Sustainable Engineering and Innovation

Journal Information
EISSN : 2712-0562
Published by: Research and Development Academy (10.37868)
Total articles ≅ 51

Latest articles in this journal

Emmanuel Olusegun Ogundimu, Esther Akinlabi, Chigbo Mgbemene, Ifeanyi Jacobs
Sustainable Engineering and Innovation, Volume 4, pp 46-57;

The optimum tilt-angle of a fixed photovoltaic solar panel is very important during the installation, in order to best exploit the accessible output power efficiency of the panel. The output power effectiveness of a PV solar collector is profoundly affected by its tilt-angle to the horizontal and its orientation. This is because of the detail that the sun’s angle varies at every point of time and location. The solar photovoltaic tilting platform plays a dynamic role in the installation of the solar photovoltaic panel. From one perspective, it protects the solar panel from mechanical pressures that can arise from the wind movement and the hand; it provides means of adjustment for the solar panel. The proposed solar photovoltaic tilting platform was designed for an adjustable angle capacity oscillating from 0? to 40?; the materials used for the construction of the tilting platform are capable to withstand a load of 45kg and resist a temperature of -50? F to 150? F under a maximum wind force of 3.78N. The numerous mechanisms of the PV tilting platform prototype were tested, the stability, strength, easy titling, and overall performance of the PV tilting platform were declared as satisfactory.
Othman Inayatullah, Nor Asrina Ramlee, Taharah Edin
Sustainable Engineering and Innovation, Volume 4, pp 1-7;

In the era of modernization, the term “Industry 4.0” has emerged and gained attention progressively from all relevant authorities. This term reflects the movement that gradually improves the current existing technologies and contributes to maintenance advancements in the future. The basic objective of this project is to learn and understand how computer-based technology can bring about revolutionary changes in maintenance to achieve an ideally smart industry. There are two inquiries being studied to fulfill the objective including the recognition of integration between Industry 4.0 and Cyber-Physical System (CPS) in the aspect of maintenance as well as the extent of its contribution to the future development of maintenance management. Both conception study and simulation are chosen as the research methodology for this project.
Rocksana Akter, Kamal Hossain, Shibly Anwar, Kalimur Rahman
Sustainable Engineering and Innovation, Volume 4, pp 82-96;

Mineral fillers provide a significant role in the Marshall properties of hot mix asphalt for paving applications. The article's goal is to assess the suitability and effectiveness of two minerals (coal dust and wood powder ash) used as fillers in asphalt concrete. Chemical composition test using X-ray fluorescence indicated a high content of SiO2, Fe2O3, and Al2O3, which encouraged us to select the coal dust and wood powder ash as mineral fillers for further investigation. A total of 90 cylindrical Marshall Specimens, made with different percentages (i.e., 4%-8%) of coal dust, wood powder ash, and conventional stone dust filler were prepared to assess the performance of individual filler within the asphalt concrete mix. And after that, volumetric characteristics such as density, stability-flow test, air void, and voids in mineral aggregates have been analyzed to evaluate the effectiveness of every sample and, afterward, to find out the optimum asphalt content. Finally, the optimum asphalt content for every filler material was ascertained, and subsequently, Marshall properties were checked again to assess the optimum filler content in the mix that satisfy all the standard criteria. The overall Marshall properties for both fillers were within the acceptable limits. Though the optimum asphalt content was higher for coal dust than wood powder ash and stone dust, the wood powder ash showed better durability than coal dust. All mixtures have been found to have better resistance to deformation, fatigue, and moisture-induced damages; however, 4% coal dust and 6% wood powder ash satisfied most of the Marshall criteria than other percentages.
Asrar Baktayan, Ibrahim Ahmed Albaltah
Sustainable Engineering and Innovation, Volume 4, pp 8-21;

The mobility nature of the wireless networks and the time-sensitive tasks make it necessary for the system to transfer the messages with a minimum delay. Cloud Radio Access Network (C-RAN) reduces the latency problem. However, due to the trustlessness of 5G networks resulting from the heterogeneity nature of devices. In this article, for the edge devices, there is a need to maintain a trust level in the C-RAN node by checking the rates of devices that are allowed to share data among other devices. The SDN controller is built into a macro-cell that plays the role of a cluster head. The blockchain-based automatically authenticates the edge devices by assigning a unique identification that is shared by the cluster head with all C-RAN nodes connected to it. Simulation results demonstrate that, compared with the benchmark, the proposed approach significantly improves the processing time of blocks, the detection accuracy of malicious nodes, and transaction transmission delay.
Adel Alzahrani, Abdullah Safhi
Sustainable Engineering and Innovation, Volume 4, pp 58-65;

Data mining is one of the most important modern techniques used to achieve high output standards at all levels. The twenty-first century saw the advent of a new trend to improve medical services in the healthcare sector. To bridge the gap between previous studies and the practical applications of data mining, this study aimed to review the theoretical literature and previous studies related to the demonstration of data mining techniques and tools and their role in big data management. To achieve the objectives of the study, the researchers used a descriptive, analytical, documentary method. The study concluded many results including that in the era of the knowledge and technology revolution, data mining is one of the important issues, that requires everyone to take into account its achievements in our current era, as well as the existence of a correlation between big data and the provision of a separate health service in the field of healthcare, and work to address epidemics and discover vaccines for them. In the healthcare industry, data mining plays a vital role, especially in predicting various types of diseases. In detecting diseases, diagnosis is the main tool. The study recommended the need to conduct more experimental and exploratory studies dealing with healthcare data mining techniques and tools and their effect on the management of big data volumes, especially in our Arab countries and the need for the development of models and action plans and the development of processes and methods from which data in the healthcare sector can be explored.
Kifilideen Osanyinpeju, Adewole A. Aderinlewo, Olawale U. Dairo, Olayide R. Adetunji, Emmanuel S.A. Ajisegiri
Sustainable Engineering and Innovation, Volume 4, pp 34-45;

At a high frequency of vibration; the cam of a vibrator always encounters the issue of jamming or the follower rolling off or losing contact with the cam when the appropriate design is not carried out. This study, therefore, developed the shape of the cam profile of mechanical yam vibrator using cycloid motion in the South. Displacement equations from the base circle to the cam profile were developed to obtain the shape of the cam using cycloid motion. A vibrometer was used to evaluate the developed 5 mm, 10 mm, and 20 mm cam sizes installed in a mechanical yam vibrator. The maximum displacement recorded for 5 mm, 10 mm and 20 mm cam sizes were 4.47 mm, 8.71 mm, and 14.54 mm respectively for low (1 – 5 Hz) frequency; 4.58 mm, 8.84 mm and 16.34 mm respectively for medium (60 – 100 Hz) frequency; and 4.66 mm, 9.09 mm and 17.30 mm respectively for high (150 – 200 Hz) frequency. This study shows that a cycloid cam would operate smoothly at low, medium, and high frequencies of vibration and function properly for frequency and displacement of vibration up to 200 Hz and 20 mm respectively without jamming and failing. A cycloid cam is therefore recommended for low, medium, and high frequencies motion of vibration.
Lorenzo Cevallos-Torres, Miguel Botto Tobar, Angela Díaz Cadena, Oscar León-Granizo
Sustainable Engineering and Innovation, Volume 4, pp 66-75;

The purpose of this work is to increase the sales of a store devoted to the purchase and sale of soft drinks, even though the store's inventory is overstocked. This occurs as a result of the business's lack of an effective management system that controls product ordering. Additionally, there is no analysis of future sales owing to the variations that may occur because of unforeseen occurrences. The main criterion was that the proprietors of the business submit monthly records from 2017 to July 2019. To accomplish this objective completely, we used the Monte Carlo simulation method to obtain data from August to December 2019; and neural networks to obtain data for all monthly periods in the years 2020, 2021, and 2022, which enabled us to generate records of demand and stock for each of the products. Finally, it was shown that the application of neural networks enables the solution of vehicle control issues, resulting in a maximization of more than 22% of sales, thus achieving the goal and giving an optimum solution to the company.
Hind B. Ali, Dalia R. Alazawi
Sustainable Engineering and Innovation, Volume 4, pp 76-81;

The impact of 3D printing parameters is critical for expanding the application of technology in the design and construction. The effect of bonding layers on the compressive strength of the material is investigated in this research by variation of the layer thickness and print speed. Cube specimens with layer thicknesses ranging from 0.05 to 0.3mm and print rates of 40mm/s, were tested on compression with the DARTEC test equipment. It was found that layer thicknesses of 0.05mm and 0.15mm have similar elastic properties while the 0.15mm layer can take additional load after initial plastic deformation. Layer thickness of 0.30mm has significantly lower elastic zone load capacity, but the stress in plastic zone continue to grow. The findings are of great importance for in explaining the S-N curve in order to enhance part manufacture.
Benjamin Kommey, Daniel Akudbilla, Godfred Doe, Clifford Owusu Amponsah
Sustainable Engineering and Innovation, Volume 4, pp 22-33;

Poultry is one of the most consumed agricultural produce in Ghana. Because of this high demand, the problem necessitates efforts to maximize the yield of poultry production in the country. Relying on natural means of hatching eggs to increase poultry production is inefficient thus the need for technologies that will aid in maximizing the yield. Artificial means of solving this problem have brought about the invention of the incubator. Although this has helped in large-scale incubation, incubators in the market are very expensive which makes Ghanaian poultry farmers find it difficult to purchase. This project investigates the design and implementation of an affordable, automated incubator for local poultry farmers. It is aimed at designing a low-cost smart incubator to ensure the maintenance of the optimum environmental conditions necessary for hatching eggs. These conditions: Ventilation, Temperature, Relative Humidity, regular positioning, and eggs turnings are kept at their optimal values to efficiently increase the hatchability rate. Temperature and humidity sensors are used to read temperature and humidity values inside the incubator respectively. These values are sent to a microcontroller which then coordinates other parts of the incubator to execute automated tasks. A mobile application is integrated with the incubator for the communication of important information to the poultry farmer.
Shahab Kareem, Zhala Jameel Hamad, Shavan Askar
Sustainable Engineering and Innovation, Volume 3, pp 148-159;

Artificial intelligence through deep neural networks is now widely used in a variety of applications that have profoundly altered human livelihoods in a variety of ways. People's daily lives have become much more convenient. Image recognition, smart recommendations, self-driving vehicles, voice translation, and a slew of other neural network innovations have had a lot of success in their respective fields. The authors present the ANN applied in weather forecasting. The prediction technique relies solely upon learning previous input values from intervals in order to forecast future values. And also, Convolutional Neural Networks (CNNs) are a form of deep learning technique that can help classify, recognize, and predict trends in climate change and environmental data. However, due to the inherent difficulties of such results, which are often independently identified, non-stationary, and unstable CNN algorithms should be built and tested with each dataset and system separately. On the other hand, to eradicate error and provides us with data that is virtually identical to the real value we need Artificial Neural Networks (ANN) algorithms or benefit from it. The presented CNN model's forecasting efficiency was compared to some state-of-the-art ANN algorithms. The analysis shows that weather prediction applications become more efficient when using ANN algorithms because it is really easy to put into practice.
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