Scopus ID: 85127540524
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-6
Conference Paper | Published: January 1, 2021
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.
Scopus ID: 85127580968
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-5
Conference Paper | Published: January 1, 2021
Abstract
Vital sign monitoring is a core component of nursing care as information regarding ‘vital functions’ strengthen medical diagnoses. Consequently, various measurement devices have been proposed and utilized from wearable devices to custom engineered equipment. To contribute to the existing innovations of monitoring devices for vital signs, this study proposed a different variation of such a medical device by incorporating the principles of an expert system together with its own wearable vital sign analyzer. At this stage of the project, the device (subsequently referred to as iVital) was a proposal with a prototype as final the product. The primary goal of iVital is to provide both patients and healthcare experts to continuously monitor vital sign measurements remotely. Further, and most importantly, it integrated an expert system where other important data (e.g., patient history and medical records) detectearly signs of clinical deterioration. This work, albeit prefatory, is evidence of how expert systems can be used in healthcare.
Scopus ID: 85127610590
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-5
Conference Paper | Published: January 1, 2021
Abstract
VIP-Guide: Development of Pedestrian Crossing Guide for the Visually Impaired people aims to help in the difficulties encountered in walking alone of the visually impaired persons on the streets, in crossing pedestrian lanes and identification of obstacles that might be in front of them. With the system, it will be able to aid them in terms of the different notifications provided by the system. Location from GPS module, Sound and vibration that alerts them whenever there is an obstacle detected. Upon crossing the street, a counter which is synchronized with the system counting on when to cross the street safely was also provided. Visually impaired persons will no longer need a companion whenever they will go outside. The VIP-Guide will be their companion that will surely make them safe even if they are alone and in the outdoors. A cane was also part of the system which will help them on the notification if an obstacle is near. It has a button that would allow the user to press it when an emergency takes place, will send its location through SMS, such feature will then be an aid for them to ask for help. A part of the system allows the user to connect an earphone to be able to hear notifications from the system, such as, “stop and go”, “do not cross” and a sound of the counter which is synchronized to the system’s counter on the traffic light. This feature will surely aid and guide visually impaired persons in their daily activities outside of their homes.
Scopus ID: 85127584267
2021 IEEE 13th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2021), pp. 1-6
Conference Paper | Published: January 1, 2021
Abstract
Quezon City is highly urbanized, it is both large and vast, covering one-third of the total land area of Metro Manila. It boasts a rapidly growing income and occupation for its population, the city with the most people. With the Philippines situated along the Pacific Ring of Fire and the path of the Typhoon Belt, this makes it susceptible to many natural disasters, not just storms and earthquakes. These disasters include floods, landslides, and volcanic eruptions, sometimes these disasters happen consequently or much worse, altogether. The creation of a disaster management system is vital to aid the people of Quezon City. In this study the researchers have developed an Incident Management System for the Quezon City Disaster Risk Reduction and Management Office, named AlertQC.
Scopus ID: 85113487106
2020 IEEE 7th International Conference on Engineering Technologies and Applied Sciences (ICETAS), (2020), pp. 1-4
Conference Paper | Published: December 18, 2020
Abstract
The most common cause of injuries in the construction site was caused by falls, slips, and trips. As a response to the Occupational Safety and Health Administration (OSHA), this agency conducted training such as fall prevention. Despite these initiatives, there are still incidents and accidents that happened on the site. According to the study conducted by previous researchers, those fatalities can be reduced by wearing a hard hat. That is why OSHA requires all construction sites to strictly implemented the wearing of hard-hat within the vicinity of the construction site. This study developed a hard hat detection system to determine if the worker is wearing a hard-hat properly. Image processing was used in this study. The proponents used the public datasets with hard hat-wearing images to evaluate the performance by using the mean average precision (mAp) where the proponents obtained an average accuracy of 79.246. The proponents of the detection system of hardhats concluded that regardless of their size, color, types, and angles with an average Training and Validation accuracy of 97.29 and 92.55, average evaluation accuracy of 79.24% with the highest model accuracy of 86.89%, and testing accuracy of 86.67%. The system works properly.
Scopus ID: 85113543634
2020 IEEE 7th International Conference on Engineering Technologies and Applied Sciences (ICETAS), (2020)
Conference Paper | Published: December 18, 2020
Abstract
In the Philippines, at least 16 million Filipinos reported smoking cigarettes amid the campaign against tobacco products due to various concerns about their adverse health effects. Due to health, environmental, and safety concerns, the President of the Philippines issued Executive Order 26 s. 2017, imposing a nationwide ban on smoking (use of tobacco including e-cigarettes) in all public places in the Philippines. Despite the implementation of this order, many are still seen smoking in prohibited smoking areas. A smoke detector can be helpful in this situation. This study proposed a smoker detection system that uses a deep learning algorithm that can detect people that are smoking cigarettes. The study used the Pascal VOC format and LabelImg tool for annotating the datasets. Training, validation, and evaluation of the system is done by presenting images, videos, and live detection using the webcam of a camera. Overall, the system produced 90% testing accuracy.
Scopus ID: 85113507662
2020 IEEE 7th International Conference on Engineering Technologies and Applied Sciences (ICETAS), (2020)
Helcy D. Alon, Michael Angelo D. Ligayo, ... Marites V. Fontanilla
Conference Paper | Published: December 18, 2020
Abstract
Dementia is a common term for memory loss, speech, problem-solving, and other cognitive skills that are serious enough to interfere with everyday life, and Alzheimer's is the leading cause of dementia. Alzheimer's disease is presumed to develop 20 years or more before symptoms occur, with degenerative changes that are unapparent to the person affected. The deep learning approach for early detection and Alzheimer's disease classification has recently gained significant attention. This study proposed disease detection trained by utilizing the YOLO v3 algorithm that aims to detect Alzheimer's disease based solely on Magnetic Resonance Imaging (MRI). Pascal VOC format and LabelImg tool are used for annotating the datasets, categorizing the image as non-demented and mild-demented. Model 4 was used in the system having 98.617% training accuracy, 98.8207% validation accuracy, and mAP of 96.17%. To test the accuracy of the used model, images of MRI scans are presented and it recorded 80% testing accuracy.
Scopus ID: 85104936823
2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2020), pp. 1-5
Conference Paper | Published: December 3, 2020
Abstract
Design Thinking is commonly used by businesses as a mindset and approach for problem-solving, learning, and collaboration. Such methodology is a beneficial addition to the pedagogy selections used in the education landscape especially to fields that build products (e.g., computer systems) requiring significant considerations to its functional designs. In this study, the use of Design Thinking Curriculum was explored in Higher Education Institutions particularly on Information Technology and Computer Science programs to determine its impact to the skills and abilities of future computing professionals. To do this, a self-assessment scale that comprises of 31 measurement items divided into seven dimensions was given to computing students. Findings establish that computing students enrolled in a Design Thinking Curriculum have significantly improved in all scales compared to those who are not. Therefore, this study validates the application of Design Thinking Curriculum in education as an approach to encourage innovation in the computing field.
Scopus ID: 85104995169
2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2020)
Conference Paper | Published: December 3, 2020
Abstract
Digitalization of different industries led to new systems that provide accurate information that results in efficient and effective services. This information is vital for decision-making and on the larger scale, policymaking especially in the health sector. In the Philippines, some healthcare establishments have not adjusted to this digital change. This study aims to develop an enhanced model of healthcare management system that can perform digitization of data, predictive health analytics and sales trend analysis. The researchers identified these three features as the focus of the system because it improves data quality, accessibility, reliability, and autonomy. The system is based on prescriptive analytics - a type of analytics that uses machine learning to process historical and predictive data. The artificially intelligent management system caters to the needs of the healthcare sector in this digital age to improve its services to the people.
Scopus ID: 85104983562
2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM), (2020), pp. 1-6
Conference Paper | Published: December 3, 2020
Abstract
Controlled environment agriculture are being developed with the purpose of increasing production yield in farms. For optimal yield, it is very important to have an understanding about the relationship of environmental factors such as radiation, temperature, nutrients, water, and in relation with the growth state of the crop. Growth monitoring of cherry tomato crops in traditional methods are extremely labor-intensive, destructive, and costly in terms of time and money. Thus, application of computer vision has become an area of interest in the study of monitoring tomatoes' growth. In this study, image processing techniques are employed to identify the growth stage of cherry tomato as fruiting, flowering, and leafing stage. Confusion matrix with True Positive rate and False negative rate, and ROC are used to evaluate the decision support system developed. Experimental results show a high performance in determining the growth stage of test cherry tomato images.