PH12015000340A1 - A system for and method of providing energy consumption related information based on monitored energy data - Google Patents

Abstract

One aspect of the present invention is directed to a computer-implemented system for providing energy consumption related information based on monitored energy data. The system comprises hardware and software units divided into energy monitoring and energy analysis groups. Energy data generated by the hardware and software units of the energy monitoring group are transmitted to the hardware and software units of the energy analysis group. The transmitted energy data are analyzed using computing function which outputs information for use in providing energy consumption related information. The energy consumption information include sets of energy consumption and recommendation data.

Description

A SYSTEM FOR AND METHOD OF PROVIDING ENERGY

CONSUMPTION RELATED INFORMATION BASED ON

MONITORED ENERGY DATA

Technical Field

The present invention relates generally to energy monitoring systems and, more particularly, to a such an energy monitoring system configured to provide energy consumption related information on a user communication device upon request of the user through a communication network.

Background of the Invention

The rising cost of energy is one of the most pressing issues that a significant number of energy consumers face today. In managing this rising cost of energy, it is desirable for energy consumers to have access to energy consumption data, in near real-time, by specific appliances inside the premises of their homes, offices, or plants. It is likewise desirable for energy consumers to be offered of recommendation on how to best manage the use of their appliances for the purpose of reducing the costs of their energy consumptions.

United States Patent Publication No. 20120316808 published on 13

December 2012 to Energyhub (New York, USA) discloses a system and method for monitoring and controlling the power consumption of a power- consuming device, wherein the system and method may connect to a power source and a power-consuming device, connecting the power- consuming device to the power source, and wherein the power usage of : the power-consuming device is then measured and monitored by a microprocessor. These data monitored by the microprocessor is then stored :

and optionally sent to a controlling device on a data network. The location of the power-consuming device is also determined, recorded, and sent to the controlling device. The system also determines optimal modifications to any existing schedules or settings applied to appliances. This implementation occurs as either a direct or automatic adjustments to the schedules, or by recommending changes to the user.

U.S. Patent Publication No. 20120316808 further discloses generation of recommendations on an efficient power-consuming device or power-producing device in the form of modifications presented to a user to improve the user's energy network. Additionally, alternative sources of energy, which may include generators, photovoltaic or other solar power systems, wind power systems, hydroelectric power systems, and geothermal power systems, are also monitored by the cited prior art system for monitoring and controlling the power consumption of a power- consuming device.

The prior art identified above further discloses that for photovoltaic systems, information on the required additional power from the grid to meet the load requirements of the power-consuming device during times that batteries receiving charge from the photovoltaic cells are depleted can be viewed by the user through a display unit. A problem associated with the cited prior art system is that it does not provide an analysis that enables a user to efficiently utilize electrical power supply from electrical grid and from alternative sources in relation to one another.

Summary of the Invention

One aspect of the invention is directed to a computer-implemented system for providing energy consumption related information based on

3 ’ monitored energy data. The system comprises hardware and software units bi divided into energy monitoring and energy analysis groups. \ Energy data from the hardware and software units of the energy monitoring group are transmitted to the hardware and software units of the : = 5 energy analysis group. The transmitted energy data are analyzed using + computing functions which output information for use in providing energy ~~ ¢ $ consumption related information. The energy consumption related information include sets of energy consumption and recommendation data. x The energy monitoring group includes hardware and software units NC od generally characterized by a signal detection unit and a signal processing © § ~-unit with a communication module. The signal detection unit is coupled to a _ oo circuitry associated with an energy consuming device, and is adapted to * rapsduce. an electrical signal associated with the circuitry. ma o t rived ave. x The signal processing unit is_disposed in an operative position 18 lative to the signal detection unt for receiving the electrical signa from ! the signal detection unit and for processing the electrical signal such that

Yog ve ky Ss provided and prepared for transmission through a

Sos . communication network.

The energy analysis. group includes hardware and software units generally characterized by (3 Vata processing unit in communication with : the signal processing unit through the communication network. ;

The data processing unit is arranged for receiving the energy data 7 when the energy signal is transmitted by the signal processing unit and for ¥ » executing computer-executable instructions which, when executed by the Load data processing unit from a memory component of the data processing / oy ers . ;

Loy, me Lo - :

Loe hi I. alae @ Prva

J Ty gl unit, causes energy consumption related information to be generated based on the energy data.

The execution of the computer-executable instructions by the data processing unit further causes the energy consumption related information to be accessed on a display screen of a user communication device connected to the communication network based upon a request received by the data processing unit from the user communication device through the communication network.

Preferably, the energy consumption related information include the set of energy consumption data, a_first set of recommendation data, a second set of recommendation data, a third set of recommendation data, and a fourth set of recommendation data. ‘ ]

The first set of recommendation data according to the system of the invention is representative of a‘ behavior of the energy consuming device in relation to another energy consuming device of the same category. The second set of recommendation data according to the system of the invention is representative of a'power consumption efficiency of the energy consuming device.

The third set of recommendation data according to the system of the invention is representative of autonomous power supply for the energy consuming device depending on the behavior of the energy consuming device receiving electrical power from an electrical grid.

The fourth set of recommendation data according to the system of the invention is representative of alternative on-grid electricity supply procurement options for the energy consuming device depending on the :

behavior of the energy consuming device receiving electrical power from the electrical grid.

The provision of the data processing unit providing the set of energy consumption data, the first set of recommendation data, the second set of recommendation data, the third set of recommendation data and the fourth set of recommendation data ensures that the user is enabled to efficiently utilize electrical power both from electrical grid and from alternative sources.

The fourth set of recommendation data, which is representative of the alternative on-grid electricity supply procurement options for the energy consuming device depending on the behavior of the energy consuming device receiving electrical power from the electrical grid, may be derived from an alternative electricity supply procurement options program for utilizing the electrical power from the electrical grid, the power supply, 1s or a combination of both the electrical power from the electrical grid and the power supply. This arrangement provides flexible yet efficient power supply options for the users.

In another aspect of the invention, a computer-implemented method of providing energy consumption related information based on monitored energy data is provided.

The method preferably comprises the steps of: (i) transducing, by a signal detection unit, an electrical signal associated with a circuitry of an energy consuming device; (ii) processing, by a signal processing unit, the electrical signal such that an energy data is provided and prepared for transmission through a communication network; and (iii) transmitting, by a communication module in communication with the signal processing unit,

the energy data to a data processing unit in communication with the signal processing unit through the communication network.

The method may further comprise executing, by the data processing unit, computer-executable instructions from a memory component of the 5s data processing unit to cause energy consumption related information to be generated based on the energy data and to further cause the energy consumption related information to be accessed on a display screen of a user communication device connected to the communication network based upon a request received by the data processing unit from the user communication device through the communication network.

The energy consumption related information according to the method of the invention may include a set of energy consumption data, a first set of recommendation data, a second set of recommendation data, a third set of recommendation data, and a fourth set of recommendation data.

The first set of recommendation data according to the method of the invention is representative of a behavior of the energy consuming device in relation to another energy consuming device of the same category. The second set of recommendation data is representative of a power consumption efficiency of the energy consuming device.

The third set of recommendation data according to the method of the invention is representative of autonomous power supply for the energy consuming device depending on the behavior of the energy consuming device receiving electrical power from an electrical grid.

The fourth set of recommendation data according to the method of the invention is representative of alternative on-grid electricity supply procurement options for the energy consuming device depending on the ; behavior of the energy consuming device receiving electrical power from the electrical grid.

For a better understanding of the invention and to show how the same may be performed, preferred embodiments thereof will now be described, by way of non-limiting examples only, with reference to the accompanying drawings.

Brief Description of the Drawings

Figure 1 is a block diagram illustrating a system for providing energy consumption related information based on monitored energy data according to one or more embodiments of the invention.

Figure 2 is a flow diagram illustrating a method of providing energy consumption related information based on monitored energy data according to one or more embodiments of the invention.

Figure 3 is flow diagram illustrating a preferred general workflow for transmission of an electrical signal suitable for use in the system of Figure 1 according to one or more embodiments of the invention. :

Figure 4 is a flow diagram illustrating a preferred operation of signal processing unit relative to signal detection unit in Figure 1 according to one or more embodiments of the invention.

Figure 5 is a block diagram illustrating a preferred architecture of signal processing unit according to one or more embodiments of the invention.

Figure 6 is an interaction diagram of a preferred data processing model according to one or more embodiments of the invention.

Figure 7 is a flow diagram illustrating a preferred flow of data from one computing resource to another according to one or more embodiments s of the invention.

Figure 8 is a block diagram illustrating a preferred recommendation data model according to one or more embodiments of the invention.

Figure 9 is a logic flow diagram illustrating a preferred process for validating a user account suitable for use in the system of Figure 1 according to one or more embodiments of the invention.

Figure 10 is a logic flow diagram illustrating a preferred process for ranking data according to one or more embodiments of the invention.

Figure 11 is a logic flow diagram illustrating a preferred process for plotting historical data according to one or more embodiments of the invention.

Figure 12 is a logic flow diagram illustrating a preferred process for executing an action based on a monitored data according to one or more embodiments of the invention.

Figure 13 is a logic flow diagram illustrating a preferred general process for performing a first energy related analysis according to one or more embodiments of the invention. :

Figure 14 is a logic flow diagram illustrating a preferred specific process for performing one component of the energy related analysis in

Figure 13 according to one or more embodiments of the invention.

Figure 15 is a logic flow diagram illustrating a preferred specific process for performing another component of the energy related analysis in

Figure 13 according to one or more embodiments of the invention.

Figure 16 is a logic flow diagram illustrating a preferred specific process for performing yet another component of the energy related analysis in Figure 13 according to one or more embodiments of the invention.

Figure 17 is a logic flow diagram illustrating a preferred general process for performing a second energy related analysis according to one or more embodiments of the invention.

Figure 18 is a table illustrating a preferred function representative of a third energy related analysis according to one or more embodiments of the invention.

Figure 19 is a graphical representation of the table illustrated in

Figure 18.

Figure 20 is a block diagram illustrating a preferred hardware architecture suitable for use in the system of Figure 1 according to one or more embodiments of the invention.

Detailed Description of Preferred Embodiments

Referring to Figure 1, there is shown a block diagram illustrating a system for providing energy consumption related information based on monitored energy data according to one or more embodiments of the present invention. The system is a computer-implemented system ; according to one aspect of the present invention and is consistently designated by reference numeral 100 throughout the ensuing description.

The system 100 may be composed of a distributed network of hardware and software units interacting with one another and generally divided into an energy monitoring group 102 and an energy analysis group 104. The hardware and software units belonging to the energy monitoring group 102 may communicate with the hardware and software units belonging to the energy analysis group 104 through a communication network 106.

In one or more embodiments of the present invention, the hardware and software units included in the energy monitoring group 102 may be made operable in an environment characterized by end consumers or end users of energy-related services. Typically, these end users include households, commercial establishments such as restaurants, grocery stores, manufacturing plants, and schools, to name a few.

On the other hand, the hardware and software units included in the energy analysis group 104 may be made operable in a network-based dynamic computing environment such as a World Wide Web environment and a cloud environment which may be embodied by either a Software as a

Service (SaaS) environment, a Platform as a Service (PaaS) environment, or an Infrastructure as a Service (IaaS), among others.

In the World Wide Web environment, in one instance, the hardware and software units included in the energy analysis group 104 may be accessed by the end users from one or more network-based servers. In the

SaaS environment, in another instance, the hardware and software units included in the energy analysis group 104 may be centrally hosted, and the use or delivery of which may be licensed to the end users on a ] subscription basis.

In the PaaS environment, the end users of the hardware and software units included in the energy analysis group 104 may be given a platform to customize their own applications as based on their individual requirements. In the IaaS environment, a third party service provider may host the computing resources associated with the hardware and software units included in the energy analysis group 104.

Every data generated by the computing resources characterizing the energy monitoring group 102 and required for energy analysis may be transmitted from the energy monitoring group 102 to the energy analysis group 104 through the communication network 106.

The communication network 106 may utilize wired or wireless connections. Wi-Fi and Ethernet connections may constitute the communication network 106. Alternatively, the communication network 106 may include Bluetooth connections. Further, the communication network 106 may be the Internet connecting one or more servers and a short message service center (SMSC).

It is to be understood and appreciated by persons skilled in the art that the communication network 106 may alternatively be characterized by any wired and wireless network which include, by way of example, the

Internet, local area network (LAN), wide area network (WAN), and metropolitan area network (MAN). Such data transmitted from the energy monitoring group 102 to the energy analysis group 104 may accessed by an end user through the use of a user communication device 108 connected to the communication network 106. ;

The data can be viewed by the user of the user communication device 108 through a user interface 110. The user communication device 108 may be a first user communication device on which a web-based application can be accessed, a second user communication device on which a mobile-based application can be accessed, or a third user communication device on which a cloud-based application can be accessed. Further, the communication device 108 may be selected from any of a desktop computer, a laptop computer, a notebook computer, a tablet, and a smartphone, among others.

The hardware and software units included in the energy monitoring group 102 mainly include a signal detection unit 112, a signal processing unit 114, and a communication module 116. The signal detection unit 112 is coupled to a circuitry 118a, 118b, or 118c associated with an energy consuming device 120a, 120b or 120c. The circuitry 118a, 118b, or 118c is electrically coupled to a power line of a power source which provides the power required to operate the energy consuming device 120a, 120b or 120c characterized, for example, by a household appliance. The power line passes through an electrical panel 122 of the type employing a fuse or a circuit breaker.

Preferably, the signal detection unit 112 includes both current sensors and voltage sensors which commonly include a built-in circuit board having a conductor portion on which the AC to be measured may flow.

It is to be understood and appreciated by persons skilled in the art that the signal detection unit 112 may be any suitable sensitive current and voltage measuring instrument of the type which generally utilizes a current and voltage measuring circuit and a transducer for use in coupling the current and voltage measuring circuit to a surface of a conductor carrying the current and voltage to be measured. The signal detection unit 112 is arranged to transduce an electrical signal associated with the circuitry 118a, 118b, or 118c.

The signal processing unit 114 is disposed in an operative position relative to the signal detection unit 112 for receiving the electrical signal from the signal detection unit 112. The operative position in which the signal processing unit 114 is disposed may be characterized by, for example, a wall-mounted position and a location that is in close proximity to a physical spot on which the electrical panel 122 is mounted.

It is preferable, however, that the signal processing unit 114 is installed in a location that is generally dry. Moisture intrusion into the electrical panel 122 and the signal processing unit 114 may cause corrosion and, in turn, damage to electrical equipment electrically connected to the electrical panel 122 or the signal processing unit 114.

The signal processing unit 114 processes the electrical signal from the signal detection unit 112 in a manner that an energy data is provided and prepared for transmission through the communication network 106.

The energy data preferably refers to electrical energy data.

The signal processing unit 114 may be a microcontroller, a microprocessor, a Field Programmable Field Array (FPGA), a programmable logic controller (PLC), a microcomputer, or a digital signal processor (DSP).

It is to be understood and appreciated by any persons skilled in the art that the signal processing unit 114 may be any suitable processor of the type that is provided with embedded controllers in the form of either generic or programmable logic devices and arrays and application specific integrated circuits. The preferable structure of the signal processing unit 114 will be disclosed in Figure 5 of the disclosure of the preferred embodiments of the present invention.

The signal processing unit 114 preferably includes a signal conditioning component (not illustrated) in the form of a circuit board to which the electrical signal is delivered from the signal detection unit 112.

The electrical signal may be an electrical current signal or an electrical voltage signal.

The signal conditioning component may be a microcontroller-based component. The signal conditioning component converts the electrical signal it receives from the signal detection unit 112 from a current or voltage signal into a signal form as required by the signal processing unit 114. In other words, the signal conditioning component converts any of the electrical current and the electrical voltage signal into a signal that is compliant to the input of the signal processing unit 114.

The signal processing unit 114 processes the input signal and : converts it to a computer-readable digital electrical value. The signal processing unit 114 captures and processes the input signal into relevant power consumption parameters, such as peak current, rms current, peak voitage, rms voltage, instantaneous real, reactive and total power values, and energy consumption in each cycle included in a predetermined number of cycles, wherein the relevant power consumption parameters are determined by the signal processing unit 114 based on the relevant power consumption parameters within any given time period or the time period defined by the predetermined numbers of cycles.

As mentioned above, the communication network 106 enables the communication between the hardware and software units of the energy monitoring group 102 and those of the energy analysis group 104. The energy analysis group 104 may be composed of a data processing unit 124 having a memory component 126. Stored on the memory component 126 are computer-executable instructions 128 which can be fetched by :

the data processing unit 124 in order to execute preconfigured computing functions.

The energy data generated by the signal processing unit 114 may ; be transmitted by the communication module 116 through a communication gateway "G." The communication gateway "G" enables the communication module 116 of the signal processing unit 114 to connect directly to a Global System for Mobile Communication (GSM) service provider's SMSC through the communication network 106 which may be defined by the Internet or Transmission Control Protocol/Internet Protocol (TCP/IP).

The energy data transmitted to the data processing unit 124 from the signal processing unit 114 through the communication module 116 connected to the communication network 106 are stored in a database system 130 hosted by the data processing unit 124. The database system 130 may include a relational database.

The data processing unit 124 is preferably a conventional processor but may alternatively be any equivalent device capable of dividing a predetermined number of tasks or computing functions to be performed based on the computer-executable instructions 128, and executing these computer-executable instructions 128 in order to perform the desired tasks or computing functions. The preferable structure of the data processing unit 124 will be disclosed in Figure 19 of the disclosure of the preferred embodiments of the present invention.

The data processing unit 124 which is in communication with the signal processing unit 114 through the communication network 106 receives the energy data when the energy data is transmitted by the signal processing unit 114 through the communication module 116 within a predetermined time interval. The data processing unit 124 further executes the computer-executable instructions 128 from the memory component 126 of the data processing unit 124 to cause energy consumption related information to be generated based on the energy data.

The execution of the computer-executable instructions 128 by the data processing unit 124 from the memory component 126 further causes the energy consumption related information to be accessed on a display screen or user interface 110 of the user communication device 108 connected to the communication network 106. The display of the energy consumption related information on the display screen or user interface 110 of the user communication device 108 is based upon a request received by the data processing unit 124 from the user communication device 108 through the communication network 106.

The execution of the computer-executable instructions 128 by the data processing unit 124 from the memory component 126 further causes generation of various data associated with the energy consumption related information.

In accordance with one or more embodiments of the system 100 of the present invention, the energy consumption related information may include a set of energy consumption data, a first set of recommendation data, second set of recommendation data, a third set of recommendation data, and a fourth set of recommendation data. :

The data associated with the energy consumption related information may be stored in the database system 130 and may be retrieved from the same database system 130 based upon a request originating from a user of the user communication device 108. :

The set of energy consumption data may include actual power consumption data and energy data, and may be generated based on any one or any suitable combination of the following frequencies: hourly, daily, weekly, monthly, and annually. The set of energy consumption data may be graphically presented on the display screen or user interface 110 of the user communication device 108. ;

The first set of recommendation data is preferably representative of a behavior of the energy consuming device 120a, 120b or 120c in relation to another energy consuming device (not illustrated) of the same category. In this regard, the energy consumption data of the energy consuming device or home appliance 120a, 120b or 120c¢, which could be a refrigerator for example, is obtained and monitored by the hardware and software units of the energy monitoring group 102.

The first set of recommendation data may include a benchmark of consumption against similar establishments associated with use of the energy consuming device 120a, 120b or 120c within any given time period.

The monitored energy consumption data of the energy consuming device 120a, 120b or 120c are then transmitted to the data processing unit 124. The data processing unit 124 determines the category under which the energy consumption data of the energy consuming device 120a, ] 120b or 120c fall. Further, the first set of recommendation data includes duration of use of the energy consuming device 120a, 120b or 120c within any given time period.

The second set of recommendation data is preferably representative of a power consumption efficiency of the energy consuming device 120a, 120b or 120c. Further, the second set of recommendation data includes an indication of a replacement of the energy consuming device 120a, 120b or 120c in relation to the power consumption efficiency of the energy consuming device 120a, 120b or 120c.

The second set of recommendation data may further include the quantity of energy consuming devices 120a, 120b and 120c which are in operation with any given time period and as well as return on investment data associated with the replacement of the energy consuming device 120a, 120b or 120c with an alternative device as recommended within any given time period.

The third set of recommendation data is preferably representative of autonomous power supply for the energy consuming device 120a, 120b or 120c depending on the behavior of the energy consuming device 120a, 120b or 120c receiving electrical power from an electrical grid.

The fourth set of recommendation data is preferably representative 1s of alternative on-grid electricity supply procurement options for the energy consuming device 120a, 120b or 120c¢ depending on the behavior of the energy consuming device 120a, 120b or 120c receiving electrical power from the electrical grid.

The provision of the data processing unit 124 providing the set of energy consumption data, the first set of recommendation data, the second set of recommendation data, the third set of recommendation data and the fourth set of recommendation data ensures that the user is enabled to : efficiently utilize electrical power both from electrical grid and from alternative sources.

The fourth set of recommendation data, which is representative of the alternative on-grid electricity supply procurement options for the energy consuming device 120a, 120b or 120c depending on the behavior ] of the energy consuming device 120a, 120b or 120c receiving electrical power from the electrical grid, may be derived from an alternative electricity supply procurement options program for utilizing the electrical 5s power from the electrical grid, the power supply, or a combination of both the electrical power from the electrical grid and the power supply. This arrangement provides flexible yet efficient power supply options for the users.

Referring to Figure 2, there is shown a method 200 of providing energy consumption related information based on monitored energy data according to one or more embodiments of the present invention. As shown in step 202, the method 200 starts by transducing, by a signal detection unit, an electrical signal associated with a circuitry of an energy consuming device. The method 200 continues in step 204 by processing, by a signal processing unit, the electrical signal such that an energy data is provided for transmission through a communication network.

The processing of the electrical signal by the signal processing unit is succeeded by the step of transmitting, by a communication module in communication with the signal processing unit, the energy data to a data processing unit in communication with the signal processing unit through the communication network, as shown in step 206.

The method 200 concludes in step 208 by executing, by the data processing unit, computer-executable instructions from a memory component of the data processing unit to cause energy consumption related information to be generated based on the energy data and to further cause the energy consumption related information to be accessed : on a display screen of a user communication device connected to the communication network based upon a request received by the data processing unit from the user communication device through the communication network.

The energy consumption related information generated in step 208 may include a set of energy consumption data, a first set of recommendation data, a second set of recommendation data, a third set of recommendation data, and a fourth set of recommendation data.

The first set of recommendation data is representative of a behavior of the energy consuming device in relation to another energy consuming device of the same category.

The second set of recommendation data is representative of an energy consumption efficiency of the energy consuming device.

The third set of recommendation data is representative of an autonomous power supply for the energy consuming device.

The step of processing the electrical signal, which may be an electrical current signal or an electrical voltage signal, includes converting the electrical signal into a signal compliant with the input of the signal processing unit.

The step of processing the electrical signal includes converting the signal compliant with the input of the signal processing unit to a computer- readable digital electrical value corresponding to the electrical parameter required.

The step of processing the electrical signal includes capturing and processing relevant electrical consumption parameter values with any given time period or the time period or the time period defined by a predetermined number of cycles. :

Referring to Figure 3, there is shown a preferred general workflow for transmission of an electrical signal suitable for use in the system of

Figure 1 according to one or more embodiments of the present invention. :

The workflow starts at block 300 wherein the input current is present on the wires that can be found in an electrical panel.

At block 302, the input current and voltage is sensed or detected by the signal detection unit illustrated in Figure 1. In one embodiment of the present invention, the signal detection unit may be commercially available ; current sensing transformers and voltage sensing transformers both with precision 0.05 class.

At block 304, the signal processing component preferably in the form of a microcontroller converts the input signal into a computer- readable digital electrical value (i.e, analog to digital conversion or quantization).

At block 306, the computer-readable digital electrical value is converted into a computer-readable digital electrical value which corresponds to the electrical signal detected by the current or voltage sensing transformer.

At block 308 is the logic to calculate electrical parameters and at block 310 is the logic to calculate the per minute electrical parameters.

Electrical data associated with these parameters are then sent to a server- hosted database system using the communication module as shown in block 312. These are the electrical parameters determined by the signal processing unit based on one or more of the digital electrical value within any given time period. The workflow from the block 300 to block 312 may be arranged to form a loop, as marked by continuation point "A."

Referring to Figure 4, there is shown a flowchart illustrating a preferred operation of the signal processing unit relative to the signal ] detection unit in Figure 1 according to one or more embodiments of the present invention. The flow starts in block 400 wherein computing functions of the signal detection unit are initialized as soon as the signal processing unit receives power from a power source or at the moment it is functionally turned on.

In the succeeding block 402, a timer is set by the signal processing unit such that the time overflows after a predetermined time period (e.g., five milliseconds or ten milliseconds) elapses and such that the timer starts over again for each moment that the predetermined time period elapses.

The previous block 402 is followed by block 404 wherein the signal processing unit checks the electrical signal originating from the signal detection unit for a fault condition and any other suspicious operating conditions which are considered failure points. Such fault condition of the electrical signal may be attributed to low values associated with the readings of the electrical signal due to various factors such as corroded contact points and terminals on the signal detection unit through which the : electrical current passes through inside an electrical panel or enclosure.

If a fault condition is detected as shown in decision block 406, the flow moves to block 408 wherein the signal processing unit generates an alert or notification. The alert or notification may be in the form of light indicators disposed on the outside surface of the signal processing unit.

Alternatively, the alert or notification may be in the form of SMS sent to a mobile communication device of a human user from a communication module of the signal processing unit. After which, the flow is directed to ignore the electrical signal having fault condition, as shown in block 410.

In the event that that the checking of the electrical signal for fault condition has a negative result (i.e., no fault condition is determined for the : electrical signal) as determined in the decision block 406, the flow advances to block 412 wherein the signal processing unit takes electrical : current reading and immediately to block 414 wherein the signal processing unit validates the electrical current reading.

The validation or inspection of the electrical current reading is required to ensure the integrity of the electrical current reading, as it is possible that the signal processing unit may have been tampered prior to taking of the electrical current reading in the previous block 412. The date and time information associated with the validation may be also be recorded by the signal processing unit.

A successful determination that the validated electrical current reading is normal, as shown in decision block 416, causes the flow to : progress to block 418 wherein the signal processing unit determines if the time that has been previously set and initialized has already overflowed. A time overflow, as determined in decision block 420 causes the flow to move to block 422 wherein the electrical current reading is prepared for transmission to a data processing unit, through a communication network, : by a communication module.

If the time has not yet elapsed as determined in the decision block 420, on the other hand, the flow moves back to 404 wherein the electrical signal is checked again for fault condition. As long as no time overflow is contemplated by the signal processing unit, a loop is formed between blocks 404 and 420, unless a fault condition is determined for the electrical signal in the decision block 406 and an abnormal electrical current reading associated with the electrical signal is contemplated by the signal processing unit in the decision block 416. :

An abnormal electrical current reading, for whatever reason, causes the flow to terminate at blocks 408 and 410, wherein the signal processing unit generates an alert or notification and ignores the electrical signal, respectively. The alert or notification may likewise be in the form of light indicators disposed on the outside surface of the signal processing unit. Alternatively, the alert or notification may be in the form of SMS sent to a mobile communication device of a human user from a communication module of the signal processing unit.

Referring now Figure 5, there is shown a block diagram illustrating preferred architecture of signal processing unit according to one or more embodiments of the present invention. The signal processing unit comprises a signal receiver 500 and a signal transmitter 502. The signal receiver 500 receives an electrical signal from a signal detection unit attached to an electrical panel. A signal conditioning component of the signal processing unit converts the electrical current signal into a voltage signal.

The signal processing unit processes the voltage signal (analog) from its input terminal 504 and converts the same voltage signal into a computer-readable digital voltage value (digital). Specifically, the conversion from the voltage signal to the computer-readable voltage value is effected by an analog-to-digital converter (ADC) 506 functionally embedded in the signal processing unit. It should be noted that external analog-to-digital converters may also be used for the purpose of converting the voltage signal into the computer-readable digital voltage value.

A voltage to current conversion equation may be functionally implemented in a firmware of the signal processing unit for converting the computer-readable voltage value into a computer-readable digital current value corresponding to the electrical signal originally detected by the signal detection unit. The signal transmitter 502 of the signal processing unit transmits the computer-readable digital current value to a remote data processing unit through a communication module connected, directly or indirectly, to a communication network.

The signal processing unit may also include other hardware resources such as, but not limited to, a central processing unit (CPU) or processor 508, a random access memory (RAM) 510, a read-only access memory (ROM) 512, a control logic 514, a timer 516, and input/out (I/O) ports 518.

The input terminal 504, the timer 516, the 1/0 ports 518, the ADC 506, the processor 508, the RAM 510, the ROM 512, and the control logic 514 are in communication with one another through a bus system 520.

The signal processing unit may also have a display component 522 for graphically displaying human-readable information generated by the data processing unit. A keypad component 524 may also be included in the signal processing unit for inputting data originating from an authorized operator of the signal processing unit.

Referring to Figure 6, there is shown an interaction diagram of a preferred data processing model according to one or more embodiments of the present invention. The data processing model in Figure 6 specifically illustrates the interaction between a data processing unit 124 with a database system 130 and also the interaction between the data processing unit 124 and a memory component 126 containing computing functions in the form of computer-executable instructions. ;

At block 600, the data processing unit 124 receives per minute energy data from a communication module of a signal processing unit. At subsequent block 602, the data processing unit 124 stores the per minute energy data into the database system 130. In turn, the database system 130 stores the per minute energy data as shown in block 604.

Consequently, the data processing unit 124 may be arranged to call computing functions for calculating energy consumption related information as shown in block 606, triggering the computer-executable instructions corresponding to the computing functions to be retrieved from the memory component 126 as shown in block 608.

The computer-executable instructions retrieved from the memory component 126 are executed by the data processing unit 124 as shown in block 610. The resulting energy consumption related information are then stored by the data processing unit 128 into the database system 130 as shown, respectively, in blocks 612 and 614.

Referring now to Figure 7, there is shown a flow diagram illustrating a preferred flow of data from one computing resource to another according to one or more embodiments of the present invention. Specifically, the flow diagram in Figure 7 illustrates a preferred flow of data from a database system 130 to an application layer 700.

End user access to various energy consumption related information, : which are generated based on raw data from the database system 130 and as well as on the derived data through energy analysis functions 702 can be provided at the application layer 700.

The database system 130 stores raw data from a signal processing unit, namely, line use intensity 704 and per minute dataset energy 706.

The line use intensity 704 is characterized by the category of the user in terms of total power rating of one power line or appliance typically associated with one energy consumer.

The per minute dataset energy 706 is the energy data, preferably in 5s kWh, saved into the database system 130 for every minute the communication module of the signal processing unit sends energy data.

Given that there is 60 minutes in one hour, a 24-hour energy data may produce 1440 data points which can be stored into or retrieved from the database system 130 at any given time.

The database system 130 also contains per hour dataset energy 708, per hour dataset peak power 710, and appliance or line class 712.

Each of the per hour dataset energy 708 and the per hour dataset peak power 710 is derived based on the per minute dataset energy 706.

The per hour dataset energy 708 may be characterized by hourly energy, preferably in kWh, saved into the database and computed from summing 60 data points from the per minute dataset energy 706. A 365- day data (8760 data points) associated with the per hour dataset energy 710 can be stored into or retrieved from the database system 130 at any point of time.

The per hour dataset peak power 710 may be characterized by hourly peak power, preferably in kW, saved into the database and computed from determining the maximum power for the hour, which is in turn computed from the per minute dataset energy 706. A 365-day data (8760 data points) associated with the per hour dataset peak power 710 ; can be stored into or retrieved from the database system 130 at any point of time.

The line class 712 specifies the type of appliance on the line. The appliance, by way of example, may include an air-conditioner, a water pump, a refrigerator, a lighting unit, a washing machine, and a water

Heater. It should be understood and appreciated by persons skilled in the art that such a household based appliance may be of the type that can also be seen commonly in commercial and industrial buildings.

The energy analysis functions or computing functions 702 may include energy related consumption information such as power rating 714, hourly energy total 716, daily energy total 718, weekly energy total 720, monthly energy total 722, annual energy total 724, on/off time function 726, per minute power 728, and peak power for the hour 730.

The on/off time function 726, the per minute power 728, and the peak power for the hour 730 are based on the per minute dataset energy 706. The on/off time function 726 may include total duration of use 732. 15s The power rating 714, the hourly energy total 716, the daily energy total 718, the weekly energy total 720, the monthly energy total 722, and the annual energy total 724 may be based on the per hour dataset energy 708.

The power consumption 714 is representative of the function for determining the actual power consumption of the associated circuitry. The ; hourly energy total 716 is representative of the function for determining the total energy for the hour in kWh.

The daily energy total 718 is representative of the function for determining the total energy for the day in kWh. The weekly energy total 720 is representative of the function for determining the total energy for the week in kWh. The monthly energy total 722 is representative of the function for determining the total energy for the month in kWh.

The annual energy total 724 is representative of the function for determining the total energy for the year in kWh. The on/off time function 726 is representative of the function for determining if the line is turned on or off. The per minute power 728 is representative of the function for determining the per-minute power of a line.

The peak power for the hour 730 is representative of the function for determining the peak power for the hour of the line. The total duration of use 732 is representative of the function to determine the total time that the line is turned on for the day, week, or month.

The application layer 700 may include line use intensity 704, energy related consumption information such as air-conditioner energy recommendations 734, refrigerator energy recommendations 736, water pump energy recommendations 738, lighting energy recommendations 740, washing energy recommendations 742, and water heater energy recommendations 744, to name a few.

Each of the recommendations 734, 736, 738, 740, 742, 744 may be based on the power consumption 714, the monthly energy total 722, and the total duration of use 732 of the energy analysis functions 702 and on the line class 712.

The air-conditioner energy recommendations 734 are representative ; of the group of functions providing the energy efficiency recommendations for the air conditioner. The refrigerator energy recommendations 736 are representative of the group of functions providing the energy efficiency recommendations for the refrigerator. The water pump energy recommendations 738 are representative of the group of functions providing the energy efficiency recommendations for the water pump.

The lighting energy recommendations 740 are representative of the group of functions providing the energy efficiency recommendations for the lighting. The washing machine energy recommendations 742 are representative of the group of functions providing the energy efficiency recommendations for the washing machine. The water heater energy recommendation 744 are representative of the group of functions providing the energy efficiency recommendations for the water heater.

Referring now to Figure 8, there is shown a block diagram illustrating a recommendation data model according to one or more embodiments of the present invention. The recommendation information illustrated in Figure 7 may be managed using a recommendation generator module 800 embodied as a combination of both hardware and software units.

The recommendation generator module 800 evaluates user generated content 802 operable by an end user or end consumer of the system described in Figure 1 based on the administrator generated content 804 operable by an administrator of the same system. The user generated content 802 and the administrator generated content 804 may be stored in the database system described in Figure 1. The recommendation generator module 800 may also include analytical tools 806 likewise embodied as a combination of both hardware and software units.

The user generated content 802 may include energy data 808, duration of use data 810, appliance specification 812, and user profiles 814. It should be understood and appreciated by persons skilled in the art the user generated content 802 may include other data that are relevant in improving the user experience of the end user accessing and using the system and method of the present invention. For example, photos, videos, and other similar multimedia content may be generated by the end user and store them into the database system of the system illustrated in Figure : 1.

Uploading the multimedia content into the database system enables the administrator of the system of the present invention to access them. If such administrator has an access to the multimedia content which, for example, depicts a complaint or technical issues from the end user, the administrator may be enabled to address the complaint or the technical issues in an accurate and efficient manner using the multimedia content. In other words, the administrator may manually review the multimedia content in order to formulate recommendation information suitable for resolving the complaint or the technical issues reported by the end user.

The administrator generated content 804 may include recommendation type 816, recommendation variables 818, recommendation benchmark 820, recommendation items 822, recommendation logic 824, and recommendation references 826. The recommendation type 816 may be representative of, by way of examples, energy saving plan, cost-efficient energy management initiatives and anomaly examination, all of which can be based on behavioral analysis, energy efficiency analysis, and power supply analysis in accordance with the system and method of the present invention.

The recommendation variables 818 may include the line use intensity, the per minute dataset energy, the per hour dataset energy, the ; per hour dataset peak power, the line class, the power consumption, the hourly energy total, the daily energy total, the weekly energy total, the monthly energy total, the annual energy total, the on/off time function, the per minute power, the peak power for the hour, and the total duration of use which are fully described in Figure 7.

The recommendation benchmark 820 enables the administrator to incorporate information on industry based energy management practices and standards, if any, into the system described in Figure 1 and to develop, : in an objective fashion, the abovementioned behavioral analysis, energy : efficiency analysis, and power supply analysis which are to be performed by the data processing unit described in Figure 1.

The recommendation items 822, which are included in the administrator generated content 804, may be related to energy saving tips.

For example, the recommendation items 822 may incorporate information on the efficient use of home appliances in order for the end user to save energy. Specific tips embodied in the recommendation items 822 may include, for example, setting an air-conditioning unit at an efficient temperature range, cleaning air filters in the air-conditioning unit, keeping a refrigeration unit closed whenever possible, and regularly cleaning a wide range of home appliances.

The recommendation logic 824, which are included in the administrator generated content 804, may be configured to generate energy consumption related information based on one or more predetermined criteria. For example, if a particular home appliance consumes energy above a given threshold, then a suitable recommendation information can be generated by the data processing unit for display on the user communication device as fully described in Figure 1.

The recommendation references 826 may include a compilation of information on laws, regulations, rules and public policies which are concerned with energy usage and energy management, among others. The inclusion of these recommendation references 826 in the administrator : generated content 804 ensures that the administrator is informed of relevant laws, regulations, rules and even public policies which may affect the arrangement and delivery of recommendation information corresponding to energy consumption related information from end users.

The analytics tools 806 may include a Boolean logic analyzer 828 and a semantic logic analyzer 830. The Boolean logic analyzer 828 includes computer-executable instructions, which when executed, may determine the relationships between the strings of characters associated with the energy data 808 included in the user generated content 802 and strings of characters associated with the energy consumption related information such as the recommendation information included in the administrator generated content 804.

In that case, a particular recommendation information characterized by the energy consumption related information may be generated based on relevant keywords from the user generated content 802. For example, if the appliance specification 812 is determined to be "refrigerator," then the

Boolean logic analyzer 828 may be initiated to retrieve recommendation items 822 from the administrator generated content 804 which contain the string of characters "refrigerator" together with other information associated with the recommendation items 822.

The semantic logic analyzer 830, which may be additionally provided in the analytics tools 806, includes computer-executable instructions, which when executed, may determine the relationships : between the meanings of the natural language associated with the energy data 808 included in the user generated content 802 and the natural language associated with the energy consumption related information such as the recommendation information included in the administrator generated content 804.

In that case, a particular recommendation information characterized by the energy consumption related information may be generated based on the meanings of the natural language from the user generated content 802. For example, if an air-conditioning unit is briefly described in the user generated content 802 to have been malfunctioning over an extended time period, then the semantic logic analyzer 830 may be initiated to derive the meaning of the brief description and map for suitable energy consumption related information from the administrator generated content 804 based on the derived meaning of said brief description.

The analytics tools 806 may further include cost savings analyzer 832 and return on investment analyzer 834. The cost savings analyzer 832 may include mathematical functions that can be evaluated to determine electricity savings and cost savings. An example of a relevant mathematical formula is "electricity savings=(power rating)*(Y,-Y,)," wherein Y, is the average duration of use of an appliance across an end : user's category, and Y; is the total duration of use of an appliance by the end user.

Another example of a relevant mathematical formula that can be evaluated through the cost savings analyzer 832 is "cost savings=electricity savings*electricity rate." The return on investment analyzer 834 may likewise include mathematical functions that can be evaluated to determine return on investment (ROI) information. An example of a relevant mathematical formula that can be evaluated through the return on investment analyzer 834 is "ROI in years=(investment : needed)/(monthly cost savings*12)."

In addition, the analytics tools 806 may be arranged to include a distributed power supply analyzer 836, an equipment analyzer 838, a behavioral analyzer 840, a retail electricity analyzer 842, an enterprise analyzer 844, all of which are suitable for periodically collecting information from one or more devices across a network or community and delivering required information.

Referring to Figure 9, there is shown a logic flow diagram illustrating a preferred process for validating a user account suitable for use in the system of Figure 1 according to one or more embodiments of the present invention. The user account is maintained in an online platform delivered by the data processing unit described in Figure 1, and belongs to an end user or end consumer desiring to have his or her home network to be optimized in terms of energy consumption.

The flow starts at block 900 wherein the data processing unit receives from the end user a request to access webpages associated with the online platform and continues to block 902 wherein the data processing unit provides the requested webpages.

If the end user does not have an existing account with the online platform as determined in decision block 904, the flow moves to block 906 wherein the data processing unit prompts the user to create a new user account. Otherwise, if the end user has an existing user account with the online platform, the data processing unit prompts the user to enter login information as shown in block 908.

Prompting the user to create the new user account in the previous block 906 is succeeded by receiving a user profile data from the end user for the user account as shown in block 910. Once the user account has been successfully created by the end user, the data processing unit prompt the administrator that a new account has been created as shown block 912. This ensures that the administrator will be informed of potential €nergy management requirements of the new user of the system fully described in Figure 1. The administrator may be a technical person knowledgeable of energy management functions.

The prompting of the user to enter login information in the previous block 908 is succeeded by the validating of the login information as shown in block 914. The validity of the login information is determined in decision block 916. If the login information is invalid, the flow moves back to the previous block 908 to once again prompt the user to enter a valid login information.

If the login information is valid as determined in the decision block 916, the flow progresses to blocks 918 and 920 wherein the data processing unit obtains all data associated with the user account and prepares the obtained data for access by the user using his or her user communication device, respectively.

It is to be understood and appreciated by persons skilled in the art that the described webpages may be replaced by any equivalents, that the described online platform delivered by the data processing unit may be formed using any suitable markup languages such as HTML and XML, and that the web-based application providing the webpages may also replaced by a mobile-based application or cloud-based application.

Referring now to Figure 10, there is shown a logic flow diagram illustrating a preferred process for ranking data according to one or more embodiments of the present invention. Specifically, the preferred process in

Figure 10 is carried out by the data processing described in Figure 1 and is : intended for ranking appliance based on one or more criteria or conditions.

The flow commences by the data processing unit receiving a request to access a list of appliances on a webpage as shown in block 1000.

The flow continues by the data processing unit displaying the requested list of appliances as shown in a subsequent block 1002. For each request to access a list of appliances received by the data processing unit, the updated energy consumption related information is checked by the data processing unit from the database described in Figure 1, as shown in block 1004.

In succeeding block 1006, the flow advances by the data processing unit ordering the appliances based on a first condition. Preferably, the first condition is characterized by highest to lowest energy consumption data per time interval. After which, the flow moves forwards by the data processing unit arranging the appliances based on a second condition, as shown in block 1008. Preferably, the second condition is characterized by regular time intervals such as daily, weekly and monthly. It should be apparent to any persons skilled in the art that the first and conditions may be applied by the data processing unit in any order and in simultaneous manner.

Once the appliances have been ordered and arranged in accordance with the first and second conditions, the flow progresses by the data processing unit providing the ordered list of appliances as shown in block 1010, and then plotting the energy consumption data of each appliance as a percentage of total energy consumption data of all the appliances : included in the ordered list, as shown in block 1012.

Referring to Figure 11, there is shown a logic flow diagram illustrating a preferred process for plotting historical data according to one or more embodiments of the present invention. Specifically, the preferred process in Figure 11 is carried out by the data processing unit Figure 1, and is intended for plotting data representative of total energy consumption of each appliance for each time interval. The flow begins at block 1100 wherein the data processing unit receives request to access a list of appliances on a webpage.

The block 1100 is followed by block 1102 of the flow wherein the data processing unit displays the requested list of appliances. At block 1104, the data processing unit checks for updated energy consumption related information from the database system described in Figure 1. At block 1106, the data processing unit arranges the appliances based on a condition. The condition is preferably characterized by regular time intervals such as daily, weekly and monthly. At block 1108, the flow concludes by the data processing unit plotting the data representative of the total energy consumption of each appliance for each time interval.

Referring to Figure 12, there is shown a logic flow diagram illustrating a preferred process for executing an action based on a monitored data according to one or more embodiments of the present invention. Specifically, the preferred process in Figure 12 is carried out by the data processing unit Figure 1, and is intended for executing an action based on energy consumption related data monitored in near real-time.

The flow starts at block 1200 wherein the data processing unit continuously monitors the incoming energy consumption data feed from the signal processing unit described in Figure 1. After which, the flow advances to block 1202, wherein the data processing unit analyzes, in near real-time, the energy consumption data it has received from the signal processing unit.

At block 1204, the data processing unit detects, in near real-time, a predefined event based on the energy consumption data it has received in the previous block 1200. an example of an event that can be detected by the data processing unit is the existence of energy consumption data feed : for a specific appliance or type of appliance or specification of appliance.

At block 1206, the data processing unit triggers an event rules algorithm and evaluate one or more rules embodied in the event rules : algorithm. For example, if there is data feed, then tag the appliance as “turned on." It is to be understood and appreciate by persons skilled in the art that a wide range of rules may be applied by the data processing unit for the purpose of performing a predefined action.

At block 1208, the data processing unit obtains a predefined action based on the evaluated one or more rules in the previous block 1206. The flow concludes at block 1210 wherein the data processing unit performs the obtained predefined action based on the evaluated rules. An example : of the predefined action that can be obtained and executed by the data processing unit is graphically displaying an indicator that the appliance is "turned on." For example, a green color indicator may be graphically rendered so that the viewer of the energy consumption data can easily distinguish one information from another.

Referring to Figure 13, there is shown a logic flow diagram illustrating a preferred general process for performing a first energy related ; analysis according to one or more embodiments of the present invention.

Specifically, the preferred general process in Figure 13 is carried out by the data processing unit Figure 1, and is intended for performing a behavioral analysis in order to provide energy consumption related recommendations.

The energy consumption related recommendations under the behavioral analysis compare the energy consumption of a user's appliance to the same appliance of other users having access or are subscribed with : the system described in Figure 1. Through the behavioral analysis, users will be informed if their consumption behavior is below or above the \ average among users in a community having access or subscribed to the system described in Figure 1. The flow of the preferred general process in

Figure 13 are mainly divided into three steps.

The first step, as shown in block 1300, is characterized by the data processing unit categorizing line of use intensity of an end user or end : consumer. The line of use intensity of the end user is the category of the user in terms of total power rating as described in Figure 7.

The second step, as shown in block 1302, is characterized by the ; data processing unit comparing the user's energy consumption related : information with the energy consumption related information of the other users on the same category.

The third step, as shown in block 1304, is characterized by the data processing unit providing recommendation information on the duration of use based on the data generated in previous two steps described in the previous blocks 1300 and 1302.

Referring to Figure 14, there is shown a logic flow diagram illustrating a preferred specific process for performing one component of the energy related analysis in Figure 13 according to one or more embodiments of the present invention. Specifically, the preferred specific process in Figure 14 is carried out by the data processing unit illustrated in

Figure 1, and is intended for performing the categorization of line use intensity illustrated in Figure 13.

The flow starts at block 1400 wherein the data processing unit finds the maximum total power rating across all users in the network of users having access or subscribed with the system illustrated in Figure 1. For example, the maximum total power rating across the users in said network of users may be found to be 100 kW.

The flow consequently moves to block 1402 wherein the data processing unit finds the minimum total power rating across the users in said network of users having access to or subscribed with the system illustrated in Figure 1. For example, the minimum total power rating across the users in said network of users may be found to be 20 kw.

It is to be understood and appreciated by persons skilled in the art that the any of the steps described in blocks 1400 and 1402 may be interchangeably implemented. In that case, the steps of finding maximum and minimum total power rating across the users in said network may be carried out in any suitable order.

Once the maximum and minimum total power ratings have been defined in the previous blocks 1400 and 1402, respectively, the flow advances to block 1404 wherein the data processing unit is arranged to perform a mathematical operation for dividing each of the maximum and minimum power rating by a certain number of constant to determine range of each category. In the illustrated example, the each of the maximum and minimum power rating, 100kW and 20kW, are divided by a constant of 10 to determine range of each category.

In the illustrated example, the range of each category is determined to be 8 kW based on the 100kW as the maximum total power rating, 20kw as the minimum total power rating, and 10 as the constant serving as divisor. In that case, the range may be established following the interval of 8 kW (e.g., 1-8 kW range, 9-16 kW range, 17-24 kW range, and so on).

At the concluding block 1406, the data processing unit is arranged to compare the user's total power rating with the established categories to determine the user's category. For example, if the user's total power rating is 18 kw, then the data processing unit will tag the user as falling under the category of "17-24kW."

Referring to Figure 15, there is shown a logic flow diagram illustrating a preferred specific process for performing another component of the energy related analysis in Figure 13 according to one or more embodiments of the present invention. Specifically, the preferred specific process in Figure 15 is carried out by the data processing unit Figure 1, and is intended for performing a comparison between the user's energy consumption related information with the energy consumption related information of the other users on the same category as the user.

The flow starts at block 1500 wherein the data processing unit determines the average monthly energy consumption across the user's category (X;) and proceeds to block 1502 wherein the data processing unit determines the monthly energy consumption of the user (Xz). At subsequent block 1504, the data processing unit compares the average monthly energy consumption across the user's category (X,) and the monthly energy consumption of the user (X»).

In decision block 1506, the data processing unit determines which of the average monthly energy consumption across the user's category (X;) and the monthly energy consumption of the user (Xz) is greater in value.

If the monthly energy consumption of the user (Xz) is greater in value than the average monthly energy consumption across the user's category (X,), the flow moves to block 1508 wherein the data processing unit prompts the user that the user is above average among its category and, consequently, to block 1510 wherein the data processing unit displays the behavioral recommendations that the user can do or follow in order to reduce his energy consumption down to, if not way below, the level of the average monthly energy consumption across the user's category (Xi).

In the decision block 1506, if the average monthly energy consumption across the user's category (Xj) is greater in value than the monthly energy consumption of the user (Xz), the flow moves to block 1512 wherein the data processing unit prompts the user that the user is below average among its category. This information will enable the user to either continue with his or her current behavior in terms of consuming energy and be motivated to incur more savings by conserving more energy.

Referring to Figure 16, there is shown a logic flow diagram illustrating a preferred specific process for performing yet another component of the energy related analysis in Figure 13 according to one or 1s more embodiments of the present invention. Specifically, the preferred specific process in Figure 13 is carried out by the data processing unit

Figure 1, and is intended for providing recommendation information on duration of use of an appliance.

The flow starts at block 1600 wherein the data processing unit determines the average duration of use of appliances across a user's category (Y;). At block 1602, the data processing unit determines the total duration of use of an appliance by the user (Y,).

At block 1604, the data processing unit compares the determined average duration of use of appliances across a user's category (Y;) and the determined total duration of use of an appliance by the user (Y.). At block 1606, the data processing unit determines all total durations of use appliance (Y;) that are higher than the total duration of use (Y) in every appliance.

At block 1608, the data processing units prompts the user of his/her behavior compared to others in the same category. Finally, the data processing unit recommends time of use reduction relative to the difference between the average duration of use (Y;) and the total duration of use (Y2), as shown in block 1610.

Referring now to Figure 17, there is shown a logic flow diagram illustrating a preferred general process for performing a second energy related analysis according to one or more embodiments of the present invention. Specifically, the preferred general process in Figure 17 is carried out by the data processing unit Figure 1, and is intended for performing an energy efficiency analysis in order to provide energy consumption related recommendations.

The flow starts at block 1700 wherein the data processing unit determines the peak power of the month. At block 1702, the data processing unit recommends a replacement with an energy efficient appliance that has the same capacity/specification with a nameplate rating that is close to the peak power of the month.

The capacity/specification depends on the type of the appliance. For example, cooling capacity for air-conditioners, volume for refrigerators and freezers, head and capacity for water pumps, average luminance for lighting units, volume for washing machines, and temperature increase per : flow rate for water heaters.

At block 1704, the data processing unit determines energy and associated cost savings. The possible energy savings can be evaluated based on the following formula: monthly energy savings=(power rating,old- power rating,new)*(monthly total duration of use). The possible cost savings can be evaluated based on the following formula: monthly cost savings=(monthly energy savings)*(electricity price).

At block 1706, the data processing unit determines return on investment (ROI). The investment can be evaluated based on the following formula: investment=cost from the system's appliance database. The ROI can be evaluated based on the following formula: ROI in years=(investment needed)/(monthly cost savings*12).

Referring to Figure 18, there is shown a table illustrating a preferred function representative of a third energy related analysis according to one or more embodiments of the invention. Specifically, the preferred function in Figure 18 is carried out by the data processing unit Figure 1, and is intended for performing a power supply analysis in order to provide energy consumption related recommendations.

The illustrated table has three columns, namely, a time interval column 1800 containing time interval data, a schedule ID column 1802 containing ID data corresponding to the time interval data in the time interval column 1800, and a consumption data column 1804 containing energy consumption data. The energy consumption data as a function of time of use is graphically represented in Figure 19 which is a graphical representation of the table illustrated in Figure 18.

In the power supply analysis aspect of the present invention, the system illustrated in Figure 1 recommends other power supply options for the users. The recommendation depends on the time range or time interval when the users have high energy consumption. The alternative electricity supply procurement function determines the time interval when the users consumes most of the energy resources (i.e., around 60-70% of the total average daily energy). If a user uses most of the energy resources during day time, the system illustrated in Figure 1 may recommend a solar photovoltaic (PV) power supply. Investment and expected returns may be included as part of the recommendations for the solar PV power supply.

If the user uses most of the energy resources during night time, the system illustrated in Figure 1 recommends a time of use program by their electricity distributor. Investment and expected returns may be included as part of the recommendations for the time of use program.

If the user's behavior is indicative of a combination of day time and night time energy consumption, then the system illustrated in Figure 1 may recommend a combination of a solar PV system and the time of use program. Likewise, investment and expected returns may be included as part of the recommendations for the combination of the solar PV system and the time of use program.

Referring now to Figure 20, there is shown a block diagram illustrating a preferred hardware architecture suitable for use in the system of Figure 1 according to one or more embodiments of the present invention.

The data processing architecture in Figure 20 exemplifies a representative hardware environment associated with the data processing unit, as illustrated in Figure 1, for carrying out any of the embodiments of the present invention. The data processing unit preferably comprises a

System bus 2000 which enables data and electronic communications of components of the data processing unit with one another.

Electronic data which include, among others, information on the set of energy consumption data, the sets of recommendation data described in

Figure 1 may be handled by a central processing unit (CPU) 2002 fetching computer-executable instructions 2004 from the memory component 2006.

The memory component 2006 may include random-access memory (RAM), read-only memory (ROM), flash memory, erasable programmable read only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), and the like. A memory controller 2008 may be used to control the memory component 2006.

An interrupt controller 2010 may be used for receiving processing interrupt signals from the components of the data processing unit. Other controllers 2012, 2014, 2016 may likewise be included in the hardware configuration of the data processing unit for controlling a CD ROM drive 2018, a fixed disk drive 2020, and a removable disk drive 2022, respectively.

Input and output devices such as keyboards, pointers, microphones, speakers, and the like may be connected to the bus system 2000 through the user interface adapter 2024. Further, a display adapter 2026 may be used to connect a display device such as a computer monitor to the system bus 2000.

The data processing unit may also include an I/O adapter 2028 for connecting one or more external peripheral devices modems, card readers, and printers to the system bus 2000. In order to facilitate transmission of data between the data processing unit and user communication devices through a communication network such as the Internet, a communications adapter 2030 may also be used for interfacing the data processing unit with the communication network. 1t is to be understood and appreciated by persons skilled in the art that the illustrated hardware configuration or architecture of the data processing unit is non-limiting.

While the present invention has been described with respect to a limited number of embodiments, those skilled in the art, having benefit of this disclosure, will appreciate that other embodiments can be devised which do not depart from the scope of the invention as disclosed herein.

Claims (23)

Claims

1. A computer-implemented system for providing energy consumption related information based on monitored energy data, the system comprising: at least one signal detection unit coupled to a circuitry associated with at least one energy consuming device, the detection unit being CO adapted to transduce an electrical signal associated with the circuitry; a signal processing unit disposed in an operative position relative to the at least one signal detection unit for receiving the electrical signal from the at least one signal detection unit and for processing the electrical signal such that an energy data is provided and prepared for transmission through a communication network; and a data processing unit in communication with the signal processing unit through the communication network for receiving the energy data when the energy signal is transmitted by the signal processing unit and for executing a data processing algorithm which, when executed by the data processing unit from at least one memory component of the data processing unit, causes energy consumption related information to be generated based on the energy data and further causes the energy consumption related information to be accessed on a display screen of at least one user communication device connected to the communication network based upon a request received by the data processing unit from the at least one user communication device through the communication network,

wherein the energy consumption related information include at least a set of energy consumption data, a first set of recommendation data representative of behavior of the at least one energy consuming device in relation to at least one another energy consuming device of the same category, a second set of ; recommendation data representative of power consumption efficiency of the at least one energy consuming device, a third set of recommendation data representative of autonomous power supply for the at least one energy consuming device depending on the behavior of the at least one energy consuming device receiving electrical power from an electrical grid, and a fourth set of recommendation data representative of alternative on-grid electricity supply procurement options for the at least one energy consuming device depending on the behavior of the at least one energy consuming device receiving electrical power from the electrical grid.

2. The system according to claim 1, wherein the set of energy consumption data includes power consumption data.

3. The system according to claim 1, wherein the set of energy consumption data is generated based on any one or any suitable ; combination of the following frequencies: hourly, daily, weekly, monthly, and annually.

4. The system according to claim 1, wherein the first set of recommendation data includes duration of use of the at least one energy consuming device within any given time period.

5. The system according to claim 1, wherein the second set of recommendation data includes an indication of a replacement of the at least one energy consuming device in relation to the energy consumption efficiency of the at least one energy consuming device.

6. The system according to claim 1, wherein the electrical signal is any of an electrical current signal and an electrical voltage signal.

7. The system according to claim 1, wherein the signal processing unit includes a signal conditioning component.

8. The system according to claims 6 and 7, wherein the signal : conditioning component converts any of the electrical current and the electrical voltage signal into a signal that is compliant to the input of the signal processing unit.

9. The system according to claim 1, wherein the signal processing unit converts the electrical signal to a computer-readable digital electrical value.

10. The system according to claim 9, wherein the signal processing unit determines at least one electrical parameter based on one or more of the computer-readable digital electrical value within any given time period. :

11. The system according to claim 1, wherein the signal processing unit is selected from any one of the following: a microcontroller, a : microprocessor, a Field Programmable Field Array (FPGA), a programmable logic controller (PLC), a microcomputer, and a digital signal processor (DSP).

12. The system according to claim 1, wherein the at least one user communication device is selected from any of the following: a first user communication device on which a web-based application can be accessed, a second user communication device on which a mobile- based application can be accessed, a third user communication device on which a cloud-based application can be accessed.

13. The system according to claim 1, wherein the communication network utilizes any of wired and wireless connections.

14. The system according to claim 1, wherein the communication network is the Internet connecting a server and a short message service center (SMSC).

15. The system according to claim 1, wherein the energy data transmitted to the data processing unit are stored in a database system hosted by the data processing unit.

16. The system according to claim 1, wherein any of the second and third sets of recommendation data include return on investment data associated with use of the at least one energy consuming device within any given time period.

17. The system according to claim 1, wherein the set of energy consumption data is graphically presented on the display screen of the at least one user communication device.

18. The system according to claim 1, wherein the second set of recommendation data includes the quantity of energy consuming devices which are in operation with any given time period.

19. A computer-implemented method of providing energy consumption related information based on monitored energy data, the method comprising the steps of:

transducing, by at least one signal detection unit, an electrical signal associated with a circuitry of at least one energy consuming device; processing, by a signal processing unit, the electrical signal such that an energy data is provided and prepared for transmission through a communication network; and transmitting, by a communication module in communication with the signal processing unit, the energy data to a data processing unit in communication with the signal processing unit through the communication network, ; wherein the data processing unit is arranged to execute a computer- executable instructions from at least one memory component of the data processing unit to cause energy consumption related information to be generated based on the energy data and to further cause the energy consumption related information to be accessed on a display screen of at least one user communication device connected to the communication network based upon a request received by the data processing unit from the at least one user communication device through the communication network, wherein the energy consumption related information include at least a set of energy consumption data, a first set of recommendation data representative of behavior of the at least one energy consuming device in relation to at least one another energy : consuming device of the same category, a second set of recommendation data representative of power consumption efficiency of the at least one energy consuming device, a third set of recommendation data representative of autonomous power supply for the at least one energy consuming device depending on the :

behavior of the at least one energy consuming device receiving electrical power from an electrical grid, and a fourth set of recommendation data representative of alternative on-grid electricity supply procurement options for the at least one energy consuming device depending on the behavior of the at least one energy consuming device receiving electrical power from the electrical grid.

20. The method according to claim 19, wherein the electrical signal is any of an electrical current signal and an electrical voltage signal.

21. The method according to claim 20, wherein the step of processing the electrical signal includes converting any of the electrical current signal and the electrical voltage signal into a signal that is compliant to the input of the signal processing unit.

22. The method according to claim 1, wherein the step of processing the electrical signal includes converting the electrical signal to a computer-readable digital electrical value.

23. The method according to claim 22, wherein the step of processing the electrical signa! includes determining at least one electrical parameter based on one or more of the computer-readable digital electrical value within any given time period.