FloatingBlue: A Delay Tolerant Networks-Enabled Internet of Things Architecture for Remote Areas Combining Data Mules and Low Power Communications
Monitoring vast and remote areas like forests using Wireless Sensor Networks (WSNs) presents significant challenges, such as limited energy resources and signal attenuation over long distances due to natural obstacles. Traditional solutions often require extensive infrastructure, which is impractica...
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MDPI AG
2024-09-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/24/19/6218 |
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| author | Ruan C. M. Teixeira Celso B. Carvalho Carlos T. Calafate Edjair Mota Rubens A. Fernandes Andre L. Printes Lennon B. F. Nascimento |
| author_facet | Ruan C. M. Teixeira Celso B. Carvalho Carlos T. Calafate Edjair Mota Rubens A. Fernandes Andre L. Printes Lennon B. F. Nascimento |
| author_sort | Ruan C. M. Teixeira |
| collection | DOAJ |
| description | Monitoring vast and remote areas like forests using Wireless Sensor Networks (WSNs) presents significant challenges, such as limited energy resources and signal attenuation over long distances due to natural obstacles. Traditional solutions often require extensive infrastructure, which is impractical in such environments. To address these limitations, we introduce the “FloatingBlue” architecture. This architecture, known for its superior energy efficiency, combines Bluetooth Low Energy (BLE) technology with Delay Tolerant Networks (DTN) and data mules. It leverages BLE’s low power consumption for energy-efficient sensor broadcasts while utilizing DTN-enabled data mules to collect data from dispersed sensors without constant network connectivity. Deployed in a remote agricultural area in the Amazon region, “FloatingBlue” demonstrated significant improvements in energy efficiency and communication range, with a high Packet Delivery Ratio (PDR). The developed BLE beacon sensor achieved state-of-the-art energy consumption levels, using only 2.25 µJ in sleep mode and 11.8 µJ in transmission mode. Our results highlight “FloatingBlue” as a robust, low-power solution for remote monitoring in challenging environments, offering an energy-efficient and scalable alternative to traditional WSN approaches. |
| format | Article |
| id | doaj-art-993d4522a6b549f0b5b13073975fa3b8 |
| institution | OA Journals |
| issn | 1424-8220 |
| language | English |
| publishDate | 2024-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj-art-993d4522a6b549f0b5b13073975fa3b82025-08-20T01:47:33ZengMDPI AGSensors1424-82202024-09-012419621810.3390/s24196218FloatingBlue: A Delay Tolerant Networks-Enabled Internet of Things Architecture for Remote Areas Combining Data Mules and Low Power CommunicationsRuan C. M. Teixeira0Celso B. Carvalho1Carlos T. Calafate2Edjair Mota3Rubens A. Fernandes4Andre L. Printes5Lennon B. F. Nascimento6Postgraduate Program in Electrical Engineering, Federal University of Amazonas, Manaus 69080-900, BrazilPostgraduate Program in Electrical Engineering, Federal University of Amazonas, Manaus 69080-900, BrazilUniversitat Politècnica de València, 46022 València, SpainInstitute of Computing, Federal University of Amazonas, Manaus 69080-900, BrazilEmbedded Systems Laboratory, State University of Amazonas, Manaus 69050-020, BrazilEmbedded Systems Laboratory, State University of Amazonas, Manaus 69050-020, BrazilEmbedded Systems Laboratory, State University of Amazonas, Manaus 69050-020, BrazilMonitoring vast and remote areas like forests using Wireless Sensor Networks (WSNs) presents significant challenges, such as limited energy resources and signal attenuation over long distances due to natural obstacles. Traditional solutions often require extensive infrastructure, which is impractical in such environments. To address these limitations, we introduce the “FloatingBlue” architecture. This architecture, known for its superior energy efficiency, combines Bluetooth Low Energy (BLE) technology with Delay Tolerant Networks (DTN) and data mules. It leverages BLE’s low power consumption for energy-efficient sensor broadcasts while utilizing DTN-enabled data mules to collect data from dispersed sensors without constant network connectivity. Deployed in a remote agricultural area in the Amazon region, “FloatingBlue” demonstrated significant improvements in energy efficiency and communication range, with a high Packet Delivery Ratio (PDR). The developed BLE beacon sensor achieved state-of-the-art energy consumption levels, using only 2.25 µJ in sleep mode and 11.8 µJ in transmission mode. Our results highlight “FloatingBlue” as a robust, low-power solution for remote monitoring in challenging environments, offering an energy-efficient and scalable alternative to traditional WSN approaches.https://www.mdpi.com/1424-8220/24/19/6218IoTDTNBLEUAVlow power communications |
| spellingShingle | Ruan C. M. Teixeira Celso B. Carvalho Carlos T. Calafate Edjair Mota Rubens A. Fernandes Andre L. Printes Lennon B. F. Nascimento FloatingBlue: A Delay Tolerant Networks-Enabled Internet of Things Architecture for Remote Areas Combining Data Mules and Low Power Communications Sensors IoT DTN BLE UAV low power communications |
| title | FloatingBlue: A Delay Tolerant Networks-Enabled Internet of Things Architecture for Remote Areas Combining Data Mules and Low Power Communications |
| title_full | FloatingBlue: A Delay Tolerant Networks-Enabled Internet of Things Architecture for Remote Areas Combining Data Mules and Low Power Communications |
| title_fullStr | FloatingBlue: A Delay Tolerant Networks-Enabled Internet of Things Architecture for Remote Areas Combining Data Mules and Low Power Communications |
| title_full_unstemmed | FloatingBlue: A Delay Tolerant Networks-Enabled Internet of Things Architecture for Remote Areas Combining Data Mules and Low Power Communications |
| title_short | FloatingBlue: A Delay Tolerant Networks-Enabled Internet of Things Architecture for Remote Areas Combining Data Mules and Low Power Communications |
| title_sort | floatingblue a delay tolerant networks enabled internet of things architecture for remote areas combining data mules and low power communications |
| topic | IoT DTN BLE UAV low power communications |
| url | https://www.mdpi.com/1424-8220/24/19/6218 |
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