A Review on IoT-Based Smart Home Automation Systems: Technologies, Architectures, and Challenges
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| Format: | Recurso digital |
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2026
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| _version_ | 1866901573990350848 |
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| author | Swarit Kori Rounak Manglani |
| author_facet | Swarit Kori Rounak Manglani |
| contents | The Internet of Things (IoT) has emerged as a transformative force in residential automation, enabling unprecedented levels of energy efficiency, safety monitoring, and remote device control from anywhere in the world. Contemporary systems now enable a single smartphone to manage thermal regulation, gas leak detection, occupant health monitoring, electricity billing oversight, and voice-commanded appliance management — all simultaneously. This paper presents a systematic review of eight recent peer-reviewed studies on IoT-based smart home automation systems, examining architectures ranging from cloud-dependent microcontroller platforms to localized edge computing frameworks. Each system is analyzed across key dimensions: hardware architecture, communication protocols, artificial intelligence integration, security frameworks, deployment model, and cost-effectiveness. A structured comparative analysis reveals three critical and recurring gaps in the literature — the near-absence of genuine AI-driven automation, pervasive reliance on basic cloud security that leaves the majority of systems vulnerable to cyberattacks, and persistent protocol fragmentation that prevents seamless cross-device interoperability. Based on these findings, a unified future research direction is proposed that integrates edge computing, predictive deep learning, universal communication standards, and blockchain-based decentralized security, collectively enabling the transition from remotely controlled devices to truly autonomous and secure intelligent living environments. |
| format | Recurso digital |
| id | zenodo_https___doi_org_10_5281_zenodo_20180386 |
| institution | Zenodo |
| language | |
| publishDate | 2026 |
| publisher | Zenodo |
| record_format | zenodo |
| spellingShingle | A Review on IoT-Based Smart Home Automation Systems: Technologies, Architectures, and Challenges Swarit Kori Rounak Manglani Internet of Things (IoT) Smart Home Automation Edge Computing Machine Learning Blockchain Security Communication Protocols NodeMCU Raspberry Pi ESP32 Energy Management The Internet of Things (IoT) has emerged as a transformative force in residential automation, enabling unprecedented levels of energy efficiency, safety monitoring, and remote device control from anywhere in the world. Contemporary systems now enable a single smartphone to manage thermal regulation, gas leak detection, occupant health monitoring, electricity billing oversight, and voice-commanded appliance management — all simultaneously. This paper presents a systematic review of eight recent peer-reviewed studies on IoT-based smart home automation systems, examining architectures ranging from cloud-dependent microcontroller platforms to localized edge computing frameworks. Each system is analyzed across key dimensions: hardware architecture, communication protocols, artificial intelligence integration, security frameworks, deployment model, and cost-effectiveness. A structured comparative analysis reveals three critical and recurring gaps in the literature — the near-absence of genuine AI-driven automation, pervasive reliance on basic cloud security that leaves the majority of systems vulnerable to cyberattacks, and persistent protocol fragmentation that prevents seamless cross-device interoperability. Based on these findings, a unified future research direction is proposed that integrates edge computing, predictive deep learning, universal communication standards, and blockchain-based decentralized security, collectively enabling the transition from remotely controlled devices to truly autonomous and secure intelligent living environments. |
| title | A Review on IoT-Based Smart Home Automation Systems: Technologies, Architectures, and Challenges |
| topic | Internet of Things (IoT) Smart Home Automation Edge Computing Machine Learning Blockchain Security Communication Protocols NodeMCU Raspberry Pi ESP32 Energy Management |
| url | https://doi.org/10.5281/zenodo.20180386 |