Carl Data Solutions Inc. announced the general availability of Auto I&I, its latest predictive analytics software product for smart city and industrial infrastructure applications that takes advantage of advanced Artificial Intelligence and Machine Learning automation. Auto I&I was successfully Beta-tested with Carl Data Solutions' partner AECOM in York Region's long-term flow monitoring program – one of the largest and most advanced flow and rainfall monitoring programs in North America. Auto I&I detects storm events that match defined rainfall criteria.

By automating Inflow and Infiltration (I&I) data gathering and reports, municipal water treatment engineers can quickly see which areas of their systems are most impacted by a storm event and visualize real-time I&I metrics on a Geographic Information System (GIS) map. Key benefits of Auto I&I include: Predictive detection of deterioration on infrastructure systems allowing for better planning and data-driven evergreening efficiency Automated tasks including detection of weather patterns reducing manual processes and increasing infrastructure needs forecasting capabilities Immediate visualizations of water utility infrastructure performance based on storm events allowing for better and faster decision making Replaces static reports with dynamic SaaS-based analytics providing a richer user experience, benefiting strategic management decision-making and facilitating governance-driven organizations York Region stretches north from Toronto to Lake Simcoe and includes many hectares of protected Greenbelt within its nine local municipalities. Since implementing an Inflow and Infiltration Reduction Strategy in 2011, the Region has made continuous progress towards reaching a 2031 I&I reduction target of 40 million litres per day.

By 2020 it had exceeded its interim target two years ahead of schedule with a total reduction of 22.87 million litres per day. It has done so by establishing leadership in I&I reduction through promoting innovation, adaptation, and digital integration in data collection and analysis to drive actions to the long-term reduction target.