Multimodal healthcare data classification with Tangent Namib Beetle Optimization based routing in blockchain based IoT

【Author】 Lakshmanan, Ramanathan; Balakrishnan, Sarojini; Mahendran, Anand; Subramanian, Ananda Kumar

【Source】COMPUTERS & ELECTRICAL ENGINEERING

【影响因子】4.152

【Abstract】Blockchain and the Internet of Things (IoT) represent the most promising digital technologies in the modern era. Blockchain serves as a data-sharing platform, while IoT is a network for real-time data transmission analysis. If both of these advancements are executed, they will bring solutions to numerous problems, especially in healthcare applications. In this research, the IoT-blockchainbased fused conventional Neural Network (FCNN) is devised for healthcare data classification. The blockchain-enabled IoT health monitoring systems provide four layers device, communication or blockchain, computation or cloud, and user interface layer. Here, the device layer gathers the data, and the routing is carried out in the communication layer. The proposed Tangent Namib Beetle Optimization (TNBO) with fitness measures is considered for the routing process. Moreover, the input voice signal and input handwriting spiral image are subjected to a computation layer, in which they are subjected to preprocessing, image augmentation, and feature extraction. The features of the input image and voice signal are applied to the healthcare classification process. Finally, the healthcare classification is done by the proposed FCNN. Moreover, the efficiency of the system is ensured via the accuracy, specificity, and sensitivity parameters with optimal values of 0.924, 0.926, and 0.921, respectively.

【Keywords】Convolution neural network (CNN); Tangent Search Algorithm (TSA); Namib Beetle Optimization (NBO); Deep Learning (DL); Internet of Things (IoT)

【发表时间】2024 DEC

【收录时间】2024-10-13

【文献类型】案例研究

【主题类别】

区块链应用-实体经济-健康领域