2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)最新文献

{"title":"Volume Approximation Using Kinect Sensor","authors":"Von Errol L. Ang, Franz Elijah O. Decinal, N. Linsangan, J. Adtoon","doi":"10.1109/HNICEM54116.2021.9731913","DOIUrl":"https://doi.org/10.1109/HNICEM54116.2021.9731913","url":null,"abstract":"Kinect has already contributed to object detection, 3D modeling, autonomous navigation, and scene mapping studies. This research aims to use Kinect’s ability to collect depth data by approximating the volume capacity of an open-top subject and producing a 3D representation of it based on the data collected from Kinect and image processing. The experiment included taking the subject’s ground truth volume and comparing it to the system’s volume output. Using Linear Regression for the data interpretation indicates that the device created is reliable enough to produce a correlation coefficient of 0.9621. A significant positive association of the two datasets: experimental volume and theoretical volume. The prototype arrived with an average error rate of 9.003%, implying that the system can get accurate results.","PeriodicalId":129868,"journal":{"name":"2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123598124","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Light Emitting Diode Systems for Artificial Photobioreactors Used in Algal Biofuel Production: A Systematic and Trend Analysis","authors":"C. L. Arroyo, Chrischell B. Lucas, Gabriel Joshua G. Giray, Christopher Marzel S. Llorente, Ronnie S. Concepcion, R. R. Vicerra","doi":"10.1109/HNICEM54116.2021.9731864","DOIUrl":"https://doi.org/10.1109/HNICEM54116.2021.9731864","url":null,"abstract":"Photobioreactors (PBR) support the production of algal biomass which is a known resource in producing biofuel. Different LED system configurations, however, affect the growth of algae. This study aims to do a literature review on the different light utilization trends of photobioreactors used for cultivating algae. This study also seeks to fill in the gaps common to the trends by using engineering principles. Photobioreactors and their working principle are introduced. Importance of light in photobioreactors is emphasized and different journals on LED trends such as LED placement, light intensity, flashing light, and light spectral quality are peer-reviewed. Results show that bottom surface directional lighting helps the cultivation more in comparison to upper surface directional lighting. Higher levels of light intensity on the other hand support the growth of algae although excessive levels cause the protective mechanism to weaken. Flashing light is also found to be slightly more conducive than continuous light mostly based on flashing light being more energy efficient. For light spectral quality, it was reported that blue and red lights are important to promote the growth of the culture. However, with regards to spectral composition of light, the best fit for one algae strain may differ from that of another strain. As such, investigation of the best-fit spectral composition for the strain to be used must be done when designing a PBR. Some recent LED system advancements were discussed and were found to be efficient devices that can be used for photobioreactors although costing remains to be a problem. Application of electronics engineering principles on the possible synchronous use of solar and artificial light is recommended to lessen the cost. Such advancement can pave the way for efficiently using LEDs in photobioreactors for large-scale deployment.","PeriodicalId":129868,"journal":{"name":"2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122082760","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Artificial Neural Network on Solid Waste Generation Based on Five (5) Categories Within Barangay Sagrada Familia in Hagonoy, Bulacan","authors":"John Mark Cagurungan, Royvin Factuar, Jan Marynelle Reyes, Dayanara Torres, Mark Paolo D. Mission, Florante D. Poso, Villamor D. Abad, Jon Arnel S. Telan","doi":"10.1109/HNICEM54116.2021.9731914","DOIUrl":"https://doi.org/10.1109/HNICEM54116.2021.9731914","url":null,"abstract":"Solid waste generation is one of the world’s most prevalent challenges, especially in places with crowded populations and inadequate solid waste disposal strategies. There are several extant influencing variables on solid waste creation. In this regard, the researchers focus on five (5) elements or categories that contributed the most to solid trash generation. The researchers sought to determine which one has the greatest influence on solid waste generation in Barangay Sagrada Familia among these five categories. This will contribute to their future solid waste management plan through minimizing, segregating, and recycling the solid waste, which is one of the causes of their flooding problem. ANN (Artificial Neural Network) is a simplified computational brain model that is one of the most often utilized artificial intelligence in solid waste management. To get the desired outcomes, Matrix Laboratory (MATLAB) testing is essential. The researchers gathered information from studies, theories, and literature in the field. The researchers then performed a survey to gather data and existing data in the barangay and used Excel and Matrix Laboratory (MATLAB) to construct the model for a Neural Network analysis. Finally, the authors analyzed the Neural Network, with the goal value varying according to Pearson’s Correlation Coefficient (R).","PeriodicalId":129868,"journal":{"name":"2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"69 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123883812","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Determination of Unsound Concrete using Non-Destructive Testing in a Smooth Concrete through various Image Processing Techniques","authors":"Raven M. Dapiton, Jan Russel P. Gonzaga, Ramon G. Garcia","doi":"10.1109/HNICEM54116.2021.9731921","DOIUrl":"https://doi.org/10.1109/HNICEM54116.2021.9731921","url":null,"abstract":"The researchers have developed a device that utilizes different image processing techniques that include Grayscale, Gaussian blur, Binary thresholding, Morphology, Contour, and Flood fill to determine a crack or spall width area. The Image capturing device that the researchers created also classifies if the said crack or spall can still be tolerable or needs structural consultation based on the thresholds set. The device has a graphical user interface that captures the images of crack or spall, measuring its width and area and classification if tolerable or needs structural consultation.","PeriodicalId":129868,"journal":{"name":"2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124123055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Associative Classifier for Data Sparsity in Predictive Analysis Recommendation","authors":"Abbigaile Anne Michico B. Cariño, John Isaiah A. Monteza, Jerome B. Tabia, R. Sagum","doi":"10.1109/HNICEM54116.2021.9731908","DOIUrl":"https://doi.org/10.1109/HNICEM54116.2021.9731908","url":null,"abstract":"The researchers developed a web-based tool entitled, BizScout: Application of Associative Classifier for Data Sparsity in Predictive Analysis, which recommends an appropriate business that can be established in the chosen area of interest by utilizing associative classifier and apriori algorithm. The study aims to help individuals who plans to venture into entrepreneurship but lacks the knowledge on what business to start. Also, this study will help in regards to Computer Science students in terms of using Associative Classification on predictive analysis as well as apriori algorithm on data mining. The developed tool uses two main process the preprocessing and the Associative Classification. The developed tool resulted to 76.67% of accuracy in terms of business recommendations for the chosen area of interest and 4.44 weighted mean which is Moderately High for the appropriateness of the recommended business for the chosen location using associative classification.","PeriodicalId":129868,"journal":{"name":"2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124288800","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Neuro-Fuzzy based Safe Landing Control System for UAVs","authors":"Jullian Dominic D. Ducut, Alezander Mikhail O. Galindo, R. Billones, E. Dadios, I. Valenzuela","doi":"10.1109/HNICEM54116.2021.9732007","DOIUrl":"https://doi.org/10.1109/HNICEM54116.2021.9732007","url":null,"abstract":"The number of aerial drone users continue to increase due to its availability, usage, and depreciation. The low cost of drones results in low-quality components that are prone to damage. One of the most common problems of drones is the landing system, where most drones crash due to uncontrolled maneuvering of the drone. In this study, Adaptive Neuro-Fuzzy inference Systems (ANFIS) using MATLAB was developed to perform a safe landing system on low-cost drones where the Gaussian Bell Membership function was used due to a low training error of 0.0015693.","PeriodicalId":129868,"journal":{"name":"2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125663144","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Application of Health Hazard Indicators and Heatmap for Residents Living Near the Philippine National Railway (PNR) Trains in the National Capital Region (NCR)","authors":"Janice A. Abellana, E. J. L. Abellana","doi":"10.1109/HNICEM54116.2021.9731902","DOIUrl":"https://doi.org/10.1109/HNICEM54116.2021.9731902","url":null,"abstract":"Noise pollution from public trains in the metro impacts both children and adults daily, posing a challenge in their daily lives. Noise has an impact on the community’s psychological and physical well-being. The Philippine National Railways trains are an integral component of the daily lives of the city’s passengers. Trains are a popular means of transportation for commuters, as it is the best and only option to travel quickly and get to your destination. Because of the severe traffic circumstances and conditions of land transportation such as jeepneys, private vehicles, and others, Filipino commuters are significant respondents to the study.","PeriodicalId":129868,"journal":{"name":"2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130559352","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementation of Project Study Courses at the Mechanical Engineering Program of FEU Tech During the COVID-19 Pandemic","authors":"M. Belino, H. F. R. Bosshard, I. V. Gue, J. D. Lopena, D. R. Rivera","doi":"10.1109/HNICEM54116.2021.9731970","DOIUrl":"https://doi.org/10.1109/HNICEM54116.2021.9731970","url":null,"abstract":"The threat of a massive spread of the SARS-CoV-2 virus in the Philippines prompted its government to implement community lockdowns all across the country. The first of which was implemented in Metro Manila beginning on 15 March 2020 and lasted up to 15 May 2020. During the lockdown, all schools were prohibited to conduct face-to-face classes while businesses were encouraged to implement work-from-home arrangements. FEU Institute of Technology (FEU Tech), located in Metro Manila, Philippines, was able to quickly adapt to the health crisis mainly due to its previous implementation of Canvas, an online learning management system, in 2017. The mechanical engineering department at FEU Tech revised its strategy in its implementation of its undergraduate Mechanical Engineering Project Study course (MEPROSTUD) to adapt to the class disruptions caused by the community quarantines imposed in Metro Manila. Comparing student performance before and during the pandemic, it was observed that there was a significant decline in oral communication and a significant improvement in written communication in MEPROSTUD1 and MEPROSTUD2, respectively. This paper documents the experiences of the mechanical engineering department at FEU Tech in its implementation of MEPROSTUD courses during the pandemic and intends to provide additional information to other engineering schools about how to remotely implement their undergraduate thesis courses.","PeriodicalId":129868,"journal":{"name":"2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126930785","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"State-of-charge Monitoring and Actuation system for Photovoltaic Solar Cell System","authors":"Jonnel D. Alejandrino, Ronnie S. Concepcion, Vincent Jan D. Almero, Maria Gemel B. Palconit, R. R. Vicerra, A. Bandala, L. A. Venancio, E. Dadios","doi":"10.1109/HNICEM54116.2021.9731983","DOIUrl":"https://doi.org/10.1109/HNICEM54116.2021.9731983","url":null,"abstract":"This paper presents a data monitoring and control for transfer switch of Solar Power System. The system is designed to solve lacking charge indicator and transfer switch mechanism for setups with photovoltaic solar cells and lead acid battery bank. Actuation system is also designed for automatic switching in the time of acquisition. LabView designing software is used in creating the whole data monitoring and control system. The state-of-charge cycle monitoring is developed through fuzzy logic. Temperatures along the PV cells are used as indicator of the upper and lower limits of maintaining charge level. Evaluation of results signified that the proposed system efficiently predicted the state-of-charge, assumed a charge limit based on average temperature and switch or maintain the system to a particular mode.","PeriodicalId":129868,"journal":{"name":"2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124072770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Implementing a Wireless Sensor Network with Multiple Arduino-Based Farming Multi-Sensor Tool to Monitor a Small Farm Area Using ESP32 Microcontroller Board","authors":"Aulivier Gilchrist Q. Aquino, A. Ballado, Azriell V. Bautista","doi":"10.1109/HNICEM54116.2021.9731989","DOIUrl":"https://doi.org/10.1109/HNICEM54116.2021.9731989","url":null,"abstract":"The Philippines is an agricultural country and in today’s commercial agriculture, technology plays an important role in the development of different sectors of farm management, especially in resource utilization. This paper focuses on implementing a deployable wireless sensor network with multiple nodes centered in an ESP32 microcontroller board, wherein each sensor node has its own multiple sensors, using the ESP-WIFI-MESH protocol, which arranges the sensor nodes in a scalable, self-forming, self-healing, and autonomous mesh network topology for small farm-area monitoring. The input needed for this research are the plant growth parameters which include soil moisture, temperature, relative humidity, and ambient sunlight intensity; they will be obtained by the various sensors connected to a sensor node. The output is a collection of historical data to be displayed to and analyzed by farmers or other relevant groups. A node separation distance tested up to 100 meters can be achieved with RSSI of −88dB. The paper also includes calibrations and testing to improve the capabilities of each node for 10 trials each, wherein the soil moisture has an $text{RMSE}=2.55%$ and $text{SD}=1.30%$, the ambient sunlight intensity has $text{RMSE}=4.12$ lux and $text{SD}=4.84$ lux, the temperature has $text{RMSE}=1.31{circ}text{C}$ and $SD=0.50{circ}text{C}$, and lastly, for the relative humidity have an $text{RMSE}=1.73%$ and $text{SD}=0.96%$. The power consumption of each of the nodes in the system is 0.865W, wherein an average current draw of 173mA drawn from a power supply with a rated capacity of 10,000mAh. The sensor nodes can last for up to 57.3 hours, but the power supply is charged during daytime with the help of solar panels.","PeriodicalId":129868,"journal":{"name":"2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"115 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124414266","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}