Abstract: Systems and methods are provided for automatically actuating preexisting water shut-off valves upon detection of leak conditions. A coupling of a valve actuator is connected to a handle of the valve, such that a motor of the valve actuator causes the selective opening and closing of the valve. A controller obtains water flow data from a non-intrusive flow sensor (e.g., an ultrasonic sensor) clamped onto a pipe attached to the valve in close proximity thereto, as well as obtaining additional sensor data from remote sensors disposed elsewhere in the water supply system (e.g., pressure levels measured by an in-line pressure sensor). When the controller determines a leak condition exists based upon the water flow data and the additional sensor data, it controls the actuator to close the valve. The controller may also test for leaks by periodically shutting the valve and measuring the pressure while the valve is shut.

Abstract: A sump pump system may implement adaptive learning and machine learning techniques to facilitate improved control of sump pumps. A sump pump system may implement the described techniques to generate, train, and/or implement a machine learning model that is capable of predicting or estimating one or more conditions of the sump pump system (e.g., water level in the basin, motor malfunction, stuck impeller, geyser effect, blocked outlet pipe, faulty level sensor/switch, faulty bearing, failure to engage pump at high-water mark, etc.) based on one or more detected input variables (e.g., acceleration or vibration patterns detected in water, on a pump, or on a pipe; capacitance values of water; audio signatures; electrical signatures, such as power or current draw; pump motor rotation speed; water pressure signatures or values, such as those detected at the bottom of a sump basin; etc.).

Abstract: A sump pump system enables automatic determination and utilization of frequencies for mechanical shakers for sump pumps. These techniques may be implemented to detect a fault (e.g., a stuck impeller) with a sump pump and to identify a desirable frequency at which a mechanical shaker for the sump pump should vibrate to correct the fault.

Abstract: Systems and methods are provided for automatically actuating preexisting water shut-off valves upon detection of leak conditions. A coupling of a valve actuator is connected to a handle of the valve, such that a motor of the valve actuator causes the selective opening and closing of the valve. A controller obtains water flow data from a non-intrusive flow sensor (e.g., an ultrasonic sensor) clamped onto a pipe attached to the valve in close proximity thereto, as well as obtaining additional sensor data from remote sensors disposed elsewhere in the water supply system (e.g., pressure levels measured by an in-line pressure sensor). When the controller determines a leak condition exists based upon the water flow data and the additional sensor data, it controls the actuator to close the valve. The controller may also test for leaks by periodically shutting the valve and measuring the pressure while the valve is shut.

Abstract: A sump pump system enables automatic determination and utilization of frequencies for mechanical shakers for sump pumps. These techniques may be implemented to detect a fault (e.g., a stuck impeller) with a sump pump and to identify a desirable frequency at which a mechanical shaker for the sump pump should vibrate to correct the fault.

Abstract: A sump pump system detects backflow from an outlet pipe in a sump pump system and implements control of the sump pump in light of the detected backflow (or lack thereof). The sump pump system may detect the backflow (or lack thereof) by detecting and comparing water rise rates in a sump basin before activation or engagement of the sump pump (e.g., immediately before the pump starts pumping) and after the pump has disengaged or deactivated (e.g., immediately after the pump stops pumping). The rises rates may be detected via sensors configured to detect motion or acceleration (e.g., accelerometers, inertial measurement units, or force acceleration sensors) placed in the sump basin such that detect motion of water in the basin corresponding to changing water levels.

Abstract: A sump pump system may detect and utilize motion or acceleration of water in sump basins when implementing control of sump pumps. To detect the motion or acceleration, the sump pump system may utilize a sensor that is configured to detect motion or acceleration, such as an accelerometer or gyroscope. The sump pump system may identify a water level in a sump basin based on the detected motion or acceleration, which may be compared to a reading or expected signal from the sump pump system's “typical” sensor (e.g., float switch) that is used to detect one or more water levels. In this manner, the sump pump system may detect a malfunctioning level sensor that is used by the pump to detect high-water and low-water marks at which the sump pump activates and deactivates, respectively.

Abstract: Example systems and methods for manipulating control of sump pumps in order to extend lifespans of the sump pumps are disclosed. An example method includes activating a sump pump a first time; deactivating the sump pump when a first current water level in a sump basin in which the sump pump is disposed reaches a first low-water mark; and determining, by one or more processors, a time since a last activation of the sump pump wherein the last activation occurred when the sump pump activated the first time. When the time satisfies a threshold, the method activates the sump pump at second time, determines, by one or more processors, a second current water level in the sump basin, and in response to determining that the second current water level in the sump basin is below a second low-water mark corresponding to a bottom of an impeller of the sump pump, deactivates the sump pump.

Abstract: Methods and systems for charging an electric vehicle (EV) are described herein. An EV may require additional battery power to reach a charging station. A remote server in communication with the EV or an on-board computer or mobile device in the EV may obtain data to determine a location for the EV to meet a charging vehicle. The charging vehicle may be dispatched to meet the EV and deliver power to it, enabling the EV to reach a charging station or other destination. In some examples, the charging vehicle may deliver power to the EV while both vehicles are stationary. In other examples, the charging vehicle may couple to the EV while both vehicles are in motion.

Abstract: Systems and methods are provided for automatically actuating preexisting water shut-off valves. A coupling of a valve actuator is connected to a handle of the valve, such that a motor of the valve actuator causes the selective opening and closing of the water shut-off valve. A controller monitors and controls valve actuation by controlling the motor. In addition to actuating the water shut-off valve upon detection of leak conditions, the controller may actuate the valve in order to test the water supply system or to test operation of the water shut-off valve. The operating status of the water shut-off valve may thus be monitored in order to detect or address problems with the water shut-off valve to prevent unexpected valve failure after a leak is detected.

Abstract: The following relates generally to providing virtual reality (VR) alerts to a driver of an autonomous vehicle. For example, a vehicle may be driving autonomously while the driver is watching a VR movie (e.g., on a pair of VR goggles); the driver may then receive a VR alert recommending that the driver take control of the vehicle (e.g., switch the vehicle from autonomous to manual mode). The following also relates to generating a VR feed for presenting real-time road conditions so that a user may preview a road segment. The following also relates to generating a VR feed corresponding to an event (e.g., a vehicle collision, a crime, a weather event, and/or a natural disaster).

Abstract: A structure plumbing flow simulation apparatus is described herein. An example structure plumbing flow simulation apparatus may include: (1) a reservoir configured to hold a set volume of a liquid; (2) a pump connected to the reservoir configured to pump the liquid; (3) a pressure source connected to the pump and configured to pressurize the liquid from the pump which flows to a water shut off valve downstream of the pressure source; (4) one or more pipes connected to the pressure source and adapted to be connected to the water shut off valve; and/or (5) a pipette connected to the one or more pipes.

Abstract: The present aspects relate to techniques for testing water mitigation equipment (e.g., sump pumps and sensors) using a testing platform that simulates a water intrusion environment. The methods and systems of simulating a water intrusion environment discussed herein improve testing and verification of water mitigation devices without the requirement of installing the devices in a real-world structure. A device may include (i) a liquid reservoir comprising a supply cavity configured to hold a volume of a liquid; (ii) a holding sump including a holding cavity; (iii) a first supply line coupled between the liquid reservoir and the holding sump; (iv) a testing sump including the testing cavity; (v) a second supply line coupled between the holding sump and the testing sump; and (vi) a return line coupled between the testing sump and the liquid reservoir.

Abstract: A sump pump system may implement adaptive learning and machine learning techniques to facilitate improved control of sump pumps. A sump pump system may implement the described techniques to generate, train, and/or implement a machine learning model that is capable of predicting or estimating one or more conditions of the sump pump system (e.g., water level in the basin, motor malfunction, stuck impeller, geyser effect, blocked outlet pipe, faulty level sensor/switch, faulty bearing, failure to engage pump at high-water mark, etc.) based on one or more detected input variables (e.g., acceleration or vibration patterns detected in water, on a pump, or on a pipe; capacitance values of water; audio signatures; electrical signatures, such as power or current draw; pump motor rotation speed; water pressure signatures or values, such as those detected at the bottom of a sump basin; etc.).

Abstract: Methods and systems for providing emergency heating in an electric vehicle (EV) running out of power are described herein. An on-board computer or mobile device in an EV may determine that an amount of charge remaining for powering the EV is below a threshold charge level. The on-board computer or mobile device may then route the remaining amount of charge to power a heating system in the EV to maintain a temperature in the EV above a threshold temperature level, and shut down power to other components within the EV.

Abstract: A sump pump system enables automatic determination and utilization of frequencies for mechanical shakers for sump pumps. These techniques may be implemented to detect a fault (e.g., a stuck impeller) with a sump pump and to identify a desirable frequency at which a mechanical shaker for the sump pump should vibrate to correct the fault.

Abstract: Systems and methods are provided for automatically actuating preexisting water shut-off valves upon detection of leak conditions. A coupling of a valve actuator is connected to a handle of the valve, such that a motor of the valve actuator causes the selective opening and closing of the valve. A controller obtains water flow data from a non-intrusive flow sensor (e.g., an ultrasonic sensor) clamped onto a pipe attached to the valve in close proximity thereto, as well as obtaining additional sensor data from remote sensors disposed elsewhere in the water supply system (e.g., pressure levels measured by an in-line pressure sensor). When the controller determines a leak condition exists based upon the water flow data and the additional sensor data, it controls the actuator to close the valve. The controller may also test for leaks by periodically shutting the valve and measuring the pressure while the valve is shut.

Abstract: Systems and methods are provided for automatically actuating preexisting water shut-off valves. A coupling of a valve actuator is connected to a handle of the valve, such that a motor of the valve actuator causes the selective opening and closing of the water shut-off valve. A controller monitors and controls valve actuation by controlling the motor. In addition to actuating the water shut-off valve upon detection of leak conditions, the controller may actuate the valve in order to test the water supply system or to test operation of the water shut-off valve. The operating status of the water shut-off valve may thus be monitored in order to detect or address problems with the water shut-off valve to prevent unexpected valve failure after a leak is detected.

Abstract: A sump pump system may implement adaptive learning and machine learning techniques to facilitate improved control of sump pumps. A sump pump system may implement the described techniques to generate, train, and/or implement a machine learning model that is capable of predicting or estimating one or more conditions of the sump pump system (e.g., water level in the basin, motor malfunction, stuck impeller, geyser effect, blocked outlet pipe, faulty level sensor/switch, faulty bearing, failure to engage pump at high-water mark, etc.) based on one or more detected input variables (e.g., acceleration or vibration patterns detected in water, on a pump, or on a pipe; capacitance values of water; audio signatures; electrical signatures, such as power or current draw; pump motor rotation speed; water pressure signatures or values, such as those detected at the bottom of a sump basin; etc.).

Abstract: Techniques for detecting damage to a roofing structure and initiating remediation procedures are disclosed herein. An exemplary computer-implemented method may include receiving sensor data from a plurality of sensors located proximate to the roofing structure to monitor a plurality of environmental conditions. The exemplary method may include (1) identifying, by one or more processors, a type of damage within the roofing structure based upon the sensor data; (2) locating a position of the damage within the roofing structure; determining a set of remediation services based upon the type of damage; and (3) identifying one or more remediation service providers to perform the set of remediation services. The exemplary method may include generating and transmitting an alert signal to a computing device identifying the type of damage to the roofing structure and contact information corresponding to at least one or more remediation service providers.