Quantum-enhanced neuro-fusion framework for intelligent decision-making in smart home IoT surveillance
- Title
- Quantum-enhanced neuro-fusion framework for intelligent decision-making in smart home IoT surveillance
- Creator
- Eugine Prince, M.; Rathi Devi, T.; Anu Disney, D.; Kannan, K.; Ramesh, K.; Sujatha Therese, P.
- Description
- Smart-home surveillance systems increasingly rely on heterogeneous IoT data streams, requiring efficient fusion, scalability, and robustness under noisy sensing conditions. This paper proposes a Quantum-Inspired Deep Neuro-Fusion Architecture (QDNFA) for anomaly detection in edgecloud IoT environments. The framework integrates modular encoders, temporal alignment, and a quantum-inspired optimisation mechanism to support multi-modal data processing while maintaining real-time performance. Experimental evaluation is conducted on the CASAS Smart Home dataset to validate sensor-centric anomaly detection, scalability across multiple devices, and edgecloud inference efficiency. While the architecture is designed to support audio and video modalities, the present study focuses on low-dimensional sensor data, and large-scale benchmarking on audiovisual surveillance datasets is identified as future work. Results demonstrate improved detection accuracy and reduced latency compared to baseline methods in sensor-driven smart-home scenarios. 2026 The Author(s).
- Source
- Franklin Open;Volume;15;Issue;;Article No.;100561;
- Date
- 01-01-2026
- Publisher
- Elsevier B.V.
- Subject
- Adversarial resilience; AI-driven IoT systems; Anomaly detection; Deep neuro-fusion; Edge computing; Internet of things; Multi-modal data fusion; Quantum-inspired optimization; Real-time surveillance; Smart home security
- Coverage
- Eugine Prince M., Department of Physics, S. T. Hindu College, Tamil Nadu, Nagercoil, India; Rathi Devi T., Department of Computer Science and Engineering, Christ University, Karnataka, Bengaluru, India; Anu Disney D., Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Tamil Nadu, Chennai, India; Kannan K., Department of Electronics and Communication Engineering, R. M. K. College of Engineering and Technology, Tamil Nadu, Thiruvallur, India; Ramesh K., Department of Electronics and Communication Engineering, Dhanalakshmi Srinivasan College of Engineering and Technology, Tamil Nadu, Chennai, India; Sujatha Therese P., Department of Electrical and Electronics Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu, India
- Rights
- All Open Access; Gold Open Access; Green Open Access
- Relation
- ISSN: 27731871;
- Format
- online
- Language
- English
- Type
- Article
Collection
Citation
Eugine Prince, M.; Rathi Devi, T.; Anu Disney, D.; Kannan, K.; Ramesh, K.; Sujatha Therese, P., “Quantum-enhanced neuro-fusion framework for intelligent decision-making in smart home IoT surveillance,” CHRIST (Deemed To Be University) Institutional Repository, accessed June 18, 2026, https://archives.christuniversity.in/items/show/22262.
