DETAILED ACTION
This communication is in response to the claims filed on 09/29/2023.
Application No: 18/477,976
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Notice of Pre-AIA or AIA Status
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 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.
Claim Objections
Claim 1 (and similarly claims 19 and 25) is objected to because of the following informalities. Claim uses “sounding the one or more stationary network devices” statement. In this statement, “Sounding” is not clearly defined (e.g. sounding signal or sounding reference signal, etc.). Appropriate correction is required for further review and compact prosecution.
Claim 8 (and similarly claims 8 and 15) is objected to because of the following informalities. Claim uses “ based on the one or more motion indications, one or more independent stationary network devices for inclusion in a motion detection network” statement. In this statement, how “motion indications” is detected or event triggered is not clearly defined (e.g. by sounding signal or sounding reference signal, etc.). Appropriate correction is required for further review and compact prosecution.
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 of this title, 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 nonobviousness.
Claims 1-12 and 14-26 are rejected under 35 U. S. C. 103 as being unpatentable over Wilson et al. ( US 20120146788 A1) in view of Omer et al. ( US 20220173939 A1).
Regarding claim 1, Wilson teaches a method ([0018], e.g. The present disclosure is directed to systems and methods of device-free motion and presence detection. The disclosed systems and methods may include a mesh network RF sensing technology that can detect and quantify the presence or motion of people and other objects within an area of interest. [0056] Detecting and estimating device-free characteristics using RSS measurements presents some unique wireless protocol challenges. Maintaining the transmission of each node in the network at a high level may be desirable in order to capture fast movements. However, as the number of nodes in the network increases, having each node reduce its rate of transmission may be desirable to avoid collisions), comprising:
determining, based on one or more signal characteristics associated with one or more network devices ([0026], e.g. The base station control 103 may be a node 102 that has special responsibilities to report signal strength measurements to a processing unit, such as the client computing device 104. [0027] One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. determining, based on signal characteristics associated with one or more network devices, additional stationary network devices). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6. [0043] The time varying aggregate disturbance Q(t) can be used to detect presence and/or motion, or to estimate other valuable characteristics, such as quantity, velocity, or size),
one or more stationary network devices of the one or more network devices ([0020], e.g. Furthermore, a network can self-form and self-heal when nodes are added or removed (I.e. stationary network devices are detected when they are added). The computations to determine detection network statistics can be arranged in various client-servers and distributed processing architectures);
configuring the one or more stationary network devices to detect motion ([0023], e.g. The nodes 102 can be positioned around an area of interest 108 and configured in a mesh wireless detection network 101. The nodes 102 may be in communication with the one or more computing devices 104, 106. [0045] The node locations do not need to be known. [0046] Aggregate disturbances are continuous, making it possible to estimate quantities and characteristics, not just detect. [0047] Aggregate disturbances can be calculated taking into account patterns of movement (i.e. configuring the one or more stationary network devices to detect motion). [0051] As shown in FIG. 4, when a person enters a network area, the aggregate disturbance increases 402 dramatically. By setting an appropriate threshold, the entering of the person to the area can be detected. The size and speed of the person entering may affect the change in aggregate disturbance. Similarly, the number of people who have entered may affect the change in aggregate disturbance. This allows an algorithm to estimate these quantities (size and/or number of people) by using multiple thresholds, or by using statistical analyses of the disturbances).
Wilson teaches systems and methods for device-free motion detection and presence detection within an area of interest. However Wilson differs from the claimed invention in not specifically and clearly describing wherein
sounding the one or more stationary network devices; and
based on sounding the one or more stationary network devices, receiving from the one or more stationary network devices, one or more motion indications.
However, in the analogous field of endeavor, Omer teaches wherein
sounding the one or more stationary network devices ([0034], e.g. In the example shown in FIG. 1, the wireless communication devices transmit wireless signals to each other over wireless communication links (e.g., according to a wireless network standard or a non-standard wireless communication protocol), and the wireless signals communicated between the devices can be used as motion probes to detect motion of objects in the signal paths between the devices (i.e. sounding the one or more stationary network devices). In some implementations, standard signals (e.g., channel sounding signals, beacon signals), non-standard reference signals, or other types of wireless signals can be used as motion probe); and
based on sounding the one or more stationary network devices, receiving from the one or more stationary network devices, one or more motion indications ([0035] In the example shown in FIG. 1, the wireless communication link between the wireless communication devices 102A, 102C can be used to probe a first motion detection zone 110A. [0036] In the example shown in FIG. 1, when an object moves in any of the motion detection zones 110, the motion detection system may detect the motion based on signals transmitted through the relevant motion detection zone 110 (i.e. receiving from the stationary network devices, motion indications). Generally, the object can be any type of static or moveable object, and can be living or inanimate. For example, the object can be a human (e.g., the person 106 shown in FIG. 1). [0037] In some examples, the wireless signals propagate through a structure (e.g., a wall) before or after interacting with a moving object, which may allow the object's motion to be detected without an optical line-of-sight between the moving object and the transmission or receiving hardware. In some instances, the motion detection system may communicate the motion detection event to another device or system, such as a security system or a control center).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the method of Omer within the method of Wilson. The motivation to combine references is that the combined method provides that a wireless sensing system can process wireless signals (e.g., radio frequency signals) transmitted through a space between wireless communication devices for wireless sensing applications. Example wireless sensing applications include detecting motion, which can include one or more of the following: detecting motion of objects in the space, motion tracking, localization of motion in a space, breathing detection and breathing monitoring (See Omer [abstract, 0017]).
Regarding claim 2, Wilson in view of Omer teaches all the limitations of claim 1. Wilson further teaches wherein the one or more stationary network devices are configured for one or more of: WiFi motion detection, BLUETOOTH motion detection, LIDAR motion detection, RADAR motion detection, or SONAR motion detection ([0025], e.g. Examples of radio modules or wireless hardware that provide RSSI include, but are not limited to, mobile phones, IEEE 802.11 wireless Internet routers and cards (WiFi), and IEEE 802.15.4 modules (Zigbee). [0017] Recent research and advancements have developed motion and presence sensing techniques that utilize received signal strength (RSS) measurements from wireless devices. For example, researchers have demonstrated motion detection using RSS measurements in IEEE 802.15.4/802.11 networks).
Regarding claim 3, Wilson in view of Omer teaches all the limitations of claim 1. Omer further teaches wherein sounding the one or more stationary devices comprises sending one or more ping sweeps comprising ending Internet Control Message Protocol (ICMP) Echo Request packets ([0034], e.g. In the example shown in FIG. 1, the wireless communication devices transmit wireless signals to each other over wireless communication links (e.g., according to a wireless network standard or a non-standard wireless communication protocol (i.e. sending ping sweeps thru Internet Control Message Protocol (ICMP) packets)), and the wireless signals communicated between the devices can be used as motion probes to detect motion of objects in the signal paths between the devices. In some implementation. [0058] In some implementations, the client devices 232 send a request to their corresponding AP 226, 228 to transmit wireless signals that can be used by the client device as motion probes to detect motion of objects in the space 201. The request sent to the corresponding AP 226, 228 may be a null data packet frame, a beamforming request, a ping, standard data traffic, or a combination thereof).
The motivation to combine reference of Omer within the method of Wilson before the effective filing date of the invention is that the new method provides techniques that that a wireless sensing system can process wireless signals transmitted through a space between wireless communication devices for wireless sensing applications. Example wireless sensing applications include smoking detection, school violence detection, human counting and metal detection (See Omer [abstract, 0017]).
Regarding claim 4, Wilson in view of Omer teaches all the limitations of claim 1. Wilson further teaches wherein further comprising determining one or more independent stationary network devices of the one or more stationary network devices ([0023], e.g. In still another embodiment, the client computing device 104 may receive data from the nodes 102 and communicate the data over a network 105, such as the Internet, to the server computing device 106. As can be appreciated, a variety of configurations of the client computing device 104 and server computing device 106 may be possible (i.e. determining independent stationary network devices of the one or more stationary network devices based on sensor data received at a server). [0027] One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101. Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6).
Regarding claim 5, Wilson in view of Omer teaches all the limitations of claim 1. Wilson further teaches wherein further comprising determining, based on the one or more signal characteristics associated with the one or more network devices, one or more mobile network devices of the one or more network devices ([0025], e.g. Examples of radio modules or wireless hardware that provide RSSI include, but are not limited to, mobile phones, IEEE 802.11 wireless Internet routers and cards (WiFi), and IEEE 802.15.4 modules (Zigbee). [0017] Recent research and advancements have developed motion and presence sensing techniques that utilize received signal strength (RSS) measurements from wireless devices. For example, researchers have demonstrated motion detection using RSS measurements in IEEE 802.15.4/802.11 networks).
Regarding claim 6, Wilson in view of Omer teaches all the limitations of claim 1. Omer further teaches wherein further comprising based on sounding the one or more stationary network devices, determining one or more stationary network devices associated with one or more independent signal paths ([0034], e.g. the wireless signals communicated between the devices can be used as motion probes to detect motion of objects in the signal paths between the devices (i.e. determining stationary network devices associated with one or more signal (i.e. sounding) paths). In some implementations, standard signals (e.g., channel sounding signals, beacon signals), non-standard reference signals, or other types of wireless signals can be used as motion probes).
The motivation to combine reference of Omer within the method of Wilson before the effective filing date of the invention is that the new method provides techniques that that a wireless sensing system can process wireless signals transmitted through a space between wireless communication devices for wireless sensing applications. Example wireless sensing applications include smoking detection, school violence detection, human counting and metal detection (See Omer [abstract, 0017]).
Regarding claim 7, Wilson in view of Omer teaches all the limitations of claim 1. Wilson further teaches wherein further comprising: detecting, on a network associated with the one or more network devices, a new network device ([0027] One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. determining, based on signal characteristics associated with one or more network devices, additional stationary network devices). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6);
determining one or more signal characteristics associated with the new network device ([0043] The time varying aggregate disturbance Q(t) can be used to detect presence and/or motion, or to estimate other valuable characteristics, such as quantity, velocity, or size); and
configuring, based on the one or more signal characteristics associated with the new network device, the new network device for motion detection ([0023], e.g. The nodes 102 can be positioned around an area of interest 108 and configured in a mesh wireless detection network 101. The nodes 102 may be in communication with the one or more computing devices 104, 106. [0045] The node locations do not need to be known. [0046] Aggregate disturbances are continuous, making it possible to estimate quantities and characteristics, not just detect. [0047] Aggregate disturbances can be calculated taking into account patterns of movement (i.e. configuring the one or more stationary network devices to detect motion).
Regarding claim 8, Wilson teaches a method ([0018], e.g. The present disclosure is directed to systems and methods of device-free motion and presence detection. The disclosed systems and methods may include a mesh network RF sensing technology that can detect and quantify the presence or motion of people and other objects within an area of interest. [0056] Detecting and estimating device-free characteristics using RSS measurements presents some unique wireless protocol challenges. Maintaining the transmission of each node in the network at a high level may be desirable in order to capture fast movements. However, as the number of nodes in the network increases, having each node reduce its rate of transmission may be desirable to avoid collisions), comprising:
determining, based on one or more signal characteristics associated with one or more network devices ([0026], e.g. The base station control 103 may be a node 102 that has special responsibilities to report signal strength measurements to a processing unit, such as the client computing device 104. [0027] One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. determining, based on signal characteristics associated with one or more network devices, additional stationary network devices). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6. [0043] The time varying aggregate disturbance Q(t) can be used to detect presence and/or motion, or to estimate other valuable characteristics, such as quantity, velocity, or size),
one or more stationary network devices of the one or more network devices ([0020], e.g. Furthermore, a network can self-form and self-heal when nodes are added or removed (I.e. stationary network devices are detected when they are added). The computations to determine detection network statistics can be arranged in various client-servers and distributed processing architectures),
configuring the one or more independent stationary network devices in the motion detection network to detect motion ([0023], e.g. The nodes 102 can be positioned around an area of interest 108 and configured in a mesh wireless detection network 101. The nodes 102 may be in communication with the one or more computing devices 104, 106. [0045] The node locations do not need to be known. [0046] Aggregate disturbances are continuous, making it possible to estimate quantities and characteristics, not just detect. [0047] Aggregate disturbances can be calculated taking into account patterns of movement (i.e. configuring the one or more stationary network devices to detect motion). [0051] As shown in FIG. 4, when a person enters a network area, the aggregate disturbance increases 402 dramatically. By setting an appropriate threshold, the entering of the person to the area can be detected. The size and speed of the person entering may affect the change in aggregate disturbance. Similarly, the number of people who have entered may affect the change in aggregate disturbance. This allows an algorithm to estimate these quantities (size and/or number of people) by using multiple thresholds, or by using statistical analyses of the disturbances).
Wilson teaches systems and methods for device-free motion detection and presence detection within an area of interest. However Wilson differs from the claimed invention in not specifically and clearly describing wherein
receiving, from the one or more stationary network devices, one or more motion indications;
selecting, from the one or more stationary network devices, based on the one or more motion indications, one or more independent stationary network devices for inclusion in a motion detection network.
However, in the analogous field of endeavor, Omer teaches wherein
receiving, from the one or more stationary network devices, one or more motion indications ([0035] In the example shown in FIG. 1, the wireless communication link between the wireless communication devices 102A, 102C can be used to probe a first motion detection zone 110A. [0036] In the example shown in FIG. 1, when an object moves in any of the motion detection zones 110, the motion detection system may detect the motion based on signals transmitted through the relevant motion detection zone 110 (i.e. receiving from the stationary network devices, motion indications). Generally, the object can be any type of static or moveable object, and can be living or inanimate. For example, the object can be a human (e.g., the person 106 shown in FIG. 1). [0037] In some examples, the wireless signals propagate through a structure (e.g., a wall) before or after interacting with a moving object, which may allow the object's motion to be detected without an optical line-of-sight between the moving object and the transmission or receiving hardware. In some instances, the motion detection system may communicate the motion detection event to another device or system, such as a security system or a control center),
selecting, from the one or more stationary network devices, based on the one or more motion indications, one or more independent stationary network devices for inclusion in a motion detection network ([0038], e.g. In some cases, the wireless communication devices 102 themselves are configured to perform one or more operations of the motion detection system (i.e. selecting, independent stationary network devices for inclusion in a motion detection network), for example, by executing computer-readable instructions (e.g., software or firmware) on the wireless communication devices. For example, each device may process received wireless signals to detect motion based on changes in the communication channel. In some cases, another device (e.g., a remote server, a cloud-based computer system, a network-attached device, etc.) is configured to perform one or more operations of the motion detection system. For example, each wireless communication device 102 may send channel information to a specified device, system, or service that performs operations of the motion detection system).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the method of Omer within the method of Wilson. The motivation to combine references is that the combined method provides that a wireless sensing system can process wireless signals (e.g., radio frequency signals) transmitted through a space between wireless communication devices for wireless sensing applications. Example wireless sensing applications include detecting motion, which can include one or more of the following: detecting motion of objects in the space, motion tracking, localization of motion in a space, breathing detection and breathing monitoring (See Omer [abstract, 0017]).
Regarding claim 9, Wilson in view of Omer teaches all the limitations of claim 8. Wilson further teaches wherein the one or more stationary network devices are WiFi enabled devices ([0025], e.g. Examples of radio modules or wireless hardware that provide RSSI include, but are not limited to, mobile phones, IEEE 802.11 wireless Internet routers and cards (WiFi), and IEEE 802.15.4 modules (Zigbee)).
Regarding claim 10, Wilson in view of Omer teaches all the limitations of claim 8. Wilson further teaches wherein the one or more stationary network devices are configured for one or more of: WiFi motion detection, BLUETOOTH motion detection, LIDAR motion detection, RADAR motion detection, or SONAR motion detection ([0025], e.g. Examples of radio modules or wireless hardware that provide RSSI include, but are not limited to, mobile phones, IEEE 802.11 wireless Internet routers and cards (WiFi), and IEEE 802.15.4 modules (Zigbee). [0017] Recent research and advancements have developed motion and presence sensing techniques that utilize received signal strength (RSS) measurements from wireless devices. For example, researchers have demonstrated motion detection using RSS measurements in IEEE 802.15.4/802.11 networks).
Regarding claim 11, Wilson in view of Omer teaches all the limitations of claim 8. Wilson further teaches wherein selecting the one or more independent stationary network devices comprises determining, based on the one or more motion indications, a first group one or more stationary network devices associated with a first plurality of motion indications of the one or more motion indications ([0025], Fig. 5, e.g. the nodes 102 can be any radio module or any wireless hardware capable of measuring signal strength. The signal strength measurements may be measured and/or reported by a received signal strength indicator (RSSI) (I.e. first motion indicator and first group is based on the RSSI signal) ),
that are independent of a second plurality of motion indications associated with a second group of the one or more stationary network devices ([0025], e.g. The nodes 102 can be any radio module or any wireless hardware capable of measuring signal strength. The signal strength measurements may be measured and/or reported by a link quality indicator (LQI) of the radio module or wireless hardware (I.e. second motion indicator and second group is based on the LQI signal). [0058] If the node is node k+1 (it is the node's turn to transmit), then the node broadcasts 514 the RSSI/LQI vector. The RSSI/LQI vector has been filled with measurements as each of the other nodes has transmitted to the currently transmitting node. This cycle may be repeated indefinitely, filling the RSSI/LQI vector upon receipt of packets from the other nodes in the network, and then broadcasting the values in the RSSI/LQI vector to the other nodes when the protocol allows (I.e. receiving motion indicators at the first and the second group Devices based on the RSSI or LQI signal respectively)).
Regarding claim 12, Wilson in view of Omer teaches all the limitations of claim 8. Wilson further teaches wherein the one or more stationary network devices are associated with a network, the method further comprising determining one or more network conditions associated with the network ([0020], e.g. The aggregate detection network statistic may be continuous, allowing for detection of presence and estimation of other important metrics such as quantity and speed. The aggregate detection network statistic can be dependent on particular patterns of movement allowing for more intelligent triggering of alarms (i.e. determining network condition based on the quality and speed of the signals)).
Regarding claim 14, Wilson in view of Omer teaches all the limitations of claim 8. Wilson further teaches wherein further comprising determining one or more performance specifications ([0040], e.g. Calibration can also be performed while the system is in use, and adjusted for better performance over time (i.e. determining one or more performance specifications). Instead of using data from a known calibration period, measurements from recent history can be processed and used for comparison to current measurements. The simplest example of this is using changes to the mean of each link. A long history of data can be used to determine the calibration mean for each link, while the mean of shorter histories can be used to see if something has changed recently), and
one or more resource requirements associated with the one or more network devices ([0027], e.g. One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. increasing nodes based resources on the network). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6).
Regarding claim 15, Wilson I teaches a method ([0018], e.g. The present disclosure is directed to systems and methods of device-free motion and presence detection. The disclosed systems and methods may include a mesh network RF sensing technology that can detect and quantify the presence or motion of people and other objects within an area of interest. [0056] Detecting and estimating device-free characteristics using RSS measurements presents some unique wireless protocol challenges. Maintaining the transmission of each node in the network at a high level may be desirable in order to capture fast movements. However, as the number of nodes in the network increases, having each node reduce its rate of transmission may be desirable to avoid collisions), comprising:
assigning, based on one or more signal characteristics associated with one or more network devices connected to a network ([0026], e.g. The base station control 103 may be a node 102 that has special responsibilities to report signal strength measurements to a processing unit, such as the client computing device 104. [0027] One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. determine and assigning, based on signal characteristics associated with one or more network devices, additional stationary network devices). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6. [0043] The time varying aggregate disturbance Q(t) can be used to detect presence and/or motion, or to estimate other valuable characteristics, such as quantity, velocity, or size),
a plurality of network devices to a group of network devices, wherein the group of network devices comprises one or more stationary network devices ([0025], Fig. 5, e.g. the nodes 102 can be any radio module or any wireless hardware capable of measuring signal strength. The signal strength measurements may be measured and/or reported by a received signal strength indicator (RSSI) (I.e. first motion indicator and first group is based on the RSSI signal) );
configuring the group of network devices for motion detection ([0023], e.g. The nodes 102 can be positioned around an area of interest 108 and configured in a mesh wireless detection network 101. The nodes 102 may be in communication with the one or more computing devices 104, 106. [0045] The node locations do not need to be known. [0046] Aggregate disturbances are continuous, making it possible to estimate quantities and characteristics, not just detect. [0047] Aggregate disturbances can be calculated taking into account patterns of movement (i.e. configuring the one or more stationary network devices to detect motion). [0051] As shown in FIG. 4, when a person enters a network area, the aggregate disturbance increases 402 dramatically. By setting an appropriate threshold, the entering of the person to the area can be detected. The size and speed of the person entering may affect the change in aggregate disturbance. Similarly, the number of people who have entered may affect the change in aggregate disturbance. This allows an algorithm to estimate these quantities (size and/or number of people) by using multiple thresholds, or by using statistical analyses of the disturbances).
Wilson teaches systems and methods for device-free motion detection and presence detection within an area of interest. However Wilson differs from the claimed invention in not specifically and clearly describing wherein
determining a change in one or more network conditions of the network;
updating, based on the change in the one or more network conditions, the group of network devices; and
configuring the updated group of network devices for motion detection.
However, in the analogous field of endeavor, Omer teaches wherein
determining a change in one or more network conditions of the network ([0038], e.g. For example, each device may process received wireless signals to detect motion based on changes in the communication channel (i.e. determining a change in network conditions of the network);
updating, based on the change in the one or more network conditions, the group of network devices ([0038], e.g. For example, each wireless communication device 102 may send channel information to a specified device, system, or service that performs operations of the motion detection system (i.e. updating, based on the change in the network conditions, the group of network devices)); and
configuring the updated group of network devices for motion detection ([0038], e.g. a network-attached device, etc. is configured to perform one or more operations of the motion detection system (i.e. configuring the updated group of network devices for motion detection). For example, each wireless communication device 102 may send channel information to a specified device, system, or service that performs operations of the motion detection system
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the method of Omer within the method of Wilson. The motivation to combine references is that the combined method provides that a wireless sensing system can process wireless signals (e.g., radio frequency signals) transmitted through a space between wireless communication devices for wireless sensing applications. Example wireless sensing applications include detecting motion, which can include one or more of the following: detecting motion of objects in the space, motion tracking, localization of motion in a space, breathing detection and breathing monitoring (See Omer [abstract, 0017]).
Regarding claim 16, Wilson in view of Omer teaches all the limitations of claim 15. Wilson further teaches wherein updating the group of network devices comprises adding a new network device to the group of network devices or removing a network device from the group of network devices ([0027], e.g. One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. increasing nodes based resources on the network). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6).
Regarding claim 17, Wilson in view of Omer teaches all the limitations of claim 15. Wilson further teaches wherein the one or more network devices are configured for one or more of: WiFi motion detection, BLUETOOTH motion detection, LIDAR motion detection, RADAR motion detection, or SONAR motion detection ([0025], e.g. Examples of radio modules or wireless hardware that provide RSSI include, but are not limited to, mobile phones, IEEE 802.11 wireless Internet routers and cards (WiFi), and IEEE 802.15.4 modules (Zigbee). [0017] Recent research and advancements have developed motion and presence sensing techniques that utilize received signal strength (RSS) measurements from wireless devices. For example, researchers have demonstrated motion detection using RSS measurements in IEEE 802.15.4/802.11 networks).
Regarding claim 18, Wilson in view of Omer teaches all the limitations of claim 15. Wilson further teaches wherein the one or more network conditions comprise one or more of: a quantity of devices connected to a local network, a change in the quantity of devices connected to the local network, available bandwidth associated with the local network, or one or more environmental conditions ([0025], e.g. The nodes 102 can be any radio module or any wireless hardware capable of measuring signal strength. The signal strength measurements may be measured and/or reported by a link quality indicator (LQI) of the radio module or wireless hardware (I.e. the network conditions comprise a quantity of devices connected to a local network)).
Regarding claim 19, Wilson in view of Omer teaches all the limitations of claim 15. Omer further teaches wherein further comprising: sounding the group of network devices ([0034], e.g. In the example shown in FIG. 1, the wireless communication devices transmit wireless signals to each other over wireless communication links (e.g., according to a wireless network standard or a non-standard wireless communication protocol), and the wireless signals communicated between the devices can be used as motion probes to detect motion of objects in the signal paths between the devices (i.e. sounding the one or more stationary network devices). In some implementations, standard signals (e.g., channel sounding signals, beacon signals), non-standard reference signals, or other types of wireless signals can be used as motion probe);
based on sounding the group of network devices, detecting a trigger event ([0035] In the example shown in FIG. 1, the wireless communication link between the wireless communication devices 102A, 102C can be used to probe a first motion detection zone 110A. [0036] In the example shown in FIG. 1, when an object moves in any of the motion detection zones 110 (I.e. generating a motion based trigger event) , the motion detection system may detect the motion based on signals transmitted through the relevant motion detection zone 110 (i.e. stationary network devices generate motion indications). Generally, the object can be any type of static or moveable object, and can be living or inanimate. For example, the object can be a human (e.g., the person 106 shown in FIG. 1); and
based on detecting the trigger event, sending a message ([0037] e.g. In some instances, the motion detection system may communicate (i.e. sends a message) the motion detection event to another device or system, such as a security system or a control center).
The motivation to combine reference of Omer within the method of Wilson before the effective filing date of the invention is that the new method provides techniques that that a wireless sensing system can process wireless signals transmitted through a space between wireless communication devices for wireless sensing applications. Example wireless sensing applications include smoking detection, school violence detection, human counting and metal detection (See Omer [abstract, 0017]).
Regarding claim 20, Wilson in view of Omer teaches all the limitations of claim 19. Wilson further teaches wherein further comprising determining one or more resource requirements associated with the plurality of network devices in the group of network devices ([0027], e.g. One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. increasing nodes based resources on the network). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6).
Regarding claim 21, Wilson in view of Omer teaches all the limitations of claim 15. Wilson further teaches wherein further comprising: detecting a new network device on the network ([0027] One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. determining, based on signal characteristics associated with one or more network devices, additional stationary network devices). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6);
determining one or more signal characteristics associated with the new network device ([0043] The time varying aggregate disturbance Q(t) can be used to detect presence and/or motion, or to estimate other valuable characteristics, such as quantity, velocity, or size); and
including, based on the one or more signal characteristics associated with the new network device, the new network device in the updated group of network devices ([0025], Fig. 5, e.g. the nodes 102 can be any radio module or any wireless hardware capable of measuring signal strength. The signal strength measurements may be measured and/or reported by a received signal strength indicator (RSSI) (I.e. first motion indicator and first group is based on the RSSI signal). [0058] If the node is node k+1 (it is the node's turn to transmit), then the node broadcasts 514 the RSSI/LQI vector. The RSSI/LQI vector has been filled with measurements as each of the other nodes has transmitted to the currently transmitting node. This cycle may be repeated indefinitely, filling the RSSI/LQI vector upon receipt of packets from the other nodes in the network, and then broadcasting the values in the RSSI/LQI vector to the other nodes when the protocol allows (I.e. receiving motion indicators at the first and the second group Devices based on the RSSI or LQI signal respectively)).
Regarding claim 22, Wilson teaches a method ([0018], e.g. The present disclosure is directed to systems and methods of device-free motion and presence detection. The disclosed systems and methods may include a mesh network RF sensing technology that can detect and quantify the presence or motion of people and other objects within an area of interest. [0056] Detecting and estimating device-free characteristics using RSS measurements presents some unique wireless protocol challenges. Maintaining the transmission of each node in the network at a high level may be desirable in order to capture fast movements. However, as the number of nodes in the network increases, having each node reduce its rate of transmission may be desirable to avoid collisions), comprising:
determining, based on one or more signal characteristics associated with one or more network devices connected to a network ([0026], e.g. The base station control 103 may be a node 102 that has special responsibilities to report signal strength measurements to a processing unit, such as the client computing device 104. [0027] One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. determining, based on signal characteristics associated with one or more network devices, additional stationary network devices). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6. [0043] The time varying aggregate disturbance Q(t) can be used to detect presence and/or motion, or to estimate other valuable characteristics, such as quantity, velocity, or size),
a group of network devices, wherein the group of network devices comprises one or more stationary network devices ([0020], e.g. Furthermore, a network can self-form and self-heal when nodes are added or removed (I.e. stationary network devices are detected when they are added). The computations to determine detection network statistics can be arranged in various client-servers and distributed processing architectures),
detecting a new network device on the network ([0026], e.g. The base station control 103 may be a node 102 that has special responsibilities to report signal strength measurements to a processing unit, such as the client computing device 104. [0027] One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. determine and assigning, based on signal characteristics associated with one or more network devices, additional stationary network devices). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6);
determining the new network device is a stationary network device ([0025], Fig. 5, e.g. the nodes 102 can be any radio module or any wireless hardware capable of measuring signal strength. The signal strength measurements may be measured and/or reported by a received signal strength indicator (RSSI) (I.e. first motion indicator and first group is based on the RSSI signal) );
determining one or more resource requirements ([0027], e.g. One of the nodes 102 may be designated a schedule manager 113 to manage "join beacons" and "join requests," for automatically adding additional nodes 102 to the wireless detection network 101 (i.e. increasing nodes based resources on the network). Automatic addition and removal of nodes 102 from the wireless detection network 101 is discussed in more detail below with reference to FIG. 6), and
one or more performance specifications associated with the new network device ([0040], e.g. Calibration can also be performed while the system is in use, and adjusted for better performance over time (i.e. determining one or more performance specifications). Instead of using data from a known calibration period, measurements from recent history can be processed and used for comparison to current measurements. The simplest example of this is using changes to the mean of each link. A long history of data can be used to determine the calibration mean for each link, while the mean of shorter histories can be used to see if something has changed recently).
Wilson teaches systems and methods for device-free motion detection and presence detection within an area of interest. However Wilson differs from the claimed invention in not specifically and clearly describing wherein
based on the new network device being the stationary network device, updating, based the one or more resource requirements or one or more performance specifications, the group of network devices.
However, in the analogous field of endeavor, Omer teaches wherein
based on the new network device being the stationary network device, updating, based the one or more resource requirements or one or more performance specifications, the group of network devices ([0025], e.g. In some instances, a wireless sensing system can be implemented using a wireless communication network. Wireless signals received at one or more wireless communication devices in the wireless communication network may be analyzed to determine channel information for the different communication links (between respective pairs of wireless communication devices) in the network) (I.e. updating, based the one or more channel quality resource requirements in a network). [0026] The channel information for each of the communication links may be analyzed by one or more motion detection algorithms (e.g., running on a hub device, a client device, or other device in the wireless communication network-1, or on a remote device communicably coupled to the network-2).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the invention to implement the method of Omer within the method of Wilson. The motivation to combine references is that the combined method provides that a wireless sensing system can process wireless signals (e.g., radio frequency signals) transmitted through a space between wireless communication devices for wireless sensing applications. Example wireless sensing applications include detecting motion, which can include one or more of the following: detecting motion of objects in the space, motion tracking, localization of motion in a space, breathing detection and breathing monitoring (See Omer [abstract, 0017]).
Regarding claim 23, Wilson in view of Omer teaches all the limitations of claim 22. Wilson further teaches wherein the one or more network devices are configured for one or more of: WiFi motion detection, BLUETOOTH motion detection, LIDAR motion detection, RADAR motion detection, or SONAR motion detection ([0025], e.g. Examples of radio modules or wireless hardware that provide RSSI include, but are not limited to, mobile phones, IEEE 802.11 wireless Internet routers and cards (WiFi), and IEEE 802.15.4 modules (Zigbee). [0017] Recent research and advancements have developed motion and presence sensing techniques that utilize received signal strength (RSS) measurements from wireless devices. For example, researchers have demonstrated motion detection using RSS measurements in IEEE 802.15.4/802.11 networks).
Regarding claim 24, Wilson in view of Omer teaches all the limitations of claim 22. Omer further teaches wherein determining the group of network devices comprises determining one or more stationary network devices with independent signal paths ([0034], e.g. the wireless signals communicated between the devices can be used as motion probes to detect motion of objects in the signal paths between the devices (i.e. determining stationary network devices associated with one or more signal (i.e. sounding) paths). In some implementations, standard signals (e.g., channel sounding signals, beacon signals), non-standard reference signals, or other types of wireless signals can be used as motion probes).
The motivation to combine reference of Omer within the method of Wilson before the effective filing date of the invention is that the new method provides techniques that that a wireless sensing system can process wireless signals transmitted through a space between wireless communication devices for wireless sensing applications. Example wireless sensing applications include smoking detection, school violence detection, human counting and metal detection (See Omer [abstract, 0017]).
Regarding claim 25, Wilson in view of Omer teaches all the limitations of claim 22. Omer further teaches wherein further comprising: sounding the group of network devices [0034], e.g. In the example shown in FIG. 1, the wireless communication devices transmit wireless signals to each other over wireless communication links (e.g., according to a wireless network standard or a non-standard wireless communication protocol), and the wireless signals communicated between the devices can be used as motion probes to detect motion of objects in the signal paths between the devices (i.e. sounding the one or more stationary network devices). In some implementations, standard signals (e.g., channel sounding signals, beacon signals), non-standard reference signals, or other types of wireless signals can be used as motion probe);
based on sounding the group of network devices, detecting a trigger event ([0035] In the example shown in FIG. 1, the wireless communication link between the wireless communication devices 102A, 102C can be used to probe a first motion detection zone 110A. [0036] In the example shown in FIG. 1, when an object moves in any of the motion detection zones 110 (I.e. generating a motion based trigger event) , the motion detection system may detect the motion based on signals transmitted through the relevant motion detection zone 110 (i.e. stationary network devices generate motion indications). Generally, the object can be any type of static or moveable object, and can be living or inanimate. For example, the object can be a human (e.g., the person 106 shown in FIG. 1); and
based on detecting the trigger event, sending a message ([0037] e.g. In some instances, the motion detection system may communicate (i.e. sends a message) the motion detection event to another device or system, such as a security system or a control center).
The motivation to combine reference of Omer within the method of Wilson before the effective filing date of the invention is that the new method provides techniques that that a wireless sensing system can process wireless signals transmitted through a space between wireless communication devices for wireless sensing applications. Example wireless sensing applications include smoking detection, school violence detection, human counting and metal detection (See Omer [abstract, 0017]).
Regarding claim 26, Wilson in view of Omer teaches all the limitations of claim 25. Omer further teaches wherein the trigger event comprises one or more of: a motion detection event, a premises entry event, or a premises exit event ([0035] In the example shown in FIG. 1, the wireless communication link between the wireless communication devices 102A, 102C can be used to probe a first motion detection zone 110A. [0036] In the example shown in FIG. 1, when an object moves in any of the motion detection zones 110 (I.e. generating a motion based trigger event) , the motion detection system may detect the motion based on signals transmitted through the relevant motion detection zone 110 (i.e. stationary network devices generate motion indications). Generally, the object can be any type of static or moveable object, and can be living or inanimate. For example, the object can be a human (e.g., the person 106 shown in FIG. 1).
The motivation to combine reference of Omer within the method of Wilson before the effective filing date of the invention is that the new method provides techniques that that a wireless sensing system can process wireless signals transmitted through a space between wireless communication devices for wireless sensing applications. Example wireless sensing applications include smoking detection, school violence detection, human counting and metal detection (See Omer [abstract, 0017]).
Allowable Subject Matter
Claim 13 is objected to as being dependent upon a rejected base claim, but would be allowable, if rewritten in independent form including all of the limitations of the base claim and any intervening claims, and amending claims to overcome any objection(s) and /or rejection(s) set forth in this Office action.
Prior Art Record
The prior art made of record and not relied upon is considered pertinent
to applicant’s disclosure.
Haiut; Moshe (US-20140140231-A1) - METHOD AND SYSTEM FOR MOTION DETECTION USING DIGITAL ENHANCED CORDLESS TELECOMMUNICAITON (DECT) SIGNALS.
Kravets; Oleksiy (US-9523760-B1) - Detecting motion based on repeated wireless transmissions.
Manku; Tajinder (US-10264405-B1) - Motion detection in mesh networks.
Kumaran; Vikram (US-20190312876-A1) - IDENTIFYING AND BLACKLISTING PROBLEM CLIENTS USING MACHINE LEARNING IN WIRELESS NETWORKS.
Ravkine; Mikhail (US-10498467-B1) - Classifying static leaf nodes in a motion detection system.
Chen; Tianwen (US-20220070975-A1) - METHODS, SYSTEMS, AND APPARATUSES FOR PRESENCE DETECTION.
BEG CHRIS (WO-2023223217-A1) - SYSTEMS AND METHODS FOR SELECTING AND UPDATING A SET OF SOUNDING DEVICES.
PENG YUXIANG (WO-2024054292-A2) - DETERMINING AN ORIENTATION OF A USER EQUIPMENT WITH A CELLULAR NETWORK.
Conclusion
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/MAHENDRA R PATEL/ Primary Examiner, Art Unit 2645