WO2019161293A1 - Methods and systems for managing warehouse information utilizing fleet vehicle data - Google Patents

Abstract

A system and method including: one or more sensors (110); a fleet data edge device (220) having a processor and addressable memory, the fleet data edge device in communication with the one or more sensors, the fleet data edge device processor configured to: collect data from one or more materials handling equipment (MHE) via the one or more sensors; and abstract the collected data to a common data schema; a business edge application server (210) having a processor and addressable memory, the business edge application server processor configured to: receive the abstracted data from the fleet data edge device; and monitor a status of the one or more MHE.

Description

METHODS AND SYSTEMS FOR MANAGING WAREHOUSE INFORMATION

UTILIZING FLEET VEHICLE DATA

CROSS-REFERENCE TO RELATED APPLICATION

[0001] This application claims the priority benefit of U.S. Provisional Patent Application Serial Number 62/631,444 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 warehouse information.

BACKGROUND

[0003] Today, supply chain management is an enormously complex operation. Some companies, like Walmart® of Bentonville, Arkansas or Costco® of Issaquah, Washington, view efficient supply chain management as a key competitive component in lowering costs and improving customer fulfillment and satisfaction. Traditional brick and mortar retailers constantly look to squeeze cost out of their warehouse operations. As an example, Walmart’ s® overall cost of distribution through its supply chain is 1.7% of product cost. This is in contrast to Kmart® of Hoffman Estates, Illinois at 3.5% and Sears at 5.0%. These cost savings flow directly to the bottom line. E-Retailers look at speed and accuracy of order fulfillment as a primary objective. Amazon® of Seattle, Washington uses over 500 metrics in its supply chain with over 80% of them focused on customer fulfillment. All of them strive to make sure their supply chain delivers exactly what is needed exactly when needed at the lowest cost.

[0004] One of the most important components of a supply chain is its warehouse operations. The capacity, velocity, accuracy, and efficiency of warehouse operations can dramatically impact the supply chain operations and company revenues. For companies like Amazon® or Staples® of Framingham, Massachusetts, warehouse operations are the most complex operations in the company and provide dramatic competitive advantages.

SUMMARY

[0005] The various embodiments of the present fleet edge data management system 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] In many embodiments, an integrated fleet vehicle data collection system includes a fleet vehicle device where the device collects data from fleet vehicles, abstracts the collected data and pushes the abstracted data to a cloud-based service, where a cloud-based application provides access to third-parties, and provides third-party software access to the abstracted data.

[0007] In additional embodiments, the cloud-based application further provides third- party warehouse management software to easily access data in a common message format.

[0008] In further embodiments, the cloud-based application further provides a common API interface for third-party warehouse management software to easily access the information.

[0009] In still additional embodiments, the abstracted data is stored in a tenant-based secure time-series database containing data captured by a wireless fleet data edge device.

[0010] In further still embodiments, the system collects individual energy data from material handling equipment and Ground Support Equipment, the data is then used to assess the energy state of the vehicle and determine the best opportunity to charge the truck.

[0011] A system embodiment may include: one or more sensors; a fleet data edge device having a processor and addressable memory, the fleet data edge device in communication with the one or more sensors, the fleet data edge device processor configured to: collect data from one or more materials handling equipment (MHE) via the one or more sensors; and abstract the collected data to a common data schema; a business edge application server having a processor and addressable memory, the business edge application server processor configured to: receive the abstracted data from the fleet data edge device; and monitor a status of the one or more MHE.

[0012] In additional system embodiments, the business edge application server may further include: a database edge module, where the database edge module may be configured to: store the received data from the fleet data edge device, where data from each customer is stored in a separate customer database. In additional system embodiments, the business edge application server may further include: an energy edge module, where the energy edge module is configured to: determine an optimal charge profile for a MHE of the one or more MHE based on the stored data from the database edge module. In additional system embodiments, the energy edge module may be further configured to: load the optimal charge profile for the MHE into a charger (240) for the MHE, where the MHE may be charged using the optimal charge profile when the MHE is plugged into the charger. In additional system embodiments, the energy edge module may be further configured to: determine an energy requirement for the one or more MHE based on the stored data from the database edge module. In additional system embodiments, the energy edge module may be further configured to: determine an energy profile for the one or more MHE based on the stored data from the database edge module. In additional system embodiments, the energy edge module may be further configured to: determine a projected battery life for the one or more MHE based on the stored data from the database edge module.

[0013] In additional system embodiments, the business edge application server may further include: an analytics edge module, where the analytics edge module may be configured to: provide access to the stored data in the database edge module. In additional system embodiments, the business edge application server may further include: a business edge module, where the business edge module may be configured to: monitor a health of at least one of: the database edge module, the energy edge module, and the analytics edge module. In additional system embodiments, the business edge module may be further configured to: provide access to the status of the one or more MHE via an edge administration portal. In additional system embodiments, the business edge module may be further configured to: provide access to a real-time energy analytics of the one or more MHE via the edge administration portal.

[0014] A method embodiment may include: collecting data, by a fleet data edge device having a processor and addressable memory, from one or more materials handling equipment (MHE) via one or more sensors; abstracting, by the fleet data edge device, the collected data to a common data schema; receiving, by a business edge application server having a processor and addressable memory, the abstracted data from the fleet data edge device; and monitoring, by the business edge application server, a status of the one or more MHE.

[0015] Additional method embodiments may include: storing, by a database edge module of the business edge application server, the received data from the fleet data edge device, where data from each customer may be stored in a separate customer database. Additional method embodiments may include: determining, by an energy edge module of the business edge application server, an optimal charge profile for a MHE of the one or more MHE based on the stored data from the database edge module. Additional method embodiments may include: loading, by the energy edge module, the optimal charge profile for the MHE into a charger for the MHE, where the MHE may be charged using the optimal charge profile when the MHE is plugged into the charger.

[0016] Additional method embodiments may include: determining, by the energy edge module, an energy requirement for the one or more MHE based on the stored data from the database edge module. Additional method embodiments may include: determining, by the energy edge module, an energy profile for the one or more MHE based on the stored data from the database edge module. Additional method embodiments may include: determining, by the energy edge module, a projected battery life for the one or more MHE based on the stored data from the database edge module.

[0017] Additional method embodiments may include: providing, by an analytics edge module of the business edge application server, access to the stored data in the database edge module. Additional method embodiments may include: monitoring, by a business edge module of the business edge application server, health of at least one of: the database edge module, the energy edge module, and the analytics edge module. Additional method embodiments may include: providing, by the business edge module, access to the status of the one or more MHE via an edge administration portal. Additional method embodiments may include: providing, by the business edge module, access to a real-time energy analytics of the one or more MHE via the edge administration portal.

[0018] Another method embodiment may include: receiving, by a business edge application server having a processor and addressable memory, abstracted data from one or more materials handling equipment (MHE) via one or more sensors; monitoring, by the business edge application server, an energy status of each MHE of the one or more MHE based on the received abstracted data; determining, by the business edge application server, an optimal charging profile for each MHE of the one or more MHE based on the monitored energy status; and sending, by the business edge application server, the optimal charging profile for each MHE to a charger, where each MHE may be configured to charge based on the sent optimal charging profile when each MHE is connected to the charger.

BRIEF DESCRIPTION OF THE DRAWINGS

[0019] 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:

[0020] FIG. 1 is a conceptual illustration of a general warehouse workflow in accordance with an embodiment of the invention;

[0021] FIG. 2 is a high-level block diagram of a fleet management edge warehouse management system architecture in accordance with an embodiment of the invention;

[0022] FIG. 3 is a conceptual illustration of a fleet data edge device and sensors in accordance with an embodiment of the invention;

[0023] FIG. 4 is a high-level diagram of a fleet management edge virtual private network (VPN) in accordance with an embodiment of the invention;

[0024] FIG. 5 is a high-level diagram of a fleet management security surface platform in accordance with an embodiment of the invention;

[0025] FIG. 6 depicts a high-level flowchart of a method embodiment of a data collection system in accordance with an embodiment of the invention;

[0026] FIG. 7 illustrates an example top-level functional block diagram of a computing device embodiment;

[0027] FIG. 8 shows a high-level block diagram and process of a computing system for implementing an embodiment of the system and process;

[0028] FIG. 9 shows a block diagram and process of an exemplary system in which an embodiment may be implemented; and

[0029] FIG. 10 depicts a cloud computing environment for implementing an embodiment of the system and process disclosed herein

DETAILED DESCRIPTION

[0030] 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.

[0031] A big challenge in supply chain management and in particular warehouse management is the integration of sensors, sensor data and multiple warehouse management system (WMS) applications. Warehouse management software is proprietary and few sensor standards exist. Often additional hardware and software are needed to convert or bridge data schemas required by the various WMS packages. Each warehouse becomes a unique integration effort between hardware sensors, data, and warehouse management software. These proprietary interfaces complicate and create added integration expense, time and costs. They also make it difficult to make future changes or modifications.

[0032] Warehouse capacity, velocity, and efficiency are becoming increasingly more important in supply chain management. Warehouse Big Data analytics are central to understanding warehouse metrics and driving improvements in both process and warehouse efficiency. One of the biggest issues is acquiring the data. Many embodiments of the disclosed system centralize and abstract the capture of this critical warehouse data. Through the use of cloud-based micro-services, 3rd party warehouse management software can easily access this data and integrate it into their applications. Additional embodiments may also employ fleet energy management services providing fleet warehouse managers better insight into the overall energy profile of their MHE.

[0033] The fleet management edge system, as enabled in various embodiments of the current application, can enable several new customer segments in addition to its traditional fleet charging and battery management segment. In various embodiments, the fleet management edge system may centralize warehouse data collection, vehicle-centric sensor hardware/software abstraction and management. In certain embodiments, sensors can be centralized as appliances and integrated into a fleet data edge device. In additional embodiments, all hardware sensors can be abstracted to facilitate third-party Warehouse Management Software (WMS) to see a common interface regardless of the manufacturer, model, or version. In further embodiments, the fleet management edge system may provide fleet energy analytics, which can include existing advanced battery charging profiles that may significantly extend the number of battery charging cycles available. Additional embodiments may also integrate specialized chargers and analytics software to better optimize charging cycles based on warehouse activity. In many embodiments, energy analytics applications integrated with third-party WMS can enable charging cycles that are more efficient for the dynamics of warehouse operations.

[0034] In still further embodiments, the fleet management edge system may provide a Software as a Service (SaaS) for data analytics access portals for third-party Warehouse Management Software (WMS). Common APIs may enable third-party Warehouse Management Software to access system information, vehicle location and status, as well as fleet status and capability.

[0035] Potential customer base categories would include the following: existing fleet battery management customers, battery manufacturers, material handling equipment (MHE) original equipment manufacturers (OEMs), and third-party warehouse manufacturing software developers. In still additional embodiments, the fleet management edge system may continue to support the existing customer at a lower cost but will provide additional value- added features such as fleet battery data analytics. In yet additional embodiments, lower cost fleet data edge devices can make this solution much more attractive to battery manufacturers who are trying to provide value-added services. In yet additional embodiments, standardized sensor hardware and software would be a real benefit for truck HME OEM’s. The fleet management edge system provider could become a one-stop supplier for warehouse sensor hardware, common software interface for Warehouse Management Software, wireless access to truck CAN bus data, and battery energy management. In many additional embodiments third-party Warehouse Manufacturing Software Developers may be provided an easy interface to access warehouse data via a common API that may allow hardware abstracted data access of vehicle status including, but not limited to, sensor data, vehicle status (vehicle CAN bus), vehicle position, safety information, authorized vehicle access and energy status.

[0036] With reference to FIG. 1, the present embodiments depict general warehouse workflow in accordance with an embodiment of the invention. Today’s modem warehouse generates an enormous amount of data. Many warehouse operations have turned to sophisticated data gathering sensors and Warehouse Management Software (WMS) to manage, track, and measure key warehouse operations. FIG. 1 depicts a typical integration of software, sensors, and material handling equipment. Sensors throughout the warehouse gather information about incoming inventory, movement, shelving/un-shelving, packing/unpacking, order fulfillment, and shipment. The data is used by WMS to orchestrate incoming SKU’s throughout the warehouse to its final order fulfillment and shipment.

[0037] A typical Walmart® regional distribution warehouse turns about one million items per day representing about a 100,000 SKU’s. That represents over five Terabytes of data captured per warehouse each day. Although not all of this data is retained, Walmart® uses this data to help with the complex operations to track and direct the movement of inventory throughout its warehouses and stores. Some examples of these WMS tools include, but are not limited to, enterprise resource planning, manufacturing resource planning, supply chain management, warehouse resource management, automated materials storage, transportation asset tracking, and/or yard stocking management. These tools not only run the operations but they also are used to derive metrics that measure and improve overall warehouse processes and efficiencies. These and other metrics are critical to the efficient and timely operation of a modern data-driven warehouse. [0038] In a number of embodiments, the general warehouse system 100 comprises a series of warehouse sensors 110. In many embodiments, these sensors may include, but are not limited to, barcode scanners, location tracking sensors, operator displays, impact, and/or load and tilt sensors. In a variety of embodiments, the warehouse sensors 110 are connected to a warehouse wireless LAN 120. The warehouse wireless LAN 120 may be connected to other warehouse automation machines 130. In further embodiments, a warehouse database (DB) 160 can connect to the warehouse wireless LAN 120. In additional embodiments, the Warehouse DB 160 can further be connected to a warehouse management software (WMS) system 170. In certain embodiments, the WMS system 170 may provide for warehouse reporting 175 generated from data contained in the Warehouse DB 160. Furthermore, in yet additional embodiments, warehouse analytics software 180 can also be connected to the warehouse DB 160 in order to provide real-time analytics 185. In a variety of embodiments, the general warehouse system 100 can provide a warehouse process flow 150 that begins with receiving, and may continue to include pallet storage, pallet separation, tray loading, automated tray loading, order picking, pallet stretch wrap, and/or shipping.

[0039] While a variety of general warehouse systems are described above with reference to FIG. 1, the specific configurations and process flows of general warehouse systems are largely dependent upon the requirements of specific applications. For example, it can be appreciated by those skilled in the art that the exact types of sensors, wireless connections, and components of the warehouse system can be adjusted based on the size, complexity, and/or analytic needs of the warehouse management. Additionally, the types of sensors 110 utilized can be any suitable sensors that can transmit quantifiable and recordable data. A discussion of fleet management edge architecture is below.

[0040] With reference to FIG. 2, the present embodiment depicts a high-level block diagram of fleet management edge warehouse management system architecture, in accordance with an embodiment of the invention. In a number of embodiments, the disclosed system 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 easy access data portals for 3 party warehouse management software.

[0041] 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 220 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 220 can utilize a versatile USB accessory bus to connect to a number of warehouse sensors. In still additional embodiments, the wireless edge hardware device 220 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.

[0042] In numerous embodiments, the disclosed system 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.

[0043] 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.

[0044] In many embodiments, the warehouse management system includes six key components: a business edge server 210 having a processor with addressable memory, a database edge module 215, a data edge module 213, an energy edge module 211, a charger edge module 214, and an analytics edge module 212. In still many embodiments, each component may be autonomous and provide extensive flexibility and scalability. In further embodiments, the platform may be cloud-based so that as customer demand increases; it can scale in performance and capacity. In still further embodiments, the underlying architecture may be micro-service based thereby enabling easy modifications without impacting other functions.

[0045] In a variety of embodiments, the Fleet Business Edge application server 210 is the brains of the Fleet Management Edge solution and operates numerous edge modules. In still more embodiments, the business edge application server 210 manages each of the edge resources modules, resource scaling, intra and extra application communications and security. In certain embodiments, the business edge application server 210 also monitors the health of each service and automatically restarts a failed module. In further embodiments, the business edge application server 210 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 250 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 255 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 210 may provide an edge customer portal 260 that can include, but is not limited to, a customer dashboard 261. 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.

[0046] In a number of embodiments, the database edge module 215 can save all data acquired by the data edge device 220 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 device 220 to the server 210 and can all be saved in the customer database 230. 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 230. In still even more embodiments, third-party warehouse management software 265 can access the data through an Analytics Edge API.

[0047] In various embodiments, the database edge module 215 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.

[0048] In further embodiments, the energy edge module 211 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 data edge application can make a good warehouse operations return on investment (ROI) decision.

[0049] In a variety of embodiments, the energy edge module 211 can use energy data from the data edge application and work with a charger 240 such as a pro core edge enabled charger. In still further embodiments, the energy edge module 211 provides the analytics to determine a more optimized charge profile and loads the profile into the pro core edge charger 240. In yet still further embodiments, the energy edge module 211 can also provide analytics to determine fleet energy requirements, energy profiles, and/or projected battery life.

[0050] In additional embodiments, the charger edge module 214 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 module 214 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 module 213 can send energy state and charge profiles to the energy edge module 211. In many additional embodiments, the energy edge module 211 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 module 214 and it begins charging the MHE when plugged into the Pro Core Edge Charger 240.

[0051] In a number of embodiments, the analytics edge module 212 provides a convenient, open API interface for all third-party Warehouse Software Management (WMS) tools 265. In many more embodiments, energy data, sensor data, and MHE vehicle status can be wirelessly sent to the database edge module 215 where it is stored on the fleet management database (DB) 230. In still more embodiments, the analytics edge module 212 provides an easy API access point to access this data. 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 module 212 can dramatically improve the ability for warehouses to gather data of their operations and better manage their fleet and warehouse operations.

[0052] With reference to FIG. 3, the present embodiment depicts a conceptual illustration of a fleet data edge device and sensors 300, in accordance with an embodiment of the invention. In many embodiments, the fleet data edge 310 is a device for gathering warehouse data and managing warehouse MHE. In a variety of embodiments, the data edge device 310 retains the previous solution’s advanced charging and energy management features. However, in accordance with a variety of embodiments, the fleet data edge device 310 can also include the ability to connect multiple warehouse sensors such as, but not limited to, operator displays 320, telematics sensors 330, impact sensors 340, energy management sensors 350, location sensors 360, employee badge readers 370, barcode scanners 380, ultra- accurate position sensors, and/or operator displays. It centralizes the capture of the data where it is most convenient to capture - right at the MHE point.

[0053] In additional embodiments, the data edge device 310 may contain a high- performance ARM 8 processor running embedded Linux. In still additional embodiments, the data edge device 310 can have multiple ports for connecting to a number of external devices. By way of example and not limitation, the battery harness bus can connect directly to the battery and may enable the data edge device 310 to evaluate the charge state and health of the battery. In still yet additional embodiments, the fleet data edge device 310 may also include a CAN bus and USB bus. In certain embodiments, the CAN bus can enable the fleet data edge device 310 to talk to the MHE vehicle computer and retrieve fault codes, service issues and state of the vehicle. In many additional embodiments, the USB bus may enable connection to a number of other vehicle data sensors.

[0054] In further embodiments, the fleet data edge device 310 can have a Wi-Fi 802. l lb/g/n 2X multiple-input multiple-output (MIMO) wireless interface to talk to the business edge server. In still further embodiments, the connection can be made very secure by using HTTPS TLS encryption along with a novel Secure Temporal Token for authentication and authorization.

[0055] While a variety of fleet management servers and applications are described above with reference to FIGS. 2 and 3, the specific configurations and communication between applications of servers and between applications are largely dependent upon the requirements of specific applications. For example, it can be appreciated by those skilled in the art that the exact types of database, security methods, and other programming patterns may be adjusted based on newly emerging methods and design patterns. A discussion of fleet management edge architecture is below.

[0056] With reference to FIG. 4, the present embodiment depicts a high-level diagram of a fleet management edge virtual private network (VPN), in accordance with an embodiment of the invention. In a number of embodiments, the fleet management edge architecture 400 is a platform agnostic cloud-based solution. Agnostic architectures may enable future implementations to be more easily run on multiple platforms. In a variety of embodiments, the architecture 400 can run on a Linux Cloud service, in-house enterprise Linux cloud service, or an enterprise multi-rack server environment. In more embodiments, the fleet management edge architecture 400 can even run on a Windows Server environment using Hyper-V. In still more embodiments, a cloud service utilized for this fleet management edge architecture 400 may be Amazon’s Web Services (AWS) by Amazon.com, Inc. of Seattle, Washington. AWS offers a multitude of solution architectures including agnostic cloud services.

[0057] In many additional embodiments, the fleet management edge architecture 400 comprises four major components: database edge, business edge, data edge, and RabbitMQ edge. In still additional embodiments, each of the components is a unique computing instance. In yet still additional embodiments, three of the instances - business edge, database edge, and data edge - support AWS auto-scaling. Auto-scaling allows can allow for seamless performance and capacity growth as the platform demand increases. In certain embodiments, the RabbitMQ edge can utilize instance clustering instead of auto-instance scaling. In this way, multiple instances can be manually implemented as resource demands require more queues and faster response.

[0058] In further embodiments, the fleet business edge is an application server that supports micro-services applications, which are self-contained embedded Linux execution units that may utilize the instance private IP address and use multiple ports to differentiate their services. In still further embodiments, the data edge instance may handle all of the MHE streaming data. In still yet further embodiments, the data edge instance can pass all data to the RabbitMQ publish/subscribe service as well as the tenant database. In still yet further embodiments again, the data edge can also handle all of the security for the actual hardware devices. In many further embodiments, the data edge devices may utilize standard HTTPS TLS encryption. In certain further embodiments, the data edge may have its own X.509 certificate that is used with the data edge hardware to generate a set of secure session keys to provide the encryption necessary for data secrecy. In additional further embodiments, a proprietary secret AES256 key can be integrated into the Data Edge hardware with a Secure Temporal Token (STT) to enable the data edge to validate the data edge hardware authentication and security authorization.

[0059] In additional embodiments, the RabbitMQ edge instance can handle third-party data subscription services. In still additional embodiments, outside services can subscribe to specific data subjects, such as, but not limited to, data edge bar code data. In still yet additional embodiments, when specific data subjects are received, the RabbitMQ Edge may forward the data to the specific third-party data subscriber.

[0060] In a variety of embodiments, the database edge can be a repository for all data edge transactions. In many additional embodiments, all data that is collected from each customer or tenant is saved in a unique and secure database. This design pattern is called a“Tenant Database” and only allows specific tenants to store or access data in their own specific tenant database. The tenant database is physically separate from other tenants and data is never intermingled. In many further embodiments, access to the tenant database can only be allowed with the use of an encrypted token only known to the tenant.

[0061] With reference to FIG. 5, the present embodiments depict a high-level diagram of a fleet management security surface platform 500, in accordance with an embodiment of the invention. Security can be a key important design factor for edge architectures. In many embodiments, the fleet management edge security surface is designed to fit into a typical Enterprise IT environment. Throughout the design, proven Enterprise IT security methods are used to ensure enhanced security. In a number of embodiments, the security surface includes the following security technologies: AWS VPC, AWS Virtual Firewalls, HTTPS/Port 443 public access only, ETser ID/Password user access, Java Spring MVC Web Security, Cisco VPN System Admin Access, Highly secure data edge security, tenant database usage, and/or secure intranet service endpoints. Numerous embodiments can utilize a Virtual Private Cloud (VPC) architecture. VPC allows systems developers to only expose a very limited number of IP ports; all other internal ports are private and cannot be accessed unless by an internal secure resource. Additionally, by way of example and not limitation, in front of all ports can be an AWS virtual firewall whose properties may be set up with the AWS administration web portal.

[0062] In additional embodiments, user access is through web portals via HTTPS utilizing TLS/X.509 secure session keys. In more additional embodiments, only port 443 is open for user access; all other ports are private and cannot be accessed from the public side of the firewall. In still additional embodiments, access can be protected by a user ID/password managed by Java Spring Password Encoder, which provides highly secure password services and password vault facilities. All of the normal password strength, password non-reuse, password vault and password encryption are supported by Password Encoder. In yet additional embodiments, web page secure access may be managed by Java Spring MVC servlet security, which can ensure that web pages are only accessed with the correct security credentials. [0063] As highlighted earlier in many embodiments, data edge access can be highly secure using a combination of HTTPS/TLS encryption and Secure Temporal Tokens (STT). HTTPS/TLS can ensure message security and secrecy while STT may authenticate a valid data edge device and provide authorization services to limit the data access of the device.

[0064] In certain embodiments, access to the RabbitMQ data publisher/subscriber server is controlled through a user ID/password and can use the Spring Password Encoder facility to manage password generation and authentication. In additional embodiments, the database uses a tenant design pattern where only data from a specific company is stored in the tenant database, allowing for proprietary corporate data that is never intermingled with another company’s data. As in similar embodiments, the databases can be user ID/password protected through Java Spring Password Encoder.

[0065] Finally, in further embodiments, the fleet management edge system may be expected to work with other internal intranet applications such as, but not limited to, Oracle Financial Databases to handle AR/AP for invoicing its customers. In still further embodiments, as with most cloud-based services, there can be no direct network domain connection, instead using a secure service endpoint for all interactions with intranet applications. In still yet further embodiments, special secure service endpoints utilizing REST may handle requests from the fleet management edge system. In more further embodiments, HTTPS/TLS may be used to enable a secure connection, and a user ID/password will be used to authenticate and set the access authorization. In still more further embodiments, agreed upon REST GET/POSTs can be used to exchange data between the FME server and a secure endpoint which will then create a secure connection with internal resources to handle the REST requests. In certain further embodiments, the fleet management edge system may forgo an internal AWS firewall and go with a Cisco and/or Checkpoint firewall solution, providing for more security options and filters along with audit and logging facilities.

[0066] FIG. 6 depicts a high-level flowchart of a method embodiment 600 of a data collection system in accordance with an embodiment of the invention. The method 600 may include collecting data from sensors on material handling equipment (MHE) (step 602). The sensors may be any sensor for collecting data on the MHE, warehouse operations, inventory, or the like. The method 600 may then include abstracting the collected data to a common schema (step 604). The abstracted data may be sent from a fleet edge device to a business edge application server (step 606). The business edge application server may receive the abstracted data (step 608). An energy status of each MHE may be monitored (step 610). The energy and health status of the fleet may be constantly measured. This information is can help warehouse management software determine the most optimal charging regime based on warehouse workload and shift schedules. The method 600 may then include determining an optimal charging profile for each MHE (step 612). The optimal charging profile may be sent to a charger (step 610). Each MHE may be charged with its respective optimal charging profile when the MHE is connected to the charger (step 612).

[0067] Most MHE’s use Lead- Acid battery packs. Lead- Acid batteries require a complex charging cycle to achieve optimal energy storage and battery lifetime. Advanced charging methods can increase the longevity of the battery pack by a factor of 3 to 4 times. MHE battery packs are expensive so an optimal charging profile provides a good return on investment (ROI). Many MHE’s may not be charged during optimal times, such as times of non-use, lunch breaks, or the like. Accordingly, a warehouse operation may decide that additional MHE’s are needed to meet demand. By instead determining an optimal charging profile, the MHE’s may be charged during available times and provide a charge when needed, which could eliminate the need for additional MHE.

[0068] FIG. 7 illustrates an example of a top-level functional block diagram of a computing device embodiment 700. The example operating environment is shown as a computing device 720 comprising a processor 724, such as a central processing unit (CPET), addressable memory 727, an external device interface 726, e.g., an optional universal serial bus port and related processing, and/or an Ethernet port and related processing, and an optional user interface 729, 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 728. In some embodiments, via an operating system 725 such as one supporting a web browser 723 and applications 722, the processor 724 may be configured to execute steps of a process establishing a communication channel and processing according to the embodiments described above.

[0069] 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.

[0070] FIG. 8 is a high-level block diagram 800 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 802, and can further include an electronic display device 804 (e.g., for displaying graphics, text, and other data), a main memory 806 (e.g., random access memory (RAM)), storage device 808, a removable storage device 810 (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 811 (e.g., keyboard, touch screen, keypad, pointing device), and a communication interface 812 (e.g., modem, a network interface (such as an Ethernet card), a communications port, or a PCMCIA slot and card). The communication interface 812 allows software and data to be transferred between the computer system and external devices. The system further includes a communications infrastructure 814 (e.g., a communications bus, cross-over bar, or network) to which the aforementioned devices/modules are connected as shown.

[0071] Information transferred via communications interface 814 may be in the form of signals such as electronic, electromagnetic, optical, or other signals capable of being received by communications interface 814, via a communication link 816 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. [0072] 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.

[0073] 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 812. 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.

[0074] FIG. 9 shows a block diagram of an example system 900 in which an embodiment may be implemented. The system 900 includes one or more client devices 901 such as consumer electronics devices, connected to one or more server computing systems 930. A server 930 includes a bus 902 or other communication mechanism for communicating information, and a processor (CPU) 904 coupled with the bus 902 for processing information. The server 930 also includes a main memory 906, such as a random access memory (RAM) or other dynamic storage device, coupled to the bus 902 for storing information and instructions to be executed by the processor 904. The main memory 906 also may be used for storing temporary variables or other intermediate information during execution or instructions to be executed by the processor 904. The server computer system 930 further includes a read only memory (ROM) 908 or other static storage device coupled to the bus 902 for storing static information and instructions for the processor 904. A storage device 910, such as a magnetic disk or optical disk, is provided and coupled to the bus 902 for storing information and instructions. The bus 902 may contain, for example, thirty-two address lines for addressing video memory or main memory 906. The bus 902 can also include, for example, a 32-bit data bus for transferring data between and among the components, such as the CPU 904, the main memory 906, video memory and the storage 910. Alternatively, multiplex data/address lines may be used instead of separate data and address lines.

[0075] The server 930 may be coupled via the bus 902 to a display 912 for displaying information to a computer user. An input device 914, including alphanumeric and other keys, is coupled to the bus 902 for communicating information and command selections to the processor 904. Another type or user input device comprises cursor control 916, such as a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to the processor 904 and for controlling cursor movement on the display 912.

[0076] According to one embodiment, the functions are performed by the processor 904 executing one or more sequences of one or more instructions contained in the main memory 906. Such instructions may be read into the main memory 906 from another computer- readable medium, such as the storage device 910. Execution of the sequences of instructions contained in the main memory 906 causes the processor 904 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 906. 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.

[0077] 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.

[0078] Generally, the term "computer-readable medium" as used herein refers to any medium that participated in providing instructions to the processor 904 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 910. 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.

[0079] 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.

[0080] Various forms of computer readable media may be involved in carrying one or more sequences of one or more instructions to the processor 904 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 930 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 902 can receive the data carried in the infrared signal and place the data on the bus 902. The bus 902 carries the data to the main memory 906, from which the processor 904 retrieves and executes the instructions. The instructions received from the main memory 906 may optionally be stored on the storage device 910 either before or after execution by the processor 904.

[0081] The server 930 also includes a communication interface 918 coupled to the bus 902. The communication interface 918 provides a two-way data communication coupling to a network link 920 that is connected to the worldwide packet data communication network now commonly referred to as the Internet 928. The Internet 928 uses electrical, electromagnetic or optical signals that carry digital data streams. The signals through the various networks and the signals on the network link 920 and through the communication interface 918, which carry the digital data to and from the server 930, are exemplary forms or carrier waves transporting the information.

[0082] In another embodiment of the server 930, interface 918 is connected to a network 922 via a communication link 920. For example, the communication interface 918 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 920. As another example, the communication interface 918 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 918 sends and receives electrical electromagnetic or optical signals that carry digital data streams representing various types of information.

[0083] The network link 920 typically provides data communication through one or more networks to other data devices. For example, the network link 920 may provide a connection through the local network 922 to a host computer 924 or to data equipment operated by an Internet Service Provider (ISP). The ISP in turn provides data communication services through the Internet 928. The local network 922 and the Internet 928 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 920 and through the communication interface 918, which carry the digital data to and from the server 930, are exemplary forms or carrier waves transporting the information.

[0084] The server 930 can send/receive messages and data, including e-mail, program code, through the network, the network link 920 and the communication interface 918. Further, the communication interface 918 can comprise a USB/Tuner and the network link 920 may be an antenna or cable for connecting the server 930 to a cable provider, satellite provider or other terrestrial transmission system for receiving messages, data and program code from another source.

[0085] The example versions of the embodiments described herein may be implemented as logical operations in a distributed processing system such as the system 900 including the servers 930. The logical operations of the embodiments may be implemented as a sequence of steps executing in the server 930, and as interconnected machine modules within the system 900. The implementation is a matter of choice and can depend on performance of the system 900 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.

[0086] Similar to a server 930 described above, a client device 901 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 928, the ISP, or LAN 922, for communication with the servers 930.

[0087] The system 900 can further include computers (e.g., personal computers, computing nodes) 905 operating in the same manner as client devices 901, where a user can utilize one or more computers 905 to manage data in the server 930.

[0088] Referring now to FIG. 10, 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. 10 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).

[0089] 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.

Claims

WHAT IS CLAIMED IS:

1. A system comprising:

one or more sensors (110);

a fleet data edge device (220) comprising a processor and addressable memory, the fleet data edge device in communication with the one or more sensors, the fleet data edge device processor configured to:

collect data from one or more materials handling equipment (MHE) via the one or more sensors; and

abstract the collected data to a common data schema;

a business edge application server (210) comprising a processor and addressable memory, the business edge application server processor configured to:

receive the abstracted data from the fleet data edge device; and

monitor a status of the one or more MHE.

2. The system of claim 1, wherein the business edge application server further comprises: a database edge module (215), wherein the database edge module is configured to:

store the received data from the fleet data edge device, wherein data from each customer is stored in a separate customer database.

3. The system of claim 2, wherein the business edge application server further comprises: an energy edge module (211), wherein the energy edge module is configured to:

determine an optimal charge profile for a MHE of the one or more MHE based on the stored data from the database edge module.

4. The system of claim 3, wherein the energy edge module is further configured to:

load the optimal charge profile for the MHE into a charger (240) for the MHE, wherein the MHE is charged using the optimal charge profile when the MHE is plugged into the charger.

5. The system of claim 3, wherein the energy edge module is further configured to:

determine an energy requirement for the one or more MHE based on the stored data from the database edge module.

6. The system of claim 3, wherein the energy edge module is further configured to:

determine an energy profile for the one or more MHE based on the stored data from the database edge module.

7. The system of claim 3, wherein the energy edge module is further configured to:

determine a projected battery life for the one or more MHE based on the stored data from the database edge module.

8. The system of claim 2, wherein the business edge application server further comprises: an analytics edge module (212), wherein the analytics edge module is configured to: provide access to the stored data in the database edge module.

9. The system of claim 8, wherein the business edge application server further comprises: a business edge module (210), wherein the business edge module is configured to: monitor a health of at least one of: the database edge module, the energy edge module, and the analytics edge module.

10. The system of claim 9, wherein the business edge module is further configured to:

provide access to the status of the one or more MHE via an edge administration portal (250).

11. The system of claim 9, wherein the business edge module is further configured to:

provide access to a real-time energy analytics (255) of the one or more MHE via the edge administration portal.

12. A method comprising:

collecting data, by a fleet data edge device (220) comprising a processor and addressable memory, from one or more materials handling equipment (MHE) via one or more sensors (110);

abstracting, by the fleet data edge device, the collected data to a common data schema; receiving, by a business edge application server (210) comprising a processor and

addressable memory, the abstracted data from the fleet data edge device; and monitoring, by the business edge application server, a status of the one or more MHE.

13. The method of claim 12 further comprising:

storing, by a database edge module (215) of the business edge application server, the received data from the fleet data edge device, wherein data from each customer is stored in a separate customer database.

14. The system of claim 13 further comprising:

determining, by an energy edge module (211) of the business edge application server, an optimal charge profile for a MHE of the one or more MHE based on the stored data from the database edge module.

15. The system of claim 14 further comprising:

loading, by the energy edge module, the optimal charge profile for the MHE into a

charger (240) for the MHE, wherein the MHE is charged using the optimal charge profile when the MHE is plugged into the charger.

16. The system of claim 14 further comprising:

determining, by the energy edge module, an energy requirement for the one or more MHE based on the stored data from the database edge module.

17. The system of claim 14 further comprising:

determining, by the energy edge module, an energy profile for the one or more MHE based on the stored data from the database edge module.

18. The system of claim 14 further comprising:

determining, by the energy edge module, a projected battery life for the one or more MHE based on the stored data from the database edge module.

19. The system of claim 14 further comprising:

providing, by an analytics edge module (212) of the business edge application server, access to the stored data in the database edge module.

20. The system of claim 19 further comprising: monitoring, by a business edge module (210) of the business edge application server, health of at least one of: the database edge module, the energy edge module, and the analytics edge module.

21. The system of claim 20 further comprising:

providing, by the business edge module, access to the status of the one or more MHE via an edge administration portal (250).

22. The system of claim 20 further comprising:

providing, by the business edge module (210), access to a real-time energy analytics (255) of the one or more MHE via the edge administration portal.

23. A method comprising:

receiving, by a business edge application server (210) comprising a processor and

addressable memory, abstracted data from one or more materials handling equipment (MHE) via one or more sensors (110);

monitoring, by the business edge application server, an energy status of each MHE of the one or more MHE based on the received abstracted data;

determining, by the business edge application server, an optimal charging profile for each MHE of the one or more MHE based on the monitored energy status; and

sending, by the business edge application server, the optimal charging profile for each MHE to a charger (240), wherein each MHE is configured to charge based on the sent optimal charging profile when each MHE is connected to the charger.