2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS)最新文献_第4页

Recognition of Mistaken Pedal Pressing based on Pedal Pressing Behavior by using Genetic Programming 基于踩踏行为的遗传规划错误踩踏识别

2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS) Pub Date : 2018-11-01 DOI: 10.1109/IOTAIS.2018.8600885

Rahadian Yusuf, Albert Podusenko, I. Tanev, K. Shimohara

引用次数: 1

Flood Modelling and Prediction Using Artificial Neural Network 基于人工神经网络的洪水建模与预测

2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS) Pub Date : 2018-11-01 DOI: 10.1109/IOTAIS.2018.8600869

Awal Rais Sanubari, P. Kusuma, C. Setianingsih

{"title":"Flood Modelling and Prediction Using Artificial Neural Network","authors":"Awal Rais Sanubari, P. Kusuma, C. Setianingsih","doi":"10.1109/IOTAIS.2018.8600869","DOIUrl":"https://doi.org/10.1109/IOTAIS.2018.8600869","url":null,"abstract":"Flood is one of the common types of natural disaster in Indonesia, we need a system that can predict the arrival of the flood is important for the Indonesian people, especially people who live a certain area of the river flow. Some parameters that can be used to predict the flood are water level and rainfall around the river. Modeling system to predict the flood must have the prediction results as accurate as possible in order to produce a good system in predicting floods. Therefore, in this study proposed method of artificial neural network to analyze flood prediction ability by using artificial neural network In this study case using artificial neural network Radial Basis Function. Radial Basis Function is a model of artificial neural network architecture consisting of three layers of which are the input layer, hidden layer, and output layer. The data used for the training and testing process are data of water level and rainfall data in 2015 in Dayeuhkolot. Prediction results in the training and testing process resulted in MAPE values are 0.047% and 1.05% for water level data and 4.97% and 29.1% for rainfall data with combination of hidden node = 35, learning rate = 0.2 and Spread constant = 1.1 with the target epoch maximum termination of 5000 epoch.","PeriodicalId":302621,"journal":{"name":"2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS)","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127992676","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: 5

Applying Intelligent Agents for Anomaly Detection of Network Traffic in Internet of Things Networks 应用智能代理进行物联网网络流量异常检测

2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS) Pub Date : 2018-11-01 DOI: 10.1109/IOTAIS.2018.8600867

Igor Kotenko, I. Saenko, S. Ageev

引用次数: 1

Optical Internet of Things within 5G: Applications and Challenges 5G光物联网:应用与挑战

2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS) Pub Date : 2018-11-01 DOI: 10.1109/IOTAIS.2018.8600894

S. Teli, S. Zvánovec, Zabih Ghassemlooy

{"title":"Optical Internet of Things within 5G: Applications and Challenges","authors":"S. Teli, S. Zvánovec, Zabih Ghassemlooy","doi":"10.1109/IOTAIS.2018.8600894","DOIUrl":"https://doi.org/10.1109/IOTAIS.2018.8600894","url":null,"abstract":"The fifth generation (5G) telecommunications standards are being developed to meet the growing demands for high-speed wireless networks (i.e., few tens of Gigabits per second). The 5G standard stems largely from an increasing number of users and plethora of different devices, collectively referred to as smart devices, connecting to a network as part of Internet-of-Things (IoT). A few potential technologies have emerged for 5G such as millimeter waves, massive multiple-input multiple-output, and small cell communications. Although these technologies would satisfy the requirements of 5G, there is a complementary alternative wireless technology of optical wireless communications (OWC), which is being considered. As part of OWC, visible light communications (VLC) and optical camera communications (OCC) are the most attractive options for 5G networks and beyond. VLC with huge frequency spectrum integrated with IoT can open up a wide range of indoor and outdoor applications as part of future smart environments. This paper provides an overview of the all-optical IoT (OIoT) focusing on VLC and OCC based potential applications and challenges as part of 5G standards.","PeriodicalId":302621,"journal":{"name":"2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS)","volume":"2022 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134265303","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: 32

Personal Authentication by Lips EMG Using Dry Electrode and CNN 使用干电极和CNN的嘴唇肌电图进行个人身份验证

2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS) Pub Date : 2018-11-01 DOI: 10.1109/IOTAIS.2018.8600859

S. Morikawa, S. Ito, Momoyo Ito, M. Fukumi

{"title":"Personal Authentication by Lips EMG Using Dry Electrode and CNN","authors":"S. Morikawa, S. Ito, Momoyo Ito, M. Fukumi","doi":"10.1109/IOTAIS.2018.8600859","DOIUrl":"https://doi.org/10.1109/IOTAIS.2018.8600859","url":null,"abstract":"As an alternative to voice, sign language and artificial larynx can be used. However, there are disadvantages where they require a long-term training and are expensive. Therefore, researches on detection of utterance by electromyography (EMG) analysis around the lips have been conducted. On the one hand, it is necessary to construct a personal authentication system to identify speakers. The electrode used in this paper is 2 electrodes sensor, which is small in size and a dry type. Three sensors are attached in the orbicularis muscle, the zygomatic major muscle, and the depressor angle oris muscle which can acquire myoelectric information necessary for identification in Japanese vowel utterance. EMG signals are measured using P-EMG plus. In order to eliminate noises, signal cutting is carried out before and after the central point of the acquired raw data. Furthermore, EMG data are divided to increase the number of data while overlapping. These are named “DATA 1”. A Hamming window is then applied for them, and the amplitude values of the power spectra are calculated by fast Fourier transform. Automatic verification and elimination of noise parts by quartile method were carried out. In order to reconstruct signals after noise elimination, the inverse Fourier transform is carried out and then a inverse Hamming window is applied. These are named “DATA 2”. Learning identification is carried out using a convolutional neural network. A large difference was found in accuracy depending on the data set created separately by measurement date. Therefore, it was found that intra-individual variation by each subject was large. In the future, it is necessary to further improve the data and to reduce individual variation within each subject.","PeriodicalId":302621,"journal":{"name":"2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133643135","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

Naive Bayes Multi-Label Classification Approach for High-Voltage Condition Monitoring 高压状态监测的朴素贝叶斯多标签分类方法

2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS) Pub Date : 2018-11-01 DOI: 10.1109/IOTAIS.2018.8600914

I. Mitiche, A. Nesbitt, P. Boreham, B. Stewart, G. Morison

引用次数: 7

Smart Air Quality Monitoring System with LoRaWAN 智能空气质量监测系统与LoRaWAN

2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS) Pub Date : 2018-11-01 DOI: 10.1109/IOTAIS.2018.8600904

M. Thu, Wunna Htun, Y. Aung, Pyone Ei Ei Shwe, N. Tun

{"title":"Smart Air Quality Monitoring System with LoRaWAN","authors":"M. Thu, Wunna Htun, Y. Aung, Pyone Ei Ei Shwe, N. Tun","doi":"10.1109/IOTAIS.2018.8600904","DOIUrl":"https://doi.org/10.1109/IOTAIS.2018.8600904","url":null,"abstract":"Nowadays, cities all over the globe are transforming into smart cities. Smart cities initiatives need to address environmental concerns such as air pollution to provide clean air. A scalable and cost-effective air monitoring system is imperative to monitor and control air pollution for smart city development. Air pollution has notable effects on the well-being of the population a whole, global atmosphere, and worldwide economy. This paper presents a scalable smart air quality monitoring system with low-cost sensors and long-range communication protocol. The sensors collect four parameters, temperature, humidity, dust and carbon dioxide in the air. The proposed end-to-end system has been implemented and deployed in Yangon, the business capital of Myanmar, as a case study since Jun 2018. The system allows the users to log in to an online dashboard to monitor the real-time status. In addition, based the collected air quality parameters for the past two months, a machine learning model has been trained to make predictions of parameters such that proactive actions can be taken to alleviate the impacts from air pollution.","PeriodicalId":302621,"journal":{"name":"2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128800065","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: 29

Smart Contracts for Machine-to-Machine Communication: Possibilities and Limitations 机器对机器通信的智能合约:可能性和局限性

2018 IEEE International Conference on Internet of Things and Intelligence System (IOTAIS) Pub Date : 2018-06-01 DOI: 10.1109/IOTAIS.2018.8600854

Yuichi Hanada, Luke Hsiao, P. Levis

引用次数: 47