AUTOMATED METER READING

A meter reader unit includes an image sensor that captures images of a face of a meter to produce image data. A computer vision processor recognizes meter data within the images. The meter data includes numerical values that indicate unit usages as measured by the meter. A wireless transceiver transmits the meter data to a remote entity. A power source provides power to the meter reader unit. A volume of the meter data transmitted to the remote entity is less than a volume of the image data so that power required to transmit the meter data is less than would be required to transmit the image data.

BACKGROUND

A smart meter is an electronic device that records consumption of electricity, water or gas in intervals of days, hours, minutes or less, and communicates that information to utilities or users for monitoring and possibly control. Utility usage is reported and charged accordingly to each household by respective utility providers. Smart electricity meters using power line communication (PLC) have been deployed in many regions. Other systems using dedicated cabling also exist. The benefit of wired system is reliability and power sufficient. The disadvantage is cost and difficulty to install. A wireless system, on the other hand, has the benefit of easy installation; however, achieving a wireless meter system that has a two to ten years of battery life of meter operation is often a challenge for meter and communication design.

Since the installed metering infrastructure is massive, the conversion of traditional metering system to smart metering system has proven to be very slow and costly.

DESCRIPTION OF THE EMBODIMENTS

An automatic meter reading (AMR) device is retrofit to traditional analog meters to modern smart meters. An AMR device is also sometimes referred to as an Advanced Metering Infrastructure (AMI). In this disclosure, AMR device and AMI are considered interchangeable terms. A meter used in an AMR device or an AMI system is often referred as a smart meter.

For example, a retrofit AMR device joins a utility provider's network, or is a customer device not joined to a utility provider's network. The AMR device allows traditional utility meters, such as electricity, water and gas meters, to be converted to smart meters that allow frequent utility usage monitoring. Image sensors and computer vision is used to extract the meter reading, as described further below. The meter reading is transmitted to a remote server continuously or in a batch. The wireless meter reading system includes one or a plurality of meters having an attached adaptor device to read and transmit the meter reading data wirelessly to customer site or to a remote server. The attached reading device includes an image sensor such as in a digital camera, a computer vision unit to convert images to meter reading data and a wireless transmit and receive unit.

For example, a wireless utility meter reading system is at least one meter, one adaptor device, a network or internet gateway and a host computer. The meter can be electricity, water or gas meter. The meter can be a modern smart meter where usage is displayed digitally or can be legacy analog meters where rotary dials represent the reading and revolving disk representing the instantaneous rate of usage. The adaptor device consists of an image sensor, a computer vision processor to convert the images to meter reading data, a wireless transceiver and a power source such as a battery. The internet gateway can be a router that connects to the Internet and connects to the meter reader wirelessly. The host computer can be a local computer, or a server in the cloud such as Amazon Web Services (AWS) or Google Cloud.

For example, an image sensor takes images of the meter at a user configurable speed, such as one image every second or one image every minute or 10 minutes. The reading accuracy of the accumulated utility usage is not dependent on the frame rate of the image sensor. The reading accuracy of the instantaneous usage is dependent on the frame rate of the image sensor. The tradeoff for high frame rate is battery life of the adaptor device.

A more frequent gathering of meter reading data not only can alert users and utility companies of abnormal usage pattern, but also can help users to see where and how utilities are used so users can modify usage, upgrade appliance, detect leaks. This ultimately results in energy and water conservation, household safety and environmental sustainability.

A first objective is to provide a utility meter reading system which allows homeowners to monitor the rate of real time usage as well as accumulated usage of electricity, water and gas.

A second objective is to provide a utility meter reading system where an adaptor can be attached to any existing utility meter, and where the installation of such an adaptor does not require electricity, water or gas professionals.

A third objective is to provide a utility meter reading system that can work with modern smart meters or legacy analog meters.

A fourth objective is to provide a utility meter reading system where an adaptor can read the meter on its own and transmit the meter reading data instead of image data, hence low power low data rate wireless radio, such as LoRa, NBIoT radios, can be used to extend battery life of the adaptor.

A fifth objective is to provide a utility meter reading system where the installation does not require interruption to the utility service.

A sixth objective is to provide a utility meter reading system where detailed usage data can be analyzed and reported such as individual appliance usage, abnormal usage pattern, leak detection etc.

A seventh objective is to provide a utility meter reading system where utility usage data, analysis and conservation suggestions can be shown on a smart phone or displayed on a household appliance.

An eighth objective is to provide a utility meter reading system that does not interfere or obstruct meter reading of utility companies.

The present disclosure describes an apparatus and methods that can convert all traditional meters into smart meters at reasonable cost and can be installed by home owners without the need of licensed professionals.

The benefit of having computer vision processing within the adaptor unit is to dramatically reduce the amount of data that need to be transmitted to the server. For example, each typical reading of meter equipped with computer vision processing contains approximately a few hundred bytes of data where an image of the meter is typically a few hundred thousand bytes. Low data rate for the wireless link allows long range and low power radios, such as LoRa or NB-IoT, to be used to transmit the meter reading data to remote servers. This obviates the need to transmit large image data to servers.

An exemplary embodiment of a wireless meter reading system is shown inFIG. 1. The system includes one or more meters, as represented by a meter11. For example, meter11is shown as a water meter but can be another type of utility meter such as an electricity meter or a gas meter. Meter11can also be another type of meter such as a pressure meter, a humidity meter, a temperature meter or another type of meter. For example, meter11can be a digital or an analog electricity meter, a digital or an analog water meter, a digital or an analog gas meter, digital or an analog pressure meter, a digital or an analog thermometer, a digital or analog humidity meter.

For example, meter11can be a passive meter without any electric power needed. Alternatively, meter11can be a meter with electricity supplied by battery, by environmentally scavenged power source or by electricity wire connection. The meters display relevant data with multiple clock hands with dials, or with digital readouts like odometers, or with LCD display. Some meters also have rotating indicators for small amount of flow which is usually for detecting water or gas leaks. Some modern meters have digital LCD display where the display can be turned off most of the time to save battery consumption. The display can be turned on either by pushing a button or by interrogating the meter electronically.

A meter reader unit12captures images of the face of meter11using an image sensor, for example, as used within digital cameras. Meter reading unit12interprets the captured images to produce meter reading numbers. For example, optical character recognition is used when meter11unit displays information digitally. When meter11uses dials or other means to display information, meter reading unit12interprets current dial position to detect current meter reading values. To perform this interpretation, meter reading unit12includes processing power implemented by hardware and software sufficient to perform the processing. Meter reading unit12produces interpreted meter data10that is transmitted wirelessly to a wireless access point by a wireless transceiver within meter reading unit12. Meter data10can be transmitted as it is generated, or meter data10can be collected within meter reading unit12and transmitted in a batch at a less frequent rate.

A holding arm13is used to position meter reading unit12so that the image sensor will be able to capture images of the face of meter11. A mounting bracket14can be used to attach the holding arm13to a nearby fixture. For example, inFIG. 1, mounting bracket14is implemented as a clip that attaches holding arm13to a pipe21.

A power source15is separate from, or incorporated within, meter reading unit12. For example, power source15is a battery, an electric outlet, or an environmentally scavenged power source such as a solar panel, a radio wave, a wind turbine or so on.

A wireless transceiver within meter reading unit12communicates with another wireless transceiver illustrated inFIG. 1by a wireless access point16. Wireless access point16can be implemented by a wireless hub or other configuration. Depending on the wireless technology used within meter reading unit12, wireless access point16can be established using Wi-Fi, ZigBee, Z-Wave, LoRa, or NB-IoT or another wireless protocol. Wireless access point16can connect to the Internet20directly as shown inFIG. 1or can connect to the Internet20via a router and so on.

A server17processes and stores data from meter reading unit12. For example, server17performs data analytics using the current and historic data to detect abnormal usage patterns and come up with utility saving recommendations. For example, real time and historic usage data can also be displayed in home on appliances such as smart refrigerators, or other home display devices such as Echo Show, or Google Display. This is represented inFIG. 1by home appliance and display18. Alternatively, or in addition, data stored on or produced by server17can be accessed by a user computing device, as illustrated inFIG. 1by a smart phone app19which can be run on a smartphone, or another application that runs on another type of computing device such as a tablet or laptop computer.

FIG. 2shows additional detail of holding arm13, power source15, meter reading unit12and mounting bracket14. For example, holding14is adjustable to allow adaption to various meter configurations.

FIG. 3shows an implementation where a holding arm23is used to position a meter reading unit25so that an image sensor within meter reading unit25is able to capture images of the face of water meter11. A mounting device24attaches holding arm23to meter reading unit25. A mounting bracket22is used to attach holding arm23to pipe21. A power source, such as power source15, can be used to power meter reading unit25.

FIG. 4shows an implementation where a holding arm33is used to position a meter reading unit35so that an image sensor within meter reading unit35is able to capture images of the face of an electricity meter31. A mounting device34attaches holding arm33to meter reading unit35. A mounting bracket32is used to attach holding arm33to electricity meter31.

FIG. 5shows an implementation where a holding arm43is used to position a meter reading unit45so that an image sensor within meter reading unit45is able to capture images of the face of a gas meter41. A mounting device44attaches holding arm43to meter reading unit45. A mounting bracket42is used to attach holding arm43to gas meter41.

FIG. 6is a simplified block diagram of meter reading unit12. An image sensor601and an illuminating light emitting diode (LED)602are used to capture images of a meter. Optics are additionally used as helpful with image sensing. Image sensor601captures an image of the meter and the resulting image data is sent to a computer vision processor603. For example, the image data may or may not be compressed into a format such as JPEG. The image data is processed by computer vision processor603to extract meter data from the image data. For example, the meter data consists of numerical values that numerically represent a current meter reading. For example, the meter data can include a meter identification, a meter model number in addition to current displayed values. The meter value data may represent units such as gallons or cubit feet for a water meter, kilowatts for an electricity meter, therms for a gas meter and so on.

An optional external memory unit606may be used if called for by a particular processor implementation. Meter data is transferred to a wireless transceiver604, which sends the meter data to a nearby access point via radio wave with the aid of an antenna609.

For example, computer vision processor603is implemented by an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a graphics processing unit (GPU) or another type of generic or specialized processor that has the required computing power and memory. For example, a computer vision algorithm running on computer vision processor603uses a neural network model for extracting meter data. For example, the algorithm allows recognition to be trained and developed using public available meter image data, meter manufacturer data, commercial collected meter images and user contributed images. For example, the computer vision algorithm and model are updated via wireless computing with meter reading unit12. Optical character recognition software or other types of recognition software may be utilized or adapted to extract meter data, as is well understood by persons of ordinary skill in the art.

Additional features may also be incorporated within meter reading unit12. For example,FIG. 6shows a temperature sensor607and a humidity sensor608. Other environmental sensors may also be included in meter reading unit12. For example, temperature and humidity data are collected by computer vision processor603and sent to the access point along with meter data. For example, all transmitted data can be encrypted or otherwise encoded.

To increase battery life, power management605is included. For example, meter reading unit12is programmed to take readings at a predetermined time interval, or on demand as a result of an instruction send via the wireless access point to meter reader unit12. For example, to achieve maximum battery life, meter reader unit12is configured to turn on once an hour, or once a day or once over a longer period of time.

For example, a portion or all of meter reading unit12can be implemented using individual integrated circuits or utilizing a system-on-a-chip (SoC) integration. For example, a single SoC is used to implement computer vision processor603, memory606wireless transceiver604, power management605, temperature sensor607, humidity sensor608, image sensor601and LED602.

For example, in various implementations a radio within meter reading unit12can be used to establish communication with the meter when the meter is a smart meter. Wireless signaling to a smart meter can also be used by the meter reading unit12to instruct the smart meter to turn on a display of the smart meter before meter reading unit12captures an image of the face of the meter.

FIG. 7illustrates signal flow within a meter reader unit72in accordance with an implementation. A current state of a meter display71is captured to produce image capture data73. A computer vision processor74produces meter data75for transfer to a wireless access point such as a wireless router76. Meter data can include, but is not limited to: meter ID, utility company name, meter model in addition to values such as kilowatts, cubit feet, therms, depending upon the type of meter being viewed.

FIG. 8shows examples of meter image and readout values utilizing computer vision. For example, image data81is captured from a meter80. A computer vision processor translates image data81into a numerical value for kilowatt usage. The resulting meter data82includes the numerical value 12408 representing an electricity usage in kilowatts and a meter ID number 14588926.

For example, image data86is captured from a meter85. A computer vision processor translates image data86into a numerical value for gallon usage. The resulting meter data87includes the numerical value 0235982 representing a water usage in gallons.

The foregoing discussion discloses and describes merely exemplary methods and implementations. As will be understood by those familiar with the art, the disclosed subject matter may be embodied in other specific forms without departing from the spirit or characteristics thereof. Accordingly, the present disclosure is intended to be illustrative, but not limiting, of the scope, which is set forth in the following claims.