Abstract
Abstract. Bees are recognized as an indispensable link in the human food chain and general ecological system. Numerous threats, from pesticides to parasites, endanger bees, enlarge the burden on hive keepers, and frequently lead to hive collapse. The Varroa destructor mite is a key threat to bee keeping, and the monitoring of hive infestation levels is of major concern for effective treatment. Continuous and unobtrusive monitoring of hive infestation levels along with other vital bee hive parameters is coveted, although there is currently no explicit sensor for this task. This problem is strikingly similar to issues such as condition monitoring or Industry 4.0 tasks, and sensors and machine learning bear the promise of viable solutions (e.g., creating a soft sensor for the task). In the context of our IndusBee4.0 project, following a bottom-up approach, a modular in-hive gas sensing system, denoted as BeE-Nose, based on common metal-oxide gas sensors (in particular, the Sensirion SGP30 and the Bosch Sensortec BME680) was deployed for a substantial part of the 2020 bee season in a single colony for a single measurement campaign. The ground truth of the Varroa population size was determined by repeated conventional method application. This paper is focused on application-specific invariant feature computation for daily hive activity characterization. The results of both gas sensors for Varroa infestation level estimation (VILE) and automated treatment need detection (ATND), as a thresholded or two-class interpretation of VILE, in the order of up to 95 % are presented. Future work strives to employ a richer sensor palette and evaluation approaches for several hives over a bee season.
Highlights
Major issues from environmental pollution to invasive species are threatening our ecological system and the human food supply
Motivated by the importance of honey bees and the increasing challenges imposed on bees and beekeepers, an in-hive close-to-brood nest sensing system was conceived and applied in a single colony for a substantial period of time during the 2020 bee season in a single measurement campaign
The underlying measurement system and the first results for the SGP30 sensor have already been reported in König (2021a) and König (2021b)
Summary
Major issues from environmental pollution to invasive species are threatening our ecological system and the human food supply. The Varroa mite is a parasite that poses a major threat to bee keeping and is the cause of many bee colony losses. The monitoring of the Varroa infestation level is one important task of conventionally operating bee keepers. There is a community practicing treatment-free bee keeping (Hudson and Hudson, 2020) or chemical-free alternatives like thermal treatment (Wimmer, 2020), the majority of bee keepers follows standard treatment practice (e.g., employing formic acid) and needs to know the right time to start treatment based on the hive infestation level. Sensors and automation (Werthschützky, 2018), like in home automation (Eric Mounier, 2017), automated agriculture (Rembert, 2020), condition monitoring (Lee et al, 2011; IEEE, 2015; Zhang et al, 2017; Weckbrodt, 2019), and Industry 4.0 (Kagermann et al, 2011; Kohlert and König, 2016), can both alleviate hive keeping and make it much more effective.
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