DETAILED ACTION
Notice of Pre-AIA or AIA Status
I. 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 Amendment
II. This action is in response to applicants amendment/arguments filed on January 23, 2026. This action is made FINAL.
Specification
III. The specification is objected to as failing to provide proper antecedent basis for the claimed subject matter. See 37 CFR 1.75(d)(1) and MPEP § 608.01(o). Correction of the following is required:
Claim 1 recites “locking, unlocking, or sealing a door, gate, or other access point” in line 19; and “opening, closing, or throttling a valve or actuator controlling a liquid, gas, or HVAC conduit; reconfiguring lighting, surveillance-camera orientation, or network communication priority” in lines 22-25.
The claimed “locking, unlocking, or sealing a door, gate, or other access point” and “opening, closing, or throttling a valve or actuator controlling a liquid, gas, or HVAC conduit; reconfiguring lighting, surveillance-camera orientation, or network communication priority is not recited in the specification as filed.
Therefore, the specification and/or claims should be amended so that the terminology of the original claims follows the nomenclature of the specification.
Claim 28 recites “a signal-analysis unit configured to perform feature extraction and/or pattern analysis upon the obtained data to generate perception-feature information representative of a local or regional condition” in lines 8-10; “ (c) generate a decision output comprising event descriptors, confidence levels or a parameter adjustment directives” in lines 16-18; and “wherein the perception terminal and the control node cooperatively form an adaptive control framework, such that the perception terminal adjusts one or more local operational parameters including a sensing schedule, processing precision, activation threshold, or data-transmission behavior according to network-level optimization or feedback information received from the control node” in lines 21-26.
The claimed “a signal-analysis unit configured to perform feature extraction and/or pattern analysis upon the obtained data to generate perception-feature information representative of a local or regional condition”; “(c) generate a decision output comprising event descriptors, confidence levels or a parameter adjustment directives”; and “wherein the perception terminal and the control node cooperatively form an adaptive control framework, such that the perception terminal adjusts one or more local operational parameters including a sensing schedule, processing precision, activation threshold, or data-transmission behavior according to network-level optimization or feedback information received from the control node” is not recited in the specification as filed.
Therefore, the specification and/or claims should be amended so that the terminology of the original claims follows the nomenclature of the specification.
Claim Rejections - 35 USC § 102
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
IV, Claims 11-13, 19, 21, 24, 28, and 30 are rejected under 35 U.S.C. 102(a)(1) as being anticipated by Vrabete et al. (US 11,200,799 B2).
Regarding claim 11 Vrabete teaches a control system for incident management, environmental monitoring, or home or facility security (see col. 2, lines 23-28, A system and method for hierarchical and adaptive traffic management reads on a control system for incident management, environmental monitoring, or home or facility security), comprising: a network node, including at least one central processing unit, a memory, firmware, and an input/output interface configured for inter-node communication and for interaction with distributed sensing devices (see col. 12, lines 8-56 & col. 14, lines 9-39 and Fig. 8 & Fig. 9, The computing device 800 may be an aggregation device, IoT sensor device, warning device, IoT and the like. An IoT device 900 may be a computing device including an aggregation device, IoT sensor device, warning device, IoT and the like. The IoT device includes processing unit, a memory, firmware and an input/output interface for communicating with other IoT sensor devices. This reads on a network node, including at least one central processing unit, a memory, firmware, and an input/output interface configured for inter-node communication and for interaction with distributed sensing devices); the network node including a multimode transceiver subsystem configured to concurrently or switchably operate under a plurality of radio access technologies (RATs), and further configured to support adaptive network topologies including mesh, star, peer-to-peer, or hybrid combinations (see col. 4, lines 39-44 & 61-67; col. 7, lines 34-40; col. 14, lines 6-50 and Fig. 2 & Fig. 9, A mesh network of IoT devices may be termed a fog device operating at an edge of a cloud network. Any number of communication links may be used between the IoT devices (IoT sensors, IoT aggregation devices, IoT gateways) making up the fog device including shorter-range wireless links, longer range wireless links, BlueTooth, Zigbee, Mesh networks. Any number of radio communications protocols may be used including LTE or other cellular technologies. This reads on the network node including a multimode transceiver subsystem configured to concurrently or switchably operate under a plurality of radio access technologies (RATs), and further configured to support adaptive network topologies including mesh, star, peer-to-peer, or hybrid combinations); and a computing and control unit operatively coupled with the network node and programmed to: (a) receive sensor data from a plurality of sensing devices distributed across monitored zones; (b) evaluate the sensor data to determine whether the sensor data indicates an abnormal condition or security incident; (c) upon detection of the abnormal condition, transmit an alert signal and automatically initiate one or more context-adaptive response operations comprising at least one of: activating, disabling, or modulating an alarm or siren; locking, unlocking, or sealing a door, gate, or other access point; commanding an elevator to a predetermined floor, standby state, or emergency mode; opening, closing, or throttling a valve or actuator controlling a liquid, gas, or HVAC conduit; reconfiguring lighting, surveillance-camera orientation, or network communication priority; or transmitting a control notification signal to a remote supervisory, monitoring, or emergency-management platform (see col. 6, lines 34-67; col. 10, lines 10-62; claim 1; and Fig. 5 & Fig. 9, The sensors measure and collect data that may be stored in memory on the sensors or other devices. The sensors and other devices may be an aggregation device or IoT gateway device that collects the data from other sensors and devices. An IoT sensor/gateway/aggregation device analyzes the collected data to determine the occurrence of an event. The event may related to heavy or light traffic conditions, a hazardous event, an emergency event and the like. The IoT sensor/gateway/aggregation device can issue a response based on the analysis including sending timing instructions/controls to sensors or devices or issuing warnings to nearby devices. This reads on a computing and control unit operatively coupled with the network node and programmed to: (a) receive sensor data from a plurality of sensing devices distributed across monitored zones; (b) evaluate the sensor data to determine whether the sensor data indicates an abnormal condition or security incident; (c) upon detection of the abnormal condition, transmit an alert signal and automatically initiate one or more context-adaptive response operations comprising at least one of: activating, disabling, or modulating an alarm or siren; locking, unlocking, or sealing a door, gate, or other access point; commanding an elevator to a predetermined floor, standby state, or emergency mode; opening, closing, or throttling a valve or actuator controlling a liquid, gas, or HVAC conduit; reconfiguring lighting, surveillance-camera orientation, or network communication priority; or transmitting a control notification signal to a remote supervisory, monitoring, or emergency-management platform).
Regarding claim 12 Vrabete teaches evaluating sensor data using one more statistical indicators including a correlation coefficient, entropy value, variance, or time-correlation index (see col. 6, lines 33-42 and col. 10, lines 31-45, The collected data may be traffic data including detecting traffic going through a particular intersection during a time, the number of vehicles waiting, or an amount of time to clear an intersection in a given direction. The data is analyzed to determine if traffic is heavy, if traffic is light, if there is no traffic, and determining traffic flow in a particular direction. This reads on evaluating sensor data using one more statistical indicators including a correlation coefficient, entropy value, variance, or time-correlation index because of the time and statical components of the traffic analysis).
Regarding claim 13 Vrabete teaches wherein the multimode transceiver subsystem supports concurrent or switchable operation under at least two radio-access technologies selected from WiFi, cellular, satellite, lower power wide-area network (LPWAN), Zigbee, Z-Wave, Thread, Bluetooth, or Matter (see col. 4, lines 39-67 and col. 14, lines 1-15 & 51-67 and Fig. 2 and Fig. 9, A mesh network of IoT devices may be termed a fog device operating at an edge of a cloud network. Any number of communication links may be used between the IoT devices (IoT sensors, IoT aggregation devices, IoT gateways) making up the fog device including shorter-range wireless links, longer range wireless links, BlueTooth, Zigbee, Mesh networks. Any number or radios configured for the above technologies may be used. Any number of radio communications protocols may be used including LTE or other cellular technologies. This reads on wherein the multimode transceiver subsystem supports concurrent or switchable operation under at least two radio-access technologies selected from WiFi, cellular, satellite, lower power wide-area network).
Regarding claim 19 Vrabete teaches modifying a sensing schedule of at least one sensing device by adjusting a sampling interval, precision, or transmission frequency response to detection of an abnormal condition (see col. 16, lines 32-52, Battery parameters detected by the sensing device may be used to determine actions on transmission frequency and sensing frequency. This reads on modifying a sensing schedule of at least one sensing device by adjusting a sampling interval, precision, or transmission frequency response to detection of an abnormal condition).
Regarding claim 21 Vrabete teaches wherein the control unit transmits coordinated control commands to multiple network nodes to perform a distributed incident-response sequence comprising alarm activation, access control, and environment stabilization (see col. 6, lines 34-67; col. 10, lines 10-62; claim 1; and Fig. 5 & Fig. 9, The sensors measure and collect data that may be stored in memory on the sensors or other devices. The sensors and other devices may be an aggregation device or IoT gateway device that collects the data from other sensors and devices. An IoT sensor/gateway/aggregation device analyzes the collected data to determine the occurrence of an event. The event may related to heavy or light traffic conditions, a hazardous event, an emergency event and the like. The IoT sensor/gateway/aggregation device can issue a response based on the analysis including sending timing instructions/controls to sensors or devices in the traffic area or issuing warnings to nearby devices. This reads on wherein the control unit transmits coordinated control commands to multiple network nodes to perform a distributed incident-response sequence comprising alarm activation, access control, and environment stabilization).
Regarding claim 24 Vrabete teaches adaptive gateway bridging a short-range mesh domain and an Internet-Protocol domain, the gateway performing protocol translation and secure session establishment between heterogenous nodes (see col. 3, lines 54-67; col. 4, lines 61-67; and Fig. 2 & Fig. 9, The cloud may represent the Internet. A gateway is configured to bridge the short range mesh network of IoT sensors. This reads on adaptive gateway bridging a short-range mesh domain and an Internet-Protocol domain, the gateway performing protocol translation and secure session establishment between heterogenous nodes).
Regarding claim 28 Vrabete teaches a perception terminal configured for distributed sensing, analysis, and adaptive cooperation within an Internet of Things network (see col. 4, lines 39-44; col. 10, lines 10-55; and Fig. 2 & Fig. 9, A mesh network of IoT devices may be termed a fog device operating at an edge of a cloud network. Any number of communication links may be used between the IoT devices (IoT sensors, IoT aggregation devices, IoT gateways) making up the fog device. IoT Sensors collect and send/receive data. The data is analyzed at a IoT data aggregator and an event is determined based on the analysis. This reads on terminal configured for distributed sensing, analysis, and adaptive cooperation within an Internet of Things network), comprising at least one processor, a memory storing executable instructions, and an interface unit configured to exchange data and control information with at least one other network node (see col. 12, lines 8-56 & col. 14, lines 9-39 and Fig. 8 & Fig. 9, The computing device 800 may be an aggregation device, IoT sensor device, warning device, IoT and the like. An IoT device 900 may be a computing device including an aggregation device, IoT sensor device, warning device, IoT and the like. The IoT device includes processing unit, a memory, firmware and an input/output interface for communicating with other IoT sensor devices. This reads on comprising at least one processor, a memory storing executable instructions, and an interface unit configured to exchange data and control information with at least one other network node); a multi-source perception unit configured to obtain physical, environmental or situational data from a plurality of sensing channels, each sensing channel corresponding to at least one of an electrical, optical, acoustic, mechanical, or electromagnetic signal; a signal-analysis unit configured to perform feature extraction and/or pattern analysis upon the obtained data to generate perception-feature information representative of a local or regional condition; a decision-control executed by the processor and configured to: (a) evaluate the perception-feature information according to one or more decision models, statistical thresholds, or inference algorithms; (b) determine, based on the evaluation, whether a specified event, state change, or control condition has occurred; and (c) generate a decision output comprising event descriptors, confidence levels or a parameter adjustment directives; and a coordination interface configured to transmit the decision output to, or receive adaptive-control information from, at least one control node (see col. 6, lines 34-67; col. 10, lines 10-62; claim 1; and Fig. 5 & Fig. 9, The sensors measure and collect data that may be stored in memory on the sensors or other devices. The sensors and other devices may be an aggregation device or IoT gateway device that collects the data from other sensors and devices. An IoT sensor/gateway/aggregation device analyzes the collected traffic pattern data to determine the occurrence of an event. The event may related to heavy or light traffic conditions, a hazardous event, an emergency event and the like. The IoT sensor/gateway/aggregation device can issue a response based on the analysis including sending timing instructions/controls to sensors or devices or issuing accident warnings to nearby devices. This reads on a multi-source perception unit configured to obtain physical, environmental or situational data from a plurality of sensing channels, each sensing channel corresponding to at least one of an electrical, optical, acoustic, mechanical, or electromagnetic signal; a signal-analysis unit configured to perform feature extraction and/or pattern analysis upon the obtained data to generate perception-feature information representative of a local or regional condition; a decision-control executed by the processor and configured to: (a) evaluate the perception-feature information according to one or more decision models, statistical thresholds, or inference algorithms; (b) determine, based on the evaluation, whether a specified event, state change, or control condition has occurred; and (c) generate a decision output comprising event descriptors, confidence levels or a parameter adjustment directives; and a coordination interface configured to transmit the decision output to, or receive adaptive-control information from, at least one control node), wherein the perception terminal and the control node cooperatively form an adaptive control framework, such that the perception terminal adjusts one or more local operational parameters including a sensing schedule, processing precision, activation threshold, or data-transmission behavior according to network-level optimization or feedback information received from the control node (see col. 6, lines 34-67; col. 10, lines 10-62; claim 1; and Fig. 5 & Fig. 9, The sensors measure and collect data that may be stored in memory on the sensors or other devices. The sensors and other devices may be an aggregation device or IoT gateway device that collects the data from other sensors and devices. An IoT sensor/gateway/aggregation device analyzes the collected traffic pattern data to determine the occurrence of an event. The event may related to heavy or light traffic conditions, a hazardous event, an emergency event and the like. The IoT sensor/gateway/aggregation device can issue a response based on the analysis including sending timing instructions/controls to sensors or devices or issuing accident warnings to nearby devices. This reads on wherein the perception terminal and the control node cooperatively form an adaptive control framework, such that the perception terminal adjusts one or more local operational parameters including a sensing schedule, processing precision, activation threshold, or data-transmission behavior according to network-level optimization or feedback information received from the control node).
Regarding claim 30 Vrabete teaches a multimode heterogenous sensing and control network system configured for coordination among distributed perception terminals and at least one control node network (see col. 4, lines 39-44; col. 10, lines 10-55; and Fig. 2 & Fig. 9, A mesh network of IoT devices may be termed a fog device operating at an edge of a cloud network. Any number of communication links may be used between the IoT devices (IoT sensors, IoT aggregation devices, IoT gateways) making up the fog device. IoT Sensors collect and send/receive data. The data is analyzed at a IoT data aggregator and an event is determined based on the analysis. This reads on a multimode heterogenous sensing and control network system configured for coordination among distributed perception terminals and at least one control node network), comprising: a plurality of perception terminals, each perception terminal comprising: (a) at least one processor, a memory storing executable instructions, and a wireless transceiver (see col. 12, lines 8-56 & col. 14, lines 9-39 and Fig. 8 & Fig. 9, The computing device 800 may be an aggregation device, IoT sensor device, warning device, IoT and the like. An IoT device 900 may be a computing device including an aggregation device, IoT sensor device, warning device, IoT and the like. The IoT device includes processing unit, a memory, and an input/output interface for communicating with other IoT sensor devices. This reads on a plurality of perception terminals, each perception terminal comprising: (a) at least one processor, a memory storing executable instructions, and a wireless transceiver) configured to communicate through multiple radio access-technologies (see col. 4, lines 39-44 & 61-67; col. 7, lines 34-40; col. 14, lines 6-50 and Fig. 2 & Fig. 9, A mesh network of IoT devices may be termed a fog device operating at an edge of a cloud network. Any number of communication links may be used between the IoT devices (IoT sensors, IoT aggregation devices, IoT gateways) making up the fog device including shorter-range wireless links, longer range wireless links, BlueTooth, Zigbee, Mesh networks. Any number of radio communications protocols may be used including LTE or other cellular technologies. This reads on a wireless transceiver configured to communicate through multiple radio access-technologies); (b) a multi-sensor acquisition unit configured to obtain physical or environmental data including at least one of temperature, motion, vibration, light intensity, sound, or electromagnetic parameters; (c) a signal-processing unit configured to perform time-domain, frequency-domain, or statistical feature extraction on the data to generate feature vectors representing a local perception state; and a decision-execution unit configured to determine, based on the feature vectors and a stored decision model, whether a predefined event or abnormal condition has occurred, and to generate a status message comprising an event descriptor and/or confidence value; and a control node comprising a processor, a memory, and a multimode transceiver, the control node being configured to: (a) collect the status messages from the plurality of perception terminals; (b) aggregate and analyze the collected messages to identify a condition or coordinated event; and (c) generate and transmit one or more adaptive-control commands to at least a subset of the perception terminals to adjust local operational parameters including sensing interval, transmission schedule, modulation scheme, transmit power, or encryption mode (see col. 6, lines 34-67; col. 10, lines 10-62; claim 1; and Fig. 5 & Fig. 9, The sensors measure and collect data that may be stored in memory on the sensors or other devices. The collected data may be traffic data including detecting traffic going through a particular intersection during a time, the number of vehicles waiting, or an amount of time to clear an intersection in a given direction (see col. 6, lines 33-42). The sensors and other devices may be an aggregation device or IoT gateway device that collects the data from other sensors and devices. An IoT sensor/gateway/aggregation device analyzes the collected data to determine the occurrence of an event. The event may related to heavy or light traffic conditions, a hazardous event, an emergency event and the like. The IoT sensor/gateway/aggregation device can issue a response based on the analysis including sending timing instructions/controls to sensors or devices or issuing warnings to nearby devices. This reads on a multi-sensor acquisition unit configured to obtain physical or environmental data including at least one of temperature, motion, vibration, light intensity, sound, or electromagnetic parameters; (c) a signal-processing unit configured to perform time-domain, frequency-domain, or statistical feature extraction on the data to generate feature vectors representing a local perception state; and a decision-execution unit configured to determine, based on the feature vectors and a stored decision model, whether a predefined event or abnormal condition has occurred, and to generate a status message comprising an event descriptor and/or confidence value; and a control node comprising a processor, a memory, and a multimode transceiver, the control node being configured to: (a) collect the status messages from the plurality of perception terminals; (b) aggregate and analyze the collected messages to identify a condition or coordinated event; and (c) generate and transmit one or more adaptive-control commands to at least a subset of the perception terminals to adjust local operational parameters including sensing interval, transmission schedule, modulation scheme, transmit power, or encryption mode).
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 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 nonobviousness.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
V. Claims 14-16, 22-23, and 25 are rejected under 35 U.S.C. 103 as being unpatentable over Vrabete et al. (US 11,200,799 B2) in view of Van Wyk et al. (US 2014/0036702 A1).
Regarding claim 14 Vrabete teaches the control system of claim 11 except for wherein the multimode transceiver subsystem dynamically switches among mesh, star, peer-to-peer, or hybrid topologies based on measured link quality, traffic density, or node availability.
Wyk teaches a transceiver subsystem dynamically switches among mesh, star, peer-to-peer, or hybrid topologies based on measured link quality, traffic density, or node availability (see paragraphs [0014] and claims 11-12, Intelligently routing communications between and/or among nodes of heterogenous mesh network includes multiple different communication technologies such as star and tree. The quality of links between nodes using different technologies can be determined and routing communications between and/or among nodes of heterogenous is based on the determined quality of the links. This reads on wherein the multimode transceiver subsystem dynamically switches among mesh, star, peer-to-peer, or hybrid topologies based on measured link quality, traffic density, or node availability).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to make Vrabete adapt to include wherein the multimode transceiver subsystem dynamically switches among mesh, star, peer-to-peer, or hybrid topologies based on measured link quality, traffic density, or node availability because link optimization would allow for a more efficient communication amount nodes in the network (see Van Wyk, paragraph [0013]).
Regarding claim 15 Vrabete teaches the control system of claim 11 except for wherein the computing and control unit computes link-quality metrics comprising signal-to-noise ratio (SNR), signal-quality index (SQI), latency, packet-loss rate, and/or channel-occupancy rate.
Wyk teaches computes link-quality metrics comprising signal-to-noise ratio (SNR), signal-quality index (SQI), latency, packet-loss rate, and/or channel-occupancy rate (see paragraphs [0014] & [0028] – [0033] and claims 11-12, Calculating Link Quality can include a loss rate on the link. This reads on computes link-quality metrics comprising signal-to-noise ratio (SNR), signal-quality index (SQI), latency, packet-loss rate, and/or channel-occupancy rate).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to make Vrabete adapt to include computes link-quality metrics comprising signal-to-noise ratio (SNR), signal-quality index (SQI), latency, packet-loss rate, and/or channel-occupancy rate because link optimization would allow for a more efficient communication amount nodes in the network (see Van Wyk, paragraph [0013]).
Regarding claim 16 Wyk teaches dynamically selecting, combining, or routing data paths among different radio-access technologies according to the computed link-quality metrics to maintain low-latency and/or energy-efficient connectivity (see paragraphs [0014] & [0028] – [0033] and claims 11-12, Intelligently routing communications between and/or among nodes of heterogenous mesh network includes multiple different communication technologies such as star and tree. The quality of links between nodes using different technologies can be determined and routing communications between and/or among nodes of heterogenous is based on the determined quality of the links. This reads on dynamically selecting, combining, or routing data paths among different radio-access technologies according to the computed link-quality metrics to maintain low-latency and/or energy-efficient connectivity).
Regarding claim 22 Vrabete teaches the control system of claim 11 including an edge-computing node configured to aggregate sensor data from a plurality of neighboring nodes (col. 5, lines 28-37 and col. 6, lines 33-42, The sensor devices can form a fog device located at the edge of a cloud network (see Fig. 1 & Fig. 2). A sensor aggregation deice IoT gateway device may receive the measured sensor data collected by nearby IoT sensor devices. This reads on an edge-computing node configured to aggregate sensor data from a plurality of neighboring nodes) and except for providing optimization feedback for communication parameters or network topology.
Van Wyk teaches providing optimization feedback for communication parameters or network topology (see paragraphs [0014] and claims 11-12, Intelligently routing communications between and/or among nodes of heterogenous mesh network includes multiple different communication technologies such as star and tree. The quality of links between nodes using different technologies can be determined and routing communications between and/or among nodes of heterogenous is based on the determined quality of the links. This reads on providing optimization feedback for communication parameters or network topology).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to make Vrabete adapt to include providing optimization feedback for communication parameters or network topology because link optimization would allow for a more efficient communication amount nodes in the network (see Van Wyk, paragraph [0013]).
Regarding claim 23 Vrabete and Van Wyk teach limitations as recited in claim 16 and therefore claim 23 is rejected for the same reasons given above.
Regarding claim 25 Vrabete teaches the control system of claim 11 except for adjusting modulation mode, channel-coding rate, or packet size of the multimode transceiver subsystem in response to channel conditions to optimize spectral efficiency.
Van Wyk teaches adjusting modulation mode, channel-coding rate, or packet size of the multimode transceiver subsystem in response to channel conditions to optimize spectral efficiency (see paragraph [0082], A determination module may determine that a node on a specified link can support up to two different modulation schemes. The determination module can ascertain a combination of communication technology using the two different modulation schemes at available data rates to determine an optimal combination of both data rate and communication technology. This reads on adjusting modulation mode, channel-coding rate, or packet size of the multimode transceiver subsystem in response to channel conditions to optimize spectral efficiency).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to make Vrabete adapt to include adjusting modulation mode, channel-coding rate, or packet size of the multimode transceiver subsystem in response to channel conditions to optimize spectral efficiency because link optimization would allow for a more efficient communication amount nodes in the network (see Van Wyk, paragraph [0013]).
VI. Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Vrabete et al. (US 11,200,799 B2) in view of Nemala et al. (US 2016/0231830 A1).
Regarding claim 17 Vrabete teaches the control system of claim 11 except for wherein encrypts sensor data and/or control messages using an adaptive encryption configuration that changes according to a selected communication pathway.
Nemala teaches encrypts sensor data and/or control messages using an adaptive encryption configuration that changes according to a selected communication pathway (see paragraph [0072], Encrypting sensor data, wherein different levels of encryption may be required for different signatures depending on the communication received and/or how it is received reads on encrypts sensor data and/or control messages using an adaptive encryption configuration that changes according to a selected communication pathway).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to make Vrabete adapt to include encrypts sensor data and/or control messages using an adaptive encryption configuration that changes according to a selected communication pathway because this would allow for enhanced user privacy (see Nemala above).
Claim 18 is rejected under 35 U.S.C. 103 as being unpatentable over Vrabete et al. (US 11,200,799 B2) in view of Cheng et al. (US 2020/0050182 A1).
Regarding claim 18 Vrabete teaches the control system of claim 11 except for employing machine-learning model trained with historical sensing data to classify abnormal conditions and/or predict incident severity.
Cheng teaches employing machine-learning model trained with historical sensing data to classify abnormal conditions and/or predict incident severity (see paragraphs [0046] – [0049], A neural network is trained using a training dataset from storage. The dataset can include prelabeled system anomalies. The neural network is trained to detect events. This reads on employing machine-learning model trained with historical sensing data to classify abnormal conditions and/or predict incident severity).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to make Vrabete adapt to include employing machine-learning model trained with historical sensing data to classify abnormal conditions and/or predict incident severity because it would allow for an improved and more efficient event detection (see Cheng, abstract).
VII. Claims 20, 27, and 29 are rejected under 35 U.S.C. 103 as being unpatentable over Vrabete et al. (US 11,200,799 B2) in view of Wu et al. (US 2021/0329193 A1).
Regarding claim 20 Vrabete teaches the control system of claim 11 except for wherein the context-adaptive response operations further comprise regulating power output or activation sate of a lighting fixture, ventilation subsystem, or surveillance camera.
Wu teaches regulating power output or activation sate of a lighting fixture, ventilation subsystem, or surveillance camera (see paragraphs [0013] & [0162], A motion detection including image capturing sensor is adapted to switch from a power saving sleep mode to a wakeup mode while being triggered by a triggering event. This reads on regulating power output or activation sate of a lighting fixture, ventilation subsystem, or surveillance camera).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to make Vrabete adapt to include regulating power output or activation sate of a lighting fixture, ventilation subsystem, or surveillance camera because such a mechanism is well-known in the art to be used for power conservation (see Wu, paragraph [0087]).
Regarding claim 20 Vrabete teaches the control system of claim 11 except for wherein the computing and control unit monitors environment parameters including temperature, humidity, smoke density, or vibration and dynamically modifies incident-response thresholds.
Wu teaches monitors environment parameters including temperature, humidity, smoke density, or vibration and dynamically modifies incident-response thresholds (see paragraph [0086], When the detector detects a temperature variation it generates a triggering signal to switch a motion detection device from the sleep mode to a wakeup mode. This reads on wherein the computing and control unit monitors environment parameters including temperature, humidity, smoke density, or vibration and dynamically modifies incident-response thresholds).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to make Vrabete adapt to include monitors environment parameters including temperature, humidity, smoke density, or vibration and dynamically modifies incident-response thresholds because such a mechanism is well-known in the art to be used for power conservation and efficiency (see Wu, paragraph [0087]).
VIII. Regarding claim 29 Vrabete teaches the perception terminal of claim 28 except for wherein the perception terminal operates in a low-power standby state and automatically reactivates upon detection of a threshold event.
Wu teaches wherein the perception terminal operates in a low-power standby state and automatically reactivates upon detection of a threshold event (see paragraphs [0013] & [0162], A sensor is adapted to switch from a power saving sleep mode to a wakeup mode while being triggered by a triggering event. This reads on wherein the perception terminal operates in a low-power standby state and automatically reactivates upon detection of a threshold event).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to make the perception terminal of Vrabete adapt to include wherein the perception terminal operates in a low-power standby state and automatically reactivates upon detection of a threshold event because such a mechanism is well-known in the art to be used for power conservation (see Wu, paragraph [0087]).
IX. Claim 26 is rejected under 35 U.S.C. 103 as being unpatentable over Vrabete et al. (US 11,200,799 B2) in view of Dor et al. (US 9,549,381 B2).
Regarding claim 26 Vrabete teaches the control system of claim 11 except for wherein the computing and control unit assigns priority weight to data packets according to data criticality, latency tolerance, or energy cost and schedules transmission accordingly.
Dor teaches wherein the computing and control unit assigns priority weight to data packets according to data criticality, latency tolerance, or energy cost and schedules transmission accordingly (see claim 1, Transmitting data via a wireless communication device includes a plurality of data packets in a buffer; determining a characteristic of each of the data packets; and selecting a data packet from the buffer based, at least in part, on the temperature of the power amplifier and a Quality of Service (QoS) index based, at least in part, on a weighted average of packet priority, data packet periodicity, and data packet latency; and transmitting the selected data packet. This reads on wherein the computing and control unit assigns priority weight to data packets according to data criticality, latency tolerance, or energy cost and schedules transmission accordingly).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to make Vrabete adapt to include assigns priority weight to data packets according to data criticality, latency tolerance, or energy cost and schedules transmission accordingly because it would allow for improved performance of the devices (see Dor, col. 1, lines 49-51),
Response to Arguments
X. Applicant’s arguments with respect to claims 11-30 have been considered but are moot in view of the new grounds of rejection.
Conclusion
XI. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Shao Patent No.: US 12,366,848 B2 discloses method and system for intelligent recommendation of production process by industrial internet of things infomation cloud sharing.
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.
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/BRANDON J MILLER/ Primary Examiner, Art Unit 2647
February 13, 2026