Next generation surveillance of biogas plants using AI - for improve efficiency and re-source utlisation

Increased biogas production, e g more biogas plants as well as increased production efficiency per plant, is clearly an important approach to reach Sweden’s environmental and climate targets and a fossil free transport sector.

In this context, a microbiological surveillance has immense potential in management and optimisation of biogas processes, coupled with traditional process monitoring parameters.

Our recent previously developed novel model for surveillance of biogas plants shows promising results for indicating process imbalance and can represent a valuable tool for process operation.

To reach the stage of application we propose that this method should be further developed and refined by using extensive long-term surveillance of different types of biogas plants.

Data from such surveillance will further one be used to a) de-velop deep machine learning models, to be used for the early warning of process instability, and b) a rapid on-site community profiling assay