ArticleSensors (Basel, Switzerland)2021
Towards Smart Home Automation Using IoT-Enabled Edge-Computing Paradigm.
Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Wide field-of-view anisotropic optoelectronic resistive memory for monocular in-sensor 3D motion perception and localization system.Nature communications · 2026Article
- Hybrid computing framework security in dynamic offloading for IoT-enabled smart home system.PeerJ. Computer science · 2024Article
- An IoT Enable Anomaly Detection System for Smart City Surveillance.Sensors (Basel, Switzerland) · 2023Article
- Solar Power Prediction Using Dual Stream CNN-LSTM Architecture.Sensors (Basel, Switzerland) · 2023Article
- An Efficient Pest Detection Framework with a Medium-Scale Benchmark to Increase the Agricultural Productivity.Sensors (Basel, Switzerland) · 2022Article
- Research on energy saving of computer rooms in Chinese colleges and universities based on IoT and edge computing technology.Heliyon · 2022Article
- Improving the Efficiency of Multistep Short-Term Electricity Load Forecasting via R-CNN with ML-LSTM.Sensors (Basel, Switzerland) · 2022Article
- An Effective Skin Cancer Classification Mechanism via Medical Vision Transformer.Sensors (Basel, Switzerland) · 2022Article
- Towards Hybrid Energy-Efficient Power Management in Wireless Sensor Networks.Sensors (Basel, Switzerland) · 2021Article
- Abnormal Activity Recognition from Surveillance Videos Using Convolutional Neural Network.Sensors (Basel, Switzerland) · 2021Article
- An Adaptive Protection System for Sensor Networks Based on Analysis of Neighboring Nodes.Sensors (Basel, Switzerland) · 2021Article
- Vision Sensor-Based Real-Time Fire Detection in Resource-Constrained IoT Environments.Computational intelligence and neuroscience · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Smart home applications are ubiquitous and have gained popularity due to the overwhelming use of Internet of Things (IoT)-based technology. The revolution in technologies has made homes more convenient, efficient, and even more secure. The need for advancement in smart home technology is necessary due to the scarcity of intelligent home applications that cater to several aspects of the home simultaneously, i.e., automation, security, safety, and reducing energy consumption using less bandwidth, computation, and cost. Our research work provides a solution to these problems by deploying a smart home automation system with the applications mentioned above over a resource-constrained Raspberry Pi (RPI) device. The RPI is used as a central controlling unit, which provides a cost-effective platform for interconnecting a variety of devices and various sensors in a home via the Internet. We propose a cost-effective integrated system for smart home based on IoT and Edge-Computing paradigm. The proposed system provides remote and automatic control to home appliances, ensuring security and safety. Additionally, the proposed solution uses the edge-computing paradigm to store sensitive data in a local cloud to preserve the customer's privacy. Moreover, visual and scalar sensor-generated data are processed and held over edge device (RPI) to reduce bandwidth, computation, and storage cost. In the comparison with state-of-the-art solutions, the proposed system is 5% faster in detecting motion, and 5 ms and 4 ms in switching relay on and off, respectively. It is also 6% more efficient than the existing solutions with respect to energy consumption.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.