Arratia Uribe, Benjamin Andrés
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- PublicationAlLoRa: Empowering environmental intelligence through an advanced LoRa-based IoT solution(Elsevier, 2024-03) Arratia Uribe, Benjamin Andrés; Rosas Olivos, Erika Susana; Tavares de Araujo Cesariny Calafate, Carlos Miguel; Cano Escribá, Juan Carlos; Cecilia Canales, José María; Manzoni, Pietro; Departamento de Informática de Sistemas y Computadores; Escuela Técnica Superior de Ingeniería Informática; Grupo de Redes de Computadores; European Commission; Generalitat Valenciana; Agencia Estatal de Investigación; Ministerio de Ciencia e Innovación; Universitat Politècnica de València[EN] Environmental intelligence aims to improve the decision-making process for high social and environmental value ecosystems. To this end, data are collected using different sensors to allow monitoring of different variables of interest. Typically, these ecosystems cover a large geographical area, with spots of low or no connectivity, preventing their monitoring in real time. In this work, we propose \allora{} (Advanced Layer LoRa), a modular, low-power, long-range communication protocol based on LoRa, that allows monitoring of remote natural areas. \allora{} has been evaluated and tested in an operational oceanographic buoy that has been deployed to address the specific environmental crisis of the Mar Menor lagoon in southeastern Spain - a region spanning 135 Km currently undergoing severe eutrophication process. Our results reveal that \allora{} offers good performance regarding transfer time, power consumption, and range. The throughput ranged from around 2 kbps with SF7 to approximately 300 bps with SF11; the power consumption per kilobyte transmitted varied from $395 \mu Wh$ to $428 \mu Wh$ depending on the specific device used. The Mesh mode test successfully maintained communication between nodes over 20.33 km. Further tests in various configurations under challenging conditions validated the mesh forwarding approach. Despite tripling the distance, the system maintained reliable data transfer, improving speeds from the original point-to-point setup.
- PublicationBODOQUE: An Energy-Efficient Flow Monitoring System for Ephemeral Streams(Association for Computing Machinery (ACM), 2023-10-26) Arratia Uribe, Benjamin Andrés; Prades Gasulla, Javier; Peña-Haro, Salvador; Cecilia Canales, José María; Manzoni, Pietro; Departamento de Informática de Sistemas y Computadores; Escuela Técnica Superior de Ingeniería Informática; Grupo de Redes de Computadores; European Commission; European Social Fund[EN] Effective environmental monitoring is crucial for managing global environmental challenges and providing the necessary data for Environmental Intelligence (EI). This discipline involves the integration of data from various sources to gain a comprehensive understanding of specific regions or processes. In this paper, we introduce BODOQUE, a hardware-software infrastructure to monitor water flows in ephemeral streams where the water rarely flows with great force. BODOQUE uses a low-power TinyML-based camera to detect the presence of water, activating a more complex system to measure flow only when the water flows, thereby optimizing energy consumption. This device is being deployed in the Segura basin, Murcia, Spain. This region is grappling with severe environmental issues that affect the Mar Menor, a unique saltwater lagoon. This paper focuses on the power-saving capabilities of BODOQUE, comparing the energy consumption of different edge devices running the code that measures water flow in the streams. Our goal is to determine the optimal hardware setup for the system based on our experiments, which involve performance and energy consumption tests. The results provide valuable information for future environmental monitoring systems, considering the best balance among the device's cost, performance, and energy consumption.