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.

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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
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article

Cost-Effective TinyML-Ready Design and Field Deployment of a Solar-Powered Environmental Monitoring Data Collector Using LTE-M Communication

Valentin Adrian Niță, Răzvan Mihai, Emanuel-Crăciun TRÎNC, Cristian Paţachia Sultănoiu et al.
Applied Sciences
Smart Agriculture and AI
article

Cost-Effective TinyML-Ready Design and Field Deployment of a Solar-Powered Environmental Monitoring Data Collector Using LTE-M Communication

Valentin Adrian Niță, Răzvan Mihai, Emanuel-Crăciun TRÎNC, Cristian Paţachia Sultănoiu, Cosmin Ancuţi, Cristina Stolojescu-Crisan
article en

Abstract

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.

Applied SciencesVol. 16(7)
Polytechnic University of Timişoara (RO), Societatea Ornitologică Română (RO)
Zero hunger
Openalex Percentile: Top 4%
Smart Agriculture and AI
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Cost-Effective TinyML-Ready Design and Field Deployment of a Solar-Powered Environmental Monitoring Data Collector Using LTE-M Communication — Valentin Adrian Niță, Răzvan Mihai, et al. · Applied Sciences (2026) | TGRS Research Map | TGRS