AJA | Environmental sensors for real-time forest ecosystem monitoring

AJA | Environmental sensors for real-time forest ecosystem monitoring

Forest health solution built upon an innovative sensor technology for real-time ecosystem monitoring

The startup foldAI has developed sensors to screen health status of forests providing forest managers with a rich understanding of their forest ecosystems, and a decision toolbox to deploy immediate mitigating actions. The team’s solution, Aja, used in the sensors is  a framework for ecosystem management based on deep technology. By harnessing state-of-art Machine Learning on precise, real-time sensor data, Aja can not only detect forest threats as they happen, but even predict their arising and forecast their unfolding. Aja improves forest health, resilience and bioeconomical performance by introducing lean processes to a broad ecosystem management community. It helps reducing greenhouse emissions by scaling high resolution forest management through a fully automated and affordable solution for more than 30 Million forest owners in Europe, Russia and North America. The solution builds on embedded Machine Learning, and biochemical and environmental signal processing on high-dimensional data. Use cases comprise the assessment of environmental impacts enabling greater accuracy in the evaluation of the environmental consequences of a strategy or policy, risks assessment including alerts to threats, biodiversity quantification and ecosystem health tracking. Aja’s significant carbon reduction impact has been independently certified by The Climate Impact Forecast.

Regiunea de origine
Potențial de sustenabilitate
Sustainable forest management is strongly supported by real time data on the forest's health status
Impactul asupra mediului și biodiversității

The solution helps to monitor ecosystem functions of forests and biodiversity, thereby improving risk management 

Domeniu 1 (principal)
Inventariere, evaluare, monitorizare
Managementul pădurilor, silvicultura, servicii ecosistemice, reziliență
Perturbări ale pădurilor, riscuri, răspuns la dezastre
Cuvinte cheie
forest monitoring; sensors; machine learning; biodiversity
Provocare abordată
1. Îmbunătățirea rezilienței pădurilor și adaptarea la schimbările climatice
Tip de soluție
Senzori, echipamente de măsurare
Soluție digitală
Țara de origine
Regiunea de origine
Scara de aplicare
Transfrontalier / multi-lateral
Anul de început și de sfârșit
2019 -
Date de contact
Proprietar sau autor
Dr. Friedrich Förster
Dr. Marie-Charlotte Hoffmann
References and Resources
Proiectul în cadrul căruia a fost creată această fișă informativă
Rosewood 4.0