Muhammad Hassan, A. Nassr, U. S. Mohammed, Mohamed Abdelraheem
{"title":"An IoT based Structural Health Monitoring System for Critical Infrastructures","authors":"Muhammad Hassan, A. Nassr, U. S. Mohammed, Mohamed Abdelraheem","doi":"10.1109/gcaiot53516.2021.9691505","DOIUrl":"https://doi.org/10.1109/gcaiot53516.2021.9691505","url":null,"abstract":"Structure Health Monitoring provides a solution for damage detection, identification and monitoring the structural behavior through collection of data from several points on the structure. In this work, we present the design and operation of an Internet of Things based structural health monitoring system. The vibration signals are collected from specific points from the monitored structure using a processing node with wireless internet connectivity. Then, the sensors data are grouped and transmitted via cellular network to a remote server where an appropriate damage detection algorithm is applied on the collected data to assess the status of the structure. We provide details about the proposed systems design and operation including the hardware and software parts. Moreover, we augment the study with a practical experiment in which a five-story building was tested under healthy and damaged status. The results show the feasibility of the proposed system in automating the damage detection process.","PeriodicalId":169247,"journal":{"name":"2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131967599","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}
{"title":"Towards the use of IoT and AI for Pervasive Exergames","authors":"Kieran Woodward, E. Kanjo, Will Parker","doi":"10.1109/gcaiot53516.2021.9692952","DOIUrl":"https://doi.org/10.1109/gcaiot53516.2021.9692952","url":null,"abstract":"An exergame is a genre of gaming that combines exercising with digital game play. The ubiquity of mobile devices make them ideal platforms for these games to promote physical activities. Advances in Internet of Things (IoT) technologies including Bluetooth Low Energy (BLE) beacons can be utilised for proximity detection to promote physical activities and the use of Artificial Intelligence (AI) in the form of object recognition can accelerate engagement with location-based pervasive games. Therefore, we have designed, implemented, and tested a casual exergame in the form of a treasure hunt that provides the approximate location of nearby points of interest in real-time within the vicinity of Bluetooth beacons. The system exploits the signal strength of the BLE beacons to measure proximity which makes it suitable for outdoor and indoor functioning where GPS signals are not accessible. Our preliminary results show that IoT technology can be successfully utilised for proximity detection with sufficient accuracy. In addition the adoption of AI and Camera challenges has offered an active gaming experience and mediated playful experiences for large spaces.","PeriodicalId":169247,"journal":{"name":"2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127783553","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}
{"title":"IoT Application for the Physical Security in Gas Transportation","authors":"N. Zingirian, Girolamo Marco Salierno","doi":"10.1109/gcaiot53516.2021.9692917","DOIUrl":"https://doi.org/10.1109/gcaiot53516.2021.9692917","url":null,"abstract":"The paper presents a theft-prevention system, called the “Security Sensor System” (SSS), currently deployed on 50+ experimental trucks for Liquid Petroleum Gas (LPG) bulk distribution, and integrated on an Oil & Gas Transportation Internet of Things (IoT) platform managing a sensor network installed on over 3,000 tank trucks. A novel working principle, based on the continuous in-pipe fluid motion monitoring, has inspired the system design. The paper shows the effectiveness of such a principle in terms of feasibility and physical security, by reporting both the development challenges and the results obtained during eight months of SSS operation on a truck fleet.","PeriodicalId":169247,"journal":{"name":"2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116167016","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}
{"title":"The Use of Arabic Language COVID-19 Tweets Analysis in IoT Applications","authors":"F. Alderazi, A. Algosaibi, M. Alabdullatif","doi":"10.1109/gcaiot53516.2021.9693080","DOIUrl":"https://doi.org/10.1109/gcaiot53516.2021.9693080","url":null,"abstract":"Social media platforms have become one of the most powerful tools for organizations and individuals to publish news and express thoughts or feelings. With the increasingly enormous number of internet users in Saudi Arabia, the need raised to analyze Arabic posts. Since the emergence of COVID-19 in the latest 2019, it lefts economies and businesses counting the cost while governments fight the spread of the virus with new compartmentalization measures. Keeping in view the importance of quick and timely data analysis and sharing for policy actions, Artificial intelligence (AI) has played a crucial role in facilitating the exchange of views and information between scientists and decision-makers during the Coronavirus pandemic, and they continue to do so. This work mined to these content-related tweets to see how people’s feelings and expressions are changing. The results of this analysis can be used with integration with several IoT technologies to reduce the impact of covid-19 and drive new decisions in this field. For this goal, we proposed a Machine Learning (ML) models that can classify both of the sentiment and topic of Modern Standard Arabic (MSA) tweets and achieve high accuracy results.","PeriodicalId":169247,"journal":{"name":"2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130338506","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}
Daniel Schoepflin, Özge Albayrak, Piet Scheffler, Arne Wendt, Martin Gomse, Thorsten Schüppstuhl
{"title":"Visual AI Applications on Smart Delivery Units","authors":"Daniel Schoepflin, Özge Albayrak, Piet Scheffler, Arne Wendt, Martin Gomse, Thorsten Schüppstuhl","doi":"10.1109/gcaiot53516.2021.9693060","DOIUrl":"https://doi.org/10.1109/gcaiot53516.2021.9693060","url":null,"abstract":"As actors in an IoT production environment, smart delivery units are tasked with identifying loaded components and acquiring shopfloor events such as consumption of material. Conventional identification procedures rely heavily on tags and markers that are applied on components. For processes that require marker-less identification procedures, AI-based object identification can be incorporated. In this paper, we present a novel integration of such visual applications on smart delivery units. We address the main challenges of this approach, namely the need for computational resources and integration with low-cost components. Additionally, we propose a scalable IoT concept for the distribution of the AI functionalities on those delivery units by utilizing containerized applications. We demonstrate the validity of this AI integration with a real-world implementation on delivery units, tested in an application near environment.","PeriodicalId":169247,"journal":{"name":"2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115590264","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}
Ismail Arai, Samy El-Tawab, A. Salman, A. Elnoshokaty
{"title":"The Effect of COVID-19 on the Transit System in Two Regions: Japan and USA","authors":"Ismail Arai, Samy El-Tawab, A. Salman, A. Elnoshokaty","doi":"10.1109/gcaiot53516.2021.9693002","DOIUrl":"https://doi.org/10.1109/gcaiot53516.2021.9693002","url":null,"abstract":"The communication revolution that happened in the last ten years has increased the use of technology in the transportation world. Intelligent Transportation Systems wish to predict how many buses are needed in a transit system. With the pandemic effect that the world has faced since early 2020, it is essential to study the impact of the pandemic on the transit system. This paper proposes the leverage of Internet of Things (IoT) devices to predict the number of bus ridership before and during the pandemic. We compare the collected data from Kobe city, Hyogo, Japan, with data gathered from a college city in Virginia, USA. Our goal is to show the effect of the pandemic on ridership through the year 2020 in two different countries. The ultimate goal is to help transit system managers predict how many buses are needed if another pandemic hits.","PeriodicalId":169247,"journal":{"name":"2021 IEEE Global Conference on Artificial Intelligence and Internet of Things (GCAIoT)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116551668","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}