About MosquitoDetect
A collaborative web platform for ovitrap image collection, manual and AI-assisted mosquito egg annotation, and GIS-based surveillance — purpose-built for public health research on mosquito species.
What is MosquitoDetect?
MosquitoDetect enables field teams to photograph ovitrap substrates, upload them with GPS coordinates and site metadata, and collaboratively annotate mosquito eggs directly in the browser.
A YOLO-based AI pipeline can pre-annotate images on demand, with human review always available. All geotagged images are visualised on an interactive GIS map.
Scientific team
MosquitoDetect was developed through the collaborative effort of the following people.
- BH Branimir K. Hackenberger
- DH Domagoj K. Hackenberger
- TD Tamara Djerdj
- NM Nadejda Mocreac
- CP Chirag Prabhakar Padubidri
- AK Andreas Kamilaris
- KM Angeliki F. (Kelly) Martinou
In collaboration with
The scientific institutions collaborating on MosquitoDetect.
Department of Biology, Josip Juraj Strossmayer University of Osijek, Sovereign Base Areas Administration, Department of Horticulture and Forestry, Faculty of Agricultural, Forestry and Environmental Sciences, Technical University of Moldova, CYENS Centre of Excellence, University of Twente, Laboratory of Vector Ecology and Applied Entomology, Joint Services Health Unit, British Forces Cyprus, Enalia Physis Environmental Research Centre, CARE-C, The Cyprus Institute
Stakeholders
The administrations and communities whose support makes the surveillance work possible.
Sovereign Base Areas Administration, Municipality of Curium, Asomatos Council, Akrotiri Council
Built by SCIOM and BioQuant
