Artificial intelligence-based IoT-enabled biogas production
Peter Onu, Charles Mbohwa, Anup Pradhan
Abstract
This study explored the use of artificial intelligence (AI) and the Internet of Things (IoT) to boost biogas production from organic waste using anaerobic digesters. An artificial neural network (ANN) genetic algorithm (GA) model predicted biogas yields and optimized production. Sensors and IoT technologies monitored factors affecting biogas production, achieving an efficiency of 78.2%. The ANN GA model showed strong accuracy, with a correlation coefficient of 0.85. AI and IoT can significantly increase biogas yield and efficiency, though challenges and limitations exist. This research highlights the potential of these technologies in biogas production.
Topics & Concepts
BiogasBiogas productionInternet of ThingsProduction (economics)Artificial neural networkComputer scienceProcess engineeringArtificial intelligenceBiochemical engineeringEnvironmental scienceEngineeringWaste managementAnaerobic digestionEmbedded systemChemistryEconomicsMacroeconomicsMethaneOrganic chemistryWater-Energy-Food Nexus StudiesSmart Grid Energy Management