Sensorbees are ENhanced Self-ORganizing Bio-hybrids for Ecological and Environmental Surveillancecore
SENSORBEES · Horizon Europe grant · 2024-09-01–2029-08-31
EC contribution
Total cost
Beneficiaries
About the data
Source: CORDIS (official EU open data), Horizon Europe. Framework HORIZON · call HORIZON-EIC-2023-PATHFINDEROPEN-01 · scheme HORIZON-EIC · topic HORIZON-EIC-2023-PATHFINDEROPEN-01-01. CORDIS record →
Objective
SENSORBEES aims at using honeybee colonies as a sensor network for tracking a set of important but undersampled ecological status variables 1) the level of pollination service in the surrounding region and 2) the level of diversity of blossoming plants. The pollination of plants is not only significant for human society in agriculture but it is also the trophic basis of the food webs that support all the other trophic layers of animals that are currently endangered in the 6th mass extinction that we are currently facing. We will equip a honeycomb that fits into a conventional beehive with a micro-robotic system that can reach every single cell on the comb. Thus, we will be able to inspect the content of each cell selectively and store its assessment into a database, containing the history of each single comb cell over years. The robot will photograph the brood in the cell at full-size from a short distance, allowing its size and health measurement. SENSORBEES will perform specific manipulations on these comb cells, for maximizing and ensuring pollination service to the environment, to favor and support plant diversity, and to defend itself against detrimental developments. Moreover, we will equip the hive with a smart pollen trap capable of selective collection and visual analysis of the pollen brought into the hive by the bees. The pollen influx, along with the data collected by the robotic agents in the hive will provide information about the health of the colony as well as on the diversity of plants within the foraging area of the bees, i.e. 5-10 km around the hive, thus sample areas of 78-314 sq km. Health estimates on the colony level can be made by looking for anomalies in brood growth and breeding success and by comparing the data streams from the hive entrance, local weather data and brood dynamics. Data fusion will be applied to several colonies to e.g. locate potential problematic feeding sites.
Beneficiaries (5)
| Organisation | Country | Role | EC contribution | SME |
|---|---|---|---|---|
| CESKE VYSOKE UCENI TECHNICKE V PRAZE | CZ | coordinator | €613,125 | |
| UNIVERSITAET GRAZ | AT | participant | €945,634 | |
| SCUOLA SUPERIORE DI STUDI UNIVERSITARI E DI PERFEZIONAMENTO S ANNA | IT | participant | €463,375 | |
| BII SMART TEKNOLODZHIS | BG | participant | €336,935 | Yes |
| UNIVERSITY OF DURHAM | UK | associatedPartner | — |
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