Arnel Fajardo - Academia.edu (original) (raw)

Papers by Arnel Fajardo

Research paper thumbnail of Iot Based Flood Detection, Alarm and Monitoring System Using Multilayer Perceptron and Regression

Zenodo (CERN European Organization for Nuclear Research), Jul 6, 2023

Flooding is a common natural event caused by heavy rainfall and high tides in the Philippines. Wh... more Flooding is a common natural event caused by heavy rainfall and high tides in the Philippines. While this disaster cannot be prevented, people can prepare themselves to face it. The City of Ilagan in the province of Isabela is one of the highly prone areas to flooding caused by the welling of the Cagayan River. Many communities are living in low-lying areas which most likely experiencing floods. An analysis of the location is conducted including the people living in the area. The analysis resulted in the development of an IoT-based technology for detection and early warning signals to people using sms notifications that can help lessen the difficulty of evacuation. The system uses Arduino UNO as a microcontroller where sensors are attached. These sensors are Light Detection and Ranging (LiDAR) for flood level measurement in feet (ft), Rain Gauge to measure the precipitation rate (mm/hr), and Flow Rate Meter to measure the fluctuation flow of the river in (L/hr). Data gathered from these sensors are processed and sent immediately to people living nearby to monitor the flood level in real-time. The predictive models are developed using the Pinacanauan River dataset taken from the river stations. The multilayer perceptron is used to develop the predictive model with 99% accuracy. The data from sensors are used also and processed using linear regression and calculated as 88% accurate and significant for prediction.

Research paper thumbnail of CNN's Resnet, YOLO, and Faster R-CNN Architectures on the Disease and Pest Classification of Local Agricultural Vegetables Towards Sustainable Production

Machine Learning & Applications

The Philippines is known to be a country that values the agricultural sector. Agriculture is the ... more The Philippines is known to be a country that values the agricultural sector. Agriculture is the backbone of the Philippine economy, contributing around 9% to its gross domestic product (GDP) and providing livelihood to millions of Filipinos. Local vegetables such as pechay, mustasa, sitaw, talong, and ampalaya are some of these essential agricultural crops, used in different famous dishes in the country. The emergence of technology helps individual and community improve their way of administering and managing crops, which is why it is very important to develop an innovative way to produce sustainable vegetable crops. The focus of this paper is on the creation of an application that can effectively categorize the ailments, pests, and nutrient deficiencies found in vegetable crops. This application uses different Convolutional Neural Networks architectures such as ResNet, YOLO, and Faster R-CNN to dissect information from digital photographs. By offering diverse insights into disease...

Research paper thumbnail of Rough Rice Grading in the Philippines Using Infrared Thermography

Communications in computer and information science, 2023

Research paper thumbnail of Tropical Cyclone Analysis and Accumulated Precipitation Predictive Model Using Regression Machine Learning Algorithm

Communications in computer and information science, 2023

Research paper thumbnail of Real-time pose detection for physical education using BlazePose and OpenCV in angle tracking

Nucleation and Atmospheric Aerosols, 2023

Research paper thumbnail of Classification of Philippine Guyabano fruit maturity based on visual properties using deep learning

Nucleation and Atmospheric Aerosols, 2023

Research paper thumbnail of Enhancing Threshold-based Phenotyping by Normalizing Image Luminosity

2022 7th International Conference on Signal and Image Processing (ICSIP), Jul 20, 2022

Research paper thumbnail of Transforming the Grid: Iot-Based Monitoring Device for Enhanced Efficiency in Secondary Line Distribution Transformers

Zenodo (CERN European Organization for Nuclear Research), Jul 29, 2023

The distribution transformer plays a crucial role in both transmission and distribution lines, se... more The distribution transformer plays a crucial role in both transmission and distribution lines, serving as a vital component for power distribution across large areas. Due to the extensive requirement of distribution transformers, it becomes imperative to monitor their operational parameters to ensure their ongoing functionality. In this study, the researcher introduces a device and software solution specifically designed to monitor Electric Companies Distribution Transformer. By closely monitoring key factors such as voltage, current, apparent power, real power, reactive power, and power factor, potential issues with the distribution transformer can be identified and addressed promptly. The monitoring process utilizes real-time data, enabling the recording and analysis of daily, weekly, and monthly measurements via the Internet of Things (IoT) technology.

Research paper thumbnail of Quality of Leaves Classification Using CNN

2023 IEEE 14th Control and System Graduate Research Colloquium (ICSGRC)

Research paper thumbnail of Defect Detection and Classification in Printed Circuit Boards using Convolutional Neural Networks

2023 2nd International Conference on Edge Computing and Applications (ICECAA)

Research paper thumbnail of Classification of Water Quality Index in Laguna de Bay using XGBoost

2023 20th International Joint Conference on Computer Science and Software Engineering (JCSSE)

This study evaluated the performance of different machine learning algorithms for water quality i... more This study evaluated the performance of different machine learning algorithms for water quality index classification in Laguna de Bay, Philippines. Specifically, XGBoost, Random Forest, and Decision Tree algorithms were employed and evaluated using accuracy, precision, recall, and F-1 score metrics. The study utilized six physico-chemical water parameters such as BOD, DO, pH, Phosphate, Ammonia, and Nitrate that came from Laguna Lake Development Authority (LLDA) from year 2017 to year 2022 as input for the classification model. Weighted Average Water Quality Index (WAWQI) was used as method for water quality index computation. The results showed that XGBoost with a learning rate of 0.10 had the highest accuracy at 96.72%, compared to Decision Tree with an accuracy of 93.45% and Random Forest with an accuracy of 93.35%. In addition, it also has the highest cross-validation score of 93.26% followed by Decision Tree with 91.24%. The findings suggest that XGBoost is a more efficient method for classifying water quality index in Laguna de Bay. The study's contribution to water quality management is noteworthy as it provides an efficient and effective way of classifying water quality index. These findings can aid in the decision-making processes aimed at ensuring the sustainability of Laguna de Bay and the health of its aquatic ecosystem.

Research paper thumbnail of Multi-layered radial basis function classification of pulmonary-lung tuberculosis utilizing dropout in maximizing model network cross-entropy accuracy

TRANSPORT, ECOLOGY - SUSTAINABLE DEVELOPMENT: EKOVarna2022

Research paper thumbnail of Iot Based Flood Detection, Alarm and Monitoring System Using Multilayer Perceptron and Regression

INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY RESEARCH AND ANALYSIS

Flooding is a common natural event caused by heavy rainfall and high tides in the Philippines. Wh... more Flooding is a common natural event caused by heavy rainfall and high tides in the Philippines. While this disaster cannot be prevented, people can prepare themselves to face it. The City of Ilagan in the province of Isabela is one of the highly prone areas to flooding caused by the welling of the Cagayan River. Many communities are living in low-lying areas which most likely experiencing floods. An analysis of the location is conducted including the people living in the area. The analysis resulted in the development of an IoT-based technology for detection and early warning signals to people using sms notifications that can help lessen the difficulty of evacuation. The system uses Arduino UNO as a microcontroller where sensors are attached. These sensors are Light Detection and Ranging (LiDAR) for flood level measurement in feet (ft), Rain Gauge to measure the precipitation rate (mm/hr), and Flow Rate Meter to measure the fluctuation flow of the river in (L/hr). Data gathered from t...

Research paper thumbnail of CNN’s Resnet, Yolo, and Faster R-CNN Architectures on the Disease and Pest Classification of Local Agricultural Vegetables Towards Sustainable Production

Research paper thumbnail of Abundance Mapping of Commercial Fisheries Production using K-Means and Forecasting Algorithm in Manila Bay, Philippines

2023 IEEE 8th International Conference for Convergence in Technology (I2CT)

Research paper thumbnail of Illuminance performance of the solar sharing smart LED lighting for indoor vertical farming using fuzzy logic controller

Nucleation and Atmospheric Aerosols, 2023

Research paper thumbnail of End-Product of Solar-Sharing Smart Lighting Artificial Intelligence Driven Platform for High-Valued Crops (Lactuca Sativa) on Indoor Hydroponics Syste

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC)

Research paper thumbnail of Identification of Dried Sea Cucumber Species using Color and Texture Extraction

2022 9th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE)

Research paper thumbnail of Performance Assessment of Scheduling Algorithm as Implemented in an Airline Booking System

SSRN Electronic Journal, 2021

Research paper thumbnail of Aedes Aegypti Egg Classification Model Using Support Vector Machine

2023 15th International Conference on Computer Research and Development (ICCRD)

Research paper thumbnail of Iot Based Flood Detection, Alarm and Monitoring System Using Multilayer Perceptron and Regression

Zenodo (CERN European Organization for Nuclear Research), Jul 6, 2023

Flooding is a common natural event caused by heavy rainfall and high tides in the Philippines. Wh... more Flooding is a common natural event caused by heavy rainfall and high tides in the Philippines. While this disaster cannot be prevented, people can prepare themselves to face it. The City of Ilagan in the province of Isabela is one of the highly prone areas to flooding caused by the welling of the Cagayan River. Many communities are living in low-lying areas which most likely experiencing floods. An analysis of the location is conducted including the people living in the area. The analysis resulted in the development of an IoT-based technology for detection and early warning signals to people using sms notifications that can help lessen the difficulty of evacuation. The system uses Arduino UNO as a microcontroller where sensors are attached. These sensors are Light Detection and Ranging (LiDAR) for flood level measurement in feet (ft), Rain Gauge to measure the precipitation rate (mm/hr), and Flow Rate Meter to measure the fluctuation flow of the river in (L/hr). Data gathered from these sensors are processed and sent immediately to people living nearby to monitor the flood level in real-time. The predictive models are developed using the Pinacanauan River dataset taken from the river stations. The multilayer perceptron is used to develop the predictive model with 99% accuracy. The data from sensors are used also and processed using linear regression and calculated as 88% accurate and significant for prediction.

Research paper thumbnail of CNN's Resnet, YOLO, and Faster R-CNN Architectures on the Disease and Pest Classification of Local Agricultural Vegetables Towards Sustainable Production

Machine Learning & Applications

The Philippines is known to be a country that values the agricultural sector. Agriculture is the ... more The Philippines is known to be a country that values the agricultural sector. Agriculture is the backbone of the Philippine economy, contributing around 9% to its gross domestic product (GDP) and providing livelihood to millions of Filipinos. Local vegetables such as pechay, mustasa, sitaw, talong, and ampalaya are some of these essential agricultural crops, used in different famous dishes in the country. The emergence of technology helps individual and community improve their way of administering and managing crops, which is why it is very important to develop an innovative way to produce sustainable vegetable crops. The focus of this paper is on the creation of an application that can effectively categorize the ailments, pests, and nutrient deficiencies found in vegetable crops. This application uses different Convolutional Neural Networks architectures such as ResNet, YOLO, and Faster R-CNN to dissect information from digital photographs. By offering diverse insights into disease...

Research paper thumbnail of Rough Rice Grading in the Philippines Using Infrared Thermography

Communications in computer and information science, 2023

Research paper thumbnail of Tropical Cyclone Analysis and Accumulated Precipitation Predictive Model Using Regression Machine Learning Algorithm

Communications in computer and information science, 2023

Research paper thumbnail of Real-time pose detection for physical education using BlazePose and OpenCV in angle tracking

Nucleation and Atmospheric Aerosols, 2023

Research paper thumbnail of Classification of Philippine Guyabano fruit maturity based on visual properties using deep learning

Nucleation and Atmospheric Aerosols, 2023

Research paper thumbnail of Enhancing Threshold-based Phenotyping by Normalizing Image Luminosity

2022 7th International Conference on Signal and Image Processing (ICSIP), Jul 20, 2022

Research paper thumbnail of Transforming the Grid: Iot-Based Monitoring Device for Enhanced Efficiency in Secondary Line Distribution Transformers

Zenodo (CERN European Organization for Nuclear Research), Jul 29, 2023

The distribution transformer plays a crucial role in both transmission and distribution lines, se... more The distribution transformer plays a crucial role in both transmission and distribution lines, serving as a vital component for power distribution across large areas. Due to the extensive requirement of distribution transformers, it becomes imperative to monitor their operational parameters to ensure their ongoing functionality. In this study, the researcher introduces a device and software solution specifically designed to monitor Electric Companies Distribution Transformer. By closely monitoring key factors such as voltage, current, apparent power, real power, reactive power, and power factor, potential issues with the distribution transformer can be identified and addressed promptly. The monitoring process utilizes real-time data, enabling the recording and analysis of daily, weekly, and monthly measurements via the Internet of Things (IoT) technology.

Research paper thumbnail of Quality of Leaves Classification Using CNN

2023 IEEE 14th Control and System Graduate Research Colloquium (ICSGRC)

Research paper thumbnail of Defect Detection and Classification in Printed Circuit Boards using Convolutional Neural Networks

2023 2nd International Conference on Edge Computing and Applications (ICECAA)

Research paper thumbnail of Classification of Water Quality Index in Laguna de Bay using XGBoost

2023 20th International Joint Conference on Computer Science and Software Engineering (JCSSE)

This study evaluated the performance of different machine learning algorithms for water quality i... more This study evaluated the performance of different machine learning algorithms for water quality index classification in Laguna de Bay, Philippines. Specifically, XGBoost, Random Forest, and Decision Tree algorithms were employed and evaluated using accuracy, precision, recall, and F-1 score metrics. The study utilized six physico-chemical water parameters such as BOD, DO, pH, Phosphate, Ammonia, and Nitrate that came from Laguna Lake Development Authority (LLDA) from year 2017 to year 2022 as input for the classification model. Weighted Average Water Quality Index (WAWQI) was used as method for water quality index computation. The results showed that XGBoost with a learning rate of 0.10 had the highest accuracy at 96.72%, compared to Decision Tree with an accuracy of 93.45% and Random Forest with an accuracy of 93.35%. In addition, it also has the highest cross-validation score of 93.26% followed by Decision Tree with 91.24%. The findings suggest that XGBoost is a more efficient method for classifying water quality index in Laguna de Bay. The study's contribution to water quality management is noteworthy as it provides an efficient and effective way of classifying water quality index. These findings can aid in the decision-making processes aimed at ensuring the sustainability of Laguna de Bay and the health of its aquatic ecosystem.

Research paper thumbnail of Multi-layered radial basis function classification of pulmonary-lung tuberculosis utilizing dropout in maximizing model network cross-entropy accuracy

TRANSPORT, ECOLOGY - SUSTAINABLE DEVELOPMENT: EKOVarna2022

Research paper thumbnail of Iot Based Flood Detection, Alarm and Monitoring System Using Multilayer Perceptron and Regression

INTERNATIONAL JOURNAL OF MULTIDISCIPLINARY RESEARCH AND ANALYSIS

Flooding is a common natural event caused by heavy rainfall and high tides in the Philippines. Wh... more Flooding is a common natural event caused by heavy rainfall and high tides in the Philippines. While this disaster cannot be prevented, people can prepare themselves to face it. The City of Ilagan in the province of Isabela is one of the highly prone areas to flooding caused by the welling of the Cagayan River. Many communities are living in low-lying areas which most likely experiencing floods. An analysis of the location is conducted including the people living in the area. The analysis resulted in the development of an IoT-based technology for detection and early warning signals to people using sms notifications that can help lessen the difficulty of evacuation. The system uses Arduino UNO as a microcontroller where sensors are attached. These sensors are Light Detection and Ranging (LiDAR) for flood level measurement in feet (ft), Rain Gauge to measure the precipitation rate (mm/hr), and Flow Rate Meter to measure the fluctuation flow of the river in (L/hr). Data gathered from t...

Research paper thumbnail of CNN’s Resnet, Yolo, and Faster R-CNN Architectures on the Disease and Pest Classification of Local Agricultural Vegetables Towards Sustainable Production

Research paper thumbnail of Abundance Mapping of Commercial Fisheries Production using K-Means and Forecasting Algorithm in Manila Bay, Philippines

2023 IEEE 8th International Conference for Convergence in Technology (I2CT)

Research paper thumbnail of Illuminance performance of the solar sharing smart LED lighting for indoor vertical farming using fuzzy logic controller

Nucleation and Atmospheric Aerosols, 2023

Research paper thumbnail of End-Product of Solar-Sharing Smart Lighting Artificial Intelligence Driven Platform for High-Valued Crops (Lactuca Sativa) on Indoor Hydroponics Syste

2022 IEEE 10th Conference on Systems, Process & Control (ICSPC)

Research paper thumbnail of Identification of Dried Sea Cucumber Species using Color and Texture Extraction

2022 9th International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE)

Research paper thumbnail of Performance Assessment of Scheduling Algorithm as Implemented in an Airline Booking System

SSRN Electronic Journal, 2021

Research paper thumbnail of Aedes Aegypti Egg Classification Model Using Support Vector Machine

2023 15th International Conference on Computer Research and Development (ICCRD)