In the heart of Jaipur, India, a team led by Sandeep Prajapati at the Center for Energy and Environment, Malaviya National Institute of Technology, is reimagining how wastewater treatment plants operate—not just as facilities for cleaning water, but as hubs for producing energy and valuable products. Their research, published in the *Chemical Engineering Journal: Green and Sustainable* (previously translated as *Химическая инженерия. Зелёная и устойчивая*), suggests that integrating artificial intelligence (AI) with microalgae-based wastewater treatment could transform these plants into smarter, more efficient, and sustainable systems.
The challenge is substantial. Traditional wastewater treatment plants struggle with inefficiencies: high energy consumption, difficulty in real-time monitoring, and limited options for sludge management. Prajapati and his team argue that AI can address these issues by optimizing microalgae cultivation and biosolids valorization—turning waste into resources. “AI can provide regular monitoring, real-time response, and optimized operations,” Prajapati explains. “This isn’t just about improving efficiency; it’s about creating a system that adapts and evolves with the needs of the plant.”
The approach leverages microalgae, which thrive in wastewater and can be converted into bioenergy through processes like anaerobic digestion. The study explores both mono-digestion (using microalgae alone) and co-digestion (combining it with other biomass), highlighting how AI can fine-tune these processes for maximum energy yield. For the energy sector, this could mean a new source of renewable energy—one that doesn’t compete with food crops or require vast land areas.
What makes this research stand out is its focus on circularity. Instead of treating wastewater as a problem to be disposed of, the team envisions a system where every component—water, sludge, and energy—is repurposed. “Microalgae-based treatment and conversion technologies can significantly improve water quality, bioenergy yield, and resource recovery efficiency,” Prajapati notes. For industries and municipalities, this could translate into lower operational costs, reduced greenhouse gas emissions, and even new revenue streams from selling bioenergy or recovered nutrients.
The implications for the energy sector are particularly compelling. As global pressure mounts to decarbonize, wastewater treatment plants could become key players in the green energy transition. AI-driven systems could enable plants to respond dynamically to changes in wastewater composition, optimizing energy production in real time. This isn’t just a theoretical advantage—it’s a practical pathway to making wastewater treatment plants net contributors to the energy grid.
For now, the research remains in the academic sphere, but the potential for commercialization is clear. Companies in water treatment, renewable energy, and AI-driven automation could collaborate to pilot these systems at scale. The question isn’t whether this technology will work, but how quickly it can be adopted. As Prajapati’s work suggests, the future of wastewater treatment might not just be cleaner water—it could be a smarter, greener energy ecosystem.