GB2542601A - Callibrating and monitoring fluid flows for liquids and pre mix syrups with communication to remote databases, online till systems and product distribution - Google Patents

Abstract

The present invention relates to a method for flow detection of both alcoholic and non-alcoholic beverages, namely pre-mix bag in the box syrups. A sensor (Fig 1, 102) on the fluid supply line, with a centralized online calibration of the sensors output to determine its true flow volume, via the control module ( Fig 1, 104) and using the remote database connecting device 208 and local and server side scripts. The device uses software for signal classification for line clean, line pull detection after line cleaning, sale and wastage state, with output signal conditioning, thus removing the need for conventional sensing points in the line to detect the fluid state. Embedded software is based on the sensor module on the fluid supply line (Fig 1, 101) on the control module (Fig 1, 104) and with the scripts remote from the sensing hardware 206. The device integrates till receipts with real line flows for all beverage types online and in real time to determine the following: till theft or discrepancies, product profitability, current stock holding and stock out date predictions, product cost based on wastage and accurate sales volumes, order numbers, trends and product ranking and sales predictions, with manual or auto ordering of products required from the site, with an auto delivery and product distribution service though a payment account or a payment gateway.

Description

Background to the conventional problems and invention

Typically in a licensed venue for the supply and sales of alcoholic and non-alcoholic beverages, the management of the operation requires data and subsequent actions from the following procedures: a) Stock holding data - that is conventionally recorded manually, through physical stocktaking and counting b) Sales data through till systems - this is conventionally recorded through a reading of the till roll/receipt or in more updated systems - from printouts or displays in applications

From this data the following actions are required: a) Decisions to be made in terms of stock purchasing dates, products and volumes b) Manually ordering the stock, through the contacting of suppliers and adjusting the known stock levels. c) Calculation of any losses or theft between the two data measurements

There are various challenges associated with managing the operation in this conventional way: 1) Stock taking is a manual and costly operation and can be subject to human error or inaccurate calculations in the volume of fluid stored in the fluid supply lines and kegs that are currently being used. 2) Prevention of managed or tenanted venues buying outside of the supply contract can’t be prevented. 3) Data for current suppliers to forecast production schedules in real time is currently not available. 4) Current calculation of stockholding is not in real time, it is only momentary after heavy analysis and manual calculation of the current days trading figures subtracted from the known stock levels. 5) Sales performance in terms of number, fluid volume, temperature and trending of products over time is unknown, unless a heavy data entry and calculation system is implemented. 6) The ability to purchase stock on the basis of current stock levels in real time is currently unavailable. 7) The ability to change till prices remotely and in real time on the basis of sales performance is currently unavailable. 8) Calculation of the volume of flow from bag in box pre mix syrups is unknown. 9) Knowledge of serving measures being served for soft drinks and alcoholic beverages is unknown. 10) Free giveaways of products at the bar are currently undetectable in real time. 11) Wastage from the supply lines is currently unknown, thus manual stock calculations are difficult to predict. 12) Visibility of sales and current stock levels at a senior position, remotely and in real time from a mobile device is currently unavailable.

There are a number of systems that are currently on the market to support and negate some of these issues. Conventional systems are available for line monitoring for beer lines only, such as flow measuring turbine sensors on the fluid supply lines. Data is then relayed on to the internet via a router and modem, radio signal or phone line connection. Data is also coupled after the flow events with till data to check for any discrepancies.

However, they have technological disadvantages. These systems are not in “real time”, till discrepancies are only known up to two weeks later, with noted recording errors in the region of up to 30% for cask ales which are more viscous typed products. These systems do not allow for the comprehensive analysis of all stocked products in the venue and only for beer line products.

Also, none of these devices or systems has been able to cost effectively determine the quantity of syrup fluid flow from the standard bag in the box for soft drink dispensing machines. The reason for this is due to the turbines performance with viscous liquids. Such high sugar liquids affect the turbine mechanism over time, with the added problem of differing fluid viscosities for different products, causing its measuring performance to degrade or have very poor generic measuring performance.

Alternative methods have been used to monitor the flow of syrups in supply lines in production or for dispensing, using positive displacement piston pumps and the like, but these come at great cost and are therefore too costly to be used for this specific application.

Methods for monitoring have been developed for soft drink dispensing after the post mix stage (Syrup and Soda) although three problems arise from this method. The first problem is with power supplies, data transfer methods, integration with the buttons or products being pushed on the standard gun and installation of it. This second problem is that the monitoring device needs to be present after the gun or mixing component in the serving area. The guns short head length then increases to the length of the sensing element, making it more awkward and unconventional to use. The third problem is that it will not give the most important information regarding the quantity of the more costly syrup component being used from the bag in box, in the served drink.

According to the present invention there is provided a cost effective method for syrup flow detection (102) from the bag in box within the fluid supply line (206) leading towards the soda mixing gun.

It was discovered that a vortex flow sensor (102) (dry sensor) with no moving parts is a cost effective way of determining the flow of syrup solutions. The vortex sensor is based on the Karman vortex sheet. The vortex sheet is a repeating pattern of swirling vortices caused by the unsteady separation of flow of a fluid around blunt body. In this case a plastic finger in the flow stream is used to separate the flow of the fluid to create the swirling vortices.

When a single vortex is shed, an asymmetrical flow pattern forms around the separating element and changes the pressure distribution in the fluid pipe. This means that the alternate shedding of vortices can create periodic lateral (sideways) forces on the body in question, causing it to vibrate. It is these vibrations that are recorded by the sensing element and is directly proportional to the fluid velocity as a function of the viscosity. i.e.

Re is the Reynolds number of the fluid given as:

/ is the vortex shedding frequency d is the diameter of the cylinder V is the flow velocity v is the kinematic viscosity of the fluid.

Assuming the viscosity of the fluid (v) and the diameter (d) is a constant value, we can prove that the fluid changing velocity (V) is directly proportional to the changing vortex shedding frequency (/):

From this relationship it is possible to determine the flow velocity from the measured shedding frequency count and hence the flow volume. This is calculated from a proportional coefficient calibration against the measured frequency count with the said fluid type.

From research into a number of mainstream soft drink products, each individual soft drink product has a different manufactured viscosity and hence giving a unique proportional calibration value. This calibration value is the gradient (calculated using a pseudo inverse method to minimise system and recording error) of the purely linear response of the sensor in relating the flow volume to the recoded shedding frequency count.

Measuring the flow of fluid with sensor points has several problems that must be overcome.

The first problem is how the sensor performs when air flows through the sensor (102). This occurrence is common when there are no fobs (205) present on the supply lines (206). In most cask beverage fluid supply apparatus or for bag in the box for syrup dispensing, fobs are not present on the supply line, thus allowing air or vacuums to pass through the sensing point when the fluid supply has been exhausted.

Typically, all sensor types will output extremely high flow rates when air or vacuums are passing through the sensing point, thus giving wildly high inaccurate readouts.

The second problem is how the system can differentiate between fluid in lines being sold and fluid in the lines being used for cleaning.

The third problem is even though the linear coefficients can be determined for each soft drink or alcoholic product, how can this be installed or programmed for each unique fluid supply line sensor on site. This will be a time consuming, costly setup and erroneous exercise to implement.

The forth problem is if the soft drink or alcoholic beverage manufacturer decides to change the chemistry/viscosity of the product in the future, how will the sensors be recalibrated for every installation for that product?

The firth problem is how can the system determine if product pulled through the supply lines has been sold and the money put through the till system.

The present invention solves these problems by adding many degrees of software sophistication to the architecture.

According to the present invention there is a flow sensor (102) with line temperature and an algorithm for the flow measurement, held on a processor inside sensor module (101); the first part of the on board flow algorithm is when fluid is pulled through the fluid supply line. The flow is recorded between flow-start and flow-stop, when the current temperature is recorded, with an ending time delay. Once the time delay has passed with no additional flows the shedding frequency count and board module number is passed onto the main controller’s memory (104) via the linking data communication system. When the data is passed from the flow sensor module (101) to the controller (104), the flow counter on the sensing module (101) is reset back to zero. A second element of the on board flow counting algorithm, held on a processor inside the flow sensor module (101), is based on the rate of flow. Flow readings and the flow frequency are both recorded. If the flow frequency of the reading exceeds a set value or the time taken between output pulses is less than a set time, then this indicates the presence of air or vacuums passing through the sensor (102). If this is the case, then the current reading of the sensor’s output (102) is stopped with a time delay. If the frequency has not reduced to a value, or the time between the pulse counts has not increased to indicate fluids in the line, then the flow value is recorded by the sensor module (101).

It can also be assumed that such detections of air or vacuums in the line, to stop sensor readouts at this point, can be determined through any form of hardware, such as: conductive, optical, electromagnetic, pressure, capacitive or other sensor types, but the present invention describes how to accomplish this without any additional hardware, through the use of a sensor frequency output algorithm only. This is such that the system requires less cost and does not run the risk of hardware failure over time due to the chemicals used for cleaning.

Conventional monitoring systems calculate which lines are being cleaned. This is so that flows in the supply line during cleaning process are not recorded as products sold. This is determined through the use of conductive or pH sensors and the like in the line next to the fluid flow sensor. However, such additional hardware adds to the cost of the product and can be subject to deterioration on contact with the line cleaning chemicals.

Additionally, the use of turbine sensors to monitor fluid flow causes resistance to the flow, thus requiring more gas or energy to overcome the turbines resistance. The turbine mechanism is also subject to a zero performance with high viscous fluids and suffers the effects of deterioration over time, when in contact with the line cleaning chemicals. Unlike the vortex sensor presented, that is a free flow dry sensor, with no mechanisms to impede the flow of highly viscous fluids and as such that it can’t be affected by any line cleaning chemical corrosion.

According to a further element of the present invention, there is a cleaning detection algorithm and flow device (202) on the cleaning ring (203) that can differentiate between sales and line cleaning in the fluid supply line (206), without the use of additional sensors;

During the line cleaning process, water is pumped or pulled from a tank (201), through the line cleaning ring (203) in the cellar, up through the attached keg couplers, through the fluid supply lines (206), through the cooler (209) and up to the bar area. A combination of the flow recorded by the cleaning ring line flow sensor module (202) and the flow through the fluid supply line sensor modules (207) is listed as lines being cleaned.

An algorithm is used to determine if any of these flows were actual sales being pulled from another flow source (204), when line cleaning on other products was currently happening at the same time. Typically, line cleaning and customer sales will rarely occur at the same time. But, the analysis is carried out in software, over expensive sensory measurement to distinguish between cleaning fluids, water and product being supplied.

The following elements of the line cleaning detection algorithm are as follows: a) As soon as a flow is detected from the sensor on the cleaning ring (202), it reports this to the controller (104), as part of bank (207), that lines are now being cleaned. b) Both sale flows and cleaning flows are then recorded as being in clean mode, by the fluid supply line sensors (207) and are sent to the remote database, via a combination of radio signal and modem or radio signal to application device (208), with their respective flow volumes and date/time stamping. c) When the fluid flow passing through the cleaning ring sensor module (202) has stopped and no air or vacuums are passing through the cleaning ring, it waits for a small fixed time period to ensure that the fluid flow has actually stopped. Once the fluid flow has stopped, the cleaning ring sensor module (202) sends out its volume of flow to the controller (104), as part of bank (207) , where it is time stamped and sent to the remote server database, via a combination of radio signal and modem or radio signal to application device (208) . d) The online scripting algorithm at this point determines the lines that were being cleaned and the ones that were being sold during this period. The summation of the volume of fluid passing through the fluid supply line sensors (207) during this period must closely represent the flow volumes recorded by the flow meter of the cleaning ring line (202), otherwise line flows are recorded as product sales. It calculates this by adding every combination of flow volume through the flowing lines in module bank (207), to determine the closest match of flows to the ring main flow volume recorded by sensor (202). e) Flows which are determined as sold, will then trigger the anti-theft algorithm, which checks to see if the correct payment was made in the till system for the product. f) After the cleaning is complete, water will remain in the fluid supply lines (206). The couplings will be connected back to a product source (204) at any time post clean. The online script and database knows the length of the supply line in question and therefore can make adjustments that the following line length pulled from the supply line is water, noting this down as ‘Line Pull’ and not ‘Sale’ and adjusting the stock holding accordingly.

According to another element of the present invention, there is a mechanical mechanism which allows sensors to be connected either in to a sensor hank (103) or as individual remote sensor modules (101) with a configurable communication system using the same housing design, from a single mould pattern to create the interlinking module.

According to a part of the present invention, there is a main controller module (104) with an on board memory; its function is to store its unique ID number, the current date and time, any flow recordings and temperatures from any of the connecting flow sensor modules (101,103 or 207).

Its function is also to accommodate the cleaning ring flow sensor module (202). The controller module (104) sets all flows from the fluid supply line sensors (207) to clean detection, during the cleaning flow. This will only be when the output cleaning ring sensor (202) is recording a flow.

According to a feature of the main controller invention (104) there are clock components; when switched on, the controller initialises its clock, by connecting to the internet via a URL server side script call. The date and time is passed back to the controller via the web based script output, according to the customer’s account in the given time zone. This then resets the clock time and date on the device to the true date and time in the installed locations time zone, to prevent any date/time tampering or electronic time drift.

According to the communication aspect of the controller invention, there is a queuing and on board memory saving system, from data transfer from the modules via a serial data transfer method. This allows the possibility of daisy chaining additional sensory modules to the other sensors, making the invention modular and scalable.

Once the frequency count data is received by the controller module (104) with the module ID number, it time and date stamps the record with the accurate web based date and time in the installation time zone. It then saves this data record to its memory sequentially against a consecutive record number starting from record number one.

Once the controller (104) has records stored in its memory it either: a) Connects to the websites script, via a combination of radio signal and modem devices (208), which then connects to the online database to transmit its data. This will occur via its connected modem which is connected to the internet, sending each record sequentially in accordance with its stored record number. Once all records have been sent, it erases all of the records stored on it’s on board memory, resetting the record number back to one. b) Waits for application software to request its stored data, via its radio or wired connection communication device (208) for which it requests to send each record sequentially. Once all records have been sent to the application software it erases all of the records on it’s on board memory, resetting the record number back to one on the controller (104).

According to the present online scripting invention for the cross referencing and editing of products, coefficients and account numbers; each product whether it is for a Soft Drink, Beer, Lager Wine or Cider, with the fluid supply line and account number is stored on a remote database online. The associating products of which can be added, edited or deleted by the users account online, against the associating sensor/module number.

The web based script then searches for the coefficient number for that specific module ID number’s product and against the user’s ID number. It then cross multiplies the coefficient number by the shedding frequency count to calculate the flow volume and adds this to the flow table. It also adds the product name, temperature, date and time and for this specific flow, against the customer’s account.

If the product is changed for the line, it can simply be changed online creating a new relation for the new product’s calibration number. The product calibration numbers are pre-determined and are stored in the centralised database. If a manufacturer changes the viscosity of the product, a simple analysis and recalculation occurs, updating the coefficient to the new number in the calibration table online. This means that for an infinite number of deployments, re-calibration and re-programming the sensor at the installation site is not required. These product calibrations linked to an infinite number of modules can change dynamically and centrally through the online database.

Independent till systems, do have the facility to remotely change prices and view sales from the till remotely, but these have never been fully integrated with a degree of intelligence to a fluid monitoring system to stop theft in real time.

According to the present online scripting invention for anti-theft, there is provided: till data and two way flow linking algorithm to calculate and prevent theft in real time, with real time till sales and flow data available through online devices.

For the prevention of theft in real time; the present invention determines this by dividing the recorded flow volume (calculated from the frequency shedding count value and its product flow coefficient) by the largest serving measurement stored on the online database to within 10% of its value. From this, it determines the numbers of individual measures or units sold at that point in time. It then waits for a given period of time before executing a second script which checks to see if this entry has been received into the database from the till system.

Similarly, every entry received by the database for the till system checks against the flow data to determine if the product and flow volume can be matched. If the entry has not been added or if there is a discrepancy from both the till and the flow system, the manager is informed via a Short Message Service (SMS) and an online login alert, full with dates and times of the discrepancy. This can then be viewed on Closed Circuit Television (CCTV) system against the time on the SMS or login to determine the person(s) involved in the discrepancy.

According to another element in the online scripting invention for margin evaluation, this is a real time method of calculating exact margins and costs to the users business. Using the real time flow data showing each serve to the nearest millilitre, it can show any under or over serving measures, calculate its true cost and sales margin for that specific transaction. This is opposed to sales data from the till system only, that will not have this degree of accuracy or account for any thefts or measurement under or overflows.

According to another element in the online scripting invention for stock evaluation, there is a real time stock taking calculation and analysis. The online system allows for an adjustable stock data entry, which is also auto adjusted for every millilitre of flow through the supply lines, at the point of flow through the sensor. This is currently an impossible evaluation from till receipt data only.

According to another element in the online scripting invention for stock evaluation, presented is a mathematical method of calculation of the likelihood of stock depletion and the day the stock will equal zero, based on sales history performance.

The described method is one which determines the underlying system function on the basis of the minimised error. A linear two coefficient prediction trending model is assumed. More than two coefficients will give non-linear prediction, thus giving inaccurate positive and negative calculations on predicted future stock depletion.

Assuming that only a two coefficient linear method is the presumed stock depletion prediction, then the function would be: y = »ix + c

Where: y is the stock level x is the day number m is the gradient of the stock depletion c is the starting stock value on day zero.

The calculation of the unknown coefficients m and c is calculated based upon sales data over the past week, month or year from: yi = itiX] + c - sale volume #1 fyi ) on recorded day (xj) Y2 = mx2 + c - sale volume #2 (y2) on recorded day (X2) yn = mxn + c - sale volume #3 (yn) on recorded day (xn)

These linear equations can be written into matrix form as:

Using the pseudo inverse method to find unknown coefficients [C]: [Y] = [X].[C]

As the inverse of [X] needs to be determined to calculate the unknown coefficients [C], [X] needs to be square. Multiply the transpose of [X] on both sides of the equation to make it square.

[Y].[X]T = [X].[X]T.[C]

Then take the inverse of square matrix [X].[X]T and multiply by [Y].[X]T to find [C]. ([X].[X]T)1.[Y].[X]T= [C]

Using the calculated coefficients of the stock depletion through sales history and then projecting this into the future through a similar presumption, this will indicate the highest mathematical probability the day (x) when the stock level (y) will reach zero from the sales data available, from simply:

This calculation for each stored item, allows for just in time purchasing based on accurate stock depletion predictions and current stock data. The main advantages of this online scripting invention for stock evaluation are: a) Stock is not purchased too long in advance, tying up company funds and also running the risk of then possessing stock which reaches its expiry date b) Stock management and ordering can always ensure that the site has the supply of product in time, so that it does not suffer from ‘dead’ or out of stock lines c) The current stock taking value is in real time for single or multiple sites d) The current stock taking volume is accurate to the nearest millilitre for products that have passed through the sensing elements in real time for single or multiple sites.

Another aspect of the online scripting invention for stock replenishment; allows the user or system to reorder stock on a next day delivery anywhere in the country. This will be on the basis of the method and analysis of online scripting invention for stock evaluation. This can either be auto ordered via the script within a fixed time frame before stocks are fully depleted or manually by adding items to the online shopping cart for single or multiple accounts via a web connecting device.

The manual or auto stock replenishment method, consists of the following: a) Items purchased to replenish stocks are charged to the user, either via accepting payment online through the payment gateway or though the customer account and invoice system. b) Successfully purchased items, give rise to the following actions: i) The purchase order (PO) is emailed to the warehouse against the customers ID number and delivery address for dispatch. ii) The payment acknowledgement or invoice is auto emailed to the customer on purchased items, which is also available online in the order history. iii) The current stock holding for the product is auto adjusted for the customer’s venue. iv) The current stockholding for the product is auto adjusted from the supplier’s warehouse.

Currently the analysis of sales performance to determine the correct management strategy to enhance profitability is very heavy in terms of data analysis.

The current invention consists of an aspect of the online scripting method for sales management, analysis and performance, consisting of the following tables and chart data displays in real time: a) Number of sales of each product over the last week, month or year; this indicates how many people made the decision to purchase that specific product. This could be influenced via advertising, special offers, word of mouth or personal preference. Changing trends in personal preference or fashions can be monitored using this key indicator to keeping or replacing a specific product. b) Sales volume generated by the product over the past week, month or year; This shows the volumetric demand of the product and can be used as an indicator for staff training or promotions to sell the current stock on hand. c) Data trend calculation of the product over the past week, month or year; using the mathematical model method described in the online scripting invention for stock evaluation, but for the number of sales. A positive gradient coefficient shows if the product is becoming more fashionable and a negative gradient coefficient shows if it is becoming less popular. d) Sales profit generated by the product over the past week, month or year; this coupled with the sales volume, number of sales and trend indicators, show the demand for the product and whether or not to change the price, to increase sales margin and profitability. Changing of the prices on the till remotely and in real time can occur through the online scripting method to the till communication system, using the customer ID and till ID protocol. e) Ranking of the product over the past week, month or year; this is an indicator which shows how important this product is to the profitability of the business.

To increase profitability it is important that the customer chooses products that create more sales margin for the business, over products that give lower sales margin, as the customer’s consumption is limited. This ranking is illustrated against all types of product or how well the product is ranked against its discrete product category such as: craft beer, cider, red wine, gin, vodka etc.

If a product ranking is low for a product type and its trend is currently negative, then it gives indication on a possible replacement for a new product of the same category, which may be more profitable and popular. Products that can generate greater profitability can be more easily found from the software’s analysis, which will arise from better supply pricing, consumer branding, trending, lower manufacturer’s overheads and greater supplier efficiencies.

Alternatives of which are suggested in the software, with the option to buy now and ship on a next day delivery service. Thus giving the user a more efficient way to order new items and replenish stocks, without going through the conventional procedures such as: ordering stock of multiple suppliers via email or telephone, arrange for possible shipping dates, with complex payment terms and methods.

Claims (1)

1. Claims 1) According to the present invention there is provided a cost effective method for flow detection, sensor calibration, data conditioning, data transfer, data linking, data analysis, real time product ordering and supply, comprising of the following: a) a communication system between installed hardware devices; b) a fluid supply line flow and temperature sensor module to detect either alcoholic or non-alcoholic beverages or viscous liquids, comprising of: i) a sensor suitable for measuring aggressive and viscous fluids flow volumes; ii) a microprocessor with embedded flow check algorithms: an algorithm for the flow measurement duration and flow volume; an algorithm for rate of flow to determine the presence of air or vacuums in the sensor, without additional sensors; iii) a flow data transmission of the flow record to the controller, along with its Module ID; c) a line cleaning flow sensor module, comprising of: i) an inline flow sensor suitable for measuring water flow volumes; ii) a microprocessor with embedded cleaning detection algorithms: an algorithm for the flow measurement and detection during cleaning; an algorithm for rate of flow to determine the presence of air or vacuums in the sensor, without additional sensors; iii) a flow data transmission of the flow record to the controller, along with its Module ID; d) a control module, comprising of: i) an on board memory device; ii) a microprocessor with embedded software; an algorithm to store on the memory device, its unique System ID, the current date and time, any flow recordings and temperatures from any of the connecting flow sensor modules; a line cleaning detection algorithm, to determine lines being in clean mode, based on the input of the line cleaning flow sensor; an algorithm for a start-up data and time calibration script call; iii) clock components to calculate its current date and time; e) a method of data communication to the remote online scripts and database from the control module; f) server side scripts and algorithms with online viewing of data or application software, with online database connections, for the calculation and processing of the following: i) an initialisation of the control modules clock in the installed time zone; flow volume calculation, through remote calibration of the recorded flow through the fluid supply lines; ii) record creation, exact cost and margin calculation, with remote database insertion and determination of pulled water through the supply lines after cleaning, without the requirement of additional hardware or sensors in the fluid supply lines; iii) line cleaning detection without using additional hardware or sensors in the fluid supply lines, which can determine line flows that are sales or line cleans, during the line cleaning period; iv) real time mathematical stock depletion expectations; v) manual or auto ordering of stock with delivery when stocks are low or when new stock is required, with additional manual or auto adjusting of stock figures when stocks are replenished; vi) real time detection of theft from the till based on line flows and till data; vii) a method with key indicators for sales management, analysis and product performance for profitability, cost, order numbers, trends and product ranking; viii) a customer user interface, facilitating a unique login user ID for single or multiple sites, based on a mobile or web based platform device; g) a method to connect with the till system, for the adjustment of till pricing remotely and in real time, for any product, against the user ID; h) a method to receive the till data in real time and insert its data into to the remote database, for a comprehensive sales and stock holding analysis; 2) A method according to Claim l(b, c & d), wherein fluid supply sensors, the line cleaning flow sensor and the control module, is to be housed in a suitable fabrication that can allow for a remote or hanked operation of devices. 3) A method according to Claim 2, wherein the housing can be fabricated from one unique mould tool to produce the complete module linking housing. 4) A method according to the communication system between installed hardware devices in Claim la. A microprocessor on a printed circuit board inside the control module, allows connection to the fluid supply line modules via a serial line, which monitors the state of the modules for bus arbitration on a command bus. The device can use a serial port for a wired connection from the sensing modules to the control module. 5) A method according to Claim lb, which describes a method for the fluid supply line flow measurement, duration, flow temperature and for the detection of air or vacuums in the sensor include: a) starting the output frequency count when the frequency count output, from its flow sensing element, increases from zero; b) if the time difference between pulses is shorter than a set known time for fluids passing through the sensor, it is then assumed that the air or vacuums are now passing through the sensor, thus moving to the pause function (5d). It can also be assumed that this can also be determined via a set high frequency value of the output count; c) if the frequency count output returns to zero, the pause function (5e) is called; d) the pause function waits for a set time period to see if the time between counts returns back to a time period greater than a set known time or if the frequency of the output count returns to a level lower that a set frequency, indicating fluids passing through the sensor; if true then the function returns back to state (5b); if false, then the flow count at the time the pause function was called is recorded, with the current temperature from the thermostat and the frequency count is reset back to zero; e) the pause function waits to see if a zero flow is recorded for a fixed time period after the first zero flow; if true, then the flow count is recorded, with the current temperature from the thermostat and the output frequency count is reset back to zero; if false, then the function returns back to state (5c). 6) A method according to Claim la, which describes a flow data transmission record to the controller, using the method presented in Claim 4, including steps: a) creating a record string after the flow stop, along with the flow frequency count, temperature and the unique module ID, set either on its processor or as processor board switches; b) sending the flow and temperature record on the communication system to the main controller; 7) A method according to Claim Id, which describes a main controller method, used to store its unique ID number, the current date and time, any flow recordings, temperatures, or status, from any of the connecting flow sensor modules. This includes the process of: a) time and date stamping the received record from the connecting flow module sensor, from the processors clock components; b) storing the received record, with time stamping and processor number into a sequential memory location on the memory device; 8) A method according to Claim lc, which describes an algorithm for the flow measurement and detection during cleaning, comprising of: a) starting the output frequency count when the frequency count output increases from zero and sending a string to the controller via the modular communication system, to inform the control module of a cleaning flow start with its respective ID number; b) if the time difference between output frequency count pulses is shorter than a set known time for fluids passing through the sensor or the frequency is higher than a set value, it is assumed that the air or vacuums are passing through the sensor point, thus moving to the pause function (8d); c) if the frequency count output returns to zero, the pause function (8e) is called; d) the pause function waits for a set time period to see if the time period between counts returns back to a time period greater than a set known time, or if the frequency returns to a value lower than a set output frequency indicating fluids passing through the sensor; if true, then the function returns back to state (8b); if false, then the flow count at the time the pause function was just called is recorded and the frequency count is then reset to zero; e) the pause function waits to see if a zero flow is recorded for a fixed time period after the first zero flow; if true, then the flow count is recorded and the output frequency count is reset to zero; if false, then the function returns back to state (8c). 9) A method according to Claim 7, which stores flow records on the main controller memory, presents an additional input on the stored record in accordance to the output stipulated in Claim 8, such as: a) if the output of the cleaning line sensor to the controller is indicating a line cleaning flow, all subsequent flow records received by the main controller after this indication are recorded as being in clean mode; b) when the output of the cleaning line sensor stipulated in Claim 8d and Claim 8e, receives a flow frequency count record or cleaning line flow stop from the cleaning line sensor, then all subsequent flows received by the control module are recorded as being in sale mode. 10) A method according to the data communication system to the remote online scripts and database as in Claim le, wherein the communication system can be: a) a direct connection, facilitating a SIM card and modem to transmit its data via a radio transmission, using standard AT modem commands, embedded on the controllers microprocessor, communicating to the server and database through a secure Hypertext Transfer Protocol (HTTP) script call; b) a wireless Ultra High Frequency (UHF) radio communication or a hard wired Local Area Network (LAN) system, directly to the sites router and modem, communicating to the server and database through a secure Hypertext Transfer Protocol (HTTP) script call; c) a wireless connection to exchange stored data from the controller to the internet via a connecting PC using a UHF narrow band transceiver or a hard wired LAN system, wherein the software on the PC decrypts and relays the data to the remote database via Virtual Private Network (VPN) connection to a database with connection strings or HTTP server side script calls; 11) A method as of Claim If, to calibrate the controllers clock in the installed systems time zone via the server side script call, also using the method described in Claim 10, consisting of: a) a database search of the time zone listed against the system ID number in the script call from the control module; b) getting the current web based date and time in the ID number’s time zone; c) echoing the date and time back at the end of the HTTP script call; d) resetting the current date and controller clock time to the echoed web based date and time; 12) A method as of Claim If, to calculate the product flow volumes, wherein the method consists of: a) a server side script call to send the control module flow record consisting of the System ID, the Module ID, the frequency flow count, the temperature and the clean status, using the method described in Claim 10; b) a database product name search, against the System ID and Module ID number; c) a coefficient search, against the product name and subsequent multiplication of the coefficient with the frequency flow count to determine the flow volume; whereby the coefficient values can be changed centrally on the remote database at any given point in time; 13) A method according to Claim If for database insertion, exact cost and margin calculation and the determination of water pulled through the lines post cleaning, without the use of additional sensors in the fluid supply lines, consisting of: a) a calculation of the flow cost price, sales price, exact sales margin and probable serving measure size within a set percentage, based on a low remainder division of the possible unit sizes sold, along with the probable units’ sell price. If not within a set percentage of the smallest measure size, then the record is noted as ‘Wastage’, with no till expectation or calling of the method disclosed in Claim 18. Calculated from a database search of the possible measures against the System ID and product name; b) if the record is of a non-clean status, a database search for the supply line length against the Module ID and System ID is returned. A database search of the flow records can then determine the volume of fluid hat has passed since the last clean status was recorded for the System and Module ID. If it is within the line length, the flow record is then set to a ‘Line Pull’ status; c) an adjustment of the stock level occurs, if the record is in ‘Line Pull’ status by reducing the stock holding by the ‘Line Pull’ flow volume;. d) an insertion into the remote database for the System ID, Module ID, product name, flow volume, temperature, cost price, sell price and status can then occur; 14) A method presented according to Claim If, for line cleaning detection without using additional hardware or sensors in the fluid supply lines, that can determine line flows which are sales or line cleans, during the line cleaning process, involving the following steps: a) The method is actioned, when the clean line flow sensor, sends its flow start and flow volume to the control module as in Claim 8, which is then relayed through the communication system as in Claim 4, via the control module as in Claim 7, to the server side script using the communication method presented as in Claim 10; b) When the server side script receives the clean stop command the following method is actioned: i) The method calculates all of the total flow volumes for every line with a flow entry, during the clean start-clean stop period, given by the cleaning ring sensor module; ii) The method adds every possible combination of the line flows occurring during this period; iii) The method determines which combination of lines flows are the most equal to the flow passing through the cleaning ring, thus most likely to be lines being cleaned. iv) A differentiation on sales and cleaning then occurs, allowing the database to update the actual lines flows being sold from a ‘Clean’ status to a ‘Sale’ status. v) Line flows being converted to a sale status then triggers the antitheft method with a fixed time delay, presented in Claim 18. 15) A method according to Claim If, based on the data from the method presented in Claim 13, for an auto adjustment of the products stock holding figure, held in the database against the System ID and product, wherein the volume of the ‘Sale’ or ‘Wastage’ status of recorded flows are subtracted from the current stock holding values. 16) A method according to Claim If, for a stock holding depletion expectation method, based upon the ‘Sale’ or ‘Wastage’ of a products recorded flows against the System ID, using the data over the past week, month or year, to calculate the expectation of the stock depletion, comprising of: a) a calculation of the actual stock volume for the product on every given day over the chosen time frame, calculated from the sales or wastage on each day for the product. b) a creation of a set of linear or non-linear equations every day for the stock of the product, over the given time frame, as a function of time. c) a translation of the linear equation set into matrix form; d) a matrix multiplication by the transpose of the time component matrix and subsequent multiplication of the inverse of the time component matrix and daily stock vector, to calculate the coefficients of the best line fitting stock model; e) a manipulation of the derived coefficients to determine the date when the stock is most likely to fall to zero, based on current sale trends; f) a table and charting display of the functions output; 17) A method according to Claim If, for the manual or auto adjusting of stock figures when stocks are replenished or for the manual or auto ordering of stock with delivery, when stocks are low or when stock is required, consisting of: a) a method of allowing the user to manually update the stock values in real time and remotely; b) a method that auto adjusts stocks based on actual flows with a ‘Sale’ or ‘Wasted’ status; c) a method that auto adjust stocks based on non-flow data from the till system; d) a method that allows for the manual purchasing of product remotely through the online system, using a payment gateway, with auto administration for picking, packing and shipping, invoicing, account payments or on account terms, with auto payment acknowledgement receipts sent through an email sending system; e) a method that allows for the auto purchasing of products when stocks are due to run out based upon the method and calculation presented in Claim 16; 18) A method according to Claim If, for real time detection of theft from the till based on line flows and till data, comprising of the following steps on its function call: a) a method to search the database for a product with a till entry at a close time to the flow, of the same product, of the similar flow volume and on the basis that it is set to a ‘Sale’ status, that has not been assigned to the given flow recording; b) if the till entry can’t be found for the product flow recording in ‘Sale’ mode, then an auto SMS message, email or website or display screen alert will be sent to the operator in real time; c) if the till entry system can be found against the flow, it will link both the flow and till entry records by their record ID numbers. 19) A method according to Claim If, to calculate key indicators for sales management, analysis and product performance for profitability, cost, order numbers, trends, predicted profitability and product ranking, thus giving the management indicators for product replacement, promotions and staffing expectations consisting of the following: a) tabular and graphical charting, illustrating real profit created from the flow volume against the till sale, with additional profit from non-flow products via data from the till system; This can be illustrated, for either the product line, the product name, the product type, the till number, the location and over the required time period, with an option to buy alternatives online; b) tabular and graphical charting, illustrating the real cost created from the flow volume for both ‘Sale’ and ‘Wastage’ status, with additional costs from non-flow products via data from the till system; This can be illustrated, for either the product line, the product name, the product type, the till number, the location and over the required time period, with an option to buy alternatives online; c) tabular and graphical charting, illustrating the numbers of physical sales or times a customer has made this order, based only on non-theft ‘Sales’ from the till system; This can be illustrated, for either the product line, the product name, the product type, the till number, the location and over the required time period, with an option to buy alternatives online; d) tabular and graphical charting, illustrating the sales trend, based only on non-theft ‘Sales’ from the till system; this is calculated using the matrix manipulation method described in Claim 16 and can be illustrated, for either the product line, the product name, the product type, the till number, the location and over the required time period, with an option to buy alternatives online; e) tabular and graphical charting, illustrating the expected profitability, based only on non-theft ‘Sales’ from the till system; this is calculated using the matrix manipulation method described in Claim 16 and can be illustrated, for either the product line, the product name, the product type, the till number, the location and over the required time period, with an option to buy alternatives online; f) tabular and graphical charting, illustrating the product ranking, based only on non-theft ‘Sales’ from the till system and profitability; this is calculated on a ranking method, which orders the products on how profitable they have been for the business over the required time period, with an option to buy alternatives online; 20) A method according to Claim If for a customer user interface, facilitating a unique login user ID for single or multiple sites, based on a mobile or web based platform device, consisting of a) a screen size and resolution classification from the viewing platform; b) a display of either the website or mobile pages to illustrate the data to the user when logged in. c) an interface for changing the product names against the Module ID number on the website against the account login ID. 21) A method according to Claim lg to connect with the remote till system, for the adjustment of till pricing and in real time, for any product, against the user ID, consisting of steps of: a) a user interface to change product pricing; b) an online script call or data transfer to the till connecting server and out to the connecting till requested to change the prices; 22) A method according to Claim lh to receive the till data in real time and insert its data into to the remote database, for a comprehensive sales and stock holding analysis, consisting of steps: a) an online on application communication to a server side script call or other data transfer method to the working script from the till system directly or through another processing device. Each transaction will send the System ID, the till name, the clerk ID, the product, the sale price and the sale volume or other such variables. b) a search for the account ID against the unique till system ID number; c) an insertion into the database of the recorded sale; d) a search against the flow item that was sold to double link the record against the flow if the item is a fluid flow product;