2026 Commissioners' Engineering Scholarship - Prince George's County Winner: Dimitri Cromarty

Artificial Intelligence and Smart Technologies in Water Utilities 

Dimitri Cromarty, Howard University 

One of the key duties held by water providers involves delivering clean, consistent, and reasonably priced water. With cities expanding, aging pipes deteriorating, and shifting weather patterns stressing supply, new methods to boost performance have become necessary. Instead of relying solely on traditional approaches, many organizations now explore digital solutions capable of reshaping system oversight. Through real time analytics, precision instruments, and self adjusting controls, losses drop while responsiveness rises across networks. Still, adoption requires caution expenses, protection against online threats, and ethical handling of information demand close attention.

A major way artificial intelligence helps water services involves finding leaks and cutting down wasted supply. Across urban areas, old pipes let through substantial amounts of cleaned water before delivery. Throughout networks, intelligent monitors track changes in pressure, movement speed, and sound vibrations inside tubes. By studying vast flows of information instantly, machine learning models spot odd behaviors pointing to breaks or weakening infrastructure. Early problem detection allows utilities to send repair teams before minor leaks escalate into expensive system breakdowns, moving beyond routine checks or user reports. Because lost water diminishes over time, less needs processing and transporting, cutting operational expenses while preserving a critical resource.

One key way artificial intelligence helps is by forecasting breakdowns in public systems. Infrastructure like water treatment facilities, pumping stations, pipes, and control valves needs consistent upkeep; sudden malfunctions may interrupt supply and trigger high cost fixes. Instead of waiting for failure, algorithms study past repair logs, real time sensor outputs, and usage patterns to estimate wear on parts. Because of these insights, operators shift from fixing problems after they happen to planning interventions ahead of time. By acting early, organizations maintain steady operations while spending less routine checks align better with actual need, preventing both delays and wasted resources.

Using smart tools improves how we watch water cleanliness and keep people safe. Throughout cleaning and delivery setups, sensor webs take constant readings chemical levels, cloudiness, heat, among others. When odd patterns appear, artificial intelligence spots them fast, hinting at possible pollution or system flaws. Catching problems early means companies act sooner, stopping harmful water from getting to homes. Less hand collected data and lab checks are needed because machines handle tracking nonstop. Speed rises, effort drops, yet oversight grows sharper under automated eyes.

Although often linked to hardware upgrades, artificial intelligence plays a strong role in reshaping how utilities interact with people. Real time data flows from smart meters placed in residences and commercial buildings. When water use spikes unexpectedly, notifications reach users hinting at possible pipe issues inside walls or underground. By studying neighborhood level trends through machine learning tools, providers adjust rate models, plan resource saving campaigns, and shape long term network development. Responses to common questions arrive quicker now, thanks to virtual assistants running on intelligent software behind digital service portals.

Energy use drops when artificial intelligence guides pumping routines and cleaning steps in water plants often top power users across city networks. Because machines learn to predict how much water people will need, they tweak daily functions so extra flows stop when demand fades. Smarter timing means less waste, shrinking both bills and carbon output over time. Environmental gains grow quietly behind these shifts, tied closely to efficiency rather than bold claims. Outcomes align with longterm ecological targets without fanfare or exaggerated promises.

Even with clear benefits, bringing AI into water systems isn’t straightforward. Cost stands out as a key barrier. Setting up intelligent sensors, modern metering setups, or tools to handle information demands large initial spending. Since numerous water providers work under tight financial limits while maintaining outdated equipment, shifting money toward digital upgrades becomes complicated. Still, such spending may lead to lasting cost reductions by cutting down leaks, boosting power performance, or decreasing upkeep demands. When choosing options, agencies should weigh gains closely, focusing on tools that show clear progress in daily function.

Security and privacy matter just as much. Generated by smart water networks, vast amounts of data include details on how customers use water. To block breaches or digital threats, utilities need robust safeguards. Ethical handling of personal records depends on clear governance rules transparency builds trust without saying it outright.

One hurdle lies in rolling out tech without leaving people behind. Because machines learn from information fed into them, flawed inputs can skew results. Oversight matters automation should support staff judgment instead of overriding it. When teams mix engineering know how with analytical findings, choices around system upkeep gain depth. Decisions affecting community well being grow stronger through shared effort across specialties.

Coming from electrical engineering, digital systems, and hardware design, excitement builds around shaping tech for public infrastructure. Working hands on with embedded systems, sensors, and blending hardware with software revealed real power in smart solutions tackling actual challenges. What stands out water utilities sit at a crossroads of practical engineering, long term sustainability, and meaningful change in communities. Thoughtful designs in sensor networks, protected data flows, and responsive monitoring tools allow better performance in utility operations. Protecting essential water resources becomes possible through such focused engineering effort.

Smart tech and artificial intelligence are shaping how water gets managed ahead. Though expenses, safety concerns, and setup hurdles need close attention, gains could outweigh difficulties. Cutting down leaks happens when digital tools guide maintenance before pipes fail. Better data tracking means cleaner supplies reach households more consistently. Trust grows where people see usage patterns clearly shared by providers. Progress depends less on gadgets alone but on choices made by leaders who value long term results over quick fixes. Engineers focused on community needs bring stability to complex networks under pressure. Decisions today influence whether cities handle shortages calmly tomorrow. Resilience emerges not through grand plans but steady improvements guided by real feedback. Long lasting systems form where learning never stops even after goals appear met.