The Conservation Technology Research Hub applies cutting-edge artificial intelligence, machine learning, and IoT technologies to promote sustainable forest conservation and management. By combining acoustic monitoring, environmental sensing, and data analytics, the hub develops innovative tools for detecting illegal logging, monitoring wildlife, and enhancing biodiversity protection.
Its mission is to strengthen forest resilience and sustainability through technology-driven research and cross-disciplinary collaboration.
To become a leading center for intelligent forest monitoring and conservation technologies that protect ecosystems, support sustainable resource use, and empower communities to participate in data-driven environmental stewardship.
To advance the use of AI, IoT, and acoustic sensing in forest research by developing real-time monitoring systems that enhance biodiversity conservation, detect illegal logging, and contribute to climate action efforts both locally and globally.
Using drones and photogrammetric mapping to analyze vegetation cover, canopy structure, and ecosystem health.
Applying deep learning and AI-based models to classify forest sounds, track species, and predict environmental threats.
Leveraging machine learning algorithms and data dashboards to inform conservation decisions and policy frameworks.
Developing sound-based detection models to monitor forest activity and identify illegal logging or wildlife presence.
Designing IoT-enabled sensing systems that capture real-time environmental and forest data for analysis.
The hub seeks to produce the following outputs
Peer-reviewed studies on forest acoustics, IoT design, and conservation AI.
MSc and PhD projects focusing on acoustic monitoring and AI for environmental applications.
Deployment of smart forest monitoring prototypes and mobile applications.
Training students and researchers in AI, IoT, and data science for environmental monitoring.
This project employs IoT-enabled acoustic sensors and ML algorithms to detect chainsaw and axe sounds in Kenyan forests, enabling faster response and reducing human patrol reliance.
Partners: Kenya Forest Research Institute (KEFRI), Kenya Forest Service (KFS), Community Forest Associations.
Daniel Simiyu
Sandra Gathoni
hmuchiri@strathmore.edu
avikiru@strathmore.edu
