Technical feasibility/SAMS definitions

Start mass nectar flow: increase in weight by a certain percentage (e.g. 10%) compared to the average weight data of the last few days. The percentage value may be country- or operation depending.

Active foraging: bees bring in slightly more nectar than they consume overnight (beehive’s weight steadily increases over several days or stays more or less the same). Theoretically, during active foraging, a distinctive pattern in weight data should be noticeable.

Consumption during dearth periods (winter in temperate zones, dry/rainy season in tropical zones): bees consume stored honey (beehive’s weight decreases).

Swarming: Detection of such a state is possible by temperature, sound or weight data. Since bees prepare their flight muscles (by heating them) before leaving the hive, the temperature inside the hive also increases, thus this can be observed in measured hive temperature data (References to be added). Several researches (references) have been dedicated to audio data analysis regarding bee colony state detection, including swarming. During these studies it was found that there is a distinguishable shift in frequencies during swarming event.

Queenless/Queenright: Some authors ^[1] ^[2] were able to determine potentials for the detection of the queenless state with analysis of audio data by applying artificial intelligence methods.

Broodless: Detection of this state could be possible by temperature data. During brood rearing bees try to maintain stable temperature (34-36°C), but in broodless state temperature inside the hive tends to depend on ambient temperature ^[3].

Absconding: Absconding is still not researched enough. Theoretically, by the assumptions of the SAMS project, it should be determined by temperature and weight data. After absconding there are no “living beings” that could perform thermoregulation inside the hive, therefore a noticeable weight reduction should also be observed.

Death: Death of the colony can be detected by the temperature measurement or/ and by sound. Death detection could involve a comparison between real-time colony temperature with the environmental temperature and if the difference is not significant, then it can be concluded that the colony is dead.

References

↑ Nolasco, I., Terenzi, A., Cecchi, S., Orcioni, S., Bear, H. L., & Benetos, E. (2019). Audio-based identification of beehive states. In ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 8256-8260). IEEE.
↑ Robles-Guerrero, A., Saucedo-Anaya, T., González-Ramírez, E., & De la Rosa-Vargas, J. I. (2019). Analysis of a multiclass classification problem by Lasso Logistic Regression and Singular Value Decomposition to identify sound patterns in queenless bee colonies. Computers and Electronics in Agriculture, 159, 69-74.
↑ Stalidzans E., Berzonis A. (2013) Temperature Changes above the Upper Hive Body Reveal the Annual Development Periods of Honey Bee Colonies, Computers and Electronics in Agriculture 90, 1–6.