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 .
Response to Arguments
Applicant's arguments filed 3/27/2026 have been fully considered but they are not persuasive.
Applicant's arguments that Williams does not disclose a second control message to configure the identification sensor/system is not persuasive.
The delivery container 110 or parcel repository of Williams, see Fig. 1, 4, includes a receiver/transceiver 20 for receiving and exchanging data communications (Page 8, lines 11-23), and control circuitry 24/224 for controlling electronic components including, but not limited to, the lock, display, and receiver/transceiver based on stored criteria (see Page 8, lines 21-23, Col. 14, lines 28-30, Col. 8, lines 28-29). For instance, the control circuitry 24 can confirm satisfaction of unlock criteria (Page 8, lines 20-21), and communicate with the reader/camera 458 that collects images of items (Page 19, lines 28-30).
This control information governs the operation of the delivery container identification and communication components and therefore constitutes a control message used to configure the identification system under the broadest reasonably interpretation of “configure”. Messages that determine how the delivery container electronics operate, communicate, authenticate, and/or respond are configuration messages in ordinary technical usage.
The claims do not require any specialized form of configuration beyond receipt of a control message for operative control of the subsystem.
Similarly, Applicant arguments on Page 8 regarding claims 14-18, and 20 that Williams in view of Sengstaken does not disclose a control message configuring the identification sensor/system is not persuasive, for the same reasons above. Messages that determine how the delivery container electronics operate, communicate, authenticate, or respond are configuration messages in ordinary technical usage.
Applicant's arguments regarding new claims 21 and 22 are also not persuasive. Applicant recites that the artificial intelligence circuit analyzes the characteristic signal based on a model, and the device comprises a repository controller that configures the artificial intelligence circuit to construct the model based on historical input data from the characteristic signal, and the configuration file configures the artificial intelligence circuit to construct a model based on historical input data from the indicator signal corresponding to the item identification characteristics.
Applicant's arguments are not persuasive since Williams discloses machine learning algorithms trained to identify an item or item condition from characteristic signals, such as from images from the reader camera 458, and further teaches the use of historical item information, such as known dimensions and/or weights associated with identified items (Page 23, lines 12-29).
For example, upon identifying an item as a known product (such as an iPhone 8, Williams determines the corresponding dimensions of the iPhone 8 from the stored data (Page 23, lines 20-25). This teaching evidences construction and use of a model based on historical input data corresponding to item identification parameters. Under the broadest reasonable interpretation, configuring the artificial intelligence circuit to construct the model includes training relationships used by the machine learning system from historical data.
Moreover, even if not expressly stated, it would have been obvious to configure the artificial intelligence circuitry (i.e., the machine learning algorithms employed by the management circuitry 457) to construct or update such a model from accumulated historical sensor data (such as images) and known item-identification information in order to improve identification accuracy. Applicant's claims do not add any meaningful new technical structure or non-conventional operation and does not automatically create a patentable distinction.
Please see grounds of rejection below.
Claim Rejections - 35 USC § 103
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) 1-7, 9-13, and 21 is/are rejected under 35 U.S.C. 103 as being unpatentable over Kutas et al (US PG. Pub. 2020/0085222) in view of Williams (GB 259 895 8 A). Relative to claims 1-7, Kutus discloses:
claim 1) A device (Fig. 1) comprising:
a repository (100)(Fig. 1) having an intake and an access (Para. 0154, intake may include aperture, 104, and/or front door 102, aperture 104 can receive letters, front door can receive packages; the access may include owner’s door, or “back door” which may be accessed from inside the owners home for the owner to place or retrieve items; Para. 0156), the access (backdoor, or door from owners side) is separate from the intake (104, 102) and the access has an access door (Fig. 1)(Para. 0154, delivery person can deliver letters into the slot 104, and deliver packages inside the door 102; Para. 0156 the door 102 of the mailbox 100, or “front door”, faces the outside, and a “backdoor” can be accessed from inside the owners home);
claim 3) the intake (104) of the repository (100) comprises an intake (104, 102) selected from an envelope intake and a package intake (Para. 0154), the envelope intake (104) has a geometric size and shape to allow a standard postal envelope to pass through the envelope intake (see Fig. 1)(aperture 104 accepts letters or flat mail), the package intake (102) has a geometric size and shape to allow a standard postal package to pass through the package intake (Para. 0154, delivery person may insert a box into door 102)(Fig. 1);
claim 6) comprising an indicator selected the group consisting of a light, an LED array, an audible speaker, and a user computing device (see identification lights, light 1102, LED light 1006, Para. 0196, see also voice input/output 1032, Para. 0193, cellular module 1028, Para. 0191)(Fig. 10-11); and
claim 7) a repository controller (1012)(Fig. 10) that configures the repository (Para. 0191).
Kutus does not expressly disclose:
claim 1) an identification system having a sensor that generates a characteristic signal corresponding to a characteristic of an item in the repository, and the identification system is to receive a control message to configure the identification system; and
an artificial intelligence circuit that receives from the sensor the characteristic signal, analyzes the characteristic signal to identify an item in the repository, and transmits an indicator signal indicative of an item in the repository;
claim 2) an indicator circuit that receives from the artificial intelligence circuit the indicator signal and that indicates the item in the repository based on the indicator signal;
claim 4) the sensor of the identification system comprises a sensor selected the group consisting of a: an audio sensor, an optical sensor, a vibration sensor, a scale, an electro/magnetic sensor;
claim 5) the artificial intelligence circuit comprises an intelligent driver, an input/output component, a processor, and a memory; or
claim 21) the artificial intelligence circuit analyzes the characteristic signal based on a model, and the device comprises a repository controller that configures the artificial intelligence circuit to construct the model based on historical input data from the characteristic signal corresponding to item identification characteristics.
Williams teaches:
claim 1) an identification system (458)(Fig. 4) having a sensor that generates a characteristic signal corresponding to a characteristic of an item in the repository (reader 458, collects information; Page 19, lines 28-30); and the identification system (458) is to receive a control message to configure the identification system (Page 19, lines 28-30); and
an artificial intelligence circuit that receives from the sensor (458) the characteristic signal, analyzes the characteristic signal to identify an item in the repository (210, 4000), and transmits an indicator signal indicative of an item in the repository (management circuitry 457 employs a database and machine learning algorithms to identify the items based on sensed images, the control circuitry that includes a data storage means and monitors data from the receiver/transceiver 20 which receives information; Page 19, lines 14-16; Page 20, lines 10-20, Page 23, lines 12-18; control circuitry is 24, transceiver/receiver is 20, Fig. 1A);
claim 2) an indicator circuit (included with display 454) that receives from the artificial intelligence circuit the indicator signal and that indicates the item in the repository based on the indicator signal (display screen displays information, Page 18, lines 15-17)(Fig. 4);
claim 4) the sensor of the identification system comprises a sensor selected the group consisting of a: an audio sensor, an optical sensor, a vibration sensor, a scale, an electro/magnetic sensor (reader 458 may be camera, Page 19, line 28); and
claim 5) the artificial intelligence circuit comprises an intelligent driver, an input/output component, a processor, and a memory (driver, input/output component, processor, and memory are inherently included in the management circuit that employs a database and machine learning algorithms to determine the identity of objects based on sensed images, input/output component may include the receiver/transceiver; Page 18, lines 19-20); and
Williams teaches the: identification system, the artificial intelligence circuit receiving from the sensor; the sensor consists of: an audio sensor, an optical sensor, a vibration sensor, a scale, and an electro/magnetic sensor; and the artificial intelligence circuit includes an intelligent driver, an input/output component, processor, and memory, for the purpose of providing an improved reusable delivery container that can ensure secure delivery of valuable items, eliminates the need to be transported back to a delivery depot, and reduces environmental impact (Page 1, lines 20-25 and lines 29-30; Page 2, lines 24-26).
It would have been obvious to one of ordinary skill in the art on or before the time of the filing to modify the system of Kutus with the identification system, the artificial intelligence circuit receiving from the sensor; the sensor consists of: an audio sensor, an optical sensor, a vibration sensor, a scale, and an electro/magnetic sensor; and the artificial intelligence circuit includes an intelligent driver, an input/output component, processor, and memory described above, as taught in Williams for the purpose of providing an improved reusable delivery container that can ensure secure delivery of valuable items, eliminates the need to be transported back to a delivery depot, and reduces environmental impact.
Relative to claim 21, the device of Kutus in view of Williams discloses all claim limitations mentioned above, but does not expressly disclose: the artificial intelligence circuit analyzes the characteristic signal based on a model, and the device comprises a repository controller that configures the artificial intelligence circuit to construct the model based on historical input data from the characteristic signal corresponding to item identification characteristics.
Kutus in view of Williams implies that the artificial intelligence circuit analyzes the characteristic signal based on a model, and the device comprises a repository controller that configures the artificial intelligence circuit to construct the model based on historical input data from the characteristic signal corresponding to item identification characteristics.
Williams discloses machine learning algorithms trained to identify an item or item condition from characteristic signals, such as from images from the reader camera 458, and further teaches the use of historical item information, such as known dimensions and/or weights associated with identified items (Page 23, lines 12-29).
For example, upon identifying an item as a known product (such as an iPhone 8, Williams determines the corresponding dimensions of the iPhone 8 from the stored data (Page 23, lines 20-25). This teaching evidences construction and use of a model based on historical input data corresponding to item identification parameters. Under the broadest reasonable interpretation, configuring the artificial intelligence circuit to construct the model includes training relationships used by the machine learning system from historical data.
Moreover, even if not expressly stated, it would have been obvious to configure the artificial intelligence circuitry (i.e., the machine learning algorithms employed by the management circuitry 457) to construct or update such a model from accumulated historical sensor data (such as images) and known item-identification information in order to improve identification accuracy.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Kutus in view of Williams so that the artificial intelligence circuit analyzes the characteristic signal based on a model, and the device comprises a repository controller that configures the artificial intelligence circuit to construct the model based on historical input data described above, since the system of Williams identifies an item as a known product, and determines the corresponding dimensions of the iPhone 8 from the stored data.
Relative to claims 9-13 and 22, the disclosure of Kutus includes:
claim 9) a system comprising:
a repository system (Fig. 1) having:
a repository (100)(Fig. 1) having an intake and an access (Para. 0154, intake may include aperture, 104, and/or front door 102, aperture 104 can receive letters, front door can receive packages; the access may include owner’s door, or “back door” which may be accessed from inside the owners home for the owner to place or retrieve items; Para. 0156), the access (backdoor, or door from owners side) is separate from the intake (104, 102) and the access has an access door (Fig. 1)(Para. 0154, delivery person can deliver letters into the slot 104, and deliver packages inside the door 102; Para. 0156 the door 102 of the mailbox 100, or “front door”, faces the outside, and a “backdoor” can be accessed from inside the owners home); and a repository controller (1012) that configures the repository system (Para. 0191); and
claim 12) the repository controller (1012)(Fig. 10) has a processor (inherently included, see for instance data bus 1016 which communicates information, memory 1014 controls the functions of the bonnet), a memory (1014)(Fig. 10), and a RF transceiver (1002)(Para. 0191)(Fig. 10); and
Kutus does not expressly disclose:
claim 9) an identification system having at least one sensor that generates a characteristic signal corresponding to a characteristic of an item in the repository;
an artificial intelligence circuit that receives from the sensor the characteristic signal, analyzes the characteristic signal to identify an item in the repository, and transmits an indicator signal indicative of the item in the repository;
an indicator circuit that receives from the artificial intelligence circuit the indicator signal and activates a notification of the presence of the item in the repository;
a user computing device that transmits a configuration file to the repository controller and produces the notification of the presence of the item in the repository,
the configuration file configures an identification system having a sensor that generates a characteristic signal corresponding to a characteristic of an item in a repository.
claim 10) the sensor of the identification system comprises a sensor selected the group consisting of a camera, a vibration sensor, a scale, an optical detector, radar sensor, laser sensor, infrared sensor, audio sensor, and a radio frequency identification sensor;
claim 11) the artificial intelligence circuit comprises an intelligent driver, an input/output component, a processor, and a memory;
claim 13) the artificial intelligence circuit is in the user computing device; or
claim 22) the configuration file configures the artificial intelligence circuit to construct a model based on historical input data from the indicator signal corresponding to item identification characteristics.
Williams teaches:
claim 9) an identification system having at least one sensor that generates a characteristic signal corresponding to a characteristic of an item in the repository;
an artificial intelligence circuit that receives from the sensor the characteristic signal, analyzes the characteristic signal to identify an item in the repository, and transmits an indicator signal indicative of the item in the repository;
an indicator circuit that receives from the artificial intelligence circuit the indicator signal and activates a notification of the presence of the item in the repository (indicator may include the display screen 454 that displays information; Page 18, lines 17-18; item deposition unit 4000 has a reader 458 and camera that can detect the presence of items; Col. 18, lines 20-24, which is transmitted to the management circuitry);
a user computing device (344 and or display screen 454) that transmits a configuration file to the repository controller (457) and produces the notification of the presence of the item in the repository (Col. 17, lines 5-6; display 454 is a user interface which may also be considered a user device for notifying the presence of an item), the configuration file configures an identification system (458) having a sensor that generates a characteristic signal corresponding to a characteristic of an item in a repository (Col. 19, lines 28-30);
claim 10) the sensor of the identification system comprises a sensor selected the group consisting of a camera, a vibration sensor, a scale, an optical detector, radar sensor, laser sensor, infrared sensor, audio sensor, and a radio frequency identification sensor (reader 458 may be camera, Page 19, line 28);
claim 11) the artificial intelligence circuit comprises an intelligent driver, an input/output component, a processor, and a memory (driver, input/output component, processor, and memory are inherently included in the management circuit 457 that employs a database and machine learning algorithms to determine the identity of objects based on sensed images, input/output component may include the receiver/transceiver; Page 18, lines 19-20); and
claim 13) the artificial intelligence circuit is in the user computing device (the user device may include the display screen 454 of the container or deposition unit (see Fig. 4; Page 18, lines 15-17, the management control circuitry performs the analysis of the images using the machine learning algorithms, Page 20, lines 10-20; This selection may be based on information provided to the management circuitry by the reader or based on information provided by the user via a touch screen, Page 21, lines 10-12).
Williams teaches the: identification system, the artificial intelligence circuit; the sensor consists of: an audio, optical, vibration, or electro/magnetic sensor, or a scale; and the artificial intelligence circuit comprising an intelligent driver, input/output component, processor, and memory described above, for the purpose of providing an improved reusable delivery container that can ensure secure delivery of valuable items, eliminates the need to be transported back to a delivery depot, and reduces environmental impact (Page 1, lines 20-25 and lines 29-30; Page 2, lines 24-26).
It would have been obvious to one of ordinary skill in the art on or before the time of the filing to modify the system of Williams with the identification system, the artificial intelligence circuit; the sensor consists of: an audio, optical, vibration, or electro/magnetic sensor, or a scale; and the artificial intelligence circuit comprising an intelligent driver, input/output component, processor, and memory described above, as taught in Williams for the purpose of providing an improved reusable delivery container that can ensure secure delivery of valuable items, eliminates the need to be transported back to a delivery depot, and reduces environmental impact.
Relative to claim 22, Kutus in view of Williams does not expressly disclose: the configuration file configures the artificial intelligence circuit to construct a model based on historical input data from the indicator signal corresponding to item identification characteristics.
Williams discloses machine learning algorithms trained to identify an item or item condition from characteristic signals, such as from images from the reader camera 458, and further teaches the use of historical item information, such as known dimensions and/or weights associated with identified items (Page 23, lines 12-29).
For example, upon identifying an item as a known product (such as an iPhone 8, Williams determines the corresponding dimensions of the iPhone 8 from the stored data (Page 23, lines 20-25). This teaching evidences construction and use of a model based on historical input data corresponding to item identification parameters. Under the broadest reasonable interpretation, configuring the artificial intelligence circuit to construct the model includes training relationships used by the machine learning system from historical data.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Kutus in view of Williams so that the configuration file configures the artificial intelligence circuit to construct a model based on historical input data, since the system of Williams identifies an item as a known product and determines the corresponding dimensions of the items from the stored data, which evidences construction and use of a model based on historical input data corresponding to item identification parameters.
Claim(s) 14, 16-18, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over Williams in view of Sengstaken (US Patent No. 11,250,652). Relative to claims 14, 16-18, and 20 Williams discloses all claim limitations mentioned above, including:
claim 14) A method comprising:
pairing a user computing device and a repository controller (transceiver 20 may exchange data communications with user device 344; Page 8, lines 18-21; Col. 17, lines 5-13);
entering a configuration mode by the repository controller (control circuitry or management circuitry 24, 224, 457 that exchanges data with the receiver/transceiver 20, control circuitry is configured to exchange information wirelessly with the user device 344 (Page 8, lines 11-12, Page 16, lines 30-34)(Fig. 3);
receiving configuration information at the user computing device (user device exchanges information with the container through the transceiver and control circuitry; Page 17, lines 1-7);
generating a configuration file by the user computing device (inherently included during exchange of data between the user device and the container’s control circuitry and transceiver; Page 16, lines 30-32, Page 17, lines 5-10, Page 19, lines 14-18; see Fig. 3);
transmitting the configuration file from the user computing device to the repository controller (inherently included during exchange of data between the user device and the container’s control circuitry and transceiver; Page 16, lines 30-32, Page 17, lines 5-10, Page 19, lines 14-18; see Fig. 3);
configuring the repository controller (24, 224, 457 etc.) to use communication protocols defined in the configuration file (inherently included in the data exchange with the user device and control circuitry through the wireless communications network, Page 16, lines 25-30);
entering a learning mode by a repository system (Page 20, lines 10-20);
transmitting a first control message from the repository controller to the repository system, the first control message comprises communication protocols (inherently included in the data exchange between various components including the transceiver, control and/or management circuitry, display and user device through the wireless communications network, Page 16, lines 25-30);
learning by the repository system from the first control message to use the communication protocols to communicate with the repository controller (inherently included in communications between the management circuitry 457 that communicates wirelessly with various components, and employs a database and images to identify the items, Page 20, lines 10-20);
transmitting a second control message from the repository controller (see management circuitry 457) to the repository system; and
artificially learning item characteristics with the repository system (Page 20, lines 10-20), the second control message configures an identification system (458) having a sensor that generates a characteristic signal corresponding to a characteristic of an item in a repository (inherently included, communications between the management circuitry 457 communicate wirelessly with various components of the container system, and employ a database and machine learning algorithms to identify the items based on images, Page 20, lines 10-20);
Claim 16) the second control message configures an artificial intelligence circuit that receives from at least one sensor a characteristic signal and that transmits an indicator signal indicative of an item in a repository (inherently included with data exchange between the reader or camara 458 and the management circuitry 457, that employs a database and machine learning algorithms to identify the items based on images, Page 20, lines 10-20); and
Claim 17) the second control message configures an indicator circuit that receives from an artificial intelligence circuit an indicator signal and that indicates an item in a repository based on the indicator signal (inherently included with data exchange between the reader or camara 458 and the management circuitry 457, that employs a database and machine learning algorithms to identify the items based on images, Page 20, lines 10-20); and
claim 20) the configuration instructions are for identifying envelopes or packages.
Williams does not expressly disclose:
14) configuring the repository controller to use radio frequency characteristics defined in the configuration file;
the transmitted first control message from the repository controller to the repository system comprises radio frequency characteristics;
learning by the repository system from the first control message to use the radio frequency characteristics to communicate with the repository controller;
claim 18) learning by the repository system from the first control message includes learning to use only the communication protocols and radio frequency characteristics of the first control message to communicate with the repository controller.
Sengstaken teaches:
claim 14) configuring the repository controller (see 156) to use radio frequency characteristics defined in the configuration file (Col. 7, lines 1-11; Col. 8, lines 8-11, Col. 8, lines 25-27);
the transmitted first control message from the repository controller (156) to the repository system comprises radio frequency characteristics (Col. 8, lines 8-11, Col. 8, lines 25-27), for the purpose of providing a smart delivery receptacle that detects and securely reports wirelessly on whether a package has been delivered to aid in tracking/determining thefts thereby improving overall satisfaction of delivery recipients. (Col. 3, lines 61-65).
It would have been obvious to one of ordinary skill in the art on or before the time of the filing to modify the method of Williams so that the repository controller is configured to use radio frequency characteristics defined in the configuration file, and transmitting the first control message using radio frequency characteristics as taught in Sengstaken for the purpose of providing a smart delivery receptacle that detects and securely reports wirelessly on whether a package has been delivered to aid in tracking/determining thefts thereby improving overall satisfaction of delivery recipients.
Relative to claim 14, Williams in view of Sengstaken does not expressly disclose the second control message comprises configuration instructions. Williams in view of Sengstaken can be modified so that the second control message comprises configuration instructions as an obvious matter of design choice.
As mentioned above, Williams discloses transmitting a second control message from the repository controller to the repository system and artificially learning item characteristics with the repository system (the management circuitry 457 of the container 10 communicates wirelessly with other various components of the container 10 to perform various functions, including obtaining images from a reader 458 communicating the images to the management circuit, and applying machine learning algorithms to identify the items and condition of the items based on images, Page 20, lines 10-20; Col. 23, lines 12-15).
Providing configuration instructions from the repository controller, which is included in the management circuitry, to the repository system described above is both well-known and implicit in computing devices that connect or communicate to another device in the art of network communications and is the foundation of networking and device communication. The computing device, such as the management circuitry or controller 457, exchanges various information with the transceiver 20, reader 458, transmitter, display, and user device 344, through wireless communications in a network (Page 7, lines 25-26; See also communication between several components in the network in Fig. 3). See MPEP §2144.01, §2144.03.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Williams in view of Sengstaken so that the second control message comprises configuration instructions as an obvious matter of design choice since providing configuration instructions from a computing device such as the management circuitry 457, to various other devices within a network is both implicit and well-known and is the foundation of networking and device communication.
Relative to claims 14 and 18, Williams in view of Sengstaken discloses all claim limitations mentioned above, including: the learning by the repository system from the first control message uses characteristics received/transmitted by the transceiver 20 to communicate with the repository controller (Williams, Page 8, lines 19-20, Page 20, lines 10-20), and learning by the repository system from the first control message includes learning to use only the communication protocols of the first control message to communicate with the repository controller (Williams, Page 16, lines 26-29; Page 20, lines 10-20, see communication between the control and/or management circuit, transceiver, display, and user device).
Williams in view of Sengstaken does not expressly disclose:
the learning by the repository system from the first control message uses the radio frequency characteristics to communicate with the repository controller; or
learning by the repository system from the first control message includes learning to use only the communication protocols and radio frequency characteristics of the first control message to communicate with the repository controller.
Williams in view of Sengstaken can be modified so that: the learning by the repository system from the first control message uses the radio frequency characteristics to communicate with the repository controller; and
learning by the repository system from the first control message includes learning to use only the communication protocols and radio frequency characteristics of the first control message to communicate with the repository controller, as an obvious matter of design choice based on the user’s preference.
The system of William teaches the communication between the management or control circuitry and the transceiver 20 comprises an RF transceiver (Page 8, lines 18-21). It is obvious to modify the transceiver 20 to include an RF transceiver so that the learning by the repository system from the first control message uses the radio frequency characteristics to communicate with the repository controller as a matter of design choice, since an RF transceiver is a type of transceiver and is commonly used in various wireless communications systems, such as Wi-Fi and Bluetooth, both of which the disclosure includes; Page 8, lines 14-20). See MPEP §2144.03.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Williams in view of Sengstaken to include an RF transceiver so that the learning by the repository system from the first control message uses the radio frequency characteristics to communicate with the repository controller as a matter of design choice, since an RF transceiver is a type of transceiver and is commonly used in various wireless communications systems).
Claim(s) 19 is/are rejected under 35 U.S.C. 103 as being unpatentable over Williams in view of Sengstaken, Jr. as applied to claim 14 above, and further in view of Farris et al (US PG. Pub. 2016/0033966). Relative to claim 19, the disclosure of Williams in view of Sengstaken discloses all claim limitations mentioned above, but does not expressly disclose: the configuration file comprises customer profile information and associated repository configuration preferences.
Farris teaches: the configuration file comprises customer profile information (customer or user 102 directly inputs information into homing device 128 and/or computing device 102, this customer specific information is stored in a database 110 which includes log-in credentials, user location, transaction history, payment and billing information, computing device used, etc., all of this can be considered customer profile information, Para. 0032-0034); and associated repository configuration preferences (for instance, user may choose a form of notification such as email, text, etc., user may also select a particular package type for the container 202; see Para. 0064; Para. 0089-0091) for the purpose of providing a drone delivery system for performing delivery and pickup of a parcels securely and accurately, without human involvement (Para. 0002; 0010).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system of Williams in view of Sengstaken so that the configuration file comprises customer profile information and associated repository configuration preferences, as taught in Farris for the purpose of providing a drone delivery system for performing delivery and pickup of a parcels securely and accurately, without human involvement.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to YOLANDA RENEE CUMBESS whose telephone number is (571)270-5527. The examiner can normally be reached M-F 10-6.
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/YOLANDA R CUMBESS/Primary Examiner, Art Unit 3651
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