IoT based smart home automation using blockchain and deep learning models

Abstract

For the past few years, the concept of the smart house has gained popularity. The major challenges concerning a smart home include data security, privacy issues, authentication, secure identification, and automated decision-making of Internet of Things (IoT) devices. Currently, existing home automation systems address either of these challenges, however, home automation that also involves automated decision-making systems and systematic features apart from being reliable and safe is an absolute necessity. The current study proposes a deep learning-driven smart home system that integrates a Convolutional neural network (CNN) for automated decision-making such as classifying the device as “ON” and “OFF” based on its utilization at home. Additionally, to provide a decentralized, secure, and reliable mechanism to assure the authentication and identification of the IoT devices we integrated the emerging blockchain technology into this study. The proposed system is fundamentally comprised of a variety of sensors, a 5 V relay circuit, and Raspberry Pi which operates as a server and maintains the database of each device being used. Moreover, an android application is developed which communicates with the Raspberry Pi interface using the Apache server and HTTP web interface. The practicality of the proposed system for home automation is tested and evaluated in the lab and in real-time to ensure its efficacy. The current study also assures that the technology and hardware utilized in the proposed smart house system are inexpensive, widely available, and scalable. Furthermore, the need for a more comprehensive security and privacy model to be incorporated into the design phase of smart homes is highlighted by a discussion of the risks analysis’ implications including cyber threats, hardware security, and cyber attacks. The experimental results emphasize the significance of the proposed system and validate its usability in the real world.

Synchronizing smart city nodes using Skew Integrated Timestamp (SIT)

“…Smart city technology typically includes the Internet of Things (IoT), which enables devices and systems to collect and share data in real-time. In smart cities advanced analytics and machine learning algorithms helps to optimize decision-making ( Hassan et al, 2021 ; Arasteh et al, 2016 ; Ghazal et al, 2023 ; Ghazal et al, 2021 ; Koubaa et al, 2020 ; Babar et al., 2021 ; Umer et al, 2023 ). IoT forms the backbone of many smart city initiatives by connecting various devices, sensors, and systems to gather data, facilitate communication, and enable intelligent decision-making.…”

Development design of an IoT-based smart home monitoring system with security features

“…The application of IoT in Indonesia has grown rapidly making it the second largest country in terms of IoT application in Southeast Asia [12]. Smart home systems using IoT platforms have been designed to improve security, safety, automate the home, provide remote monitoring and control [13]. The use of cloud-based IoT in monitoring and controlling electrical resources at home can result in energy savings and cost reductions [14].…”