LoRaWAN Class A soil sensor measuring temperature, moisture, and electrical conductivity with up to 10 km range and 3-year battery life
One probe simultaneously captures soil temperature (-40–80°C, ±0.5°C), volumetric moisture (0–100%, ±2–3%), and electrical conductivity (0–20 ms/cm, ±3–5%) — eliminating the need for three separate sensors. EC measurement reveals salinity stress before visual symptoms appear, while high-resolution moisture data (0.03% in the 0–50% range) enables precise deficit irrigation. The combined dataset allows agronomists to correlate salinity, water content, and temperature for a complete root-zone health profile.
With 19dBm transmit power and -136dBm receiver sensitivity at SF12/125kHz, the KM-S8 achieves reliable 2–10 km communication range across open farmland — reaching sensors deployed in distant fields without repeaters. LoRaWAN Class A v1.0.3 protocol ensures interoperable integration with any standard-compliant gateway and network server. This long-range architecture reduces gateway density requirements, lowering infrastructure cost per monitored hectare.
Powered by a single 19Ah D-cell lithium-thionyl chloride battery, the sensor operates 1 to 3 years without replacement — the actual duration determined by sampling frequency rather than a fixed calendar limit. Combined with IP66-rated dust and water ingress protection and a -40–85°C operating range, the KM-S8 is engineered for season-after-season deployment in harsh outdoor environments without service visits. This maintenance-free design enables large-scale, permanent sensor networks at a predictable total cost of ownership.
Built-in Bluetooth enables sensor provisioning, parameter setting, and firmware updates entirely through a mobile app — no USB cable, no AT commands, no laptop required. Field technicians configure device parameters, adjust sampling intervals, and verify operation standing at the deployment site. This zero-code setup dramatically reduces deployment labor and eliminates the skill barrier for farm staff operating the sensor network.
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