System and method for controlling and monitoring bathroom water flow

A system for training a neural network, comprising:

• a first processor;
• a receiving device;
• and
• a transmitting device, wherein:
• the receiving device provides to the first processor a plurality of first reception signals received by a first occupancy sensor, the first reception signals corresponding to one or more features associated with one or more first sources of flowing water associated with a first property location, wherein the plurality of first reception signals comprises (i) one or more first signals based on the one or more first sources of flowing water in a bath stall being occupied by a bather in the bath stall and (ii) one or more second signals based on the one or more first sources of flowing water in the bath stall being unoccupied by the bather in the bath stall, wherein the one or more features includes a state of a bather in relation to the one or more first sources of flowing water;
• the first processor trains a neural network based on the one or more features and on the plurality of first reception signals comprising the one or more first signals and the one or more second signals to create a trained neural network, wherein the trained neural network is configured to provide one or more categorizations from a set of categorizations associated with reception signals that are based on sources of flowing water, wherein the one or more categorizations includes whether a bath space is unoccupied or occupied;
• the first processor optimizes the trained neural network for a lower-powered processor to create an optimized neural network, wherein the first processor is configured to operate at a higher power than the lower-powered processor, wherein the trained neural network is configured to optimally operate at the higher power of the first processor and the optimized neural network is configured to optimally operate at the lower power of the low-powered processor;
• and
• the first processor deploys, via the transmitting device, the optimized neural network on a remote device comprising a second processor and a second occupancy sensor of a same type as the first occupancy sensor, wherein the second processor is a same type as the lower-power processor, wherein the deployed optimized neural network causes the remote device to determine, via the second processor, a first categorization of whether a bath space is unoccupied or occupied from the set of categorizations based on second reception signals received by the second occupancy sensor from one or more second sources of flowing water of the unoccupied or occupied bath space associated with a second property location.

A method comprising:

• providing, to a first processor, a plurality of first reception signals received by a first occupancy sensor, the first reception signals corresponding to one or more features associated with one or more first sources of flowing water associated with a first property location, wherein the plurality of first reception signals comprises one or more first signals based on the one or more first sources of flowing water in at least one bath stall being occupied by at least a first bather at a first time and a second bather at a second time;
• training, by the first processor, a neural network based on the one or more features and on the plurality of first reception signals comprising the one or more first signals, wherein the trained neural network is configured to provide one or more categorizations from a set of categorizations associated with reception signals that are based on sources of flowing water, wherein the one or more categorizations includes whether a bath space is unoccupied or occupied;
• optimizing, by the first processor, the trained neural network for a lower-powered processor to create an optimized neural network, wherein the first processor is configured to operate at a higher power than the lower-powered processor, wherein the trained neural network is configured to optimally operate at the higher power of the first processor and the optimized neural network is configured to optimally operate at the lower power of the low-powered processor;
• and
• deploying, by the first processor, the optimized neural network on a remote device comprising a second processor and a second occupancy sensor of a same type as the first occupancy sensor, wherein the second processor is a same type as the lower-power processor, wherein the deployed optimized neural network causes the remote device to minimize water usage associated with one or more second sources of flowing water based on a first categorization of whether a bath space is unoccupied or occupied from the set of categorizations based on second reception signals received by the second occupancy sensor from one or more second sources of flowing water of the unoccupied or occupied bath space associated with a second property location.