<p>This paper provides a real-time environmental monitoring system based on modular IoT-enabled system to detect greenhouse gases: CO₂, CH₄, and N₂O, temperature, and humidity, and soil moisture. The system also combines multi-modal sensing, in-board signal conditioning and adaptive sampling with multi-protocol wireless communication (Wi-Fi, LoRa and cellular). High quality calibration programs, drift removal, and environmental compensation programs are provided to provide high fidelity measurements in different operating conditions. Analytics are based on the cloud to assist in the detection of anomalies, predictive modelling, and long-term data visualisation. The laboratory experiments and simulated field deployments were used as system performance evaluations. It can be seen that sensor measurement error is below  ± 10&#xa0;ppm in the case of CO₂ and within ±  2–3% in the case of CH4, N₂O. The results of communication testing indicate that a high degree of packet delivery reliability (&gt; 90%) can be achieved with all protocols, and LoRa has better long-range stability. The adaptive sampling strategy is about 40% power-saving, which increases remote and battery-powered works. The long-term drift analysis reveals that there are predictable linear trends with the drift less than 1.5% in all the sensors. Altogether, the system has a high potential in the use of the system as continuous environmental monitoring in agricultural, ecological and climate-resilience practices.</p>