2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)最新文献_第7页

Eco-Friendly IoT Solutions for Smart Cities Development: An Overview 面向智慧城市发展的生态友好型物联网解决方案综述

2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085100

Nesma Abd El-mawla, M. Badawy

{"title":"Eco-Friendly IoT Solutions for Smart Cities Development: An Overview","authors":"Nesma Abd El-mawla, M. Badawy","doi":"10.1109/ICAISC56366.2023.10085100","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085100","url":null,"abstract":"The last three years showed global systems’ fragility in different disciplines, such as medicine, travel, and trade. Moreover, environmental changes are still happening in extreme weather phenomena, exacerbating COVID-19 in the world health sector. Therefore, the world needs to work hard in both traditional and modern technological ways to develop smart solutions for the development of smart cities to create open, interconnected networks for everyone. The focus of intense research worldwide is the development of standardized eco-friendly sensor networks enabled by IoT technology. This study presents a comprehensive overview of the challenges facing the world and humans in the current era and how modern technologies, including the Internet of Things (IoT), can make a real change in smart city development and save the global environment. These technological solutions and frameworks help to achieve innovative administration, high adaptability, better efficiency, and productivity. In particular, the paper spots light on top environmental challenges according to impact and likelihood classifications. Also, it discusses recent green technology solutions for smart city development in many applications, such as e-waste management, climate change adaptation, water crises, and natural disaster management.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128102713","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

Online Phishing Detection Using Machine Learning 使用机器学习的在线网络钓鱼检测

2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085377

Rabab Alayham Abbas Helmi, M. Johar, Muhammad Alif Sazwan Bin Mohd. Hafiz

引用次数: 1

Utilizing metabolite connectivity and G-CNN to detect gallbladder cancer 利用代谢物连通性和G-CNN检测胆囊癌

2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085286

A. Obaid, Mohamed Ksantini, Amina Turki, Abdullah Safaaldin, H. Bellaaj

{"title":"Utilizing metabolite connectivity and G-CNN to detect gallbladder cancer","authors":"A. Obaid, Mohamed Ksantini, Amina Turki, Abdullah Safaaldin, H. Bellaaj","doi":"10.1109/ICAISC56366.2023.10085286","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085286","url":null,"abstract":"The hallmark of cancer is metabolic remodelling, which offers a unique insight into the biology of the disease revealing an opportunity for gallbladder cancer identification. By conceptualising the diagnosis of gallbladder cancer as a classification problem, it is possible to assess the capacity of several Machine Learning (ML) models to distinguish between gallbladder cancer patients and healthy individuals. Some of the models that are widely used in metabolomics literature include Support Vector Machines (SVM), Random Forest (RF) classifiers, Artificial Neural Networks (ANN), and Partial Least Squares-Discriminant Analysis (PLS-DA). The use of these models with metabolomic data has been successful. However, whether using them for classification tasks is preferable to using other or more complicated ML models has not been explored. We investigate a novel strategy for classifying people with gallbladder cancer by applying a Graph-Convolutional Neural Network (G-CNN) model to a dataset of patients. The methodical biological model of metabolite interactions and pathways as links is the foundation for this approach. Our findings show that the G-CNN significantly outperforms the most commonly used techniques, in contrast to the RF, whose effectiveness is marginally less but still equivalent to our model. Our findings suggest that using G-CNNs in metabolomics research is promising, and the adoption of non-invasive methods of metabolomic data extraction may help identify gallbladder cancer. Our suggested method achieves an accuracy of 93.6%, a specificity of 97%, and an AUC of 99.2%.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131861163","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

IoT-Based Smart Cities Beyond 2030: Enabling Technologies, Challenges, and Solutions 2030年后基于物联网的智慧城市:使能技术、挑战和解决方案

2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085126

Wesal Melibari, Hamzah Baodhah, N. Akkari

引用次数: 0

Mapping the Scientific Landscape of Smart Buildings and Climate Change 绘制智能建筑与气候变化的科学景观

2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085598

Saliha Ayman Ahmed, Lina Sami Abouelnaga, T. Brahimi

{"title":"Mapping the Scientific Landscape of Smart Buildings and Climate Change","authors":"Saliha Ayman Ahmed, Lina Sami Abouelnaga, T. Brahimi","doi":"10.1109/ICAISC56366.2023.10085598","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085598","url":null,"abstract":"The purpose of this paper is to conduct a comprehensive data mining, analysis, and visualization of smart cities and climate change, with a focus on development, trends, active actors, and the interrelationship between countries and active institutions. The study is based on the Scopus database and the Visualization Of Similarities Method (VOS) method between objects. Results revealed that 1653 articles were published since 1997, but 97% of these articles were published in the last 10 years alone. The top five most active countries are the USA, India, UK, Italy, and China. 20% of the total documents were in engineering, 16% in environmental science, 14% in social sciences, 12% in computer science, and 12% in energy. The overly visualization revealed that recent publications are more focused on smart cities, climate change, and energy storage with the application of AI, machine learning, deep learning, IoT, and sensors. This study shows how important it is to map the scientific landscape of smart buildings and climate change, which has unveiled an increase in research and provide a valuable tool for finding practical ways to build smart cities while fighting climate change and protecting the environment.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121523289","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

Document Provenance and Authentication through Authorship Classification 通过作者身份分类的文档来源和认证

2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085330

Muhammad Tayyab Zamir, Muhammad Asif Ayub, Jebran Khan, Muhammad Jawad Ikram, Nasir Ahmad, Kashif Ahmad

{"title":"Document Provenance and Authentication through Authorship Classification","authors":"Muhammad Tayyab Zamir, Muhammad Asif Ayub, Jebran Khan, Muhammad Jawad Ikram, Nasir Ahmad, Kashif Ahmad","doi":"10.1109/ICAISC56366.2023.10085330","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085330","url":null,"abstract":"Style analysis, which is relatively a less explored topic, enables several interesting applications. For instance, it allows authors to adjust their writing style to produce a more coherent document in collaboration. Similarly, style analysis can also be used for document provenance and authentication as a primary step. In this paper, we propose an ensemble-based text-processing framework for the classification of single and multi-authored documents, which is one of the key tasks in style analysis. The proposed framework incorporates several state-of-the-art text classification algorithms including classical Machine Learning (ML) algorithms, transformers, and deep learning algorithms both individually and in merit-based late fusion. For the merit-based late fusion, we employed several weight optimization and selection methods to assign merit-based weights to the individual text classification algorithms. We also analyze the impact of the characters on the task that are usually excluded in NLP applications during pre-processing by conducting experiments on both clean and un-clean data. The proposed framework is evaluated on a large-scale benchmark dataset, significantly improving performance over the existing solutions.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116633729","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 Systematic Overview on Simulation of Connected Vehicles Infrastructure in Smart Cities 智慧城市网联车辆基础设施仿真系统综述

2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10084942

Manik Gupta, I. Dhaou, K. Garg, B. Sharma

引用次数: 0

QuadSWARM: A Real-Time Autonomous Surveillance System using Multi-Quadcopter UAVs QuadSWARM:使用多四轴无人机的实时自主监视系统

2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085441

Ajiya Fatima Moiz, Hassaan Moiz Khawaja, Z. Khan, Raja Sohail

{"title":"QuadSWARM: A Real-Time Autonomous Surveillance System using Multi-Quadcopter UAVs","authors":"Ajiya Fatima Moiz, Hassaan Moiz Khawaja, Z. Khan, Raja Sohail","doi":"10.1109/ICAISC56366.2023.10085441","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085441","url":null,"abstract":"This paper presents an automated solution for real time perimeter surveillance in smart cities. By using a swarm of custom-made drones, installed with surveillance payloads, which is specially designed to carry out such missions, additional advantages can be gained due to multiple drones simultaneously covering different observatory areas. These flying robots have multiple degrees of autonomy, from completely manual to fully scripted pre-planned mission execution. Moreover, they are difficult to detect due to smaller size and signature as compared to fixed wing unmanned aircraft, and even if one of them is compromised, others in the swarm can complete the mission. The real-time video received from the drone can also detect the land mapping of enemy territory and quickly provide live data for situational awareness. The present system uses a leader/follower approach based on the hierarchical swarm of four drones which is able to operate in all terrain and fly over hard to reach places carrying a limited payload which can help saving lives in time constrained missions.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"02 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124452738","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

Flash Flood Simulation for Assisting Children to Understand the Flood Disaster 帮助儿童了解洪水灾害的山洪模拟

2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085494

Nur Khairunnisaa’ Suraidi, Nur Shafiza Che Ismail, Safinaz Mustapha

引用次数: 0

Instructors Experience of using Cloud Computing Based Applications in Saudi Arabia 讲师在沙特阿拉伯使用基于云计算的应用程序的经验

2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC) Pub Date : 2023-01-23 DOI: 10.1109/ICAISC56366.2023.10085435

Mohammed Gollapalli, Bador Alqahtani, Amnah Alghamdi, Meera Alotaibi

{"title":"Instructors Experience of using Cloud Computing Based Applications in Saudi Arabia","authors":"Mohammed Gollapalli, Bador Alqahtani, Amnah Alghamdi, Meera Alotaibi","doi":"10.1109/ICAISC56366.2023.10085435","DOIUrl":"https://doi.org/10.1109/ICAISC56366.2023.10085435","url":null,"abstract":"With the recent global spread of the COVID-19 (also known as the corona virus) pandemic, several governments have attempted to control its transmission through preventive and precautionary measures. Education is one of the factors that has been impacted by the pandemic. As a result, to limit the spread of the virus, many countries adopted distance education instead of traditional education to ensure the continuity of the educational process. Cloud computing is a technology that offers numerous advantages in the field of education. The Kingdom of Saudi Arabia was one of the countries that had decided and continues to use various cloud platforms for distance education. In this study, we look at how effective cloud computing platforms are in the learning process in Saudi Arabian schools. The primary goal of this research was to investigate the teacher’s ability to access different cloud computing services, as well as their ease of use and utility, by evaluating the effectiveness of these platforms as a mode of teaching before and after the pandemic. A total of 559 male and female schoolteachers’ data was collected using self-administered questionnaires in Al-Bahah region and was analyzed using the IBM SPSS Statistics software. The analysis of this study expanded our understanding on the possibility of using educational platforms across schools in the kingdom. The findings also revealed that the use of cloud platforms during the pandemic increased by 28% in the region which have now become integral part of education. Furthermore, the findings revealed that teachers frequently encountered difficulties in implementing cloud-based educational processes, particularly in rural and mountainous areas.","PeriodicalId":422888,"journal":{"name":"2023 1st International Conference on Advanced Innovations in Smart Cities (ICAISC)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131317054","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