Modern treatment of sewage and industrial effluents as we know it has remained relatively unchanged in terms of how plants leverage biological processes to treat wastewater. For approximately 100 years these systems have been studied and optimized for hydraulic retention times, sludge retention times, and other control variables.
Considering our sewage and industrial effluent plays a big role on the quality of our environment, industrial and municipal operations often resort to large capital improvement projects, or static studies to determine best operating practices for their wastewater treatment system.
Though these practices help us make better decisions at our plants, things change, the environment has proven unpredictable every year, and the characteristics of our influent continue to evolve. When this happens, we often find we don’t have the money to re-calibrate or we must spend a lot of money to re-optimize our facilities to conditions that may never be experienced.
As we continue to upgrade our plants, add sensors, and increase the amount of data we collect, we add data points to repositories of relevant treatment data, which can span back decades.
Improved treatment of sewage and industrial effluents relies largely on data – and we have a lot of it. So how can we leverage our century’s worth of knowledge of wastewater treatment, and all the data points we have collected throughout the process? The solution is found in a not-so-new science that has become more assessible to the masses by ways of more affordable computing power; Artificial Intelligence (AI).
AI is a broad multi-disciplinary branch of computer science that looks to perform tasks that typically require human intelligence.
Operations of a plant rely on the ability to analyze various factors, such as biological relationships, pressure, flow, and water quality data to determine the days activities required to achieve certain treatment outcomes. This process can take years if not decades of practice to perfect. It also requires time that we sometimes don’t have when we must make quick decisions on the job.
Guided by permit requirements and various performance goals, AI can be leveraged as a tool to help us optimize our plants without the need for large process changes that typically require capital improvement projects. Artificial Intelligence can; (1) remind us of best management practices in real-time, (2) find unknown relationships pertinent to the efficacy of our treatment’s plants, and (3) help us manage and predict system anomality’s before they happen, all while remaining compliant, and reducing our operational expenses.
That means less energy use, less chemical consumption, and better quality water for today’s and tomorrow’s problems, through advanced data analytics and operational expertise, adapting and making continuous improvements in real time.
With the domain expertise in the water and software, Innovyze has combined all associated disciplines to create unique machine learning models for the industry. The result is water optimization intelligence, that can be implemented in both municipal and industrial water systems. Ultimately, operators can access solutions created by water engineers for water users.
No longer do we need to spend money to learn how to optimize to static conditions that may never be seen. Already, Innovyze has partnered with municipalities and industrial partners to bring the benefit of AI to their systems. These organizations are leveraging the power of AI and advance computational processing to predict outcomes and optimize operations. Now, they can increase the bottom line and save rate payers money, and further improve the management of their plants.
Innovyze is currently offering a free AI readiness assessment and return on investment report which can highlight the benefits and potential savings that AI can bring your organization across all stages of the water cycle.