Techniques for managing delivery of water or other fluids have been disclosed. A central server provides real-time data and cost analysis to a client. In addition, fluid delivery techniques provide alerts or automatic schedule suspensions to reduce risk of loss. The techniques reduce or eliminate the impact of air or gas captured with water or other fluid of a fluid delivery system. The techniques allow a preexisting fluid delivery system to be retrofitted to communicate with a central system and one or more sensors of a fluid delivery system.

Examples of a leak detection system are disclosed. In one example according to aspects of the present disclosure, a leak detection system includes a housing defining an interior, the housing connected to a component of a water distribution system. The leak detection system also includes a leak detection sensor contained within the interior of the housing and configured to detect a leak within the water distribution system. Additionally, the leak detection system includes a digital signal processing circuit in communication with the leak detection sensor.

A nozzle cap for a fire hydrant includes a cap cover comprising a metal material; and a cap body defining a cap axis, the cap body comprising: an inner housing comprising a metal material; and an outer housing comprising a non-metal material, the outer housing disposed axially between the inner housing and the cap cover, the outer housing comprising a substantially circumferential wall, the substantially circumferential wall defining a cavity between the inner housing and the cap cover, wherein a first end of the substantially circumferential wall engages the inner housing.

A device and method of pressure testing a conduit structure to determine if there is a leak in a conduit layout, which includes employing a pressure testing device having a first part having a coupling end for sealably connecting to a first conduit portion, a second part communicably connecting to the first part and having a valve connection adapted to receive one of a positive pressure source and a negative pressure source, and a pressure meter operably connected to the pressure testing device, wherein the valve is open to receive one of the positive pressure source and the negative pressure source, the pressure meter displays one of a positive pressure and a negative pressure, opening the valve to receive one of the positive pressure source and negative pressure source, and reading the pressure on the pressure meter to determine if the pressure is being maintained.

In order to keep the deterioration of water distribution pipes from progressing, a tap water management system is provided with: a water pressure detection unit for detecting the water pressure in at least one location in a water distribution pipe for carrying clean water from a water distribution site to a consumer. and transmitting the detection result as water pressure information; a deterioration detection unit for detecting deterioration in at least one location in a water distribution pipe, and transmitting the detection result as deterioration information; a water distribution planning unit for causing a water distribution plan that is a plan for water distribution pressure to be determined on the basis of information regarding past water demand; a deterioration-reducing water distribution planning unit for deciding, on the basis of the water distribution plan, the water pressure information, and the deterioration information, a deterioration-reducing water distribution plan according to the extent of deterioration; a water distribution pressure changing unit for changing the water distribution pressure of the water distribution pipe; and a water distribution pressure control unit for controlling the water distribution pressure changing unit on the basis of the deterioration-reducing water distribution plan.

An intelligent water-monitoring system includes a water-monitoring device installable inline with a building water system (e.g., at an inlet of the system). A plurality of sensors of the water-monitoring device are configured to sense properties of the building water system, such as water pressure and water flow. The water-monitoring device has a valve and a controller configured to automatically shut the valve in response to sensed data indicating a possible problem in the building water system. The intelligent water-monitoring system may include an app executable by a computing device to display information based on the sensed data.

A monitoring system includes a plurality of sensor terminals installed for a target to be measured, a base station wirelessly communicating with the sensor terminals, and a calculator communicable with the base station. The sensor terminal includes a sensor element which acquires vibration information of a target to be measured, an arithmetic unit which performs an arithmetic operation for data including the vibration information of the sensor element, and a wireless communication unit. The arithmetic unit performs a reduction process for reducing an amount of data of the sensor element. The wireless communication unit transmits data processed by the arithmetic unit to the base station. After the transmitted data is received, the base station transmits it to the calculator. The calculator includes a signal processing unit. The signal processing unit complements the reduction-processed data to acquire vibration information, and averages the vibration information for a predetermined period of time.

Disclosed herein is a method and system for predicting water leakage events in district metered area of water distribution network. The method comprises receiving historic data of water flow and water pressure associated with DMA for predicting flow data and pressure data of water in the DMA for predefined future time period. Thereafter, method comprises retrieving plurality of cluster points corresponding to the predicted flow data, the pressure data, and an anomaly score identified for each of the plurality of cluster points from machine learning model. The method detects one or more cluster points as anomaly points by comparing anomaly scores with lower bound value and upper bound value and thereafter predicts leakage events corresponding to each of the detected anomaly points. In this manner, present disclosure predicts water leakage events in DMA for future time intervals and hence necessary leakage maintenance actions may be taken to avoid such events.

A system for pipe network failure classification, may include one or more sensors, a pipe network parts database, and at least one processor communicatively networked to the one or more sensors and the pipe network parts database. The at least one processor is configured to intermittently receive sensor collected parameters from the one or more sensors, reference, upon receipt of an indication of a failure of a pipe in the pipe network, records of the pipe network parts database and retrieve one or more feature parameter values associated with the failed pipe's operational or environmental conditions, and classify the pipe failure into one of two or more failure categories associated with different failure causes, based on values of parameters associated with the failed pipe that are received from at least one of the one or more sensors or the pipe network parts database.

A data collection device and method for determining an alternative event condition is presented. The method includes receiving a first data communication including a first data value from a first sensor and determining a first event condition based on the first data value being beyond a predetermined threshold. The method further includes receiving additional data communications including additional data values from one or more second sensors, aggregating the first data value and the additional data values, and determining that the determination of the first event condition is incorrect based on the aggregated data values and a known relationship between the first sensor and the one or more second sensors. The method additionally includes determining a second event condition based on the first data value and the additional data values being beyond the predetermined threshold. An action may then be performed in response to the determination of the second event condition.