eLogUp! A precise, affordable and open-source IoT data logger to scale-up long-term environmental monitoring
eLogUp! is a low-cost, modular, and open-source data logger designed to support both research and operational environmental monitoring applications requiring accurate data recording and storage, efficient power management, and reliable data transmission. It serves as a key component for the implemen...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
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| Series: | HardwareX |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2468067225000380 |
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| Summary: | eLogUp! is a low-cost, modular, and open-source data logger designed to support both research and operational environmental monitoring applications requiring accurate data recording and storage, efficient power management, and reliable data transmission. It serves as a key component for the implementation of effective Low-Cost Network Sensor (LCNS) systems, enhancing environmental observation capabilities. eLogUp! consists of a custom-designed PCB integrated with an Arduino® MKR microcontroller, enabling data acquisition from a wide range of analog and digital sensors, such as temperature, water level, and humidity probes, with user-defined sampling intervals. A distinctive feature of eLogUp! is its auto-wake-up function, which powers down the system between measurements to optimize energy consumption. It also integrates several electronic components (e.g. RTC) to minimize the overall footprint of the system. The system can thus operate on a small LiPo battery and solar panel. Data transmission can be carried out using different protocols (e.g., WiFi, GSM, or LoRaWAN). Developed as an alternative to commercial environmental data loggers, which are often expensive, overly specialized, proprietary, or limited to a narrow set of parameters, eLogUp! offers an affordable, adaptable, and open-source solution. This makes it a versatile tool for environmental researchers, field practitioners, and citizen science initiatives, providing a scalable and accessible approach to long-term environmental data collection. |
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| ISSN: | 2468-0672 |