NZ756702A - Systems and methods for forecasting a water level in a water storage receptacle - Google Patents
Systems and methods for forecasting a water level in a water storage receptacleInfo
- Publication number
- NZ756702A NZ756702A NZ756702A NZ75670219A NZ756702A NZ 756702 A NZ756702 A NZ 756702A NZ 756702 A NZ756702 A NZ 756702A NZ 75670219 A NZ75670219 A NZ 75670219A NZ 756702 A NZ756702 A NZ 756702A
- Authority
- NZ
- New Zealand
- Prior art keywords
- water
- water level
- storage receptacle
- water storage
- forecasting
- Prior art date
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 508
- 238000000034 method Methods 0.000 claims description 37
- 238000010801 machine learning Methods 0.000 claims description 19
- 230000001537 neural Effects 0.000 claims description 6
- YHXISWVBGDMDLQ-UHFFFAOYSA-N moclobemide Chemical compound C1=CC(Cl)=CC=C1C(=O)NCCN1CCOCC1 YHXISWVBGDMDLQ-UHFFFAOYSA-N 0.000 claims description 5
- 238000004364 calculation method Methods 0.000 claims description 4
- 230000001419 dependent Effects 0.000 claims 1
- 238000010586 diagram Methods 0.000 description 8
- UIIMBOGNXHQVGW-UHFFFAOYSA-M buffer Substances [Na+].OC([O-])=O UIIMBOGNXHQVGW-UHFFFAOYSA-M 0.000 description 5
- 210000001035 Gastrointestinal Tract Anatomy 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000006011 modification reaction Methods 0.000 description 2
- 238000009877 rendering Methods 0.000 description 2
- 239000012536 storage buffer Substances 0.000 description 2
- 238000004891 communication Methods 0.000 description 1
- 238000001983 electron spin resonance imaging Methods 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 230000002708 enhancing Effects 0.000 description 1
- 239000000835 fiber Substances 0.000 description 1
- 238000011010 flushing procedure Methods 0.000 description 1
- 230000014759 maintenance of location Effects 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 238000010295 mobile communication Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000001932 seasonal Effects 0.000 description 1
- 230000005236 sound signal Effects 0.000 description 1
- 230000000007 visual effect Effects 0.000 description 1
Abstract
A system and method is provided for forecasting a water level in a water storage receptacle, the water level transmitted to at least one computing device connected to a communications network, the system including at least one processor in operable connection with a memory configured by a database, the processor configured to: receive an initial water level in the water storage receptacle; receive a water storage receptacle location; determine from the water storage receptacle location, an associated rainfall catchment area; retrieve from a database an actual rainfall recorded for the location; determine a change in water level in the water storage receptacle based on the catchment area and the actual rainfall; retrieve an estimated water consumption rate for the water storage receptacle; and calculate a current water level based on the initial water level, the change in water level and the estimated water consumption rate; and display the current water level to a user. the processor configured to: receive an initial water level in the water storage receptacle; receive a water storage receptacle location; determine from the water storage receptacle location, an associated rainfall catchment area; retrieve from a database an actual rainfall recorded for the location; determine a change in water level in the water storage receptacle based on the catchment area and the actual rainfall; retrieve an estimated water consumption rate for the water storage receptacle; and calculate a current water level based on the initial water level, the change in water level and the estimated water consumption rate; and display the current water level to a user.
Description
Systems and Methods for Forecasting a Water Level in a Water Storage
Receptacle
This application claims priority from Australian Application No. 2018903173
filed on 29 August 2018, the contents of which are to be taken as incorporated herein
by this reference.
Technical Field
The present invention relates generally to systems and methods for
forecasting the water level in a water storage receptacle, and more particularly the
use of computers to facilitate real-time delivery of modelling and forecasting of the
water level to a user.
Background of Invention
Although water is innately a renewable resource, providing reliable access
to water can be a challenge, particularly in regions that are not connected to a mains
water supply. That is, if rainfall is not occurring in the locations where it is needed,
then water storages in those areas are not being replenished. Moreover, due to
heightened awareness of the prevalence of drought in Australia and elsewhere, even
those households having access to a mains water supply are installing water storage
receptacles or tanks in increasing numbers to capture and store water for use inside
or outside the home, i.e. for flushing toilets or irrigating the garden, in addition to
those who have always relied on their own water storage to supply household,
commercial, industrial and agricultural purposes.
Thus it will be understood that it is useful to monitor the water level within
water storage tanks. In some cases, monitoring is necessary since an alternative
source of water must be obtained if water levels are running low, or in other cases, for
interest.
Various methods and apparatus for measuring the water level within a
storage tank are known, including manual means such as using a stick, or knocking
on the side of the tank to assess acoustically where the approximate water level
resides, or sensor based systems including pressure sensors, depth sensors, float
systems and the like. However, the manual means exemplified require regular input
from a user which may be inconvenient. Moreover, continuous monitoring of sensor
based systems at a remote location has the disadvantage of requiring power to be
provided to the sensors at all times in what may be a remote location. Additionally,
sensor based monitoring systems cause power and data to be constantly consumed
resulting in significant costs.
Furthermore, knowing the current water level in the water storage
receptacle does not alone assist a user in understanding whether the water level is
above or below a critical level, nor does it indicate when it is necessary to arrange for
a top up of the water storage levels by a water carter. Generally, the decision to order
water is made based on a “gut feel”.
Therefore it would be desirable to provide means for monitoring, with a
reasonable degree of accuracy, the water level in a water storage tank over time,
without having to make continuous measurements and additionally to reliably forecast
when the water level will fall below a critical level.
[0008] A reference herein to a patent document or other matter which is given as
prior art is not to be taken as an admission that that document or matter was known
or that the information it contains was part of the common general knowledge as at
the priority date of any of the claims.
Summary of Invention
[0009] According to an aspect of the present invention, there is provided a system
for forecasting a water level in a water storage receptacle, the water level transmitted
to at least one computing device connected to a communications network, the system
including at least one processor in operable connection with a memory configured by
a database, the processor configured to receive an initial water level in the water
storage receptacle; receive a water storage receptacle location; determine from the
water storage receptacle location, an associated rainfall catchment area; retrieve from
a database an actual rainfall recorded for the location; determine a change in water
level in the water storage receptacle based on the catchment area and the actual
rainfall; retrieve an estimated water consumption rate for the water storage
receptacle; and calculate a current water level based on the initial water level, the
change in water level and the estimated water consumption rate; and display the
current water level to a user.
The processor is preferably further configured to forecast a period of time
remaining before the water level drops below a predetermined threshold based on the
current water level and the water consumption estimate.
In some embodiments, the system includes a water storage receptacle
location input component which receives an input from the user in the form of an
address.
The system may further include a global positioning system enabled device
positioned in the vicinity of the water storage and a water storage receptacle location
input component which receives coordinates or a latitude or longitude from the global
positioning system enabled device.
The system may provide access to a database storing overhead imagery
wherein determining the associated rainfall catchment area includes identifying,
based on the water storage receptacle location, a nearby rainfall catchment area from
the overhead imagery and estimating a size of the rainfall catchment area. The rainfall
catchment area may comprise a roof.
In some embodiments, the system includes a water storage receptacle
volume input component for receiving a receptacle volume from the user.
[0015] The change in water level may be calculated at intervals based on a
volume of water that should have flowed into the tank based on the size of the rainfall
catchment area and the actual rainfall recorded at the location since a previous
calculation of the change in water level. The intervals at which the change in water
level is calculated may be regular intervals.
[0016] In certain embodiments, the estimated water consumption rate is derived
from an estimated volume of water consumed per person per interval and the number
of residents known to reside at the water storage receptacle location.
According to some embodiments, the estimated water consumption rate for
the water storage receptacle is determined by retrieving at least two water levels
received for the water storage receptacle and determining the consumption rate over
a period of time based on the change in water level from a first water level to a
second water level together with any volume of water that should have flowed into the
tank based on the size of the rainfall catchment area and the actual rainfall recorded
at the location during the period of time.
Preferably, more than two water levels are received for the water storage
receptacle and more than one consumption rate is calculated, each consumption rate
being determined for a different period of time and the estimated consumption rate is
determined by calculating an average of the more than one consumption rates.
[0019] The estimated water consumption rate may be determined via application
of machine learning techniques. The machine learning techniques may include
Random Forecast, Neural Networks, ARIMA or regression methods.
In some embodiments, forecasting a period of time remaining before the
water level drops below a predetermined threshold involves retrieving a most recent
water level, based on the estimated consumption rate determining a period of time in
which the water level will reach zero and checking whether rainfall is forecast during
the period of time, and if no rain is forecast, displaying the period of time in which the
water level will reach zero to the user and if rain is forecast during the period of time
in which the water level will reach zero, forecasting the volume of water that should
flow into the tank based on the size of the rainfall catchment area and the rainfall
forecast for the location and recalculating the period of time in which the water level
will reach zero.
According to another aspect of the present invention, there is provided a
method for forecasting a water level in a water storage receptacle, the method
including the following steps: receiving an initial water level in the water storage
receptacle; receiving a water storage receptacle location; determining from the water
storage receptacle location, an associated rainfall catchment area; retrieving from a
database an actual rainfall determined for the location; determining a change in water
level in the water storage receptacle based on the catchment area and the actual
rainfall; retrieving an estimated water consumption rate for the water storage
receptacle; and calculating a current water level based on the initial water level, the
change in water level and the estimated water consumption rate; and displaying the
current water level to a user.
The method may further include the step of forecasting a period of time
remaining before the water level drops below a predetermined threshold based on the
current water level and the water consumption estimate.
In some embodiments, the step of receiving a water storage receptacle
location involves receiving an input from the user in the form of an address. In other
embodiments, the step of receiving a water storage receptacle location involves
receiving coordinates or a latitude or longitude from a GPS enabled device positioned
in the vicinity of the water storage receptacle location.
The step of determining the associated rainfall catchment area may include
identifying, based on the water storage receptacle location, a nearby rainfall
catchment area from overhead imagery and estimating a size of the rainfall catchment
area. The rainfall catchment area may comprise a roof.
[0025] In some embodiments, the method further includes the step of receiving an
input of a water storage receptacle volume.
The step of calculating the change in water level may be executed at
intervals based on a volume of water that should have flowed into the tank based on
the size of the rainfall catchment area and the actual rainfall recorded at the location
since a previous calculation of the change in water level. The intervals at which the
step of calculating the change in water level is executed may be regular intervals.
In certain embodiments, the step of calculating the estimated water
consumption rate involves deriving an estimated water consumption rate from an
estimated volume of water consumed per person per interval and the number of
residents known to reside at the water storage receptacle location.
The step of calculating the estimated water consumption rate may involve
retrieving at least a first water level received at a first time and a second water level
received at a second time and determining a consumption rate over a period of time
elapsed between the first time and the second time based on the change in water
level together with any volume of water that should have flowed into the tank based
on the size of the rainfall catchment area and the actual rainfall recorded at the
location during the period of time.
Preferably, more than two water levels are received for the water storage
receptacle and more than one consumption rate is calculated, each consumption rate
being determined for a different period of time and the estimated consumption rate is
determined by calculating an average of the more than one consumption rates.
The estimated water consumption rate may be determined via application
of machine learning techniques. The machine learning techniques may include
Random Forecast, Neural Networks, ARIMA or regression methods.
[0031] In some embodiments, the step of forecasting a period of time remaining
before the water level drops below a predetermined threshold involves retrieving a
most recent water level and based on the estimated consumption rate determining a
period of time within which the water level will reach zero, checking whether rainfall is
forecast during the period of time, and if no rain is forecast during the period of time
displaying the period of time in which the water level will reach zero to the user, and if
rain is forecast during the period of time in which the water level will reach zero,
forecasting the volume of water that should flow into the tank based on the size of the
rainfall catchment area and the rainfall forecast for the location and recalculating the
period of time in which the water level will reach zero.
[0032] According to another aspect of the present invention, there is provided a
non-transitory computer readable media embodied with software for forecasting a
water level in a water storage receptacle, the software when executed configured to
receive an initial water level in the water storage receptacle; receive a water storage
receptacle location; determine from the water storage receptacle location, an
associated rainfall catchment area; retrieve from a database an actual rainfall
determined for the location; determine a change in water level in the water storage
receptacle based on the catchment area and the actual rainfall; retrieve an estimated
water consumption rate for the water storage receptacle; and calculate a current
water level based on the initial water level, the change in water level and the
estimated water consumption rate; and display the current water level to a user.
Brief Description of Drawings
Embodiments of the invention will now be described with reference to the
accompanying drawings. It is to be understood that the embodiments are given by
way of illustration only and the invention is not limited by this illustration. In the
drawings:
[0034] Figure 1 shows a system diagram of an exemplary embodiment of a
system for monitoring a water level in a water storage receptacle.
Figure 2 shows a schematic diagram showing the processes that interact
according to an embodiment of the present invention.
Figure 3 shows a process flow diagram of an exemplary method for
calculating a current water level in the water storage receptacle.
Figure 4 shows a process flow diagram of an exemplary method for
determining the water consumption rate for the water storage receptacle.
Figure 5 shows a process flow diagram of an exemplary method for
forecasting the expected water level in a water storage receptacle.
[0039] Figure 6 shows an exemplary graphical use interface for the displaying the
water level forecast to a user.
Figure 7 shows an exemplary computing device in a computer network
which may be used to implement the present invention.
Detailed Description
[0041] Referring to Figure 1, there is shown a system 100 for implementing the
method for forecasting the water level in a water storage receptacle 110. The water
storage receptacle 110 is associated with and located generally nearby to a structure
or building 120, which could take the form of a private residence, business or
government owned building. By associated with, it will be understood that the water
storage receptacle 110 will store water that is utilised by the residents or other
inhabitants of the building or structure 120. Typically, the building or structure 120 will
include a roof structure 130 which may serve as the only, or one of several rainfall
catchment areas associated with the water storage receptacle 110. That is, the
rainfall catchment area 130 provides a catchment area from which rainfall flows into
water storage receptacle 110.
A communications network includes one or more servers 170 including one
communicatively coupled to a wireless communications network 160. The server 170
including at least one processor in operable connection with a memory configured by
a database 180. The communications network could take the form of a packet
switching network, such as the Internet, a network WLAN or a cloud computing
environment. The cloud computing environment includes a set of network services
that are capable of being used remotely over a network, and the method described
herein may be implemented as a set of instructions stored in a memory and executed
by a cloud computing platform.
Throughout the description there are references to computers as example
devices where information is moved to and from. In other embodiments, the
implemented devices are smartphones, tablets, laptop computers, desktop
computers, server computers, among other forms of computer systems.
User 150 may include an owner, resident or manager of building or
structure 120 having an interest in the water level in the water storage receptacle 110.
That is, user 150 wishes to know whether the water level in the water storage
receptacle 110 has or will drop below a predetermined threshold and is approaching
critical levels. This provides user 150 with an opportunity to take measures to
replenish the water level using means other than relying on rainfall. For instance, by
having water carted to the water storage receptacle 110. The user 150 is provided
with a user computer 140 which may include any one or more of a mobile
communication device, tablet, desktop computer or the like.
[0045] In some embodiments, the water storage receptacle 110 includes a sensor
(not shown) for sensing the water level, either on demand or at predetermined
intervals. Such a water level sensor may be a pressure sensor, ultrasonic sensor,
float system, or the like. In the alternative, it will be understood that there are other
means for determining the current water level in the water storage receptacle
including banging on the wall of the tank to sense the approximate water level
acoustically, manually reading a measuring device placed inside of the water tank
which can be used to manually ascertain a current water level that can be input into
the system by the user 150 using the mobile communications device. Regardless of
the means for determining the water level, it will be understood that the current, or at
least a recent water level, is a necessary input into the forecasting model.
[0046] In some embodiments, the water storage receptacle 110 is provided with a
GPS receiver (not shown) or the mobile communications device 140 associated with
the user 150 is GPS enabled in order that a location of the water storage receptacle
can be accurately determined. That is, in the case of the mobile communications
device being GPS enabled, determining the location of the water storage receptacle
110 can be determined by the user 150 positioning the mobile communications device
in proximity to the water storage receptacle to ascertain the GPS location. Other
means of determining the water storage receptacle location include prompting the
user 150 to input an address for a location associated with the water storage
receptacle on registration for the water level forecasting service. The requirement for
the water storage receptacle location as an input to the forecasting model will become
apparent below. Other data input by the user 150 during registration for the water
level forecasting service includes a count of the number of residents or people
associated with the building or structure. The number of people occupying the
building is relevant to determination of water consumption which is described in more
detail below.
A further input into the forecast model is the rainfall catchment area, i.e.
dimensions thereof. It will be understood that catchment area data may be obtained,
for example, from overhead imagery that could be supplied by satellite 190 and stored
in database 195. Rainfall catchment areas such as rooves are readily discernible from
overhead imagery provided, for example, by Google Earth and Google Maps, Landsat
and ESRI and the like, and the roof area can be readily estimated from the overhead
imagery and extrapolated into real world dimensions to provide a relatively accurate
estimate of the rainfall catchment area. In turn, knowing the rainfall catchment area
can be used to estimate the rainfall that would flow into the associated water storage
receptacle for different rates of rainfall.
Referring now to Figure 2 there is shown a schematic diagram 200
showing the various processes that interact to provide water level forecasts to a user
150 (see Figure 1). Sensed and calculated data concerning water storage receptacle
110 (see Figure 1) is stored in one or more databases 210 which are accessible via
communications network 160, also described with reference to Figure 1. This includes
sensor readings taken at the water storage receptacle 110 to determine the current
water level.
Using other inputs such as the rainfall catchment area, which is
approximated in the manner previously described, together with local rainfall data and
water consumption rates, the determination of which is detailed below, a future water
level of the water storage receptacle is forecast at 230. This model can be executed
at predetermined intervals or on a regular schedule, say every 12 to 24 hours to
provide a current, up-to-date estimate of current water levels in the water storage
receptacle.
In an embodiment, the present invention may be provided in a number of
locations over a geographical area and the water storage receptacle systems may
communicate with one another. For example, tens, hundreds or thousands of units
(which may be battery powered) may be present and in-use at any given point in time
over a particular geographic location. Data from a water storage receptacle in a
particular geographic location may be provided to another water storage receptacle
system – to improve accuracy and avoiding the need for duplication in sending data
from water storage receptacle systems which are in the same geographic location
with similar weather patterns.
The sensor associated with the water storage receptacle system may be
both low power and low frequency avoiding complexity in terms of electrical and RF
interference and, in turn, increasing the ease of which data may be reliably captured
and transmitted wirelessly. For example sensors utilising a low-power narrowband
are low cost and provide long battery life.
The sensors may be provided across a geographical area in a distributed
wireless sensor system via a low-density mesh of base stations - avoiding the cost
and complexity of high-density mesh systems. A messaging protocol system based
on IEEE 802.15.4, such as ZigBee, may be used with the sensor in order to simplify
the messaging structures and network mesh controls.
Advantageously, the physical implementation of the sensors allows for the
data to be provided in a reliable and low cost manner.
At 240, a water consumption rate is estimated for the water storage
receptacle. The water consumption rate is based on the historical actual measured or
sensed water levels for the water storage receptacle, together with actual rainfall, i.e.
the rate at which the water levels are being replenished by rainfall. Determination of
water consumption rate involves a machine learning element. For example, the
system is trained over time to determine a typical water consumption rate for a
particular household or business, based on regular readings of the actual water level
in the water storage receptacle, whilst correlating that usage data with actual rainfall
data. The rainfall data and water consumption rates will be understood to have a
seasonal element, for example, water consumption rates will typically increase over
the warmer summer months and decrease over the cooler winter months. Moreover,
typically higher levels of rainfall will be recorded, during the cooler, wetter season,
than during the hotter, drier season. The water consumption model can be executed
on a regular schedule, say every 7 to 10 days to provide a current, up-to-date water
consumption rate.
At 250, a forecasting model is executed to predict how long the current
water level in the water storage receptacle will last based the water consumption rate
and forecast rainfall. More detail regarding the respective models is provided with
reference to Figures 3 to 5 below.
A user 150 associated with mobile communications device 150 makes a
request to forecast the water level for a water receptacle at a particular location. In
response the system 100 examines data associated with one or more data sources
which may be stored on databases 180 and 195 which are accessible via a
telecommunications network. Specifically, the processor is configured to forecast a
period of time remaining before the water level drops below a predetermined
threshold based on the current water level, the water consumption rate determined for
the water storage receptacle and the forecast rainfall.
[0057] Referring now to Figure 3, there is shown a process flow diagram for the
method for calculating the current water level in the water storage receptacle. This
process flow is an expansion of process 230 referenced in Figure 2. The water level is
sensed or measured at predetermined intervals employing means described with
reference to Figure 2. Each time a current water level is sensed at step 310, at step
320 there is a decision point to query whether any rainfall has occurred since the
immediately previous water level reading. If the answer to the query at step 320 is no,
then at step 330 a current water level is determined having regard to the current
volume of water residing in the water storage receptacle, the water consumption rate
per person, per day, the number of residents/people associated with the water
storage receptacle and the period of time elapsed since the immediately previous
water level reading, i.e. :
Result_1 = Max (A - B * C * D, 0)
wherein:
A = Current water volume
B = Volume consumed per person per day
C = Number of residents
D = Time since last water level reading
On the other hand, in the event that the answer to the query at step 320 is
yes, then at step 340 the amount of water assumed to have flowed into the water
storage receptacle since the immediately previous water level reading is calculated.
This involves determining, via weather data, the amount of rainfall recorded at the
location associated with the water storage receptacle, in the period since the
immediately previous water level reading, together with the estimated rainfall
catchment area and the time elapsed since the previous water level reading, i.e. :
Result_2 = (A * B) * C
wherein:
A = Rainfall in location, over period
B = Estimated rainfall catchment area
C = Time since last reading
At step 350 the the new water level (Result_1) and the amount of water
that would have flowed into the water storage receptacle since the immediately
previous water level reading (Result_2) are stored in a database 180 where they can
be retrieved as inputs into related models.
Referring now to Figure 4, there is shown a process flow diagram for
calculating a water consumption rate for the water storage receptacle. This process
flow is an expansion of process 240 referenced in Figure 2. As described with
reference to Figure 2, determining the water consumption rate involves the application
of machine learning and is preferably calculated over a number of water storage
receptacles, to provide an average water consumption rate per person, which may be
seasonally adjusted as required. The use of readings from multiple water storage
receptacles will be understood to enhance the machine learning aspects by providing
a larger data store for training the system, ultimately resulting in more accurate
determination of typical water consumption rates.
The machine learning component uses previously calculated water
consumption rates and divides those patterns into features and utilises those features
to apply various machine learning techniques to see which technique provides an
appropriate level of accuracy, i.e. best fit. That machine learning technique is then
selected to calculate the water consumption rate for the next periods. For each water
consumption rate that is calculated, the accuracy is subsequently checked against
actual measured water level data for the period. If the accuracy of the applied
machine learning technique drops below a predetermined threshold, then alternative
machine learning techniques are applied to the existing water consumption rate data
to select the technique providing optimal accuracy. Examples of suitable machine
learning techniques include Random Forecast, Neural Networks with various
configurations, ARIMA and various regression methods.
[0062] Firstly, at step 410 the process starts and at step 420 a previous water
level reading is retrieved for preferably more than one water storage receptacle from
the database. For example, in the case where a water level is being sensed or
measured at 12 hour intervals for a group of water storage receptacles, the following
readings are retrieved for each of the water storage receptacles:
i) immediate last reading (i.e. 12 hours ago);
ii) preceding day reading (i.e. 24 hours ago);
iii) one week ago reading; and
iv) one month ago reading.
At step 430, for each time period, confirm that are at least two readings, i.e.
associated with two different water storage receptacles are available to ensure
sufficient data is available for training of machine learning techniques at decision point
labelled as step 440. Subsequently, at step 450, for each water storage receptacle,
and for each pair of readings, a change in water volume over the time period is
determined, together with the rainfall recorded at the location over the time period,
and the change in time, i.e. = the time period, to calculate the water consumption rate
for that particular water storage receptacle over the period, i.e.:
Result = (A + B) / C
wherein:
A = Change in volume over the period
B = Rainfall over the period
C = Change in time
The calculated value is then stored into a data store buffer. Stored values are
subsequently sent to a neural network or similar for learning and testing recognition.
At step 460, the water consumption rate is determined for a particular
period by calculating an average consumption rate from the values stored in the data
store buffer. At step 470 the recently calculated water consumption rate is stored for
later retrieval.
Referring now to Figure 5, there is shown a process flow for forecasting a
future water level for the storage receptacle based on the current water level
calculated according to the process described with reference to Figure 3 and the
water consumption rate calculated according to the process described with reference
to Figure 4, together with a rainfall forecast for the location obtained from weather
data. This process flow is an expansion of process 250 referenced in Figure 2.
Firstly, at step 510 the process starts and at step 520 a previous water
level reading is retrieved for the water storage receptacle queried by the user. At step
530, the number of days X until the water level will drop below a predetermined
threshold, i.e. for example, when the tank will be empty, is determined based on the
current water level retrieved at step 520 and the recently calculated water
consumption rate stored in the data store buffer. The number of days X to empty is
stored in another temporary data storage buffer together with the most recent water
level sensed or measured for the water storage receptacle.
At step 540, if the water level in the buffer indicates that the water storage
receptacle is currently full, then the process is terminated at step 545 and the output
displayed to the user will be the number of days X until the water level will drop below
the predetermined threshold. If the tank is not full, at step 550 the weather data is
queried to determine whether any rainfall is forecast in the following period.
In the event that rainfall is forecast, at step 555 an amount of water that will
flow into the water storage receptacle. This is calculated based on the rainfall forecast
for the location over a period, the rainfall catchment area associated with the water
storage receptacle; and the time elapsed since the last water level reading, i.e.:
Result_B = (A * B) * C
wherein:
A = Rainfall at location, over period
B = Rainfall catchment area
C = Time elapsed since last water level reading
In the event that no rainfall is forecast, at step 560 a new water level is
determined based on the current water level, the water consumption rate per person,
the number of people residing at the location and the time elapsed since the last
water level reading, i.e.:
Result_A = Max (A - B * C * D, 0)
wherein:
A = Last water level reading
B = Water consumption rate
C = Number of residents at location
D = Time elapsed since last water level reading
At step 570, the new water level, i.e. Result_A and the amount of water
predicted to flow into the water storage receptacle as a result of the forecast rainfall,
i.e. Result_B, are combined and added to the data storage buffer. If the water level in
the buffer indicates that the tank is full at step 540, then the process is terminated at
step 545 and the output displayed to the user will be the number of days X until the
water level will drop below a predetermined threshold. If the tank is not full, at step
550 the weather data is queried as to whether there is any rainfall forecast and the
process flow continues.
[0071] Referring now to Figure 6, there is shown a graphical user interface (GUI)
on a mobile communications device for presenting the water level forecast to a user in
an easy to interpret format. The GUI includes a water level indicator 620 as a
percentage of full, e.g. showing 85% full, together with a count of days 630 remaining
until the water level drops below a predetermined threshold. Optionally, the GUI may
include an order water icon, which links directly to an online ordering facility or
optionally a telephone number for a local water carter.
Referring now to Figure 7, there is shown schematically, an illustrative
computer 700 on which any aspect of the present disclosure may be implemented. In
the embodiment shown in Figure 7, the computer 700 includes a processing unit 705
having one or more processors and a non-transitory computer-readable storage
medium 710 that may include, for example, volatile 715 and/or non-volatile 720
memory. The memory 710 may store one or more instructions to program the
processing unit 705 to perform any of the functions described herein. The computer
700 may also include other types of non-transitory computer-readable mediums, such
as storage 725 (e.g., one or more disk drives) in addition to the system memory 710.
The storage 725 may also store one or more application programs and/or external
components used by application programs (e.g., software libraries), which may be
loaded into the memory 730.
The computer 700 may have one or more input devices and/or output
devices, such as devices 735 and 740 illustrated in Figure 7. These devices can be
used, among other things, to present a user interface. Examples of output devices
that can be used to provide a user interface include printers or display screens for
visual presentation of output and speakers or other sound generating devices for
audible presentation of output. Examples of input devices that can be used for a user
interface include keyboards and pointing devices, such as mice, touch pads, and
digitizing tablets. As another example, the input devices 740 may include a
microphone for capturing audio signals, and the output devices 735 may include a
display screen for visually rendering, and/or a speaker for audibly rendering,
recognized text.
As shown in Figure 7, the computer 700 may also comprise one or more
network interfaces (e.g., the network interface 745) to enable communication via
various networks (e.g., the network 750). Examples of networks include a local area
network or a wide area network, such as an enterprise network or the Internet. Such
networks may be based on any suitable technology and may operate according to
any suitable protocol and may include wireless networks, wired networks or fiber optic
networks.
It will be understood that the method and system of the present invention
solves a problem for users reliant on water storage who find it difficult to determine
how long the current water storage levels will last. Conventionally, the appropriate
time to order water to replenish water storage levels is based on “gut feel” or in some
cases, when the water runs out, which leads to inconvenience, and could result in
unnecessary costs and ineffective use of natural resources. The methods described
herein take the guesswork out of determining how long current water storage levels
will last and provide means for reliably forecasting when the water storage level will
drop below a critical predetermined threshold. This is achieved by using a
combination of data sources, for example to monitor the actual water level in the
water storage receptacle, track actual and forecast rainfall for the location, determine
the rainfall catchment area, and machine learning to determine water consumption
rates.
Where the terms "comprise", "comprises", "comprised" or "comprising" are
used in this specification (including the claims) they are to be interpreted as specifying
the presence of the stated features, integers, steps or components, but not precluding
the presence of one or more other features, integers, steps or components, or group
thereof.
While the invention has been described in conjunction with a limited
number of embodiments, it will be appreciated by those skilled in the art that many
alternative, modifications and variations in light of the foregoing description are
possible. Accordingly, the present invention is intended to embrace all such
alternative, modifications and variations as may fall within the spirit and scope of the
invention as disclosed.
The present application may be used as a basis or priority in respect of one
or more future applications and the claims of any such future application may be
directed to any one feature or combination of features that are described in the
present application. Any such future application may include one or more of the
following claims, which are given by way of example and are non-limiting in regard to
what may be claimed in any future application.
Claims (31)
1. A system for forecasting a water level in a water storage receptacle, the water level transmitted to at least one computing device connected to a communications 5 network, the system including at least one processor in operable connection with a memory configured by a database, the processor configured to: a. receive an initial water level in the water storage receptacle; b. receive a water storage receptacle location; c. determine from the water storage receptacle location, an associated 10 rainfall catchment area; d. retrieve from a database an actual rainfall recorded for the location; e. determine a change in water level in the water storage receptacle based on the catchment area and the actual rainfall; f. retrieve an estimated water consumption rate for the water storage 15 receptacle; and g. calculate a current water level based on the initial water level, the change in water level and the estimated water consumption rate; and h. display the current water level to a user.
2. The system for forecasting a water level in a water storage receptacle 20 according to claim 1, wherein the processor is further configured to forecast a period of time remaining before the water level drops below a predetermined threshold based on the current water level and the water consumption estimate.
3. The system for forecasting a water level in a water storage receptacle according to claim 1 or 2, further including a water storage receptacle location input 25 component which receives an input from the user in the form of an address.
4. The system for forecasting a water level in a water storage receptacle according to claim 1 or 2, the system further including a global positioning system enabled device positioned in the vicinity of the water storage and a water storage receptacle location input component which receives coordinates or a latitude or longitude from the global positioning system enabled device.
5. The system for forecasting a water level in a water storage receptacle 5 according to claim 3 or 4, further including access to a database storing overhead imagery wherein determining the associated rainfall catchment area includes identifying, based on the water storage receptacle location, a nearby rainfall catchment area from the overhead imagery and estimating a size of the rainfall catchment area. 10
6. The system for forecasting a water level in a water storage receptacle according to claim 5, wherein the rainfall catchment area comprises a roof.
7. The system for forecasting a water level in a water storage receptacle according to any one of claims 1 to 6, further including a water storage receptacle volume input component for receiving a receptacle volume from the user. 15
8. The system for forecasting a water level in a water storage receptacle according to claim 7, wherein the change in water level is calculated at intervals based on a volume of water that should have flowed into the tank based on the size of the rainfall catchment area and the actual rainfall recorded at the location since a previous calculation of the change in water level. 20
9. The system for forecasting a water level in a water storage receptacle according to claim 8, wherein the intervals at which the change in water level is calculated are regular intervals.
10. The system for forecasting a water level in a water storage receptacle according to any one of claims 1 to 9, wherein the estimated water consumption rate 25 is derived from an estimated volume of water consumed per person per interval and the number of residents known to reside at the water storage receptacle location.
11. The system for forecasting a water level in a water storage receptacle according to any one of claims 1 to 10, wherein the estimated water consumption rate for the water storage receptacle is determined by retrieving at least two water levels 30 received for the water storage receptacle and determining the consumption rate over a period of time based on the change in water level from a first water level to a second water level together with any volume of water that should have flowed into the tank based on the size of the rainfall catchment area and the actual rainfall recorded at the location during the period of time. 5
12. The system for forecasting a water level in a water storage receptacle according to any one of claims 1 to 11, wherein more than two water levels are received for the water storage receptacle and more than one consumption rate is calculated, each consumption rate being determined for a different period of time and the estimated consumption rate is determined by calculating an average of the more 10 than one consumption rates.
13. The system for forecasting a water level in a water storage receptacle according to any one of claims 10 to 12, wherein the estimated water consumption rate is determined via application of machine learning techniques.
14. The system for forecasting a water level in a water storage receptacle 15 according to claim 13, wherein the machine learning techniques include Random Forecast, Neural Networks, ARIMA or regression methods.
15. The system for forecasting a water level in a water storage receptacle according to any one of claims 1 to 14, wherein forecasting a period of time remaining before the water level drops below a predetermined threshold involves retrieving a 20 most recent water level, based on the estimated consumption rate determining a period of time in which the water level will reach zero and checking whether rainfall is forecast during the period of time, and if no rain is forecast displaying the period of time in which the water level will reach zero to the user and if rain is forecast during the period of time in which the water level will reach zero, forecasting the volume of 25 water that should flow into the tank based on the size of the rainfall catchment area and the rainfall forecast for the location and recalculating the period of time in which the water level will reach zero.
16. A method for forecasting a water level in a water storage receptacle, the method including the following steps: 30 a. receiving an initial water level in the water storage receptacle; b. receiving a water storage receptacle location; c. determining from the water storage receptacle location, an associated rainfall catchment area; d. retrieving from a database an actual rainfall determined for the location; 5 e. determining a change in water level in the water storage receptacle based on the catchment area and the actual rainfall; f. retrieving an estimated water consumption rate for the water storage receptacle; and g. calculating a current water level based on the initial water level, the 10 change in water level and the estimated water consumption rate; and h. displaying the current water level to a user.
17. The method for forecasting a water level in a water storage receptacle according to claim 16, wherein the method further includes the step of forecasting a period of time remaining before the water level drops below a predetermined 15 threshold based on the current water level and the water consumption estimate.
18. The method for forecasting a water level in a water storage receptacle according to claim 16 or 17, wherein the step of receiving a water storage receptacle location involves receiving an input from the user in the form of an address.
19. The method for forecasting a water level in a water storage receptacle 20 according to claim 16 or 17, wherein the step of receiving a water storage receptacle location involves receiving coordinates or a latitude or longitude from a GPS enabled device positioned in the vicinity of the water storage receptacle location.
20. The method for forecasting a water level in a water storage receptacle according to claim 18 or 19, wherein the step of determining the associated rainfall 25 catchment area includes identifying, based on the water storage receptacle location, a nearby rainfall catchment area from overhead imagery and estimating a size of the rainfall catchment area.
21. The method for forecasting a water level in a water storage receptacle according to claim 20 wherein the rainfall catchment area comprises a roof.
22. The method for forecasting a water level in a water storage receptacle according to any one of claims 16 to 21, further including the step of receiving a 5 receptacle volume for the water storage receptacle.
23. The method for forecasting a water level in a water storage receptacle according to claim 21, wherein the step of calculating the change in water level is executed at intervals based on a volume of water that should have flowed into the tank based on the size of the rainfall catchment area and the actual rainfall recorded 10 at the location since a previous calculation of the change in water level.
24. The method for forecasting a water level in a water storage receptacle according to claim 23, wherein the intervals at which the step of calculating the change in water level is executed are regular intervals.
25. The method for forecasting a water level in a water storage receptacle 15 according to any one of claims 16 to 24, wherein the step of calculating the estimated water consumption rate involves deriving an estimated water consumption rate from an estimated volume of water consumed per person per interval and the number of residents known to reside at the water storage receptacle location.
26. The method for forecasting a water level in a water storage receptacle 20 according to any one of claims 16 to 25, wherein the step of calculating the estimated water consumption rate involves retrieving at least a first water level received at a first time and a second water level received at a second time and determining a consumption rate over a period of time elapsed between the first time and the second time based on the change in water level together with any volume of water that should 25 have flowed into the tank based on the size of the rainfall catchment area and the actual rainfall recorded at the location during the period of time.
27. The method for forecasting a water level in a water storage receptacle according to any one of claims 16 to 23, wherein more than two water levels are received for the water storage receptacle and more than one consumption rate is 30 calculated, each consumption rate being determined for a different period of time and the estimated consumption rate is determined by calculating an average of the more than one consumption rates.
28. The method for forecasting a water level in a water storage receptacle according to any one of claims 25 to 27, wherein the estimated water consumption 5 rate is determined via application of machine learning techniques.
29. The method for forecasting a water level in a water storage receptacle according to claim 28, wherein the machine learning techniques include Random Forecast, Neural Networks, ARIMA or regression methods.
30. The method for forecasting a water level in a water storage receptacle 10 according to claim 17 or any one of claims 18 to 29, when dependent on claim 17, wherein the step of forecasting a period of time remaining before the water level drops below a predetermined threshold involves retrieving a most recent water level and based on the estimated consumption rate determining a period of time within which the water level will reach zero, checking whether rainfall is forecast during the 15 period of time, and if no rain is forecast during the period of time displaying the period of time in which the water level will reach zero to the user, and if rain is forecast during the period of time in which the water level will reach zero, forecasting the volume of water that should flow into the tank based on the size of the rainfall catchment area and the rainfall forecast for the location and recalculating the period 20 of time in which the water level will reach zero.
31. Non-transitory computer readable media embodied with software for forecasting a water level in a water storage receptacle, the software when executed configured to: a. receive an initial water level in the water storage receptacle; 25 b. receive a water storage receptacle location; c. determine from the water storage receptacle location, an associated rainfall catchment area; d. retrieve from a database an actual rainfall determined for the location; e. determine a change in water level in the water storage receptacle based on the catchment area and the actual rainfall; f. retrieve an estimated water consumption rate for the water storage receptacle; and 5 g. calculate a current water level based on the initial water level, the change in water level and the estimated water consumption rate; and h. display the current water level to a user.
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
AU2018903173 | 2018-08-29 |
Publications (1)
Publication Number | Publication Date |
---|---|
NZ756702A true NZ756702A (en) |
Family
ID=
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US10255644B2 (en) | System and method for identifying power usage issues | |
US7996192B2 (en) | Method and apparatus for generating an environmental element prediction for a point of interest | |
CN103370601B (en) | The system and method for determining height above sea level | |
TWI629495B (en) | Method and system for refining weather forecasts using point observations | |
US8552910B2 (en) | System and method of locating missing nodes in networks | |
WO2016064464A1 (en) | Grid topology mapping with voltage data | |
US20140245204A1 (en) | System and method for collecting and representing field data in disaster affected areas | |
Campisano et al. | Evaluating the SWMM LID Editor rain barrel option for the estimation of retention potential of rainwater harvesting systems | |
US20140074733A1 (en) | Photograph initiated appraisal process and application | |
CN104239959A (en) | Geographical disaster prediction system | |
CN105008958A (en) | Method and apparatus for enabling the use of global navigation satellite system (GNSS) signals indoors | |
US20140358468A1 (en) | Apparatus for automatically arranging sensors and meters based on building information modeling | |
CN109784653A (en) | One kind is prepared for a meal method, apparatus and system | |
JP2020012348A (en) | Estimation device, learning model, computer program, temporary toilet, and server device | |
CN203298925U (en) | GPS-supported wireless pipe network pressure measuring apparatus | |
NZ756702A (en) | Systems and methods for forecasting a water level in a water storage receptacle | |
AU2019222779A1 (en) | Systems and methods for forecasting a water level in a water storage receptacle | |
CN104583726A (en) | Providing location assistance information using data from smart meters | |
US11494069B2 (en) | System and method for fire incident mitigation | |
US10338624B2 (en) | System and method for monitoring and reducing energy usage in the home | |
CN114511149A (en) | Layered distributed meteorological prediction platform, method, medium and equipment | |
JP2009171126A (en) | Monitor apparatus management system, monitor apparatus management method, monitor apparatus, and monitor apparatus management device | |
Dutta et al. | Dynamic annotation and visualisation of the South Esk hydrological sensor web | |
Mendoza García et al. | Study of domestic water consumption in intermittent supply of the Riberas de Sacramento sector in Chihuahua, Mexico | |
US20180067014A1 (en) | Water leak early detection system and method |