ATBECHDEDKESFRGBGRITLILUNLSEMCPTIESILTLVFIROMKCYALTRBGCZEEHUPLSKBAHRIS..MTNORSMESMMA....MD..........
J
BDM Ver 0.1.63 (23 May 2017) - 1100000/0
3474243
EUROPEAN PATENT APPLICATION
A1
20190424
EP
17197216.9
20171019
20171019
20180613
en
en
en
20190424
201917
20190424
201917
G07D 11/00 20190101AFI20180430BHEP
de
TRANSAKTIONSVORRICHTUNG UND VERFAHREN ZUR WÄHRUNGSOBJEKTAUFFÜLLUNG IN EINER TRANSAKTIONSVORRICHTUNG
en
A TRANSACTION DEVICE AND A METHOD OF CURRENCY ITEM REPLENISHMENT IN A TRANSACTION DEVICE
fr
DISPOSITIF DE TRANSACTION ET PROCÉDÉ DE RÉAPPROVISIONNEMENT D'UN ÉLÉMENT DE DEVISE DANS UN DISPOSITIF DE TRANSACTION
1
Innovative Technology Limited
101696566
P024EP
Derker Street
Oldham, Lancashire OL1 4EQ
GB
Sumner, Dylan
Innovative Technology Limited, Development Innovative Development Park Derker Street
Oldham, Lancashire Ol1 4EQ
GB
AL
AT
BE
BG
CH
CY
CZ
DE
DK
EE
ES
FI
FR
GB
GR
HR
HU
IE
IS
IT
LI
LT
LU
LV
MC
MK
MT
NL
NO
PL
PT
RO
RS
SE
SI
SK
SM
TR
BA
ME
MA
MD
A method and device for managing currency item replenishment in a transaction device (1) configured to accept a plurality m of currency item denominations, wherein the method comprises analysing transaction history data to produce statistics from which an optimum currency item replenishment period and currency item replenishment levels are determined.
The present invention generally relates to the management of cash levels in machines configured to accept currency items in exchange for goods and/or services. In particular, the present invention relates to a method of managing currency item replenishment in a transaction device adapted to receive coins or banknotes or a combination of the two.
Although the invention will be described in the context of coin handling, this is only for convenience, and it should be understood that the present invention is equally applicable to the handling of other items of currency, such as banknotes for example.
Conventionally, vending machines and gaming machines, or other similar transaction machines or coin-freed apparatus, include a currency item acceptor/dispenser and a cashbox. Typically, the cashbox will be periodically emptied and replenished with a predetermined quantity of currency items in the form of a cash 'float'. A cash float will comprise a given number of each of the currency denominations that is accepted by the transaction machine, and the levels for each denomination are usually calculated to ensure an adequate supply of currency items (banknotes and coins) for dispensing as change to a user of the machine when required.
A problem exists in that the periodic emptying of transaction machine cashboxes and the refilling of them with a predetermined float level of currency items is time consuming and inefficient. Furthermore, it is difficult to strike a balance between maintaining float levels that are adequate for continuous transaction machine functioning whilst avoiding a situation in which large volumes of cash are being unnecessarily stored within the transaction machine. Also, different transaction machines often require differing float levels. For instance, a gaming machine will typically have a much larger cash float than, say, a vending machine, since gaming machines need to retain sufficient amounts of currency items in order to meet the demands of jackpot and prize win payouts.
A further problem arises in relation to the geographic location of transaction machines. Transaction machines in some locations may experience much greater use than machines in other areas leading to the need for a higher frequency of collection and replenishment operations.
The present invention seeks to address the aforementioned problems that are associated with the prior art.
According to an aspect of the present invention there is provided a method of managing currency item replenishment in a transaction device configured to accept a plurality m of currency item denominations, wherein the method comprises analysing transaction history data to produce at least one statistical distribution from which an optimum currency item replenishment period and currency item replenishment levels are determined.
Preferably, the method comprises: monitoring a plurality of monetary transactions executed by said transaction apparatus; determine for each of the plurality of currency item denominations a net payout per transaction distribution over the plurality of monetary transactions; determine a probability density function for currency exhaustion after n transactions for each of the m currency item denominations; determine a global probability density function for currency exhaustion of at least one of the plurality of currency item denominations after n transactions based on the m probability density functions; iteratively adjust the probability density function for each of the m currency item denominations by exchanging currency item quantity allocation q between the m currency item denominations until the number of transactions N at which the global probability density function equals a predetermined probability T converges to a stationary value; and use the stationary value of N to calculate the optimum currency item replenishment period and set q for which N is stationary to be the optimum currency item replenishment level.
The optimum currency item replenishment level q comprises a set of currency item quantity allocations, and for i = 1 to m, q = q_1 + q_2 + ... + q_m. That is to say, q is the total number of currency items, coins for example, that are required for a given replenishment operation.
The optimum currency item replenishment period can be calculated using the average time elapsed between each of the n transactions.
Preferably, transaction history data is monitored and collected locally by the transaction apparatus. Alternatively, transaction history data is monitored and collected by a remote processing means via a wired or a wireless network connection.
Preferably, the transaction control means is configured to record transaction history data and includes a statistics module. Alternatively, or in addition, the remote processing means includes a statistics module.
The transaction device is configured to accept and process coins and/or banknotes.
According to another aspect of the present invention there is provided a transaction device configured to accept a plurality m of currency item denominations, wherein said transaction device comprises: a currency item validator unit including a currency item input/output; a currency item storage means; a currency item transport mechanism interconnecting the currency item validator unit and the currency item storage means; and transaction control means connected to the currency item validator unit and the currency item storage means; wherein the transaction control means is configured to record transaction history data.
Preferably, the transaction control means includes a statistics module configured to execute statistical analysis of transaction history data.
Preferably, the transaction device includes a wired or wireless network interface configured to communicate with a remote processing means.
The transaction device is configured to accept and process coins and/or banknotes.
Advantageously, the transaction control means is configured to execute the method as claimed in any of claims 1 to 6.
Advantageously, the remote processing means is configured to execute the method as claimed in any of claims 1 to 6.
An embodiment of the present invention will now be described, by way of example only, with reference to the accompanying drawings, in which:
- Figure 1 shows an embodiment of a transaction device according to the present invention;
- Figure 2 shows a transaction histogram;
- Figure 3 shows a family of transaction probability distributions;
- Figure 4 shows a global transaction probability distribution;
- Figure 5 illustrates the change in the frequency of transaction device refill operations; and
- Figure 6 shows a network of transaction devices.
As shown in Figure 1, a transaction device 1 of the present invention comprises a currency item validator unit 2 and a currency item storage means 4.
The currency item validator unit 2 may be a conventional coin validator/acceptor, a conventional banknote validator/acceptor, or a combination unit configured to validate both coins and banknotes. The currency item validator unit 2 includes a currency input/output 3 enabling the transaction device 1 to receive and dispense currency items.
The currency item validator unit 2 is interconnected with the currency item storage means 4 via a currency transport mechanism 5 which is adapted to transport currency items to and from the currency item storage means 4 in any of the known conventional ways.
The transaction device 1 includes a transaction control means 6 which is configured to monitor the input of currency items and record the number of each denomination of currency items that is dispensed during any given period of transaction operations. The transaction control means 6 may be a microprocessor or other such suitable processing unit connected to both the currency item validator unit 2 and the currency item storage means 4.
Advantageously, the transaction control means 6 incorporates a statistics module (not shown) for implementing statistical analysis of transaction data and executing associated statistical algorithms.
A display unit 7 is provided to enable an operative attending the transaction device 1 to obtain transaction data from the transaction control means 6.
The transaction device 1 incorporates a network connection 8 to enable transaction data to a be accessed from a remote location. The network connection may be an interface for a wired or wireless network. Preferably, the network connection 8 enables remote interrogation of the transaction device 1 via the Internet. However, it should be understood that other networks can be utilised such as mobile telephone networks or an ultra-narrowband low power wide area network, for example.
The currency item storage means 4 may take the form of a multi-denomination coin hopper as are well known in the art. Alternatively, or in combination, the storage means 6 may be one or more banknote storage drums or stacker units. Such banknote storage devices are also well known in the art.
In operation, the transaction device 1 is configured to accept and process m denominations of currency items (banknotes or coins). In the example discussed below m = 8. Here, the transaction device was configured to accept coins only and the denominations acceptable were: €0.01, €0.02, €0.05, €0.1, €0.2, €0.5, €1, and €2. However, it should be noted that any number of denominations may be used in the method according to the present invention.
In a given transaction device 1 the initial quantity of coins stored in the currency item storage means 6 is defined as Q, where Q = [q_1, q_2, ..., q_m] and q_m is the number of coins stored for the mth denomination. The task is therefore to determine an optimal level for Q in order that over a given transaction period, which may be a number of days, weeks or months, the probability of coin starvation for any denomination is minimised or kept within a predetermined risk level T [see below].
Firstly, it is necessary to make predictions as to when each denomination will run out, and this is done by recording and analysing the transaction history of a particular transaction device and using this information to extrapolate probabilities of coin starvation events. In a preferred embodiment the transaction history data is recorded and compiled by the transaction control means 6. This data is then analysed to produce histograms of the net payout per transaction for each of the m denominations.
An example histogram is shown in Figure 2, and the distribution illustrates the net change in coin levels per 10 transactions. A transaction is defined as any coin input or output event at a given transaction device.
From normalised histogram data a probability density function (PDF) for each of the m denominations can be determined from the mean (µ) and standard deviation (σ) of the collated transaction data.
If data is obtained for the net coin change per n transactions, then the central limit theorem predicts that as n approaches infinity the PDF tends to an approximation of a normal distribution. Consequently, for any given n transactions probability density function parameters can be defined as:
μ
n
=
nμ
σ
n
2
=
nσ
2
From equations (1) and (2) a probability density function can be defined by:
f
x
=
1
σ
2
πn
e
−
(
x
−
nμ
)2
2
n
2
σ
2
where x is the net change in coin numbers per transactions. From equation (3) it is possible to construct a family of probability distributions as shown in Figure 3.
In the example illustrated by Figure 3 we have a separate distribution (labelled 10 to 17) for each coin denomination. Line 18 represents a predetermined threshold probability. In the example shown this has been selected to be a probability of 0.05, and this represents a chosen acceptable risk for a coin starvation event. It should be understood that this level can be set at any risk value and this is determined by the operator of the transaction device.
From Figure 3 it can be seen that as the number of transactions increases the probability of a coin starvation event increases for each denomination. In the example shown line 10 represents the PDF for €0.1 coins, line 11 is the PDF for €0.05 coins, line 12 is the PDF for €1.0 coins, line 13 is the PDF for €0.50 coins, line 14 is the PDF for €2 coins, line 15 is the PDF for €0.02 coins, line 16 is the PDF for €0.01 coins, and line 17 is the PDF for €0.20 coins. It should be understood that this family of PDFs is an example only, each transaction device will have a unique set of PDFs and these may change over time.
It can be seen from line 10 in Figure 3 that the probability of coin starvation occurring for €0.1 coins, for example, crosses the acceptable threshold probability at around 500 transactions. In contrast, the PDF for €0.10 coins (line 16) does not exceed the threshold until around 900 transactions.
For a particular given denomination i the probability of running out as a function of n is given by:
f
i
n
=
∫−∞
−
q
i
1
σ
i
2
πn
e
−
(
x
−
nμ
i
)2
2
n
2
σ
i
2
ⅆ
x
Equation (4) can be expressed in terms of an the error function:
f
i
n
=
1
2
er f
−
q
i
−
nμ
i
σ
i
n
−
2
+
1
2
From equation (5) a global risk function
F
(
n
)
for a coin starvation event occurring for any one of the m denominations can be determined and this is given by:
F
n
=
1
−
∏
i
=
1
m
1
−
f
i
n
Equation (6) provides a means of predicting the probability of each denomination running out after a certain number of transactions given an initial quantity of coins
q
_m
for each of the m denominations. An example of a global probability function is shown as line 20 in Figure 4.
If T is the predetermined threshold probability, i.e. the maximum acceptable probability of a coin starvation event irrespective of denomination, then T comprises a set
t
_1
,
t
_2
, ...,
t
_m
of maximum acceptable probabilities for a coin starvation event for each denomination. From equation (6) T is defined as:
T
=
1
−
∏
i
=
1
m
1
−
t
i
Assuming that the probability of a coin starvation event occurring is the same for each denomination, i.e. t_1 = t_2 = ... t_m = t, then t is defined as:
t
=
1
−
T
m
From equation (6) a value N can be determined, where N is the number of transactions that have occurred before the likelihood of a coin starvation event for any one of the m denominations of coins has reached the probability T.

OPTIMISATION
Conventionally, transaction device operators prefer to maximise the time period between transaction device replenishment operations whilst maintaining a more-or-less constant monetary balance in each of the transaction devices for which they are responsible.
Maximising the time period between replenishments and maintaining a constant monetary balance is equivalent to maximising the number of transactions that have occurred before the probability density function for a particular denomination is equal to t. From this it is possible to define a constant total monetary value Z for a transaction device with a given coin capacity c_{max}, where:
Z
=
∑
i
=
1
m
υ
i
q
i
c
max
≥
∑
i
=
1
m
c
i
q
i
Here
υ
i
is the monetary value of the ith denomination (€2 for example), and
c
_i
is the number of units of capacity occupied by a coin of the ith denomination. Here, a unit of capacity can be the volume that a single coin (or banknote) occupies or it might be the width of the coin (or banknote). Alternatively, the unit of capacity might be the proportion of the total capacity of the transaction device a single coin occupies or some other suitable metric of capacity.
To determine optimal coin levels for each coin denomination it is necessary to perform a redistribution operation on the number of units of capacity that are allocated to each of the coin denominations. This process follows the steps described below.

Step 1
The number q_i of coins of the denomination having the largest value of
n
_i
at probability t is reduced and the number of coins for the denomination with the lowest value of
n
_i
at probability t is increased by a weighted amount that satisfies the combined requirements of equations (9) and (10). A new value of
n
_i
at probability t is then determined for each denomination and these new values are compared with the median value for
n
_i
from the family of denomination distributions [see Figure 3]. The process is repeated until one of either of the recalculated values for
n
_i
changes from being more than the value of the median
n
_i
to being less than the value of the median
n
_i
, or one of either of the recalculated
n
_i
changes from being less than the value of the median
n
_i
to being more than the value of the median
n
_i
. At this point a new value for N is determined and the current value for each
q
_i
is recorded.

Step 2
Step 1 is repeated until the numerical range n_1- n_8 has become fixed and no substantial change is seen and/or the value of N has reached a static limit and further iterations of Step 2 yield no overall change.
When Step 2 has reached a static conclusion the current values for each
q
_1
to
q
_8
are rounded to the nearest whole number and these values are determined to be the optimum coin replenishment levels for each of the respective eight coin denominations.
From the static value of N a time period can be calculated from which an optimum coin replenishment frequency can be determined. Typically, this will be calculated by determining the average time span between transactions and multiplying this period by N to yield a future time point by when a replenishment operation should take place.

EXAMPLE
Figure 3 shows a family of distributions for Euro coins. After executing the steps discussed above the following values for q were determined:
- q
_1
(€0.1 coin) = 50
- q
_2
(€0.05 coin) = 25
- q
_3
(€1.0 coin) = 165
- q
_4
(€0.50 coin) = 80
- q
_5
(€2.0 coin) = 138
- q
_6
(€0.02 coin) = 15
- q
_7
(€0.01 coin) = 10
- q
_8
(€0.2 coin) = 75
- N = 560 transactions.
For this particular transaction device, the average time between transactions was determined to be approximately 25 minutes. From this it is calculated that the optimum frequency for replenishment operations would be 560 hours, which equates to 10 days when rounded to the nearest whole number of days.
Consequently, the cash float for this particular device is €502.65 made up of the above numbers of coins for each denomination, and the transaction device needs to be replenished with this amount every 10 days until and unless a repeat of the above described calculation steps yields a different float level and/or replenishment frequency. It should be noted that this example is specific to a certain transaction device for a particular transaction observance period, and that for any given transaction device 1, the process of float optimisation is dynamic and is executed repeatedly. The frequency of execution of the optimisation process, and the number of historical transactions that are observed before conducting an optimisation, is determined an implemented by the operator of the transaction device(s).
Typically, the float level and replenishment frequency will be determined by operation of the transaction control means 6 statistics module, and this information will be displayed on the display unit 7 from where the details can be noted by a transaction operative during a routine visit to the transaction device 1.
In some situations, it may be desirable to ensure that the quantity of certain denominations of coins never falls below a predetermined minimum or goes above a predetermined maximum. In this instance if the
q
_i
allocation for a particular denomination in Step 1 or Step 2 becomes too low or too high, then the process switches to the denomination with the next lowest or next highest
n
_i
as appropriate.
Figure 5 shows the change in the replenishment frequency for a given transaction device subsequent to the execution and implementation of the above described optimisation process.
Graph 21 shows the occurrences 21' of refill operations before optimisation, and graph 22 shows the frequency of refill operations after optimisation. It can be seen from a comparison of the two graphs that the occurrences 22' of refill operations after optimisation has clearly reduced and the period between replenishment operations has become more regular.
Figure 6 illustrates an alternative embodiment of the present invention in which optimisation of float levels for a network of transaction devices is controlled from a central, remote location.
Here, a plurality of transaction devices is connected to a transaction server 24 and/or a central transaction terminal 25 via a network 23. The network 23 may be wired or wireless, but preferably the transaction server 24 and/or the central transaction terminal 25 communicate with the transaction devices 1 over the Internet.
In this embodiment transaction data is collected by the transaction control means 6 from each of the transaction devices 1, and this data is transferred to the transaction server 24. The transaction server 24 includes a statistics module [not shown] which collates and stores the transaction data for each transaction device and performs the statistical analysis and optimisation steps as described above.
The operator of the network of transaction devices can access the results of the statistical and optimisation procedure via a central transaction terminal 25. The central transaction terminal 25 will display to the operator a suitable user interface which details the location and identity of each transaction device 1 in the network, along with the forecast float level (comprising the quantity
q
_i
for each currency item denomination) and the date at which the next replenishment operation should occur. Alternatively, this information is automatically forwarded to the central transaction terminal 25 from the transaction server 24 at suitable periodic intervals.
Advantageously, this enables the operator to plan and schedule a replenishment routine that takes into account the location, replenishment forecast date and requisite float level for each of the transaction devices within the network of devices for which the operator has responsibility.
1. A method of managing currency item replenishment in a transaction device configured to accept a plurality m of currency item denominations, wherein the method comprises analysing transaction history data to produce at least one statistical distribution from which an optimum currency item replenishment period and currency item replenishment levels are determined.
2. A method as claimed in claim 1, wherein the method comprises:
monitoring a plurality of monetary transactions executed by said transaction apparatus;
determine for each of the plurality of currency item denominations a net payout per transaction distribution over the plurality of monetary transactions;
determine a probability density function for currency exhaustion after n transactions for each of the m currency item denominations;
determine a global risk function for currency exhaustion of at least one of the plurality of currency item denominations after n transactions based on the m probability density functions;
iteratively adjust the probability density function for each of the m currency item denominations by exchanging currency item quantity allocation q between the m currency item denominations until the number of transactions N at which the global risk function equals a predetermined probability T converges to a stationary value; and
use the stationary value of N to calculate the optimum currency item replenishment period and set q for which N is stationary to be the optimum currency item replenishment level.
3. A method as claimed in claim 2, wherein q comprises a set of currency item quantity allocations and for i = 1 to
m
,
q
= q_1 + q_2 + ... + q_m.
4. A method as claimed in claim 3, wherein the optimum currency item replenishment period is calculated using the average time elapsed between each of the n transactions.
5. A method as claimed in claim 2, wherein transaction history data is monitored and collected locally by the transaction apparatus.
6. A method as claimed in claim 2, wherein transaction history data is monitored and collected by a remote processing means via a wired or a wireless network connection.
7. A method as claimed in claim 5 or 6, wherein a transaction control means is configured to record transaction history data.
8. A method as claimed in claim 7, wherein the transaction control means includes a statistics module.
9. A method as claimed in claim 6, wherein the remote processing means includes a statistics module.
10. A method as claimed in any preceding claim, wherein the transaction device is configured to accept and process coins and/or banknotes.
10. A transaction device configured to accept a plurality m of currency item denominations, wherein said transaction device comprises:
a currency item validator unit including a currency item input/output;
a currency item storage means;
a currency item transport mechanism interconnecting the currency item validator unit and the currency item storage means; and
transaction control means connected to the currency item validator unit and the currency item storage means;
wherein the transaction control means is configured to record transaction history data.
11. A transaction device as claimed in claim 10, wherein the transaction control means includes a statistics module configured to execute statistical analysis of transaction history data.
12. A transaction device as claimed in claim 10, wherein the transaction device includes a wired or wireless network interface configured to communicate with a remote processing means.
13. A transaction device as claimed in claim 10, wherein the transaction device is configured to accept and process coins and/or banknotes.
14. A transaction device as claimed in any of claims 10, wherein said transaction control means is configured to execute the method as claimed in any of claims 1 to 6.
15. A transaction device as claimed in claim 12, wherein the remote processing means is configured to execute the method as claimed in any of claims 1 to 6.
P024EP
EP
17197216.9
Innovative Technology Limited
1
DH
20180507
G07D
US
2011225087
A1
AGRAWAL SUBHASH C [US]
20110915
X
1-15
* paragraphs [0006] - [0008], [0012] *
* paragraphs [0064] - [0066], [0074] *
* paragraphs [0161], [0162] *
* figure 1 *
US
2004158539
A1
AKITA MASAYUKI [JP] ET AL
20040812
X
1-15
* paragraphs [0065] - [0070], [0074] *
* paragraphs [0080] - [0085], [0093] *
* paragraphs [0099] - [0104], [0186] *
* figure 1 *
US
2010082355
A1
FOLK AMY BAKER [US] ET AL
20100401
X
1-15
* paragraphs [0001], [0004], [0031] *
* paragraphs [0040] - [0043] *
* paragraphs [0058] - [0062] *
* figures 1,2,9 *
Bauer, Sebastian
The Hague
20180426
US
2011225087
A1
20110915
US
7946474
B1
20110524
US
2011225087
A1
20110915
US
2014006090
A1
20140102
US
2004158539
A1
20040812
JP
4394876
B2
20100106
JP
2004206413
A
20040722
US
2004158539
A1
20040812
US
2010082355
A1
20100401
US
2010082355
A1
20100401
WO
2010039705
A1
20100408