Analyse the health of your parcel through biodiversity and pollution monitoring

Working together with wild bees and implementing an image recognition AI model, BeeOmetrics is a low cost nature-based solution which aims to provide detailed environmental measurements at site level (40 ha).

EIC funded

BeeOmetrics is an European Innovation Council-funded project

Abeille butinant une fleur

Purpose

What we’re aiming for

To protect and restore biodiversity, and reduce environmental pollution, our BeeOmetrics R&D project aims to introduce a cost-effective, non-intrusive green technology for environmental monitoring and remediation. It focuses on wild bees as a scalable environmental bioindicator.

Our solution will first make it possible to monitor specific pollution and biodiversity metrics, facilitating in-depth ecosystem health analysis, and through AI, will also generate predictive recommendations for remediating environmental contaminants and revitalizing biodiversity.

BeeOmetrics is designed to offer metrics and recommendations to policy makers, businesses and land managers, empowering them to make informed choices.

Mission

Project Timeline
& Practicalities

50 sites

50 sites to be selected in 2024 
in Belgium and France

50 sites
150 additional sites selected in 2025
50 sites

Sites in both agricultural 
and urban settings

50 sites

2 years of data collection: 2024, 2025

How it works

How does BeeOmetrics work?

The machine learning model that the BeeOmetrics platform will use to make estimations of ecosystem health indicators is based on measurements taken from three primary sources:

AI powered predictive platform, showing interpretation, KPIs & actions

  • Indicators from air, ground, plants & wild pollinators
  • Multi-factor & multi-indicator ecosys, health reports
  • Recommendations for ecosys, health improvement

On-site plant samples

Plants biodiversity & pollen polluants

#eDNA, bioinformatics
#mass spec/chromato analysis

Picture of “Beeôtel” nests

Wild bee (40ha foraging area) biodiversity & population density

#AI, ML, image recognition
#participative science

Sensors

Air pollution, temperature & humidity

#remote sensors

Soil samples

Soil buidiversity & soil pollutants

#eDNA, bioinformatics
#mass spec/chromato analysis

Plant samples

Plant biodiversity

#eDNA, bioinformatics

On-site plant samples

Plants biodiversity & pollen polluants

#eDNA, bioinformatics
#mass spec/chromato analysis

Picture of “Beeôtel” nests

Wild bee (40ha foraging area) biodiversity & population density

#AI, ML, image recognition
#participative science

Sensors

Air pollution, temperature & humidity

#remote sensors

Soil samples

Soil buidiversity & soil pollutants

#eDNA, bioinformatics
#mass spec/chromato analysis

Plant samples

Plant biodiversity

#eDNA, bioinformatics

A On-site bee hotel device, the “BeeÔtel”

B On-site soil samples

C On-site plant samples

A The BeeÔtel

The device provides accommodation for wild bee species, also called solitary bees, and integrate multiple sensors for data collection on various aspects of ecosystem health.
Bee

Solitary bees

Several data sources are provided from the solitary bees, including:

  • Pollen samples, which allows to assess the surrounding plant biodiversity and pollution by eDNA analysis and chemical analysis respectively.
  • Pollinator biodiversity determined by the BeeÔtel occupancy rates that indirectly allows us to assess the health of the surrounding ecosystem.

As solitary bees reside in the BeeÔtel, they leave characteristic “plugs” in the orifices, allowing to distinguish the species occupying each opening. Leveraging this fact, we will use an image recognition algorithm (step 2) to determine (i) the occupancy rate and (ii) biodiversity of local wild bee populations. These two elements can be used as core bioindicators for the health of an ecosystem.

Bee

Integrated Sensors

The BeeÔtel also integrates sensors to simultaneously measure (step 3) other ecosystem indicators, such as pollution levels (i.e., NO2, NH3 and particulate matter of sizes PM2.5 and PM10), temperature and relative humidity.

B On-site soil samples

The second BeeOmetrics data source is on-site soil samples (step 4). These samples, taken from the vicinity of the BeeÔtel, when relevant, undergo key analyses:
 

  • Chemical analysis to detect pesticides and heavy metals in the ecosystem.
  • Environmental DNA analysis to determine soil health.

C On-site plant samples

The third BeeOmetrics data source is on-site plant samples (Step 5) which can be subjected to eDNA analysis to assess the species present in the ecosystem, including invasive or remarkable plants.

About

About BeeOdiversity

Established in 2012 with headquarters in Brussels, BeeOdiversity is a nature-tech company which empowers companies and public entities to create value through biodiversity regeneration and pollution reduction.

We are a 25-strong team of scientists, bio-engineers, biologists, data scientists, IT developers and sales and marketing professionals, and we run 150+ projects in 20+ countries in Europe, North America, South America and Africa.

Our offering is structured around consulting services and state-of-the-art, nature-based monitoring solutions to allow data-driven actions on the ground and engage relationships with stakeholders.
Des ruches dans un champs naturel avec pièce d'eau