# Multisensor Data Fusion for Automatized Insect Monitoring (KInsecta)

arXiv: https://arxiv.org/abs/2404.18504 · HTML: https://mlsanity.com/paper/2404.18504/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 15 references that are in the map.
- First posted on arXiv 29 Apr 2024.

## Builds on (most cited first, 2 of 2)

- [MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications](https://mlsanity.com/paper/1704.04861/) (2017)
- [Low Cost Machine Vision for Insect Classification](https://mlsanity.com/paper/2404.17488/) (2024)

## Abstract (arXiv)

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.