Team 2

Based on ATTRACT project: SENSEI

Modality A






Modality A

Academic year



Continuous water and air pollution are affecting the quality of our soils which are responsible for most of our freshwater and food supply, and with no easy way to assess its state, it becomes a hidden danger to our future. It is essential to tackle this problem before it is too late. Therefore, we want to develop an innovative solution to monitor and predict the quality of the soil by combining the new state-of-the-art sensor technology SENSEI and Artificial Intelligence.

SENSEI consists of a network of live, autonomous biosensor modules that can detect and quantify any organic or inorganic material present in the soil. The idea consists mainly of three steps:

  • Create a network of SENSEI sensors that detect the presence of target materials in the soil.
  • Build a model that predicts soil pollution build-up with the help of machine learning.
  • Visualization of collected data on a platform in form of e.g., a dashboard.

With a network of these sensors, any farmer but also governments will be able to easily monitor land and soil with access to real-time reports on the condition of the soil and AI-supported predictions. This way, we can fight the continued progress of soil pollution and reduce the global CO2 footprint.