2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)最新文献

Human Activity Recognition System using Smart Phone based Accelerometer and Machine Learning 基于智能手机加速度计和机器学习的人体活动识别系统

2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2020-07-01 DOI: 10.1109/IAICT50021.2020.9172037

Shan Ali, A. Khan, Shafaq Zia, Mayyda Mukhtar

{"title":"Human Activity Recognition System using Smart Phone based Accelerometer and Machine Learning","authors":"Shan Ali, A. Khan, Shafaq Zia, Mayyda Mukhtar","doi":"10.1109/IAICT50021.2020.9172037","DOIUrl":"https://doi.org/10.1109/IAICT50021.2020.9172037","url":null,"abstract":"Human Activity Recognition (HAR) has gained significance importance due to its wide range of applications in security, healthcare, surveillance, virtual reality, control systems and automation. Sensors embedded in modern mobile phones enable unobtrusive detection of Activities of Daily Living (ADL). Various statistical and deep learning techniques for the automated detection of human activity have been presented recently. In this study, we have collected accelerometry data through a mobile phone carried by a user for number of days to classify ADL on the basis of exhibited movement into stationary, light ambulatory, intense ambulatory and abnormal classes. ADL such as walking, sitting and jogging etc. are performed and classified simultaneously by mobile phone application and users for comparative analysis. Collected data is given as an input to the trained model and analyzed by implementing the J48 classifier. Results reveal an accuracy score of around 70% for each activity class and it is noted that the classification was performed with an accuracy of above 80% for stationary activity. It is shown that ADL can be recognized with high accuracy using accelerometry data collected in a constrained environment and a single sensor. J48 classifier also correctly classified activities that have a strong correlation between them such as sitting on a chair and standing in stationary position. This work is significant for utilization in long term health monitoring systems that are capable of ensuring neurological health for masses through HAR and mobile phones embedded with accelerometers.","PeriodicalId":433718,"journal":{"name":"2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114281607","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: 6

SigFox-based Internet of Things Network Planning for Advanced Metering Infrastructure Services in Urban Scenario 基于sigfox的城市场景下先进计量基础设施服务物联网规划

2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2020-07-01 DOI: 10.1109/IAICT50021.2020.9172022

Arrizky Ayu Faradila Purnama, M. I. Nashiruddin

{"title":"SigFox-based Internet of Things Network Planning for Advanced Metering Infrastructure Services in Urban Scenario","authors":"Arrizky Ayu Faradila Purnama, M. I. Nashiruddin","doi":"10.1109/IAICT50021.2020.9172022","DOIUrl":"https://doi.org/10.1109/IAICT50021.2020.9172022","url":null,"abstract":"SigFox is a Low Power Wide Area Network (LPWAN) technology using unlicensed frequency bands with Ultra Narrow Band technology. It has advantages in terms of very low power consumption, high receiver sensitivity, and the cheap cost of end devices. SigFox technology is based on Link Quality Control (LQI). One parameter is the division of zones is based on radio configuration, where Indonesia included in zone 2 with radio configuration RC4. SigFox is very suitable as a solution in terms of radio connectivity. In this study, an analysis of the Internet of Thing (IoT) network design was carried out in the East Java province of Indonesia, particularly in the cities of Surabaya, Sidoarjo, and Gresik as Urban Scenario. The Advanced Metering Infrastructure services include electricity, water, gas, and fuel. From the simulations that have been carried out, the optimal number of gateways obtained respectively 34 sites for the Surabaya area with the average signal level received was −78 dBm, and SNR value was 17.27 dB. While five gateways need for the Sidoarjo area with the average signal level received was −89.68 dBm, and SNR value was −1.06 dB, and eight sites for the Gresik area with the average signal level received was −89.14 dBm, and SNR value was −1.12 dB.","PeriodicalId":433718,"journal":{"name":"2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129351408","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: 3

Detection of Motor Seizures and Falls in Mobile Application using Machine Learning Classifiers 使用机器学习分类器检测移动应用中的运动癫痫和跌倒

2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2020-07-01 DOI: 10.1109/IAICT50021.2020.9172028

Shafaq Zia, A. Khan, Mayyda Mukhtar, Shan Ali, Jibran Shahid, Mobeen Sohail

{"title":"Detection of Motor Seizures and Falls in Mobile Application using Machine Learning Classifiers","authors":"Shafaq Zia, A. Khan, Mayyda Mukhtar, Shan Ali, Jibran Shahid, Mobeen Sohail","doi":"10.1109/IAICT50021.2020.9172028","DOIUrl":"https://doi.org/10.1109/IAICT50021.2020.9172028","url":null,"abstract":"We have developed a healthcare mobile application, for human activity recognition, monitoring of well-being and detection of individuals going towards a health hazard based on the data collected from sensors embedded in mobile phones and wearables. The data from sensors are processed within the mobile application to detect and classify different Activities of Daily Living. The developed framework is used to collect data in an unconstraint environment from individuals suffering from neurological disorders. The data is further tested using signal processing and machine learning algorithms. Results of in-app processing and classification are stored in a dedicated mobile database for later reference and analysis. This paper shows that statistical and Machine Learning methods can also be used within a mobile application for classification of ADLs. MyNeuroHealth has been designed in accordance with the scale of the prevalence of neurological disorders among the general population of developing countries and has become more relevant in COVID-19 pandemic as it offers real-time nonintrusive monitoring. Results show that MyNeuroHealth can detect and classify Motor Seizures and falls with an accuracy of 99%. The app is also able to detect if a patient had stumbled or fallen due to any reason and notifies caregiver accordingly.","PeriodicalId":433718,"journal":{"name":"2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131949196","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: 3

Food Detection with Image Processing Using Convolutional Neural Network (CNN) Method 使用卷积神经网络(CNN)方法进行图像处理的食物检测

2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2020-07-01 DOI: 10.1109/IAICT50021.2020.9172024

A. Ramdani, Agus Virgono, C. Setianingsih

引用次数: 4

Sigfox Based Network Planning Analysis for Public Internet of Things Services in Metropolitan Area 基于Sigfox的城域公共物联网服务网络规划分析

2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2020-07-01 DOI: 10.1109/IAICT50021.2020.9172012

Fenta Febriyandi, A. S. Arifin, M. I. Nashiruddin

{"title":"Sigfox Based Network Planning Analysis for Public Internet of Things Services in Metropolitan Area","authors":"Fenta Febriyandi, A. S. Arifin, M. I. Nashiruddin","doi":"10.1109/IAICT50021.2020.9172012","DOIUrl":"https://doi.org/10.1109/IAICT50021.2020.9172012","url":null,"abstract":"Sigfox is a radio protocol Low Power Wide Area Network (LPWAN) technology that has a characteristic global reach, cost-effective, energy efficiency, and simplicity. Sigfox operates in the unlicensed spectrum frequency band, during transmitting and receiving messages, Sigfox uses ultra-narrow band (UNB) modulation technique. This paper analyzes Sigfox based network planning for public Internet of Things (IoT) services in a metropolitan area that has 10.37 million population and 662.3 km2. The result of the study stated that 33 access points are needed to cover the entire city. The simulation result shows that 99.9% of the area has a Reference Signal Received Power (RSRP) Downlink level above −134 dBm. The mean values of RSRP Downlink and Signal to Interference and Noise Ratio (SINR) Downlink are −91.81 dBm and 7.98 dB, respectively. Meanwhile, for the Received Signal Strength Indicator (RSSI) Downlink parameter, 98.7% metropolitan area is covered and has a mean value of −87.91 dBm. Okumura-Hata radio propagation model is used and gives results that allowed propagation loss and shadow fading margin are 152.5 dB and 7.5 dB, respectively, thus cell range for one access point reaches 3.28 km.","PeriodicalId":433718,"journal":{"name":"2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129627427","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: 2

Immersion Effect of Dielectric Lens Radiation Performances Fed with Double Crossed Terahertz Planar Bow-Tie Antenna 双交叉太赫兹平面领结天线馈电介质透镜辐射性能的浸没效应

2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2020-07-01 DOI: 10.1109/IAICT50021.2020.9172017

C. Apriono, Farida Ulfah

{"title":"Immersion Effect of Dielectric Lens Radiation Performances Fed with Double Crossed Terahertz Planar Bow-Tie Antenna","authors":"C. Apriono, Farida Ulfah","doi":"10.1109/IAICT50021.2020.9172017","DOIUrl":"https://doi.org/10.1109/IAICT50021.2020.9172017","url":null,"abstract":"The size of a detector is the primary consideration to obtain a high-resolution imaging quality. A THz quasi optic can combine an optical component of a hemispherical dielectric lens and an antenna-based sensor to capture effectively incoming radiation. The use of the hemispherical lens can contribute to sensor size. This paper investigates an immersion technique for dielectric lens size reduction to provide radiation performances of gain and radiation efficiency on the purpose of antenna size miniaturization at Terahertz (THz) frequency. This investigation is using the CST Microwave Studio simulation software. Gain and radiation efficiency show a decreasing pattern as the dielectric thickness increases. The obtained gain is still 30 dB by adding thickness until half of the hemispherical radius once combined with matching layers and 0.6 of the radius once without matching layers. Therefore, a smaller size than a hemispherical structure can still provide excellent radiation performance. This information is useful to design as small as a THz detector to obtain high-resolution imaging.","PeriodicalId":433718,"journal":{"name":"2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121052507","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

Design of Detection Device for Sea Water Waves with Fuzzy Algorithm Based on Internet of Things 基于物联网的模糊算法海浪检测装置设计

2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2020-07-01 DOI: 10.1109/IAICT50021.2020.9172018

Surya Darmawan, Budhi Irawan, C. Setianingsih, Muhammad Ary Murty

引用次数: 6

Evaluation of the Maintainability Aspect of Industry 4.0 Service-oriented Production 工业4.0服务型生产可维护性评价

2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2020-07-01 DOI: 10.1109/IAICT50021.2020.9172010

Khalil Esper, Frank Schnicke

{"title":"Evaluation of the Maintainability Aspect of Industry 4.0 Service-oriented Production","authors":"Khalil Esper, Frank Schnicke","doi":"10.1109/IAICT50021.2020.9172010","DOIUrl":"https://doi.org/10.1109/IAICT50021.2020.9172010","url":null,"abstract":"Current markets are characterized by rapid changing in requirements and new customer needs. Thus, fast changeable production is a fundamental goal of Industry 4.0 scheme, which aims to make the manufacturing more changeable and efficient by interconnecting the various factory components, and representing the factory assets virtually in digital twins.In order to study the Industry 4.0 changeability capability, we apply scenario-based evaluation. We derive three change scenarios that can be observed in a plant: Change of product flow depending on quality, depending on product type and the introduction of a new product. Using these scenarios, we compare between the third industrial revolution (Industry 3) and Industry 4.0 architectures based on the resultant change impact.For our evaluation, we utilize the Architecture-Level Modifiability Analysis (ALMA) method and describe its instantiation to the given context, providing ALMA 4.0, a guideline for Industry 4.0 Maintainability scenario-based evaluation. The result shows that the change impact on Industry 4.0 is less than Industry 3. Thus, we provide quantitative evidence that changing Industry 4.0 architecture incurs less efforts than Industry 3 changes.","PeriodicalId":433718,"journal":{"name":"2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117340624","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: 7

Performance Analysis of FBMC-OQAM System for Barcode and QR Code Image Transmission FBMC-OQAM系统在条码和二维码图像传输中的性能分析

2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2020-07-01 DOI: 10.1109/IAICT50021.2020.9172034

A. F. Isnawati, M. Afandi, J. Hendry

{"title":"Performance Analysis of FBMC-OQAM System for Barcode and QR Code Image Transmission","authors":"A. F. Isnawati, M. Afandi, J. Hendry","doi":"10.1109/IAICT50021.2020.9172034","DOIUrl":"https://doi.org/10.1109/IAICT50021.2020.9172034","url":null,"abstract":"Nowadays, the use of barcode and QR code has been very common. The implementation of barcode and QR code is not only to ease the identification and inventory of goods but it is also used for goods tracking, place tracking, document management, and others. The performance of FBMC-OQAM communication system for image transmission of barcode and QR code become important to be researched considering both image data input have different characteristics. This study uses Zero Forcing (ZF) equalization as a symbol detection. The result of the study shows that in general, the accepted image data on system which used ZF equalization is better than the other without using ZF. The result of simulation also showed BER on barcode image as much as 1.94e-03 and on QR code as much as 8.125e-05 which meant that the performance of QR code transmission system earns better result compared to barcode. Based on the reading process of the data by reader or scanner, it showed that barcode image needed higher SNR, that was 27 dB compared to QR code image that only needed SNR 20 dB. In addition, barcode image enables data misreading even though the reader or scanner could detect the code that was on SNR 19 dB, it is different from QR code which the result of image reading earned correct information if it reached threshold.","PeriodicalId":433718,"journal":{"name":"2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123737348","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: 2

Development of a Hand held device for Automatic License Plate Recognition 手持车牌自动识别装置的研制

2020 IEEE International Conference on Industry 4.0, Artificial Intelligence, and Communications Technology (IAICT) Pub Date : 2020-07-01 DOI: 10.1109/IAICT50021.2020.9172026

Jampu Raju, C. V. Raghu, S. N. George, T. Bindiya

引用次数: 2