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Title:
DEVICES AND SYSTEMS FOR EDGE VEHICLE DATA MANAGEMENT
Document Type and Number:
WIPO Patent Application WO/2019/161296
Kind Code:
A1
Abstract:
Systems and methods for a fleet data edge (110) including: a processor (210) having addressable memory (220, 230); an open USB accessory bus (250) in communication with the processor, the open USB accessory bus configured to connect to one or more sensors (115); a transceiver (280) in communication with the processor, the transceiver configured to wirelessly connect to a data management server (140); where the fleet data edge processor is configured to: collect, by the open USB accessory bus, proprietary sensor data from the one or more sensors; convert the collected sensor data to a common messaging data schema; and transmit, by the transceiver, the converted sensor data to the data management server.

Inventors:
MANSFIELD, Stephen, K. (2627 Treanor Terrace, Wellington, FL, 33414, US)
Application Number:
US2019/018344
Publication Date:
August 22, 2019
Filing Date:
February 15, 2019
Export Citation:
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Assignee:
WEBASTO CHARGING SYSTEMS, INC. (800 Royal Oaks Drive, Suite 210Monrovia, CA, 91016, US)
International Classes:
G01M17/00; B28C5/42; G07C5/08
Attorney, Agent or Firm:
ZARRABIAN, Michael et al. (Brooks Acordia IP Law, P.C.11601 Wilshire Blvd.,Fifth Floo, Los Angeles CA, 90025, US)
Download PDF:
Claims:
WHAT IS CLAIMED IS:

1. A system comprising:

a fleet data edge (110) comprising:

a processor (210) having addressable memory (220, 230);

an open USB accessory bus (250) in communication with the processor, the open USB accessory bus configured to connect to one or more sensors (115); and a transceiver (280) in communication with the processor, the transceiver configured to wirelessly connect to a data management server (140);

wherein the fleet data edge processor is configured to:

collect, by the open USB accessory bus, proprietary sensor data from the one or more sensors;

convert the collected sensor data to a common messaging data schema; and

transmit, by the transceiver, the converted sensor data to the data

management server.

2. The system of claim 1, wherein the fleet data edge processor is further configured to:

detect a sensor of the one or more sensors connected to the fleet data edge; install a USB driver (316) for the detected sensor; and install a data abstraction (314) for the detected sensor, wherein the

installed data abstraction converts the collected sensor data to the common messaging data schema.

3. The system of claim 1, wherein the one or more sensors comprise at least one of: a bar code scanner, a precision locator, and an employee card swipe device.

4. The system of claim 1, wherein the transceiver is configured to wirelessly transmit via at least one of: WiFi (135) and cellular Internet communications (130).

5. The system of claim 1, wherein the open USB accessory bus comprises one or more four- pin circular plastic connectors (CPC).

6. The system of claim 1, wherein the fleet data edge further comprises: a battery harness analog-to-digital converter (ADC) (240) in communication with the processor, the ADC configured to connect to one or more battery packs of a material handling equipment (MHE) (120).

7. The system of claim 6, wherein the fleet data edge processor is further configured to:

collect, by the ADC, battery pack data on the one or more battery packs of the MHE, wherein the battery pack data comprises at least one of: a battery voltage, a mid-battery voltage, a battery current, a battery temperature, a specific gravity, a water level, a power, a ground, a charging communications port, and a harness ID.

8. The system of claim 7, wherein the fleet data edge processor is further configured to:

convert the collected battery pack data to the common messaging data schema.

9. The system of claim 8, wherein the fleet data edge processor is further configured to:

transmit, by the transceiver, the converted battery pack data.

10. The system of claim 7, wherein the fleet data edge processor is further configured to:

analyze the one or more battery packs based on at least one of: an energy usage, an energy capacity, a battery technology, the battery temperature, the specific gravity, and the water level of the one or more battery packs based on the collected battery pack data.

11. The system of claim 10, wherein the fleet data edge processor is further configured to:

determine a charge profile for the one or more battery packs based on the analyzed one or more battery packs, wherein the determined charge profile is an optimum charge cycle.

12. The system of claim 11, wherein the fleet data edge processor is further configured to:

transmit, by the transceiver, the determined charge profile, wherein the determined charge profile is configured to be downloaded to one or more chargers (125).

13. The system of claim 7, wherein the fleet data edge processor is further configured to: determine an energy state of the one or more battery packs of the MHE based on the collected battery pack data;

determine an energy capacity of the one or more battery packs of the MHE based on the collected battery pack data; and

determine an energy utilization of the one or more battery packs of the MHE based on the collected battery pack data.

14. The system of claim 6, wherein a battery pack of the one or more battery packs is a lead- acid battery pack.

15. The system of claim 6, wherein the ADC comprises one or more eighteen-pin battery harness connectors.

16. A method comprising:

collecting, by an open ETSB accessory bus (250) in communication with a fleet data edge (110) processor (210) having addressable memory (220, 230), proprietary sensor data from one or more sensors (115), wherein the open ETSB accessory bus is configured to connect to the one or more sensors;

converting, by the processor, the collected sensor data to a common messaging data

schema; and

transmitting, by a transceiver (280) in communication with the processor, the converted sensor data to the data management server.

17. The method of claim 16 further comprising:

detecting, by the processor, a sensor of the one or more sensors connected to the fleet data edge;

installing, by the processor, a ETSB driver (316) for the detected sensor; and

installing, by the processor, a data abstraction (314) for the detected sensor, wherein the installed data abstraction converts the collected sensor data to the common messaging data schema.

18. The method of claim 16 further comprising: collecting, by a battery harness analog-to-digital converter (ADC) (240) in communication with the processor, battery pack data on the one or more battery packs of a material handling equipment (MHE) (120), wherein the battery pack data comprises at least one of: a battery voltage, a mid-battery voltage, a battery current, a battery temperature, a specific gravity, a water level, a power, a ground, a charging communications port, and a harness ID, and wherein the ADC is configured to connect to one or more battery packs of the MHE;

converting, by the processor, the collected battery pack data to the common messaging data schema; and

transmitting, by the processor, by the transceiver, the converted battery pack data.

19. The method of claim 16 further comprising:

collecting, by a battery harness analog-to-digital converter (ADC) (240) in

communication with the processor, battery pack data on the one or more battery packs of a material handling equipment (MHE) (120), wherein the battery pack data comprises at least one of: a battery voltage, a mid-battery voltage, a battery current, a battery temperature, a specific gravity, a water level, a power, a ground, a charging communications port, and a harness ID, and wherein the ADC is configured to connect to one or more battery packs of the MHE;

analyzing, by the processor, the one or more battery packs based on at least one of: an energy usage, an energy capacity, a battery technology, the battery temperature, the specific gravity, and the water level of the one or more battery packs based on the collected battery pack data;

determining, by the processor, a charge profile for the one or more battery packs based on the analyzed one or more battery packs, wherein the determined charge profile is an optimum charge cycle; and

transmitting, by the transceiver, the determined charge profile, wherein the determined charge profile is configured to be downloaded to one or more chargers (125).

20. A system comprising:

a fleet data edge (110) comprising:

a processor (210) having addressable memory (220, 230);

an open USB accessory bus (250) in communication with the processor, the open USB accessory bus configured to connect to one or more sensors (115); a battery harness analog-to-digital converter (ADC) (240) in communication with the processor, the ADC configured to connect to one or more battery packs of a material handling equipment (MHE) (120); and

a transceiver (280) in communication with the processor, the transceiver

configured to wirelessly connect to a data management server (140);

wherein the fleet data edge processor is configured to:

collect, by the open UAB accessory bus, proprietary sensor data from the one or more sensors;

convert the collected sensor data to a common messaging data schema; collect, by the ADC, battery pack data on the one or more battery packs of the MHE, wherein the battery pack data comprises at least one of: a battery voltage, a mid-battery voltage, a battery current, a battery temperature, a specific gravity, a water level, a power, a ground, a charging communications port, and a harness ID;

convert the collected battery pack data to a common messaging data

schema; and

transmit, by the transceiver, at least one of: the converted battery pack data and the converted sensor data to the data management server.

Description:
DEVICES AND SYSTEMS FOR EDGE VEHICLE DATA MANAGEMENT

CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the priority benefit of U.S. Provisional Patent Application Serial Number 62/631,446 filed February 15, 2018, incorporated herein by reference in its entirety.

FIELD OF ENDEAVOR

[0002] The present embodiments relate to supply chain management. In particular, the present embodiments relate to managing edge vehicle data.

BACKGROUND

[0003] Most companies use some form of supply chain management to lower costs and improve the efficiency of delivery of goods to their customers. Some of the best companies have optimized their supply chain performance by investing in Information Technology, Big Data and Big Data analytics. Big Data analytics can often reveal inefficient processes and provide insight into new ways of managing the supply chain.

[0004] As an example, Walmart® of Bentonville, Arkansas is using big data analytics to squeeze costs out of its supply chain. Walmart collects 2.5 Petabytes of data from over 1 million customers that visit it’s stores or website each day. Utilizing a 250 node Hadoop cluster, it analyzes this data to make real-time supply chain inventory management decisions using predictive analytics. Walmart cost of distribution is 1.7% of sales. This is in contrast to Kmart® of Hoffman Estates, Illinois and Sears at 2.5% and 5% respectively.

SUMMARY

[0005] The various embodiments of the present devices, methods, and systems have several features, no single one of which is solely responsible for their desirable attributes. Without limiting the scope of the present embodiments as expressed by the claims that follow, their more prominent features now will be discussed briefly. After considering this discussion, and particularly after reading the section entitled“Detailed Description,” one will understand how the features of the present embodiments provide the advantages described herein.

[0006] One aspect of the present embodiments includes an integrated device comprising a plurality of sensors, a data store to store collected sensor data, a network connection, wherein the device collects and stores sensor data, translates the stored sensor data, transmits the translated sensor data to a cloud-based server via the network connection; and is attached to a material handling equipment vehicle.

[0007] A system embodiment may include: a fleet data edge comprising: a processor having addressable memory; an open USB accessory bus in communication with the processor, the open USB accessory bus configured to connect to one or more sensors; a transceiver in communication with the processor, the transceiver configured to wirelessly connect to a data management server; where the fleet data edge processor may be configured to: collect, by the open USB accessory bus, proprietary sensor data from the one or more sensors; convert the collected sensor data to a common messaging data schema; and transmit, by the transceiver, the converted sensor data to the data management server.

[0008] In additional system embodiments, the fleet data edge processor may be further configured to: detect a sensor of the one or more sensors connected to the fleet data edge; install a USB driver for the detected sensor; and install a data abstraction for the detected sensor, where the installed data abstraction may convert the collected sensor data to the common messaging data schema. In additional system embodiments, the one or more sensors may include at least one of: a bar code scanner, a precision locator, and an employee card swipe device. In additional system embodiments, the transceiver may be configured to wirelessly transmit via at least one of: WiFi and cellular Internet communications. In additional system embodiments, the open USB accessory bus may include one or more four- pin circular plastic connectors (CPC).

[0009] In additional system embodiments, the fleet data edge may further include: a battery harness analog-to-digital converter (ADC) in communication with the processor, the ADC configured to connect to one or more battery packs of a material handling equipment (MHE). In additional system embodiments, the fleet data edge processor may be further configured to: collect, by the ADC, battery pack data on the one or more battery packs of the MHE, where the battery pack data may include at least one of: a battery voltage, a mid- battery voltage, a battery current, a battery temperature, a specific gravity, a water level, a power, a ground, a charging communications port, and a harness ID. In additional system embodiments, the fleet data edge processor may be further configured to: convert the collected battery pack data to the common messaging data schema. In additional system embodiments, the fleet data edge processor may be further configured to: transmit, by the transceiver, the converted battery pack data. [0010] In additional system embodiments, the fleet data edge processor may be further configured to: analyze the one or more battery packs based on at least one of: an energy usage, an energy capacity, a battery technology, the battery temperature, the specific gravity, and the water level of the one or more battery packs based on the collected battery pack data. In additional system embodiments, the fleet data edge processor may be further configured to: determine a charge profile for the one or more battery packs based on the analyzed one or more battery packs, wherein the determined charge profile is an optimum charge cycle. In additional system embodiments, the fleet data edge processor may be further configured to: transmit, by the transceiver, the determined charge profile, where the determined charge profile may be configured to be downloaded to one or more chargers.

[0011] In additional system embodiments, the fleet data edge processor may be further configured to: determine an energy state of the one or more battery packs of the MHE based on the collected battery pack data; determine an energy capacity of the one or more battery packs of the MHE based on the collected battery pack data; and determine an energy utilization of the one or more battery packs of the MHE based on the collected battery pack data. In additional system embodiments, a battery pack of the one or more battery packs may be a lead-acid battery pack. In additional system embodiments, the ADC may include one or more eighteen-pin battery harness connectors.

[0012] A method embodiment may include: collecting, by an open ETSB accessory bus in communication with a fleet data edge processor having addressable memory, proprietary sensor data from one or more sensors, where the open ETSB accessory bus may be configured to connect to the one or more sensors; converting, by the processor, the collected sensor data to a common messaging data schema; and transmitting, by a transceiver in communication with the processor, the converted sensor data to the data management server.

[0013] Additional method embodiments may include: detecting, by the processor, a sensor of the one or more sensors connected to the fleet data edge; installing, by the processor, a ETSB driver for the detected sensor; and installing, by the processor, a data abstraction for the detected sensor, where the installed data abstraction may convert the collected sensor data to the common messaging data schema. Additional method embodiments may include: collecting, by a battery harness analog-to-digital converter (ADC) in communication with the processor, battery pack data on the one or more battery packs of a material handling equipment (MHE), where the battery pack data may include at least one of: a battery voltage, a mid-battery voltage, a battery current, a battery temperature, a specific gravity, a water level, a power, a ground, a charging communications port, and a harness ID, and where the ADC may be configured to connect to one or more battery packs of the MHE; converting, by the processor, the collected battery pack data to the common messaging data schema; and transmitting, by the processor, by the transceiver, the converted battery pack data. Additional method embodiments may include: collecting, by a battery harness analog-to-digital converter (ADC) in communication with the processor, battery pack data on the one or more battery packs of a material handling equipment (MHE), where the battery pack data may include at least one of: a battery voltage, a mid-battery voltage, a battery current, a battery temperature, a specific gravity, a water level, a power, a ground, a charging communications port, and a harness ID, and where the ADC may be configured to connect to one or more battery packs of the MHE; analyzing, by the processor, the one or more battery packs based on at least one of: an energy usage, an energy capacity, a battery technology, the battery temperature, the specific gravity, and the water level of the one or more battery packs based on the collected battery pack data; determining, by the processor, a charge profile for the one or more battery packs based on the analyzed one or more battery packs, where the determined charge profile may be an optimum charge cycle; and transmitting, by the transceiver, the determined charge profile, where the determined charge profile may be configured to be downloaded to one or more chargers.

[0014] Another system embodiment may include: a fleet data edge comprising: a processor having addressable memory; an open USB accessory bus in communication with the processor, the open USB accessory bus configured to connect to one or more sensors; a battery harness analog-to-digital converter (ADC) in communication with the processor, the ADC configured to connect to one or more battery packs of a material handling equipment (MHE); a transceiver in communication with the processor, the transceiver configured to wirelessly connect to a data management server; where the fleet data edge processor may be configured to: collect, by the open UAB accessory bus, proprietary sensor data from the one or more sensors; convert the collected sensor data to a common messaging data schema; collect, by the ADC, battery pack data on the one or more battery packs of the MHE, where the battery pack data may include at least one of: a battery voltage, a mid-battery voltage, a battery current, a battery temperature, a specific gravity, a water level, a power, a ground, a charging communications port, and a harness ID; and convert the collected battery pack data to a common messaging data schema; and transmit, by the transceiver, at least one of: the converted battery pack data and the converted sensor data to the data management server.

BRIEF DESCRIPTION OF THE DRAWINGS [0015] The various embodiments of the present ultrasonic audio for device setup now will be discussed in detail with an emphasis on highlighting the advantageous features. These embodiments depict the novel and non-obvious ultrasonic audio for device setup shown in the accompanying drawings, which are for illustrative purposes only. These drawings include the following figures, in which like numerals indicate like parts:

[0016] FIG. 1 is a conceptual illustration of a fleet data edge topology in accordance with an embodiment of the invention;

[0017] FIG. 2 is a high-level block diagram of a fleet data edge device in accordance with an embodiment of the invention;

[0018] FIG. 3 is a conceptual block diagram of a software architecture of a fleet data edge device in accordance with an embodiment of the invention;

[0019] FIG. 4 is a connectivity chart for a fleet data edge device in accordance with an embodiment of the invention;

[0020] FIG. 5 is a high-level system diagram of a fleet server edge system in accordance with an embodiment of the invention;

[0021] FIG. 6 is an illustration of a fleet data edge device output mapping in accordance with an embodiment of the invention;

[0022] FIG. 7 depicts a high-level flowchart of a method embodiment of a fleet data edge device process in accordance with an embodiment of the invention;

[0023] FIG. 8 illustrates an example top-level functional block diagram of a computing device embodiment;

[0024] FIG. 9 shows a high-level block diagram and process of a computing system for implementing an embodiment of the system and process;

[0025] FIG. 10 shows a block diagram and process of an exemplary system in which an embodiment may be implemented; and

[0026] FIG. 11 depicts a cloud-computing environment for implementing an embodiment of the system and process disclosed herein.

DETAILED DESCRIPTION

[0027] The following detailed description describes the present embodiments with reference to the drawings. In the drawings, reference numbers label elements of the present embodiments. These reference numbers are reproduced below in connection with the discussion of the corresponding drawing features. [0028] One of the big issues facing supply chain management is the cost, accuracy, and placement of warehouse sensors. Standardization of sensor data schemas is also problematic. Proprietary and unique sensor data schemas require extra hardware and software and are costly and impact future extensibility. In many embodiments of the disclosed system and method, an integrated edge sensor device solves many of the issues facing warehouse sensor integration. In a number of embodiments, a fleet data edge device can provide easy integration of warehouse sensors. A fleet data edge device can be installed on any material handling equipment (MHE) or ground support equipment (GSE), and allows for easy integration of a number of sensors. In a variety of embodiments, acquired data may be abstracted into a message format that allows easy integration to any third-party warehouse management software (WMS) package. The fleet data edge device may also include Wi-Fi and cellular data services that securely push data to a Fleet Management Edge Server. Such data can be saved and made available to third-party WMS packages. In this way, the fleet data edge system may provide for a better understanding and optimization of warehouse operations in a simple nitrated package.

[0029] With reference to FIG. 1, the present embodiments depict a fleet data edge topology in accordance with an embodiment of the invention. In a number of embodiments, the fleet data edge system 100 can be a small, self-contained high-performance computing, communications, and sensor data collection platform. In a variety of embodiments, the fleet data edge system 100 includes a series of data edge devices 110 that are each in communication with a series of sensors 115. In certain embodiments, the data edge devices 110 can be a complete data capture device designed to be installed on a vehicle or other device where data capture is desired. In further embodiments, the vehicle may be a piece of material handling equipment (MHE) or a piece of ground support equipment (GSE). In still further embodiments, the fleet data edge system 100 has a series of data edge devices 110 installed on forklifts 120 and/or other warehouse devices and/or chargers 125. In yet still further embodiments, the data edge device 110 may be installed on emerging technology warehouse robots that support a multitude of warehouse data sensors.

[0030] In additional embodiments, the data edge devices 110 communicate with a network including, but not limited to, the Internet 130. In still additional embodiments, this communication can include, but is not limited to, wirelessly via Wi-Fi 135, via Bluetooth, hard-wired via a hardware connection to another Internet-enabled device, and/or to another local edge device for later transmission. In yet additional embodiments, once the data has been transferred, it can then be transmitted to another Internet-enabled device via Wi-Fi 136, or to a cloud-based data management server 140. In more additional embodiments, the cloud- based data management server 140 can communicate with third-party applications 150 and/or a database 145. The database 145 may be stored internally on the cloud-based data management server 140 or externally on another server or through a third-party service. In still more additional embodiments, the cloud-based data management server 140 can be located on site with the data edge devices 110 or in the cloud at an external site.

[0031] While a variety of fleet data edge systems are described above with reference to FIG. 1, the specific configurations and communication channels of fleet data edge systems are largely dependent upon the requirements of specific applications. For example, it can be appreciated by those skilled in the art that an edge data device may utilize a number of methods to communicate with the network including transmitting signals on internal device busses or network streams. Additionally, the types of sensors 115 utilized by the data edge device 110 can be any suitable sensors that can transmit quantifiable and recordable data. A discussion of data edge device hardware architecture is below.

[0032] With reference to FIG. 2, the present embodiments depict a generalized hardware architecture of a fleet data edge device, in accordance with an embodiment of the invention. The data edge device hardware architecture 200 includes a CPU 210, which may be a processor having addressable memory. In many embodiments, the CPU 210 may be an integrated system on a chip (SoC). This may enable the data edge device to function as a small, very high-performance computing platform. In many additional embodiments, the CPU 210 SoC is an AM3358 SoC by Texas Instruments, Inc. of Dallas, TX. In many further embodiments, the SoC provides modules that support multiple processors as well as extensive hardware input and output (I/O) interface support. Utilizing a SoC platform allows for the support of multiple popular interfaces with very little incremental costs. In numerous embodiments, the data edge device architecture 200 includes a local storage option 220 as well as a RAM memory module 230. In a variety of embodiments, the CPU 210 may include an ARM 8 Cortex single core processor with 32K L1/256K L2 cache running at lGHz. In certain embodiments, the RAM memory module 230 may be an external memory module is supported through a DDR3 interface, enabling flexible memory options. In still more embodiments, the CPU 210 may include an integrated graphics controller. This graphics controller may be used to power an integration display through an HDMI interface. In certain additional embodiments, the HDMI interface can be exposed on the data edge unit.

[0033] In further embodiments, the CPU 210 may also have extensive peripheral management including, but not limited to, DMA controllers, timers, RTC, HRPWM, JTAG, and integrated security support. In still further embodiments, the CPU 210 may have a variety of I/O options including, but not limited to: UART, SDIO, SPI I 2 C, McASP, CAN, GPIO, EMAC, USB, and a multi-channel ADC. In still yet further embodiments, the I/O options may all have physical interface support to facilitate lowering of the cost of the EO port integration.

[0034] In additional embodiments, data edge hardware architecture 200 may include a specialized wireless transceiver 280 to facilitate wireless communication to a network or other device. In certain additional embodiments, the wireless transceiver 280 may be a WiLink module combination Wi-Fi 802.11 and Bluetooth transceiver by Texas Instruments, Inc. of Dallas, TX. In still yet additional embodiments, the transceiver may support 2.4 GHz Wi-Fi 802.11 a/b/n/g, Bluetooth 4.1, high performance TCP/UDP, TLS Security, as well as multiple-input, multiple-output (MIMO) antennas 290. The transceiver 280 may be utilized to connect to the Internet and exchange data with the Fleet Management System. In still additional embodiments, the Bluetooth communication may be used for maintenance and setup. In still yet additional embodiments, the data edge hardware architecture 200 may include at least two MIMO antennas 290.

[0035] In numerous embodiments, the CPU 210 may include four external, powered USB 2.0 ports 250, a controller area network (CAN) port 270, a programmable logic controller (PLC) bus 260, and a battery harness analog-to-digital converter (ADC) 240. In many additional embodiments, a key feature of the disclosed system and method is an open USB accessory bus 250 that can enable easy integration of a multitude of sensors that utilize USB for communication. Sensor systems utilized in edge networks may have a multitude of varying and/or proprietary data formats, which can make it difficult to process. In further additional embodiments, proprietary sensor data may be converted to a common messaging data schema, which may enable easy third-party software integration during later processing. In yet more additional embodiments, the edge data collected and processed by the CPU 210 may be pushed to an application server through an integrated Wi-Fi or cellular communication system. In yet further embodiments, the cellular communication may be accomplished through an external device in communication with the data edge device through a USB connection. In still yet additional embodiments, the data edge hardware architecture may provide for an energy management reporting solution to provide fleet energy status data that may significantly extend the useful life of the system and/or vehicle battery pack. [0036] While a variety of fleet data edge hardware architectures are described above with reference to FIG. 2, the specific configurations and component make-up of fleet data edge hardware architectures are largely dependent upon the requirements of specific applications. For example, a module system may allow for the inclusion of a new module that adds functionality or expands the capable inputs. Additionally, transceiver 280 may be upgraded via software or by the removal and replacement of the transceiver 280 to upgrade the wireless standards and capabilities that the fleet data edge device may contain. A discussion of data edge device software architecture is below.

[0037] With reference to FIG. 3, the present embodiments depict a generalized software architecture of a fleet data edge device, in accordance with an embodiment of the invention. In many embodiments, the data edge device software architecture 300 is based upon an embedded Linux operating system. In many additional embodiments, the use of Linux, and especially Debian may provide significant advantages including, but not limited to, preemptive execution, active memory management, and support for multiple programming languages, extensive platform utilities, extensive development tools, TCIP/IP support, HTTP/HTTPS support, extensive driver libraries, and additional security features. In many further embodiments, the security features may include encryption such as SHA, and TLS. In many embodiments, the libraries included may contain USB, UART, I2C, and EMAC. In further embodiments, a Linux operating system may provide an environment that enables feature-rich applications that can be very fast to code by utilizing existing libraries that have been well tested.

[0038] In additional embodiments, the data edge device software architecture 300 includes an application server 310 that can support container-based architecture. Container-based applications and services can isolate and enable modular coding to develop. In numerous additional embodiments, container-based applications can more easily isolate errors and significantly reduce propagation into other services. In a variety of embodiments, container- based applications can be faster to program, especially in multi-programmer/multi-tester development environments. In still additional embodiments, the software architecture can support multiple vehicle warehouse sensors added as accessories via the USB interface. In yet still additional embodiments, when a first supported sensor is plugged into the fleet data edge device, a first USB driver 316, a first data abstraction 314, and a first sensor device manager 315 may be installed. In additional embodiments, as data is collected, the collected data may be automatically pushed to a fleet management edge server. In additional embodiments, a first data abstraction 314 can convert the sensor data to a standard data schema. In this way, no matter what vendor sensors are utilized, third-party software can access the sensor data in a common format. In yet still more additional embodiments, the sensor data is made accessible via a third-party API on the fleet edge server. In this way, third-party software developers may only need to create one common interface and have uniform access to critical warehouse data. Likewise, in further embodiments, a second sensor device may be connected to the fleet data edge device, which may then create a second instance of a USB driver 319, a second device manager instance 318, and second data abstraction instance 317. It should be appreciated by those skilled in the art that any number of instances can be created based upon the specific needs of the application and/or the amount of available computational resources.

[0039] Warehouse data can be considered highly valuable and in most cases is a proprietary corporate secret. For example, an intruder acquiring information about a single SKU is not that important, but acquiring all SKU data over time can give competitive insight to company financial performance and velocity of supply chain operations. In still further embodiments, the fleet data edge device software architecture 300 utilizes encryption technology including, but not limited to, HTTPS/TLS 320 along with Secure Temporal Tokens (STT) 330. TLS utilizes the server’s digital certificates to exchange secure session keys. In certain embodiments, the session keys could be a data edge secret key 340 and/or a QR Code secret key 350. In yet further embodiments, each time the data edge device establishes a connection to the Fleet Edge Server, a new set of encryptions keys are created and exchanged between the data edge device and the Fleet Edge Server, providing necessary secrecy. In still yet further embodiments, an STT 330 is generated by the data edge device and sent as part of the HTTPS header. In additional embodiments, the STT 330 may be decrypted by the Fleet Edge Server where it validates the authenticity of the device and its security access authorization. In this way, secrecy, authentication, and authorization may be provided.

[0040] In a number of embodiments, battery analytics 311 may be included in the data edge device software architecture 300 and provided through the analog capture 313 device through a third instantiated device manager 312. Lead-acid batteries can often have a very complex charge-discharge cycle. Utilizing incorrect charging cycles may limit the battery to just 350 charge cycles before replacement is required. In a variety of embodiments, battery analytics 311 may be able to facilitate the achieving of 2,500 charge cycles. In numerous embodiments, battery analytics 311 may include, but are not limited to, analyzing energy usage, energy capacity, battery technology, temperature, specific gravity, and/or water level. In further embodiments, the utilization of battery analytics can help determine the optimum charge cycle. In still more further embodiments, this data can be converted and downloaded to chargers such as, but not limited to, Pro-Core chargers through the Wi-Fi interface or the integrated power line communications (PLC) bus.

[0041] In still yet more embodiments, the fleet data edge device can work with or without a wireless connection. By way of example, and not limitation, when the data edge device is connected via either Wi-Fi or cellular network, it can collect extensive battery analytics. In certain embodiments, analytics software running on the Fleet Edge Server may analyze energy utilization profiles, energy states, battery energy capacities, and historic charge profiles. In many embodiments, this software on the Fleet Edge Server can determine the optimal charge profiles.

[0042] While a variety of fleet data edge software architectures are described above with reference to FIG. 3, the specific configurations and component make-up of fleet data edge software architectures are largely dependent upon the requirements of specific applications. For example, new methods of measuring sensor data may require for the development of new types of software and interfaces for the data edge device. Additionally, new and/or more secure methods of data encryption may become available and be added into the data transmission protocols of the data edge device. A discussion of data edge device connectivity is below.

[0043] With reference to FIG. 4, the present embodiments depict a connectivity chart for a fleet data edge device, in accordance with an embodiment of the invention. The connectivity chart 400 comprises a fleet data edge device 410 that has a plurality of input and/or output options. In many embodiments, the fleet data edge device 410 can be a small rectangular package that is rated NEMA 4X, and contains six NEMA 4X rated circular plastic connectors (CPC) and a single LED. In some embodiments, one or more CPC may be used. In various embodiments, the first connector comprises a battery bus 412 that may be an 18-pin CPC battery harness connector. In some embodiments, one or more battery harness connectors may be used. Such a connector may support a variety of analog battery sensors 420 including, but not limited to, battery voltage, mid-battery voltage, battery current, battery temperature, specific gravity, water level, power, ground, charging communications port, and/or a harness ID. In additional embodiments, the connector can support multiple harnesses for different battery pack configurations. Each harness can be identified by a unique harness ID pinout arrangement. [0044] In further embodiments, the fleet data edge device 410 also includes a CAN bus 414 through a 4-pin CPC connector. In further additional embodiments, the connector can connect to an MHE vehicle 430. In still further embodiments, the connector can be a non standard connector on one end and a standard CAN connector on the other end. In yet further embodiments, the CAN bus interface extracts vehicle status data, trouble codes and/or battery charge status data. In still yet further embodiments, this data can be pushed to the Fleet Edge Server and may be exposed to the third-party software API interface.

[0045] In still additional embodiments, the fleet data edge device 410 can also include a series of 4-pin CPC connectors for a USB accessory bus 416. In many additional embodiments, any of a series of sensors 440 may connect to the fleet data edge device 410 through the USB Accessory Bus 416. In certain embodiments, the 4-pin connectors are not part of the USB standard. In many cases, this is because standard USB connectors could not pass shock, vibration, and the harsh environment the fleet data edge devices 410 are constantly exposed to. In additional further embodiments, the ports may be configured as USB slaves and provide a maximum of 40W (8 A @ 5V) of accessory power combined between all four ports.

[0046] In a number of embodiments, the base features of the fleet data edge device 410 can include 802.11 b/g/n, MHE battery energy management, pro core PLC bus, CAN bus, and a USB accessory bus. In a variety of additional embodiments, all other functions beyond standard features are extended through the USB accessory bus, including the addition of additional USB ports. Further accessories may include, but are not limited to, bar code scanners, RFID scanners, precision locators, GPS yard locators, employee card swipe readers, bump detectors, load/tilt sensors, displays, keyboards, energy gauges, cellular interfaces, and/or three-axis accelerometers.

[0047] With reference to FIG. 5, the present embodiments depict a high-level block diagram of a fleet management edge warehouse management system architecture, in accordance with an embodiment of the invention. In a number of embodiments, the current invention gathers and manages warehouse data and MHE fleet status. In certain embodiments, the disclosed system is called Fleet Management Edge (FME), and integrates cutting edge cloud services, Industrial Internet of Things (IloT) technology and advanced fleet energy analytics, allowing for centralized data gathering, fleet vehicle status and for easy access data portals for 3 party warehouse management software.

[0048] In a variety of embodiments, the disclosed system may centralize the capture of data right at a very crucial point - the Materials Handling Equipment (MHE). In additional embodiments, a wireless edge hardware device can be installed on the MHE which may directly capture inventory and other data at the source, then publishing this information to a centralized cloud-based server. In further embodiments, the wireless edge hardware can utilize a versatile USB accessory bus to connect to a number of warehouse sensors. In still additional embodiments, the wireless edge hardware device can abstract and consolidate the sensor information collected into a common data schema. Thus, in certain embodiments, the warehouse management software can subscribe to a common interface to retrieve data of interest.

[0049] In numerous embodiments, the current invention can help to consolidate many aspects of a warehouse’s inventory and fleet vehicle data. By way of example and not limitation, as inventory is removed from delivery trucks, the pallet can be immediately bar code scanned and weighed. Furthermore, a display driven by warehouse management software can direct the operator where to move the pallet. Precision location horizontal and vertical sensors can record the precise location of the pallet and assure that the inventory may be found even if placed in the wrong location. In still many embodiments, warehouse management software subscribes to such data and can orchestrate warehouse operations.

[0050] In still additional embodiments, the warehouse management system 200 may constantly monitor the energy and health status of the fleet as well, helping warehouse management software determine the most optimal charging regime based on warehouse workload and shift schedules. In still yet additional embodiments, the warehouse management system 200 can also monitor the fleet vehicles’ Controller Area Network (CAN) bus to interrogate fault codes and determine the best service solutions.

[0051] In many embodiments, the warehouse management system consists of six key components: business edge, database edge, data edge, energy edge, charger edge, and analytics edge. In still many embodiments, each component is autonomous and provides extensive flexibility and scalability. In further embodiments, the platform is cloud-based so that as customer demand increases; it can scale in performance and capacity. In still further embodiments, the underlying architecture is micro-service based enabling easy modifications without impacting other functions.

[0052] In a variety of embodiments, the Fleet Business Edge application server 510 is the brains of the fleet management edge solution and operates numerous edge applications. In still more embodiments, the business edge application server 510 manages each of the edge resources applications, resource scaling, intra and extra application communications and security. In certain embodiments, the business edge application server 510 also monitors the health of each service and automatically restarts a failed application. In further embodiments, the business edge application server 510 provides common API portals so various functions can access, store, or provide information about specific tasks. Web portals can be made available for users to access data and evaluate MHE status. In yet further embodiments, an administrator web portal 550 is provided for data administrators to monitor and maintain the Fleet Management Service, and is protected by user ID/password access. In a variety of embodiments, data stored in the database may also be encrypted and data access can be only allowed through secure encrypted temporal tokens.

[0053] In a number of embodiments, the database edge can save all data acquired by the data edge device 520 including, but not limited to, battery energy data, charging data, information from the edge sensors, as well as location information. In still more embodiments, the data is pushed from the data edge to the server and can all be saved in the customer database 530. In certain embodiments, the database technology can be a NoSQL relational database such as Mongo by MongoDB, Inc. of New York City, New York. In even more embodiments, all information may be stored in a customer unique database in a relational schema, and all of the application services have access to the database. In still even more embodiments, third-party warehouse management software can access the data through an Analytics Edge API.

[0054] In various embodiments, the database edge is a tenant-based design pattern architecture, or in other words, just one copy of the code can run on the server but several customers, or tenants, utilize the services in parallel. However, in most embodiments, all customer data is completely separate and is not intermixed. Furthermore, in still more embodiments, each customer can have their own database instance that is protected by a secure encryption system such as, but not limited to, AES256 encrypted tokens so no one other than the customer can view their data.

[0055] In further embodiments, the energy edge application is a set of analytic tools that run in the cloud and automatically help determine optimal charging solutions for the warehouse fleet. Many MHE’s use Lead- Acid battery packs, which can require a complex charging cycle to achieve optimal energy storage and battery lifetime. Often, advanced charging methods easily increase the longevity of the battery pack by a factor of three to four times. MHE battery packs are expensive so the disclosed data edge application can provide a good warehouse operations return on investment (ROI) decision.

[0056] In a variety of embodiments, the energy edge application can use energy data from the data edge application and work with pro core edge enabled charger 540. In still further embodiments, the energy edge application provides the analytics to determine a more optimized charge profile and loads the profile into the pro core edge charger 540. In yet still further embodiments, the energy edge application can also provide analytics to determine fleet energy requirements, energy profiles, and/or projected battery life.

[0057] In additional embodiments, the charger edge application is part of a product line of battery chargers from the Pro Core family developed by Webasto Charging Systems, Inc. of Monrovia, California. In more additional embodiments, the charger edge application can charge a variety of battery technologies including the common Lead- Acid families as well as Lithium-Ion batteries. In even more additional embodiments, the data edge application can send energy state and charge profiles to the energy edge application. In many additional embodiments, the energy edge application can determine a more efficient charge profile for the specific MHE. In yet more additional embodiments, the charge profile can be wirelessly sent to the charger edge application and it begins charging the MHE when plugged into the Pro Core Edge Charger 540.

[0058] In a number of embodiments, the analytics edge application provides a convenient, open API interface for all third-party Warehouse Software Management (WMS) tools 565. In many more embodiments, energy data, sensor data, and MHE vehicle status can be wirelessly sent to the database edge application where it is stored on the fleet management database (DB) 530. In still more embodiments, the analytics edge application provides an easy API access point to access this data. In yet further embodiments, an administrator web portal 550 is provided for data administrators to monitor and maintain the Fleet Management Service, and is protected by user ID/password access. In still more embodiments, a series of analytic screens 555 may be provided to a user including, but not limited to, administrator dashboard analytics screen and real-time energy analytics screen. In yet more embodiments, the edge server may provide an edge customer portal 560 that can include, but is not limited to, a customer dashboard. In certain embodiments, the information can be time-series stamped so applications always know the age of the data and can evaluate events or patterns over time. In this way, numerous embodiments, of the fleet analytics edge application can dramatically improve the ability for warehouses to gather data of its operations and better manage its fleet and warehouse operations.

[0059] With reference to FIG. 6, the present embodiments depict an illustration of a fleet data edge device output mapping 600, in accordance with an embodiment of the invention. In many embodiments the fleet edge output mapping may be printed on a fleet data edge device label 610 that can be applied to a fleet edge device. In certain embodiments, the mapping printed on the label can correspond to the output ports on the fleet data edge device.

[0060] FIG. 7 depicts a high-level flowchart of a method embodiment 700 of a fleet data edge device process in accordance with an embodiment of the invention. The method 700 may include collecting, by an open USB accessory bus in communication with a fleet data edge processor having addressable memory, proprietary sensor data from one or more sensors (step 702). The open USB accessory bus may be configured to connect to the one or more sensors. The method 700 may then include converting, by the processor, the collected sensor data to a common messaging data schema (step 704). The method 700 may then include collecting, by a battery harness analog-to-digital converter (ADC) in communication with the processor, battery pack data on the one or more battery packs of a material handling equipment (MHE) (step 706). The battery pack data may include a battery voltage, a mid- battery voltage, a battery current, a battery temperature, a specific gravity, a water level, a power, a ground, a charging communications port, and/or a harness ID. The ADC may be configured to connect to one or more battery packs of the MHE. The method 700 may then include converting, by the processor, the collected battery pack data to the common messaging data schema (step 708). The method 700 may then include transmitting, via a transceiver in communication with the processor, the converted sensor data and/or the converted battery pack data (step 710). The transceiver may be configured to wirelessly connect to a data management server via WiFi, a cellular Internet connection, or the like.

[0061] In some embodiments, the method 700 may include analyzing the battery pack data (step 712). The one or more battery packs may be analyzed based on an energy usage, an energy capacity, a battery technology, the battery temperature, the specific gravity, and/or the water level of the one or more battery packs based on the collected battery pack data. The method 700 may then include determining a charge profile based on the analyzed battery pack data (step 714). The determined charge profile may be an optimum charge cycle. The method 700 may then include transmitting the charge profile to one or more chargers (step 716). When each MHE is connected to the charger, the MHE may follow the determined charge profile to maximize the lifetime of the one or more battery packs of the MHE.

[0062] FIG. 8 illustrates an example of a top-level functional block diagram of a computing device embodiment 800. The example operating environment is shown as a computing device 820 comprising a processor 824, such as a central processing unit (CPU), addressable memory 827, an external device interface 826, e.g., an optional universal serial bus port and related processing, and/or an Ethernet port and related processing, and an optional user interface 829, e.g., an array of status lights and one or more toggle switches, and/or a display, and/or a keyboard and/or a pointer-mouse system and/or a touch screen. Optionally, the addressable memory may, for example, be: flash memory, eprom, and/or a disk drive or other hard drive. These elements may be in communication with one another via a data bus 828. In some embodiments, via an operating system 825 such as one supporting a web browser 823 and applications 822, the processor 824 may be configured to execute steps of a process establishing a communication channel and processing according to the embodiments described above.

[0063] System embodiments include computing devices such as a server computing device, a buyer computing device, and a seller computing device, each comprising a processor and addressable memory and in electronic communication with each other. The embodiments provide a server computing device that may be configured to: register one or more buyer computing devices and associate each buyer computing device with a buyer profile; register one or more seller computing devices and associate each seller computing device with a seller profile; determine search results of one or more registered buyer computing devices matching one or more buyer criteria via a seller search component. The service computing device may then transmit a message from the registered seller computing device to a registered buyer computing device from the determined search results and provide access to the registered buyer computing device of a property from the one or more properties of the registered seller via a remote access component based on the transmitted message and the associated buyer computing device; and track movement of the registered buyer computing device in the accessed property via a viewer tracking component. Accordingly, the system may facilitate the tracking of buyers by the system and sellers once they are on the property and aid in the seller’s search for finding buyers for their property. The figures described below provide more details about the implementation of the devices and how they may interact with each other using the disclosed technology.

[0064] FIG. 9 is a high-level block diagram 900 showing a computing system comprising a computer system useful for implementing an embodiment of the system and process, disclosed herein. Embodiments of the system may be implemented in different computing environments. The computer system includes one or more processors 902, and can further include an electronic display device 904 (e.g., for displaying graphics, text, and other data), a main memory 906 (e.g., random access memory (RAM)), storage device 908, a removable storage device 910 (e.g., removable storage drive, a removable memory module, a magnetic tape drive, an optical disk drive, a computer readable medium having stored therein computer software and/or data), user interface device 911 (e.g., keyboard, touch screen, keypad, pointing device), and a communication interface 912 (e.g., modem, a network interface (such as an Ethernet card), a communications port, or a PCMCIA slot and card). The communication interface 912 allows software and data to be transferred between the computer system and external devices. The system further includes a communications infrastructure 914 (e.g., a communications bus, cross-over bar, or network) to which the aforementioned devices/modules are connected as shown.

[0065] Information transferred via communications interface 914 may be in the form of signals such as electronic, electromagnetic, optical, or other signals capable of being received by communications interface 914, via a communication link 916 that carries signals and may be implemented using wire or cable, fiber optics, a phone line, a cellular/mobile phone link, an radio frequency (RF) link, and/or other communication channels. Computer program instructions representing the block diagram and/or flowcharts herein may be loaded onto a computer, programmable data processing apparatus, or processing devices to cause a series of operations performed thereon to produce a computer implemented process.

[0066] Embodiments have been described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments. Each block of such illustrations/diagrams, or combinations thereof, can be implemented by computer program instructions. The computer program instructions when provided to a processor produce a machine, such that the instructions, which execute via the processor, create means for implementing the functions/operations specified in the flowchart and/or block diagram. Each block in the flowchart/block diagrams may represent a hardware and/or software module or logic, implementing embodiments. In alternative implementations, the functions noted in the blocks may occur out of the order noted in the figures, concurrently, etc.

[0067] Computer programs (i.e., computer control logic) are stored in main memory and/or secondary memory. Computer programs may also be received via a communications interface 912. Such computer programs, when executed, enable the computer system to perform the features of the embodiments as discussed herein. In particular, the computer programs, when executed, enable the processor and/or multi-core processor to perform the features of the computer system. Such computer programs represent controllers of the computer system.

[0068] FIG. 10 shows a block diagram of an example system 1000 in which an embodiment may be implemented. The system 1000 includes one or more client devices 1001 such as consumer electronics devices, connected to one or more server computing systems 1030. A server 1030 includes a bus 1002 or other communication mechanism for communicating information, and a processor (CPU) 1004 coupled with the bus 1002 for processing information. The server 1030 also includes a main memory 1006, such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 1002 for storing information and instructions to be executed by the processor 1004. The main memory 1006 also may be used for storing temporary variables or other intermediate information during execution or instructions to be executed by the processor 1004. The server computer system 1030 further includes a read only memory (ROM) 1008 or other static storage device coupled to the bus 1002 for storing static information and instructions for the processor 1004. A storage device 1010, such as a magnetic disk or optical disk, is provided and coupled to the bus 1002 for storing information and instructions. The bus 1002 may contain, for example, thirty -two address lines for addressing video memory or main memory 1006. The bus 1002 can also include, for example, a 32-bit data bus for transferring data between and among the components, such as the CPU 1004, the main memory 1006, video memory and the storage 1010. Alternatively, multiplex data/address lines may be used instead of separate data and address lines.

[0069] The server 1030 may be coupled via the bus 1002 to a display 1012 for displaying information to a computer user. An input device 1014, including alphanumeric and other keys, is coupled to the bus 1002 for communicating information and command selections to the processor 1004. Another type or user input device comprises cursor control 1016, such as a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to the processor 1004 and for controlling cursor movement on the display 1012.

[0070] According to one embodiment, the functions are performed by the processor 1004 executing one or more sequences of one or more instructions contained in the main memory 1006. Such instructions may be read into the main memory 1006 from another computer- readable medium, such as the storage device 1010. Execution of the sequences of instructions contained in the main memory 1006 causes the processor 1004 to perform the process steps described herein. One or more processors in a multi-processing arrangement may also be employed to execute the sequences of instructions contained in the main memory 1006. In alternative embodiments, hard-wired circuitry may be used in place of or in combination with software instructions to implement the embodiments. Thus, embodiments are not limited to any specific combination of hardware circuitry and software. [0071] The terms "computer program medium," "computer usable medium," "computer readable medium", and "computer program product," are used to generally refer to media such as main memory, secondary memory, removable storage drive, a hard disk installed in hard disk drive, and signals. These computer program products are means for providing software to the computer system. The computer readable medium allows the computer system to read data, instructions, messages or message packets, and other computer readable information from the computer readable medium. The computer readable medium, for example, may include non-volatile memory, such as a floppy disk, ROM, flash memory, disk drive memory, a CD-ROM, and other permanent storage. It is useful, for example, for transporting information, such as data and computer instructions, between computer systems. Furthermore, the computer readable medium may comprise computer readable information in a transitory state medium such as a network link and/or a network interface, including a wired network or a wireless network that allow a computer to read such computer readable information. Computer programs (also called computer control logic) are stored in main memory and/or secondary memory. Computer programs may also be received via a communications interface. Such computer programs, when executed, enable the computer system to perform the features of the embodiments as discussed herein. In particular, the computer programs, when executed, enable the processor multi-core processor to perform the features of the computer system. Accordingly, such computer programs represent controllers of the computer system.

[0072] Generally, the term "computer-readable medium" as used herein refers to any medium that participated in providing instructions to the processor 1004 for execution. Such a medium may take many forms, including but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media includes, for example, optical or magnetic disks, such as the storage device 1010. Volatile media includes dynamic memory, such as the main memory 1006. Transmission media includes coaxial cables, copper wire and fiber optics, including the wires that comprise the bus 1002. Transmission media can also take the form of acoustic or light waves, such as those generated during radio wave and infrared data communications.

[0073] Common forms of computer-readable media include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, a CD-ROM, any other optical medium, punch cards, paper tape, any other physical medium with patterns of holes, a RAM, a PROM, an EPROM, a FLASH-EPROM, any other memory chip or cartridge, a carrier wave as described hereinafter, or any other medium from which a computer can read. [0074] Various forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to the processor 1004 for execution. For example, the instructions may initially be carried on a magnetic disk of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to the server 1030 can receive the data on the telephone line and use an infrared transmitter to convert the data to an infrared signal. An infrared detector coupled to the bus 1002 can receive the data carried in the infrared signal and place the data on the bus 1002. The bus 1002 carries the data to the main memory 1006, from which the processor 1004 retrieves and executes the instructions. The instructions received from the main memory 1006 may optionally be stored on the storage device 1010 either before or after execution by the processor 1004.

[0075] The server 1030 also includes a communication interface 1018 coupled to the bus 1002. The communication interface 1018 provides a two-way data communication coupling to a network link 1020 that is connected to the worldwide packet data communication network now commonly referred to as the Internet 1028. The Internet 1028 uses electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on the network link 1020 and through the communication interface 1018, which carry the digital data to and from the server 1030, are exemplary forms or carrier waves transporting the information.

[0076] In another embodiment of the server 1030, interface 1018 is connected to a network 1022 via a communication link 1020. For example, the communication interface 1018 may be an integrated services digital network (ISDN) card or a modem to provide a data communication connection to a corresponding type of telephone line, which can comprise part of the network link 1020. As another example, the communication interface 1018 may be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links may also be implemented. In any such implementation, the communication interface 1018 sends and receives electrical electromagnetic or optical signals that carry digital data streams representing various types of information.

[0077] The network link 1020 typically provides data communication through one or more networks to other data devices. For example, the network link 1020 may provide a connection through the local network 1022 to a host computer 1024 or to data equipment operated by an Internet Service Provider (ISP). The ISP in turn provides data communication services through the Internet 1028. The local network 1022 and the Internet 1028 both use electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on the network link 1020 and through the communication interface 1018, which carry the digital data to and from the server 1030, are exemplary forms or carrier waves transporting the information.

[0078] The server 1030 can send/receive messages and data, including e-mail, program code, through the network, the network link 1020 and the communication interface 1018. Further, the communication interface 1018 can comprise a USB/Tuner and the network link 1020 may be an antenna or cable for connecting the server 1030 to a cable provider, satellite provider or other terrestrial transmission system for receiving messages, data and program code from another source.

[0079] The example versions of the embodiments described herein may be implemented as logical operations in a distributed processing system such as the system 1000 including the servers 1030. The logical operations of the embodiments may be implemented as a sequence of steps executing in the server 1030, and as interconnected machine modules within the system 1000. The implementation is a matter of choice and can depend on performance of the system 1000 implementing the embodiments. As such, the logical operations constituting said example versions of the embodiments are referred to for e.g., as operations, steps or modules.

[0080] Similar to a server 1030 described above, a client device 1001 can include a processor, memory, storage device, display, input device and communication interface (e.g., e-mail interface) for connecting the client device to the Internet 1028, the ISP, or LAN 1022, for communication with the servers 1030.

[0081] The system 1000 can further include computers (e.g., personal computers, computing nodes) 1005 operating in the same manner as client devices 1001, where a user can utilize one or more computers 1005 to manage data in the server 1030.

[0082] Referring now to FIG. 11, illustrative cloud computing environment 50 is depicted. As shown, cloud computing environment 50 comprises one or more cloud computing nodes 10 with which local computing devices used by cloud consumers, such as, for example, personal digital assistant (PDA), smartphone, smart watch, set-top box, video game system, tablet, mobile computing device, or cellular telephone 54A, desktop computer 54B, laptop computer 54C, and/or automobile computer system 54N may communicate. Nodes 10 may communicate with one another. They may be grouped (not shown) physically or virtually, in one or more networks, such as Private, Community, Public, or Hybrid clouds as described hereinabove, or a combination thereof. This allows cloud-computing environment 50 to offer infrastructure, platforms and/or software as services for which a cloud consumer does not need to maintain resources on a local computing device. It is understood that the types of computing devices 54A-N shown in FIG. 11 are intended to be illustrative only and that computing nodes 10 and cloud computing environment 50 can communicate with any type of computerized device over any type of network and/or network addressable connection (e.g., using a web browser).

[0083] The above description presents the best mode contemplated for carrying out the present embodiments, and of the manner and process of practicing them, in such full, clear, concise, and exact terms as to enable any person skilled in the art to which they pertain to practice these embodiments. The present embodiments are, however, susceptible to modifications and alternate constructions from those discussed above that are fully equivalent. Consequently, the present invention is not limited to the particular embodiments disclosed. On the contrary, the present invention covers all modifications and alternate constructions coming within the spirit and scope of the present disclosure. For example, the steps in the processes described herein need not be performed in the same order as they have been presented, and may be performed in any order(s). Further, steps that have been presented as being performed separately may in alternative embodiments be performed concurrently. Likewise, steps that have been presented as being performed concurrently may in alternative embodiments be performed separately.