Implementation and Evaluation of a Low-Cost Measurement Platform over LoRa and Applicability for Soil Monitoring
Year: 2024
Type: article
Abstract: Efficiently reporting soil-specific information is of key importance for plant growth but can be quite demanding as well. Indeed, it may require expensive digitizers, subscriptions to services for communication links between each sensor and the cloud, and the incorporation of power-hungry elements. Added to this, soil sensors may vary drastically, e.g., in terms of power characteristics, response times, or interfacing options. The need for improved energy autonomy increases reporting complexity, as it presupposes that the participating components will enter a low-power (sleep) state when not in action. Furthermore, the IoT nodes hosting the sensing instruments should be able to work unattended for long periods under varying environmental conditions. In response to the aforementioned physical and technical challenges, this work highlights the details behind the cooperation of a cost-effective microprocessor equipped with a radio transceiver and some simple and widely available electronic components to form nodes that can host a diverse set of soil sensors and deliver reliable data in satisfactory ranges. The sensitivity and power efficiency of the LoRa protocol make it ideal for rural agri-field use; in the meantime, optimized action/sleep management, along with tiny solar panels, guarantee sustainable operation. The proposed system was tested utilizing various typical soil instruments, and its range coverage, consumption, and measurement quality were thoroughly evaluated under different installation settings, thus providing guidance for similar implementations and indicating its suitability for a wide set of monitoring applications.
Source: Future Internet
DOI: 10.3390/fi16120443
Institution: Agricultural University of Athens
Language: English
Topic: Smart Agriculture and AI
Subfield: Plant Science
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $1,819
OpenAlex ID: W4404821644
