2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)最新文献_第6页

Design and Analysis of a Robotic Articulating Laparoscopic Instrument End Effectors 机器人关节式腹腔镜器械末端执行器的设计与分析

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2020-12-03 DOI: 10.1109/HNICEM51456.2020.9400053

Francisco Emmanuel T. Munsayac, Francheska B. Chioson, Noelle Marie D. Espiritu, Fersen N. Jimenez, Michael Bryan S. Santos, R. Baldovino, N. Bugtai

引用次数: 1

Greenroof Irrigation Using Evapotranspiration for Alfalfa and Basil 利用紫花苜蓿和罗勒的蒸散量进行屋顶绿化灌溉

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2020-12-03 DOI: 10.1109/HNICEM51456.2020.9400151

J. D. dela Cruz, M. V. Caya, Anne Drea Fajardo, Michael Jubert Manzanilla, M. R. Sabuco, Adrian Chummac, Nadiatulhuda Binti Zulkifli Fke

引用次数: 1

Classification Between Pedestrians and Motorcycles using FasterRCNN Inception and SSD MobileNetv2 基于fastrcnn Inception和SSD MobileNetv2的行人和摩托车分类

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2020-12-03 DOI: 10.1109/HNICEM51456.2020.9400113

Nemuel Norman F. Giron, R. Billones, Alexis M. Fillone, J. R. D. del Rosario, A. Bandala, E. Dadios

{"title":"Classification Between Pedestrians and Motorcycles using FasterRCNN Inception and SSD MobileNetv2","authors":"Nemuel Norman F. Giron, R. Billones, Alexis M. Fillone, J. R. D. del Rosario, A. Bandala, E. Dadios","doi":"10.1109/HNICEM51456.2020.9400113","DOIUrl":"https://doi.org/10.1109/HNICEM51456.2020.9400113","url":null,"abstract":"Philippines is on the list of the top ten fastest growing economy in the world. One of its developments is in its traffic law enforcement. Today, the government is continuously finding ways on how to alleviate the problem on its roads with the use of technology. The Metro Manila Development Authority (MMDA) has offered a solution which is the No Contact Traffic Apprehension Policy, that utilizes Closed-Circuit Television (CCTV) Monitoring to apprehend vehicles violating traffic laws, rules and regulations by capturing videos and images. To further enhance this, the government has partnered with the De La Salle University to use artificial intelligence in the system with the project “CATCH-ALL”. With the use of CCTVs and artificial intelligence system, it can help the system detect traffic violations using an automated process. But some tasks are not that easy to execute by the computer like differentiating a pedestrian and a motorcycle. In this study, a novel approach to classifying a pedestrian and a motorcycle with the use of object detection will be developed. It will be demonstrated using deep machine learning, specifically convolutional neural network and by utilizing different pre-trained models to a gathered dataset.","PeriodicalId":230810,"journal":{"name":"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"709 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125409139","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}

引用次数: 1

Trend Forecasting of Computer Vision Application in Aquaponic Cropping Systems Industry 计算机视觉在水培种植系统工业中的应用趋势预测

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2020-12-03 DOI: 10.1109/HNICEM51456.2020.9400070

Heinrick L. Aquino, Ronnie S. Concepcion, E. Dadios, E. Sybingco, A. Bandala

{"title":"Trend Forecasting of Computer Vision Application in Aquaponic Cropping Systems Industry","authors":"Heinrick L. Aquino, Ronnie S. Concepcion, E. Dadios, E. Sybingco, A. Bandala","doi":"10.1109/HNICEM51456.2020.9400070","DOIUrl":"https://doi.org/10.1109/HNICEM51456.2020.9400070","url":null,"abstract":"Computer vision is a fast-growing technology that provides exceptional impact in the world of agriculture. As different problems affecting crop cultivation emerge, as well as the increase in world population, the threat to food security becomes more significant. This paper discussed the international and local agricultural advancements. Trends of computational intelligence (CI) applications in aquaponics systems were also reviewed. This is to see the growth of the industry in terms of technological advancements and determine where the industry is heading. Computer vision allows a non-destructive way of monitoring and detecting agricultural irregularities. Integration of CI in aquaponics made the system more cost-efficient, and beneficial both for the farmers and the environment. This integration has been gaining more attention through the years and the increasing technical publications about the applications it is the significant proofs. This expansion of CI application in the Philippine farm industry can shift old manual labor into a fully automated scheme of farming. Though the Philippine agricultural growth in the past five years has been slow with 1.3% between 2016 and 2019, the introduction of CI, as well as different technologies, can help boost the industry performance especially now that the whole world is now engaging in the fourth industrial reform (FIRe). Therefore, technology intensification of computer vision in Philippine agriculture is expected to crest in the coming two decades.","PeriodicalId":230810,"journal":{"name":"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126100868","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}

引用次数: 8

Development of Evapotranspiration-Based Irrigation System Using Hargreaves-Samani Equation for Public Park Application 基于Hargreaves-Samani方程的公园蒸散灌溉系统开发

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2020-12-03 DOI: 10.1109/HNICEM51456.2020.9400090

M. V. Caya, Ryan Gosiaco, Daniel Jaezon Sablay, Immanuel Robert Sioson, J. D. dela Cruz, N. Zulkifli, Adrian Chummac

{"title":"Development of Evapotranspiration-Based Irrigation System Using Hargreaves-Samani Equation for Public Park Application","authors":"M. V. Caya, Ryan Gosiaco, Daniel Jaezon Sablay, Immanuel Robert Sioson, J. D. dela Cruz, N. Zulkifli, Adrian Chummac","doi":"10.1109/HNICEM51456.2020.9400090","DOIUrl":"https://doi.org/10.1109/HNICEM51456.2020.9400090","url":null,"abstract":"Different methods in water saving are applied to maintain the landscapes and reduce the amount of water needed to be irrigated in public parks. Scheduled watering is the most common type of method used by public parks, in which estimating the amount of water leads to over or under irrigation. Irrigation systems that uses evapotranspiration as a parameter in controlling the amount of water to irrigate on public parks are not found in the Philippines. Evapotranspiration is the rate of water lost from plants and soil through evaporation and transpiration within a specific area. This study focuses on the development of a device that would be used for the monitoring of evapotranspiration using the Hargreaves-Samani Equation. This would include the calibration of sensors and development of device used such as the DHT22 Humidity and Temperature sensor, Water Flow sensors and Tipping Bucket Rain Gauge. Furthermore, a Stevenson screen is created to provide the sensors protection from harsh weather conditions and provide proper ventilation. After testing the prototype, the results obtained from the sensors provided an average percent difference of less than 5%, indicating that the prototype is functioning properly.","PeriodicalId":230810,"journal":{"name":"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"26 9","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121012043","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}

引用次数: 0

Development of Wireless Heating E-Textile Belt for Thermotherapy Application with Four Quadrant Control 四象限控制热疗用无线加热电子织物带的研制

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2020-12-03 DOI: 10.1109/HNICEM51456.2020.9400129

Rodney Gian R. Yrureta, M. V. Caya, Wen-Yaw Chung

{"title":"Development of Wireless Heating E-Textile Belt for Thermotherapy Application with Four Quadrant Control","authors":"Rodney Gian R. Yrureta, M. V. Caya, Wen-Yaw Chung","doi":"10.1109/HNICEM51456.2020.9400129","DOIUrl":"https://doi.org/10.1109/HNICEM51456.2020.9400129","url":null,"abstract":"Thermotherapy is the application of heat as a relief for pain and discomfort. This study presents a heating e-textile belt to provide the needed temperatures for thermotherapy using conductive thread as heating element. The belt was controlled wirelessly using an Android mobile application connected to the microcontroller through Bluetooth Low Energy (BLE). The belt was set to provide temperatures of 33 °C to 44 °C for 5 to 30 minutes from four heating quadrants using proportional-integral-derivative (PID) as a control system. Bekinox 50/1 (BK 50/1) conductive thread heating element was tested for the accuracy of its produced temperature during a recommended thermotherapy session with a target temperature of 44° C for 30 minutes. Using two-tailed paired-sample t-test, the result indicates that the heating e-textile belt produced temperatures that are reliably the same as the set temperature with T-score of 2.2130 and reference value of 2.262. Tests conducted have a 95% interval of confidence.","PeriodicalId":230810,"journal":{"name":"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128109969","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}

引用次数: 0

Automated Sorter and Grading of Tomatoes using Image Analysis and Deep Learning Techniques 使用图像分析和深度学习技术的西红柿自动分选和分级

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2020-12-03 DOI: 10.1109/HNICEM51456.2020.9400055

Justine Fred Bautista, Christian Dave Oceña, Mher Jason Cabreros, S. P. L. Alagao

{"title":"Automated Sorter and Grading of Tomatoes using Image Analysis and Deep Learning Techniques","authors":"Justine Fred Bautista, Christian Dave Oceña, Mher Jason Cabreros, S. P. L. Alagao","doi":"10.1109/HNICEM51456.2020.9400055","DOIUrl":"https://doi.org/10.1109/HNICEM51456.2020.9400055","url":null,"abstract":"Many sorting machines were made in the past that classifies the ripeness of tomatoes. These machines do not classify the size and quality of tomatoes like physical damage, defects, and bruises of plants, resulting in the traditional checking of the quality and size estimation. Based on the Philippines Statistics Office, the Philippines produces many tomatoes that become the driving force to push through this study. This study aims to innovate the existing method of sorting and grading tomatoes depending on the size and quality, including the color, defects, physical damage, and bruises. Specifically, this study aims to create software and hardware that can analyze tomatoes' grades based on color and classify the fruit according to size. Also, to conduct a statistical analysis of the efficiency of the system. The process starts from capturing an image of a tomato, which will be analyzed by applying the image processing techniques such as deep learning algorithms to determine the quality and the Canny-Edge Detection to categorize the size in small, medium, large, and jumbo. The Conveyor is controlled by an Arduino microcontroller transporting the tomatoes into the spot where the tomatoes' image is captured. This study results in an overall efficiency of 88% after testing multiple batches of tomatoes of different sizes and quality.","PeriodicalId":230810,"journal":{"name":"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124403442","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}

引用次数: 4

Detection of Bovine Mastitis Milk through Somatic Cell Count using Electrical Conductivity Property 利用电导率特性体细胞计数检测奶牛乳腺炎乳

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2020-12-03 DOI: 10.1109/HNICEM51456.2020.9400084

Karl Lienus S. Tungol, Jvee Mikell B. Primero, J. Villaverde

{"title":"Detection of Bovine Mastitis Milk through Somatic Cell Count using Electrical Conductivity Property","authors":"Karl Lienus S. Tungol, Jvee Mikell B. Primero, J. Villaverde","doi":"10.1109/HNICEM51456.2020.9400084","DOIUrl":"https://doi.org/10.1109/HNICEM51456.2020.9400084","url":null,"abstract":"this study describes the detection of bovine mastitis infection in milk for both clinical and subclinical mastitis. The presence of mastitis triggers the bovine's immune system to secrete a concentration of certain ions, Na+, and Cl-, to balance the osmotic pressure caused by changes in the blood capillary permeability. This makes electrical conductivity a great indicator in detecting mastitis. The advantage of using electrical conductivity as an indicator in detecting mastitis is not having to rely on an organoleptic test which has a big drawback since dairy farmer's assessment differs widely from what is considered acceptable based on the milk's appearance, color, smell, and taste. A temperature sensor and an electrical conductivity probe are used on the sensor-based system. The device applies temperature compensation to the measured electrical conductivity and reports what the electrical conductivity would be at the reference temperature. The electrical conductivity meter circuit is utilized to process the gathered data from the probe and temperature sensor. By analyzing the electrical conductivity data and the somatic cell count, an estimate of the level of mastitis infectivity of the milk can be projected. Using the sample data given, and polynomial regression to further predict data, an equation was formed $mathrm{y}=9137.86times 3-199200.97times 2+1482591.79mathrm{x} -3523533.92$ where y is the calculated somatic cell count and x is the value of measured electric conductivity. The milk grade is then determined through the standard somatic cell count threshold and Masti-check grading developed by Central Luzon State University. Based on the data acquired, there is no significant difference between the data measured from the laboratory and the data measured from the system.","PeriodicalId":230810,"journal":{"name":"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122652565","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}

引用次数: 0

A Technical Review on Existing pH Detection and Monitoring Technology for in-Vivo Diagnostic Application 现有体内诊断用pH检测与监测技术综述

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2020-12-03 DOI: 10.1109/HNICEM51456.2020.9400104

Ruth Maica C. Gonzales, D. Pacis, N. Bugtai, Janella Marie M. Cu

引用次数: 1

Congestion Detection in Wireless Sensor Networks Based on Artificial Neural Network and Support Vector Machine 基于人工神经网络和支持向量机的无线传感器网络拥塞检测

2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM) Pub Date : 2020-12-03 DOI: 10.1109/HNICEM51456.2020.9400062

Jonnel D. Alejandrino, Ronnie S. Concepcion, Sandy C. Lauguico, Maria Gemel B. Palconit, A. Bandala, E. Dadios

{"title":"Congestion Detection in Wireless Sensor Networks Based on Artificial Neural Network and Support Vector Machine","authors":"Jonnel D. Alejandrino, Ronnie S. Concepcion, Sandy C. Lauguico, Maria Gemel B. Palconit, A. Bandala, E. Dadios","doi":"10.1109/HNICEM51456.2020.9400062","DOIUrl":"https://doi.org/10.1109/HNICEM51456.2020.9400062","url":null,"abstract":"A wireless sensor network (WSN) monitors a certain phenomenon through interconnecting voluminous quantity of interconnected sensor nodes that are implemented in the sensing space and event. Transmission reliability is the key contributing factor in of WSN. Network latency, data packet loss, throughput reduction, and low energy efficiency is caused by a congested network. To solve the network congestion issue, a proposed strategy of congestion detection using ANN (artificial neural network) in comparison to SVM (support vector machine) is presented in this paper. The number of sensor nodes, traffic rate, and node retention are the parameter used. These were generated from the WSN setup in the lettuce smart farm located in Rizal, Philippines. Network Simulator 2 (NS-2) is used for network design, traffic generation, and data gathering. The 3-layer feedforward ANN is optimized using scaled conjugate gradient with sigmoidal function as output activation. SVM is configured using box constraint of 564.22 and kernel scale of 0.1475. There is 0.00776625 CE performance (cross-entropy) and 98.8% accuracy through network training. Conversely, SVM shows 95.18% accuracy. Thus, the developed ANN-based WSN congestion detection model with +3.62% accuracy is an effective tool for agricultural wireless network where array of sensors for crop and environmental monitoring is connected.","PeriodicalId":230810,"journal":{"name":"2020 IEEE 12th International Conference on Humanoid, Nanotechnology, Information Technology, Communication and Control, Environment, and Management (HNICEM)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130472299","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}

引用次数: 11