[image] [image] Ressource protégée - Inria - Institut national de recherche en sciences et technologies du numérique **Accéder directement au contenu**

[image] [image]

* Documentation

* FR
  Français (FR)

* Anglais (EN)
  Se connecter

* Portail HAL Inria

* Recherche
  Loading...

## Recherche avancée

Information de documents

Titres

○ Titres

○ Sous-titre

○ Titre de l'ouvrage

○ Titre du volume (Série)

○ Champ de recherche par défaut (multicritères) + texte intégral des PDF

○ Résumé

○ Texte intégral indexé des documents PDF

○ Mots-clés

○ Type de document

○ Sous-type de document

○ Tous les identifiants du document

○ Identifiant HAL du dépôt

○ Langue du document (texte)

○ Pays (Texte)

○ Ville

○ À paraître (true ou false)

Ajouter
<figure><img src="image_1.png" /></figure>

ifip

International Federation for Information Processing

This document is the original author manuscript of a paper submitted to an IFIP
conference proceedings or other IFIP publication by Springer Nature. As such, there
may be some differences in the official published version of the paper. Such
differences, if any, are usually due to reformatting during preparation for publication or
minor corrections made by the author(s) during final proofreading of the publication
manuscript.
## Auteur

### Auteur (multicritères)

○ Auteur (multicritères)

○ Auteur : Nom complet

○ Auteur : Nom de famille

○ Auteur : Prénom

○ Auteur : Complément de nom, deuxième prénom

○ Auteur : Organisme payeur

○ Auteur : IdHal (chaîne de caractères)

○ Auteur : Fonction

○ Auteur : personID (entier)

○ Auteur : Identifiant de l'organisme payeur

○ Auteur : Identifiant de la structure

○ Directeur de thèse

○ Éditeur

○ Éditeur scientifique

○ Éditeur de la série

## Ajouter

### Structure

#### Structure (multicritères)

○ Structure (multicritères)

○ Structure : Acronyme

○ Structure : Nom

○ Structure : Code

○ Structure : Pays

○ Structure : Type

○ Structure : État dans le référentiel

○ Structure : Identifiant HAL de la structure

○ Structure/équipe de recherche : Pays

○ Structure/regroupement d'équipes : Pays

○ Structure/laboratoire : Pays

○ Structure/regroupement de laboratoires : Pays

○ Structure/institution : Pays

○ Structure/regroupement d'institutions : Pays

## Ajouter
# A study on small sensor node antenna performance camouflaged under grassland fire

Tiago E. S. Oliveira¹,², Mário Vala¹,³ Stefânia Faria¹,², João R. Reis¹,², Nuno Leonor¹,², and Rafael F. S. Caldeirinha¹,²

¹ Instituto de Telecomunicações, Leiria, Portugal

² Politécnico de Leiria, Leiria, Portugal

³ Instituto Superior Técnico, University of Lisbon, Lisbon, Portugal

**Abstract.** In this paper, the impact of vegetation and fire on the radiation pattern of a small antenna to be used in a WSN sensor node, is studied. The proposed antenna used in this study is based on a differential patch design, tuned to operate in the 2.4 GHz frequency band. The antenna presents a reduced size of 45 x 45 mm² (0.36λ x 0.36λ). The simulations were carried using a full-wave EM solver (CST MWS) considering four different scenarios: the first scenario only containing the antenna placed on the ground to serve as reference; in the second scenario vegetation was introduced to serve as the “normal” state of the terrain surrounding the sensor node; the third scenario includes the impact of surrounding fire considering the permittivity expected during such an event; and the last simulation was performed to include all the previous components simultaneously.

**Keywords:** Sensor node, patch antenna, grassland, wildfire.

## 1 Introduction

Wildfires are the uncontrolled fires that spread in non-urban areas. Their destructive potential may result in fatalities and loss of properties and natural landscape [1]. The consequences are, often, irreversible damages to the atmosphere and environment. Some examples such as the Dwellingup (1961) and Lara (1969) wildfires in Australia [2], the 2017 tragic wildfire episode in Portugal [3] and also the seasonal wildfires in California have demonstrated the fragility of keeping large grassland and forest areas without remote monitoring.

According to government records, 84% of all wildfires from 1992 to 2012 were human-induced in the United States [4] and this statistic is even higher for fires in Europe, which reaches 95% [5]. The necessity of a comprehensive system providing real-time information from extensive vegetation areas has become crucial. Detecting a fire in its early stages contributes to a faster reaction from the fire fighters and thus a better control over the wild fire, preventing a the spread of devastation.

Wireless Sensor Networks (WSNs) are commonly proposed in the literature as a solution for an early stage fire-detection system implementation [6–8]. A
Autres

Champ de recherche par défaut (multicritères)

○ Champ de recherche par défaut (multicritères)

○

○ Revues (multicritères)

○ Revue : Éditeur

○ Revue : Titre abrégé

○ Revue : Titre

○ Revue : Identifiant interne

○ Revue : Date de début de publication

○ Revue : ISSN électronique

○ Revue : ISSN

○ Revue : Éditeur

○ Revue : Couleur dans SHERPA/RoMEO

○ Revue : État dans le référentiel

○

○ Colloque (multicritères)

○ Colloque : Titre

○ Colloque : Organisateur

○ Colloque : date de début (Année)

○ Colloque : date de fin (Année)

○ Conférence invitée (oui/non)

○

○ Projets ANR (multicritères)

○ Projet ANR : Acronyme

○ Projet ANR : Acronyme du programme

○ Projet ANR : Code décision (référence)

○ Projet ANR : Nom

○ Projet ANR : Identifiant interne

○ Projet ANR : État dans le référentiel

○

○ Projets européens (multicritères)

○ Projet européen : Acronyme

○ Projet européen : Identifiant de l'appel à projet

○ Projet européen : Référence

○ Projet européen : Nom

○ Projet européen : Date de fin

○ Projet européen : Financement

○ Projet européen : Date de début
WSN is typically composed of one or more Base Stations (BS) and multiple
Sensor Nodes (SN), being that the SNs have the task to retrieve data from
the environment and send it to the BS, where it is stored to be processed and
analysed [9,10]. Thus, SN which employ fire or smoke detection capabilities [11]
can be used to create a fire-detection system that covers a wide vegetation area.

To build a robust detection network, particularly for early fire detection, WSN networks benefit from having several sensor nodes scattered in large natural areas, e.g. large portions of forest, with the purpose of environmental monitoring. Therefore, it is desirable that SN are as compact and concealed as possible, with small form factors, to reduce the visual impact when deployed in the field, in large scale. Thus, to maintain the small size of the SN, the antenna size is an important factor to have in consideration at the design stage, particularly if relatively high gain antennas (>3 dBi) are required. In [12], the authors have already presented a slotted differential patch antenna operating at 2.4 GHz ISM band for SN usage which utilises the ground plane as shielding for possible electromagnetic noise produced from the circuitry.

The existence of heavy fire plumes as a result from overall combustion of veg-
etation will change the dielectric properties of the media around the antenna,
as studied in [13], leading to changes in the effective permittivity and possible
degradation of the antenna performance, which may affect antenna impedance
matching and the shape of the radiation pattern. To this extent, the work pre-
sented herein aims at the study of the effects of both the environment (soil and
undergrowth) and the fire in the overall performance of an antenna specially
designed to be used in a sensor node.

This paper is organised as follows: in section 2 the antenna used in this study is presented, where its standalone performance is evaluated; in section 3 the results of the simulations carried out are presented for four different scenarios, that allow to draw conclusions of the enveloping environment effects on the radiation pattern of the antenna. Lastly, in section 5, the main conclusions of this work are presented, as well as some directives to future work.

## 2 Sensor node antenna

The SN antenna being used in this study was firstly presented by the authors in [14] and further optimised by the authors in [12]. This differential antenna was designed to meet specific project requirements, namely to be utilised in a differential RF system set by the sensor node radio front-end architecture. The system that employ an output differential RF signal on the radio frequency system-on-chip (RF SoC) benefit from the intrinsic suppression of the common mode current [15] eliminating the need of Integrated Circuitry (ICs) for filtering processes, leading to an overall reduction of the sensor nodes size.

The proposed antenna, depicted in Fig. 1, is based on a differential microstrip patch using etched resonating slots to reduce the overall size of the patch. Moreover, two circular slots were added around the feeding points that ensure an input impedance of 100 Ω [12]. A great advantage of this design relies in the ground
○ Projet européen : État dans le référentiel

○ Projet européen : Identifiant interne

○

○ Date de production : année

○ Date de mise en ligne : année

○ Date de publication : année

○ Date d'écriture : année

○ Date de modification du dépôt : année

○ Date de dépôt : année

○ Date de publication électronique : année

○

○ Collection HAL (multicritères)

○ Collection HAL : catégorie

○ Collection HAL : Code

○ Collection HAL : Nom

○ Collection HAL : Identifiant interne

○

○ Identifiant interne du contributeur/déposant

○ Nom complet du contributeur/déposant

○

○ Domaines

○ Domaine primaire

○ Domaine racine

○ Sous-domaine niveau 1

○ Sous-domaine niveau 2

○ Sous-domaine niveau 3

○

○ Statut du document

○ Version du document

○ Type de dépôt

○ Type de document

○ ISBN

○ Numéro - référence

○ Identifiant DOI

○

○ Classification

○ Audience

○ Vulgarisation

○ Comité de lecture - texte (oui ou non)

○ Actes de colloque
<figure><img src="image_2.png" /><figcaption>Fig. 1: Final antenna design: (a) top view, (b) bottom view, (c) balun design and (d) differential patch antenna coupled to balun.</figcaption></figure>

plane which provide shielding from possible electromagnetic noise produced by the circuitry present in the SN.

The optimised antenna design [12] has dimensions of 45 x 45 mm², operating at 2.4 GHz, with 160 MHz of bandwidth, with 5.1 dBi of a gain. The final layout (top and bottom) of the antenna can be observed in Figs. 1a 1b, respectively.

For simulation purposes the antenna was coupled to a balun which is composed by a quarter-wave transformer and a 180° phase shifter, as shown in Fig. 1c. The balun was incorporated in these simulations in order to have a differential signal as the input of the antenna when considering only one input port. This configuration (presented in Fig.1d) allows the analysis of some antenna parameters that could not be obtained while using only the antenna (e.g. $S_{11}$). However, as mentioned before, the antenna is thought to be coupled to a differential RF SoC when implemented in a real scenario. Both the antenna and balun were designed using a double sided FR-4 substrate, with $ε_r$ = 4.4 and $tan(δ)$ = 0.014.

According to the simulations depicted in Fig. 2a, it is possible to observe a $S_{11}$<-10 dB, between 2.36 and 2.51 GHz, i.e. 160 MHz of bandwidth (6.7% of centre frequency). At the centre frequency, the antenna presents a realised gain of 5.1 dBi, with a broadside radiation pattern, characterised by having 79° and 100° of Half-Power Beamwidth (HPBW), in the main antenna planes, as shown in Fig.2b.
○ Référence interne

○ Financement

○ Collaborations

Ajouter

Lancer la recherche

Recherche experte (SolR)

Recherche experte (SolR)

Lancer la recherche
Vers la recherche avancée

• Déposer

Portail INRIA.HAL.SCIENCE
Les publications, logiciels... des scientifiques Inria

• Accueil

• Publications Inria

○ Consulter les derniers dépôts

○ Par équipe de recherche

○ Par auteur

○ Rapports de recherche et techniques

○ Livres blancs

○ Rapports d'activité des équipes

○ Statistiques

• Boite à Outils

○ X2Hal : importer par lot

○ Logiciels : créer le Codemeta.json

○ Créer mon IDHal

○ Créer mon CVHal

○ Haltools : créer ma page de publications

○ Haltools : extraire des données (réservé Inria)

○ Les bonnes pratiques

■ Comment bien s'affilier ?
<figure><img src="image_3.png" /><figcaption>Fig. 2: Antenna (a) $S_{11}$, (b) radiation pattern (on azimuth and elevation planes) and (c) 3D representation of the radiation pattern.</figcaption></figure>

## 3 Scenario definition and case studies

Following the full characterisation of the antenna, the next step was to start building the simulation environment to be as close to reality as possible in the event of the start of a wildfire in the vicinity of the antenna.

The first simulation performed was when the forest soil was considered below the antenna. For this simulation a 50 x 50 cm² (4λ x 4λ) square with a depth of 20 cm, being the antenna placed 5 mm above the centre, as shown in Fig. 3a. The material used for the soil already existed in CST Material Library as *Loamy Soil* (*wet*), presenting an $ε_r$ = 13.8 and $tan(δ)$ = 0.18. These dimensions are thought to be enough since only the elements near the antenna will have a significant impact on its radiation pattern.

Following this simulation, a layer of vegetation was added above the soil and surrounding the antenna. A 3D model of tall grass was used as depicted in
* Quelle version puis-je déposer ?

* Choisir le bon « type de document »

* Mettre en valeur ses publications

○ Les tutos IES Inria

* Lier les notices dans HAL

* Umbrhal Inria pour l'accessibilité

* Personnaliser son CVHAL

* Créer et Personnaliser sa collection

• Documentation

○ Aide en ligne HAL

○ Aide en ligne Haltools

○ Aide en ligne X2hal

○ Tutoriels video HAL

○ Documentation API HAL

○ Ajouter des vignettes

○ Identifiant auteur IdHAL et CV

○ Compléter son dossier ORCID avec ses dépôts HAL

○ Inria et la Science Ouverte

X

X

X

Loading...

X

Le document que vous demandez est en access restreint
jusqu'au 2025-01-01 !

Revenir a la notice

Retourner à l'accueil

Contact

•

Ressources
Fig. 3b. The dielectric properties were taken from [16] for a moisture content of 45%, where $ε_r = 10$ and $tan(δ) = 0.4$ were considered for simulation purposes.

Lastly, fire was introduced in the simulation to ascertain how it would impact the antenna performance. In order to obtain the dielectric characteristics of fire, another simulation tool, Fire Dynamic Simulator (FDS), which is a computational fluid dynamics solver released by the National Institute of Standards and Technology (NIST) [17], was used. In FDS it is possible to realistically simulate a fire environment and obtain some parameters such as gas densities and temperature profiles. In post-processing, from this data, it is possible to obtain the electron density and collision frequency that can subsequently be used to calculate the permittivity, as described in [3]. The fuel and burner characteristics were introduced and temperature and density profiles of the environment were extracted in order to calculate the electrical permittivity in a fire region [18]. Even though the fire is a turbulent media, characterised by fast and random variations (fire plumes) overtime, for simulation purposes only a single frame (single time instant) has been considered. For such frame, several permittivities and conductivities ranging from air characteristics $ε_r = 1$ and $tan(δ) = 0$ to $ε_r = 0.9535$ and $tan(δ) = 0.1343$ were obtained in FDS software and imported to CST, resulting in the 3D scenario presented in Fig. 3c.

## 4 Simulation results and discussion

In each one of the scenarios described above, both the $S_{11}$ and radiation pattern of the antenna were analysed to infer how these would be affected with the presence of the soil, vegetation and fire, individually.

The simulated $S_{11}$ is depicted in Fig. 4. From the results, it can be seen that by adding the soil to the simulation, a degradation of 1.7 dB (from -23.3 dB to -21.6 dB) in antenna matching is observed. On the other hand, when vegetation is considered, the $S_{11}$ almost remains unchanged. However, when the fire is taken into consideration, the $S_{11}$ value decreases to -18 dB, presenting a difference of 5 dB from the case with only the antenna. This indicates that the fire has a significant impact in the antenna performance. Lastly, for the complete scenario, there is not a large difference in the $S_{11}$ when compared to the previous set of simulations.

In terms of the radiation pattern of the antenna in its main planes, i.e. azimuth and elevation, there are also some differences for the various scenarios, as shown in Fig. 5. Note that to match the coordinate system of the simulation (CST MWS) the boresight direction is set to +90° in azimuth and elevation. The first and most visible difference occurs when the soil is introduced in the model. Due to high $ε_r$ and $tan(δ)$ of the material considered, the back lobe is severely attenuated (with consequent front to back lobe level enhancement), also verifying a small decrease in gain of 0.6 dB, i.e. from 5.1 to 4.49 dBi. Moreover, it can also be noticed a decrease in the realised gain of around 2 dB, when vegetation is included in the simulation model. For this particular case, it can also be seen a slight deformation in the shape of the radiation pattern, also visible in the 3D
• Documentation

• FAQ

• API

• OAI-PMH

• AuréHAL

## Informations

• À propos

• Données personnelles

• Mentions légales

• Accessibilité

• Conformité RGAA

## Questions juridiques

• Je publie, quels sont mes droits ?

• Loi pour une République numérique

• Stratégie de non-cession des droits

• SHERPA/RoMEO

## Portails

• Portails institutionnels

• HAL

• HAL SHS

• HAL Thèses

• MédiHAL

## CCSD

• CCSD

• Episciences

• Sciencesconf
<figure><img src="image_4.png" /><figcaption>Fig. 3: CST simulation environments: (a) soil only, (b) grass, (c) fire and (d) full scenario.</figcaption></figure>

radiation patterns of Fig. 6. The simulation with fire also resulted in a decrease in the gain of around 0.8 dB, when comparing with the radiation pattern of Fig. 2. Lastly, with the scenario containing both vegetation and fire, the antenna gain decreases from 5.1 to 3.01 dBi (a difference of 2.1 dB). These results show that the fire still has an impact on the gain of the antenna even when vegetation is present. However, the decrease observed in the full scenario is smaller than that of the superposition of the vegetation and fire scenarios (Figs. 6b and 6c), due to the overlapping of the fire with the vegetation.

# 5 Conclusions

This paper presents the impact of grassland fire in the performance of a Sensor node antenna for wireless sensing networks. Firstly, a small antenna designed
<figure><img src="image_5.png" /><figcaption>Fig. 4: Antenna $S_{11}$ for all scenarios considered.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Fig. 5: Antenna radiation patterns for the different scenarios: (a) azimuth and (b) elevation.</figcaption></figure>

to be used in a sensor node operating in the 2.4 GHz frequency band, was presented. Based on previous work conducted by the authors, the antenna presents a realised gain of 5.1 dBi over a band of operation of 160 MHz (6.7% of central frequency).

This antenna was then involved by soil, vegetation and fire, approximating the model to a real case scenario of a wildfire. A study for each of the identified parameters was performed by simulation, to ascertain the impact of each model component in antenna performance. From the simulation results, it was observed that all these factors have impact in the performance of the antenna, deteriorating both the $S_{11}$ and the radiation pattern. For a small area of simulation of
<figure><img src="image_7.png" /><figcaption>Fig. 6: 3D radiation patterns: (a) soil only, (b) grass, (c) fire and (d) full scenario.</figcaption></figure>

50 x 50 cm² and considering only a single frame of a propagation fire, a decrease up to 2 dB of the maximum antenna gain was observed. This attenuation however is expected to be higher if considering larger combustion scenarios or taller grass which automatically generate higher fire plumes.

Future work will address further simulations with different vegetation densities and types, different time instants of fire, as well as an increase in the overall simulation environment size in order to ascertain at which distance the surroundings of the antenna will not have an important impact on its performance. The antenna prototyping and its testing in a real scenario is also thought to be done in the near future.

## Acknowledgments

This research was partially supported by FCT under the projects WSN-EM (PTDC/EEI-EEE/30539/2017), RESCuE-TOOL (PCIF/SSI/0194/2017) and by
FCT/MCTES through national funds and when applicable, co-funded EU funds
under the project UID/EEA/50008/2021.

References

1. J. Minas, J. Hearne, and J. Handmer, "A review of operations research methods applicable to wildfire management," *International Journal of Wildland Fire*, vol. 21, pp. 189-196, 02 2012.

2. K. M. Mphale, “Radiowave propagation measurements and prediction in bushfires,” Ph.D. dissertation, School of Mathematical and Physical Sciences - James Cook University, 2008.

3. S. S. Faria, N. Leonor, C. A. Fernandes, J. Felicio, C. Salema, and R. F. S. Caldeirinha, “Radiowave propagation modelling in the presence of wildfires: Initial results,” in *2020 14th European Conference on Antennas and Propagation (EuCAP)*. IEEE, mar 2020.

4. J. Balch, B. Bradley, J. Abatzoglou, C. Nagy, E. Fusco, and A. Mahood, “Human-started wildfires expand the fire niche across the united states,” *Proceedings of the National Academy of Sciences*, vol. 114, p. 201617394, 02 2017.

5. J. San-Miguel-Ayanz, E. Schulte, G. Schmuck, A. Camia, P. Strobl, G. Libertà, C. Giovando, R. Boca, F. Sedano, P. Kempeneers, D. McInerney, C. Withmore, S. Oliveira, M. Rodrigues, T. Durrant, P. Corti, F. Oehler, L. Vilar, and G. Amatulli, *Comprehensive Monitoring of Wildfires in Europe: The European Forest Fire Information System (EFFIS)*, 03 2012.

6. V. Sittakul, S. Pasakawee, and C. Jan-im, "Wireless sensor network for wildfire detection and notification via walkie - talkie network," in *2019 16th International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON)*. IEEE, jul 2019.

7. S. Verma, S. Kaur, D. B. Rawat, C. Xi, L. T. Alex, and N. Z. Jhanjhi, "Intelligent framework using IoT-based WSNs for wildfire detection," *IEEE Access*, vol. 9, pp. 48 185-48 196, 2021.

8. Z. Ateeq and M. Momani, "Wireless sensor networks using image processing for fire detection," in *2020 5th International Conference on Innovative Technologies in Intelligent Systems and Industrial Applications (CITISIA)*. IEEE, nov 2020.

9. M. Assim and A. Al-Omary, “Design and implementation of smart home using WSN and IoT technologies,” in *2020 International Conference on Innovation and Intelligence for Informatics, Computing and Technologies (3ICT)*. IEEE, dec 2020.

10. Ekoprayitno, N. Fahmi, M. U. H. A. Rasyid, and A. Sudarsono, “Smart environment: Accuracy of a server side model in design topology WSN and IoT,” in *2019 International Electronics Symposium (IES)*. IEEE, sep 2019.

11. A. Gaur, A. Singh, A. Kumar, K. S. Kulkarni, S. Lala, K. Kapoor, V. Srivastava, A. Kumar, and S. C. Mukhopadhyay, "Fire sensing technologies: A review," *IEEE Sensors Journal*, vol. 19, no. 9, pp. 3191-3202, may 2019.

12. Tiago E. S. Oliveira, João R. Reis, Mário Vala, Rafael F. S. Caldeirinha, “High Performance Antennas for Early Fire Detection Wireless Sensor Networks at 2.4 GHz,” in *10th IEEE-APS Topical Conference on Antennas and Propagation in Wireless Communications APWC*, Aug. 2021.

13. S. Faria, M. Vala, P. Coimbra, J. Felicio, N. Leonor, C. Fernandes, C. Salema, and R. Caldeirinha, “Analytical studies of refractive index variation in pine needles
media under wildfire conditions,” in *2021 15th European Conference on Antennas and Propagation (EuCAP)*. IEEE, mar 2021.

14. S.-J. Wang, L. Li, and M. Fang, “A NOVEL COMPACT DIFFERENTIAL MICROSTRIP ANTENNA,” *Progress In Electromagnetics Research Letters*, vol. 57, pp. 97–101, 2015.

15. R. Bourtoutian, C. Delaveaud, and S. Toutain, “Differential antenna design and characterization,” in *2009 3rd European Conference on Antennas and Propagation*, 2009, pp. 2398–2402.

16. B. L. Shrestha, H. C. Wood, and S. Sokhansanj, “Modeling of vegetation permit-tivity at microwave frequencies,” *IEEE Transactions on Geoscience and Remote Sensing*, vol. 45, no. 2, pp. 342–348, feb 2007.

17. K. McGrattan, R. McDermott, S. Hostikka, J. Floyd, and M. Vanella, *Fire Dynamics Simulator*, sixth edition ed., 2018.

18. K. Mphale and M. Heron, “Plant alkali content and radio wave communication efficiency in high intensity savanna wildfires,” *Journal of Atmospheric and Solar-Terrestrial Physics*, vol. 69, p. 471–484, 04 2007.