  Insect populations are declining globally, making systematic monitoring
essential for conservation. Most classical methods involve death traps and
counter insect conservation. This paper presents a multisensor approach that
uses AI-based data fusion for insect classification. The system is designed as
low-cost setup and consists of a camera module and an optical wing beat sensor
as well as environmental sensors to measure temperature, irradiance or daytime
as prior information. The system has been tested in the laboratory and in the
field. First tests on a small very unbalanced data set with 7 species show
promising results for species classification. The multisensor system will
support biodiversity and agriculture studies.
