Empirical test of Wi-Fi environment stability for smart farm platform

JiHye, O; Noh, Dong-Hee; Sohn, Young-Ho

doi:10.1109/caipt.2017.8320656

Cited by 8 publications

(2 citation statements)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…While the LPWAN and satellite technologies are ideal for IoT-enabled agricultural technologies, transmitting small packets of sensory data, they are not designed to handle the bandwidth requirements of verticals such as voice, imaging, and video transmission. These use cases can be enabled through on-farm Wi-Fi networks [24].…”

Section: A State-of-the-art In Communication Technologies For Data-dr...mentioning

confidence: 99%

Wireless Communications for Internet of Farming: An Early 5G Measurement Study

et al. 2022

View full text Add to dashboard Cite

Data-driven agriculture and Internet of Farming (IoF) require reliable communication systems. Nowadays, only some of the key use cases demanded by the agricultural industry verticals get support from multiple state of the art wireless technologies such as 4G, Wi-Fi, or Low Power Wide Area Network (LPWAN) technologies, combined with satellite and cloud access. However, the ones demanding very high data rates or very low latency are still not feasible. With 5G, designed for flexible support of Extreme Mobile Broadband (xMBB), Massive Machine-Type Communications (mMTC) and Ultra-reliable Machine-Type Communications (uMTC), more agricultural use cases will be possible. This paper provides a reference list of data-driven agriculture scenarios and use cases with their associated communication requirements, and whose feasibility is evaluated in a live 5G trial performed in a representative rural area scenario in the south of Denmark. The paper details a reference methodology for assessing 5G Quality of Service (QoS), including multi-connectivity schemes and reports the empirical 5G performance results, which are put in perspective of the requirements for the different IoF reference scenarios. The empirical results indicate that early 5G deployments are already capable of reliably serving data-driven agriculture vertical use cases such as those related to agricultural logistics or configuration of machinery and diagnostics in 65.8-99% of the cases; but it will be necessary to wait for 5G network upgrades and coming 5G Releases in order to operate the more low latency demanding use cases.

show abstract

Section: A State-of-the-art In Communication Technologies For Data-dr...mentioning

confidence: 99%

Wireless Communications for Internet of Farming: An Early 5G Measurement Study

et al. 2022

View full text Add to dashboard Cite

show abstract

“…Padalalu et al [45] investigated the smart water dripping system for smart farming. Likewise, JiHye et al [46] tested the WiFi stability for the smart farm platform.…”

Section: Related Workmentioning

confidence: 99%

Internet of Things Data Collection Using Unmanned Aerial Vehicles in Infrastructure Free Environments

et al. 2020

View full text Add to dashboard Cite

With the immensity of distributed Internet of Things (IoT) devices and the exponential increase in data generated from a variety of IoT-driven smart-world applications, how to effectively provide data driven service supported by IoT has become a critical issue. While the state-of-the-art technologies have been developed and network infrastructures with high capabilities have been designed to deal with the data collection problem, there are still application scenarios, in which network infrastructure is not available or appropriate in large target areas (e.g., farmlands deployed with IoT sensors in operation, providing precise agriculture; emergency responder with IoT sensors, providing public safety service). To address the issue of efficiently collecting data from IoT devices deployed in large areas without predeployed network infrastructure, we formalize the problem space in a three-dimensional model that considers task, resource, and methodology. Based on the designed problem space, we propose a novel solution that deploys an unmanned aerial vehicle (UAV), as a critical next generation mobile network, to achieve intermittent IoT device connections and enable data collection based on delay tolerant network (DTN) protocol. The UAV flight path is determined using a Hilbert Curve-based path planning algorithm. Through a series of quantitative experiments, we validate the effectiveness of our approach in a network emulation environment, and confirm its advantages in comparison with several baseline approaches. The results of our research shows the capability of quality and cost control in IoT applications such as smart agriculture, public safety disaster recovery and rescue. INDEX TERMS Internet of Things, delay tolerant networks, next generation mobile networks, unmanned aerial vehicles, path planning, data collection.

show abstract