Author
Listed:
- Felipe Pinheiro Correia
(Graduate Program in Electrical Engineering, Department of Electrical and Computer Engineering, Federal University of Bahia (UFBA), Salvador 40210-630, Brazil
Federal Institute of Education, Science and Technology of Sertão Pernambucano (IF Sertão PE), Petrolina 56316-686, Brazil)
- Samara Ruthielle da Silva
(Graduate Program in Electrical Engineering, Department of Electrical Engineering, Federal University of Paraíba (UFPB), João Pessoa 58051-900, Brazil)
- Fabricio Braga Soares de Carvalho
(Graduate Program in Electrical Engineering, Department of Electrical Engineering, Federal University of Paraíba (UFPB), João Pessoa 58051-900, Brazil)
- Marcelo Sampaio de Alencar
(Graduate Program in Electrical Engineering, Department of Electrical and Computer Engineering, Federal University of Bahia (UFBA), Salvador 40210-630, Brazil)
- Karcius Day Rosario Assis
(Graduate Program in Electrical Engineering, Department of Electrical and Computer Engineering, Federal University of Bahia (UFBA), Salvador 40210-630, Brazil)
- Rodrigo Moreira Bacurau
(Department of Computational Mechanics (DMC), School of Mechanical Engineering (FEM), State University of Campinas (UNICAMP), Campinas 13083-860, Brazil)
Abstract
The use of Wireless Sensor Networks (WSN) in smart agriculture has emerged in recent years. LoRaWAN (Long Range Wide Area Networks) is widely recognized as one of the most suitable technologies for this application, due to its capacity to transmit data over long distances while consuming little energy. Determining the number and location of gateways (GWs) in a production setting is one of the most challenging tasks of planning and building this type of network. Various solutions to the LoRaWAN gateway placement problem have been proposed in the literature, utilizing clustering algorithms; however, few works have compared the performance of various strategies. Considering all these facts, this paper proposes a strategy for planning the number and localization of LoRaWAN GWs, to cover a vast agricultural region. Four clustering algorithms were used to deploy the network GWs: K-Means and its three versions: Minibatch K-Means; Bisecting K-Means; and Fuzzy c-Means (FCM). As performance metrics, uplink delivery rate (ULDR) and energy consumption were used, to provide subsidies for the network designer and the client, with which to choose the best setup. A stochastic energy model was used to evaluate power consumption. Simulations were performed, considering two scenarios: Scenario 1 with lower-medium concurrence, and Scenario 2 with higher-medium concurrence. The simulations showed that the use of more than two GWs in Scenario 1 did not lead to significant improvements in ULDR and energy consumption, whereas, in Scenario 2, the suggested number of GWs was between 11 and 15. The results showed that for Scenario 1, the FCM algorithm was superior to all alternatives, regarding the ULDR and mean energy consumption, while the K-Means algorithm was superior with respect to maximum energy consumption. In relation to Scenario 2, K-Means caused the best ULDR and mean consumption, while FCM produced the lowest maximum consumption.
Suggested Citation
Felipe Pinheiro Correia & Samara Ruthielle da Silva & Fabricio Braga Soares de Carvalho & Marcelo Sampaio de Alencar & Karcius Day Rosario Assis & Rodrigo Moreira Bacurau, 2023.
"LoRaWAN Gateway Placement in Smart Agriculture: An Analysis of Clustering Algorithms and Performance Metrics,"
Energies, MDPI, vol. 16(5), pages 1-21, March.
Handle:
RePEc:gam:jeners:v:16:y:2023:i:5:p:2356-:d:1084725
Download full text from publisher
References listed on IDEAS
- Geovanny Yascaribay & Mónica Huerta & Miguel Silva & Roger Clotet, 2022.
"Performance Evaluation of Communication Systems Used for Internet of Things in Agriculture,"
Agriculture, MDPI, vol. 12(6), pages 1-22, May.
- Douglas de Farias Medeiros & Cleonilson Protasio de Souza & Fabricio Braga Soares de Carvalho & Waslon Terllizzie Araújo Lopes, 2022.
"Energy-Saving Routing Protocols for Smart Cities,"
Energies, MDPI, vol. 15(19), pages 1-19, October.
Full references (including those not matched with items on IDEAS)
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.
- Anna Jasińska-Biliczak, 2022.
"Smart-City Citizen Engagement: The Answer to Energy Savings in an Economic Crisis?,"
Energies, MDPI, vol. 15(23), pages 1-15, November.
- Gniewko Niedbała & Sebastian Kujawa, 2023.
"Digital Innovations in Agriculture,"
Agriculture, MDPI, vol. 13(9), pages 1-10, August.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:16:y:2023:i:5:p:2356-:d:1084725. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.