A Trustable Federated Learning Framework for Rapid Fire Smoke Detection at the Edge in Smart Home Environments

被引:0
|
作者
Nikul Patel, Aryan [1 ]
Srivastava, Gautam [2 ,3 ,4 ]
Kumar Reddy Maddikunta, Praveen [5 ]
Murugan, Ramalingam [5 ]
Yenduri, Gokul [6 ]
Reddy Gadekallu, Thippa [7 ,8 ,9 ]
机构
[1] Vellore Institute of Technology, School of Computer Science and Engineering, Vellore,632014, India
[2] China Medical University, Research Centre for Interneural Computing, Taichung,404, Taiwan
[3] Lebanese American University, Department of Computer Science and Math, Beirut,03797751, Lebanon
[4] Chitkara University Institute of Engineering And Technology, Chitkara University, Centre for Research Impact and Outcome, Rajpura,140401, India
[5] Vellore Institute of Technology, School of Computer Science Engineering and Information Systems, Vellore,632014, India
[6] VIT-AP University, School of Computer Science and Engineering, Amaravati,522237, India
[7] Zhejiang A&f University, College of Mathematics and Computer Science, Hangzhou,311300, China
[8] Lovely Professional University, Division of Research and Development, Phagwara,144411, India
[9] Chitkara University, Center of Research Impact and Outcome, Rajpura,140401, India
关键词
D O I
10.1109/JIOT.2024.3439228
中图分类号
学科分类号
摘要
引用
收藏
页码:37708 / 37717
相关论文
共 50 条
  • [31] Early Detection System for Gas Leakage and Fire in Smart Home Using Machine Learning
    Salhi, Lamine
    Silverston, Thomas
    Yamazaki, Taku
    Miyoshi, Takumi
    [J]. 2019 IEEE INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS (ICCE), 2019,
  • [32] A conceptual framework for designing smart learning environments
    Sirkka Freigang
    Lars Schlenker
    Thomas Köhler
    [J]. Smart Learning Environments, 5 (1)
  • [33] An interdisciplinary Framework for Designing Smart Learning Environments
    Freigang, Sirkka
    Schlenker, Lars
    Koehler, Thomas
    [J]. CHALLENGES AND SOLUTIONS IN SMART LEARNING, 2018, : 17 - 20
  • [34] kubeFlower : A privacy-preserving framework for Kubernetes-based federated learning in cloud-edge environments
    Parra-Ullauri, Juan Marcelo
    Madhukumar, Hari
    Nicolaescu, Adrian-Cristian
    Zhang, Xunzheng
    Bravalheri, Anderson
    Hussain, Rasheed
    Vasilakos, Xenofon
    Nejabati, Reza
    Simeonidou, Dimitra
    [J]. FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2024, 157 : 558 - 572
  • [35] A Federated Learning Approach to Anomaly Detection in Smart Buildings
    Sater, Raed Abdel
    Ben Hamza, A.
    [J]. ACM TRANSACTIONS ON INTERNET OF THINGS, 2021, 2 (04):
  • [36] Ferrari: A Personalized Federated Learning Framework for Heterogeneous Edge Clients
    Yao, Zhiwei
    Liu, Jianchun
    Xu, Hongli
    Wang, Lun
    Qian, Chen
    Liao, Yunming
    [J]. IEEE TRANSACTIONS ON MOBILE COMPUTING, 2024, 23 (10) : 10031 - 10045
  • [37] A Distributed Federated Transfer Learning Framework for Edge Optical Network
    Yang, Hui
    Yao, Qiuyan
    Zhang, Jie
    [J]. 2020 ASIA COMMUNICATIONS AND PHOTONICS CONFERENCE (ACP) AND INTERNATIONAL CONFERENCE ON INFORMATION PHOTONICS AND OPTICAL COMMUNICATIONS (IPOC), 2020,
  • [38] Federated Learning-Oriented Edge Computing Framework for the IIoT
    Liu, Xianhui
    Dong, Xianghu
    Jia, Ning
    Zhao, Weidong
    [J]. SENSORS, 2024, 24 (13)
  • [39] FLight: A lightweight federated learning framework in edge and fog computing
    Zhu, Wuji
    Goudarzi, Mohammad
    Buyya, Rajkumar
    [J]. SOFTWARE-PRACTICE & EXPERIENCE, 2024, 54 (05): : 813 - 841
  • [40] A privacy preserving framework for federated learning in smart healthcare systems
    Wang, Wenshuo
    Li, Xu
    Qiu, Xiuqin
    Zhang, Xiang
    Brusic, Vladimir
    Zhao, Jindong
    [J]. INFORMATION PROCESSING & MANAGEMENT, 2023, 60 (01)