A smart campus is an intelligent infrastructure where smart sensors and actuators collaborate to collect information and interact with the machines, tools, and users of a university campus. As in a smart city, a smart campus represents a challenging scenario for Internet of Things (IoT) networks, especially in terms of cost, coverage, availability, latency, power consumption, and scalability. The technologies employed so far to cope with such a scenario are not yet able to manage simultaneously all the previously mentioned demanding requirements. Nevertheless, recent paradigms such as fog computing, which extends cloud computing to the edge of a network, make possible low-latency and location-aware IoT applications. Moreover, technologies such as Low-Power Wide-Area Networks (LPWANs) have emerged as a promising solution to provide low-cost and low-power consumption connectivity to nodes spread throughout a wide area. Specifically, the Long-Range Wide-Area Network (LoRaWAN) standard is one of the most recent developments, receiving attention both from industry and academia. In this article, the use of a LoRaWAN fog computing-based architecture is proposed for providing connectivity to IoT nodes deployed in a campus of the University of A Coruna (UDC), Spain. To validate the proposed system, the smart campus has been recreated realistically through an in-house developed 3D Ray-Launching radio-planning simulator that is able to take into consideration even small details, such as traffic lights, vehicles, people, buildings, urban furniture, or vegetation. The developed tool can provide accurate radio propagation estimations within the smart campus scenario in terms of coverage, capacity, and energy efficiency of the network. The results obtained with the planning simulator can then be compared with empirical measurements to assess the operating conditions and the system accuracy. Specifically, this article presents experiments that show the accurate results obtained by the planning simulator in the largest scenario ever built for it (a campus that covers an area of 26,000 m 2 ), which are corroborated with empirical measurements. Then, how the tool can be used to design the deployment of LoRaWAN infrastructure for three smart campus outdoor applications is explained: a mobility pattern detection system, a smart irrigation solution, and a smart traffic-monitoring deployment. Consequently, the presented results provide guidelines to smart campus designers and developers, and for easing LoRaWAN network deployment and research in other smart campuses and large environments such as smart cities.

Design and Experimental Validation of a LoRaWAN Fog Computing Based Architecture for IoT Enabled Smart Campus Applications

This work was supported in part by the 2017 Predoctoral Research Grant through the Xunta de Galicia and the Research Projects funded by the Ministerio de Ciencia, Innovacion y Universidades, Gobierno de Espana through Ministerio de Ciencia, Innovacion y Universidades (MCIU)/Agencia Estatal de Investigacion (AEI)/Fondo Europeo de Desarrollo Regional (FEDER)/Union Europea (UE) under Grant TEC2017-85529-C03-3R and Grant RTI2018-095499-B-C31, and in part by the European Union’s Horizon 2020 Research and Innovation Program (Stardust-Holistic and Integrated Urban Model for Smart Cities) under Grant N◦774094.

/pdf/aggregator-to-electric-vehicle-lorawan-based-communication-58jmwwavtg.pdf

Aggregator to electric vehicle LoRaWAN based communication analysis in vehicle-to-grid systems in smart cities

Transportation system is experiencing steady growth, with the aim of providing more efficient, reliable, and comfortable services, in the framework of intelligent transportation systems. Moreover, context aware environments are one of the main drivers in the achievement of smart cities and smart regions. In this paper, wireless sensor networks (WSNs) embedded in urban transportation systems will be analyzed in terms of impact on wireless channel behavior and system performance. An in-house developed 3-D ray launching tool, with the inclusion of in-house human body model as well as with the study of interference levels is employed. Wireless channel estimations indicate an initial infrastructure node density in the order of 1node/150m2 to 1node/500m2 as a function of the employed transceivers. A practical solution has been implemented, combining an Android-based application and a system level architecture over the WSN for urban train transportation environmental monitoring, providing interaction between users and the environment, with the aid of a combined WSN/WLAN platform as well as an implemented software architecture, scalable in terms of user density and future needs.

Design and Implementation of Context Aware Applications With Wireless Sensor Network Support in Urban Train Transportation Environments

Simulation techniques based on deterministic methods such as ray tracing and ray launching are widely used to perform radioplanning tasks. However, the quality of the simulations depends on the number of rays and the angular resolution. The computational cost of these simulations in high definition prevents their use in complex environment, and their low-definition counterparts are used instead. In this letter, we propose a technique based on collaborative filtering to lessen the poor-quality problems of low-definition simulations. We show that our approach obtains results very similar to those of high definition in much less time. Also, we compare our approach to other well-known techniques and show that it performs better in terms of accuracy and precision. The use of combined deterministic/collaborative filtering techniques allows the estimation of radioplanning tasks in large, complex scenarios with a potentially large amount of transceivers.

Optimized Wireless Channel Characterization in Large Complex Environments by Hybrid Ray Launching-Collaborative Filtering Approach

A novel and efficient deterministic approach to model radiowave propagation channels in complex indoor environments, improving prediction accuracy, is proposed. This technique combines a three-dimensional ray launching algorithm based on geometrical optics with a diffusion equation method based on the equation of transfer. A comparison between the geometrical optics-only approach and the new method considering the diffusion equation has been presented for studying indoor radiowave propagation. The geometrical optics–diffusion equation method achieves better agreement with measurements, while resulting in high computational efficiency, with approximately 40% savings in simulation time.

A Hybrid Ray Launching-Diffusion Equation Approach for Propagation Prediction in Complex Indoor Environments

In this paper, a convergence analysis to obtain the optimal calculation parameters in an inhouse 3D ray launching algorithm to model the radio wave propagation channel in complex indoor environments is presented. Results show that these parameters lead to accurate estimations with reduced computational time. In addition, simulation results of an indoor complex scenario in terms of received power and power delay profile are presented, showing significant influence of multipath propagation in an indoor radio channel. The adequate election of simulation parameters given by convergence conditions, can aid in optimizing required computational time.

Convergence Analysis in Deterministic 3D Ray Launching Radio Channel Estimation in Complex Environments

Handle everyday research tasks with reliable, citation-backed results

Your personal Research Agent to handle research tasks with citation-backed results

Popular Tasks used by Researchers

How can I help with your research?

Meet SciSpace

Get more enhanced response by uploading the PDFs you want me to reference.

No relevant PDFs in your library

SciSpace is the AI research assistant for academics. Run systematic literature reviews on 280M+ papers, and write papers with cited sources. Trusted by 1M+ students, PhDs & researchers.

SciSpace | AI for Research

Analyze PDFs

Code & Manuscripts

Funding & Grants

Literature & Patents

Medical & Clinical Data

Systematic Review

Visualize & Present

Web & Data

Build a Google Scholar-like website for your research.

Build a website

Create charts and images for your research

Create a Chart

Write a paper for submission to a journal

Draft a manuscript

Patent Search

Design eye-catching scientific posters in minutes.

Scientific Poster Generation

Systematic Literature Review

One task is running at the moment. Your messages will be shown right after.

Drag and drop or click here to browse

Loved by <highlight>1 million+</highlight> researchers

Extract a list of specific topics and their sources from unstructured text

Topics

Compare and analyze relevant papers that matches with your search

Papers

Get insights from PDFs and bookmarked papers from your library

My library

Recent searches

Try searching for:

Catch AI-generated content in scholarly and non-scholarly content

{ai} Detector

Ai Writer

Get PDF Summaries, highlighted text explanations 

Chat with PDF

Effortlessly create in-text citations and bibliographies in APA and 2,500 other formats

Citation generator

Get explanations, summaries, and answers on academic papers

Ease up your research workflow with {scispace}'s cohort of exciting AI tools

Elevate your academic writing skills and convey your ideas the way you want

Paraphraser

Explore our range of reading and writing tools

Your file is being prepared and should be ready in a few minutes. If it's a large file, it might take a bit longer. You can close this window, and we'll email you the file when it's done.

You have reached a maximum limit of <strong>{limit}</strong> columns in the table. Remove at least <strong>1</strong> column to add or create another one.

Y. Li

Author Tools

Chat about Author

Papers

Convergence Analysis in Deterministic 3D Ray Launching Radio Channel Estimation in Complex Environments