2023 International Seminar on Intelligent Technology and Its Applications (ISITIA)最新文献_第3页

Virtual Plant Design: Automatic Sortation and Warehouse System for Distribution Intralogistics based on Petri-Net Method 虚拟工厂设计:基于Petri-Net方法的配送物流自动分拣与仓储系统

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2023-07-26 DOI: 10.1109/ISITIA59021.2023.10221169

E. Iskandar, Ali Fatoni, Aqil Rabbani Nurhadi

{"title":"Virtual Plant Design: Automatic Sortation and Warehouse System for Distribution Intralogistics based on Petri-Net Method","authors":"E. Iskandar, Ali Fatoni, Aqil Rabbani Nurhadi","doi":"10.1109/ISITIA59021.2023.10221169","DOIUrl":"https://doi.org/10.1109/ISITIA59021.2023.10221169","url":null,"abstract":"Warehousing has a pivotal role in the distribution of goods across the supply chain. However, many manual processes still exist in intralogistics distribution, relying on employees to operate the system. This emphasizes the need for an automated intralogistics distribution system that incorporates automatic object sorter, which then feeds into palletizer followed by the use of cranes. The system utilizes a programmable logic controller (PLC) as a controller, with ladder diagrams as the programming language. The current approach to designing ladder diagrams lacks structure and can be challenging to solve problems efficiently. To address this, the petri net method is employed as a guide for programming, enabling the design of a more structured ladder diagram, and facilitating the characterization of discrete event simulation models. The ladder diagram’s results were recreated through simulation by employing a virtual plant implemented via Factory I/O, providing a close depiction of the logistics process within the manufacturing sector. The design result for intralogistics distribution in virtual plant involves the integration of 53 sensors and 68 actuators. The recorded time for distributing 25 palletized products to the warehouse averages at 17 minutes and 38 seconds.","PeriodicalId":116682,"journal":{"name":"2023 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128236251","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

Emotion Recognition from Video Frame Sequence using Face Mesh and Pre-Trained Models of Convolutional Neural Network 基于人脸网格和卷积神经网络预训练模型的视频帧序列情感识别

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2023-07-26 DOI: 10.1109/ISITIA59021.2023.10221117

Derry Pramono Adi, E. M. Yuniarno, D. P. Wulandari

{"title":"Emotion Recognition from Video Frame Sequence using Face Mesh and Pre-Trained Models of Convolutional Neural Network","authors":"Derry Pramono Adi, E. M. Yuniarno, D. P. Wulandari","doi":"10.1109/ISITIA59021.2023.10221117","DOIUrl":"https://doi.org/10.1109/ISITIA59021.2023.10221117","url":null,"abstract":"Emotions are a collection of subjective cognitive experiences and psychological and physiological characteristics that express a wide range of feelings, thoughts, and behaviors in human interaction. Emotions can be represented through several means, such as facial expressions, tone of voice, and behavior. Deep Learning (DL) research has focused on incorporating facial expressions. Images with facial expressions are commonly used as data input for the DL model. Unfortunately, most DL models in Facial Emotion Recognition (FER) use static images. This method does not take into consideration all conceivable facial expressions. The static image of facial expressions is insufficient for recognizing emotions, but a sequential image from a video is required. In this study, we extract MediaPipe’s face mesh feature, the state-of-the-art multidimensional expression key points embedded in the video image sequence. Furthermore, we feed sequence image data into the pre-trained Convolutional Neural Network (CNN) model. The data we used is from The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) with the emotion classes of “Anger,” “Fearful,” “Happy,” and “Sad.” For this specific FER task, we found that the best pre-trained CNN model achieved 92.8% accuracy (using the VGG-19 model), with the fastest runtime of $sim2.3$ seconds (achieved using the SqueezeNet model).","PeriodicalId":116682,"journal":{"name":"2023 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132422345","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

Comparing Various Combined Techniques at Seasonal Autoregressive Integrated Moving Average (SARIMA) for Electrical Load Forecasting 比较季节自回归综合移动平均(SARIMA)各种组合技术在电力负荷预测中的应用

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2023-07-26 DOI: 10.1109/ISITIA59021.2023.10221130

Mega Silfiani, Happy Aprillia, Yustina Fitriani

{"title":"Comparing Various Combined Techniques at Seasonal Autoregressive Integrated Moving Average (SARIMA) for Electrical Load Forecasting","authors":"Mega Silfiani, Happy Aprillia, Yustina Fitriani","doi":"10.1109/ISITIA59021.2023.10221130","DOIUrl":"https://doi.org/10.1109/ISITIA59021.2023.10221130","url":null,"abstract":"The objective of this study is to investigate the accuracy of forecasting electrical consumption using various combined techniques at the seasonal autoregressive integrated moving average (SARIMA) ensemble. A SARIMA ensemble is created by modeling various SARIMA models and combining techniques such as arithmetic averaging, Bates-Granger weight, Akaike weight, and Principal Component Regression (PCR) weight. Results indicate that SARIMA’s ensemble-based PCR outperformed all the remaining models in both categories and forecast horizons. In general, ensemble models produced by Bates–Granger perform better than ensemble models produced by Akaike weight and averaging. Meanwhile, an ensemble model based on Akaike weight and averaging have equal performance. In addition, the public electrical load forecast has the best performance in forecast horizon and various models. Generally, household and electrical industry loads have equal performance three months ahead and twelve months ahead of the forecast horizon. A further investigation ought to explore the various construction and combination techniques implemented by ensemble members.","PeriodicalId":116682,"journal":{"name":"2023 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130870091","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

Word Syllabification for Indonesian Language using Transformer 使用Transformer的印尼语单词音节化

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2023-07-26 DOI: 10.1109/ISITIA59021.2023.10221089

Muhammad Haykal Kamil, S. Suyanto, M. Bijaksana

{"title":"Word Syllabification for Indonesian Language using Transformer","authors":"Muhammad Haykal Kamil, S. Suyanto, M. Bijaksana","doi":"10.1109/ISITIA59021.2023.10221089","DOIUrl":"https://doi.org/10.1109/ISITIA59021.2023.10221089","url":null,"abstract":"Syllabification is a process from word to a series of syllable. Syllabification can be used in Natural Language Processing (NLP) such as speech recognition, text-to-speech, rhyme detection, and many more. Syllabification of the Indonesian language will refers to the General Guidelines for Indonesian Language Spelling (PUEBI). The corpus for this research containing the main word and the syllable. The corpus for this research is using ”50k KBBI 5-k fold” and combined with ”103k Named Entity 5-k fold”. The evaluation for this model is using Word Error Rate (WER). WER of previous deep learning model for syllabification is still high with 3.75% WER. The objective of this research is to lower the WER for deep learning using Transformer and Syllable Tagging because it can accept long contextual dependency. The evaluation result of this model is 3.68% WER and can be used universally for Indonesian words because the margin between Formal Words and Named Entity Words is close with the average result. Thus, this model currently the better model for Indonesian syllabification deep learning model according from the average WER is lower than the other deep learning model.","PeriodicalId":116682,"journal":{"name":"2023 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131672304","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

Design and Implementation of Smart Surveillance System Using Deep Learning Method 基于深度学习方法的智能监控系统设计与实现

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2023-07-26 DOI: 10.1109/ISITIA59021.2023.10221154

Edi Johan Syah Djula, E. Husni, Rahadian Yusuf

{"title":"Design and Implementation of Smart Surveillance System Using Deep Learning Method","authors":"Edi Johan Syah Djula, E. Husni, Rahadian Yusuf","doi":"10.1109/ISITIA59021.2023.10221154","DOIUrl":"https://doi.org/10.1109/ISITIA59021.2023.10221154","url":null,"abstract":"This works explored deep learning techniques to create a Smart Surveillance System, also known as Smart CCTV, for vehicle categorization. Unlike traditional Smart CCTV systems, which rely on centralized video processing and analysis, this system is self-contained and capable of producing textual data on its own. To develop the model, the YOLOv7 algorithm method is employed, and the process of creating datasets, labeling, training, verifying, and testing the deep learning model is detailed. To ensure platform compatibility, the trained models are executed on the Jetson Nano device, and the whole procedure and output data processing are performed in Python. We also performed durability testing on various weather condition. The proposed system is intended to provide a more efficient and dependable surveillance system for applications such as traffic monitoring and security. Where can devices that are independent in terms of process and data processing be obtained, so that output is obtained in the form of data on the number and classification, as well as the status and performance of the devices being built. The developed series of devices perform well in terms of status and performance. CPU utilization is within acceptable limits, and physical RAM consumption is consistent. Despite an increase in SWAP RAM consumption, the stable fan speed indicated that there was no significant overheating.","PeriodicalId":116682,"journal":{"name":"2023 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116709386","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

Pulse Shape Analysis of Partial Discharge in Air Insulation Using Commercial HFCT Sensor 用商用HFCT传感器分析空气绝缘局部放电的脉冲形状

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2023-07-26 DOI: 10.1109/ISITIA59021.2023.10221182

Muhammad Kodrat, U. Khayam

引用次数: 0

A Comparative Analysis of Sensor Fusion Algorithms for Miniature IMU Measurements 微型IMU测量传感器融合算法的比较分析

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2023-07-26 DOI: 10.1109/ISITIA59021.2023.10220994

Kristel Çoçoli, L. Badia

引用次数: 0

Novel Technologies of Exoskeleton Systems Applied to Rehabilitation for Hand Therapies: A Technological Review 外骨骼系统应用于手部康复治疗的新技术:技术综述

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2023-07-26 DOI: 10.1109/ISITIA59021.2023.10221151

Tania Barreda-Galvez, Dana Terrazas-Rodas

{"title":"Novel Technologies of Exoskeleton Systems Applied to Rehabilitation for Hand Therapies: A Technological Review","authors":"Tania Barreda-Galvez, Dana Terrazas-Rodas","doi":"10.1109/ISITIA59021.2023.10221151","DOIUrl":"https://doi.org/10.1109/ISITIA59021.2023.10221151","url":null,"abstract":"Movement disorders and injuries affect partial or full control of the parts of the body that affect your movement. Among the affected parts are the hands, which are vital to carrying out daily activities. According to the World Health Organization (WHO) around 15% of the world’s population, that is, 1000 million people, suffers from some type of disability. Only in Peru, there are around 1 million 575 thousand people who suffer from a variety of deficiencies, according to the National Institute of Statistics and Informatics (INEI). As a solution to this problem, hand exoskeletons emerge, which are devices that restore or improve the motor skills of the affected hand. In this review, 64 publications on hand exoskeletons were analyzed and classified into the following categories: trade names, acronyms or the name of the main author of the device, the degrees of freedom, the type of exoskeleton that can be passive or active, the mechanism that covers the parts of the hand, the types of movements that are performed, the kind of rehabilitation, the pathology that causes the injury or disability in the hand and the technology readiness level.","PeriodicalId":116682,"journal":{"name":"2023 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116986194","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 Study of the Performance of Solar Cell Powered IoT-based Air Pollution Sensor Node in Indoor Environment 基于太阳能电池的物联网室内空气污染传感器节点性能研究

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2023-07-26 DOI: 10.1109/ISITIA59021.2023.10221112

Moch Bilal Zaenal Asyikin, C. Kuncoro

{"title":"A Study of the Performance of Solar Cell Powered IoT-based Air Pollution Sensor Node in Indoor Environment","authors":"Moch Bilal Zaenal Asyikin, C. Kuncoro","doi":"10.1109/ISITIA59021.2023.10221112","DOIUrl":"https://doi.org/10.1109/ISITIA59021.2023.10221112","url":null,"abstract":"The Internet of Things is boosting indoor solar technologies. It is suitable for low-power applications. However, many low-power communication protocols are not widely used in society, despite the fact that user-friendliness is important for implementation. A sensor node for tracking indoor air pollution is introduced. The sensor module can measure up to 100 ppm of carbon monoxide gas concentration and share real-time data via wifi protocol. One cycle of the carbon monoxide measurement process required 1.093 mWh of total energy capacity over a duration of 33.51s to operate. The system power mode strategy uses a minor current consumption of 31.40 mA, while data transmission uses the most, approximately 113.20 mA. The sensor node could be powered on for 726 cycles with a voltage range of 4.1V-3.3V without solar cells. While including solar cells, the cycles increased to 889 (500 lx) and 1056 (750 lx). It can also be optimized by increasing the luminance and solar cell area. All the carbon monoxide gas concentration data were collected to the IoT server and made online for visualization throughout the testing.","PeriodicalId":116682,"journal":{"name":"2023 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115014690","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

Clutter Reduction in Detecting Trapped Human Respiration Under Rubble for FMCW Radar System FMCW雷达系统对碎石下被困呼吸的杂波抑制

2023 International Seminar on Intelligent Technology and Its Applications (ISITIA) Pub Date : 2023-07-26 DOI: 10.1109/ISITIA59021.2023.10221122

Queen Hesti Ramadhamy, A. A. Pramudita, F. Y. Suratman

{"title":"Clutter Reduction in Detecting Trapped Human Respiration Under Rubble for FMCW Radar System","authors":"Queen Hesti Ramadhamy, A. A. Pramudita, F. Y. Suratman","doi":"10.1109/ISITIA59021.2023.10221122","DOIUrl":"https://doi.org/10.1109/ISITIA59021.2023.10221122","url":null,"abstract":"Detecting human respiration under rubble using a radar system causes an attenuation effect and generates additional signals beyond the target. In addition, the rubble can cause detection errors caused by the clutter from the surface and some reflections of objects under the rubble. Therefore, clutter reduction of the surface and other objects under the rubble is necessary. The identification of clutter signals originating from the wall surface performs by a method whose results uses to reduce the beat frequency arising from wall obstructions. Furthermore, that method combines with a phase detection method that extracts the Doppler response of human respiration activity. Meanwhile, reducing the clutter that comes from other reflections under the rubble is done with the proposed method, namely weighting process method. Clutter reduction aims to increase the Signal-to-Clutter Ratio (SCR) value. Laboratory experiment performed in this study used a Frequency Modulated Continuous Wave (FMCW) radar system which working at frequency of 24 GHz with a bandwidth of 200 MHz. The clutter reduction results show the extraction of respiration patterns and human position under the rubble. The obtained result using weighting process method able to increasing the SCR value approximately 10 dB, and the proposed method applies to this experimental condition.","PeriodicalId":116682,"journal":{"name":"2023 International Seminar on Intelligent Technology and Its Applications (ISITIA)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116733142","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