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
1. This action is response to application filed on 04/02/2025. Claims 1-18 are pending.
Claim rejections-35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1, 4, 10, 13 are rejected under 35 U.S.C. 103 as being unpatentable over Ajay (WO 2018022627 A1) in view of Li et al. (WO 2019136128 A1) and further in view of Arches et al. (US 20170055117).
Regarding claim 1:
A method for operating a device performing group calibration in a machine-to-machine (M2M) system, the method comprising:
setting connection with Internet-of-things (loT) devices that belong to a device group: (setting up an IOF ecosystem includes plurality of sensor devices, plurality of stationary, portable and wearable consumer devices,…etc. The IOT ecosystem implements as an IOT hub which comprise a plurality of connected cloud devices: Ajay page 8, page 9; page 13).
However, Ajay does not explicitly teach receiving information for group calibration for the IoT devices from a platform.
In similar art, Li teaches an IoT server broadcasts messages to environmental sensors over a large area, such as a national park. The messages would bring calibration information which may be location dependent (see, Li, [0038]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Li’s ideas into Ajay’s system in order to effective IoT network management system (see, Li [0003]).
However, Ajay- Li does not explicitly teach performing calibration for the loT devices based on the information for the group calibration.
In similar art, Archer teaches transmitting a burst of calibrating probe requests from one or more mobile calibration devices at the one or more locations to one or more of a plurality of receivers in order to calibrate the location aggregation network (Archer abstract);
transmitting information on a result of the group calibration to the platform: (the server uses calibration data (data corresponding to the calibrating probe requests, such as MAC address of the mobile calibrating devices) from the receivers to form a radio map of the facility. Additionally, the server uses the calibration data to fit a model for predicting the received signal strength (RSS) of the visitor mobile devices: Archer [0038]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Archer’s ideas into Ajay-Li’s system in order to effective network management system (see, Archer [0002]).
Regarding claim 4:
In addition to the rejection claim 1, Ajay-Li-Archer further teaches the information on the result of the group calibration includes at least one of a list of the IoT devices, adjustment values for each of the IoT devices, or an adjustment method: (the server forms a calibration data dictionary for the each ID in calibration IDs and for the each location in calibration data. Further, the server updates a list of time at which the probes were received and further updates probes in raw data form. The server clusters the calibration data and resulting in the formation of the calibration data dictionary. The server combines all the calibration IDs into a single entry: Archer [0125]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Archer’s ideas into Ajay-Li’s system in order to effective network management system (see, Archer [0002]).
Regarding claim 10:
A device for performing group calibration in a machine-to-machine (M2M) system, the device comprising: a transceiver; and a processor coupled with the transceiver, wherein the processor is configured to:
set connection with Internet-of-things (IoT) devices that belong to a device group (setting up an IOF ecosystem includes plurality of sensor devices, plurality of stationary, portable and wearable consumer devices,…etc. The IOT ecosystem implements as an IOT hub which comprise a plurality of connected cloud devices: Ajay page 8, page 9; page 13).
However, Ajay does not explicitly teach receive information for group calibration for the IoT devices from a platform.
In similar art, Li teaches an IoT server broadcasts messages to environmental sensors over a large area, such as a national park. The messages would bring calibration information which may be location dependent (see, Li, [0038]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Li’s ideas into Ajay’s system in order to effective IoT network management system (see, Li [0003]).
However, Ajay-Li does not explicitly teach perform calibration for the IoT devices based on the information for the group calibration.
In similar art, Archer teaches transmitting a burst of calibrating probe requests from one or more mobile calibration devices at the one or more locations to one or more of a plurality of receivers in order to calibrate the location aggregation network (Archer abstract);
transmit information on a result of the group calibration to the platform: (the server uses calibration data (data corresponding to the calibrating probe requests, such as MAC address of the mobile calibrating devices) from the receivers to form a radio map of the facility. Additionally, the server uses the calibration data to fit a model for predicting the received signal strength (RSS) of the visitor mobile devices: Archer [0038]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Archer’s ideas into Ajay-Li’s system in order to effective network management system (see, Archer [0002]).
Regarding claim 13:
In addition to the rejection claim 10, Ajay-Li-Archer further teaches the information on the result of the group calibration includes at least one of a list of the IoT devices, adjustment values for each of the IoT devices, or an adjustment method: (the server forms a calibration data dictionary for the each ID in calibration IDs and for the each location in calibration data. Further, the server updates a list of time at which the probes were received and further updates probes in raw data form. The server clusters the calibration data and resulting in the formation of the calibration data dictionary. The server combines all the calibration IDs into a single entry: Archer [0125]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Archer’s ideas into Ajay-Li’s system in order to effective network management system (see, Archer [0002]).
Claims 2 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Ajay-Li-Arches in view of Bhatia et al. (US 20260154292)
Regarding claim 2:
Ajay-Li-Arches discloses the invention substantially as disclosed in claim 1, but does not explicitly teach the IoT devices include sensors of a same type.
In similar art, Bhatia teaches IoT devices are grouping based on sensor types (Bhatia [0074]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Bhatia’s ideas into Ajay-Li-Arches’s system in order to save resources and development time by implying Bhatia’s ideas into Ajay-Li-Arches’s system.
Regarding claim 11:
Ajay-Li-Arches discloses the invention substantially as disclosed in claim 10, but does not explicitly teach the IoT devices include sensors of a same type.
In similar art, Bhatia teaches IoT devices are grouping based on sensor types (Bhatia [0074]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Bhatia’s ideas into Ajay-Li-Arches’s system in order to save resources and development time by implying Bhatia’s ideas into Ajay-Li-Arches’s system.
Claims 5-6, 8-9, 14-15, 17-18 are rejected under 35 U.S.C. 103 as being unpatentable over Li et al. (WO 2019136128 A1) in view of Arches et al. (US 20170055117) and further in view of Pal et al. (US 20210243081)
Regarding claim 5:
A method for operating a device supporting group calibration in a machine-to- machine (M2M) system, the method comprising:
receiving a request for information for group calibration for Internet-of-things (IoT) devices that belong to a device group: (Li teaches an IoT server broadcasts messages to environmental sensors over a large area, such as a national park. The messages would bring calibration information which may be location dependent: Li, [0038]).
However, Li does not explicitly teach transmitting the information for the group calibration.
In similar art, Archer teaches transmitting a burst of calibrating probe requests from one or more mobile calibration devices at the one or more locations to one or more of a plurality of receivers in order to calibrate the location aggregation network (Archer abstract).
receiving information on a result of the group calibration: (data corresponding to the calibrating probe requests, such as MAC address of the mobile calibrating devices) from the receivers to form a radio map of the facility. Additionally, the server uses the calibration data to fit a model for predicting the received signal strength (RSS) of the visitor mobile devices: Archer [0038]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Archer’s ideas into Li’s system in order to effective network management system (see, Archer [0002]).
However, Li- Archer does not teach storing the information on the result of the group calibration in a resource for the group.
In similar art, Pal teaches the results of the calibration process, i.e., the recorded response of the sensor at each calibration set point, are preprocessed locally by the IoT gateway. More specifically, the IoT gateway is configured to summarize and aggregate the calibration results, and to tactically analyze the results for deviations from the expected values, (see, [0071]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Pal’s ideas into Li-Archer’s system in order to provide an efficient IoT network management system (see Pal, [0004]).
Regarding claim 6:
In addition to the rejection claim 5, Li-Archer-Pal further teaches the resource includes at least one of a first attribute indicating a type or a group of IoT devices that are subject to the group calibration, a second attribute indicating a parameter for performing the group calibration, a third attribute including a list of IoT devices that are registered for the group calibration, a fourth attribute including a calibration result list according to each IoT device, or a fifth attribute including an adjustment value list of each IoT device that requires adjustment: (the server forms a calibration data dictionary for the each ID in calibration IDs and for the each location in calibration data. Further, the server updates a list of time at which the probes were received and further updates probes in raw data form. The server clusters the calibration data and resulting in the formation of the calibration data dictionary. The server combines all the calibration IDs into a single entry: Archer [0125]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Archer’s ideas into Li-Pal’s system in order to save resources and development time by implying Archer’s ideas into Li-Pal’s system.
Regarding claim 8:
In addition to the rejection claim 5, Li-Archer-Pal further teaches the information for the group calibration includes at least one of a method of calibration, a protocol of calibration, a format of an adjustment value, a sensitivity of calibration, or an accuracy of calibration: (Pal teaches sensors typically require periodic calibration. Many sensors tend to lose accuracy over time due to poor maintenance and harsh environmental conditions (Pal, [0003]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Pal’s ideas into Li-Arches’s system in order to save resources and development time by implying Pal’s ideas into Li-Arches’s system.
Regarding claim 9:
In addition to the rejection claim 5, Li-Archer-Pal further teaches the information on the result of the group calibration includes at least one of a list of the IoT devices, adjustment values for each of the IoT devices, or an adjustment method: (the server forms a calibration data dictionary for the each ID in calibration IDs and for the each location in calibration data. Further, the server updates a list of time at which the probes were received and further updates probes in raw data form. The server clusters the calibration data and resulting in the formation of the calibration data dictionary. The server combines all the calibration IDs into a single entry: Archer [0125]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Archer’s ideas into Li-Pal’s system in order to save resources and development time by implying Archer’s ideas into Li-Pal’s system.
Regarding claim 14:
A device for supporting group calibration in a machine-to-machine (M2M) system, the device comprising: a transceiver; and a processor coupled with the transceiver, wherein the processor is configured to:
receive a request for information for group calibration for Internet-of-things (IoT) devices that belong to a device group: (Li teaches an IoT server broadcasts messages to environmental sensors over a large area, such as a national park. The messages would bring calibration information which may be location dependent: Li, [0038]).
However, Li does not explicitly teach transmit information for the group calibration.
In similar art, Archer teaches transmitting a burst of calibrating probe requests from one or more mobile calibration devices at the one or more locations to one or more of a plurality of receivers in order to calibrate the location aggregation network (Archer abstract).
receive information on a result of the group calibration: (the server uses calibration data (data corresponding to the calibrating probe requests, such as MAC address of the mobile calibrating devices) from the receivers to form a radio map of the facility. Additionally, the server uses the calibration data to fit a model for predicting the received signal strength (RSS) of the visitor mobile devices: Archer [0038]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Archer’s ideas into Li’s system in order to effective network management system (see, Archer [0002]).
However, Li-Archer does not teach store the information on the result of the group calibration in a resource for the group calibration.
In similar art, Pal teaches the results of the calibration process, i.e., the recorded response of the sensor at each calibration set point, are preprocessed locally by the IoT gateway. More specifically, the IoT gateway is configured to summarize and aggregate the calibration results, and to tactically analyze the results for deviations from the expected values, (see, [0071]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Pal’s ideas into Li-Archer’s system in order to provide an efficient IoT network management system (see Pal, [0004]).
Regarding claim 15:
In addition to the rejection claim 14, Li-Archer-Pal further teaches the resource includes at least one of a first attribute indicating a type or a group of IoT devices that are subject to the group calibration, a second attribute indicating a parameter for performing the group calibration, a third attribute including a list of IoT devices that are registered for the group calibration, a fourth attribute including a calibration result list according to each IoT device, or a fifth attribute including an adjustment value list of each IoT device that requires adjustment: (the server forms a calibration data dictionary for the each ID in calibration IDs and for the each location in calibration data. Further, the server updates a list of time at which the probes were received and further updates probes in raw data form. The server clusters the calibration data and resulting in the formation of the calibration data dictionary. The server combines all the calibration IDs into a single entry: Archer [0125]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Archer’s ideas into Li-Pal’s system in order to save resources and development time by implying Archer’s ideas into Li-Pal’s system.
Regarding claim 17:
In addition to the rejection claim 14, Li-Archer-Pal further teaches the information for the group calibration includes at least one of a method of calibration, a protocol of calibration, a format of an adjustment value, a sensitivity of calibration, or an accuracy of calibration: (Pal teaches sensors typically require periodic calibration. Many sensors tend to lose accuracy over time due to poor maintenance and harsh environmental conditions (Pal, [0003]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Pal’s ideas into Li-Arches’s system in order to save resources and development time by implying Pal’s ideas into Li-Arches’s system.
Regarding claim 18:
In addition to the rejection claim 14, Li-Archer-Pal further teaches the information on the result of the group calibration includes at least one of a list of the IoT devices, adjustment values for each of the IoT devices, or an adjustment method: (the server forms a calibration data dictionary for the each ID in calibration IDs and for the each location in calibration data. Further, the server updates a list of time at which the probes were received and further updates probes in raw data form. The server clusters the calibration data and resulting in the formation of the calibration data dictionary. The server combines all the calibration IDs into a single entry: Archer [0125]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Archer’s ideas into Li-Pal’s system in order to save resources and development time by implying Pal’s ideas into Li- Pal’s system.
Claims 3 and 12 rejected under 35 U.S.C. 103 as being unpatentable over Ajay-Li-Arches in view of Pal et al. (US 20210243081)
Regarding claim 3:
Ajay-Li-Arches discloses the invention substantially as disclosed in claim 1, but does not explicitly teach the information for the group calibration includes at least one of a method of calibration, a protocol of calibration, a format of an adjustment value, a sensitivity of calibration, or an accuracy of calibration.
In similar art, Pal teaches sensors typically require periodic calibration. Many sensors tend to lose accuracy over time due to poor maintenance and harsh environmental conditions (Pal, [0003]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Pal’s ideas into Ajay-Li-Arches’s system in order to save resources and development time by implying Pal’s ideas into Ajay-Li-Arches’s system.
Regarding claim 12:
Ajay-Li-Arches discloses the invention substantially as disclosed in claim 10, but does not explicitly teach the information for the group calibration includes at least one of a method of calibration, a protocol of calibration, a format of an adjustment value, a sensitivity of calibration, or an accuracy of calibration.
In similar art, Pal teaches sensors typically require periodic calibration. Many sensors tend to lose accuracy over time due to poor maintenance and harsh environmental conditions (Pal, [0003]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Pal’s ideas into Ajay-Li-Arches’s system in order to save resources and development time by implying Pal’s ideas into Ajay-Li-Arches’s system.
Claims 7 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Li-Arches-Pal in view of Bhatia et al. (US 20260154292)
Regarding claim 7:
Li-Arches-Pal discloses the invention substantially as disclosed in claim 5, but does not explicitly teach the IoT devices include sensors of a same type.
In similar art, Bhatia teaches IoT devices are grouping based on sensor types (Bhatia [0074]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Bhatia’s ideas into Li-Arches-Pal’s system in order to save resources and development time by implying Bhatia’s ideas into Li-Arches-Pal’s system.
Regarding claim 16:
Li-Arches-Pal discloses the invention substantially as disclosed in claim 14, but does not explicitly teach the IoT devices include sensors of a same type.
In similar art, Bhatia teaches IoT devices are grouping based on sensor types (Bhatia [0074]).
Thus, it would have been obvious to a person of ordinary skill in the art before the effective filling date of the claimed invention was made to modify Bhatia’s ideas into Li-Arches-Pal’s system in order to save resources and development time by implying Bhatia’s ideas into Li-Arches-Pal’s system.
Conclusions
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/LAN DAI T TRUONG/Primary Examiner, Art Unit 2444
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