Optimizing Wastewater Treatment Processes through the Integration of Artificial Intelligence and the Internet of Things: The Shift from Traditional Paradigms to Smart Plants

Fatemeh Soleymani¹ Davoud Ebrahimi² Seyedreza Karrari³

1) Master of Science in Civil Engineering, Environmental Engineering Major, Payam Noor University, Shiraz Branch, Iran, Email:
2) Master of Science in Civil Engineering, Environmental Engineering Major, Payam Noor University, Shiraz Branch, Iran, Email:
3) Master of Science in Civil Engineering, Transportation Engineering Major, Islamic Azad University, South Tehran Branch, Iran, Email:

IOI Code : AACZ-AAKABE
Publication : The 5th International Conference on Seismic Retrofitting(5icst.ir)
Abstract :
    Conventional wastewater treatment plants are increasingly facing the challenges of unstable energy demand, variable treatment efficiency, and rising operational costs. This paper introduces a paradigm shift that transforms treatment plants from static, command-driven hardware into adaptive, self-optimizing systems that function like living organisms—equipped with a nervous system (IoT networks) and a cognitive brain (AI analytics). The proposed intelligent hierarchical architecture integrates real-time IoT data acquisition, predictive modeling using Long Short-Term Memory (LSTM) networks, and closed-loop optimization via Model Predictive Control (MPC). While addressing implementation challenges such as data security and sensor reliability, this framework achieved significant results in a full-scale case study: a 30% reduction in aeration energy consumption, a 4 percentage point increase in COD removal efficiency (from 92% to 96%), and a 25% reduction in total operational costs. This research demonstrates that the integration of AI and IoT can simultaneously optimize the critical triad of energy, cost, and quality, marking a definitive transition from the art of operation based on experiential knowledge to a predictable science driven by data intelligence.

Keywords : smart wastewater treatment internet of things (iot) artificial intelligence (ai) energy optimization model predictive control (mpc) digital twin real time data