WO2007148299A2 - Environmental monitor and power management system - Google Patents

Environmental monitor and power management system Download PDF

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Publication number
WO2007148299A2
WO2007148299A2 PCT/IB2007/052391 IB2007052391W WO2007148299A2 WO 2007148299 A2 WO2007148299 A2 WO 2007148299A2 IB 2007052391 W IB2007052391 W IB 2007052391W WO 2007148299 A2 WO2007148299 A2 WO 2007148299A2
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Prior art keywords
sensor
controller
data
battery
connection
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PCT/IB2007/052391
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French (fr)
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WO2007148299A3 (en )
Inventor
Darren Grant Lucinsky
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Concept Technologies Limited
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    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J7/00Circuit arrangements for charging or depolarising batteries or for supplying loads from batteries
    • H02J7/34Parallel operation in networks using both storage and other dc sources, e.g. providing buffering
    • H02J7/35Parallel operation in networks using both storage and other dc sources, e.g. providing buffering with light sensitive cells
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J13/00Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network
    • H02J13/0003Circuit arrangements for providing remote indication of network conditions, e.g. an instantaneous record of the open or closed condition of each circuitbreaker in the network; Circuit arrangements for providing remote control of switching means in a power distribution network, e.g. switching in and out of current consumers by using a pulse code signal carried by the network for DC networks
    • HELECTRICITY
    • H02GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
    • H02JCIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
    • H02J3/00Circuit arrangements for ac mains or ac distribution networks
    • H02J3/38Arrangements for parallely feeding a single network by two or more generators, converters or transformers
    • H02J3/381Dispersed generators
    • H02J3/382Dispersed generators the generators exploiting renewable energy
    • H02J3/383Solar energy, e.g. photovoltaic energy
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/50Photovoltaic [PV] energy
    • Y02E10/56Power conversion electric or electronic aspects
    • Y02E10/563Power conversion electric or electronic aspects for grid-connected applications
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E10/00Energy generation through renewable energy sources
    • Y02E10/50Photovoltaic [PV] energy
    • Y02E10/56Power conversion electric or electronic aspects
    • Y02E10/566Power conversion electric or electronic aspects concerning power management inside the plant, e.g. battery charging/discharging, economical operation, hybridisation with other energy sources
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02EREDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E40/00Technologies for an efficient electrical power generation, transmission or distribution
    • Y02E40/70Systems integrating technologies related to power network operation and communication or information technologies for improving the carbon footprint of electrical power generation, transmission or distribution, i.e. smart grids as climate change mitigation technology in the energy generation sector
    • Y02E40/72Systems characterised by the monitoring, control or operation of energy generation units, e.g. distributed generation [DER] or load-side generation
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y04INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
    • Y04SSYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
    • Y04S10/00Systems supporting electrical power generation, transmission or distribution
    • Y04S10/10Systems characterised by the monitored, controlled or operated power network elements or equipment
    • Y04S10/12Systems characterised by the monitored, controlled or operated power network elements or equipment the elements or equipment being or involving energy generation units, including distributed generation [DER] or load-side generation
    • Y04S10/123Systems characterised by the monitored, controlled or operated power network elements or equipment the elements or equipment being or involving energy generation units, including distributed generation [DER] or load-side generation the energy generation units being or involving renewable energy sources

Abstract

A device includes a power management system. The power management system has a circuit including a connection for a power source, a connection for a load, a connection for a first electrical storage battery and a connection for a second electrical storage battery. The circuit includes switches for selectively connecting each of the storage battery connections to the power source connection in a circuit wherein current may only flow to the battery connection. The circuit includes switches for selectively connecting each of the storage battery connections to the load connection in a circuit in which current may only flow from said battery connection. A controller is programmed to select a battery to be on load and a battery to be on charge. The controller provides output signals to the switches to connect the connections for the battery on load to the load connection and not to the power source connection, and to connect the battery on charge to the power source connections and not to the load connection. Other inventions are also disclosed.

Description

"Environmental monitor, sensors therefor, and/or power management system"

Field of the invention

This invention relates to an environmental monitor and to disparate parts suitable for use in the environmental monitor for use in agriculture or horticulture or any land use. One aspect of the invention concerns an environmental event prediction device, another aspect concerns a power management system, a third aspect concerns a ground temperature sensor and a fourth aspect concerns a cloud cover sensor. The second, and fourth aspects have utility outside the environmental monitor.

Background of the invention

All users dependent on the land for their livelihood such as farmers, horticulturists, croppers and growers, understand the importance of weather effects on their operations. Economically extreme events such as frosts can be devastating.

Currently users take as needed readings in relation to temperature, which are then connected to temperature alarms. These readings are taken by sensors and the results can be connected to a computer, with alarms being triggered once a set temperature is reached. However these types of alarms do not give sufficient warning to allow enough preventive measures to be taken, especially in the case of frost.

However frosts though dependent on low air temperatures, are complex weather events not just triggered by air temperature, but by many other factors such as different microclimates, humidity and wind.

The occurrence of Frost requires low air temperatures, so the prediction of the minimum air temperature (T311 mln) is quite useful in determining if a frost is likely. The first attempts at predicting T211 1111n were made as early as 1885. Cold damage to fruit and crops in the far western regions of the United States in the early 1900s prompted further studies. The first suggested empirical relationships simply related T311. mn to air temperature. These equations take temperature measurements at set times during the day and a mathematical interpolation is made from the maximum air temperature (T3111113x). One relationship suggested by Beals (Beals, Edward A., 1912: Forecasting frost in the North Pacific states. Bulletin No 41-W.B. No. 473, pp 49) used the "median hour" temperature which he defined as the mean time of the midway point between maximum and minimum daily temperatures. At the median hour half the temperature fall has occurred, from this point an estimate can then be made of the minimum temperature: air mm air mas \ air mas air median hour /

Further studies during the 1920s investigated relationships between Υm mιn and the Dew Point Temperature (Tdp) or wet-bulb temperature (Tw). Humphreys (Humphreys, WJ., 1914: Frost protection. Mon. Wea. Rev.42, pp 562-569) proposed an "evening dew-point" relationship which essentially predicted that Tm mm should equal the evening Tdp.

Much of the published work on predicting minimum air temperature has been based upon empirical hygrometric relationships involving relative humidity (H) and have the general form:

Tttm = F(Tdp) + F(H) where F( ) is a function

The first application of a curvilinear hygrometric formula was made by Young (Young, F.D., 1920: Forecasting minimum temperatures in Oregon and California. Mon. Wea. Rev., 16, Supplement, pp 53-60). His equation was:

Tωmn = Tdp - (H - n)/4 + Vd + VH Young's Formula

Where n = 20, 30 and 40 for clear, partly cloudy and cloudy skies, respectively, and Vd and VH are "constants that are empirically derived" and are dependant on the evening values of Td and H respectively.

Smith (Smith, J.W., 1920: Predicting minimum temperatures from hygrometric data. Mon. Wea. Rev., 16, Supplement, pp 6-19) developed a method to fit parabolic curves to the hygrometric data and obtained:

T3J1 mm - Tdp = a + bH + cH2 Smith's Formula (where a, b and c are empirically derived)

Nichols (Nichols, E. S., 1920: Notes on damage to fruit by low temperatures; prediction of minimum temperatures. Mon. Wea. Rev., 16, Supplement, pp 37-45) and Keyser (Keyser, E.M., 1922: Calculating temperature extremes in Spokane County, Washington. Mon. Wea. Rev., 50, pp 526-528) suggested that the line of best fit might be drawn by inspection rather than by fitting curves.

T111Mn = Tap + VH Nichols' Formula (where VH is empirically derived) Of all the empirical formula given, Ellison (Ellison, E. S., 1928: A critique on the construction and use of minimum temperature formulas. Mon. Wea. Rev., 56 pp 485-495) concluded that the hygrometric types were superior and Young's formula was best when sufficient data existed for determining its constants; otherwise the formulae of Smith or Nichols was best.

Since 1930 most of the studies concerned with forecasting local minimum air temperature (T311 mn) have essentially followed a hygrometric approach. The United States Weather Bureau developed a Frost Warning Service that had excellent success for over 70 years using these methods — one Bureau unit was awarded a citation in 2003 by the National Oceanic and Atmospheric Administration of the U.S. Dept. of Commerce for "outstanding specialised forecasting during the past year".

Applying the laws of heat transfer, it can be shown that the temperature of the Earth's surface at night should be highly correlated with that of the air in the surface layer. Therefore a good forecast of the minimum ground temperature should provide good forecast of the minimum air temperature. This logic resulted in the development of several semi-empirical and theoretical techniques and these have become popular in recent years.

Of particular note is Brunt's Formula (Brunt, David, 1941 : Physical and Dynamical Meteorology. Cambridge University Press, New York, pp 428). He is credited with the first theoretical solution of predicting the nocturnal cooling of the Earth's surface on clear, calm nights.

ΔT = (2 / π) * Vt σT4(l - a - bVe) / ρs Cs K8 Brunt's Formula

ΔT = fall in temperature at the ground surface

t = time from sunset to sunrise

T = sunset temperature of the ground

σ = Stefan-Boltzmann constant

ρs = Soil density

Cs = Specific heat of the soil

K5 = Thermal diffusivity of the soil

e = Vapour pressure a, b = Empirically derived constants

Obviously a complicated formula, but there are many constants. Once the Brunt equation is solved for known conditions (location history) the derived constants can be used to predict minimum ground temperature. There are several extensions to the Brunt Formula that have made other assumptions regarding heat flux, wind effects and height above ground and there are also many simplifications.

On review of the Weather Service prediction techniques used by various countries (World Metrological Office, Technical Note 157: Techniques of Frost Prediction and Methods of Frost and Cold Protection, WMO No.487), the most common formulae are those developed by Young and Nichols and/or a simplified Brunt equation. In all cases however, constants need to be empirically derived to solve the equations and this requires the analysis of history data. Consequently many of the simplified formulae lump all the constants together, minimising the mathematics of the equation.

The term "comprising" as used in this specification means "consisting at least in part of. When interpreting each statement in this specification that includes the term "comprising", features other than that or those prefaced by the term may also be present. Related terms such as "comprise" and "comprises" are to be interpreted in the same manner.

Summary of the Invention

It is the object of the present invention to provide an environmental event prediction device, a power management system, a ground temperature sensor and/or a cloud cover sensor which will go some way toward overcoming these problems or which will at least provide the public with a useful choice.

In a first aspect the invention consists in a device including a power management system comprising

a circuit including a connection for a power source, a connection for a load, a connection for a first electrical storage battery, a connection for a second electrical storage battery and switches for selectively connecting each said storage battery connection to said power source connection, in a circuit wherein current may only flow to said battery connection, and to said load connection, in a circuit in which current may only flow from said battery connection, and a controller programmed to select a battery to be on load and a battery to be on charge, and to provide output signals to said switches to connect the connections for said battery on load to said load connection and not to said power source connection, and to connect said battery on charge to said power source connections and not to said load connection.

According to a further aspect said controller is programmed to, if said battery on charge has immediately prior been a battery on load, connect said battery on load to said load connection before disconnecting said battery on charge from said load connection.

According to a further aspect said circuit includes at least one switch to connect and disconnect the power source connection to the load connection, including in parallel with a said battery connection, and said controller is programmed to provide output signals to control said switches.

According to a further aspect said controller is programmed to disconnect each said battery connection from said power source connection and said load connection and to determine the battery voltage of each said battery and to select the battery with the lowest terminal voltage to be the battery on charge, and the battery with the highest terminal voltage to be the battery on load.

According to a further aspect the device included a solar power source connected to said power source connector, said circuit includes a known load and switches to connect said solar power source to said known load, and said controller is programmed to determine the voltage level offered by said solar power source across said known load.

According to a further aspect said controller is connected to said load connection.

According to a further aspect the device includes a support structure, and one or more environmental sensors supported on said support structure and connected to said load connection.

According to a further aspect said environmental sensors provide output data for an event prediction program to predict environmental events from said sensor output.

According to a further aspect said environmental sensors include said controller, said controller generating data indicative of the determined light level from said output voltage of a solar power source.

According to a further aspect said sensors include two or more of the following: • air humidity sensor

• air temperature sensor

• air pressure sensor

• lapse rate sensors

• ground temperature sensor

• wind speed detector

• a cloud coverage sensor

According to a further aspect said ground temperature sensor includes a first sensor for location immediately above ground, and a second sensor spaced close below said first sensor for location immediately below ground.

According to a further aspect said cloud coverage sensor comprises an image capture device arranged on said support structure to take images of at least a part of the sky when said support structure is locates upright in an open sky location, a controller connected to receive image data from said image capture device and process said image data to generate summary data representative of the cloud cover detected in said image.

According to a further aspect said device includes a transmitter and said controller is programmed to send output data from said sensors over said transmitter.

In a further aspect the invention consists in apredictor for environmental events comprising:

a controller programmed to receive data from at least three sensors at a single locality, said sensors being selected from the group of

• air humidity sensor

• air temperature sensor

• air pressure sensor

• lapse rate sensors

• ground temperature sensor • wind speed detector

• cloud coverage sensor

and to determine for said locality, from said data, a prediction of the occurance of a predetermined environmental event by calculating a plurality of meteorological parameters from said data, comparing said calculated parameters against one or more stored scenarios for said location to determine the likelihood that an event will occur.

According to a further aspect said controller provides an alarm signal or alarm trigger data if said prediction is for the occurance of the event.

According to a further aspect wherein said controller calculates from said data and/or said parameters, a predicted time frame for said event, and provides output data indicating the predicted time of said occurance of said event.

According to a further aspect said controller stores said calculated parameter data, and data indicating the actual occurance (or not) of a said event.

According to a further aspect said meteorological parameters include at least two of:

• dew point

• lapse rate

• air temperature

• ground temperature

• air pressure

• an estimate of the time when a minimum temperature will occur

• a frost time estimate

According to a further aspect said parameters include a predicted minimum nocturnal air temperature.

According to a further aspect said controller calculates a said minimum nocturnal air temperature using data from a dew point sensor, said dew point data collected after the maximum daytime temperature is reached. According to a further aspect said controller calculates a said minimum nocturnal air temperature using data from a said cloud cover sensor.

According to a further aspect said parameters include a minimum ground temperature.

According to a further aspect said controller calculates a said minimum ground temperature by modifying a said minimum nocturnal air temperature using data from said ground temperature sensor.

According to a further aspect said controller calculates a said minimum ground temperature using a derivation of the Brunt formula.

According to a further aspect said predetermined event comprises a frost, and predicts a time when the occurrence of said frost will commence.

According to a further aspect said controller calculates said time for said frost to occur by estimating backward from the typical coldest minimum temperature time assuming that that is the time when the minimum predicted air or ground temperature will occur.

According to a further aspect said controller determines a prediction for the occurance of an event for each node of a plurality of remotely located data collection nodes.

According to a further aspect said controller is programmed to send or cause to be sent an alert to a client associated with a data collection node for which said program predicts the occurance of an event.

According to a further aspect said predictor includes a software program which performs the steps of:

generating a map of a client property including locations of a plurality of data collection nodes;

indicating on said map whether said node location is predicted to experience an event within a subsequent known time frame;

presenting said map to a user.

In a still further aspect the invention consists in a data collection node for an environmental event prediction system includes a ground temperature sensor comprising:

a support structure, a first temperature sensor, suitable for detecting the temperature of air, mounted on said support structure at a first location

a second temperature sensor, suitable for detecting the temperature of earth, mounted on said support structure at a second location spaced close below said first location.

According to a further aspect said second sensor is spaced less than 10cm from said first sensor.

According to a further aspect said node includes a downwardly facing shoulder on said support structure at a level between said first sensor and said second sensor.

According to a further aspect said support structure comprises a spike for inserting into the ground.

In a still further aspect the invention consists in a cloud cover sensor comprising:

an image capture device arranged on a support structure to take images of at least a part of the sky when said support structure is located upright in an open sky location, a controller connected to receive image data from said image capture device and programmed to process said image data to generate summary data representative of the cloud cover detected in said image.

According to a further aspect said image data represents the colour and/or brightness of each element in a two dimensional pattern of image elements and said controller is programmed to determine for each element between sky and cloud based on the brightness and/or colour of each element and aggregate a value from the elements determined to be sky or cloud.

According to a further aspect said controller aggregates said value from weighted values for individual elements, wherein said weighting is determined by the location of said element in said two pattern.

According to a further aspect said image capture device comprises a digital camera and each said element comprises a pixel in a captured digital image.

According to a further aspect said support structure includes a spike for inserting into ground, and said camera is oriented to point along the axis of said spike in a direction away from the ground insertion end of said spike. According to a further aspect said controller is programmed to determine whether it is presently daytime or night time, and to chooses a filter for determining a pixel as sky or cloud according to said day/night determination.

In a still further aspect the invention consists in a data collection node for an environmental event prediction system includes a cloud cover sensor as set forth above.

To those skilled in the art to which the invention relates, many changes in construction and widely differing embodiments and applications of the invention will suggest themselves without departing from the scope of the invention as defined in the appended claims. The disclosures and the descriptions herein are purely illustrative and are not intended to be in any sense limiting.

Brief description of the drawings

Embodiments of the invention will be described by way of example, with reference to the figures of the accompanying drawings.

Figure 1 is a schematic representation of the events prediction system.

Figure 2 is a schematic representation of the components of the master station.

Figure 3 is a schematic representation of the collection node.

Figure 4 is a schematic representation of the components of the solar power unit.

Figure 5 is a schematic representation of a ground sensor.

Figure 6 is a schematic representation of the components of the air temperature sensors.

Figure 7 is a schematic representation of the humidity, temperature pressure sensor.

Figure 8 is a schematic representation of the components of the cloud daylight infrared sensor.

Figure 9 is a schematic drawing showing how the node controller interact with the sensor modules.

Description of the preferred embodiments

In summary as shown in figure 1, the preferred events prediction system 1 includes the following components operatively in communication with each other: sensors 2 to gather real time readings and supply data to at least one collection node 3. The collection node 3 in turn sends the data via local radio communication 3a to a master station 4 which gathers other readings from other nodes 2. The master station 4 in turn sends the collected data via another communication network 4a to a data processing centre such as computer 5 or at least one computer(s) or fax or laptop or client phone. Communication means 4a can, for example, be cellular, POTS, VPN via the web or cellular or telephone network.

The communication between any or all of the sensors, nodes 3, master station 4 and server 5 can be remote (wireless) or wired and can transmitting or receiving or both.

Generally there will be more than one collection node. Each node 3 will have at least one sensor. The data centre can include a server executing a software program. The server 5 preferably provides a user or operator with a means to visually see the results and/or alarms which can be accessed or automatically passed on to other users.

The preferred event prediction system 1 uses remote collection nodes 3 to collect meteorological sensor information to predict the minimum nocturnal temperature and time at each node site. Ideally each micro climate in a typical installation location should have at least one node and a client site is likely to have several micro climate sites of interest. In summary, if the prediction system predicts that the minimum nocturnal temperature will be less than zero degrees (all temperatures indicated in Centigrade), the system makes a further estimate is made of when the temperature is likely to achieve zero (prior to the average time of minimum temperature). Preferably the system provides a web, interface for users to view the data and any predictions.

Each remote node collector 3 collects data and sends it to a master station 4 which relays the data to a server 5 at the data centre. The server has software that displays, stores, analyses and allows modelling of the data. From the collected information, the server calculates a series of current metrological parameters including dew point, lapse rate, air temperature, ground temperature and air pressure. The maxima, minima and mean parameter values (for example taken over a predetermined time period) for each node location are recorded throughout the day and night as well as what time they occurred.

The server also records the time at which the temperature maximum and minimums occur is recorded, so that the server can estimate when (on future nights) minimum and maximum temperatures can be expected. Once the maximum temperature for the day has passed (for example 1600 hours) the server analyses the accumulated received data from each node and, for each node, estimates the minimum nocturnal temperature using hygrometric formulae. The server is programmed to determine a temperature bandwidth (typically 1.5 standard deviations from the average = 86.6% probability range). If the lower extreme of this bandwidth is near (or less than) freezing, the server generates a report (or alarm). If the temperature minimum is estimated to be less than zero degrees (freezing), the server makes a linear prediction of when the zero point is likely to occur - this is the frost time estimate.

For each node the server stores previous sensor readings of metrological parameters. This historical sensor data is algebraically weighted according to its likely correspondence to the present date (specifically from the night before, the last seven days and the same time last year) and combined to determine hygrometric constants and parameters. This allows the previous night's estimate, for example, to be compared with the previous night's actual minimum temperatures to determine how close the estimate actually was. Should the temperature estimate prove to be too far out, the hygrometric equations can be solved with known parameters and the constants re-evaluated. The server records constants used for each daily estimate so that they can be reviewed and analysed post-estimate to improve prediction accuracy.

Preferably the system is predictive and/or has a learning capability.

In the case of frost, there are several effects relating to metrological parameters that occur prior to and during frost formation that can be detected (change in lapse rate or air temperatures, humidity, air pressure, air movement, ground temperature). A summary of certain typical frost formation conditions follows as Appendix A. Each time the server determines that a frost event has actually occurred for a particular data collection node, the server assesses stored sensor data to determine what and when changes occurred in the sensor data prior to the event. Sensor parameters are then recorded as a "frost scenario" for this data collection node. Each frost event can be stored and used to further enhance the predictive capability.

The server is programmed to sort and compare these scenarios in a scenario manager. The scenario manager has a series of options it can take if various "scenarios" are detected. For example the scenario manager triggers a variety of alerts based on the scenario classification (predicted frost) and sensor readings. There are obviously other types of alerts that could be detected, but the key to frost management is the need to know in advance. Other alerts are possible based on real-time readings meeting set parameters.

The server program preferably includes a user interface providing access to the scenario manager and the datastore, such that any operators having access to server 5:

- are able to control and store the modelling and classification of data from events - scenarios. - can collect data from all nodes for possible re-processing, sales to new clients, etc.

- can control all reporting techniques from a central point.

- clients will always see the latest version of scenario manager.

- clients can log into a web interface and "see" the status of their frost site and public (those provided by system owner) nodes.

- can monitor the status of each Master Station to check it is responding - unresponsiveness will cause an alarm condition.

- can monitor the status of field equipment for maintenance purposes as each node and sensor are identified uniquely.

- can charge a fee for scenario management and alert services

All hygrometric analysis is performed at the data centre for business security and system control. Using a data centre allows charging for services and keeps the system owner in constant contact with their clients. Having public or system owner owned or sponsored sensor nodes allows the sharing and sale of the same information several times and is another feature of the system owner business model. Continuous monitoring, like an alarm centre, allows a variety of features that benefit both client and system owner.

Utilising the web interface allows the client access to their node information from anywhere in the world. There will be a capacity limit to the number of nodes a data centre can handle — either a communication, data storage, processing speed or financial bottleneck. However this is one of the few ways that system owner can control the service, so regional data centres are preferable.

The inventors intend that nodes report frequently, for example every six minutes - this is to generate sufficient data for fast response to changing conditions. The data rate can be easily adjusted centrally by system owner if necessary.

The prediction calculations are described as being performed at the server 5. However it would be equally possible for the prediction calculations to be performed at the master station 4 or at each collection node 3. It would also be possible for the parts of the calculation to be distributed between these parts. In effect a node could operate as a standalone device including data collection, calculation and reporting for a single location. Alternatively a group of nodes could operate with a master station, sharing the calculation between them, but providing a central reporting function to the user through the master station.

According to the preferred embodiment of the invention a collection of sensor devices (at least two), are assembled into a system to enable frost prediction by collecting metrological sensor information. The same basic nodes can have additional sensors attached for other purposes. Customised applications for soil temperature, gas detection, PIR sensing, etc are all possible add-ons for a collection node.

A summary of the devices or apparatus for a standard frost prediction system according to a preferred embodiment incorporating all of the inventions defined herein could be as follows:

Server 5

A central data centre including a server and scenario manager software executable on the server. The server could preferably include a cellular communication module for communicating and a POTS Network connection for playing back recorded messages, sending fax alerts and accessing a pager network, for pager alerts. The server may also preferably include a VPN network connection to client site master stations 4.

Preferably the server has web reporting software for presenting a user interface for data access and manipulation by clients and system owners.

Server 5

Scenario Manager

Each scenario is essentially a set of sensor trigger points compared to the timeframe of an event. Typically the sensors will indicate several key parameter movements that occur prior to the occurrence of an event. These key indicators will vary from micro climate to micro climate, hence the need to post-process the sensor history of a real event to re-calculate and trim local parameters and create customised scenarios for each collection node.

The scenario manager compares a group of sensor readings against a set of predefined scenarios for the respective collection node to see if the trend of the readings is likely to fit into a known (undesirable) scenario. Based on what type of event this scenario indicates will occur (or looks like it will) the scenario manager program proceeds to calculate a time frame based on existing sensor readings is calculated (if possible). Where a real time frame is calculated, and the sensor readings fit into an undesirable scenario, an alarm will be triggered. The scenario manager program processes sensor readings on a server at the data centre. Using minimum temperature estimates and time frames plus current sensor data and its trend, an increased prediction confidence is possible. If both the estimated minimum temperature and the current temperature trend look like they will coincide, it is probable that the hygrometric parameters are correct. An alarm needs to be triggered if the minimum temperatures are predicted at or below freezing.

The formulae used by the scenario manager to predict the minimum nocturnal air temperature may initially be based on the Nichols' Formula as this is very easy to calculate from a database point of view. Once the temperature maximum has been achieved for the day (approx 1500 hours) the database selects the dew point temperature recorded at the maximum and feeds this number into the Nichol's equation. The software uses data collected over preceding days and nights to calculate the missing parameters using simultaneous equations with average, maximum and minimum parameter values.

Using cloud cover data from the preferred data collection node, the software makes another estimate using Young's formula. These two bandwidth estimates should overlap or coincide.

Preferably the software uses ground temperatures to modify the estimates by applying a correction if the ground temperatures are above or below estimated dew point temperatures. If there is sufficient data in the database for the collection node the software can also use a simplification of the Brunt formula (with constants lumped together) to determine the minimum ground temperature (algorithmically). The software can determine parameters for the simplified Brunt formula using simultaneous equations. The software feeds the max, min and mean values into the formula to obtain a minimum ground temperature bandwidth.

The Brunt calculation complements the other calculations. Ground temperatures that fall below the Dew Point will form condensation and should temperatures keep falling to zero or below, a frost will form.

After estimating the minimum temperatures the software reports any temperatures that are predicted to fall below or close to zero. Typically the minimum temperatures will occur in the last stage of the night (say 0600 hours) prior to daybreak the next day. Where the software estimates a minimum temperature value below zero, the software proceeds to estimate (linear straight line) back from the typical minimum temperature time to determine a prediction of the approximate time when the temperature will reach zero degrees. This time forms a time frame for frost occurrence. Once the sun has set, the software can calculate a better estimate of the zero degree timeframe by calculating using the current rate of change of temperature within the ground and the air.

Web Reporting

As shown in figure 1 sensor 2 data collected by the collection node 3 is sent back via the master station 4 and the communication network to the server 5 for analysis and storage. The client may log on to the Web Server to see a map of their property and an indication of the node positioning in relation to the map. The display will show the current node status information and upon selection, more details such as specific sensor readings may be made available to the client

Preferably the web reporting module generates a map showing an immediate visual verification of the status of each node. Any node that has an alarm condition can then be instantly identified and interrogated further.

Master Station 4 - see figure 2

The Master Station 4 as shown in figure 2 is the communication controller for the central collection of node data. Master station 4 is responsible for displaying node status, configuring nodes 3, sensors 2 and setting off local alarms and actuators.

Figure 2 shows the logical design for the master station. The firmware within the master station controller 10 manages the interface between each of the blocks and performs diagnostic, housekeeping and communication scheduling functions.

Controller 10 includes memory and time functions (clocks etc). These features may also be handled by the server 5 or by a PC at the interface 11. The master station 4 is not essential with the system being able to operate in some cases without a separate station - for example with only one node collector or alternatively be combined with the data management system or server 5.

As shown in figure 2, the preferred master station 4 includes a master station controller 10, an interface 11, node communication system 12 (eg an external aerial), a status display 13, an alarm 14, telecommunication interface 15, cellular network communication interface 16 and a VPN network interface 17. The external aerial can be located remotely from controller 10 which can be housed in a housing. The housing can also include a display 13 or the display can be handled by a local PC which could then show status display, alarms and network connections.

Master station 4 can be powered from the mains or from other sources, so the transceiver (RF serial modem) for the node communication 12 can be continuously in 'receive' mode. That way if any node has an alarm condition or a status fault, it can be immediately reported to the master station for display on the status display 13 and communication back to the data centre.

As a device, master station 4 is quite simple. In summary, master station 4 is a data communications manager and status display device. The most complicated portion of its communication manager is the mechanism that is used for reporting back to the data centre. Preferably this uses a VPN -Virtual Private Network 17 using either a managed network controller or mini-PC based system. A cellular communications module 16 is typically intended for SMS Text Messaging and the Telephone (POTS - Plain Old Telephone System 15) would mostly likely be used for paging. Recorded message payback is also possible, but this would require a standard message to be kept at the master station and modification may be difficult (recording quality issues and the extreme length of audio files).

Collection Node 3

Collection nodes 2 should be placed in all areas of interest - say along a known frost front or starting point. The node controller 26 contains the RF modem for communication to the master station as well as memory storage and a clock for time and date information (real time clock).

Using the preferred off-the-shelf transceiver there can be 127 separately addressable nodes within the range of any one master station 4. The modems come in a range of frequencies (channels) so neighbours can be isolated by either address range or channel selection. Should this prove an insufficient address space, the address range of the nodes can be expanded, but as the serial modems have limited directional range and a variety of channels to choose from, this is a low risk.

Figures 3 & 9 show the physical layout of the exemplary collection node 3. A node consists of the following basic components:

Pole or standard 19

Warning or alarm module - xenon flash device, 20 Cloud, daylight and infrared (CDI) sensing apparatus 21,

Transceiver aerial 22,

Wind speed indicator (WSD) apparatus, 23

Lapse rate sensing (LRS) apparatus 24

Node controller (and transceiver module) 26.

Power management apparatus 27

Humidity, temperature and pressure (HTP) sensing apparatus 28,

Ground temperature (GND) Sensing apparatus 29

Node communication module 26a

Real time clock 26b

Memory 26c

As indicated in schematic figure 9, each sensor module or apparatus 21, 23, 24, 27, 28 & 29 on node pole 18 is connected to be interrogated by the node controller 26. The node controller is programmed to assemble sensor readings into a data packet for transmission at the end of each period interval (for example each six minutes) to the master station and/or server. The node controller 26 is also programmed to create error checking data in the form of a simple CRC check combined with a byte count. Should the transmitted data not be acknowledged or erroneous, the node controller 26 is programmed to retransmit the data several seconds later.

The data memory 26c within node 3 is preferably constructed as a continuous loop buffer, so many days worth of data can be stored within a node before any over-writing takes place. This allows a reasonable time frame to repair transmission faults or issues with master station 4 without losing data.

As node 3 could possibly be the tallest entity in an area, there is a possibility of lightning strike. The amount of energy in a lightning strike is enormous and even with a lightning rod, damage to the node would be inevitable. Node pole 19 is preferably made of light-weight materials.. Node pole 19 needs to be removable from the ground and is preferably collapsible into sections for access to the upper sensors for maintenance and installation. Preferably the node support structure or pole is formed from a metal, such as steel or aluminium bar or pipe to the power supply module. The power supply module is both the single heaviest item and will act like a sail in high wind conditions. Beyond the solar panel, a plastic (or other non conducting material) pole should be used, as the sensors above this point are lightweight and this would reduce the risk of lightning strike.

Collection node modules/apparatus

The collection node 3 has an array of attached modules. Each module, being items 20 to 29 in Figure 3, is described below.

Visible Alarm - xenon flash module 20 in figure 3

Module 20 provides a visual verification that an alarm condition has been triggered. This is activated by the node controller 26 or master station. Preferably module 20 has low power requirements and is elevated for viewing.

The controller 26 is programmed to activate the flash module when the event predictor indicates an impending event or when any significant aspect of the system reports a fault to the node controller.

Transceiver + Transmission Aerial 22 in figure 3

The node controller includes a transceiver for communicating with master station 4.

One suitable transceiver is a TAIT radio modem TOP-X271A-T0. Each unit is capable of 310 separate channels over six different frequency bands. This allows a sufficient variety of selections to avoid local interference and contention with neighbouring systems.

Electrically this device looks like an RS485 (addressable) interface with an RF aerial BNC style connector and 12v power connections. The RF connection is to an external aerial via 75ohm coaxial cable. The power requirements vary from 50mA on standby to 2A for burst transmission. In the preferred data collection node the transmission bursts are short (approximately 3 seconds) and at intervals of six minutes, so the power supply has time to "recover" before supplying another large current pulse. Operation of the transceiver is is determined by the node controller and is a mixture of software and hardware settings.

An equivalent transceiver is also used within each master station 4 and is labelled 12 in figure 2.

Master station controller 10 can change the channel settings on the transceiver or can use a network style node address system. The Tait unit is capable of a multi drop addressable communications (RS-485). This is where one master transceiver (at the master station for example) can communicate with and control up to 127 slave units (one at each node 3) on the same channel as long as their addresses (8 bit with 1 bit used for R/W indication, hence 7 bits = 128, zero not used = 127) are different. The slaves (nodes) always receive unless asked to transmit by the master station. This system is a "pole and respond" type of communication mechanism and allows the master to easily step through the slave addresses, simplifying the control software within the micro controller. Each node (slave) is asked in turn for a status report and its data. The master station controller will record an error condition for nodes that do not respond.

Wind Speed Indicator WSD apparatus 23 in figure 3

Frost does not occur (easily) if the air is moving, that is why smoke pots and helicopters are so effective at stopping frost formation. Wind direction is mostly irrelevant as long as the air is moving. Sites near oceans and mountainous areas could see more dramatic effects due to wind direction, but this is more of a wind chill (or warming) effect. A standard anemometer will indicate wind speed and direction and this sensor is available from a variety of third party sources

Electrically, most speed indicators provide a pulse train of say 32 pulses per revolution (possibly as low as 4). These pulses are fed into a counter on the node controller. The node controller is programmed to read and clear the counter periodically. The value of the count during a fixed period is directly proportional to the velocity. The datasheet on the specific anemometer will provide the necessary specifications to convert revolutions (per minute) into wind velocity (metres per second). The controller preferably stores the conversion data in a suitable lookup table. The controller reads conversion data from the lookup table to convert the determined count data to wind speed.

Power management apparatus 27- figure 3 & 4.

The power management apparatus 27 as schematically shown in figure 4 is designed to be particularly adapted to power a collection node 3. However the power management device may also be applied to power supplies for other installations requiring or using battery backup.

In the preferred embodiment the power management apparatus has physical support structure. However the elements of the apparatus may be integrated into other modules or devices.

The apparatus includes a controller 30 operatively connected to a power supply output or load connection 31. Preferably the apparatus includes a data transfer interface, such as a RS485 Bus 32 to operatively connect the power management apparatus and all the other system modules back to the node controller 26.

The apparatus includes connections for first and second batteries 34 & 35.

The apparatus 27 includes a power source connector. For remote installations, and particularly for the preferred horticultural application, the apparatus includes a solar power source such as a panel 33. The panel may be located outside the case of the power management apparatus. The power source may be any other suitable power source depending on the intended application, including mains power, with the batteries specifically being provided for emergency backup power.

The controller includes connection circuits and switches to make and break connections between the first and second battery connections, the power source connection and the load connection. These circuits allow for each battery connection to be connected to either the power source connection or the load connection. The circuit or circuits for connecting the battery connection to the power source connection only allow current to flow to the battery. The circuit or circuits for connecting the battery connection to the load connection only allow current to flow to the load connection.

The preferred circuits of the controller also allow for the power source connection to be connected and disconnected from the load connection. The circuits provide, as an alternative, for the power source connection to be connected across a known standard load.

The controller switches may comprise transistors or suitable capacity for the expected power supply requirements, each transistor being gated by an output of a processor or section of control logic. The various connection circuits may include suitable diodes or diode bridges to ensure the required current flows.

The controller is programmed to switch periodically from one battery to the other. One battery is used to power or backup the load while the other is being charged. During the day the power management apparatus 27 tries to feed solar power exclusively to the node modules (sensors and devices) using the battery connected to the load as backup if the light level drops due to clouds etc.

Preferably power management apparatus 27 also occasionally switches the solar panel to operate across said known load and records the solar panel voltage. The solar panel voltage over the known load indicates the radiant intensity of the sun. Most solar panels 33 provide similar voltages even in poor lighting conditions, but the current capability changes dramatically. Data derived from testing the solar panel voltage level across a standard load indicates the solar panel current which is proportional to solar intensity (on the panel).

Frost typically occurs during poor weather so the lighting levels are not high during the day and the battery voltage levels suffer. Power management apparatus 27 may use a charge pump to increase the voltage level from the solar panel so that some battery charging can still occur - this may be economically less efficient than just using larger batteries or solar panels. For the preferred application, the power management apparatus 27 should be able to run the node 3 for several days without charging the batteries 34, 35 at all, but this could indicate some form of failure, such as the solar panel being blown off or covered.

Power management apparatus 27 is preferably controlled by a microcontroller 30 that has interface circuits adapted for testing voltage levels. The microcontroller 30 includes memory for storing sensed voltage levels. The microcontroller is has a communication interface, such as Rs485 Bus 32, for communicating to the node controller 26. Node controller 26 and power management apparatus 27 communicate about the voltage levels of the batteries 34 & 35. Should batteries 34, 35 not be charging or there are other problems with the power levels, the power management apparatus 27 will indicate an error condition for node controller 26 to pass on to master station 4 and then on to server 5. Both the master station 4 and the server 5 will take action in the form of alarms and warnings to ensure continued power availability.

In one embodiment the power management apparatus 27 is programmed to perform the steps:

a) Initialisation and setup.

b) Disconnect Solar panel 33 from battery 34 being charged and main output power 31. Next determine the solar panel open circuit voltage. This will indicate if the solar panel exists

c) Connect solar panel 33 to a known fixed load (based on the specification of the solar panel) and read the voltage level. From the voltage (V) across the known load (R) the current (T) can be determined (V = IR). The solar panel current output is directly related to the incident intensity on the solar panel. Then determine the incident intensity. . If the voltage on solar panel 33 has dropped to half (9v) of the maximum (18v) determine the occurance a sunset condition. If the voltage on solar panel 33 rises to half (9v) of the maximum (18v) determine the occurance a sunrise condition. d) Determine the battery voltage of the battery 34 just disconnected from charging. Now connect this battery 34 to the main output power 31 connection and check the voltage level. Disconnect the other battery 35 from main output power 31 and check the voltage level of the battery 35. Now connect battery 35 to solar panel 33 for charging and check the battery voltage level. If the level does not increase determine that the battery is not charging correctly. Connect the main output power to solar panel 33 so daytime running is, as far as possible, entirely from the solar panel 33.

Report the battery status information and solar intensity to the node controller 26.

e) Sleep (microcontroller low power mode) until the node controller 26 wakes (activates) the power management apparatus 27.

Go to step b).

The use of charging controllers is standard practise, but the inventor is not aware of any power management system using two batteries (or two sets of batteries) and alternating between them for load balancing and battery recover.

The controller minimises power consumption between sample times by putting the power management apparatus controller to "sleep" (low power mode).

Ground temperature (GND) sensing apparatus 29 - figures 3 and 5

The ground temperature sensing apparatus (GND) 29 of figure 5 is used to determine how far temperatures have been absorbed into the ground. Heat stored in the soil is radiated at night and assists in keeping the ground warm enough to ward off a frost or at least minimise the effect of frost - the reverse is also true. As soil temperatures drop over increasing periods of cold weather, the ground becomes more susceptible to surface frost when air temperatures start to approach freezing and are below the dew point.

GND sensing apparatus 29 includes ground spike for pushing into the ground. The ground spike supports several sensors 41-45 under and just above the ground. The spike is adapted to be inserted into the ground or any support means such that it can support at least one sensor and communicate with the rest of the events system. Two sensors, one intended for location just under ground 43 and one intended for location just above ground 44, allow the detection of temperature transitions near the surface of the ground. Ground surface temperature is defined to be the just under ground QUG) temperature. Air surface temperature is defined to be the just above ground (JAG) temperature. Preferably the support spike 49 includes a downwardly facing shoulder at or very slightly below the intended ground level. The spike can be driven by a user until the shoulder presses against the ground surface. This shoulder is located at a level between the sensor 44 and the sensor 43 so that with the shoulder pressed to the ground the sensor 43 is just below ground and sensor 44 is just above ground.

The ground temperature readings combined with the solar intensity information (power management apparatus and CDI) can be used by the event predictor in a calculation to determine the absorptivity of the soil. This is one of the parameters in the Brunt equation.

In the preferred embodiment there is also a sensor 45, 5cm into the air and two more 41 & 42 buried in the ground at 25cm and 50cm respectively. These sensors are connected back to a GND controller 50 on a common communication bus, such as an I2C bus. The GND controller 50 collects the temperature readings together and passes them on to the node controller 26 via an RS485 interface 32. The event predictor can use data from these additional sensor data for making further corrections to parameters used by the hygrometric equations.

In one implementation the GND sensing apparatus 29 is programmed to take the following steps:

1. Initialise and setup.

2. Take temperature readings on all sensors 41-45.

3. Report the temperature information to the node controller 26.

4. Sleep until woken by the node controller 26.

5. Go to Step 2.

To sense ground temperatures, a temperature sensor can be placed on, above or below the ground to determine the temperature. Ground sensor 29 groups more than one sensor together. It defines the temperature sensors JAG and JUG and their positioning and keeps a copy of max, min, and mean temperature variations. The GND controller minimises power between samples by putting to "sleep" all of the sensors and controllers when not in use.

Lapse rate sensing (LRS) apparatus 24- see figures 3 & 6.

In the preferred data collection node air temperature sensors are placed high in the air on the node pole 19 (figure 3) at 6m, 4m and 2m from the ground, to allow the calculation of the lapse rate (the rate at which the air is cooling at different altitudes). Essentially the controller 50 calculates a temperature gradient to see how quickly the air temperature is falling (or rising).

Should the ground temperature, air temperature and dew point temperature start to coincide or fall at a (lapse) rate that will go below zero or below a known (as calculated from historical data) level the event predictor will see that the collection of parameters match a defined scenario that indicated the strong likelihood of a frost and an alarm can be triggered.

Electronically the lapse rate sensing apparatus may advantageously form part of the GND sensing apparatus as it is also gathering in temperature readings, so the input interfaces to the controller will be compatible. Figure 3 indicates the physical placement of the LRS sensors such as sensors 24. Figure 6 provides a schematic layout of the relationship of the GND 29 and LRS sensors 2. The LRS sensors may be coupled to the GND controller to save on microcontrollers and minimise the part count and power requirements. The GND Sensors 29 and LRS sensors 24 can report back to one microcontroller 50 for calculation purposes and this micro can then pass the data onto the node controller 26.

Preferably the temperature sensors for the ground sensing (56-60) and LRS (51-53) are stand alone electronic devices that communicate through a suitable shared bus, for example an I2C bus. Suitable sensors include DALLAS digital thermometers - part numbers DSl 621 and DS1631. The two devices are very similar except that the DS1621 has higher resolution (512th degree). The DSl 631 has less error, but also less resolution.

The lapse ratesSensors 51-53 are air temperature sensors placed a differing heights which can form (electronically) part of the GND sensor module. The GND Controller 50 keeps a copy of maximum, minimum, and mean temperature variations for these sensors. The controller 50 preferably also minimises power between samples by putting to "sleep" all of the sensors and controllers when not in use.

Humidity, temperature, pressure (HTP) sensing apparatus 28 - see figure 7

This apparatus takes readings of humidity, temperature and air pressure via humidity sensor 64, temperature sensor 65 & air pressure sensor 66 and communicates this data back to the node controller 26 via RS485 Bus. 63. A logical diagram of the sensor is shown in figure 7.

The humidity and temperature can be used for the calculation of dew point using standard physics. From the dew point and current temperatures an estimate of the frost point can be determined. Dew point temperatures are a set point for the frost alarm and the value itself gives an indication of how "deep" the frost might be.

The air pressure is also monitored with this sensor module and it helps indicate that other weather changes may occur. Frost occurs when the air pressure is high (indicating possible clear skies). Low air pressures would indicate that you were in poor weather conditions already and the need for a frost warning is not necessary as other weather factors would take precedence (rain, storms, etc).

The air pressure is monitored with a standard pressure sensor such as a Motorola MPX4115A. This type of device outputs a voltage level that is directly proportional to air pressure. As only the atmospheric pressure ranges are required, the output of the pressure sensor needs to be offset and scaled up to provide more accuracy. This is done with some standard interface which allows an upper and lower voltage reference to be specified to the HTP Controller. The interface preferably applies a multuple-bit analogue to digital conversion across this defined reference range.

The humidity is classically (and professionally) determined by obtaining the wet and dry bulb temperatures and then determining humidity from charts or calculations. As the HTP sensor 28 will be used in near-freezing conditions, using a wet bulb temperature sensor would be ill- advised. There has been some success recently with digital humidity sensors. One such device is the Sensirion ™ SHT75 which not only provides humidity, but also temperature at the same point.

The SHT75 has been calibrated at the factory with calibration parameters set in digital OTP (One Time Programmable) memory. The HTP controller 61 calculates dew point from the temperature and humidity readings using the simplified dew point formula developed by Berry [RA Berry, Jr. 1945: Handbook of Meteorology, McGraw-Hill, pp 343]. There are other versions of this formula, but the mathematical capabilities of the HTP controller 61 may be limited, as may the resolution of both the temperature and humidity sensor. Using more complex formulae would be a considerable firmware commitment (in terms of total HTP controller capacity) for very little increase in accuracy and/or resolution.

In one embodiment the logical steps the HTP sensing apparatus 28 will take are as follows:

1. Initialise and setup.

2. Activate sensors and wait a few seconds for stability. 3. Read the voltage level on the air pressure sensor and convert to mBar.

4. Read the temperature and humidity and calculate dew point.

5. Report status information to the node controller.

6. Sleep until woken by the node controller.

7. Go to Step 2.

The HTP controller is programmed to sleep when not used and keep metrics on the sensor readings taken.

Cloud, daylight and infrared (CDI) sensing apparatus 21, figure 8.

The CDI sensing apparatus 21 observes and determines a quantitative value for cloud cover as a ratio from 0% to 100%. Apparatus 21 as shown in figure 8 includes a controller 67 (and firmware) powered by power input 68 communicating (with the node controller 26) via the RS485 Bus 69. The apparatus includes a camera module 70.

The apparatus may also include one or both of a daylight sensor 71 and infrared sensor 72. Daylight sensor 71 is used to determine what type of light is shining on the sensor — sunlight, moonlight or artificial light like for example a headlight. Infrared sensor 72 is used to determine the heating effect of the sun by comparing two surface temperatures - one coloured black, the other silvered.

As frost is related to temperature, any condition that may cause temperature increase or decrease will have an effect. CDI apparatus 21 is used to determine what is likely to happen to the night time temperature based on cloud cover. In addition, with additional sensors 71, 72, the CDI apparatus will also indicate the solar intensity and the Infrared light level (heat spectrum).

Cloud cover during the day traps heat close to the ground as the clouds act like an insulator and this increases ground and air temperature. During the night, if the cloud cover remains intact, the clouds reflect some of the energy being radiated by the ground and the drop in air temperature is reduced. Should however there be no night time cloud, this insulating effect is lost and heat is rapidly dissipated into the atmosphere. Zero cloud cover (especially during the night) combined with still air, low ground temperature (close to freezing) and an air temperature approaching the dew point temperature has the highest probability of frost occurrence. At least one parameter in the event predictor preferably draws on input data concerning the degree of cloud cover.

CDI sensor 21 uses camera module 70 to capture an image of the sky directly above the collection node 3 to calculate a value for cloud cover (cloud present as a percentage of sky captured). The scenario manager is programmed to use this data within the hygrometric equations to calculate a correction value to estimated minimum temperatures. Generally speaking, minimal cloud cover drastically lowers night time temperatures and as a consequence frost probabilities increase dramatically.

The camera module 70 has a sensor which can be one of two types - either analogue or digital. With analogue some form of average voltage level would need to be recorded and the support circuitry may be excessive. Preferably the image capture device is a digital camera. A camera module 70 is arranged to be directed upward so that the camera views the sky. The image data from the camera is received by controller 67. The controller 67 is programmed to test each pixel of the digital image for colour to determine if each pixel is cloud or sky. The controller accumulates at least one of a cloud or sky count, and calculates a ratio of cloud to sky for the image. The calculation may divide the cloud or sky pixel count by the total resolution of the image.

Preferably the controller is programmed to modify the ratio on a clear night when a full moon is present. For this purpose the controller may detect the full moon by brightness and/or shape, or may use a calendar or lunar calculation to determine times when the moon may be in the field of view.

Preferably the controller is programmed to weight pixels in one or more areas of the image more heavily than pixels in other areas of the image. For example the central zone of the sky is directly above the node. The controller may be programmed to weight pixels having addresses in a predefined middle region of the image more heavily than pixels in a peripheral region. The controller may then divide the weighted cloud or sky pixel count by the weighted resolution of the full image.

The camera unit may be position adjustable at the control of the controller 67 to take images of other areas solely for transmission. Daylight sensor 71 is a digital device that has very similar light sensing characteristics to that of the human eye. An example is the Agilent Technologies HDSL-9000. Standard light sensors tend to "see" in the wrong light spectrum - their responsiveness in the 550nm range is usually poor. This sensor sees the correct wavelength. It can be used to determine the first and last points of sunlight during the day.

Preferably the controller 67 is programmed to select whether the camera sensor is looking at the moon and night time sky, or at the daytime sky based on the output of sensor 71. The controller selects a filter for determining whether a pixel is cloud or sky based on the selection.

Infrared Sensor 72 is two plates of equal area — one black, one silvered — with temperature sensors underneath. The purpose is to get some idea of the heating (infrared) power of the sun. These readings when combined with the ground temperature readings should show some correlation. The temperature difference between the black and silvered sides of the detector will act somewhat like a radiometer.

As this module is looking at the sky, some regular maintenance is required to ensure the lens is not obscured.

The preferred minimum functionality of this sensor module is the cloud cover percentage - the infrared intensity can be determined from the ground sensor readings as a heating effect and the daylight intensity can determined from the solar panel, if a solar power source is provided in the power supply.

To the inventor's knowledge there has been no previous effort to optically determine cloud cover, or any method by which it can be calculated. Typically this value (for the hygrometric equations) has been determined by an experienced meteorologist. The addition of infrared sensor 72 and daylight sensor 71 adds the further benefit of validating day and night for making the cloud cover calculations.

Node controller

Figure 9 shows how the various components or modules or apparatus can be co-ordinated via node controller 26. In the preferred embodiment each of the sensor units receives power from the load connection of the power management unit 27. Also in the preferred embodiment each of the different controllers communicates with the node controller over a common data bus. Additional features such as node communication (a transceiver for communicating with the master station), a real time clock and memory for storing sensor data are also included. The device implementing event prediction based on data collected at a locality (by a node), uses multiple metrological parameters which better accounts for the variety of triggers typical for environmental events (such as the different frost formation mechanisms, or possibly hail triggers) and for the effect of local ( or very local) conditions. The device automates event prediction and may provide timing data for the event. This assists users to make sensible economic decisions about and choices for combating the event.

The events predictions system can also be used to predict other events such as fog, storms or ice build-up and also have other application such as for example in roads, mountain passes- avalanches/rock falls or pasture growth determination/prediction.

The power management apparatus can improve battery life by avoiding having batteries on float charging for extended time periods.

The cloud sensor has the advantage of providing a true indication of cloud cover rather than providing an output simply of light intensity.

The ground sensor with a sensor just below and just above ground level provides useful data about heat flow at the air/ground interface.

In the above description "node" refers to a remote data collection device placed in the field with sensors attached. The node transmits data to a master station periodically and monitors the status of the sensors.

By "controller programmed" we mean to include all types of device for receiving input data, executing complex sets of instructions or making sets of determinations, and providing control signals or data as outputs. For example typical controllers include; a processor, memory and associated I/O circuits (a computer); programmable logic hardware such as FPGAs; or fully determined electronic circuits. "Programmed" includes sets of instructions stored in memory, logic structures configured into programmable logic hardware permanently or temporarily, and logic structures designed directly into electronic circuits.

By "data" we mean information in any physical form. This includes data represented in analogue electrical signals, stored or transmitted in digital form, plain or encoded. This includes raw or processed sensor output, controller output, and data stored or manipulated in the controller. Appendix A: Frost Descriptions

There are two main types of Frost:

• Radiation Frost: Frost moves from the ground up. This frost is often characterised by clear skies, low humidity and minimal wind.

• Advection Frost: Frost moves down towards the ground. This type of frost is not very common and occurs when a cold air mass (Antarctic or Artie) moves over an area.

Advection frosts are not common and can be detected in advance by meteorological services and locally with high altitude and strategically placed temperature sensors. This would suggest therefore that we are primarily concerned with the conditions that favour a radiation frost as this is the type of frost that occurs quickly and apparently without warning.

When a radiation frost occurs it can appear in one of two forms:

• White Frost: This frost occurs when the Dew Point temperature is above OC. As the temperature approaches OoC, ice crystals form in the water causing the "White" appearance.

• Black Frost: This frost occurs when the Dew Point temperature is below OC. This frost occurs without any visible signs and is usually called Black Ice.

Appendix B: - Electronic / Electrical Abbreviations /

RF Radio Frequency

BNC A style of electrically shielded connector that uses a bayonet connection.

RS-232 A defined standard for point to point serial data transfer between two devices.

RS-485 A defined standard for point to multi-point (often called multi-drop) serial data transfer between a "master" and several "slave" devices. Each slave device has an address that allows the master to select which device to communicate with.

PSTN Plain Standard Telephone Network, also called POTS. Essentially a phone line connection.

POTS Plain Old Telephone Network

VPN Virtual Private Network. Allows the transmission of private data through the internet global communications system.

HTP Humidity Temperature Pressure Sensor unit

GND Ground Temperature Sensor unit

LRS Lapse Rate Sensor unit

BUS Data communication system where several devices are attached to a common "bus" so all devices can see the data. Each device either takes a turn at "talking" (windowed), waits for the line to be free (collision detection) or uses a master-slave address system (like RS-485) before data is transmitted to ensure the correct devices are talking together.

OTP (One Time Programmable)

This is the term given to memory that can be written to only once. When programmed this memory cannot be altered. It is often used to record data constants i.e. calibration data, serial numbers, etc. Similarly an OTP microcontroller can only be programmed once, so these devices are used when firmware has matured and programming faults have been corrected.

SMS Small message service specifically setup for sending small text messages over a cellular network. Appendix C: Numbers associated with components as in the drawings

1 events prediction system

2 sensors

3 collection nodes

4 master station

5 management system - server

10 master station controller

11 serial interface

12 node communications (aerial and transceiver)

13 status display

14 alarms

15 telephonic communication

16 cellular/SMS

17 virtual private network (VPN)

18 collection node assembly

19 pole or standard

20 xenon flash module

21 image capture device for cloud coverage sensor

22 transceiver/aerial

23 wind speed indicator

24 lapse rate sensor (LRS)

25 node controller and transceiver module 26a node communication means

26b real time measuring means

26c memory means

27 power management system

28 humidity, temperature, pressure sensor unit (HTP)

29 ground temperature sensor (GND)

30 power management controller

31 load connection

32 RS485 bus

33 solar panel

34 first battery connection

35 second battery connection

41 50cm under ground sensor

42 25cm under ground sensor

43 just under ground sensor

44 just above ground sensor

45 5cm Above Ground Sensor

46 ambient air on close proximity to the ground

47 ground level

48 downwardly facing shoulder

49 ground spike

50 controller (or microcontroller) 51 2m-Laρse Rate Sensor (attached to GND controller)

52 4m-Laρse Rate Sensor (attached to GND controller)

53 -6m-Laρse Rate Sensor (attached to GND controller)

54 power supply input

55 RS485 Bus communication to node controller

61 HTP sensor controller

62 power supply input

63 RS485 Bus communication to node controller

64 humidity sensor

65 temperature sensor

66 air pressure sensor

67 cloud cover sensor controller

68 power supply input

69 RS485 Bus communication to node controller

70 imaging device, upwardly facing digital camera

71 daylight sensor

72 infrared sensor

Claims

Claims:
1. A device including a power management system comprising
a circuit including a connection for a power source, a connection for a load, a connection for a first electrical storage battery, a connection for a second electrical storage battery and switches for selectively connecting each said storage battery connection to said power source connection, in a circuit wherein current may only flow to said battery connection, and to said load connection, in a circuit in which current may only flow from said battery connection, and
a controller programmed to select a battery to be on load and a battery to be on charge, and to provide output signals to said switches to connect the connections for said battery on load to said load connection and not to said power source connection, and to connect said battery on charge to said power source connections and not to said load connection.
2. A device as claimed in claim 1 wherein said controller is programmed to, if said battery on charge has immediately prior been a battery on load, connect said battery on load to said load connection before disconnecting said battery on charge from said load connection.
3. A device as claimed in either claim 1 or claim 2 wherein said circuit includes at least one switch to connect and disconnect the power source connection to the load connection, including in parallel with a said battery connection, and said controller is programmed to provide output signals to control said switches.
4. A device as claimed in any one of claims 1 to 3 wherein said controller is programmed to disconnect each said battery connection from said power source connection and said load connection and to determine the battery voltage of each said battery and to select the battery with the lowest terminal voltage to be the battery on charge, and the battery with the highest terminal voltage to be the battery on load.
5. A device as claimed in any one of claims 1 to 4 including a solar power source connected to said power source connector, said circuit includes a known load and switches to connect said solar power source to said known load, and said controller is programmed to determine the voltage level offered by said solar power source across said known load.
6. A device as claimed in any one of claims 1 to5 wherein said controller is connected to said load connection.
7. A device as claimed in any one of claims 1 to 6 including a support structure, and one or more environmental sensors supported on said support structure and connected to said load connection.
8. A device as claimed in claim 7 wherein said environmental sensors provide output data for an event prediction program to predict environmental events from said sensor output.
9. A device as claimed in claim 7 or claim 8 wherein said environmental sensors include said controller, said controller generating data indicative of the determined light level from said output voltage of a solar power source.
10. A device as claimed in any one of claims 7 to 9 wherein said sensors include two or more of the following:
• air humidity sensor
• air temperature sensor
• air pressure sensor
• lapse rate sensors
• ground temperature sensor
• wind speed detector
• a cloud coverage sensor
11. A device as claimed in claim 10 wherein said ground temperature sensor includes a first sensor for location immediately above ground, and a second sensor spaced close below said first sensor for location immediately below ground.
12. A device as claimed in claim 10 wherein said cloud coverage sensor comprises an image capture device arranged on said support structure to take images of at least a part of the sky when said support structure is locates upright in an open sky location, a controller connected to receive image data from said image capture device and process said image data to generate summary data representative of the cloud cover detected in said image.
13. A device as claimed any one of claims 10 to 12 wherein said device includes a transmitter and said controller is programmed to send output data from said sensors over said transmitter.
14. A predictor for environmental events comprising:
a controller programmed to receive data from at least three sensors at a single locality, said sensors being selected from the group of
• air humidity sensor
• air temperature sensor
• air pressure sensor
• lapse rate sensors
• ground temperature sensor
• wind speed detector
• cloud coverage sensor
and to determine for said locality, from said data, a prediction of the occurance of a predetermined environmental event by calculating a plurality of meteorological parameters from said data, comparing said calculated parameters against one or more stored scenarios for said location to determine the likelihood that an event will occur.
15. A predictor for environmental events as claimed in claim 14 wherein said controller provides an alarm signal or alarm trigger data if said prediction is for the occurance of the event.
16. A predictor for environmental events as claimed in either claim 14 or claim 15 wherein said controller calculates from said data and/or said parameters, a predicted time frame for said event, and provides output data indicating the predicted time of said occurance of said event.
17. A predictor for environmental events as claimed in any one of claims 14 to 16 wherein said controller stores said calculated parameter data, and data indicating the actual occurance (or not) of a said event.
18. A predictor for environmental events as claimed in 14 to 17 wherein said meteorological parameters include at least two of:
• dew point
• lapse rate • air temperature
• ground temperature
• air pressure
• an estimate of the time when a minimum temperature will occur
• a frost time estimate
19. A predictor for environmental events as claimed in claim 18 wherein said parameters include a predicted minimum nocturnal air temperature.
20. A predictor for environmental events as claimed in claim 19 wherein said controller calculates a said minimum nocturnal air temperature using data from a dew point sensor, said dew point data collected after the maximum daytime temperature is reached.
21. A predictor for environmental events as claimed in either claim 18 or claims 19 wherein said controller calculates a said minimum nocturnal air temperature using data from a said cloud cover sensor.
22. A predictor for environmental events as claimed in any one of claims 18 to 21 wherein said parameters include a minimum ground temperature.
23. A predictor for environmental events as claimed in claim 22 wherein said controller calculates a said minimum ground temperature by modifying a said minimum nocturnal air temperature using data from said ground temperature sensor.
24. A predictor for environmental events as claimed in claim 22. wherein said controller calculates a said minimum ground temperature using a derivation of the Brunt formula.
25. A predictor for environmental events as claimed in any one of claims 18 to 24 wherein said predetermined event comprises a frost, and predicts a time when the occurrence of said frost will commence.
26. A predictor for environmental events as claimed in claim 25wherein said controller calculates said time for said frost to occur by estimating backward from the typical coldest minimum temperature time assuming that that is the time when the minimum predicted air or ground temperature will occur.
27. A predictor for environmental events as claimed in any one of claims 14 to 26 wherein said controller determines a prediction for the occurance of an event for each node of a plurality of remotely located data collection nodes.
28. A predictor for environmental events as claimed in claim 27 wherein said controller is programmed to send or cause to be sent an alert to a client associated with a data collection node for which said program predicts the occurance of an event.
29. A predictor for environmental events as claimed in either claim 27 or claim 28 including a software program which performs the steps of:
generating a map of a client property including locations of a plurality of data collection nodes;
indicating on said map whether said node location is predicted to experience an event within a subsequent known time frame;
presenting said map to a user.
30. A data collection node for an environmental event prediction system includes a ground temperature sensor comprising:
a support structure,
a first temperature sensor, suitable for detecting the temperature of air, mounted on said support structure at a first location
a second temperature sensor, suitable for detecting the temperature of earth, mounted on said support structure at a second location spaced close below said first location.
31. A data collection node as claimed in claim 30 wherein said second sensor is spaced less than 10cm from said first sensor.
32. A data collection node as claimed in either claim 30 or claim 31 including a downwardly facing shoulder on said support structure at a level between said first sensor and said second sensor.
33. A data collection node as claimed in any one of claims 30 to 32 wherein said support structure comprises a spike for inserting into the ground.
34. A cloud cover sensor comprising: an image capture device arranged on a support structure to take images of at least a part of the sky when said support structure is located upright in an open sky location, a controller connected to receive image data from said image capture device and programmed to process said image data to generate summary data representative of the cloud cover detected in said image.
35. A cloud cover sensor as claimed in claim 34 wherein said image data represents the colour and/or brightness of each element in a two dimensional pattern of image elements and said controller is programmed to determine for each element between sky and cloud based on the brightness and/or colour of each element and aggregate a value from the elements determined to be sky or cloud.
36. A cloud cover sensor as claimed in claim 35 wherein said controller aggregates said value from weighted values for individual elements, wherein said weighting is determined by the location of said element in said two pattern.
37. A cloud cover sensor as claimed in claim 35 or claim 36 wherein said image capture device comprises a digital camera and each said element comprises a pixel in a captured digital image.
38. A cloud cover sensor as claimed in any one of claims 34 to 37 wherein said support structure includes a spike for inserting into ground, and said camera is oriented to point along the axis of said spike in a direction away from the ground insertion end of said spike.
39. A cloud cover sensor as claimed in any one of claims 34 to 38 wherein said controller is programmed to determine whether it is presently daytime or night time, and to chooses a filter for determining a pixel as sky or cloud according to said day/night determination.
40. A data collection node for an environmental event prediction system includes a cloud cover sensor as claimed in any one of claims 34 to 39.
PCT/IB2007/052391 2006-06-20 2007-06-20 Environmental monitor and power management system WO2007148299A3 (en)

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