Scaling up the FINAPP Cosmic Ray Neutron Sensing probe.
Sector: Water Supply and Storage • Location: Italy
Source: EU Funding & Tenders Portal
The water present in the soil, in the biomass and in the snow represents extremely sensitive data for various sectors. Monitoring soil moisture is crucial in agriculture to irrigate efficiently, save water and costs, and obtain a healthier and more abundant harvest. The snow water equivalent (water content in the snow pack) is a crucial parameter for water availability forecasting for spring/summe
Project Information FAQ
Project Information
Want to explore the full details? View the full report
Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | ended |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | The water present in the soil, in the biomass and in the snow represents extremely sensitive data for various sectors. Monitoring soil moisture is crucial in agriculture to irrigate efficiently, save water and costs, and obtain a healthier and more abundant harvest. The snow water equivalent (water content in the snow pack) is a crucial parameter for water availability forecasting for spring/summer. Finapp’s Cosmic Ray Neutron Sensing (CRNS) probes are novel, next-generation, water-content estimators with a broad range of applications. They detect the neutrons generated from the interaction of cosmic rays with the Earth atmosphere and water surfaces, and from those measurements, they estimate the water content. All probes are connected to an AI-based, IoT cloud that provides the data in real-time via a user interface, and estimates specific factors for each of the applications in the different industries (e.g., plants/crops health, fire risk). |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
Project Type | Obfuscated Data |
Article Published Date | Obfuscated Data |
