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 .
Status of Claims
This action is in reply to the application filed on 3/5/2025 which is a Continuation of Application 18/396058 which was issued as US Patent No. 12,266,020; which is a Continuation of Applications 17/346818, 15/844830, 17/346818, and 18/163051, wherein:
Claims 1-21 are currently pending and have been examined.
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-21 of Application 19/071,449 are rejected on the ground of nonstatutory double patenting as being unpatentable over: claims 1-21 of US 12,266,020; claims 1-14 of US Patent No. 11,068,991; claims 1-21 of US Patent No. 11,599,952; and claims 1-21 of US 11,893,645. Although the claims at issue are not identical, they are not patentably distinct from each other because: the claims of: the ‘058 Patent; the ‘952 Patent, the 645’ Patent, and the 991’ Patent, recite all the limitations in claims 1-21 of the instant Application No. 18/396,058 as indicated in the comparison table below.
Claims of 19/071449
US 12266020
US 11893645
US 11068991
US 11599952
1. A system to facilitate predictive risk analytics for an enterprise, comprising:
(a) a risk monitoring data store containing a set of electronic data records, each electronic data record being associated with a stream of sensor data received via a first communication network from a risk monitoring site;
(b) a risk analytics platform computer, coupled to the risk monitoring data store, the risk analytics platform computer including a processor and a memory in communication with the processor and storing program instructions for
controlling the processor;
(c) a risk operations platform which includes a thresholding process;
(d) a set of sensor systems at the risk monitoring site, the set of sensors including a static sensor; and
(e) a second communication network interconnecting the risk monitoring data store with the risk analytics platform computer; wherein the risk analytics platform computer is programmed to:
(i) receive information associated with the sensor data in substantially real- time,
(ii) analyze the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with
a vibrational-damage condition and
a structural damage condition at the risk monitoring site,
(iii) adjust the at least one risk analytics algorithm based on feedback information to improve performance of the at least one risk analytics algorithm;
(iv) automatically transmit a result of the analysis to the risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the vibrational- damage condition; and
(v) analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system;
wherein said analyzing by the risk analytics platform computer is performed remotely from the risk monitoring site;
and further wherein: the stream of sensor data is associated with a physical damage sensor device including a vibration sensor;
and the sensor systems including a mobile robotic sensor, the mobile robotic sensor operating to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location.
1. A system to facilitate predictive risk analytics for an enterprise, comprising:
(a) a risk monitoring data store containing a set of electronic data records, each electronic data record being associated with a stream of sensor data received via a first communication network from a risk monitoring site;
(b) a risk analytics platform computer, coupled to the risk monitoring data store, the risk analytics platform computer including a processor and a memory in communication with the processor and storing program instructions for controlling the processor;
(c) a risk operations platform which includes a thresholding process;
(d) a set of sensor systems at the risk monitoring site, the set of sensors including a static sensor; and
(e) a second communication network interconnecting the risk monitoring data store with the risk analytics platform computer; wherein the risk analytics platform computer is programmed to:
(i) receive information associated with the sensor data in substantially real-time,
(ii) analyze the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
and a structural damage condition at the risk monitoring site,
iii) adjust the at least one risk analytics algorithm based on feedback information to improve performance of the at least one risk analytics algorithm;
(iv) automatically transmit a result of the analysis to the risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition; and
(v) analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system;
wherein said analyzing by the risk analytics platform computer is performed remotely from the risk monitoring site;
and further wherein: the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor;
and the sensor systems including a mobile robotic sensor, the mobile robotic sensor operating to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location.
1. A system to facilitate predictive risk analytics for an enterprise, comprising:
(a) a risk monitoring data store containing a set of electronic data records, each electronic data record being associated with a stream of sensor data received via a first communication network from a risk monitoring site;
(b) a risk analytics platform computer, coupled to the risk monitoring data store, the risk analytics platform computer including a processor and a memory in communication with the processor and storing program instructions for controlling the processor;
(c) a risk operations platform which includes a thresholding process;
(d) a set of sensor systems at the risk monitoring site, the set of sensors including a static sensor; and
(e) a second communication network interconnecting the risk monitoring data store with the risk analytics platform computer; wherein the risk analytics platform computer is programmed to:
(i) receive information associated with the sensor data in substantially real-time,
(ii) analyze the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and intrusion condition at the risk monitoring site,
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
4. The system of claim 1, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor
(iii) adjust the at least one risk analytics algorithm based on feedback information to improve performance of the at least one risk analytics algorithm;
(iv) automatically transmit a result of the analysis to the risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition; and
(v) analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system;
wherein said analyzing by the risk analytics platform computer is performed remotely from the risk monitoring site;
and further wherein: the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor;
and the sensor systems including a mobile robotic sensor, the mobile robotic sensor operating to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location.
1. A system to facilitate predictive risk analytics for an enterprise, comprising:
(a) a risk monitoring data store containing a set of electronic data records, each electronic data record being associated with a stream of sensor data received via a first communication network from a risk monitoring site;
(b) a risk analytics platform computer, coupled to the risk monitoring data store, the risk analytics platform computer including a processor and a memory in communication with the processor and storing program instructions for controlling the processor;
(c) a risk operations platform which includes a thresholding process;
(d) a set of sensor systems at the risk monitoring site, the set of sensors including a static sensor; and
(e) a second communication network interconnecting the risk monitoring data store with the risk analytics platform computer;
wherein the risk analytics platform computer is programmed to:
(i) receive information associated with the sensor data in substantially real-time,
(ii) analyze the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and a fire condition at the risk monitoring site,
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
4. The system of claim 1, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
Claim 1…(iii) adjust the at least one risk analytics algorithm based on feedback information to improve performance of the at least one risk analytics algorithm;
(iv) automatically transmit a result of the analysis to the risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition; and
(v) analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system;
wherein said analyzing by the risk analytics platform computer is performed remotely from the risk monitoring site;
wherein: the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor, (ii) a moisture sensor, and (iii) a vapor sensor;
and the sensor systems including a mobile robotic sensor, the mobile robotic sensor operating to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location.
1. A system to facilitate predictive risk analytics for an enterprise, comprising:
(a) a risk monitoring data store containing a set of electronic data records, each electronic data record being associated with a stream of sensor data received via a first communication network from a risk monitoring site;
(b) a risk analytics platform computer, coupled to the risk monitoring data store, the risk analytics platform computer including a processor and a memory in communication with the processor and storing program instructions for controlling the processor;
(c) a risk operations platform which includes a thresholding process;
(d) a set of sensor systems at the risk monitoring site, the set of sensors including a static sensor; and
(e) a second communication network interconnecting the risk monitoring data store with the risk analytics platform computer;
wherein the risk analytics platform computer is programmed to:
(i) receive information associated with the sensor data in substantially real-time,
(ii) analyze the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and a fire condition at the risk monitoring site,
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
4. The system of claim 1, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
Claim 1…(iii) adjust the at least one risk analytics algorithm based on feedback information to improve performance of the at least one risk analytics algorithm;
(iv) automatically transmit a result of the analysis to the risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition; and
(v) analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system;
wherein said analyzing by the risk analytics platform computer is performed remotely from the risk monitoring site;
wherein: the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor; and
the sensor systems including a mobile robotic sensor, the mobile robotic sensor operating to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location.
2. The system of claim 1, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things ("IoT") data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional system information.
2. The system of claim 1, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional system information.
2. The system of claim 1, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional system information.
2. The system of claim 1, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional system information.
2. The system of claim 1, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional system information.
3. The system of claim 1, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
3. The system of claim 1, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
3. The system of claim 1, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
3. The system of claim 1, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
3. The system of claim 1, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
4. The system of claim 1, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
4. The system of claim 1, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
4. The system of claim 1, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
4. The system of claim 1, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
4. The system of claim 1, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
5. The system of claim 1, wherein the stream of sensor data is associated with an accelerometer sensor.
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
6. The system of claim 1, wherein the stream of sensor data is associated with a positioning sensor device including at least one of: (i) a gyroscope, (ii) a Global Positioning System ("GPS") satellite sensor, and (iii) a magnetic sensor.
6. The system of claim 1, wherein the stream of sensor data is associated with a positioning sensor device including at least one of: (i) a gyroscope, (ii) a Global Positioning System (“GPS”) satellite sensor, and (iii) a magnetic sensor.
6. The system of claim 1, wherein the stream of sensor data is associated with a positioning sensor device including at least one of: (i) a gyroscope, (ii) a Global Positioning System (“GPS”) satellite sensor, and (iii) a magnetic sensor.
6. The system of claim 1, wherein the stream of sensor data is associated with a positioning sensor device including at least one of: (i) a gyroscope, (ii) a Global Positioning System (“GPS”) satellite sensor, and (iii) a magnetic sensor.
6. The system of claim 1, wherein the stream of sensor data is associated with a positioning sensor device including at least one of: (i) a gyroscope, (ii) a Global Positioning System (“GPS”) satellite sensor, and (iii) a magnetic sensor.
7. The system of claim 1, wherein the stream of sensor data is associated with an environmental sensor device including at least one of: (i) a temperature sensor, (ii) a particulate sensor, (iii) a radioactivity sensor, and (iv) a voltage sensor.
7. The system of claim 1, wherein the stream of sensor data is associated with an environmental sensor device including at least one of: (i) a temperature sensor, (ii) a particulate sensor, (iii) a radioactivity sensor, and (iv) a voltage sensor.
7. The system of claim 1, wherein the stream of sensor data is associated with an environmental sensor device including at least one of: (i) a temperature sensor, (ii) a particulate sensor, (iii) a radioactivity sensor, and (iv) a voltage sensor.
7. The system of claim 1, wherein the stream of sensor data is associated with an environmental sensor device including at least one of: (i) a temperature sensor, (ii) a particulate sensor, (iii) a radioactivity sensor, and (iv) a voltage sensor.
7. The system of claim 1, wherein the stream of sensor data is associated with an environmental sensor device including at least one of: (i) a temperature sensor, (ii) a particulate sensor, (iii) a radioactivity sensor, and (iv) a voltage sensor.
8. A computerized method to facilitate predictive risk analytics for an enterprise, comprising:
receiving, at a risk analytics platform computer from a risk monitoring data store via a communication network, information associated with a stream of sensor data generated by a remote set of sensor systems located at a risk monitoring site,
the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
the set of sensor systems including a static sensor; analyzing the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated
with a vibrational-damage condition and
a structural damage condition at the risk monitoring site,
the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, said analyzing being performed remotely from the risk monitoring site;
automatically transmitting a result of the analysis to a risk operations platform,
thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the vibrational-damage condition, the risk operations platform including a thresholding process;
analyzing results of predictive analytic algorithms to reduce a number of algorithms processed in the communication network and to reduce usage of communication links in a system that includes the risk analytics platform computer and the risk monitoring data store;
and operating a mobile robotic sensor to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein the stream of sensor data is associated with a physical damage sensor device including vibration sensor.
8. A computerized method to facilitate predictive risk analytics for an enterprise, comprising:
receiving, at a risk analytics platform computer from a risk monitoring data store via a communication network, information associated with a stream of sensor data generated by a remote set of sensor systems located at a risk monitoring site,
the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
the set of sensor systems including a static sensor; analyzing the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition
19. The medium of claim 15, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
and a structural damage condition at the risk monitoring site,
the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, said analyzing being performed remotely from the risk monitoring site;
automatically transmitting a result of the analysis to a risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition, the risk operations platform including a thresholding process;
analyzing results of predictive analytic algorithms to reduce a number of algorithms processed in the communication network and to reduce usage of communication links in a system that includes the risk analytics platform computer and the risk monitoring data store;
and operating a mobile robotic sensor to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor.
8. A computerized method to facilitate predictive risk analytics for an enterprise, comprising:
receiving, at a risk analytics platform computer from a risk monitoring data store via a communication network, information associated with a stream of sensor data generated by a remote set of sensor systems located at a risk monitoring site,
the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
the set of sensor systems including a static sensor; analyzing the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and an intrusion condition at the risk monitoring site,
19. The medium of claim 15, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, said analyzing being performed remotely from the risk monitoring site;
automatically transmitting a result of the analysis to a risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition, the risk operations platform including a thresholding process;
analyzing results of predictive analytic algorithms to reduce a number of algorithms processed in the communication network and to reduce usage of communication links in a system that includes the risk analytics platform computer and the risk monitoring data store;
and operating a mobile robotic sensor to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor.
8. A computerized method to facilitate predictive risk analytics for an enterprise, comprising:
receiving, at a risk analytics platform computer from a risk monitoring data store via a communication network, information associated with a stream of sensor data generated by a remote set of sensor systems located at a risk monitoring site,
the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
the set of sensor systems including a static sensor; analyzing the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and a fire condition at the risk monitoring site,
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
Claim 8…the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, said analyzing being performed remotely from the risk monitoring site;
automatically transmitting a result of the analysis to a risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition, the risk operations platform including a thresholding process;
analyzing results of predictive analytic algorithms to reduce a number of algorithms processed in the communication network and to reduce usage of communication links in a system that includes the risk analytics platform computer and the risk monitoring data store;
and operating a mobile robotic sensor to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor, (ii) a moisture sensor, and (iii) a vapor sensor.
8. A computerized method to facilitate predictive risk analytics for an enterprise, comprising:
receiving, at a risk analytics platform computer from a risk monitoring data store via a communication network, information associated with a stream of sensor data generated by a remote set of sensor systems located at a risk monitoring site,
the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
the set of sensor systems including a static sensor;
analyzing the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and a fire condition at the risk monitoring site,
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
Claim 8…the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, said analyzing being performed remotely from the risk monitoring site;
automatically transmitting a result of the analysis to a risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition, the risk operations platform including a thresholding process;
analyzing results of predictive analytic algorithms to reduce a number of algorithms processed in the communication network and to reduce usage of communication links in a system that includes the risk analytics platform computer and the risk monitoring data store;
and operating a mobile robotic sensor to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor.
9. The method of claim8, wherein the risk monitoring data store further contains at least one of:(i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things ("IoT") data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional method information.
9. The method of claim 8, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional method information.
9. The method of claim 8, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional method information.
9. The method of claim 8, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional method information.
9. The method of claim 8, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional method information.
10. The method of claim 8, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) 3incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
10. The method of claim 8, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
10. The method of claim 8, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
10. The method of claim 8, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
10. The method of claim 8, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
12. A system to facilitate predictive risk analytics for an enterprise, comprising:
(a) a risk monitoring data store containing a set of electronic data records, each electronic data record being associated with a stream of sensor data received via a first communication network from a remote set of sensor systems located at a risk monitoring site;
(b) a risk analytics platform computer, coupled to the risk monitoring data store, the risk analytics platform computer including a processor and a memory in communication with the processor and storing program instructions for controlling the processor, the risk analytics platform computer programmed to:
(i) receive information associated with the sensor data in substantially real- time,
(ii) analyze the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern
associated with a vibrational-damage condition
and a structural damage condition at the risk monitoring site,
the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, and
(iii) automatically transmit a result of the analysis to a risk operations platform;
(c) the risk operations platform, wherein the risk operations platform is programmed to implement an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the vibrational-damage condition and further wherein the risk operations platform includes a thresholding process;
(d) the set of sensor systems at the risk monitoring site, including a static sensor; and
(e) a second communication network interconnecting the risk monitoring data store with the risk analytics platform computer;4the risk analytics platform computer further programmed to analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system;
the set of sensor systems including a mobile robotic sensor that is operated to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein said analyzing by the risk analytics platform computer is performed remotely from the risk monitoring site; and the stream of sensor data is associated with a physical damage sensor device including vibration sensor.
12. A system to facilitate predictive risk analytics for an enterprise, comprising:
(a) a risk monitoring data store containing a set of electronic data records, each electronic data record being associated with a stream of sensor data received via a first communication network from a remote set of sensor systems located at a risk monitoring site;
(b) a risk analytics platform computer, coupled to the risk monitoring data store, the risk analytics platform computer including a processor and a memory in communication with the processor and storing program instructions for controlling the processor, the risk analytics platform computer programmed to:
(i) receive information associated with the sensor data in substantially real-time,
(ii) analyze the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition
19. The medium of claim 15, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
and a structural damage condition at the risk monitoring site,
the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, and
(iii) automatically transmit a result of the analysis to a risk operations platform;
(c) the risk operations platform, wherein the risk operations platform is programmed to implement an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition and further wherein the risk operations platform includes a thresholding process;
(d) the set of sensor systems at the risk monitoring site, including a static sensor; and
(e) a second communication network interconnecting the risk monitoring data store with the risk analytics platform computer; the risk analytics platform computer further programmed to analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system;
the set of sensor systems including a mobile robotic sensor that is operated to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein said analyzing by the risk analytics platform computer is performed remotely from the risk monitoring site; and the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor.
12. A system to facilitate predictive risk analytics for an enterprise, comprising:
(a) a risk monitoring data store containing a set of electronic data records, each electronic data record being associated with a stream of sensor data received via a first communication network from a remote set of sensor systems located at a risk monitoring site;
(b) a risk analytics platform computer, coupled to the risk monitoring data store, the risk analytics platform computer including a processor and a memory in communication with the processor and storing program instructions for controlling the processor, the risk analytics platform computer programmed to:
(i) receive information associated with the sensor data in substantially real-time,
(ii) analyze the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and an intrusion condition at the risk monitoring site,
19. The medium of claim 15, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, and
(iii) automatically transmit a result of the analysis to a risk operations platform;
(c) the risk operations platform, wherein the risk operations platform is programmed to implement an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition and further wherein the risk operations platform includes a thresholding process;
(d) the set of sensor systems at the risk monitoring site, including a static sensor; and
(e) a second communication network interconnecting the risk monitoring data store with the risk analytics platform computer; the risk analytics platform computer further programmed to analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system;
the set of sensor systems including a mobile robotic sensor that is operated to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein said analyzing by the risk analytics platform computer is performed remotely from the risk monitoring site; and the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor.
12. A system to facilitate predictive risk analytics for an enterprise, comprising:
(a) a risk monitoring data store containing a set of electronic data records, each electronic data record being associated with a stream of sensor data received via a first communication network from a remote set of sensor systems located at a risk monitoring site;
(b) a risk analytics platform computer, coupled to the risk monitoring data store, the risk analytics platform computer including a processor and a memory in communication with the processor and storing program instructions for controlling the processor, the risk analytics platform computer programmed to:
(i) receive information associated with the sensor data in substantially real-time,
(ii) analyze the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and a fire condition at the risk monitoring site,
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
12…the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, and
(iii) automatically transmit a result of the analysis to a risk operations platform;
(c) the risk operations platform, wherein the risk operations platform is programmed to implement an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition and further wherein the risk operations platform includes a thresholding process;
(d) the set of sensor systems at the risk monitoring site, including a static sensor; and
(e) a second communication network interconnecting the risk monitoring data store with the risk analytics platform computer;
the risk analytics platform computer further programmed to analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system;
the set of sensor systems including a mobile robotic sensor that is operated to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein: said analyzing by the risk analytics platform computer is performed remotely from the risk monitoring site; the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor, (ii) a moisture sensor, and (iii) a vapor sensor.
12. A system to facilitate predictive risk analytics for an enterprise, comprising:
(a) a risk monitoring data store containing a set of electronic data records, each electronic data record being associated with a stream of sensor data received via a first communication network from a remote set of sensor systems located at a risk monitoring site;
(b) a risk analytics platform computer, coupled to the risk monitoring data store, the risk analytics platform computer including a processor and a memory in communication with the processor and storing program instructions for controlling the processor, the risk analytics platform computer programmed to:
(i) receive information associated with the sensor data in substantially real-time,
(ii) analyze the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and a fire condition at the risk monitoring site,
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
Claim 14…the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, and
(iii) automatically transmit a result of the analysis to a risk operations platform;
(c) the risk operations platform, wherein the risk operations platform is programmed to implement an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition and further wherein the risk operations platform includes a thresholding process;
(d) the set of sensor systems at the risk monitoring site, including a static sensor; and
(e) a second communication network interconnecting the risk monitoring data store with the risk analytics platform computer;
the risk analytics platform computer further programmed to analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system;
the set of sensor systems including a mobile robotic sensor that is operated to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein: said analyzing by the risk analytics platform computer is performed remotely from the risk monitoring site; the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor.
13. The system of claim 12, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things ("IoT") data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional system information.
13. The system of claim 12, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional system information.
13. The system of claim 12, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional system information.
13. The system of claim 12, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional system information.
13. The system of claim 12, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional system information.
14. The system of claim 12, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching,(ii)incorporate a machine learning process,(iii)incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
14. The system of claim 12, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
14. The system of claim 12, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
14. The system of claim 12, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
14. The system of claim 12, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
15. A non-transitory, computer-readable medium storing instructions, that, when executed by a processor, cause the processor to perform a method to facilitate predictive risk analytics for an enterprise,
the method comprising: receiving, at a risk analytics platform computer from a risk monitoring data store via a communication network, information associated with a stream of sensor data generated by a remote set of sensor systems located at a risk monitoring site,
the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
the set of sensor systems including a static sensor; analyzing the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with
a vibrational-damage condition and
a structural damage condition at the risk monitoring site,
the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, said analyzing being performed remotely from the risk monitoring site;
automatically transmitting a result of the analysis to a risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the vibrational-damage condition, the risk operations platform including a thresholding process;
analyzing results of predictive analytic algorithms to reduce a number of algorithms processed in the communication network and to reduce usage of communication links in a system that includes the risk analytics platform computer and the risk monitoring data store;
and operating a mobile robotic sensor to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein the stream of sensor data is associated with a physical damage sensor device including vibration sensor.
15. A non-transitory, computer-readable medium storing instructions, that, when executed by a processor, cause the processor to perform a method to facilitate predictive risk analytics for an enterprise,
the method comprising: receiving, at a risk analytics platform computer from a risk monitoring data store via a communication network, information associated with a stream of sensor data generated by a remote set of sensor systems located at a risk monitoring site,
the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
the set of sensor systems including a static sensor; analyzing the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition
19. The medium of claim 15, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
and a structural damage condition at the risk monitoring site,
the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, said analyzing being performed remotely from the risk monitoring site;
automatically transmitting a result of the analysis to a risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition, the risk operations platform including a thresholding process;
analyzing results of predictive analytic algorithms to reduce a number of algorithms processed in the communication network and to reduce usage of communication links in a system that includes the risk analytics platform computer and the risk monitoring data store;
and operating a mobile robotic sensor to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor.
15. A non-transitory, computer-readable medium storing instructions, that, when executed by a processor, cause the processor to perform a method to facilitate predictive risk analytics for an enterprise,
the method comprising: receiving, at a risk analytics platform computer from a risk monitoring data store via a communication network, information associated with a stream of sensor data generated by a remote set of sensor systems located at a risk monitoring site,
the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
the set of sensor systems including a static sensor; analyzing the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and an intrusion condition at the risk monitoring site,
19. The medium of claim 15, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, said analyzing being performed remotely from the risk monitoring site;
automatically transmitting a result of the analysis to a risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition, the risk operations platform including a thresholding process;
analyzing results of predictive analytic algorithms to reduce a number of algorithms processed in the communication network and to reduce usage of communication links in a system that includes the risk analytics platform computer and the risk monitoring data store;
and operating a mobile robotic sensor to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor.
8. A computerized method to facilitate predictive risk analytics for an enterprise… the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
comprising: receiving, at a risk analytics platform computer from a risk monitoring data store via a communication network, information associated with a stream of sensor data generated by a remote set of sensor systems located at a risk monitoring site,
the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
the set of sensor systems including a static sensor; analyzing the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and a fire condition at the risk monitoring site,
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
11. The method of claim 8, wherein the stream of sensor data is associated with at least one of: (i) a security sensor device, (ii) a movement sensor device, (iii) a physical damage sensor device, (iv) a positioning sensor device, and (v) an environmental sensor device.
Claim 8…the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, said analyzing being performed remotely from the risk monitoring site;
automatically transmitting a result of the analysis to a risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition, the risk operations platform including a thresholding process;
analyzing results of predictive analytic algorithms to reduce a number of algorithms processed in the communication network and to reduce usage of communication links in a system that includes the risk analytics platform computer and the risk monitoring data store;
and operating a mobile robotic sensor to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor, (ii) a moisture sensor, and (iii) a vapor sensor.
15. A non-transitory, computer-readable medium storing instructions, that, when executed by a processor, cause the processor to perform a method to facilitate predictive risk analytics for an enterprise,
the method comprising:
receiving, at a risk analytics platform computer from a risk monitoring data store via a communication network, information associated with a stream of sensor data generated by a remote set of sensor systems located at a risk monitoring site,
the risk analytics platform including a processor and a memory in communication with the processor, the memory storing program instructions for controlling the processor,
the set of sensor systems including a static sensor; analyzing the received sensor data, using at least one risk analytics algorithm, to detect an abnormal pattern associated with a water-damage condition and a fire condition at the risk monitoring site,
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
18. The medium of claim 15, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
15…the at least one risk analytics algorithm being adjusted based on feedback information to improve performance of the at least one risk analytics algorithm, said analyzing being performed remotely from the risk monitoring site;
automatically transmitting a result of the analysis to a risk operations platform, thereby triggering an active adjustment at the risk monitoring site responsive to the result of the analysis to automatically mitigate the water-damage condition, the risk operations platform including a thresholding process;
analyzing results of predictive analytic algorithms to reduce a number of algorithms processed in the communication network and to reduce usage of communication links in a system that includes the risk analytics platform computer and the risk monitoring data store;
and operating a mobile robotic sensor to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location;
wherein the stream of sensor data is associated with a physical damage sensor device including: (i) a water sensor and (ii) a vapor sensor.
16. The medium of claim 15, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things ("IoT") data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional method information.
16. The medium of claim 15, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional method information
16. The medium of claim 15, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional method information.
9. The method of claim 8, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional method information.
16. The medium of claim 15, wherein the risk monitoring data store further contains at least one of: (i) historical data, (ii) derived analytic elements, (iii) a streaming architecture, (iv) Internet of Things (“IoT”) data, (v) information about other risk monitoring sites, (vi) third-party data, and (vii) enterprise transactional method information.
17. The medium of claim 15, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
17. The medium of claim 15, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
17. The medium of claim 15, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
10. The method of claim 8, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
17. The medium of claim 15, wherein the risk analytics platform computer is further programed to: (i) execute pattern matching, (ii) incorporate a machine learning process, (iii) incorporate an artificial intelligence process, and (iv) automatically adjust the risk analytics algorithm.
18. The medium of claim 15, wherein the stream of sensor data is associated with a security sensor device including at [east one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
18. The medium of claim 15, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
18. The medium of claim 15, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
4. The system of claim 1, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
18. The medium of claim 15, wherein the stream of sensor data is associated with a security sensor device including at least one of: (i) an acoustic sensor, (ii) a broken glass detection sensor, (iii) a thermal sensor, (iv) a visual light sensor, (v) an infrared sensor, (vi) a motion sensor, and (vii) a sonar sensor.
19. The medium of claim 15, wherein the stream of sensor data is associated with a movement sensor device including an accelerometer sensor.
19. The medium of claim 15, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
19. The medium of claim 15, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
5. The system of claim 1, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
19. The medium of claim 15, wherein the stream of sensor data is associated with a movement sensor device including at least one of: (i) a vibration sensor, and (ii) an accelerometer sensor.
20. The medium of claim 15, wherein the stream of sensor data is associated with a positioning sensor device including at least one of: (i) a gyroscope, (ii) a Global Positioning System ("GPS") satellite sensor, and (iii) a magnetic sensor.
20. The medium of claim 15, wherein the stream of sensor data is associated with a positioning sensor device including at least one of: (i) a gyroscope, (ii) a Global Positioning System (“GPS”) satellite sensor, and (iii) a magnetic sensor.
20. The medium of claim 15, wherein the stream of sensor data is associated with a positioning sensor device including at least one of: (i) a gyroscope, (ii) a Global Positioning System (“GPS”) satellite sensor, and (iii) a magnetic sensor.
6. The system of claim 1, wherein the stream of sensor data is associated with a positioning sensor device including at least one of: (i) a gyroscope, (ii) a Global Positioning System (“GPS”) satellite sensor, and (iii) a magnetic sensor.
20. The medium of claim 15, wherein the stream of sensor data is associated with a positioning sensor device including at least one of: (i) a gyroscope, (ii) a Global Positioning System (“GPS”) satellite sensor, and (iii) a magnetic sensor.
21. The medium of claim 15, wherein the stream of sensor data is associated with an environmental sensor device including at least one of: (i) a temperature sensor, (ii) a particulate sensor, (iii) a radioactivity sensor, and (iv) a voltage sensor.7
21. The medium of claim 15, wherein the stream of sensor data is associated with an environmental sensor device including at least one of: (i) a temperature sensor, (ii) a particulate sensor, (iii) a radioactivity sensor, and (iv) a voltage sensor.
21. The medium of claim 15, wherein the stream of sensor data is associated with an environmental sensor device including at least one of: (i) a temperature sensor, (ii) a particulate sensor, (iii) a radioactivity sensor, and (iv) a voltage sensor.
7. The system of claim 1, wherein the stream of sensor data is associated with an environmental sensor device including at least one of: (i) a temperature sensor, (ii) a particulate sensor, (iii) a radioactivity sensor, and (iv) a voltage sensor.
21. The medium of claim 15, wherein the stream of sensor data is associated with an environmental sensor device including at least one of: (i) a temperature sensor, (ii) a particulate sensor, (iii) a radioactivity sensor, and (iv) a voltage sensor.
Allowable Subject Matter
Claims 1-21 would be allowable if rewritten to overcome the double patenting rejections set forth in this Office action.
The following is an examiner’s statement of reasons for indicating Patent-eligible subject matter in view of 35 USC § 101:
The steps in the independent claims of: “the sensor systems including a mobile robotic sensor, the mobile robotic sensor operating to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location” are limitations, which when considered as an ordered combination, are indicative of integration into a practical application. For these reasons, independent claims 1, 8, 12, and 15 are deemed patent eligible. Dependent claims 2-7, 9-11, 13, 14, and 16-21 are deemed patent eligible by virtue of dependency on an allowed claim.
The following is a statement of reasons for the indication of allowable subject matter of independent claims 1, 8, 12, and 15 over prior art.
The closest prior art of record is: WO 2016/118979 to Tchankotadze et al. (hereinafter Tchankotadze), US 20170091871 to Trainor et al. (hereinafter referred to as Trainor), US 2016/0163177 to Klicpera (hereinafter referred to as Klicpera), and US 2009/0265193 to Collins et al. (hereinafter referred to as Collins). Allowance is indicated because none of the prior art of record, alone or in combination, appears to teach or fairly suggest or render obvious the combination set forth in independent claims 1, 8, 12, and 15. In regards to claim 1, the prior art of Tchankotadze, Trainor, Klicpera, and Collins, specifically do not disclose: “analyze results of predictive analytic algorithms to reduce a number of algorithms processed in the second communication network and to reduce usage of communication links in the system; a physical damage sensor device including a vibration sensor; and the sensor systems including a mobile robotic sensor, the mobile robotic sensor operating to monitor conditions at a first location, to generate and transmit data representative of the conditions at the first location, to move from the first location to a second location different from the first location, to monitor conditions at the second location, and to generate and transmit data representative of the conditions at the second location. Similar reasoning and rationale apply to the other independent claims 8, 12 and 15.
For these reasons, independent claims 1, 8, 12, and 15 are deemed allowable over the prior art. Dependent claims 2-7, 9-11, 13, 14, and 16-21 are allowable by virtue of dependency on an allowed claim.
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Conclusion
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/PAUL S SCHWARZENBERG/Examiner, Art Unit 3695 2/13/2026