Cost-Effective TinyML-Ready Design and Field Deployment of a Solar-Powered Environmental Monitoring Data Collector Using LTE-M Communication
Environmental monitoring is essential for smart agriculture, renewable energy assessment, and climate-aware farm management. However, deploying autonomous sensing platforms in rural environments remains challenging because of energy constraints, communication reliability, and real-time processing requirements. This paper presents a modular, solar-powered environmental monitoring platform integrating LTE-M communication and TinyML-enabled edge sensing. The proposed system adopts a dual-microcontroller architecture that combines an Arduino Nano 33 BLE for real-time sensor acquisition and edge processing with an Arduino MKR NB 1500 dedicated to low-power wide-area communication. The platform integrates temperature, humidity, atmospheric pressure, rainfall, wind, and light sensors within a scalable framework. Two monitoring stations were deployed in rural regions of Romania to evaluate communication robustness, sensing stability, and energy autonomy. Field results demonstrated reliable LTE-M connectivity (4306 received signal strength indicator [RSSI] samples; mean −75.51 dBm) and strong agreement with a regional weather station, with mean deviations of −0.71 °C (temperature), 4.98% (humidity), and a stable pressure offset of −9.58 hPa attributable to altitude differences. Despite a total system cost of €315, the platform achieved measurement performance comparable to that of professional meteorological stations while maintaining long-term solar-powered operation. The proposed architecture provides a scalable and cost-effective solution for distributed smart agriculture and environmental monitoring applications.
Authors
- Valentin Adrian Niță
- Răzvan Mihai (ORCID: https://orcid.org/0009-0000-7250-2825)
- Emanuel-Crăciun TRÎNC
- Cristian Paţachia Sultănoiu
- Cosmin Ancuţi
- Cristina Stolojescu-Crisan
Institutions
- Polytechnic University of Timişoara (RO)
- Societatea Ornitologică Română (RO)
Publication Details
- Journal
- Applied Sciences
- Published
- 2026-03-27
- DOI
- https://doi.org/10.3390/app16073237
- Primary Topic
- Smart Agriculture and AI
- Type
- article
- Field-Weighted Citation Impact
- 0.00