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Titlebook: Intelligent Systems for Smart Cities; Select Proceedings o Anand J. Kulkarni,Naoufel Cheikhrouhou Conference proceedings 2024 The Editor(s)

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书目名称Intelligent Systems for Smart Cities
副标题Select Proceedings o
编辑Anand J. Kulkarni,Naoufel Cheikhrouhou
视频video
概述Comprises peer-reviewed proceedings of the conference ICISA 2023.Covers the latest research in technological advances in the field of artificial intelligence and machine learning.Enriches understandin
图书封面Titlebook: Intelligent Systems for Smart Cities; Select Proceedings o Anand J. Kulkarni,Naoufel Cheikhrouhou Conference proceedings 2024 The Editor(s)
描述.This book presents the select proceedings of the 2nd International Conference on Intelligent Systems and Applications 2023. The theme of this conference is ‘Intelligent Systems for Smart Cities‘. It covers the topics of intelligent systems in multiple aspects such as healthcare, supply chain and logistics, smart homes and smart structures, banking and finance, a sustainable environment, social media and cyber security, crime prevention, and disaster management. The book will be useful for researchers and professionals interested in the broad field of artificial intelligence and machine learning..
出版日期Conference proceedings 2024
关键词Smart Cities; Banking and Finance; Social-Media, Cyber security & Crime Prevention; Infrastructure; Heal
版次1
doihttps://doi.org/10.1007/978-981-99-6984-5
isbn_softcover978-981-99-6983-8
isbn_ebook978-981-99-6984-5
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
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Image Steganography Using Particle Swarm Optimizationoses a steganographic method based on JPEG and the nature–inspired algorithm, Particle Swarm Optimisation (PSO) algorithm. The algorithm is used to first construct an optimal substitution matrix for modifying the undisclosed messages to make the quality of stego-images better. As well as being alter
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Intelligent Inventory Management in Retail Stores Using Four State of the Art Object Detection Modelolutional Neural Network), and MOBILENETSSD. These algorithms are being implemented and compared by mAP, or mean, average, and precision, and from that, the algorithm that works best for tracking is determined. Also, a webapp is created as a medium for visualization of the detected objects. Overall,
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Real Time Food Monitoring and Quality Alert System Using IoT and Streamlitth an accuracy of 78%. Novel Visualizations and a dynamic food quality graph are displayed over an interactive Streamlit website and Thingspeakcloud server achieving real time data communication with the user. The results show its relevance in the field of food logistics.
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