antonio Cano-Ortega, Miguel A. Garcia-Cumbreras, Francisco Sanchez-Sutil, Jesus C. Hernandez
Summary: This paper introduces a smart meter for smart homes and proposes a new platform for analyzing Internet of Things data from smart homes, photovoltaics, and electric vehicles. By using cloud systems to enable data-based services, it addresses the challenges of complexities and resource demands for online and offline data processing, storage, and classification analysis.
Article
Agriculture, Multidisciplinary
Shinwoo Hyun, Jin Yu Park, Junhwan Kim, David H. Fleisher, Kwang Soo Kim
Summary: This study proposes a distributed computing system framework called GLUEOS for assisting in the calibration of crop model parameters. By comparing the wall time of different computing systems, it was found that GLUEOS can complete parameter calibration with less time. Additionally, the comparison of calibration and validation datasets shows reliable results from GLUEOS.
COMPUTERS AND ELECTRONICS IN AGRICULTURE
(2022)
Article
Energy & Fuels
Paulo C. M. Carvalho, Tatiane C. Carneiro
Summary: The study introduces a new methodology for evaluating future electricity generation scenarios, finding that scenarios based solely on wind and photovoltaic generation have the lowest water consumption values, while the inclusion of concentrating solar power significantly increases water consumption, posing challenges to sustainability.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2021)
Article
Energy & Fuels
Marcello Anderson F. B. Lima, Luis M. Fernandez Ramirez, Paulo C. M. Carvalho, Josias G. Batista, Deivid M. Freitas
Summary: Solar energy is a significant renewable energy source that can contribute to global energy demand. However, its intermittent nature makes it challenging to integrate into the electrical system. In this study, we compared two machine learning techniques, deep learning (DL) and support vector regression (SVR), for solar forecasting. Our testing in Spain found that DL achieved a mean absolute percentage error of 7.9%, while SVR achieved 8.52%. Although DL had the best results, it is worth mentioning that SVR also performed well.
JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME
(2022)
Review
Energy & Fuels
Tatiane Carolyne Carneiro, Paulo Cesar Marques de Carvalho, Heron Alves dos Santos, Marcello Anderson Ferreira Batista Lima, Arthur Plinio de Souza Braga
Summary: This study provides a systematic review of various methodologies for predicting PV power and solar irradiation. It highlights the use of hybrid approaches and postprocessing methods for future improvements in individualized applications.
JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME
(2022)
Article
Computer Science, Information Systems
Bruna O. Busson, Leticia O. Santos, Paulo C. M. Carvalho, Clodoaldo O. Carvalho Filho
Summary: The paper proposes passive cooling of a floating PV module using fixed heat bridges to reduce operating temperature and increase energy conversion efficiency. Experimental tests show that the FPV module with heat bridges has lower temperature and higher productivity compared to a conventional PV module.
IEEE LATIN AMERICA TRANSACTIONS
(2021)
Article
Energy & Fuels
Tatiane C. Carneiro, Marcello A. Ferreira Batista Lima, Paulo C. Marques de Carvalho, Josias Guimaraes Batista, Luis M. Fernandez-Ramirez
Summary: An improved adaptation of the portfolio theory is proposed in this article, which integrates artificial neural networks for wind speed forecasting and aims to analyze the impact of errors and achieve more accurate results.
INTERNATIONAL JOURNAL OF ENERGY RESEARCH
(2022)
Article
Energy & Fuels
Jonas Platini Reges, Paulo C. M. Carvalho, Jose Carlos de Araujo, Tatiane Carolyne Carneiro
Summary: In this study, a new method for sizing FPV plants in dams of semi-arid regions is proposed, which can be applied in reservoirs. The method uses flood duration curves for sizing and has innovations such as no use of commercial software, the possibility of choosing the reliability level, and the use of graphic analysis of reservoir hydrological behavior.
JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME
(2022)
Review
Energy & Fuels
Leticia de Oliveira Santos, Paulo Cesar Marques de Carvalho, Clodoaldo de Oliveira Carvalho Filho
Summary: This article provides a review of steady-state models for calculating the operating temperature of photovoltaic (PV) cells developed since 2000. It aims to assist researchers and professionals in selecting significant parameters and suitable experimental arrangements to create accurate models. The article summarizes 33 correlations found in the literature and presents three general forms of these correlations. The main parameters affecting the operating temperature are discussed, along with their most accurate data collection methods. The strategies for obtaining the operating temperature, such as using the module back side temperature or internal sensors, for model validation purposes are also discussed.
IEEE JOURNAL OF PHOTOVOLTAICS
(2022)
Article
Energy & Fuels
Tatiane C. Carneiro, Paulo A. C. Rocha, Paulo C. M. Carvalho, Luis M. Fernandez-Ramirez
Summary: With the rapid development of wind and solar power generation, the issue of intermittency becomes more prominent, and ensemble learning methods can improve predictions and be applied to wind and solar data from different locations. The ensemble model achieves better performance in predicting solar data from Brazil and Spain, as well as wind data from Brazil and Spain, compared to individual models.
Article
Computer Science, Information Systems
A. W. B. Silva, B. B. Freitas, C. L. A. Filho, C. D. Freitas, E. A. S. Junior, E. S. Castro, E. M. Araujo, F. I. F. Correia, F. R. P. Silva, J. J. S. Souza, L. L. P. Martins, L. R. R. Coutinho, N. P. L. Ces, R. Castelo, P. C. M. Carvalho, T. C. Carneiro
Summary: This study proposes a method to predict the hourly photovoltaic power of two solar plants in Fortaleza, Brazil using artificial neural networks. The results indicate that the neural networks have the potential to learn the behavior of the plants, with MLP showing higher accuracy.
IEEE LATIN AMERICA TRANSACTIONS
(2022)
Article
Engineering, Multidisciplinary
Thiago Angelino dos Santos, Filipe Gomes de Freitas, Diego Lima Carvalho Goncalves, Luis Miguel Fernandez-Ramirez
Summary: The use of photovoltaic systems for electricity generation is growing in Brazil, and consumers are investing in PV microgeneration to reduce power bills. This study developed an IoT monitoring system applied to a grid-connected PV system in an educational institution to teach IoT and PV generation concepts. The system, based on open source and programmable hardware, sends data to a cloud database for remote access worldwide.
INGENIUS-REVISTA DE CIENCIA Y TECNOLOGIA
(2022)
Article
Engineering, Multidisciplinary
Renata Pereira, Cleonilson de Souza, Darwin Patino, Juan Lata
Summary: With the increasing development of embedded systems and the Internet of Things, devices based on microcontrollers are being used in various fields. This paper describes the design and development of an online educational platform that offers four products for teaching microcontrollers and IoT. These products are based on open-source software, allowing free online distribution and can be accessed through a cloud server. The platform enables remote programming of ESP32 firmware and Linux embedded systems, offering virtual microcontroller laboratory applications.
INGENIUS-REVISTA DE CIENCIA Y TECNOLOGIA
(2022)
Review
Computer Science, Information Systems
I Cruz, N. Batista, Paulo C. M. Carvalho
Summary: This article provides a systematic literature review on hybrid renewable systems applied to water pumping, with photovoltaic energy being the dominant generation.
IEEE LATIN AMERICA TRANSACTIONS
(2022)
Review
Energy & Fuels
Jose Janiere Silva de Souza, Paulo Cesar Marques de Carvalho, Giovanni Cordeiro Barroso
Summary: This paper presents a literature review on experimental studies characterizing the effects of soiling on the performance of photovoltaic (PV) systems. The study methodology includes systematic review of the literature, selection criteria, search strategies, and extraction and summarization procedures. The results show that the short-circuit current is most affected by dirt, and different behaviors are observed for other parameters depending on the PV technology. The most commonly reported chemical elements are Ca, Si, Al, O, Fe, and Mg, and the main mineral compounds include quartz, calcite, hematite, gypsum, and orthoclase.
JOURNAL OF SOLAR ENERGY ENGINEERING-TRANSACTIONS OF THE ASME
(2023)
Article
Green & Sustainable Science & Technology
Natasha E. Batista, Paulo C. M. Carvalho, Luis M. Fernandez-Ramirez, Arthur P. S. Braga
Summary: Based on a systematic and bibliometric review, the combined use of Portfolio Theory (PT) and Particle Swarm Optimization (PSO) is proposed for the energy management of a Hybrid Renewable Energy System (HRES) powered reverse osmosis (RO) plant. The aim is to achieve Multi-Objective Optimization (MOO), decreasing the Drinking Water Cost (DWC) and increasing the system reliability and components lifetime. The review reveals that HOMER is the most commonly used software for hybrid plants sizing and optimization, but it has limitations in terms of component power range and computational cost associated with hydrogen production and storage. In contrast, optimization methods based on PSO show lower computational cost and robust results. Additionally, the use of PT for HRES energy management is innovative, as PT has traditionally been applied in the economy sector.
RENEWABLE & SUSTAINABLE ENERGY REVIEWS
(2023)
Article
Computer Science, Information Systems
Danielly Araujo, Natasha Batista, Paulo Carvalho, Jonas Reges, Douglas Costa, Robson Dias, Deivid Freitas, Siomara Lima, Kaio Ramos, Shakil Ribeiro, Fellipe Soares
IEEE LATIN AMERICA TRANSACTIONS
(2020)
Article
Engineering, Multidisciplinary
Sicheng Jiao, Shixiang Wang, Minge Gao, Min Xu
Summary: This paper presents a non-contact method of thickness measurement for thin-walled rotary shell parts based on a chromatic confocal sensor. The method involves using a flip method to obtain surface profiles from both sides of the workpiece, measuring the decentration and tilt errors of the workpiece using a centering system, establishing a unified reference coordinate system, reconstructing the external and internal surface profiles, and calculating the thickness. Experimental results show that the method can accurately measure the thickness of a sapphire spherical shell workpiece and is consistent with measurements of other materials.
Article
Engineering, Multidisciplinary
Rajeev Kumar, Sajal Agarwal, Sarika Pal, Alka Verma, Yogendra Kumar Prajapati
Summary: This study evaluated the performance of a CaF2-Ag-MXene-based surface plasmon resonance (SPR) sensor at different wavelengths. The results showed that the sensor achieved the maximum sensitivity at a wavelength of 532 nm, and higher sensitivities were obtained at shorter wavelengths at the expense of detection accuracy.
Article
Engineering, Multidisciplinary
Attilio Di Nisio, Gregorio Andria, Francesco Adamo, Daniel Lotano, Filippo Attivissimo
Summary: Capacitive sensing is a widely used technique for a variety of applications, including avionics. However, current industry standard Capacitive Level Sensors (CLSs) used in helicopters perform poorly in terms of sensitivity and dynamic characteristics. In this study, novel geometries were explored and three prototypes were built and tested. Experimental validation showed that the new design featuring a helicoidal slit along the external electrode of the cylindrical probe improved sensitivity, response time, and linearity.
Article
Engineering, Multidisciplinary
Kai Yang, Huiqin Wang, Ke Wang, Fengchen Chen
Summary: This paper proposes an effective measurement method for dynamic compaction construction based on time series model, which enables real-time monitoring and measurement of anomalies and important construction parameters through simulating motion state transformation and running time estimation.
Article
Engineering, Multidisciplinary
Hui Fu, Qinghua Song, Jixiang Gong, Liping Jiang, Zhanqiang Liu, Qiang Luan, Hongsheng Wang
Summary: An automatic detection and pixel-level quantification model based on joint Mask R-CNN and TransUNet is developed to accurately evaluate microcrack damage on the grinding surfaces of engineering ceramics. The model is effectively trained on actual micrograph image dataset using a joint training strategy. The proposed model achieves reliable automatic detection and fine segmentation of microcracks, and a skeleton-based quantification model is also proposed to provide comprehensive and precise measurements of microcrack size.
Review
Engineering, Multidisciplinary
Sang Yeob Kim, Da Yun Kwon, Arum Jang, Young K. Ju, Jong-Sub Lee, Seungkwan Hong
Summary: This paper reviews the categorization and applications of UAV sensors in forensic engineering, with a focus on geotechnical, structural, and water infrastructure fields. It discusses the advantages and disadvantages of sensors with different wavelengths and addresses the challenges of current UAV technology and recommendations for further research in forensic engineering.
Article
Engineering, Multidisciplinary
Anton Nunez-Seoane, Joaquin Martinez-Sanchez, Erik Rua, Pedro Arias
Summary: This article compares the use of Mobile Laser Scanners (MLS) and Aerial Laser Scanners (ALS) for digitizing the road environment and detecting road slopes. The study found that ALS data and its corresponding algorithm achieved better detection and delimitation results compared to MLS. Measuring the road from a terrestrial perspective negatively impacted the detection process, while an aerial perspective allowed for scanning of the entire slope structure.
Article
Engineering, Multidisciplinary
Nur Luqman Saleh, Aduwati Sali, Raja Syamsul Azmir Raja Abdullah, Sharifah M. Syed Ahmad, Jiun Terng Liew, Fazirulhisyam Hashim, Fairuz Abdullah, Nur Emileen Abdul Rashid
Summary: This study introduces an enhanced signal processing scheme for detecting mouth-click signals used by blind individuals. By utilizing additional band-pass filtering and other steps, the detection accuracy is improved. Experimental results using artificial signal data showed a 100% success rate in detecting obstacles. The emerging concepts in this research are expected to benefit radar and sonar system applications.
Article
Engineering, Multidisciplinary
Jiqiang Tang, Shengjie Qiu, Lu Zhang, Jinji Sun, Xinxiu Zhou
Summary: This paper studies the magnetic noise level of a compact high-performance magnetically shielded room (MSR) under different operational conditions and establishes a quantitative model for magnetic noise calculation. Verification experiments show the effectiveness of the proposed method.
Review
Engineering, Multidisciplinary
Krzysztof Bartnik, Marcin Koba, Mateusz Smietana
Summary: The demand for miniaturized sensors in the biomedical industry is increasing, and optical fiber sensors (OFSs) are gaining popularity due to their small size, flexibility, and biocompatibility. This study reviews various OFS designs tested in vivo and identifies future perspectives and challenges for OFS technology development from a user perspective.
Article
Engineering, Multidisciplinary
Yue Wang, Lei Zhou, Zihao Li, Jun Wang, Xuangou Wu, Xiangjun Wang, Lei Hu
Summary: This paper presents a 3-D reconstruction method for dynamic stereo vision of metal surface based on line structured light, overcoming the limitation of the measurement range of static stereo vision. The proposed method uses joint calibration and global optimization to accurately reconstruct the 3-D coordinates of the line structured light fringe, improving the reconstruction accuracy.
Article
Engineering, Multidisciplinary
Jaafar Alsalaet
Summary: Order tracking analysis is an effective tool for machinery fault diagnosis and operational modal analysis. This study presents a new formulation for the data equation of the second-generation Vold-Kalman filter, using separated cosine and sine kernels to minimize error and provide smoother envelopes. The proposed method achieves high accuracy even with small weighting factors.
Article
Engineering, Multidisciplinary
Tonglei Cao, Kechen Song, Likun Xu, Hu Feng, Yunhui Yan, Jingbo Guo
Summary: This study constructs a high-resolution dataset for surface defects in ceramic tiles and addresses the scale and quantity differences in defect distribution. An improved approach is proposed by introducing a content-aware feature recombination method and a dynamic attention mechanism. Experimental results demonstrate the superior accuracy and efficiency of the proposed method.
Article
Engineering, Multidisciplinary
Qinghong Fu, Yunxi Lou, Jianghui Deng, Xin Qiu, Xianhua Chen
Summary: Measurement and quantitative characterization of aging-induced gradient properties is crucial for accurate analysis and design of asphalt pavement. This research proposes the composite specimen method to obtain asphalt binders at different depths within the mixture and uses dynamic shear rheometer tests to measure aging-induced gradient properties and reveal internal mechanisms. G* master curves are constructed to investigate gradient aging effects in a wide range. The study finds that the composite specimen method can effectively restore the boundary conditions and that it is feasible to study gradient aging characteristics within the asphalt mixture. The study also observes variations in G* and delta values and the depth range of gradient aging effects for different aging levels.
Article
Engineering, Multidisciplinary
Min Li, Kai Wei, Tianhe Xu, Yali Shi, Dixing Wang
Summary: Due to the limitations of ground monitoring stations in China for the BDS, the accuracy of BDS Medium Earth Orbit (MEO) satellite orbits can be influenced. To overcome this, low Earth orbit (LEO) satellites can be used as additional monitoring stations. In this study, data from two LEO satellites were collected to improve the precise orbit determination of the BDS. By comparing the results with GPS and BDS-2/3 solutions, it was found that including the LEO satellites significantly improved the accuracy of GPS and BDS-2/3 orbits.
