Abstract: System that monitors and manages a network of smart filtering containers, such as water pitchers with integrated sensors. Measurements are collected from the containers and forwarded to a centralized system, such as an Internet server; data may be analyzed to determine performance modifications or recommendations for selected containers. Centralizing the data enables discovery of patterns and correlations across containers; for example, abnormal measurements from multiple pitchers in an area may suggest contamination of the area's water supply. The centralized system may automatically update settings of containers to optimize their performance. It may send messages to users suggesting different usage patterns or configurations. It may automatically order components such as replacement filters or upgrades.

Abstract: A container for liquids that measures flow using capacitive sensor strips. Capacitance data is processed to identify points in time when liquid levels reach or pass specified levels, and flow metrics may be calculated from these points in time. Embodiments may use one or more horizontal capacitive strips, which may be located in a removable sensing package that is not in contact with the liquid in the container. Because discrete points in time are used instead of analog fluid level measurements, flow metrics are more robust than previous approaches that use vertical parallel capacitors within the container to continuously measure fluid levels. The container may have a filter, and capacitance data may be used to calculate metrics such as filter flow rate and cumulative volume through the filter, and to identify when the filter needs to be replaced. Embodiments may use UV light to sanitize the liquid or the filter.