DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
This is a response to U.S. Patent Application No. 18/560,362 filed on 11/10/2023 in which Claims 1 – 20 were filed for examination.
Election/Restrictions
Applicant's election with traverse of Group 1, Claims 1 – 15 in the reply filed on 03/30/2026 is acknowledged. The traversal is on the ground(s) that Satoi does not disclose a building management system, receiving inputs from building devices, or controlling one or more building devices as alleged at page 4 of the Office Action. Instead, Satoi relates to a “biological information detection device” that detects light reflected from a patient and measures biological parameters based on the detected light. Satoi at abstract, figures. Such a device is not within the broadest reasonable interpretation of a “building inputs from building devices”, page 4 of the restriction requirement cites measurement of “a change in the cerebral blood flow rate and blood flow component” of a human, which is a measurement of blood flow in a human, not “inputs from building devices”.
This is not found persuasive because Satoi in par 0044, teaches estimating a level of concentration, emotions and others of a subject, and controlling various instruments according to a result of the estimation. Satoi in par 0048, further teaches that a biological information detection device in operation, generates a signal of biological information related to a blood flow in a target area in the test portion based on the electrical signal, in which the light detector is an image sensor, the electrical signal includes an image signal obtained by the image sensor. Satoi in par 0113, further teaches that in response to a change in feelings of human, the activity of nerve cells changes, and thereby the cerebral blood flow rate or blood flow component is changed. Thus, measurement of biological information such as a change in the cerebral blood flow rate and blood flow component makes it possible to estimate the mental state of a subject.
Satoi in par 0218, further teaches that the environmental control device includes the biological information detection device 100. The environmental control device 700 may be an air conditioner or an audio, for instance. A device capable of controlling such surrounding environment (such as temperature, sound, light, humidity and smell) of a user is referred to as an “environmental control device” in the present description. In this embodiment, the subject O may be one or a plurality of users of the environmental control device 700.
Accordingly, Satoi teaches the use of a biological information detection device positioned within devices in a location capable of controlling the surrounding environment and using the obtained data to estimate the level of concentration, emotions and others of a subject and controlling various instruments according to a result of the estimation. Accordingly, Satoi teaches a building management system, receiving inputs from building devices and controlling one or more building devices.
The requirement is still deemed proper and is therefore made FINAL.
Status of the Claims
Claims 1 – 15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph and Claims 1 – 5, and 9 – 15 are rejected under 35 U.S.C. 103.
Examiner Note
The Examiner cites particular columns, line numbers and/or paragraph numbers in the references as applied to the claims below for the convenience of the Applicant(s). Although the specified citations are representative of the teachings in the art and are applied to the specific limitations within the individual claim, other passages and figures may apply as well. It is respectfully requested that, in preparing responses, the Applicant fully consider the references in their entirety as potentially teaching all or part of the claimed invention, as well as the context of the passage as taught by the prior art or disclosed by the Examiner.
Information Disclosure Statement
The information disclosure statement (IDS) submitted on 01/08/2024 have been entered and considered by the examiner.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 1 – 15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claims 1 recites “control one or more of the building devices based on the SoM score while maintaining a temperature, a humidity, and a pressure within a compliance standard within the building”. This claim language is indefinite, because it is unclear which type of pressure the system is controlling, The claim recites a pressure within a compliance standard within the building but it is unclear which type of pressure the claim is intending to control.
After despite reviewing of the disclosure (See paragraph 0031), it appears that the controlled pressure may be associated with the airflow within a building.
For purposes of examination, the examiner is interpreting the claim as pressure associated with the airflow.
Due to at least their dependency upon Claim 1, Claims 2 – 15 are also indefinite.
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.
Claims 1 – 5 and 11 – 15 are rejected under 35 U.S.C. 103 as being unpatentable over Satoi et al. (US 2017/0231544) (hereinafter, Satoi) (cited in IDs dated 01/02/2024) in view of Raveendran et al. (WO-2019/063079) (hereinafter, Raveendran) (Cited in IDs dated 01/08/2024).
Regarding Claim 1, Satoi teaches a building management system (BMS) of a building for controlling a healthcare facility (See Satoi’s par 0005 and par 0044), the BMS comprising:
one or more processing circuits comprising one or more memory devices configured to store instructions thereon that, when executed by one or more processors (Satoi in par 0105 and Fig. 3, teaches that the processor 150 includes a read only memory (ROM) 152, a random access memory (RAM) 153, a control circuit 155, and the calculation circuit 200. The control circuit 155 is an integrated circuit including, for instance, a central processing unit (CPU). The control circuit 155 controls the entire operation of the biological information detection device 100), cause the one or more processors to:
receive inputs from building devices (Satoi in par 0075, teaches that a light detector 140 converts the entered light into an electrical signal, and outputs the signal. The calculation circuit 200 generates biological information related to the blood flow in the test portion based on the signal outputted from the light detector 140. Satoi in par 0113, further teaches that measurement of biological information such as a change in the cerebral blood flow rate and blood flow component makes it possible to estimate the mental state of a subject);
determine a state-of-mind (SoM) score of a patient based on the inputs using a learning model (Satoi in par 0044, teaches that in communication (hereinafter may be referred to as “conversation”) of a user with an interactive robot via voice or image, control that changes the contents of the conversation according to a level of concentration or a mental state of the user may also be adopted. Satoi in par 0113, teaches that in response to a change in feelings of human, the activity of nerve cells changes, and thereby the cerebral blood flow rate or blood flow component is changed. Thus, measurement of biological information such as a change in the cerebral blood flow rate and blood flow component makes it possible to estimate the mental state of a subject. The mental state of a subject indicates, for instance, a feeling (such as comfort and discomfort), an emotion (such as relief, anxiety, sadness and anger), a physical condition (such as liveliness and fatigue), and temperature sensation (such as hot, cold and sultry). In addition, as a derivative state, the mental state also includes an index indicating a degree of brain activity, for instance, a level of proficiency, a level of mastery, and a level of concentration); and
control one or more of the building devices based on the SoM score while maintaining a temperature, a humidity (Satoi in par 0044, teaches control on setting the temperature of an air conditioner or changing the sound volume of audio equipment according to an emotion (including sensation of heat, cold, etc.) of an indoor user may also be adopted. Satoi in par 0218, further teaches that the environmental control device 700 may be an air conditioner. A device capable of controlling such surrounding environment (such as temperature, sound, light, humidity and smell) of a user is referred to as an “environmental control device”. Satoi in par 0221, further teaches that where the environmental control device 700 is an air conditioner, the environmental control device 700 can automatically turn on the power supply to start the operation or decrease or increase the preset temperature during the operation. In the case where the environmental control device 700 is an audio device, the environmental control device 700 may automatically turn the sound volume down, and may automatically select a music piece (such as a classical music piece) which is expected to provide a relaxing effect, for instance).
Satoi in par 0218, teaches the control of surrounding environment of a user
However, does not specifically disclose the control of “a pressure within a compliance standard within the building”.
Raveendran teaches a method for energy and comfort optimization in a building automation environment (See Abstract). Raveendran in page 46 lines 1 – 18, further teaches that the parameters which are monitored in a home automation environment to optimize energy consumption includes environmental conditions such as temperature, humidity pressure m natural lighting etc.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to utilize the teachings as in Raveendran with the teachings as in Satoi to include pressure in the surrounding environment of Satoi as disclosed in Raveendran. The motivation for doing so would have been to effectively control the surrounding environment parameters, thus optimizing user comfort (See Raveendran’s Abstract).
Regarding Claim 2, Satoi in view of Raveendran teaches the limitations contained in parent Claim 1.
Satoi further teaches:
wherein the one or more memory devices are further configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
determine the SoM score based on visual information, audio information, nurse call information, thermostat information, and occupancy information (Satoi in par 0044, teaches that in communication (hereinafter may be referred to as “conversation”) of a user with an interactive robot via voice or image, control that changes the contents of the conversation according to a level of concentration or a mental state of the user may also be adopted. In addition, control on an automated driving vehicle according to a level of concentration of a driver, and control on setting the temperature of an air conditioner or changing the sound volume of audio equipment according to an emotion (including sensation of heat, cold, etc.) of an indoor user may also be adopted. Satoi in par 0113, further teaches that the mental state of a subject indicates, for instance, a feeling (such as comfort and discomfort), an emotion (such as relief, anxiety, sadness and anger), a physical condition (such as liveliness and fatigue), and temperature sensation (such as hot, cold and sultry).
Regarding Claim 3, Satoi in view of Raveendran teaches the limitations contained in parent Claim 1. Satoi further teaches:
wherein the one or more memory devices are further configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
determine the SoM score based on electronic medical records information (Satoi in par 0113, further teaches that in response to a change in feelings of human, the activity of nerve cells changes, and thereby the cerebral blood flow rate or blood flow component is changed. Thus, measurement of biological information such as a change in the cerebral blood flow rate and blood flow component makes it possible to estimate the mental state of a subject. The mental state of a subject indicates, for instance, a feeling (such as comfort and discomfort), an emotion (such as relief, anxiety, sadness and anger), a physical condition (such as liveliness and fatigue), and temperature sensation. Satoi in par 0130, further teaches that the calculation circuit 200 estimates a mental state of the subject based on the biological information. For instance, the calculation circuit 200 estimates a mental state such as a level of concentration and an emotion of the subject O based on the oxygenation state of hemoglobin).
Regarding Claim 4, Satoi in view of Raveendran teaches the limitations contained in parent Claim 1. Raveendran further teaches:
wherein the one or more processing circuits include one or more processing circuits located on-premises and comprising one or more on-premises memory devices, and one or more processing circuits located off-premises and comprising one or more off-premises memory devices (Raveebdran in page 19 lines 8 – 19, further teaches that each building includes a learning agent capable of optimizing energy and comfort for each of the buildings individually. Raveendran in page 53, lines 20 – 25, further teaches distributed circuit settings where circuitry is connected via communication buses, circuitry or links. In distributed settings, control/instructions may occur from both local and remote computer storage media including memory storage devices); and
wherein the one or more off-premises memory devices are configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
receive confidential information (Raveendran in page 39 lines 23 – 32, further teaches that parameters tat alter the state of the home automation environment 302 and the effective goal of reducing energy consumption with improved comfort are stored in a database on the computing device.; and
train the learning model using the received confidential information (Raveendran in page 39 line 23 – page 40 line 3, further teaches that the computing device 340 re-trains the home model at predetermined time intervals. The re-training is based on the experience gained throughput the pre-determined interval. The re-trained model is then used to repeat the step 410 whereby the energy and comfort of the home automation environment 302 is optimized); and
wherein the one or more on-premises memory devices are configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
receive the trained learning model (Raveendran in page 10 lines 26 – 30, further teaches that the building model generator generates a building model of the building automation environment. The building model is a virtual replica of the building automation environment that is trained based on historical environment data or predicted environment data or a combination. Raveendran in page 14, lines 9 – 16, further teaches that the energy learning agent is initially trained with the predicted environment data for the building automation environment. The energy learning agent can be trained to learn situations it has not encountered);
receive the inputs from in-room devices (Raveendran in page 17 lines 11 – 16, teaches that the occupant can either accept or reject the recommended state and the system automatically adapts to feedback from the occupant in order to provide maximum energy saving while not compromising on the occupant comfort levels. Raveendran in page 18 lines 15 – 21, further teaches that the feedback can be provided either via the application installed on the user device or directly through interaction with the system via voice command); and
implement the learning model (Raveendran in page 3 lines 7 – 15, teaches that the system controls and monitors the building mechanical, structural and electrical equipment such as ventilation, lighting, power systems, fire systems, and security systems and monitors occupant behavior and activity to optimize energy comfort. Raveendran in page 18 lines 15 – 21, further teaches that the comfort learning agent in combination with the emotion and behavior analyzer understand discomfort in voice patterns of the occupant to determine the comfort reward vectors that automatically generate a new comfort action)..
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to utilize the teachings as in Raveendran with the teachings as in Satoi to receive user feedback in Satoi as disclosed in Raveendran. The motivation for doing so would have been to effectively control the surrounding environment parameters, thus optimizing user comfort (See Raveendran’s Abstract).
Regarding Claim 5, Satoi in view of Raveendran teaches the limitations contained in parent Claim 4. Satoi further teaches:
wherein the one or more on-premises memory devices are configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
control the one or more room devices automatically based on the SoM score (Satoi in par 0044, teaches estimating a level of concentration, emotions and others of a subject, and controlling various instruments according to a result of the estimation. Control on setting the temperature of an air conditioned or changing the sound volume of audio equipment according to an emotion of an indoor user).
Regarding Claim 11, Satoi in view of Raveendran teaches the limitations contained in parent Claim 1. Satoi further teaches:
wherein the one or more memory devices are further configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
determine that the SoM score is less than a threshold (Satoi in par 0044, teaches estimating a level of concentration, emotions and others of a subject, and controlling various instruments according to a result of the estimation. Satoi in par 0178, further teaches that the calculation circuit 200 measures the variance of the period of pulse wave in a predetermined time period, and can determine a mental state such as a concentrated state and a relaxed state. In general, in a concentrated or nervous state, the period of pulse wave tends to be uniform, whereas in a relaxed state, the period of pulse wave tends to vary. Thus, when the variance of the period is less than a predetermined value, the calculation circuit 200 determines that the subject O is in a concentrated state or in a nervous state. With the breathing, the variance may gradually increase and exceed a predetermined value. In this case, the calculation circuit 200 may determine that the subject O is in a relaxed state); and
adjust the temperature or lighting of the healthcare facility automatically based on the SoM score being less than the threshold to meet a patient preference (Satoi in par 0044, teaches estimating a level of concentration, emotions and others of a subject, and controlling various instruments according to a result of the estimation. Control on setting the temperature of an air conditioned or changing the sound volume of audio equipment according to an emotion of an indoor user).
Regarding Clam 12, Satoi in view of Raveendran teaches the limitations contained in parent Claim 1. Raveendran further teaches:
wherein the one or more memory devices are further configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
receive a data set of historical environmental changes and correlated patient reactions (Raveendran in page 4 lines 7 – 17, teaches that the building model for the building automation environment can be generated based on a historical environment data and a predicted environment data. The historical environment data refers to the sensor data, the energy data and the ambient data of the building automation environment that is previously recorded). ;
build patient profiles based on the data set (Raveendran in page 15 lines 20 – 29, teaches that the convolutional networks are capable of extracting relevant information from the pixels of the video data and image data which is fed into a fully-connected neural network. The behavior or activity such as sleeping, eating, cooking, walking, position of the occupant, etc. are recognized by determining a softmax output to profile the occupant);
associate the patient with a patient profile (Raveendran in page 30 lines 4 – 10, further teaches that the occupant data is used to build the occupant profile of the occupant in the building automation environment. Raveendran in page 32, lines 7 – 16, further teaches that where there are multiple occupants, the clustering module 224 clusters the occupants into groups based on similarity in occupant profile);
input the patient profile to the learning model to affect the determination of the SoM score (Raveendran in page 6 lines 6 – 9, teaches that deep reinforcement learning includes multiple objectives such as reduced energy utilization and improved comfort in the building automation environment. Raveendran in page 26 line 30 – page 27 line 9, further teaches that the optimization of the energy and the comfort in the office space is performed by clustering the occupants into groups based on similarity in occupant profile. Occupant profile is emotion and behavior patterns of the occupant. The energy and comfort is optimized by optimizing energy and comfort at multiple sections based on a section optimization policy for each of the sections).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to utilize the teachings as in Raveendran with the teachings as in Satoi to receive user feedback in Satoi as disclosed in Raveendran. The motivation for doing so would have been to effectively control the surrounding environment parameters, thus optimizing user comfort (See Raveendran’s Abstract).
Regarding Claim 13, Satoi in view of Raveendran teaches the limitations contained in parent Claim 1. Raveendran further teaches:
wherein the one or more memory devices are further configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
receive patient feedback (Raveendran in page 7 lines 10 – 26, further teaches that feedback from the occupant can also be received. The occupant feedback on the new state of the building automation environment is received after analyzing emotion and behavior of the occupant); and
update the learning model based on the patient feedback (Raveendran in page 7 lines 10 – 26, further teaches that the building environment model is updated at predetermined intervals with the occupant feedback).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to utilize the teachings as in Raveendran with the teachings as in Satoi to receive user feedback in Satoi as disclosed in Raveendran. The motivation for doing so would have been to effectively control the surrounding environment parameters, thus optimizing user comfort (See Raveendran’s Abstract).
Regarding Claim 14, Satoi in view of Raveendran teaches the limitations contained in parent Claim 1. Satoi further teaches:
wherein the one or more memory devices are further configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
monitor the SoM score over time (Satoi in par 0044, further teaches that in communication of a user with an interactive robot via voice or image, control that changes the contents of the conversation according to a level of concentration or a mental state of the user may also be adopted. In addition, control on setting the temperature of an air conditioner or changing the sound volume of audio equipment according to an emotion of an indoor user may also be adopted. Satoi in par 0113, further teaches that measurement of biological information such as a change in the cerebral blood flow rate and blood flow component makes it possible to estimate the mental state of a subject);
input a change of the SoM score over time into the learning model (Satoi in par 0044, teaches that in communication (hereinafter may be referred to as “conversation”) of a user with an interactive robot via voice or image, control that changes the contents of the conversation according to a level of concentration or a mental state of the user may also be adopted. Satoi in par 0113, teaches that in response to a change in feelings of human, the activity of nerve cells changes, and thereby the cerebral blood flow rate or blood flow component is changed. Thus, measurement of biological information such as a change in the cerebral blood flow rate and blood flow component makes it possible to estimate the mental state of a subject. The mental state of a subject indicates, for instance, a feeling (such as comfort and discomfort), an emotion (such as relief, anxiety, sadness and anger), a physical condition (such as liveliness and fatigue), and temperature sensation (such as hot, cold and sultry). In addition, as a derivative state, the mental state also includes an index indicating a degree of brain activity, for instance, a level of proficiency, a level of mastery, and a level of concentration. Satoi in par 0178, further teaches that the calculation circuit 200 measures the variance of the period pulse wave in a predetermined time period and can determine a mental state); and
control the one or more room devices automatically based of the change of the SoM score over time (Satoi in par 0044, further teaches estimating a level of concentration, emotions and others of a subject, and controlling various instruments according to a result of the estimation. Control on setting the temperature of an air conditioner or changing the sound volume of audio equipment according to an emotion (including sensation of heat, cold, etc.) of an indoor user may also be adopted).
Regarding Claim 15, Satoi in view of Raveendran teaches the limitations contained in parent Claim 1. Raveendran further teaches:
wherein the one or more memory devices are further configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
receive inputs from room devices including audio data from at least one audio sensor (Raveendran in page 17 lines 11 – 16, teaches that the occupant can either accept or reject the recommended state and the system automatically adapts to feedback from the occupant in order to provide maximum energy saving while not compromising on the occupant comfort levels. Raveendran in page 18 lines 15 – 21, further teaches that the feedback can be provided either via the application installed on the user device or directly through interaction with the system via voice command);
analyze the audio data using voice recognition to convert speech from a first occupant of the building into a command (Raveendran in page 18 lines 15 – 21, further teaches that the comfort learning agent in combination with the emotion and behavior analyzer understand discomfort in voice patterns of the occupant to determine the comfort reward vectors that automatically generate a new comfort action); and
controlling the one or more room devices based on the command (Raveendran in page 3 lines 7 – 15, teaches that the system controls and monitors the building mechanical, structural and electrical equipment such as ventilation, lighting, power systems, fire systems, and security systems and monitors occupant behavior and activity to optimize energy comfort. Raveendran in page 18 lines 15 – 21, further teaches that the comfort learning agent in combination with the emotion and behavior analyzer understand discomfort in voice patterns of the occupant to determine the comfort reward vectors that automatically generate a new comfort action).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to utilize the teachings as in Raveendran with the teachings as in Satoi to allow the user of Satoi to perform voice commands as disclosed in the Raveendran. The motivation for doing so would have been to effectively control the surrounding environment parameters, thus optimizing user comfort (See Raveendran’s Abstract).
Claim(s) 9 and 10 are rejected under 35 U.S.C. 103 as being unpatentable over Satoi in view or Raveendran and in further view of Prugh et al. (US 2020/0341457) (hereinafter, Prugh).
Regarding Claim 9, Satoi in view of Raveendran teaches the limitations contained in parent Claim 1.
However, Satoi in view of Raveendran does not specifically disclose
wherein the one or more memory devices are further configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
determine a number of visitors over a specified period of time based on the inputs from the building devices; and
control one or more room devices automatically including a nurse call system to prompt a visit based on the number of visitors over a specified period of time.
Prugh in par 0033, teaches that floor contact sensors located in a room of a property can collect data that can be processed to determine the number of people in the room. Prugh in par 0124, further teaches that to prevent noise and damage to the property that can be cause by large parties, the property owners may write the terms of the rental agreement limiting the number of people allowed in the property to six people. Prugh in par 0130, further teaches that the monitoring system can correlate the floor contact sensor 210a data with other sensor data. For example, if there are a large number of people gathered in a room, the temperature of the room will rise over time. Additionally, a door sensor can detect how many times the front door 230a opens and shuts, which can assist the monitoring system in approximating the number of guests.
Prugh in par 0201, further teaches that the threshold occupancy of the property may be ten people. Therefore, the monitoring system can determine that the occupancy of the living room exceeds the threshold occupancy of the property. In response to determining that the occupancy of the living room exceeds the threshold occupancy of the property, the monitoring system can perform a monitoring system action, for example, by sending a notification to an owner of the property indicating that the occupancy exceeds the threshold occupancy.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to utilize the teachings as in Prugh with the teachings as in Satoi and Raveendran to monitor the number of persons in room in Satoi as disclosed in Prugh. The motivation for doing so would have been to effectively provide a monitoring system that track the number of visitors, thus enhancing security,, safety and convenience of the property (See Prugh’s par 0033, 0168 and 0201).
Regarding Claim 10, Satoi in view of Raveendran teaches the limitations contained in parent Claim 1.
However, Satoi in view of Raveendran does not specifically disclose wherein the one or more memory devices are further configured to store instructions thereon that, when executed by the one or more processors, cause the one or more processors to:
determine a number of visitors over a specified period of time based on the inputs from the building devices; and
push a notification to an identified user device to request a point of contact based on the number of visitors over a specified period of time.
Prugh in par 0033, teaches that floor contact sensors located in a room of a property can collect data that can be processed to determine the number of people in the room. Prugh in par 0130, further teaches that the monitoring system can correlate the floor contact sensor 210a data with other sensor data. For example, if there are a large number of people gathered in a room, the temperature of the room will rise over time. Additionally, a door sensor can detect how many times the front door 230a opens and shuts, which can assist the monitoring system in approximating the number of guests.
Prugh in par 0131, further teaches that the monitoring system analyzes the data 235a from the floor contact sensor 210a and the sensors at the property. The monitoring system makes a determination that there are approximately 10 to 15 people in the living room, and takes an action 240a. The monitoring system takes the action 240a of notifying the property owner of the high occupancy at the property. The monitoring system sends a notification to the property owner's mobile device that there are approximately 10 to 15 people gathered in the living room. This can prompt the property owner to visit the property or to call the occupants and ask if they are throwing a party, violating the terms of the lease.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date to utilize the teachings as in Prugh with the teachings as in Satoi and Raveendran to monitor the number of persons in room in Satoi as disclosed in Prugh. The motivation for doing so would have been to effectively provide a monitoring system that track the number of visitors, thus enhancing security,, safety and convenience of the property (See Prugh’s par 0033, 0168 and 0201).
Allowable Subject Matter
Claims 6 – 8 are 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.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ARIEL MERCADO VARGAS whose telephone number is (571)270-1701. The examiner can normally be reached M-F 8:00am - 4:00pm.
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/ARIEL MERCADO-VARGAS/Primary Examiner, Art Unit 2118
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