Sub-1Ghz Low-Power Wireless Node For IoT Based Smart Home System

Suranata, I Wayan Aditya; Suweken, Gede; Sariyasa,; Krisnawijaya, Ngakan Nyoman Kutha; Wardana, I Nyoman Kusuma; Aryanto, Kadek Yota Ernanda

doi:10.1109/iotais.2018.8600886

Cited by 3 publications

(2 citation statements)

References 18 publications

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“…As future work, open Sub-1 GHz standards such as IEEE 802. 15.4g and open-source hardware platforms such as Zolertia REmote and OpenMoteB [47] could be included to further validate the checklist for completeness and comparison among different Sub-1 GHz hardware and protocols.…”

Section: Discussionmentioning

confidence: 99%

“…Jardosh et al use simulations to produce real-world scenarios for mobile network evaluation using a mobility and signal propagation model [14]. Suranata et al record and analyze their field experiment results on the practical efficiency of Sub-1 GHz networks for low-power systems [15]. Researchers also try to ease the 2 Wireless Communications and Mobile Computing tension between the realistic environment and simulation by adding realistic simulation features.…”

Section: Related Workmentioning

confidence: 99%

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Factors Affecting the Performance of Sub-1 GHz IoT Wireless Networks

Yang

Ghubaish

Ünal

et al. 2021

Wireless Communications and Mobile Computing

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Internet of Things (IoT) devices frequently utilize wireless networks operating in the Industrial, Scientific, and Medical (ISM) Sub-1 GHz spectrum bands. Compared with higher frequency bands, the Sub-1 GHz band provides broader coverage and lower power consumption, which are desirable properties for low-cost IoT applications. However, low-power and low-cost IoT modules cause high variability in network performance. The varying influence from real-world environments additionally undermines wireless propagation and aggravates this variability. We explore these influences and provide a checklist of potential factors affecting wireless network performance in real-world environments. Using multiple low-cost IoT modules, we conduct multiple experiments in five real-world scenarios: indoor, street, open field, ground-to-drone (G2D), and drone-to-drone (D2D). Specifically, the tests are conducted inside a building, on a straight street with wooded sidewalks and aligned houses, on an open field golf course, and high up in the air between drones. To understand the difficulty of reproducibility in IoT deployments, we studied the effect of factors in four categories. This includes the effect of path (line of sight, distance, and obstruction), configuration (transmit power level), weather (precipitation, temperature, and humidity), and installation (IoT module mobility and position). We find that some of the factors in the path and weather categories have the most influence among all the factors, while the rest have moderate to low impacts. In the end, we provide a complete checklist of all the tested factors, which we believe would be constructive not only to academics but also to industrial practitioners working on wireless IoT systems.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%