DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 2, 5 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Daniels (US 20250069401).
Regarding claim 1, An intelligent alert system for warehouse environments, the system comprising: at least one first user device; at least one second user device; (“Referring again to FIG. 1, by way of example, user equipment 101 is any type of embedded system, mobile terminal, fixed terminal, or portable terminal including a built-in navigation system, a personal navigation device, mobile handset, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal digital assistants (PDAs), audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, game device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof” Daniels: paragraph 28 & “In another embodiment, one or more users may reserve a parking space via user interfaces on their respective user equipment” Daniels: paragraph 79 – showing that there are multiple “user equipment” devices in the system)
at least one sensor device located within a warehouse environment; (“a system for automating management of a warehouse is disclosed. The system includes monitoring, in real-time, a plurality of items in the warehouse, a plurality of tasks associated with the warehouse, and/or incoming vehicles to the warehouse; receiving, via a plurality of sensors, image data and/or video data associated with the plurality of items” Daniels: paragraph 7)
one or more servers, (“In one embodiment, the machine learning system 115 and/or computer vision system 117 may be a platform with multiple interconnected components. The machine learning system 115 and/or computer vision system 117 may include multiple servers, intelligent networking devices, computing devices, components and corresponding software for automating the management of a warehouse. In addition, it is noted that the machine learning system 115 and/or computer vision system 117 may be a separate entity of the system 100, or included within the user equipment 101, vehicle 109, and/or warehouse facility 113” Daniels: paragraph 36)
the one or more servers being configured to: continuously monitor sensed data from the at least one sensor for a pre- defined alert trigger; (“For example, as vehicle 109 approaches the entrance of warehouse facility 113, location sensor 111 detects its presence and provides a signal indicative thereof to machine learning system” Daniels: paragraph 62)
receive real-time warehouse data relating to the warehouse environment; execute a machine learning algorithm to monitor the at least one sensor and identify discrepancies between the sensed data an expected parameter based on the warehouse data; (“In step 215, machine learning system 115 may receive, via a plurality of sensors, e.g., sensors 111, image data and/or video data associated with the plurality of items, the plurality of tasks, and/or the incoming vehicles. In one embodiment, the image data and/or the video data may indicate a change in position of at least one of the plurality of items, at least one incomplete task from the plurality of tasks, and/or a change in location of at least one of the incoming vehicles. In one embodiment, the plurality of sensors may collect the image data and/or the video data in real-time, per demand, according to a set schedule, in response to one or more activities detected in a particular area of the warehouse, or a combination thereof. In one embodiment, machine learning system 115 may process and segment the image data and/or the video data into a plurality of regions” Daniels: paragraph 52)
receive an alert trigger from one of: a received input signal from the at least one first user device; a pre-defined trigger being identified in the sensed data; and the machine learning algorithm; and in response to the alert trigger, send a notification to one or more of the second user devices. (“In one embodiment, machine learning system 115 may determine whether one or more users have exceeded the duration of their stay in the rented space. In one example embodiment, machine learning system 115 may notify the users in their respective UE 101 that they have overstayed and are subject to penalty fees, e.g., on an hourly basis or a daily basis. In another example embodiment, machine learning system 115 may generate alerts in the UE 101 of the users that they have exceeded their duration and have to leave the rented space because of bookings by other users to ensure the spaces are available per their reserved timings.” Daniels: paragraph 57)
Regarding claim 2, An intelligent alert system according to claim 1, wherein the system further comprises one or more integrated automation and robotics systems having their own sensors and processing software, and which are communicatively coupled to the one or more servers, and wherein the one or more servers are further configured alert triggers from said one or more automation and robotics systems. (“As depicted in FIG. 3G, mobile robot 313 comprising a plurality of sensors is moved within an area of warehouse facility 113 to scan each item of inventory 307. Mobile robot 313 may transmit, in real-time, sensor information to machine learning system 115, and machine learning system 115 may update inventory information in database 119. In one example embodiment, each item of inventory 307 may comprise a sensor or a tag, e.g., radio frequency identification (RFID) tags. Mobile robot 313 may comprise an RFID reader that reads and writes information to the RFID tags. In another embodiment, warehouse facility 113 comprises smart shelves 311 that are equipped with weight sensors, proximity sensors, 3D cameras, microphones, RFID tags, near-field communication (NFC), electronic printed tags, LED sensors, optical sensors, IOT sensors, etc., to monitor the occupancy, vacancy, and/or capacity of the shelf. These smart shelves 311 are designed to automatically keep track of products on the shelf, e.g., when an item/product is picked from the shelf, smart shelves 311 may send a notification, in real-time, to user equipment 101, machine learning system 115, computer vision system 117, or a combination thereof. In such a manner, real-time inventory status is available without the errors and delays associated with manual level readings” Daniels: paragraph 68 & “In one embodiment, monitoring module 201 may monitor, in real-time, the warehouse environment. In one instance, the warehouse environment includes real-time inventory information, estimated future inventory information, and historical inventory information. In one example embodiment, monitoring module 201 may monitor misplaced items within the warehouse environment, and may provide feedback associated with the misplaced items based on detected events, e.g., suggest correct locations for misplaced items” Daniels: paragraph 43; inventory monitoring using robots leading to misplaced item notifications)
Regarding claim 5, An intelligent alert system according to claim 1, wherein the at least one sensor is selected from the group consisting of: weight scales, cameras, and barcode scanners. (“In one example embodiment, sensors 111 include a camera/imaging sensor for gathering image data, e.g., the camera sensors may automatically capture ground control point imagery etc., for analysis.” Daniels: paragraph 32)
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 3, 4, 11, 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Daniels in view of Peters (US 20240069531).
Regarding claim 3, An intelligent alert system according to claim 1, wherein one or more of the first user devices are handheld devices (“Referring again to FIG. 1, by way of example, user equipment 101 is any type of embedded system, mobile terminal, fixed terminal, or portable terminal including a built-in navigation system, a personal navigation device, mobile handset, station, unit, device, multimedia computer, multimedia tablet, Internet node, communicator, desktop computer, laptop computer, notebook computer, netbook computer, tablet computer, personal communication system (PCS) device, personal digital assistants (PDAs), audio/video player, digital camera/camcorder, positioning device, television receiver, radio broadcast receiver, electronic book device, game device, or any combination thereof, including the accessories and peripherals of these devices, or any combination thereof.” Daniels: paragraph 28)
The claimed configured to send alert triggers via accessing a digital interface hosted by the one or more servers is not specifically disclosed by Daniels. Peters discloses a system for managing a warehouse that teaches a machine learning algorithm receiving a notification from a user through a software application on a mobile device (“For example, the warehouse operator may identify that the warehouse needs to replenish the stock of a particular item. The warehouse operator may declare the need for the stock-replenishment via a software application (e.g., a software application on one of the the mobile devices 116)” Peters: paragraph 64). Modifying Daniels to include software to allow the user to notify the machine learning system of issues would increase the overall utility of the system by allowing for more ways to indicate potential issues. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Daniels according to Peters.
Regarding claim 4, An intelligent alert system according to claim 1, wherein one or more of the first user devices are configured to manually trigger alerts using a dedicated physical input trigger is not specifically disclosed by Daniels. Peters discloses a system for managing a warehouse that teaches a warehouse that includes a button that can be pressed to indicate the need for stock replacement (“For example, a warehouse may include a button, which may be an edge device 102 or a distributed IIOT device 103. A warehouse operator may use the button to indicate a need for stock replenishment. Pressing the button may trigger generation of sensor data that indicates a need for stock replenishment (i.e., a binary value equal to one).” Peters: paragraph 62). Modifying Daniels to include a button for indicating a need for stock replacement would increase the overall utility of the system by allowing for more ways to indicate potential issues. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Daniels according to Peters.
Regarding claim 11, An intelligent alert system according to claim 1, wherein the at least one second user device is associated with a user profile of a manager or team lead of the warehouse environment is not specifically disclosed by Daniels. Peters discloses a system for managing a warehouse that teaches a warehouse operator (manager) using a mobile device to send notifications (“For example, the warehouse operator may identify that the warehouse needs to replenish the stock of a particular item. The warehouse operator may declare the need for the stock-replenishment via a software application (e.g., a software application on one of the the mobile devices 116)” Peters: paragraph 64). Modifying Daniels to have managerial users operate the user device would increase the overall utility of the system by allowing for more users to indicate potential issues. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Daniels according to Peters.
Regarding claim 12, An intelligent alert system according to claim 11, wherein the notification to the second user device is in the form of an IM, text message, or e-mail to the associated user profile of the second user device. (“The completion of the parking assignment may automatically trigger transmission of an SMS text to user equipment 101 of the checked-in driver. The SMS text may include specific information regarding parking, e.g., navigation information, location information, etc. (as depicted in FIG. 4I). The operator and the driver can communicate via text through this channel.” Daniels: paragraph 80)
Claim(s) 6, 7, 8, 9 is/are rejected under 35 U.S.C. 103 as being unpatentable over Daniels in view of Wilson (US 20100079274).
Regarding claim 6, An intelligent alert system according to claim 1, wherein the system further comprises at least one physical alert device located within the same warehouse environment, and the one or more servers are further configured to trigger the at least one physical alert device in response to the alert trigger is not specifically disclosed by Daniels. Wilson discloses a warehouse with physical indicators that are in a stack format of green, yellow, and red (“The multiple indicator devices 132a-132c shown in FIG. 5 are of the stack light type of indicators that may serve to best display the type of assistance that is required by a particular employee at a particular location. Using the standard green/yellow/red (G/Y/R) color combination, these indicators may easily provide information about the urgency of the request for assistance. These color coded lights (in G/Y/R or some other color combination) may alternately serve to indicate different needs such as "parts needed" or "relief needed" or "job completed" or the like.” Wilson: paragraph 99). Modifying Daniels to include a physical alert indicator would increase the overall capabilities of the system by providing an easy to see and understand indication of potential issues that would allow the user to more quickly find and fix problems. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Daniels according to Wilson.
Regarding claim 7, An intelligent alert system according to claim 6, wherein the at least one physical alert device includes at least one set of alert lights. (“The multiple indicator devices 132a-132c shown in FIG. 5 are of the stack light type of indicators that may serve to best display the type of assistance that is required by a particular employee at a particular location. Using the standard green/yellow/red (G/Y/R) color combination, these indicators may easily provide information about the urgency of the request for assistance. These color coded lights (in G/Y/R or some other color combination) may alternately serve to indicate different needs such as "parts needed" or "relief needed" or "job completed" or the like.” Wilson: paragraph 99)
Regarding claim 8, An intelligent alert system according to claim 7, wherein the alert lights include andon lights. (“The multiple indicator devices 132a-132c shown in FIG. 5 are of the stack light type of indicators that may serve to best display the type of assistance that is required by a particular employee at a particular location. Using the standard green/yellow/red (G/Y/R) color combination, these indicators may easily provide information about the urgency of the request for assistance. These color coded lights (in G/Y/R or some other color combination) may alternately serve to indicate different needs such as "parts needed" or "relief needed" or "job completed" or the like.” Wilson: paragraph 99; andon lights are merely a Japanese loan-word for stacked multicolor lights such as the one show in Wilson)
Regarding claim 9, An intelligent alert system according to claim 6, wherein the physical alert devices further comprise a set of audible alarm systems. (“Shown as examples in FIG. 4 are the industrial indicator strobe light 84, as described with FIG. 3 with wireless switch receiver 94 associated therewith. In a similar manner, multi-switch handheld transmitter 72 may control: industrial indicator illuminated sign 96 (having wireless switch receiver 98 and indicator sign panel 102); industrial machinery power interrupt 104 (having wireless switch receiver 106 and electrical plug connectors 108); and (as a further example) industrial indicator audible alarm 110 (having wireless switch receiver 112 and loudspeaker/siren 114 with optional indicator lights 116)” Wilson: paragraph 96)
Claim(s) 10 is/are rejected under 35 U.S.C. 103 as being unpatentable over Daniels in view of Ganapathi (US 20210374659).
Regarding claim 10, An intelligent alert system according to claim 1, wherein the real-time warehouse data is received via one or more of: WMS systems, ERP systems, and CRM systems associated with the warehouse environment is not specifically disclosed by Daniels. Ganapathi discloses a warehouse management and monitoring system that teaches using a WMS system to monitor inventory and potential issues (“This information is then compared against the Warehouse Management System (WMS) to determine if there are any discrepancies between the incoming or outgoing bills of lading and the actual shipment” Ganapathi: paragraph 63). Modifying Daniels to include a WMS system would increase the overall capabilities of the system by providing the user with additional means to manage inventory and deliveries and detect issues. Therefore it would have been obvious to one of ordinary skill in the art before the effective filing date to modify Daniels according to Ganapathi.
Conclusion
Related Art:
US 20240371254 A1 – anomaly detection with machine learning
US 20210276842 A1 – WMS system
US 10614091 B1 – discrepancy detection in a warehouse
US 20200056927 A1 – variation detection in a warehouse
US 20110273303 A1 – stack lights for indicating issues
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TRAVIS R HUNNINGS whose telephone number is (571)272-3118. The examiner can normally be reached M: 6-7:30a, 9:30a-4:45p, 8:30-10p; T: 6-7:30a, 12-4p, 7:30p-12a; W: 6-7:30a, 9:30a-4:45p; H: 6-7:30a, 8:15a-4:45p; F: 12:00-4:45p.
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/TRAVIS R HUNNINGS/ Primary Examiner, Art Unit 2689