Fusion: Practice and Applications FPA 2692-4048 2770-0070 10.54216/FPA https://www.americaspg.com/journals/show/1902 2018 2018 Department of Intelligent Medical Systems, University of Information Technology and Communications, Biomedical Informatics College Zainab N. Al Al-Qudsy Department of Computer Engineering, University of Technology – Iraq, Baghdad, Iraq Zainab Mahmood Fadhil Department of Information and Communication Engineering, Al-Nahrain University, Baghdad, Iraq Refed Adnan Jaleel Computer Techniques Engineering Department, Al-Mustaqbal University, Babil, Iraq Musaddak Maher Abdul Zahra The Internet of Things (IoTs) has accelerated with the introduction of powerful biomedical sensors, telemedicine services and population ageing are concerns that can be solved by smart healthcare systems. However, the security of medical signal data that collected from sensors of IoTs technology, while it is being transmitted over public channels has grown to be a serious problem that has limited the adoption of intelligent healthcare systems. This suggests using the technology of blockchain to create a safe and reliable heart sound signal (PCG) that can communicate with wireless body area networks. The security plan offers a totally dependable and safe environment for every data flowing from the back end to front-end. Also in this paper, to classify heart sound signals, we suggested a one-dimensional convolutional neural network (1D-CNN) model. The denoising autoencoder extracted the heart sounds' deep features as an input feature of 1D-CNN. To extract the detailed characteristics from the PCG signals, a Data Denoising Auto Encoder (DDAE) was used instead of the standard MFCC, the suggested model shows significant improvement. The system's benefits include a less difficult encryption algorithm and a more capable and effective blockchain-based data transfer and storage system.   2023 2023 28 41 10.54216/FPA.120203 https://www.americaspg.com/articleinfo/3/show/1902