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 .
Detailed Action
Claims 1,3-6,8,10-13,16,18 and 19 are currently pending.
Information Disclosure Statement
The information disclosure statements (IDS) submitted on 8/19/2025 and 12/16/2025 have been considered. The submission is in compliance with the provisions of 37 CFR 1.97. Accordingly, an initialed and dated copy of Applicant's IDS form SB08 filed 8/19/2025 and 12/16/2025 are attached to the instant Office action.
Response to Amendment
This action is in response to the amendment filled on 12/19/2025. The amendment has been entered. Claims 1 and 16 have been amended and claims 2,7,9,14,15,17 and 20 have been cancelled. Claims 1,3-6,8,10-13,16,18 and 19 are pending, with claims 1 and 16 being independent in the instant application.
Response to Arguments
Applicant's Arguments/Remarks filed on 07/25/2025 page 6-10 regarding 35 U.S.C. 103 rejections have been fully considered and are found persuasive in view of the amended claims and presented Arguments/Remarks by the Applicant. Specifically, Examiner considers in Arguments/Remarks in page 8 under heading ‘Feature 2’ (stated by Applicants) that He doesn’t teach Feature 2 (in page 6 of Arguments/Remarks): “to correlate the integrated sensor data with the physical geometric model of a physical object or space, and to fuse the integrated sensor data with the physical geometric model to produce a dynamic digital twin”. However, a new ground of rejections is necessitated by Applicant's claim amendments.
Therefore, the previous rejections regarding 35 U.S.C.103 are being amended in this current office action. (See analysis below Claim Rejections-35 U.S.C. 103).
Examiner Notes
Examiner cites particular columns, paragraphs, figures and line numbers in the references as applied to the claims below for the convenience of the applicant. Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the examiner. The entire reference is considered to provide disclosure relating to the claimed invention. The claims & only the claims form the metes & bounds of the invention. Office personnel are to give the claims their broadest reasonable interpretation in light of the supporting disclosure. Unclaimed limitations appearing in the specification are not read into the claim. Prior art was referenced using terminology familiar to one of ordinary skill in the art. Such an approach is broad in concept and can be either explicit or implicit in meaning. Examiner's Notes are provided with the cited references to assist the applicant to better understand how the examiner interprets the applied prior art. Such comments are entirely consistent with the intent & spirit of compact prosecution.
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.
The factual inquiries set forth in Graham, v. John Deere Co., 383 U.S.1.148 USPQ 459 (1966), that are applied for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or non-obviousness.
7. Claims 1,4,5,10-13,16,18 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over NPL “From Surveillance to Digital Twin: Challenges and recent advances of signal processing for the industrial Internet of Things” by Yuan He et al. (hereinafter He, Date of publication: 28 August 2018), in view of a conference paper “Recognising Activities in Real Time Using Body Worn Passive Sensors With Sparse Data Streams: To Interpolate or Not To Interpolate?” by Asanga Wickramasinghe et al. (hereinafter Asanga) and a conference paper “A battery-free RFID-based indoor acoustic localization platform” by Yi Zhao et al. (hereinafter Zhao, published in 2013) and further in view of JEON et al. (Pub. No. US2016/0330182A1) (hereinafter Jeon, IDS provided dated 3/9/2023) and an NPL “Digital twin for adaptation of robots’ behavior in flexible robotic assembly lines Author links open overlay panel” by Niki Kousi et al. (hereinafter Kousi, NPL available online 25 January 2019).
Regarding claim 1, He teaches a system for constructing a dynamic digital twin, (He disclosed in page 120 (1st para, before the ‘Introduction’): “In this article, we survey the promising industrial applications of IoT technologies and discuss the challenges and recent advances in this area. We also share our early experience with Pavatar, a real-world industrial IoT system that enables comprehensive surveillance and remote diagnosis for ultrahigh-voltage converter station (UHVCS).” In page 126 heading ‘Case study: Pavatar’ (right col.): “Pavatar is an IoT system for UHVCS management. … Aiming to build a digital twin of this UHVCS, Pavatar monitors the entire operation process in real time and provides decisions and support for UHVCS administrators.”).
He teaches the system comprising: at least one battery-less passive RFID sensor configured to monitor at least one physical parameter in real time; (He disclosed in page 125 heading ‘Cross-technology heterogeneous wireless communication’ (left col.): “In digital twin for smart factories, embedded sensors with various sensing capabilities are networked together to monitor the same area. These sensors might adopt heterogeneous wireless communication technologies, … High-density deployment: In many cases, networked sensors are densely deployed, which induces nontrivial challenges in collecting data in real time. Interconnecting heterogeneous devices: Due to the complicated operating states of industrial machinery, multiple devices need to exchange information in suit for a real-time understanding of current states.”).
He teaches a plurality of readers configured to wirelessly read sensor data produced by the at least one battery-less passive RFID sensor, (He disclosed in page 122 (1st para, left col. under heading ‘Wireless and battery-free sensing’: “Wireless and battery-free sensing, e.g., radio-frequency identification (RFID), which leverages backscattered radio-frequency signals to carry information, has received plenty of attention in the past few years, due to its low-cost, nonintrusive, and easy-deployment properties. A typical RFID system, as shown in Figure 1, consists of RFID tags that store information in nonvolatile memories, and two-way radio transmitter–receivers called RFID readers that send signals to tags and receive their responses. Recent advances in RFID offer a promising technique for cross-modal sensing where many physical metrics are sampled with only battery-free devices and wireless signals …”).
He teaches a gateway in communication with each reader, wherein the gateway is configured to acquire the sensor data from each reader, (Applicant of this current Application stated in Specification para [0028]: “the gateway can also include a processor, and can process data by integrating data from multiple readers”
He disclosed in page 125 heading ‘Cross-technology heterogeneous wireless communication’ (left col.): “Today, how to organize, manage, and cooperate heterogeneous IoT devices is increasingly drawing attention. A simple solution is to deploy a gateway with various radio interfaces for access control and information exchange among heterogeneous devices.” It has been discussed in page 126 heading ‘Case study: Pavatar’ (right col.) that a real-world industrial IoT system ‘Pavatar’ is introduced. Pavatar is an IoT system for UHVCS management. Figure 4 shows the architecture of Pavatar. Pavatar collects data from both built-in and ambient sensors in UHVCSs. Typical internal sensor readings include temperature, pressure, vibration, rotation, etc., which provide the key metrics for decision making. This disclosure “Pavatar is an IoT system; Pavatar collects data from both built-in and ambient sensors in UHVCSs” (ultrahigh-voltage converter station) corresponds to the claim limitation).
He teaches an internet of things hub in communication with the gateway, wherein the gateway is arranged to communicate the integrated sensor data to the internet of things hub; (He disclosed in page 125 heading ‘Cross-technology heterogeneous wireless communication’ (left col.): “Today, how to organize, manage, and cooperate heterogeneous IoT devices is increasingly drawing attention. A simple solution is to deploy a gateway with various radio interfaces for access control and information exchange among heterogeneous devices. …”. It has been discussed in page 126 heading ‘Case study: Pavatar’ (right col.) that a real-world industrial IoT system ‘Pavatar’ is introduced. Pavatar is an IoT system for UHVCS management. Figure 4 shows the architecture of Pavatar. Pavatar collects data from both built-in and ambient sensors in UHVCSs. Typical internal sensor readings include temperature, pressure, vibration, rotation, etc., which provide the key metrics for decision making. This disclosure “Pavatar is an IoT system; Pavatar collects data from both built-in and ambient sensors in UHVCSs” (ultrahigh-voltage converter station) corresponds to the claim limitation).
He teaches data storage storing a physical geometric model of a physical object or space correlating with the at least one battery-less passive RFID sensors; (He disclosed in page 122 (at left col. 1st para): “A typical RFID system, as shown in Figure 1, consists of RFID tags that store information in nonvolatile memories, and two-way radio transmitter–receivers called RFID readers that send signals to tags and receive their responses. Recent advances in RFID offer a promising technique for cross-modal sensing where many physical metrics are sampled with only battery-free devices and wireless signals …”. The disclosure “RFID system (shown in Fig. 1) consists of RFID tags that store information in nonvolatile memories” corresponds to the claim limitation “storing a physical geometric model of a physical object or space correlating with the battery-less passive RFID sensors”).
He teaches a processor in communication with the internet of things hub and the data storage, the processor programmed to receive the integrated sensor data from the internet of things hub and physical geometric model data from the data storage, (He disclosed in page 122 (at left col. 1st para): “A typical RFID system, as shown in Figure 1, consists of RFID tags that store information in nonvolatile memories, and two-way radio transmitter–receivers called RFID readers that send signals to tags and receive their responses. Recent advances in RFID offer a promising technique for cross-modal sensing where many physical metrics are sampled with only battery-free devices and wireless signals …”. In page 126 heading ‘Case study: Pavatar’ (right col.): “Figure 4 shows the architecture of Pavatar. Pavatar collects data from both built-in and ambient sensors in UHVCSs. Typical internal sensor readings include temperature, pressure, vibration, rotation, etc., … In the surrounding environment, low-power and battery-free sensors are deployed to sense temperature, humidity, noise, air quality, and liquid leakage, etc., as supplementary information … The high-frequency and big-volume stream data are collected and transmitted through heterogeneous networks to fulfill upper-level applications …”. The disclosure “high-frequency and big-volume stream data are collected and transmitted through heterogeneous networks” corresponds to the claim limitation “processor programmed to receive the integrated sensor data from the internet of things hub”).
However, He doesn’t explicitly teach the limitation “the sensor data comprises interpolated values calculated between discrete sensor readings via a simulation engine configured to continuously interpolate between discrete data states produced by the sensor data;”
wherein Asanga teaches the sensor data comprises interpolated values calculated between discrete sensor readings via a simulation engine configured to continuously interpolate between discrete data states produced by the sensor data; and integrate the determined sensor location and the sensor data from each reader; (Asanga disclosed in page 5 section 3.3: “We denote the ith sensor observation si at time ti, where si is the 5-tuple obtained for each sensor observation … using the pair (ti, si) then sequence of received sensor observations … We interpolate the sensor observations within a given segment to obtain a data stream segment with a regular sampling rate. … the dynamic sensor data augmentation algorithm in Algorithm 1 that considers a sequence of sensor observations … to interpolate the ith segment. Different interpolants require different number of minimum data points, N, for successful interpolation. … we augment the sensor data stream by replicating the furthest sensor observation (ts, ss) from (ti, si), where (ts < ti), at time steps of δt from ts until the required number of samples for interpolation is obtained (line 5 in Algorithm 1). For example, if a single sensor observation needs to be augmented, then it is augmented as (ts−1, ss−1) = (ts − δt, ss).” The disclosure above “the dynamic sensor data augmentation algorithm shown in Algorithm 1 considers a sequence of sensor observations, in order to interpolate the ith sensor observation segment; the sensor data stream augmented by replicating the furthest sensor observation, at time steps of δt from ts until the required number of samples for interpolation is obtained” reads the whole claim limitation. The augmentation algorithm shown in Algorithm 1 teaches the claim limitation “integrate the determined sensor location and the sensor data from each reader”).
He and Asanga are analogous art because they are related to have lightweight, battery-less computing platforms having sensor enabled RFID tags creating prospects for sensor-based applications. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He and Asanga to modify reading sensor data wirelessly using CTC (cross-technology communication) heterogeneous devices can directly exchange information for fast and effective control and cooperation, satisfies the timeliness and interconnection requirements in industrial IoT in He’s disclosure (in page 125). A finding that one of ordinary skill in the art could have to include the teaching of Asanga to achieve/get interpolated values of sensor data streams. The suggestion/motivation for doing so would have been obvious by Asanga because “In this study, we propose an approach that reduces online interpolation errors to facilitate interpolating sparse acceleration data streams from a passive RFID tag with an on-board accelerometer sensor. We demonstrate that for these types of sensors, features readily available from a typical RFID platform can be successfully used instead of features extracted from an interpolated data stream to achieve similar or better activity recognition performance without preprocessing and, whilst, using significantly less number of features.” (Asanga disclosed in page 1 under ‘Abstract’).
Neither He nor Asanga explicitly teaches the limitations “determine a location of the at least one battery-less passive RFID sensor based on triangulation performed using the sensor data acquired from each reader,”
Zhao teaches determine a location of the at least one battery-less passive RFID sensor based on triangulation performed using the sensor data acquired from each reader, (Zhao disclosed in page 2 section II (left col.): “Our RFID localization system uses programmable EPC Gen2 UHF tags (WISP) … A passive WISP tag is localized by measuring the ToA of three ultrasounds signal transmitted … Three tag-beacon distances (dT1-dT3) are obtained based on this measurement and the location of the tag can further be computed using trilateration.” In page 4 same section disclosed: “from Figure 5, we can see that dTi refers to the distance between the WISP Rx and transmitter i, and we use … the time difference of ultrasound propagation between distance dTi and dTj (Equation (2)). Generally, the WISP Rx will not be placed in between any two of the transmitters i,j, then because of the trigonometric conditions, … So in order to improve the system accuracy, we use a first order polynomial line fit model to matching dTi and TRi. The line fit model is pre-trained by several tested data with known location and can be expressed as dTi = ai x dTi +bi (i = 1,2,3). Finally, we can calculate the position of WISP Rx with these calculated distances using triangulation.”).
He, Asanga and Zhao are analogous art because they are related in designing digital twin. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga and Zhao, to modify reading sensor data wirelessly using CTC (cross-technology communication) heterogeneous devices can directly exchange information for fast and effective control and cooperation, satisfies the timeliness and interconnection requirements in industrial IoT in He’s disclosure (in page 125). A finding that one of ordinary skill in the art could have to include the teaching of Zhao to achieve/get the location of battery-less passive RFID sensor based on triangulation performed using the sensor data. The suggestion/motivation for doing so would have been obvious by Zhao because “This paper presents a working prototype of a RFID-based system that localizes a custom battery-free, EPC Gen2-compatible UHF tag. The system uses the RFID communication channel for synchronization and inventory, and acoustic propagation delays for distance measurement. This paper presents a novel high-precision RFID localization system based on acoustic ToA. The system can locate a battery-free EPC Gen2 UHF WISP tag with ultrasound detectors using a commercial reader and three acoustic reference beacons. (Zhao disclosed in page 1 and 8 under headings ‘Abstract’ and ‘Conclusion’).
However, He, Asanga and Zhao do not explicitly teach the limitations “a server in communication with the internet of things hub, the server hosting the digital twin; and wherein the internet of things hub, the data storage, and the processor are provided on a server in a local area network.
and Jeon teaches a server in communication with the internet of things hub, the server hosting the digital twin; (Jeon disclosed in page 13 para [0197]: “The management server 635 and/or the server 645 may store or analyze a signal received from the communication network 631. The management server 635 and/or the server 645 may transmit the analysis result to at least one of the IoT devices 610, 620, 630, and 640 via the communication network 631. The management server 635 may manage the states of the hub 200, the gateway 625, the communication network 631, and/or the IoT devices …”. In para [0058 and 0059] discussed that FIG. 1 is a block diagram of an internet of things (IoT) network system includes a hub, a first and second controller, and an IoT device, further the hub and the IoT device may perform the device pairing according to the control of the first and second controller. Therefore, this disclosure corresponds to the claim element “digital twin”, since an IoT network system may include an IoT device, a hub, an access point, a gateway, a communication network, and/or a server, therefore it is concluded that “a server in communication with the internet of things hub, the server hosting the digital twin”).
and wherein Jeon teaches the internet of things hub, the data storage, and the processor are provided on a server in a local area network. (Jeon disclosed in page 13 para [0197]: “The management server 635 and/or the server 645 may store or analyze a signal received from the communication network 631. The management server 635 and/or the server 645 may transmit the analysis result to at least one of the IoT devices 610, 620, 630, and 640 via the communication network 631. The management server 635 may manage the states of the hub 200, the gateway 625, the communication network 631, and/or the IoT devices …”. In page 18 para [0277]: “The IoT device application 1310, as a software component, may control the communication module 1320 and may be executed by a CPU of the IoT device 1300. The CPU may be included in the processing circuit 230, 330, 450, or 530 such as an AP. The communication module 1320 may be a modem communication connectable to LAN, … or mobile cellular network.”).
He, Asanga, Zhao and Jeon are analogous art because they are related in designing digital twin. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao and Jeon to modify communication between Internet of Things (IoT) with the reader/sensor of He, to include the communication between Internet of Things, gateway, reader and HTTP protocol of Jeon. The suggestion/motivation for doing so would have been obvious by Jeon because “The IoT network system 100B may also include a gateway 625. The gateway 625 may connect the hub 200, which functions as an access point, to an external communication network. One of the IoT devices 610, 620, 630, and 640 may function as the gateway 625. For instance, a smart phone may be both an IoT device and the gateway 625. The smart phone may be connected to a mobile cellular network. (Jeon disclosed in page 13 para [0193-0194]).
However, the abovementioned prior arts He, Asanga, Zhao and Jeon do not explicitly teach the limitations: “to correlate the integrated sensor data with the physical geometric model of a physical object or space, and to fuse the integrated sensor data with the physical geometric model to produce a dynamic digital twin; wherein the physical geometric model is a computer aided design model of the physical space or object;”
Kousi teaches to correlate the integrated sensor data with the physical geometric model of a physical object or space, and to fuse the integrated sensor data with the physical geometric model to produce a dynamic digital twin; (Kousi disclosed in page 121 heading ‘Abstract’: “The suggested digital world model infrastructure involves three main functionalities: a) Virtual representation of the shopfloor, combining multiple sensor data and CAD models. The digital shopfloor is rendered in the 3D environment exploiting the capabilities provided by Robot Operating System (ROS) framework, … and c) Dynamic update of the digital twin based on real time sensor and resource data coming from the actual shopfloor. The communication and integration layer among the physical and the virtual agents is realized on top of the ROS framework.” In page 123-124 section 3: “As visualized in Fig. 1. four subcomponents are deployed under the suggested Digital Twin infrastructure: a) Resource Manager, b) Sensor Manager, c) Layout Manager and d) 3D environment constructor. … Two sub-components, namely the Resource location monitoring and Resource status monitoring are responsible for real-time monitoring the status and location of each mobile resource and update online the actual values in Digital Twin. As visualized in Fig. 2a specific ROS topics and services are initiated for each subscribed resource broadcasting their real time related data. The Sensor Manager is responsible for interfacing with the existing sensors’ ROS drivers and registering their configuration data in Digital Twin repository using the unified data model format. … To facilitate the use of standard motion and path planning algorithms … the 2D-3D sensor data combination module allows to easily and dynamically (merge multiple, sensor data into one topic. To efficiently represent the entire shopfloor, the static layout needs to be represented inside the Digital Twin. The Layout Manager is responsible for the control and storage of all CADs files related to static fixtures, parts and products in .sdf format … This component allows the user to upload the CAD file and configure various parameters concerning: a) the parts involved in the process, b) the stationary fixtures included in the shopfloor. The final component in the process chain is the 3D environment constructor (Fig. 2c). This component retrieves the locations of all parts, fixtures, sensors and resources to construct an environment with a global world frame … Fig. 3. represents the unified data model implemented under the deployed infrastructure. The used color coding maps the consumed data structures by the developed sub-components under the Digital Twin as presented in Fig. 1.”).
wherein Kousi teaches the physical geometric model is a computer aided design model of the physical space or object; (Kousi disclosed in page 121 section 2: “Virtual representation of the shopfloor using resource related information (Resource Manager), multiple sensor data combination (Sensor Manager) and CAD models (Layout Manager). The information is continuously updated through a network of services by all resources and sensors creating a synthesis of all perception data.
• A unified semantic data model is implemented in order to semantically represent the geometrical as well as the workload state. This data model should be generic enough to be able to address multiple cases as well as to be consumed by multiple components inside execution system.” In page 124 (1st para): “To efficiently represent the entire shopfloor, the static layout needs to be represented inside the Digital Twin. The Layout Manager is responsible for the control and storage of all CADs files related to static fixtures, parts and products in .sdf format defining also the collisions, the inertia and the mass parameters. This component allows the user to upload the CAD file and configure various parameters concerning: a) the parts involved in the process, b) the stationary fixtures included in the shopfloor.”).
He, Asanga, Zhao, Jeon and Kousi are analogous art because they are related in designing digital twin. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao, Jeon and Kousi to modify data storage storing a geometric model of a physical object or space relating sensor of He, to include Kousi’s teaching to fuse/integrate the sensor data with the geometric model (e.g., CAD model) to produce a digital twin. The suggestion/motivation for doing so would have been obvious by Kousi because “The latest trends in EU manufacturing foster the deployment of hybrid production systems where humans can coexist and cooperate with mobile multi-arm robots. Such flexible robot workers should be able to perceive their environment in terms of process requirements and human activity. Driven by this need, the Digital Twin system presented in this work, provides the infrastructure for integrating all the hardware components involved in the assembly and synthesizing all the data coming from the shopfloor under a unified common environment. Upon this model, each resource applies cognition techniques to transform the sensor data into usable information and eventually to knowledge of the shop floor status.” (Kousi disclosed in page 126 section 5).
Regarding Claim 4, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 1, however He, Asanga, Zhao, and Kousi do not explicitly teach the limitation “communications between the plurality of readers and the gateway and between the gateway and the internet of things hub are provided using Message Queue Telemetry Transport (MQTT)”.
wherein Jeon teaches communications between the plurality of readers and the gateway and between the gateway and the internet of things hub are provided using Message Queue Telemetry Transport (MQTT). (Jeon disclosed in page 12 para [0185-0186]: “The IoT may refer to a network of IoT devices that use wired and/or wireless communication. Accordingly, the IoT may be referred to as an IoT network system, a ubiquitous sensor network (USN) communication system, a machine type communication (MTC) system, … Here, an IoT network system may include elements, such as, an IoT device, a hub, an access point, a gateway, a communication network, and/or a server. … The IoT network system may use a user datagram protocol (UDP), … a message queue telemetry transport (MQTT), or an MQTT for sensors networks (MQTT-S) for exchange (or communication) of information among at least two elements therewithin.”).
He, Asanga, Zhao and Jeon are analogous art because they are related in designing digital twin. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao and Jeon to modify communication between Internet of Things (IoT) with the reader/sensor of He, to include the communication between Internet of Things, gateway, reader and HTTP protocol of Jeon. The suggestion/motivation for doing so would have been obvious by Jeon because “The IoT network system 100B may also include a gateway 625. The gateway 625 may connect the hub 200, which functions as an access point, to an external communication network. One of the IoT devices 610, 620, 630, and 640 may function as the gateway 625. For instance, a smart phone may be both an IoT device and the gateway 625. The smart phone may be connected to a mobile cellular network. (Jeon disclosed in page 13 para [0193-0194]).
Regarding Claim 5, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 1, however He, Asanga, Zhao, and Kousi do not explicitly teach the limitation “communications between the plurality of readers and the gateway and between the gateway and the internet of things hub are provided using HTTP/HTTPS protocol”.
wherein Jeon teaches communications between the plurality of readers and the gateway and between the gateway and the internet of things hub are provided using HTTP/HTTPS protocol. (Jeon disclosed in page 12 para [0185-0186]: “The IoT may refer to a network of IoT devices that use wired and/or wireless communication. Accordingly, the IoT may be referred to as an IoT network system, a ubiquitous sensor network (USN) communication system, a machine type communication (MTC) system, … Here, an IoT network system may include elements, such as, an IoT device, a hub, an access point, a gateway, a communication network, and/or a server. … The IoT network system may use a user datagram protocol (UDP), … a hypertext transfer protocol (HTTP), … for exchange (or communication) of information among at least two elements therewithin.”).
He, Asanga, Zhao and Jeon are analogous art because they are related in designing digital twin. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao and Jeon to modify communication between Internet of Things (IoT) with the reader/sensor of He, to include the communication between Internet of Things, gateway, reader and HTTP protocol of Jeon. The suggestion/motivation for doing so would have been obvious by Jeon because “The IoT network system 100B may also include a gateway 625. The gateway 625 may connect the hub 200, which functions as an access point, to an external communication network. One of the IoT devices 610, 620, 630, and 640 may function as the gateway 625. For instance, a smart phone may be both an IoT device and the gateway 625. The smart phone may be connected to a mobile cellular network. (Jeon disclosed in page 13 para [0193-0194]).
Regarding Claim 10, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 1, however He, Asanga, Zhao, and Jeon do not explicitly teach the limitation “the physical geometric model is a geographic map”.
wherein Kousi teaches the physical geometric model is a geographic map. (Kousi disclosed in page 125 (2nd and 3rd para) section 3: “The path planning component interface that was implemented is based on ROS navigation stack for mobile robots. In particular the Digital Twin provides: … c) the global map of the shopfloor–3D map created in occupancy grid … For ensuring a collision free trajectory of the robot, the Digital Twin provides global planning scene with all the objects and resources. This planning scene is published as an occupancy map constructed by the 3D environment constructor. This map is then online updated using the available multi-sensor data.”).
He, Asanga, Zhao, Jeon and Kousi are analogous art because they are related in designing digital twin. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao, Jeon and Kousi to modify data storage storing a geometric model of a physical object or space relating sensor of He, to include Kousi’s teaching to fuse/integrate the sensor data with the geometric model (e.g., CAD model) to produce a digital twin. The suggestion/motivation for doing so would have been obvious by Kousi because “The latest trends in EU manufacturing foster the deployment of hybrid production systems where humans can coexist and cooperate with mobile multi-arm robots. Such flexible robot workers should be able to perceive their environment in terms of process requirements and human activity. Driven by this need, the Digital Twin system presented in this work, provides the infrastructure for integrating all the hardware components involved in the assembly and synthesizing all the data coming from the shopfloor under a unified common environment. Upon this model, each resource applies cognition techniques to transform the sensor data into usable information and eventually to knowledge of the shop floor status.” (Kousi disclosed in page 126 section 5).
Regarding Claim 11, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 1, however, He, Zhao, Jeon and Kousi do not explicitly teach the limitation “the physical geometric model comprises a location of each of the plurality of passive RFID sensors”.
wherein Asanga teaches the physical geometric model comprises a location of each of the plurality of passive RFID sensors. (Asanga disclosed in page 5 section 3.3: “We denote the ith sensor observation si at time ti, where si is the 5-tuple obtained for each sensor observation … using the pair (ti, si) then sequence of received sensor observations … We interpolate the sensor observations within a given segment to obtain a data stream segment with a regular sampling rate. … the dynamic sensor data augmentation algorithm in Algorithm 1 that considers a sequence of sensor observations … to interpolate the ith segment. Different interpolants require different number of minimum data points, N, for successful interpolation. … we augment the sensor data stream by replicating the furthest sensor observation (ts, ss) from (ti, si), where (ts < ti), at time steps of δt from ts until the required number of samples for interpolation is obtained (line 5 in Algorithm 1).” The location of each of the plurality of passive RFID sensors is determined in sensor data augmentation algorithm in Algorithm 1 that considers a sequence of sensor observations, as discussed above).
He, Zhao, Jeon, Kousi and Asanga are analogous art because they are related to have lightweight, battery-less computing platforms having sensor enabled RFID tags creating prospects for sensor-based applications. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Zhao, Jeon, Kousi and Asanga to modify reading sensor data wirelessly using CTC (cross-technology communication) heterogeneous devices can directly exchange information for fast and effective control and cooperation, satisfies the timeliness and interconnection requirements in industrial IoT in He’s disclosure (in page 125). A finding that one of ordinary skill in the art could have to include the teaching of Asanga to include interpolated values of sensor data streams. The suggestion/motivation for doing so would have been obvious by Asanga because “In this study, we propose an approach that reduces online interpolation errors to facilitate interpolating sparse acceleration data streams from a passive RFID tag with an on-board accelerometer sensor. We demonstrate that for these types of sensors, features readily available from a typical RFID platform can be successfully used instead of features extracted from an interpolated data stream to achieve similar or better activity recognition performance without preprocessing and, whilst, using significantly less number of features.” (Asanga disclosed in page 1 under ‘Abstract’).
Regarding Claim 12, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 1, however, He, Asanga, Zhao and Jeon do not explicitly teach the limitation “the processor is further programmed to provide a simulation model and to incorporate the sensor data in the simulation model”.
wherein Kousi teaches the processor is further programmed to provide a simulation model and to incorporate the sensor data in the simulation model. (Kousi disclosed in page 123 (last para) section 3: “The Sensor Manager is responsible for interfacing with the existing sensors’ ROS drivers and registering their configuration data in Digital Twin repository using the unified data model format. All sensorial data are made available to robots’ planners, using a publish/subscribe pattern as a communication mechanism as shown in Fig.2b.” In page 125 (last para) section 3: “For ensuring a collision free trajectory of the robot, the Digital Twin provides global planning scene with all the objects and resources. This planning scene is published as an occupancy map constructed by the 3D environment constructor. This map is then online updated using the available multi-sensor data.” In page 125-126 section 4: “The proposed system has been implemented and tested in a case study from the automotive sector for the assembly of a vehicle’s front axle. … b) static obstacles and moving humans/obstacles for ensuring collision free navigation, using 2D laser scanner data. … To test the functionality of the developed system, the scenario has been set up in GAZEBO physics simulation engine (Fig. 5) using: a) CAD files of LMS Machine Shop for the layout representation, b) ROS virtual controllers of Universal Robots (UR) arms and mobile platform, c) 2D laser scanner data for the 2D map creation d) simulated stereo camera data for virtual object detection …”.
The disclosure above, GAZEBO physics simulation engine (in Fig. 5) corresponds to claim element “simulation model”, which has been used in a case study e.g., automotive sector for the assembly of a vehicle’s front axle, Robot Operating System (ROS) navigation stack for mobile robots used in path and motion planning. In order to ensure a collision free trajectory of the robot, the Digital Twin provides global planning by publishing occupancy map constructed by the 3D environment constructor and this map is then online updated using the available multi - sensor data. Therefore, it is understood from the disclosure above that the sensor data incorporated in the simulation model).
He, Asanga, Zhao, Jeon and Kousi are analogous art because they are related in designing digital twin. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao, Jeon and Kousi to modify data storage storing a geometric model of a physical object or space relating sensor of He, to include Kousi’s teaching to fuse/integrate the sensor data with the geometric model (e.g., CAD model) to produce a digital twin. The suggestion/motivation for doing so would have been obvious by Kousi because “The latest trends in EU manufacturing foster the deployment of hybrid production systems where humans can coexist and cooperate with mobile multi-arm robots. Such flexible robot workers should be able to perceive their environment in terms of process requirements and human activity. Driven by this need, the Digital Twin system presented in this work, provides the infrastructure for integrating all the hardware components involved in the assembly and synthesizing all the data coming from the shopfloor under a unified common environment. Upon this model, each resource applies cognition techniques to transform the sensor data into usable information and eventually to knowledge of the shop floor status.” (Kousi disclosed in page 126 section 5).
Regarding Claim 13, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 1, wherein He teaches the reader is at least one of a Wi-Fi reader, a narrow band internet of things reader, or a wireless communications protocol. (Examiner notes that the claim language includes two optional embodiments, a first embodiment “a Wi-Fi reader”, "or" a second embodiment “a narrow band internet of things reader” "or" a third embodiment “a wireless communications protocol”. Since "and/or" is interpreted as at least one of, only one of the two embodiments need to be taught by the reference.
He disclosed in page 122 heading ‘Wireless and battery-free sensing’ (left col.): “Wireless and battery-free sensing, e.g., radio-frequency identification (RFID), which leverages backscattered radio-frequency signals to carry information, ... A typical RFID system, as shown in Figure 1, consists of RFID tags that store information in nonvolatile memories, and two-way radio transmitter–receivers called RFID readers that send signals to tags and receive their responses.”).
Regarding Claim 16, the same ground of rejection is made as discussed in claim 1 for substantially similar rationale, therefore claim 16 is rejected under 35 U.S.C. 103 as being unpatentable over He, Asanga, Zhao, Jeon and Kousi as discussed above for substantially similar rationale. In addition, claim 16 recites following limitations:
He teaches a method for producing a dynamic digital twin, the method comprising: acquiring real-time sensor data with at least one battery-less passive RFID sensor, (He disclosed in page 120 (1st para, before the ‘Introduction’): “In this article, we survey the promising industrial applications of IoT technologies and discuss the challenges and recent advances in this area. We also share our early experience with Pavatar, a real-world industrial IoT system that enables comprehensive surveillance and remote diagnosis for ultrahigh-voltage converter station (UHVCS).” In page 126 heading ‘Case study: Pavatar’ (right col.): “Pavatar is an IoT system for UHVCS management. … Aiming to build a digital twin of this UHVCS, Pavatar monitors the entire operation process in real time and provides decisions and support for UHVCS administrators.”
In page 125 heading ‘Cross-technology heterogeneous wireless communication’ (left col.): “In digital twin for smart factories, embedded sensors with various sensing capabilities are networked together to monitor the same area. These sensors might adopt heterogeneous wireless communication technologies, … High-density deployment: In many cases, networked sensors are densely deployed, which induces nontrivial challenges in collecting data in real time. Interconnecting heterogeneous devices: Due to the complicated operating states of industrial machinery, multiple devices need to exchange information in suit for a real-time understanding of current states.”).
He teaches transmitting the integrated sensor data from the internet of things hub to a data fusion processor; (He disclosed in page 126 heading ‘Case study: Pavatar’ (right col.): “Figure 4 shows the architecture of Pavatar. Pavatar collects data from both built-in and ambient sensors in UHVCSs. Typical internal sensor readings include temperature, pressure, vibration, rotation, etc., … In the surrounding environment, low-power and battery-free sensors are deployed to sense temperature, humidity, noise, air quality, and liquid leakage, etc., as supplementary information … The high-frequency and big-volume stream data are collected and transmitted through heterogeneous networks to fulfill upper-level applications …”. The disclosure “high-frequency and big-volume stream data are collected and transmitted through heterogeneous networks” corresponds to the claim limitation “transmitting the integrated sensor data from the internet of things hub to a data fusion processor”).
However, He doesn’t explicitly teach the limitation “the sensor data comprises interpolated values calculated between discrete sensor readings via a simulation engine configured to continuously interpolate between discrete data states produced by the sensor data;”
wherein Asanga teaches the sensor data comprises interpolated values calculated between discrete sensor readings via a simulation engine configured to continuously interpolate between discrete data states produced by the sensor data; and integrate the determined sensor location and the sensor data from each reader; (Asanga disclosed in page 5 section 3.3: “We denote the ith sensor observation si at time ti, where si is the 5-tuple obtained for each sensor observation … using the pair (ti, si) then sequence of received sensor observations … We interpolate the sensor observations within a given segment to obtain a data stream segment with a regular sampling rate. … the dynamic sensor data augmentation algorithm in Algorithm 1 that considers a sequence of sensor observations … to interpolate the ith segment. Different interpolants require different number of minimum data points, N, for successful interpolation. … we augment the sensor data stream by replicating the furthest sensor observation (ts, ss) from (ti, si), where (ts < ti), at time steps of δt from ts until the required number of samples for interpolation is obtained (line 5 in Algorithm 1). For example, if a single sensor observation needs to be augmented, then it is augmented as (ts−1, ss−1) = (ts − δt, ss).” The disclosure above “the dynamic sensor data augmentation algorithm shown in Algorithm 1 considers a sequence of sensor observations, in order to interpolate the ith sensor observation segment; the sensor data stream augmented by replicating the furthest sensor observation, at time steps of δt from ts until the required number of samples for interpolation is obtained” reads the whole claim limitation. The augmentation algorithm shown in Algorithm 1 teaches the claim limitation “integrate the determined sensor location and the sensor data from each reader”).
He and Asanga are analogous art because they are related to have lightweight, battery-less computing platforms having sensor enabled RFID tags creating prospects for sensor-based applications. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He and Asanga to modify reading sensor data wirelessly using CTC (cross-technology communication) heterogeneous devices can directly exchange information for fast and effective control and cooperation, satisfies the timeliness and interconnection requirements in industrial IoT in He’s disclosure (in page 125). A finding that one of ordinary skill in the art could have to include the teaching of Asanga to include interpolated values of sensor data streams. The suggestion/motivation for doing so would have been obvious by Asanga because “In this study, we propose an approach that reduces online interpolation errors to facilitate interpolating sparse acceleration data streams from a passive RFID tag with an on-board accelerometer sensor. We demonstrate that for these types of sensors, features readily available from a typical RFID platform can be successfully used instead of features extracted from an interpolated data stream to achieve similar or better activity recognition performance without preprocessing and, whilst, using significantly less number of features.” (Asanga disclosed in page 1 under ‘Abstract’).
Neither He nor Asanga explicitly teaches the limitations “determine a location of the at least one battery-less passive RFID sensor based on triangulation performed using the sensor data acquired from each reader,”
Zhao teaches determining, by the gateway, a location of the at least one battery-less passive RFID sensor based on triangulation performed using the sensor data acquired from each reader, (Zhao disclosed in page 2 section II (left col.): “Our RFID localization system uses programmable EPC Gen2 UHF tags (WISP) … A passive WISP tag is localized by measuring the ToA of three ultrasounds signal transmitted … Three tag-beacon distances (dT1-dT3) are obtained based on this measurement and the location of the tag can further be computed using trilateration.” In page 4 same section disclosed: “from Figure 5, we can see that dTi refers to the distance between the WISP Rx and transmitter i, and we use … the time difference of ultrasound propagation between distance dTi and dTj (Equation (2)). Generally, the WISP Rx will not be placed in between any two of the transmitters i,j, then because of the trigonometric conditions, … So in order to improve the system accuracy, we use a first order polynomial line fit model to matching dTi and TRi. The line fit model is pre-trained by several tested data with known location and can be expressed as dTi = ai x dTi +bi (i = 1,2,3). Finally, we can calculate the position of WISP Rx with these calculated distances using triangulation.”).
He, Asanga and Zhao are analogous art because they are related in designing digital twin. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga and Zhao, to modify reading sensor data wirelessly using CTC (cross-technology communication) heterogeneous devices can directly exchange information for fast and effective control and cooperation, satisfies the timeliness and interconnection requirements in industrial IoT in He’s disclosure (in page 125). A finding that one of ordinary skill in the art could have to include the teaching of Zhao to achieve/get the location of battery-less passive RFID sensor based on triangulation performed using the sensor data. The suggestion/motivation for doing so would have been obvious by Zhao because “This paper presents a working prototype of a RFID-based system that localizes a custom battery-free, EPC Gen2-compatible UHF tag. The system uses the RFID communication channel for synchronization and inventory, and acoustic propagation delays for distance measurement. This paper presents a novel high-precision RFID localization system based on acoustic ToA. The system can locate a battery-free EPC Gen2 UHF WISP tag with ultrasound detectors using a commercial reader and three acoustic reference beacons. (Zhao disclosed in page 1 and 8 under headings ‘Abstract’ and ‘Conclusion’).
However, He, Asanga and Zhao do not explicitly teach the limitations “the internet of things hub is in communication with a server, the server hosting the digital twin; and wherein a server on a local area network provides data storage, the data fusion processor, and the internet of things hub”.
wherein Jeon teaches the internet of things hub is in communication with a server, the server hosting the digital twin; (Jeon disclosed in page 13 para [0197]: “The management server 635 and/or the server 645 may store or analyze a signal received from the communication network 631. The management server 635 and/or the server 645 may transmit the analysis result to at least one of the IoT devices 610, 620, 630, and 640 via the communication network 631. The management server 635 may manage the states of the hub 200, the gateway 625, the communication network 631, and/or the IoT devices …”. In para [0058 and 0059] discussed that FIG. 1 is a block diagram of an internet of things (IoT) network system includes a hub, a first and second controller, and an IoT device, further the hub and the IoT device may perform the device pairing according to the control of the first and second controller. Therefore, this disclosure corresponds to the claim element “digital twin”, since an IoT network system may include an IoT device, a hub, an access point, a gateway, a communication network, and/or a server, therefore it is concluded that “a server in communication with the internet of things hub, the server hosting the digital twin”).
and wherein Jeon teaches a server on a local area network provides data storage, the data fusion processor, and the internet of things hub. (Jeon disclosed in page 13 para [0197]: “The management server 635 and/or the server 645 may store or analyze a signal received from the communication network 631. The management server 635 and/or the server 645 may transmit the analysis result to at least one of the IoT devices 610, 620, 630, and 640 via the communication network 631. The management server 635 may manage the states of the hub 200, the gateway 625, the communication network 631, and/or the IoT devices …”. In page 18 para [0277]: “The IoT device application 1310, as a software component, may control the communication module 1320 and may be executed by a CPU of the IoT device 1300. The CPU may be included in the processing circuit 230, 330, 450, or 530 such as an AP. The communication module 1320 may be a modem communication connectable to LAN, … or mobile cellular network.”).
He, Asanga, Zhao and Jeon are analogous art because they are related in designing digital twin. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao and Jeon to modify communication between Internet of Things (IoT) with the reader/sensor of He, to include the communication between Internet of Things, gateway, reader and HTTP protocol of Jeon. The suggestion/motivation for doing so would have been obvious by Jeon because “The IoT network system 100B may also include a gateway 625. The gateway 625 may connect the hub 200, which functions as an access point, to an external communication network. One of the IoT devices 610, 620, 630, and 640 may function as the gateway 625. For instance, a smart phone may be both an IoT device and the gateway 625. The smart phone may be connected to a mobile cellular network. (Jeon disclosed in page 13 para [0193-0194]).
However, the abovementioned prior arts He, Asanga, Zhao and Jeon do not explicitly teach the limitations: “fusing the integrated sensor data and the data defining the physical object; and constructing a dynamic digital twin of the physical space or object including the sensor data; wherein the physical space or object is a computer aided design model of the physical space or object;”
Kousi teaches fusing the integrated sensor data and the data defining the physical object; and constructing a dynamic digital twin of the physical space or object including the sensor data; (Kousi disclosed in page 121 heading ‘Abstract’: “The suggested digital world model infrastructure involves three main functionalities: a) Virtual representation of the shopfloor, combining multiple sensor data and CAD models. The digital shopfloor is rendered in the 3D environment exploiting the capabilities provided by Robot Operating System (ROS) framework, … and c) Dynamic update of the digital twin based on real time sensor and resource data coming from the actual shopfloor. The communication and integration layer among the physical and the virtual agents is realized on top of the ROS framework.” In page 123-124 section 3: “As visualized in Fig. 1. four subcomponents are deployed under the suggested Digital Twin infrastructure: a) Resource Manager, b) Sensor Manager, c) Layout Manager and d) 3D environment constructor. … Two sub-components, namely the Resource location monitoring and Resource status monitoring are responsible for real-time monitoring the status and location of each mobile resource and update online the actual values in Digital Twin. As visualized in Fig. 2a specific ROS topics and services are initiated for each subscribed resource broadcasting their real time related data. The Sensor Manager is responsible for interfacing with the existing sensors’ ROS drivers and registering their configuration data in Digital Twin repository using the unified data model format. … To facilitate the use of standard motion and path planning algorithms … the 2D-3D sensor data combination module allows to easily and dynamically (merge multiple, sensor data into one topic. To efficiently represent the entire shopfloor, the static layout needs to be represented inside the Digital Twin. The Layout Manager is responsible for the control and storage of all CADs files related to static fixtures, parts and products in .sdf format … This component allows the user to upload the CAD file and configure various parameters concerning: a) the parts involved in the process, b) the stationary fixtures included in the shopfloor. The final component in the process chain is the 3D environment constructor (Fig. 2c). This component retrieves the locations of all parts, fixtures, sensors and resources to construct an environment with a global world frame … Fig. 3. represents the unified data model implemented under the deployed infrastructure. The used color coding maps the consumed data structures by the developed sub-components under the Digital Twin as presented in Fig. 1.”).
wherein Kousi teaches the physical space or object is a computer aided design model of the physical space or object; (Kousi disclosed in page 121 section 2: “Virtual representation of the shopfloor using resource related information (Resource Manager), multiple sensor data combination (Sensor Manager) and CAD models (Layout Manager). The information is continuously updated through a network of services by all resources and sensors creating a synthesis of all perception data.
• A unified semantic data model is implemented in order to semantically represent the geometrical as well as the workload state. This data model should be generic enough to be able to address multiple cases as well as to be consumed by multiple components inside execution system.” In page 124 (1st para): “To efficiently represent the entire shopfloor, the static layout needs to be represented inside the Digital Twin. The Layout Manager is responsible for the control and storage of all CADs files related to static fixtures, parts and products in .sdf format defining also the collisions, the inertia and the mass parameters. This component allows the user to upload the CAD file and configure various parameters concerning: a) the parts involved in the process, b) the stationary fixtures included in the shopfloor.”).
He, Asanga, Zhao, Jeon and Kousi are analogous art because they are related in designing digital twin. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao, Jeon and Kousi to modify data storage storing a geometric model of a physical object or space relating sensor of He, to include Kousi’s teaching to fuse/integrate the sensor data with the geometric model (e.g., CAD model) to produce a digital twin. The suggestion/motivation for doing so would have been obvious by Kousi because “The latest trends in EU manufacturing foster the deployment of hybrid production systems where humans can coexist and cooperate with mobile multi-arm robots. Such flexible robot workers should be able to perceive their environment in terms of process requirements and human activity. Driven by this need, the Digital Twin system presented in this work, provides the infrastructure for integrating all the hardware components involved in the assembly and synthesizing all the data coming from the shopfloor under a unified common environment. Upon this model, each resource applies cognition techniques to transform the sensor data into usable information and eventually to knowledge of the shop floor status.” (Kousi disclosed in page 126 section 5).
Regarding Claim 18, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 16, however He, Zhao, Jeon and Kousi do not explicitly teach the limitation “the method comprises transmitting, by the passive RFID sensor a unique identifier (UID) to the plurality of readers”.
wherein Asanga teaches the method comprises transmitting, by the passive RFID sensor a unique identifier (UID) to the plurality of readers. (Asanga disclosed in page 5860-5861 section II: “we utilize a WISP (Wireless Identification and Sensing Platform) tag, which is a passive CRFID embedded … there are two approaches for sensor data acquisition from CRFID sensors: … Although embedding sensor data in a tag ID sacrifices the range of the unique tag identifiers, this approach eliminates the energy intensive and time consuming operation of writing sensor data … During the next inventory round, which is marked by a QUERY command, the CRFID sensor transmits sensor data by embedding them in the tag ID. … Figure 3 illustrates the 96 bit Electronic Product Code (EPC) tag ID format re-defined for sensor data acquisition. … The Tag type is used to identify the type and hence capabilities of the tag. The sensor data section is used to embed acquired sensor data. We only utilized 30 bits in this section to embed acceleration data as shown in Figure 3, … The Tag ID section is composed of the WISP hardware version and the tag serial number, and a WISP can be uniquely identified using this Tag ID.”).
He, Zhao, Jeon, Kousi and Asanga are analogous art because they are related to have lightweight, battery-less computing platforms having sensor enabled RFID tags creating prospects for sensor-based applications. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Zhao, Jeon, Kousi and Asanga to modify reading sensor data wirelessly using CTC (cross-technology communication) heterogeneous devices can directly exchange information for fast and effective control and cooperation, satisfies the timeliness and interconnection requirements in industrial IoT in He’s disclosure (in page 125). A finding that one of ordinary skill in the art could have to include the teaching of Asanga to include interpolated values of sensor data streams. The suggestion/motivation for doing so would have been obvious by Asanga because “In this study, we propose an approach that reduces online interpolation errors to facilitate interpolating sparse acceleration data streams from a passive RFID tag with an on-board accelerometer sensor. We demonstrate that for these types of sensors, features readily available from a typical RFID platform can be successfully used instead of features extracted from an interpolated data stream to achieve similar or better activity recognition performance without preprocessing and, whilst, using significantly less number of features.” (Asanga disclosed in page 1 under ‘Abstract’).
Regarding Claim 19, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 16, further He teaches the step of using the digital twin to provide at least one of asset tracking, process planning, monitoring, and data visualization. (He disclosed in page 126-127 heading ‘Case study: Pavatar’: “Figure 4 shows the architecture of Pavatar. Pavatar collects data from both built-in and ambient sensors in UHVCSs. … In addition, networked cameras are deployed to cover walkable areas. The maximum density of sensor deployment is about 50/m2, the highest sampling frequency of internal sensors is around 10 KHz, and the total data volume size per day is over 1 TB. The high-frequency and big-volume stream data are collected and transmitted through heterogeneous networks to fulfill upper-level applications such as data visualization, event detection, and system diagnosis. Moreover, a three-layer edge computing architecture is proposed to process massive video data.” It has been disclosed in page 121 (left col. last para): “visual sensing is extremely informative for the surveillance of physical assets and their surroundings. In digital twin, intensive networked cameras are deployed at a high density to provide seamless monitoring.” This disclosure teaches the limitation “using the digital twin to provide monitoring, and data visualization”).
Claim 3 is rejected under 35 U.S.C. 103 as being unpatentable over He, Asanga, Zhao, Jeon and Kousi and further in view of journal “Design of Passive RFID Sensor Tags Enhanced by a Novel Logical Communication Procedure over LLRP” by Luca Catarinucci et al. (hereinafter Luca).
Regarding Claim 3, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 1, however He, Asanga, Zhao, Jeon and Kousi do not explicitly teach the limitation “communications between the passive RFID sensors are provided using a low-level reader protocol (LLRP).”
wherein Luca taches communications between the passive RFID sensors are provided using a low-level reader protocol (LLRP). (Luca disclosed in page 120 section I: “Sustained by the technological advances in Radiofrequency Identification (RFID), new RFID-based devices with augmented capabilities have appeared in recent years in the literature. Some of them, … named SPARTACUS (Self-Powered Augmented RFID Tag for Autonomous Computing and Ubiquitous Sensing), conjugate canonical RFID identification with extra functionalities such as sensing, computation, data storing, and actuation. … In this paper, a new version of SPARTACUS provided with a new physical layer implementing a logical communication procedure over Low Level Reader Protocol (LLRP) is presented as an extension of the paper … The device has been exhaustively tested and validated in terms of both electromagnetic characterization and working principle. The achieved results demonstrate that the improved device is a promising solution for implementing a real autonomous and distributed RFID-based passive computing in IoT scenarios.”).
He, Asanga, Zhao, Jeon, Kousi and Luca are analogous art because they are related computing platforms having sensor enabled RFID tags creating prospects for sensor-based applications. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao, Jeon, Kousi and Luca to modify communications between the passive RFID sensors in He’s disclosure. A finding that one of ordinary skill in the art could have to include the teaching of Luca applied the known “improvement” technique “passive RFID sensors are provided using a low-level reader protocol or LLRP” in the same way to achieve some power efficiency/optimization. The suggestion/motivation for doing so would have been obvious by Luca because “In this work an enhanced version of one of such devices, called SPARTACUS, is presented. While being completely passive, it conjugates identification, sensing, local computing, and actuation control and enables a proactive communication with any standard RFID reader. The paper presents details on a novel logical communication procedure over Low-Level Reader Protocol (LLRP), besides discussing system validation and performance evaluation.” (Luca disclosed in page 120 under ‘Abstract’).
Claims 6 and 8 are rejected under 35 U.S.C. 103 as being unpatentable over He, Asanga, Zhao, Jeon and Kousi and further in view of a Journal “C2PS: A Digital Twin Architecture Reference Model for the Cloud-based Cyber-Physical Systems Kazi Masudul Alam et al. (hereinafter Alam, Journal published on 2017).
Regarding Claim 6, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 1, however He, Asanga, Zhao, Jeon and Kousi do not explicitly teach the limitation “the internet of things hub, the data storage, and the processor are provided in an internet of things Platform as a Service (IoT PaaS).”
wherein Alam teaches the internet of things hub, the data storage, and the processor are provided in an internet of things Platform as a Service (IoT PaaS). (Alam disclosed in page 2052-2053 (right col.): “We proposed a vehicular CPS (VCPS) architecture, Social Internet-of-Vehicles (SIoV), ... SIoV is a vehicular domain of SIoT and exploits social network like characteristics … In this paper, we present a digital twin architecture reference model for cloud based CPS (C2PS), where we use the standard CPS design concepts to incorporate cloud support to it. In Table 1, we compare relevant works that present CPS architecture models. … In our work, we have followed the state machine based analytical design techniques to describe this integration. In this process, we have identified various types of computations and communications (i.e. physical, cyber and hybrid) possible in the C2PS. We also present Bayes network and fuzzy logic based reconfigurable model that considers system contexts while selecting a possible interaction mode.” In Table 1, “PaaS” shown under ‘Cloud integration’ column, has been inherently presented in proposed “cloud-based CPS reference model’. Further, in page 2053 section III: “In the proposed C2PS, we assume that a number of independent systems connect together to perform a common goal … All the data that are useful to improve the Quality of Service (QoS) of the physical things, are stored in the cloud based Data Center (Fig. 2). In the C2PS, a smart thing can be both stationary or mobile and can provide various services to other smart things. All the data gathered by the smart things are stored at different levels of storage from mobile, stationary to the cloud based data center.” Alam teaches the whole limitation).
He, Asanga, Zhao, Jeon, Kousi and Alam are analogous art because they are related to use digital twin in modern industry. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao, Jeon, Kousi and Alam to modify the internet of things hub, the data storage, and the processor are provided in an internet of things Platform in He’s disclosure. A finding that one of ordinary skill in the art could have the teaching of Alam to include or integrate digital twins with the cloud infrastructure becomes the true bridge between the physical layer and the application layer of CPS (Cyber-physical system). The suggestion/motivation for doing so would have been obvious by Alam because “In this paper, we present a digital twin architecture reference model for cloud-based CPS (C2PS), where we use the standard CPS design concepts to incorporate cloud support to it. In this process, we have identified various types of computations and communications (i.e. physical, cyber and hybrid) possible in the C2PS. We also present Bayes network and fuzzy logic based reconfigurable model that considers system contexts while selecting a possible interaction mode. This kind of smart connection model has been prescribed for the CPS, additionally, we also present a model to describe the formation of various possible cloud infrastructures. (Alam disclosed in page 2052 (right col. last para).
Regarding Claim 8, He, Asanga, Zhao, Jeon and Kousi teach the system of claim 1, however He, Asanga, Zhao, Jeon and Kousi do not explicitly teach the limitation “the passive RFID sensors produce unique identifier, and wherein the processor is programmed to identify the sensor based on the unique identifier”.
wherein Alam teaches the passive RFID sensors produce unique identifier, and wherein the processor is programmed to identify the sensor based on the unique identifier. (Alam disclosed in page 2053 section III: “In C2PS every physical thing is automatically accompanied by a representative digital twin hosted in the cloud. … Whenever physical world changes, a physical sensor tries to update the current status to its digital twin representative in the cloud. Every physical thing and its corresponding cyber thing manages a Data Store. Every physical or cyber thing is identified by a unique ID (i.e. IPv6, Universal Product Code (UPC), Electronic Product Code (EPC), etc.) and is aware of the existence of its twin counterpart.”).
He, Asanga, Zhao, Jeon, Kousi and Alam are analogous art because they are related to use digital twin in modern industry. Before the effective filing date of the claimed invention, it would have been obvious to one of ordinary skill in the art, having the teachings of He, Asanga, Zhao, Jeon, Kousi and Alam to modify the internet of things hub, the data storage, and the processor are provided in an internet of things Platform in He’s disclosure. A finding that one of ordinary skill in the art could have the teaching of Alam to include or integrate digital twins with the cloud infrastructure becomes the true bridge between the physical layer and the application layer of CPS (Cyber-physical system). The suggestion/motivation for doing so would have been obvious by Alam because “In this paper, we present a digital twin architecture reference model for cloud-based CPS (C2PS), where we use the standard CPS design concepts to incorporate cloud support to it. In this process, we have identified various types of computations and communications (i.e. physical, cyber and hybrid) possible in the C2PS. We also present Bayes network and fuzzy logic based reconfigurable model that considers system contexts while selecting a possible interaction mode. This kind of smart connection model has been prescribed for the CPS, additionally, we also present a model to describe the formation of various possible cloud infrastructures. (Alam disclosed in page 2052 (right col. last para).
Conclusion
8. Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. DEUTSCH et al. (Pub. No. US20190138333A1) disclosed systems and methods for managing a contextual digital twin. The example embodiments provide a system that can create and run full lifecycle digital twin models of all active entities in an industrial environment including, but not limited to, physical assets and systems of assets, software and physical processes, actors, resources, and the like. Assets may be outfitted with one or more sensors (e.g., physical sensors, virtual sensors, etc.) configured to monitor respective operations or conditions of the asset and the environment in which the asset operates. Data from the sensors can be recorded or transmitted to a cloud-based or other remote computing environment. Industrial Internet of Things (IIoT). For example, an IIoT may connect physical assets, such as turbines, jet engines, locomotives, healthcare devices, and the like, software assets, processes, actors, and the like, to the Internet or cloud, or to each other in some meaningful way such as through one or more networks.
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/NUPUR DEBNATH/Examiner, Art Unit 2186
/RENEE D CHAVEZ/Supervisory Patent Examiner, Art Unit 2186