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Ecological and Hydrological Weather Networks

The future of weather and ecosystem monitoring. Our IoT-based sensor network provides real-time, high-precision environmental data to support research, agriculture, climate science, and smart city applications.

Sensing Metrics



Key IoT Sensor Metrics for Environmental Monitoring

Our IoT sensors are designed to measure a variety of environmental factors that provide valuable insights for weather forecasting, agriculture, and climate research. These metrics include it real-time data to remote servers or dashboards.

> Albedometer: Measure the reflectivity of the Earth's surface to understand how much solar radiation is being absorbed or reflected, which impacts local energy balance and climate conditions.

> Relative Humidity: Track the amount of water vapor in the air to assess moisture availability, predict precipitation, and monitor plant and soil health.

> Solar Radiation: Measure the intensity of sunlight reaching the surface, a key factor for photosynthesis, energy transfer, and water evaporation rates.

> Soil Moisture: Monitor the amount of water present in the soil to optimize irrigation practices, track drought conditions, and manage water resources in agricultural or natural ecosystems.

> Barometric Pressure: Measure atmospheric pressure to detect changes that indicate upcoming weather patterns such as storms, high or low-pressure systems, and temperature fluctuations.

> Temperature: Track ambient air or surface temperature to understand local climate conditions, predict weather changes, and evaluate ecosystem health and crop growth.

> Wind Direction: Monitor the direction from which the wind is blowing to forecast weather patterns, air quality, and assess wind-related environmental impacts.

> Wind Speed: Measure the rate of wind movement to understand local weather conditions, predict storms, and assess impacts on ecosystems and hydrological systems.

> Wind Gust: Detect short bursts of high wind speed that can cause damage to vegetation, disrupt ecosystems, and indicate storm conditions.

Soil Moisture and Temperature Profile

Sub-surface 600 mm profile with 6x capacitance-based soil moisture and soil temperature sensors Moisture / Scaled Frequency Unit  Range: From 0 (air) to 100% (water) Resolution: 0.01 Accuracy: ±1% at calibration Temperature  Range: From -20 to +50 °C Resolution: 0.1 °C Accuracy: ±0.2 °C, 0.1% per °C Length cable: 5m *Custom profile configuration and length on request LoRaWAN® class A 2 C alkaline batteries

1,799.94 €

Soil Moisture Temperature and Salinity Profile

Soil Moisture Range: From 0 to 100 % volumetric water content (VWC) Resolution: 0.01 % Accuracy: ±0.03 % Soil Temperature Range: From -20 to 60 °C Accuracy: ±2.0 °C at 25 °C Resolution: ±0.01°C *Inaccuracy can be higher under moderate-to-high solar radiation. Salinity Range: From 0 to 8000 volumetric ion content (VIC) Accuracy: Not specified *600 mm probe length, 6 soil moisture, temperature and salinity sensors. Other lengths, number of sensors: contact us 

2,136.68 €

Soil Moisture Temperature and Electrical Conductivity

Volumetric Water Content (VWC) Range: Mineral soil: From 0.00 to 0.70 m³/m³ Soilless media: From 0.0 to 1.0 m³/m³ Apparent dielectric permittivity εa: 1 (air) to 80 (water) Resolution: 0.001 m³/m³ Accuracy: ±0.03 m³/m³ (±3% VWC) typical in mineral soils Temperature Range: From -40 to +60 °C Resolution: 0.1 °C Accuracy: ±0.5 °C from −40 to 0 °C, ±0.3 °C from 0 to +60 °C Bulk Electrical Conductivity  Range:  From 0 to 20 dS/m (bulk) Resolution: 0.001 dS/m Accuracy: ±(5% +0.01 dS/m) from 0 … 10 dS/m, ±8% from 10 … 20 dS/m Cable length: 5 meter  LoRaWAN® class A 2 C alkaline batteries

1,145.09 €

Surface, Air, Dew point Temperature Relative Humidity

High-Precision Winter Road Maintenance Sensor Range: From -40 to 70°C (-40 to 160°F) Accuracy: From -40 to 60°C (±0.5°C) Note: Accuracy is temperature dependent. The quoted accuracy is against a blackbody source within the ambient temperature range of -20 to 50°C and object temperature range of -40 to 60°C. Resolution: ±0.01°C Air Temperature Range: From -40 to 70°C (-40 to 160°F) Accuracy: ±0.4°C Note:  Inaccuracy can be higher under moderate-to-high solar radiation. Resolution: ±0.01°C Relative Humidity Range: From 0 to 100 % Resolution: 0.1 % Accuracy: < ±3 % or better Dew Point Temperature (Calculated) Range: From -40 to 70°C (-40 to 160°F) Accuracy: ±1.0 °C (-35 to 50 °C) Note: The calculated dew point temperature is found from Tetens' equation solved for dew point with coefficients optimized for the temperature range -35 to 50°C. Resolution: 0.1°C LoRaWAN® class A 2 C alkaline batteries

4,886.53 €

Wind Speed Wind Direction and Temperature

Horizontal Wind Speed Range: From 0 to 30 m/s Resolution: 0.01 m/s Accuracy: the greater of 0.3 m/s or 3% of measurement Wind Gust Range: From 0 to 30 m/s Resolution: 0.01 m/s Accuracy: the greater of 0.3 m/s or 3% of measurement Wind Direction Range: From 0 to 359° Resolution: 1° Accuracy: ±5° Tilt Range: From -90° to +90° Resolution: 0.1° Accuracy: ±1° Temperature Range: From -50 to +60 °C Resolution: 0.1 °C Accuracy: ±0.6 °C, not protected from solar radiation Length cable: 5m  LoRaWAN® class A 2 C alkaline batteries

2,408.21 €

Weather Station

Solar Radiation Range: From 0 to 1'750 W/m² Resolution: 1 W/m² Accuracy: ±5% of measurement typical Precipitation Range: From 0 to 400 mm/h Resolution: 0.017 mm Accuracy: ±5% of measurement from 0 to 50 mm/h Vapor Pressure Range: From 0 to 47 kPa Resolution: 0.01 kPa Accuracy: ±0.2 kPa typical below 40 °C Relative Humidity Range: From 0 to 100% RH Resolution: 0.1% RH Accuracy: ±3% RH typical Air Temperature Range: From -50 to +60 °C Resolution: 0.1 °C Accuracy: ±0.6 °C Barometric Pressure Range: From 50 to 110 kPa Resolution: 0.01 kPa Accuracy: ±0.1 kPa from -10 to 50 °C, ±0.5 kPa from -40 to 60 °C Horizontal Wind Speed Range: From 0 to 30 m/s Resolution: 0.01 m/s Accuracy: the greater of 0.3 m/s or 3% of measurement Wind Gust Range: From 0 to 30 m/s Resolution: 0.01 m/s Accuracy: the greater of 0.3 m/s or 3% of measurement Wind Direction Range: From 0 to 359° Resolution: 1° Accuracy: ±5° Tilt Range: From -90° to +90° Resolution: 0.1° Accuracy: ±1° Lightning Strike Count Range: From 0 to 65'535 strikes Resolution: 1 strike Accuracy: variable with distance, >25% detection at <10km typical Lightning Avarage Distance Range: From 0 to 40 km Resolution: 3 km Accuracy: variable Length cable: 5m LoRaWAN® class A 2 C alkaline batteries

4,609.69 €

    Benefits of IoT Sensors for Ecological and Hydrological Weather Networks

    1. Optimized Resource Management: By continuously monitoring key metrics such as soil moisture, temperature, and solar radiation, IoT sensors help optimize the use of water resources, energy, and land, enabling better management of natural resources.
    2. Enhanced Weather Forecasting and Early Warning Systems: Real-time data from wind speed, wind direction, and barometric pressure sensors allow for more accurate predictions of weather events, such as storms or droughts, providing early warnings to mitigate potential impacts on ecosystems and infrastructure.
    3. Improved Ecosystem Health Monitoring: By tracking factors like temperature, humidity, and solar radiation, IoT sensors help monitor ecosystem health and biodiversity, enabling the identification of changes or stressors that could affect plant and animal life.
    4. Better Climate Change Assessment: With continuous measurement of environmental variables such as albedo and soil moisture, IoT sensors contribute to understanding long-term climate trends and how they affect local ecosystems, which is crucial for climate adaptation strategies.
    5. Efficient Disaster Management: By detecting sudden changes in wind gusts, soil moisture, or atmospheric pressure, IoT sensors can provide crucial information to help predict and respond to environmental disasters like floods, wildfires, or extreme weather events.
    6. Sustainability and Conservation: By monitoring environmental conditions with high precision, IoT sensors support sustainable practices in agriculture, water conservation, and habitat preservation, contributing to a healthier planet.
    7. Real-Time Remote Monitoring: IoT sensors provide real-time, remote monitoring of ecological and hydrological conditions, allowing stakeholders to access critical data from anywhere, improving decision-making and responsiveness to changing conditions.
    "Empower your environmental monitoring with IoT sensors, delivering real-time, actionable data to optimize resource management, enhance weather forecasting, and support sustainable practices for a healthier planet."

    Sectors


    Agricultural


    Governmental