ArticleSensors (Basel, Switzerland)2018
Design, Implementation and Practical Evaluation of an IoT Home Automation System for Fog Computing Applications Based on MQTT and ZigBee-WiFi Sensor Nodes.
Article in Sensors (Basel, Switzerland), 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.
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Who cites it
30 citing papers in PubMed.
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- Edge-Computing Meshed Wireless Acoustic Sensor Network for Indoor Sound Monitoring.Sensors (Basel, Switzerland) · 2022Article
- Knowledge Diffusion of the Internet of Things (IoT): A Main Path Analysis.Wireless personal communications · 2022Article
- Reliable Control Applications with Wireless Communication Technologies: Application to Robotic Systems.Sensors (Basel, Switzerland) · 2021Article
- Towards Smart Home Automation Using IoT-Enabled Edge-Computing Paradigm.Sensors (Basel, Switzerland) · 2021Article
- A Novel Robust Smart Energy Management and Demand Reduction for Smart Homes Based on Internet of Energy.Sensors (Basel, Switzerland) · 2021Article
- An IoT-Based Smart Home Automation System.Sensors (Basel, Switzerland) · 2021Article
- BACnet Application Layer over Bluetooth-Implementation and Validation.Sensors (Basel, Switzerland) · 2021Article
- FogFrame: a framework for IoT application execution in the fog.PeerJ. Computer science · 2021Article
- IoT-Based Applications in Healthcare Devices.Journal of healthcare engineering · 2021Review
- Toward Resilient Wireless Sensor Networks: A Virtualized Perspective.Sensors (Basel, Switzerland) · 2020Article
- Breaking Down the Compatibility Problem in Smart Homes: A Dynamically Updatable Gateway Platform.Sensors (Basel, Switzerland) · 2020Article
- Edge Machine Learning for AI-Enabled IoT Devices: A Review.Sensors (Basel, Switzerland) · 2020Review
- A Parallel Evolutionary Computing-Embodied Artificial Neural Network Applied to Non-Intrusive Load Monitoring for Demand-Side Management in a Smart Home: Towards Deep Learning.Sensors (Basel, Switzerland) · 2020Article
- Proof of Concept of Scalable Integration of Internet of Things and Blockchain in Healthcare.Sensors (Basel, Switzerland) · 2020Article
Corrections and comments
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Authors and funding
4 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In recent years, the improvement of wireless protocols, the development of cloud services and the lower cost of hardware have started a new era for smart homes. One such enabling technologies is fog computing, which extends cloud computing to the edge of a network allowing for developing novel Internet of Things (IoT) applications and services. Under the IoT fog computing paradigm, IoT gateways are usually utilized to exchange messages with IoT nodes and a cloud. WiFi and ZigBee stand out as preferred communication technologies for smart homes. WiFi has become very popular, but it has a limited application due to its high energy consumption and the lack of standard mesh networking capabilities for low-power devices. For such reasons, ZigBee was selected by many manufacturers for developing wireless home automation devices. As a consequence, these technologies may coexist in the 2.4 GHz band, which leads to collisions, lower speed rates and increased communications latencies. This article presents ZiWi, a distributed fog computing Home Automation System (HAS) that allows for carrying out seamless communications among ZigBee and WiFi devices. This approach diverges from traditional home automation systems, which often rely on expensive central controllers. In addition, to ease the platform's building process, whenever possible, the system makes use of open-source software (all the code of the nodes is available on GitHub) and Commercial Off-The-Shelf (COTS) hardware. The initial results, which were obtained in a number of representative home scenarios, show that the developed fog services respond several times faster than the evaluated cloud services, and that cross-interference has to be taken seriously to prevent collisions. In addition, the current consumption of ZiWi's nodes was measured, showing the impact of encryption mechanisms.
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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.