DETAILED ACTION
This is a Final Office Action on the Merits in response to communications filed by applicant on October 8th, 2025. Claims 1-6, 8-16, and 18-20 are currently pending and examined below.
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 .
Response to Amendment
The amendments to the Claims filed on October 8th, 2025 have been entered. Claims 1, 11, and 20 are currently amended and pending, claims 2-6, 8-10, 12-16, and 18-19 are original, unamended, and pending, and claims 7 and 17 have been canceled. The amendments to the Specifications filed on October 8th, 2025 have been entered and have overcome each and every objection to the Specification and Drawings set forth in the previous Non-Final Office Action mailed on July 31st, 2025.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claim(s) 1-2, 4, 8, 11, 12, 14, and 20 is/are rejected under 35 U.S.C. 103 as being unpatentable over JP 2021070447 A ("Yokoyama") in view of US 11604178 B2 ("Chilla").
Regarding claim 1, Yokoyama teaches a system for detecting and reporting fires by an autonomous vehicle, the autonomous vehicle having an exterior, the system comprising (Yokoyama: ¶ 0031, “The vehicle management system 1 acquires the occurrence of a fire in the vicinity of the vehicle S based on the surrounding conditions acquired by the sensor or from the notification server 2 that holds information related to the occurrence of the fire (hereinafter referred to as fire information). This is a system for automatically running the vehicle S to evacuate when it is detected based on fire information.”):
a fire detection system comprising one or more sensors oriented outwards from the exterior of the autonomous vehicle to collect data in one or more areas surrounding the autonomous vehicle (Yokoyama: ¶ 0038, “The external world sensor 11 (external world information acquisition device) captures electromagnetic waves such as light from the periphery of the vehicle S, heat, sound waves, etc., detects objects, substances, heat, sound, etc. outside the vehicle, and detects the surrounding conditions of the vehicle S. As shown in FIGS. 2 and 3, the sensor includes a temperature sensor 28, a smoke sensor 29, a microphone 30, a sonar 31, an external camera 32, a radar 33, and a rider 34. The external sensor 11 outputs the detection result to the control device 14.”);
and a processing system, the processing system including a processor and a memory device, the memory device storing instructions that when executed cause the processor to (Yokoyama: ¶ 0051, “The control device 14 is an electronic control unit (ECU) composed of a central processing unit (CPU), a ROM, a RAM, peripheral circuits, an input / output interface, various drivers, and the like. The control device 14 executes various vehicle controls by executing arithmetic processing according to the program by the CPU. The control device 14 may be configured as one hardware, or may be configured as a unit composed of a plurality of hardware. Further, at least a part of each functional unit of the control device 14 may be realized by hardware such as LSI, ASIC, FPGA, or may be realized by a combination of software and hardware.”):
receive, from the one or more sensors, at least one sensor signal representing one or more fire-related conditions surrounding the autonomous vehicle (Yokoyama: ¶ 0064, “The fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S (more specifically, the vehicle parking area) based on the detection result of the outside world sensor 11. When a fire is detected based on the detection result of the outside world sensor 11, the fire detection unit 47 generates fire occurrence information including specific fire position information indicating that the fire occurrence position is the own vehicle parking area.”);
identify one or more fire-indicative conditions surrounding the autonomous vehicle based on the one or more fire-related conditions (Yokoyama: ¶ 0066, “As described above, the external sensor 11 includes the temperature sensor 28 that detects the temperature outside the vehicle, and the control device 14 of the vehicle control unit 3 detects the fire based on the output of the temperature sensor 28. Therefore, when the temperature outside the vehicle becomes abnormally high, the control device 14 can detect a fire based on the output of the temperature sensor 28.”, ¶ 0067, “Further, the fire detection unit 47 determines that a fire has occurred in the vicinity of the vehicle S when the concentration of smoke contained in the outside air is higher than the predetermined fire determination concentration by the smoke sensor 29, and the own vehicle parking area. Detect the fire that broke out in.”, ¶ 0070, “Further, when the fire detection unit 47 analyzes the image captured by the vehicle exterior camera 32 using a known analysis method and detects, for example, flame, smoke, sprinkler water discharge, etc., a fire occurs around the vehicle S. It is determined that the vehicle is in use, and a fire that has occurred in the vehicle parking area is detected. Alternatively, the fire detection unit 47 may detect the water discharge of the sprinkler based on the detection of a large amount of raindrops by the optical rain sensor and the parking position information, and detect the fire that has occurred in the own vehicle parking area.”);
generate a fire detection signal based at least on the one or more fire-indicative conditions, a location of the one or more fire-indicative conditions, and a location of the autonomous vehicle (Yokoyama: ¶00064, “The fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S (more specifically, the vehicle parking area) based on the detection result of the outside world sensor 11. When a fire is detected based on the detection result of the outside world sensor 11, the fire detection unit 47 generates fire occurrence information including specific fire position information indicating that the fire occurrence position is the own vehicle parking area.”, ¶ 0073, “Further, the fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S based on the fire information transmitted from the notification server 2 and the position of the vehicle S acquired by the own vehicle position recognition unit 52. When a fire is detected based on the fire information and the own vehicle position information, the fire detection unit 47 includes a fire including specific fire position information indicating that the fire occurrence position is in the own vehicle parking area or a peripheral area other than the own vehicle parking area. Generate occurrence information.”);
and transmit the fire detection signal to an external receiver (Yokoyama: ¶ 0044, “The communication device 12 mediates the connection of the control device 14 to the network 35 such as the Internet. As a result, the control device 14 can be connected to a network 35 such as the Internet via the communication device 12, and communicates with various servers and a terminal 4 owned by a user outside the vehicle S via the network 35. It is possible. Further, the communication device 12 sends and receives signals by transmitting and receiving radio waves. As a result, the control device 14 can directly communicate with the external device of the vehicle S via the communication device 12.”, ¶ 0087, “Further, when a fire is detected by the fire detection unit 47, the state management unit 50 transmits specific fire position information to another vehicle in the parking facility where the vehicle S is parked, and also transmits specific fire position information according to the position of the fire source.”. The cited passage clearly shows that the fire detection signal is transmitted to other vehicles.); and
control operation of the autonomous vehicle, based on the one or more fire-indicative conditions (Yokoyama: ¶ 0077, “When the fire risk calculation unit 48 determines that the fire risk is equal to or higher than a predetermined threshold value (for example, "medium"), the evacuation route determination unit 49 refers to the navigation device 13, the position of the vehicle S, the map information, and the fire. An evacuation site suitable for evacuation of the vehicle S is set based on the specific fire position information included in the occurrence information. After that, the evacuation route determination unit 49 sets an evacuation route from the current position of the vehicle S to the evacuation site.”, ¶ 0081, “When the action planning unit 53 receives an instruction to travel on the evacuation route from the state management unit 50, the action planning unit 53 sends this instruction to the travel control unit 54. When the travel control unit 54 receives an instruction from the action planning unit 53 to travel on the evacuation route, the travel control unit 54 controls the travel motor 7, the steering device 8, and the brake device 9 so that the vehicle S travels on the evacuation route.”. The cited passages clearly teach that once a fire is determined, the system is configured to control the operation of the autonomous vehicle.).
Yokoyama does not teach wherein the one or more sensors comprise a chemical sensor configured for chemical detection of the one or more fire-related conditions,
the one or more fire-related conditions including a carbon dioxide amount and a carbon monoxide amount.
Chilla, in the same field of endeavor, teaches wherein the one or more sensors comprise a chemical sensor configured for chemical detection of the one or more fire-related conditions (Chilla: Column 29 lines 14-28, “In various embodiments, FDS or CO detection devices (e.g., 120c and 120d) may be configured to detect potential or actual fire events (e.g., fire 155) and/or high levels of CO and report information to a remote server 142 providing fire detection system services via the wireless network 100. Similarly, the remote server 142 may be configured to receive fire event reports and sensor data from several FDS or CO detection devices (e.g., 120c and 120d) as well as provide command signals (e.g., to wake up, activate certain sensors, report data, move, and/or shutdown or go into a low-power mode or other mode). In some embodiments a server providing fire detection system services may be deployed as or included within the functionality of a network element (e.g., a server coupled to a macro base station 110a).”, Column 31 lines 9-35, “Any number of such sensors and/or other sensors of any type may be included in different implementations of the FDS or CO detection device 200.”, Column 31 lines 36-48, “The sensors may include (but is not limited to) a variety of sensors including a local ambient temperature sensor 230 (i.e., a sensor for detecting a temperature outside of the FDS device), a remote temperature sensor 232, a smoke detector 234, an image sensor 236, an infrared sensor 238, an ambient humidity sensor 240, a chemical sensor 242 such as a carbon monoxide (CO) sensor, a carbon dioxide (CO2) sensor, and/or another chemical sensor, a sound sensor 244 (such as a microphone), a soil sensor 246, and other sensors or sensing devices, including any combination of the foregoing. It should be clear that any number of these (and/or other) sensors may be included in different implementations of the FDS device 200.”. The cited passages clearly teach that the device is configured with chemical sensors used to detect fire—related conditions.),
the one or more fire-related conditions including a carbon dioxide amount and a carbon monoxide amount (Patel: Column 31 lines 9-35, “Any number of such sensors and/or other sensors of any type may be included in different implementations of the FDS or CO detection device 200.”, Column 31 lines 36-48, “The sensors may include (but is not limited to) a variety of sensors including a local ambient temperature sensor 230 (i.e., a sensor for detecting a temperature outside of the FDS device), a remote temperature sensor 232, a smoke detector 234, an image sensor 236, an infrared sensor 238, an ambient humidity sensor 240, a chemical sensor 242 such as a carbon monoxide (CO) sensor, a carbon dioxide (CO2) sensor, and/or another chemical sensor, a sound sensor 244 (such as a microphone), a soil sensor 246, and other sensors or sensing devices, including any combination of the foregoing. It should be clear that any number of these (and/or other) sensors may be included in different implementations of the FDS device 200.”, Column 38 lines 55-62, “In block 606, the processor may generate a fire warning message comprising a fire alarm object in response to determining that the information received from the one or more sensors satisfy one or more threshold criteria indicative of a fire event or CO detection. In some embodiments, means for performing functions of the operations in block 604 may include the processor (e.g., 312, 314, 316, 318, 352, 366).”. The cited passages clearly teach that that a carbon monoxide and carbon dioxide amount are fire related conditions detected by the chemical sensors.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention, to have combine the system for detecting and reporting fires by an autonomous vehicle taught in Yokoyama with wherein the one or more sensors comprise a chemical sensor configured for chemical detection of the one or more fire-related conditions, the one or more fire-related conditions including a carbon dioxide and a carbon monoxide amount taught in Chilla with a reasonable expectation of success. One of ordinary skill in the art would have been motivated to make this modification because it would have been obvious to try. One of ordinary skill in the art would have known that fire produces both carbon dioxide and carbon monoxide, and that the presence of these gases could be used to indicate the presence of a fire. Furthermore, a sensor that is configured to detect one or both of carbon dioxide and monoxide would have been known to one of ordinary skill in the art. Additionally, the device taught in Chilla is already configured to be used in a vehicle (Chilla: Column 29 line 48 – Column 30 line 3). A person of ordinary skill in the art would have had the technological capabilities required to have integrated such a senor into the system taught in Yokoyama. The combination would not have changed or introduced new functionality to either. No inventive effort would have been required.
Regarding claim 2, Yokoyama in view of Chilla teaches wherein the system further comprises a drive system configured to move the autonomous vehicle (Yokoyama: ¶ 0033, “The traveling motor 7 is driven by receiving electric power supplied from the battery 6 (driving storage battery) to rotate the driving wheels. In the present embodiment, the left and right rear wheels of the vehicle S are driving wheels. The battery 6 supplies electric power not only to the traveling motor 7, but also to the steering device 8, the braking device 9, the control device 14, and the like.”),
the processor being further caused to control the drive system to move the autonomous vehicle into a hazard-response position (Yokoyama: ¶ 0077, “When the fire risk calculation unit 48 determines that the fire risk is equal to or higher than a predetermined threshold value (for example, "medium"), the evacuation route determination unit 49 refers to the navigation device 13, the position of the vehicle S, the map information, and the fire. An evacuation site suitable for evacuation of the vehicle S is set based on the specific fire position information included in the occurrence information. After that, the evacuation route determination unit 49 sets an evacuation route from the current position of the vehicle S to the evacuation site.”, ¶ 0081, “When the action planning unit 53 receives an instruction to travel on the evacuation route from the state management unit 50, the action planning unit 53 sends this instruction to the travel control unit 54. When the travel control unit 54 receives an instruction from the action planning unit 53 to travel on the evacuation route, the travel control unit 54 controls the travel motor 7, the steering device 8, and the brake device 9 so that the vehicle S travels on the evacuation route.”. The cited passages clearly teach that once a fire is determined, the system is configured to determine an evacuation site and cause the drive system to move the vehicle to the evacuation site. Furthermore, one of ordinary skill in the art would see that an “evacuation site” is a “hazard-response position”.).
Regarding claim 4, Yokoyama in view of Chilla teaches wherein the one or more sensors comprise a camera configured for visual detection of the one or more fire-related conditions (Yokoyama: ¶ 0070, “Further, when the fire detection unit 47 analyzes the image captured by the vehicle exterior camera 32 using a known analysis method and detects, for example, flame, smoke, sprinkler water discharge, etc., a fire occurs around the vehicle S. It is determined that the vehicle is in use, and a fire that has occurred in the vehicle parking area is detected. Alternatively, the fire detection unit 47 may detect the water discharge of the sprinkler based on the detection of a large amount of raindrops by the optical rain sensor and the parking position information, and detect the fire that has occurred in the own vehicle parking area.”),
the one or more fire-related conditions comprising at least one of a color, an illumination level, and a smoke amount (Yokoyama: ¶ 0070, ¶ 0071, “As described above, the external sensor 11 includes the external camera 32, and the control device 14 of the vehicle control unit 3 detects the fire by analyzing the image taken by the external camera 32. Therefore, the control device 14 analyzes the image to extract flames, smoke, and the like, so that a fire around the vehicle can be detected quickly.”. The system is clearly able to determine the presence of a fire based on the amount of smoke captured in the image, as shown in the cited paragraphs.).
Regarding claim 8, Yokoyama in view of Chilla teaches wherein the fire detection signal comprises at least one of a time, a location of the autonomous vehicle, a location of the one or more fire-indicative conditions, the one or more fire-indicative conditions, and a fire probability assessment (Yokoyama: ¶ 0064, “The fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S (more specifically, the vehicle parking area) based on the detection result of the outside world sensor 11. When a fire is detected based on the detection result of the outside world sensor 11, the fire detection unit 47 generates fire occurrence information including specific fire position information indicating that the fire occurrence position is the own vehicle parking area.”, ¶ 0076, “For example, when the fire risk calculation unit 48 detects a fire that has occurred in the own vehicle parking area based on the detection result of the external sensor 11, the fire risk is calculated as “high”. When the fire risk calculation unit 48 detects a fire that has occurred in the vehicle parking area based on the fire information, the fire risk has not yet been detected based on the detection result of the outside world sensor 11, so the fire risk is set to "medium". calculate. When the fire risk calculation unit 48 detects a fire that has occurred in the surrounding area based on the fire information, the fire risk calculation unit 48 calculates the fire risk as “low” or “medium”. Specifically, the fire risk calculation unit 48 calculates the possibility that a fire that occurs in the surrounding area will spread to the own vehicle parking area based on the fire type information, fire occurrence position information, and weather information included in the fire information. However, when the fire spread possibility is equal to or less than a predetermined threshold, the fire risk is calculated as "low", and when the fire spread possibility exceeds the predetermined threshold, the fire risk is calculated as "medium".”, ¶ 0091, “The control device 14 (state management unit 50) transmits the first reception start signal to the terminal 4 in step ST2. The first reception start signal includes fire occurrence information, a peripheral image of the vehicle S acquired from the external camera 32, and a fire risk.”. The cited passages clearly show that the fire signal comprises the location of the fire and a fire probability (the fire risk).).
Regarding claim 11, Yokoyama teaches a method for detecting and reporting fires by an autonomous vehicle, the method comprising (Yokoyama: ¶ 0031, “The vehicle management system 1 acquires the occurrence of a fire in the vicinity of the vehicle S based on the surrounding conditions acquired by the sensor or from the notification server 2 that holds information related to the occurrence of the fire (hereinafter referred to as fire information). This is a system for automatically running the vehicle S to evacuate when it is detected based on fire information.”):
receiving, from one or more sensors, at least one sensor signal representing one or more fire-related conditions surrounding the autonomous vehicle (Yokoyama: ¶ 0064, “The fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S (more specifically, the vehicle parking area) based on the detection result of the outside world sensor 11. When a fire is detected based on the detection result of the outside world sensor 11, the fire detection unit 47 generates fire occurrence information including specific fire position information indicating that the fire occurrence position is the own vehicle parking area.”);
identifying one or more fire-indicative conditions surrounding the autonomous vehicle based on the one or more fire-related conditions (Yokoyama: ¶ 0066, “As described above, the external sensor 11 includes the temperature sensor 28 that detects the temperature outside the vehicle, and the control device 14 of the vehicle control unit 3 detects the fire based on the output of the temperature sensor 28. Therefore, when the temperature outside the vehicle becomes abnormally high, the control device 14 can detect a fire based on the output of the temperature sensor 28.”, ¶ 0067, “Further, the fire detection unit 47 determines that a fire has occurred in the vicinity of the vehicle S when the concentration of smoke contained in the outside air is higher than the predetermined fire determination concentration by the smoke sensor 29, and the own vehicle parking area. Detect the fire that broke out in.”, ¶ 0070, “Further, when the fire detection unit 47 analyzes the image captured by the vehicle exterior camera 32 using a known analysis method and detects, for example, flame, smoke, sprinkler water discharge, etc., a fire occurs around the vehicle S. It is determined that the vehicle is in use, and a fire that has occurred in the vehicle parking area is detected. Alternatively, the fire detection unit 47 may detect the water discharge of the sprinkler based on the detection of a large amount of raindrops by the optical rain sensor and the parking position information, and detect the fire that has occurred in the own vehicle parking area.”);
generating a fire detection signal based at least on the one or more fire-indicative conditions, a location of the one or more fire-indicative conditions, and a location of the autonomous vehicle (Yokoyama: ¶00064, “The fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S (more specifically, the vehicle parking area) based on the detection result of the outside world sensor 11. When a fire is detected based on the detection result of the outside world sensor 11, the fire detection unit 47 generates fire occurrence information including specific fire position information indicating that the fire occurrence position is the own vehicle parking area.”, ¶ 0073, “Further, the fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S based on the fire information transmitted from the notification server 2 and the position of the vehicle S acquired by the own vehicle position recognition unit 52. When a fire is detected based on the fire information and the own vehicle position information, the fire detection unit 47 includes a fire including specific fire position information indicating that the fire occurrence position is in the own vehicle parking area or a peripheral area other than the own vehicle parking area. Generate occurrence information.”);
and transmitting the fire detection signal to an external receiver (Yokoyama: ¶ 0044, “The communication device 12 mediates the connection of the control device 14 to the network 35 such as the Internet. As a result, the control device 14 can be connected to a network 35 such as the Internet via the communication device 12, and communicates with various servers and a terminal 4 owned by a user outside the vehicle S via the network 35. It is possible. Further, the communication device 12 sends and receives signals by transmitting and receiving radio waves. As a result, the control device 14 can directly communicate with the external device of the vehicle S via the communication device 12.”, ¶ 0087, “Further, when a fire is detected by the fire detection unit 47, the state management unit 50 transmits specific fire position information to another vehicle in the parking facility where the vehicle S is parked, and also transmits specific fire position information according to the position of the fire source.”. The cited passage clearly shows that the fire detection signal is transmitted to other vehicles.); and
controlling operation of the autonomous vehicle, based on the one or more fire-indicative conditions (Yokoyama: ¶ 0077, “When the fire risk calculation unit 48 determines that the fire risk is equal to or higher than a predetermined threshold value (for example, "medium"), the evacuation route determination unit 49 refers to the navigation device 13, the position of the vehicle S, the map information, and the fire. An evacuation site suitable for evacuation of the vehicle S is set based on the specific fire position information included in the occurrence information. After that, the evacuation route determination unit 49 sets an evacuation route from the current position of the vehicle S to the evacuation site.”, ¶ 0081, “When the action planning unit 53 receives an instruction to travel on the evacuation route from the state management unit 50, the action planning unit 53 sends this instruction to the travel control unit 54. When the travel control unit 54 receives an instruction from the action planning unit 53 to travel on the evacuation route, the travel control unit 54 controls the travel motor 7, the steering device 8, and the brake device 9 so that the vehicle S travels on the evacuation route.”. The cited passages clearly teach that once a fire is determined, the system is configured to control the operation of the autonomous vehicle.).
Yokoyama does not teach wherein the one or more sensors comprise a chemical sensor configured for chemical detection of the one or more fire-related conditions,
the one or more fire-related conditions including a carbon dioxide amount and a carbon monoxide amount.
Chilla, in the same field of endeavor, teaches wherein the one or more sensors comprise a chemical sensor configured for chemical detection of the one or more fire-related conditions (Chilla: Column 29 lines 14-28, “In various embodiments, FDS or CO detection devices (e.g., 120c and 120d) may be configured to detect potential or actual fire events (e.g., fire 155) and/or high levels of CO and report information to a remote server 142 providing fire detection system services via the wireless network 100. Similarly, the remote server 142 may be configured to receive fire event reports and sensor data from several FDS or CO detection devices (e.g., 120c and 120d) as well as provide command signals (e.g., to wake up, activate certain sensors, report data, move, and/or shutdown or go into a low-power mode or other mode). In some embodiments a server providing fire detection system services may be deployed as or included within the functionality of a network element (e.g., a server coupled to a macro base station 110a).”, Column 31 lines 9-35, “Any number of such sensors and/or other sensors of any type may be included in different implementations of the FDS or CO detection device 200.”, Column 31 lines 36-48, “The sensors may include (but is not limited to) a variety of sensors including a local ambient temperature sensor 230 (i.e., a sensor for detecting a temperature outside of the FDS device), a remote temperature sensor 232, a smoke detector 234, an image sensor 236, an infrared sensor 238, an ambient humidity sensor 240, a chemical sensor 242 such as a carbon monoxide (CO) sensor, a carbon dioxide (CO2) sensor, and/or another chemical sensor, a sound sensor 244 (such as a microphone), a soil sensor 246, and other sensors or sensing devices, including any combination of the foregoing. It should be clear that any number of these (and/or other) sensors may be included in different implementations of the FDS device 200.”. The cited passages clearly teach that the device is configured with chemical sensors used to detect fire—related conditions.),
the one or more fire-related conditions including a carbon dioxide amount and a carbon monoxide amount (Patel: Column 31 lines 9-35, “Any number of such sensors and/or other sensors of any type may be included in different implementations of the FDS or CO detection device 200.”, Column 31 lines 36-48, “The sensors may include (but is not limited to) a variety of sensors including a local ambient temperature sensor 230 (i.e., a sensor for detecting a temperature outside of the FDS device), a remote temperature sensor 232, a smoke detector 234, an image sensor 236, an infrared sensor 238, an ambient humidity sensor 240, a chemical sensor 242 such as a carbon monoxide (CO) sensor, a carbon dioxide (CO2) sensor, and/or another chemical sensor, a sound sensor 244 (such as a microphone), a soil sensor 246, and other sensors or sensing devices, including any combination of the foregoing. It should be clear that any number of these (and/or other) sensors may be included in different implementations of the FDS device 200.”, Column 38 lines 55-62, “In block 606, the processor may generate a fire warning message comprising a fire alarm object in response to determining that the information received from the one or more sensors satisfy one or more threshold criteria indicative of a fire event or CO detection. In some embodiments, means for performing functions of the operations in block 604 may include the processor (e.g., 312, 314, 316, 318, 352, 366).”. The cited passages clearly teach that that a carbon monoxide and carbon dioxide amount are fire related conditions detected by the chemical sensors.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention, to have combine the method for detecting and reporting fires by an autonomous vehicle taught in Yokoyama with wherein the one or more sensors comprise a chemical sensor configured for chemical detection of the one or more fire-related conditions, the one or more fire-related conditions including a carbon dioxide and a carbon monoxide amount taught in Chilla with a reasonable expectation of success. One of ordinary skill in the art would have been motivated to make this modification because it would have been obvious to try. One of ordinary skill in the art would have known that fire produces both carbon dioxide and carbon monoxide, and that the presence of these gases could be used to indicate the presence of a fire. Furthermore, a sensor that is configured to detect one or both of carbon dioxide and monoxide would have been known to one of ordinary skill in the art. Additionally, the device taught in Chilla is already configured to be used in a vehicle (Chilla: Column 29 line 48 – Column 30 line 3). A person of ordinary skill in the art would have had the technological capabilities required to have integrated such a senor into the system taught in Yokoyama. The combination would not have changed or introduced new functionality to either. No inventive effort would have been required.
Regarding claim 12, Yokoyama in view of Chilla teaches further comprising controlling a drive system configured to move the autonomous vehicle into a hazard-response position (Yokoyama: ¶ 0077, “When the fire risk calculation unit 48 determines that the fire risk is equal to or higher than a predetermined threshold value (for example, "medium"), the evacuation route determination unit 49 refers to the navigation device 13, the position of the vehicle S, the map information, and the fire. An evacuation site suitable for evacuation of the vehicle S is set based on the specific fire position information included in the occurrence information. After that, the evacuation route determination unit 49 sets an evacuation route from the current position of the vehicle S to the evacuation site.”, ¶ 0081, “When the action planning unit 53 receives an instruction to travel on the evacuation route from the state management unit 50, the action planning unit 53 sends this instruction to the travel control unit 54. When the travel control unit 54 receives an instruction from the action planning unit 53 to travel on the evacuation route, the travel control unit 54 controls the travel motor 7, the steering device 8, and the brake device 9 so that the vehicle S travels on the evacuation route.”. The cited passages clearly teach that once a fire is determined, the system is configured to determine an evacuation site and cause the drive system to move the vehicle to the evacuation site. Furthermore, one of ordinary skill in the art would see that an “evacuation site” is a “hazard-response position”.).
Regarding claim 14, Yokoyama in view of Chilla teaches wherein receiving from the one or more sensors comprises receiving visual detection signal data from a camera (Yokoyama: ¶ 0070, “Further, when the fire detection unit 47 analyzes the image captured by the vehicle exterior camera 32 using a known analysis method and detects, for example, flame, smoke, sprinkler water discharge, etc., a fire occurs around the vehicle S. It is determined that the vehicle is in use, and a fire that has occurred in the vehicle parking area is detected. Alternatively, the fire detection unit 47 may detect the water discharge of the sprinkler based on the detection of a large amount of raindrops by the optical rain sensor and the parking position information, and detect the fire that has occurred in the own vehicle parking area.”),
the one or more fire-related conditions comprising at least one of a color, an illumination level, and a smoke amount (Yokoyama: ¶ 0070, ¶ 0071, “As described above, the external sensor 11 includes the external camera 32, and the control device 14 of the vehicle control unit 3 detects the fire by analyzing the image taken by the external camera 32. Therefore, the control device 14 analyzes the image to extract flames, smoke, and the like, so that a fire around the vehicle can be detected quickly.”. The system is clearly able to determine the presence of a fire based on the amount of smoke captured in the image, as shown in the cited paragraphs.).
Regarding claim 20, Yokoyama teaches a processing system for detecting and reporting fires by an autonomous vehicle, the processing system including a processor and a memory device, the memory device storing instructions that when executed cause the processor to (Yokoyama: ¶ 0031, “The vehicle management system 1 acquires the occurrence of a fire in the vicinity of the vehicle S based on the surrounding conditions acquired by the sensor or from the notification server 2 that holds information related to the occurrence of the fire (hereinafter referred to as fire information). This is a system for automatically running the vehicle S to evacuate when it is detected based on fire information.”, ¶ 0051, “The control device 14 is an electronic control unit (ECU) composed of a central processing unit (CPU), a ROM, a RAM, peripheral circuits, an input / output interface, various drivers, and the like. The control device 14 executes various vehicle controls by executing arithmetic processing according to the program by the CPU. The control device 14 may be configured as one hardware, or may be configured as a unit composed of a plurality of hardware. Further, at least a part of each functional unit of the control device 14 may be realized by hardware such as LSI, ASIC, FPGA, or may be realized by a combination of software and hardware.”):
receive, from the one or more sensors, at least one sensor signal representing one or more fire-related conditions surrounding the autonomous vehicle (Yokoyama: ¶ 0064, “The fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S (more specifically, the vehicle parking area) based on the detection result of the outside world sensor 11. When a fire is detected based on the detection result of the outside world sensor 11, the fire detection unit 47 generates fire occurrence information including specific fire position information indicating that the fire occurrence position is the own vehicle parking area.”);
identify one or more fire-indicative conditions surrounding the autonomous vehicle based on the one or more fire-related conditions (Yokoyama: ¶ 0066, “As described above, the external sensor 11 includes the temperature sensor 28 that detects the temperature outside the vehicle, and the control device 14 of the vehicle control unit 3 detects the fire based on the output of the temperature sensor 28. Therefore, when the temperature outside the vehicle becomes abnormally high, the control device 14 can detect a fire based on the output of the temperature sensor 28.”, ¶ 0067, “Further, the fire detection unit 47 determines that a fire has occurred in the vicinity of the vehicle S when the concentration of smoke contained in the outside air is higher than the predetermined fire determination concentration by the smoke sensor 29, and the own vehicle parking area. Detect the fire that broke out in.”, ¶ 0070, “Further, when the fire detection unit 47 analyzes the image captured by the vehicle exterior camera 32 using a known analysis method and detects, for example, flame, smoke, sprinkler water discharge, etc., a fire occurs around the vehicle S. It is determined that the vehicle is in use, and a fire that has occurred in the vehicle parking area is detected. Alternatively, the fire detection unit 47 may detect the water discharge of the sprinkler based on the detection of a large amount of raindrops by the optical rain sensor and the parking position information, and detect the fire that has occurred in the own vehicle parking area.”);
generate a fire detection signal based at least on the one or more fire-indicative conditions, a location of the one or more fire-indicative conditions, and a location of the autonomous vehicle (Yokoyama: ¶00064, “The fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S (more specifically, the vehicle parking area) based on the detection result of the outside world sensor 11. When a fire is detected based on the detection result of the outside world sensor 11, the fire detection unit 47 generates fire occurrence information including specific fire position information indicating that the fire occurrence position is the own vehicle parking area.”, ¶ 0073, “Further, the fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S based on the fire information transmitted from the notification server 2 and the position of the vehicle S acquired by the own vehicle position recognition unit 52. When a fire is detected based on the fire information and the own vehicle position information, the fire detection unit 47 includes a fire including specific fire position information indicating that the fire occurrence position is in the own vehicle parking area or a peripheral area other than the own vehicle parking area. Generate occurrence information.”);
and transmit the fire detection signal to an external receiver (Yokoyama: ¶ 0044, “The communication device 12 mediates the connection of the control device 14 to the network 35 such as the Internet. As a result, the control device 14 can be connected to a network 35 such as the Internet via the communication device 12, and communicates with various servers and a terminal 4 owned by a user outside the vehicle S via the network 35. It is possible. Further, the communication device 12 sends and receives signals by transmitting and receiving radio waves. As a result, the control device 14 can directly communicate with the external device of the vehicle S via the communication device 12.”, ¶ 0087, “Further, when a fire is detected by the fire detection unit 47, the state management unit 50 transmits specific fire position information to another vehicle in the parking facility where the vehicle S is parked, and also transmits specific fire position information according to the position of the fire source.”. The cited passage clearly shows that the fire detection signal is transmitted to other vehicles.); and
control operation of the autonomous vehicle, based on the one or more fire-indicative conditions (Yokoyama: ¶ 0077, “When the fire risk calculation unit 48 determines that the fire risk is equal to or higher than a predetermined threshold value (for example, "medium"), the evacuation route determination unit 49 refers to the navigation device 13, the position of the vehicle S, the map information, and the fire. An evacuation site suitable for evacuation of the vehicle S is set based on the specific fire position information included in the occurrence information. After that, the evacuation route determination unit 49 sets an evacuation route from the current position of the vehicle S to the evacuation site.”, ¶ 0081, “When the action planning unit 53 receives an instruction to travel on the evacuation route from the state management unit 50, the action planning unit 53 sends this instruction to the travel control unit 54. When the travel control unit 54 receives an instruction from the action planning unit 53 to travel on the evacuation route, the travel control unit 54 controls the travel motor 7, the steering device 8, and the brake device 9 so that the vehicle S travels on the evacuation route.”. The cited passages clearly teach that once a fire is determined, the system is configured to control the operation of the autonomous vehicle.).
Yokoyama does not teach wherein the one or more sensors comprise a chemical sensor configured for chemical detection of the one or more fire-related conditions,
the one or more fire-related conditions including a carbon dioxide amount and a carbon monoxide amount.
Chilla, in the same field of endeavor, teaches wherein the one or more sensors comprise a chemical sensor configured for chemical detection of the one or more fire-related conditions (Chilla: Column 29 lines 14-28, “In various embodiments, FDS or CO detection devices (e.g., 120c and 120d) may be configured to detect potential or actual fire events (e.g., fire 155) and/or high levels of CO and report information to a remote server 142 providing fire detection system services via the wireless network 100. Similarly, the remote server 142 may be configured to receive fire event reports and sensor data from several FDS or CO detection devices (e.g., 120c and 120d) as well as provide command signals (e.g., to wake up, activate certain sensors, report data, move, and/or shutdown or go into a low-power mode or other mode). In some embodiments a server providing fire detection system services may be deployed as or included within the functionality of a network element (e.g., a server coupled to a macro base station 110a).”, Column 31 lines 9-35, “Any number of such sensors and/or other sensors of any type may be included in different implementations of the FDS or CO detection device 200.”, Column 31 lines 36-48, “The sensors may include (but is not limited to) a variety of sensors including a local ambient temperature sensor 230 (i.e., a sensor for detecting a temperature outside of the FDS device), a remote temperature sensor 232, a smoke detector 234, an image sensor 236, an infrared sensor 238, an ambient humidity sensor 240, a chemical sensor 242 such as a carbon monoxide (CO) sensor, a carbon dioxide (CO2) sensor, and/or another chemical sensor, a sound sensor 244 (such as a microphone), a soil sensor 246, and other sensors or sensing devices, including any combination of the foregoing. It should be clear that any number of these (and/or other) sensors may be included in different implementations of the FDS device 200.”. The cited passages clearly teach that the device is configured with chemical sensors used to detect fire—related conditions.),
the one or more fire-related conditions including a carbon dioxide amount and a carbon monoxide amount (Patel: Column 31 lines 9-35, “Any number of such sensors and/or other sensors of any type may be included in different implementations of the FDS or CO detection device 200.”, Column 31 lines 36-48, “The sensors may include (but is not limited to) a variety of sensors including a local ambient temperature sensor 230 (i.e., a sensor for detecting a temperature outside of the FDS device), a remote temperature sensor 232, a smoke detector 234, an image sensor 236, an infrared sensor 238, an ambient humidity sensor 240, a chemical sensor 242 such as a carbon monoxide (CO) sensor, a carbon dioxide (CO2) sensor, and/or another chemical sensor, a sound sensor 244 (such as a microphone), a soil sensor 246, and other sensors or sensing devices, including any combination of the foregoing. It should be clear that any number of these (and/or other) sensors may be included in different implementations of the FDS device 200.”, Column 38 lines 55-62, “In block 606, the processor may generate a fire warning message comprising a fire alarm object in response to determining that the information received from the one or more sensors satisfy one or more threshold criteria indicative of a fire event or CO detection. In some embodiments, means for performing functions of the operations in block 604 may include the processor (e.g., 312, 314, 316, 318, 352, 366).”. The cited passages clearly teach that that a carbon monoxide and carbon dioxide amount are fire related conditions detected by the chemical sensors.).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention, to have combine the system for detecting and reporting fires by an autonomous vehicle taught in Yokoyama with wherein the one or more sensors comprise a chemical sensor configured for chemical detection of the one or more fire-related conditions, the one or more fire-related conditions including a carbon dioxide and a carbon monoxide amount taught in Chilla with a reasonable expectation of success. One of ordinary skill in the art would have been motivated to make this modification because it would have been obvious to try. One of ordinary skill in the art would have known that fire produces both carbon dioxide and carbon monoxide, and that the presence of these gases could be used to indicate the presence of a fire. Furthermore, a sensor that is configured to detect one or both of carbon dioxide and monoxide would have been known to one of ordinary skill in the art. Additionally, the device taught in Chilla is already configured to be used in a vehicle (Chilla: Column 29 line 48 – Column 30 line 3). A person of ordinary skill in the art would have had the technological capabilities required to have integrated such a senor into the system taught in Yokoyama. The combination would not have changed or introduced new functionality to either. No inventive effort would have been required.
Claim(s) 3, 5-6, 13, and 15-16 is/are rejected under 35 U.S.C. 103 as being unpatentable over JP 2021070447 A ("Yokoyama") in view of US 11604178 B2 ("Chilla") in further view of US 2019/0226856 A1 ("Ghannam").
Regarding claim 3, Yokoyama in view of Chilla does not teach wherein the external receiver comprises at least one of a local authority and a control center configured for further signal dissemination to the local authority.
Ghannam, in the same field of endeavor, teaches wherein the external receiver comprises at least one of a local authority and a control center configured for further signal dissemination to the local authority (Ghannam: Figure 7, Abstract, “A wireless communication module communicates with a remote fire response center, and transmits the fused data to the fire response center when a fire-related event is detected.”, ¶ 0008, “A wireless communication module is adapted to communicate with a remote fire response center, wherein the communication module transmits the fused data to the fire response center when the fire-related event is detected.”, ¶ 0035, “FIG. 7 depicts cloud-based fire response center 22 receiving fused data and performing various functions and interactions with a fleet of vehicles 65 and other assets such as 911 centers and emergency responders 66.”. One of ordinary skill in the art would see from the cited passages that the external receiver that the system transmits the fire signal to is a control center that further disseminates the signal.).
Yokoyama in view of Chilla teaches a system for detecting and reporting fires by an autonomous vehicle, but does not teach wherein the external receiver comprises at least one of a local authority and a control center configured for further signal dissemination to the local authority. Ghannam teaches wherein the external receiver comprises at least one of a local authority and a control center configured for further signal dissemination to the local authority. A person of ordinary skill in the art would have had the technological capabilities required to have modified the system for detecting and reporting fires by an autonomous vehicle taught in Yokoyama in view of Chilla with wherein the external receiver comprises at least one of a local authority and a control center configured for further signal dissemination to the local authority taught in Ghannam. Furthermore, the system taught in Yokoyama in view of Chilla is already configured transmit a fire detection signal to an external receiver, so modifying the system such that it transmits to the at least one of a local authority and a control center configured for further signal dissemination to the local authority as taught in Ghannam would not change or introduce new functionality, and would be well within the capabilities of one of ordinary skill in the art. No inventive effort would have been required. The combination would have yielded the predictable result of a system for detecting and reporting fires by an autonomous vehicle that transmits a fire detection signal to an external receiver, wherein the external receiver comprises at least one of a local authority and a control center configured for further signal dissemination to the local authority.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention, to have combine the system for detecting and reporting fires by an autonomous vehicle taught in Yokoyama in view of Chilla with wherein the external receiver comprises at least one of a local authority and a control center configured for further signal dissemination to the local authority taught in Ghannam with a reasonable expectation of success. One of ordinary skill in the art would have been motivated to make this modification because the combination would have yielded predictable results.
Regarding claim 5, Yokoyama in view of Chilla does not teach wherein the one or more sensors comprise an infrared camera configured for heat detection of the one or more fire-related conditions,
the one or more fire-related conditions comprising a temperature.
Ghannam, in the same field of endeavor, teaches wherein the one or more sensors comprise an infrared camera configured for heat detection of the one or more fire-related conditions (Ghannam: ¶ 0023, “An infrared camera subsystem 31 may also present in the vehicle as part of an object detection system capable of gathering data under low visible light conditions, for example. Infrared camera subsystem 31 also provides signal processing which is able to examine environmental parameters in the form of infrared images to detect a respective fire related trigger (such as a concentration of high intensity infrared indicative of fire).”),
the one or more fire-related conditions comprising a temperature (Ghannam: ¶ 0023. One of ordinary skill in the art would know that the intensity of the infrared signal captured by an infrared signal represents the thermal energy of thee object, or in other words, the objects temperature.).
Yokoyama in view of Chilla teaches a system for detecting and reporting fires by an autonomous vehicle, but does not teach wherein the one or more sensors comprise an infrared camera configured for heat detection of the one or more fire-related conditions, the one or more fire-related conditions comprising a temperature. Ghannam teaches wherein the one or more sensors comprise an infrared camera configured for heat detection of the one or more fire-related conditions, the one or more fire-related conditions comprising a temperature. A person of ordinary skill in the art would have had the technological capabilities required to have modified the system for detecting and reporting fires by an autonomous vehicle taught in Yokoyama in view of Chilla with wherein the one or more sensors comprise an infrared camera configured for heat detection of the one or more fire-related conditions, the one or more fire-related conditions comprising a temperature taught in Ghannam. Furthermore, the system taught in Yokoyama in view of Chilla is already configured a camera, so modifying the system such that it uses an infrared camera as taught in Ghannam would not change or introduce new functionality, and would be well within the capabilities of one of ordinary skill in the art. No inventive effort would have been required. The combination is therefore a substitution of a known sensor for another.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention, to have combine the system for detecting and reporting fires by an autonomous vehicle taught in Yokoyama in view of Chilla with wherein the one or more sensors comprise an infrared camera configured for heat detection of the one or more fire-related conditions, the one or more fire-related conditions comprising a temperature taught in Ghannam with a reasonable expectation of success. One of ordinary skill in the art would have been motivated to make this modification because the combination comprises a substitution of a known sensor for another.
Regarding claim 6, Yokoyama in view of Chilla in further view of Ghannam teaches wherein the infrared camera is further configured for nighttime visual detection of the one or more fire-related conditions (Ghannam: ¶ 0023, “An infrared camera subsystem 31 may also present in the vehicle as part of an object detection system capable of gathering data under low visible light conditions, for example. Infrared camera subsystem 31 also provides signal processing which is able to examine environmental parameters in the form of infrared images to detect a respective fire related trigger (such as a concentration of high intensity infrared indicative of fire).”),
the one or more fire-related conditions comprising at least one of an illumination level and a smoke amount (Ghannam: ¶ 0030, “In step 41, each separate subsystem examines its particular environmental parameters and compares them to corresponding triggers which may identify the potential presence of flame or smoke in the vicinity of the vehicle.”. The presence of absence of smoke is clearly one of the fire-related conditions.).
Regarding claim 13, Yokoyama in view of Chilla does not teach wherein transmitting the fire detection signal to the external receiver comprises transmitting to at least one of a local authority and a control center configured for further signal dissemination to the local authority.
Ghannam, in the same field of endeavor, teaches wherein transmitting the fire detection signal to the external receiver comprises transmitting to at least one of a local authority and a control center configured for further signal dissemination to the local authority (Ghannam: Figure 7, Abstract, “A wireless communication module communicates with a remote fire response center, and transmits the fused data to the fire response center when a fire-related event is detected.”, ¶ 0008, “A wireless communication module is adapted to communicate with a remote fire response center, wherein the communication module transmits the fused data to the fire response center when the fire-related event is detected.”, ¶ 0035, “FIG. 7 depicts cloud-based fire response center 22 receiving fused data and performing various functions and interactions with a fleet of vehicles 65 and other assets such as 911 centers and emergency responders 66.”. One of ordinary skill in the art would see from the cited passages that the external receiver that the system transmits the fire signal to is a control center that further disseminates the signal.).
Yokoyama in view of Chilla teaches a method for detecting and reporting fires by an autonomous vehicle, but does not teach wherein transmitting the fire detection signal to the external receiver comprises transmitting to at least one of a local authority and a control center configured for further signal dissemination to the local authority. Ghannam wherein transmitting the fire detection signal to the external receiver comprises transmitting to at least one of a local authority and a control center configured for further signal dissemination to the local authority. A person of ordinary skill in the art would have had the technological capabilities required to have modified the method for detecting and reporting fires by an autonomous vehicle taught in Yokoyama in view of Chilla with wherein transmitting the fire detection signal to the external receiver comprises transmitting to at least one of a local authority and a control center configured for further signal dissemination to the local authority taught in Ghannam. Furthermore, the method taught in Yokoyama in view of Chilla is already configured transmit a fire detection signal to an external receiver, so modifying the method such that it transmits to the at least one of a local authority and a control center configured for further signal dissemination to the local authority as taught in Ghannam would not change or introduce new functionality, and would be well within the capabilities of one of ordinary skill in the art. No inventive effort would have been required. The combination would have yielded the predictable result of a method for detecting and reporting fires by an autonomous vehicle that transmits a fire detection signal to an external receiver, wherein transmitting the fire detection signal to the external receiver comprises transmitting to at least one of a local authority and a control center configured for further signal dissemination to the local authority.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention, to have combine the method for detecting and reporting fires by an autonomous vehicle taught in Yokoyama in view of Chilla with wherein transmitting the fire detection signal to the external receiver comprises transmitting to at least one of a local authority and a control center configured for further signal dissemination to the local authority taught in Ghannam with a reasonable expectation of success. One of ordinary skill in the art would have been motivated to make this modification because the combination would have yielded predictable results.
Regarding claim 15, Yokoyama in view of Chilla does not teach wherein receiving from the one or more sensors comprises receiving heat detection signal data from an infrared camera,
the one or more fire-related conditions comprising a temperature.
Ghannam, in the same field of endeavor, teaches wherein receiving from the one or more sensors comprises receiving heat detection signal data from an infrared camera (Ghannam: ¶ 0023, “An infrared camera subsystem 31 may also present in the vehicle as part of an object detection system capable of gathering data under low visible light conditions, for example. Infrared camera subsystem 31 also provides signal processing which is able to examine environmental parameters in the form of infrared images to detect a respective fire related trigger (such as a concentration of high intensity infrared indicative of fire).”),
the one or more fire-related conditions comprising a temperature (Ghannam: ¶ 0023. One of ordinary skill in the art would know that the intensity of the infrared signal captured by an infrared signal represents the thermal energy of thee object, or in other words, the objects temperature.).
Yokoyama in view of Chilla teaches a method for detecting and reporting fires by an autonomous vehicle, but does not teach wherein receiving from the one or more sensors comprises receiving heat detection signal data from an infrared camera, the one or more fire-related conditions comprising a temperature. Ghannam teaches wherein receiving from the one or more sensors comprises receiving heat detection signal data from an infrared camera, the one or more fire-related conditions comprising a temperature. A person of ordinary skill in the art would have had the technological capabilities required to have modified the method for detecting and reporting fires by an autonomous vehicle taught in Yokoyama in view of Chilla with wherein receiving from the one or more sensors comprises receiving heat detection signal data from an infrared camera, the one or more fire-related conditions comprising a temperature taught in Ghannam. Furthermore, the method taught in Yokoyama in view of Chilla is already configured a camera, so modifying the method such that it uses an infrared camera as taught in Ghannam would not change or introduce new functionality, and would be well within the capabilities of one of ordinary skill in the art. No inventive effort would have been required. The combination is therefore a substitution of a known sensor for another.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention, to have combine the method for detecting and reporting fires by an autonomous vehicle taught in Yokoyama in view of Chilla with wherein receiving from the one or more sensors comprises receiving heat detection signal data from an infrared camera, the one or more fire-related conditions comprising a temperature taught in Ghannam with a reasonable expectation of success. One of ordinary skill in the art would have been motivated to make this modification because the combination comprises a substitution of a known sensor for another.
Regarding claim 16, Yokoyama in view of Chilla in further view of Ghannam teaches wherein receiving from the one or more sensors further comprises receiving nighttime visual detection signal data from the infrared camera (Ghannam: ¶ 0023, “An infrared camera subsystem 31 may also present in the vehicle as part of an object detection system capable of gathering data under low visible light conditions, for example. Infrared camera subsystem 31 also provides signal processing which is able to examine environmental parameters in the form of infrared images to detect a respective fire related trigger (such as a concentration of high intensity infrared indicative of fire).”),
the one or more fire-related conditions comprising at least one of an illumination level and a smoke amount (Ghannam: ¶ 0030, “In step 41, each separate subsystem examines its particular environmental parameters and compares them to corresponding triggers which may identify the potential presence of flame or smoke in the vicinity of the vehicle.”. The presence of absence of smoke is clearly one of the fire-related conditions.).
Claim(s) 9-10 and 18-19 is/are rejected under 35 U.S.C. 103 as being unpatentable over JP 2021070447 A ("Yokoyama") in view of US 11604178 B2 ("Chilla") in further view of US 10257669 B2 ("Patel").
Regarding claim 9, Yokoyama in view of Chilla does not teach wherein the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature.
Patel, in the same field of endeavor, teaches wherein the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature (Patel: Column 9 line 47 – Column 10 line 19, “In the example of fire detection, the risk indicator is calculated by comparing the input data (e.g., a measured ambient temperature) with a pre-determined temperature value that indicates a fire breakout, and the pre-determined temperature value may be determined based on the history of the ambient temperature and adjusted to take into consideration of factors such as the time (e.g., afternoon vs. night time) and the season (e.g., winter vs. summer) when the input data is measured. When the calculated risk indicator is larger than a pre-determined risk threshold, which may indicate a high probability (e.g., larger than 85%) of a risk event (e.g., fire breakout), the DAE (e.g., the time-series database 435 of the DAE) declares that the risk event is detected. In embodiments where input data from multiple input sources (e.g., temperature sensors, smoke sensors, light sensors, and CO sensors) are used to detect a risk event, each sensor's data may be used to produce a respective risk indicator and/or a respective temporary risk event detection decision, and the risk indicators and/or the temporary risk event detection decisions from multiple sensors are analyzed and combined by the time-series database 435 to form a final risk indicator and/or to form a final decision regarding detection of the risk event. Rules (e.g., the weighted sum rule, the majority rule) for combining risk indicators and/or the temporary risk event detection decisions are discussed previously and not repeated here.”).
Yokoyama in view of Chilla teaches a system for detecting and reporting fires by an autonomous vehicle, but does not teach wherein the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature. Patel teaches wherein the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature. A person of ordinary skill in the art would have had the technological capabilities required to have modified the system taught in Yokoyama in view of Chilla with wherein the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature taught in Patel. Furthermore, the system taught in Yokoyama in view of Chilla is configured to determine at least one a smoke amount, and a temperature. One of ordinary skill in the art would have been able to have modified the system taught in Yokoyama in view of Chilla to determine a fire probability based on these values as taught in Patel without changing or introducing new functionality. No inventive effort would have been required. The combination would have yielded the predictable result of a system for detecting and reporting fires by an autonomous vehicle wherein the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention, to have combine the system for detecting and reporting fires by an autonomous vehicle taught in Yokoyama in view of Chilla with wherein the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature taught in Patel with a reasonable expectation of success. One of ordinary skill in the art would have been motivated to make this modification because the combination would have yielded predictable results.
Regarding claim 10, Yokoyama in view of Chilla in further view of Patel teaches wherein the fire probability assessment is further based on a number of sensor signals received and a number of the one or more sensors from which sensor signals were received (Patel: Column 9 lines 20-46, “In some embodiments, the time-series database 435 interprets collected data from multiple input sources (e.g., different sensors) to calculate a risk indicator and/or to detect a risk event. The data (e.g., input signals) from the multiple input sources may be discrete data samples taken at discrete time slots. As an example, consider fire detection by the DAE 400 using multiple sensors, e.g., temperature sensor, smoke sensor, light sensor, and/or CO sensor. Each sensor may periodically send a measured data to the DAE 400. By combing data across multiple APIs (e.g., data from different sensors), the time-series database 435 compares the outcomes (e.g., risk indicators, predicted risk indicators, risk events detection, or potential risk events detection) generated using data from multiple input sources, and identifies a correlation or certain degrees of consistency among the outcomes, and uses the identified correlation or consistency to form a final outcome.”, Column 9 line 47 – Column 10 line 19, “In the example of fire detection, the risk indicator is calculated by comparing the input data (e.g., a measured ambient temperature) with a pre-determined temperature value that indicates a fire breakout, and the pre-determined temperature value may be determined based on the history of the ambient temperature and adjusted to take into consideration of factors such as the time (e.g., afternoon vs. night time) and the season (e.g., winter vs. summer) when the input data is measured. When the calculated risk indicator is larger than a pre-determined risk threshold, which may indicate a high probability (e.g., larger than 85%) of a risk event (e.g., fire breakout), the DAE (e.g., the time-series database 435 of the DAE) declares that the risk event is detected. In embodiments where input data from multiple input sources (e.g., temperature sensors, smoke sensors, light sensors, and CO sensors) are used to detect a risk event, each sensor's data may be used to produce a respective risk indicator and/or a respective temporary risk event detection decision, and the risk indicators and/or the temporary risk event detection decisions from multiple sensors are analyzed and combined by the time-series database 435 to form a final risk indicator and/or to form a final decision regarding detection of the risk event. Rules (e.g., the weighted sum rule, the majority rule) for combining risk indicators and/or the temporary risk event detection decisions are discussed previously and not repeated here.”. One of ordinary skill in the art would see from the cited passages that the system is configured to determine the fire probability based on the number of sensor data points received and the number of sensors they are received from.).
Regarding claim 18, Yokoyama in view of Chilla teaches wherein transmitting the fire detection signal comprises transmitting at least one of a time, a location of the autonomous vehicle, a location of the one or more fire-indicative conditions, the one or more fire-indicative conditions, and a fire probability assessment (Yokoyama: ¶ 0064, “The fire detection unit 47 detects a fire that has occurred in the vicinity of the vehicle S (more specifically, the vehicle parking area) based on the detection result of the outside world sensor 11. When a fire is detected based on the detection result of the outside world sensor 11, the fire detection unit 47 generates fire occurrence information including specific fire position information indicating that the fire occurrence position is the own vehicle parking area.”, ¶ 0076, “For example, when the fire risk calculation unit 48 detects a fire that has occurred in the own vehicle parking area based on the detection result of the external sensor 11, the fire risk is calculated as “high”. When the fire risk calculation unit 48 detects a fire that has occurred in the vehicle parking area based on the fire information, the fire risk has not yet been detected based on the detection result of the outside world sensor 11, so the fire risk is set to "medium". calculate. When the fire risk calculation unit 48 detects a fire that has occurred in the surrounding area based on the fire information, the fire risk calculation unit 48 calculates the fire risk as “low” or “medium”. Specifically, the fire risk calculation unit 48 calculates the possibility that a fire that occurs in the surrounding area will spread to the own vehicle parking area based on the fire type information, fire occurrence position information, and weather information included in the fire information. However, when the fire spread possibility is equal to or less than a predetermined threshold, the fire risk is calculated as "low", and when the fire spread possibility exceeds the predetermined threshold, the fire risk is calculated as "medium".”, ¶ 0091, “The control device 14 (state management unit 50) transmits the first reception start signal to the terminal 4 in step ST2. The first reception start signal includes fire occurrence information, a peripheral image of the vehicle S acquired from the external camera 32, and a fire risk.”. The cited passages clearly show that the fire signal comprises the location of the fire and a fire probability (the fire risk).),
Yokoyama in view of Chilla does not teach the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature.
Patel, in the same field of endeavor, teaches the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature (Patel: Column 9 line 47 – Column 10 line 19, “In the example of fire detection, the risk indicator is calculated by comparing the input data (e.g., a measured ambient temperature) with a pre-determined temperature value that indicates a fire breakout, and the pre-determined temperature value may be determined based on the history of the ambient temperature and adjusted to take into consideration of factors such as the time (e.g., afternoon vs. night time) and the season (e.g., winter vs. summer) when the input data is measured. When the calculated risk indicator is larger than a pre-determined risk threshold, which may indicate a high probability (e.g., larger than 85%) of a risk event (e.g., fire breakout), the DAE (e.g., the time-series database 435 of the DAE) declares that the risk event is detected. In embodiments where input data from multiple input sources (e.g., temperature sensors, smoke sensors, light sensors, and CO sensors) are used to detect a risk event, each sensor's data may be used to produce a respective risk indicator and/or a respective temporary risk event detection decision, and the risk indicators and/or the temporary risk event detection decisions from multiple sensors are analyzed and combined by the time-series database 435 to form a final risk indicator and/or to form a final decision regarding detection of the risk event. Rules (e.g., the weighted sum rule, the majority rule) for combining risk indicators and/or the temporary risk event detection decisions are discussed previously and not repeated here.”).
Yokoyama in view of Chilla teaches a method for detecting and reporting fires by an autonomous vehicle wherein transmitting the fire detection signal comprises transmitting at least one of a time, a location of the autonomous vehicle, a location of the one or more fire-indicative conditions, the one or more fire-indicative conditions, and a fire probability assessment, but does not teach wherein the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature. Patel teaches the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature. A person of ordinary skill in the art would have had the technological capabilities required to have modified the method taught in Yokoyama in view of Chilla with the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature taught in Patel. Furthermore, the method taught in Yokoyama in view of Chilla is configured to determine at least one a smoke amount, and a temperature. One of ordinary skill in the art would have been able to have modified the method taught in Yokoyama in view of Chilla to determine a fire probability based on these values as taught in Patel without changing or introducing new functionality. No inventive effort would have been required. The combination would have yielded the predictable result of a method for detecting and reporting fires by an autonomous vehicle wherein the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claimed invention, to have combine the method for detecting and reporting fires by an autonomous vehicle taught in Yokoyama in view of Chilla with the fire probability assessment is based on at least one of a light threshold amount, a smoke threshold amount, and a threshold temperature taught in Patel with a reasonable expectation of success. One of ordinary skill in the art would have been motivated to make this modification because the combination would have yielded predictable results.
Regarding claim 19, Yokoyama in view of Chilla in further view of Patel teaches wherein transmitting the fire probability assessment is further based on a number of sensor signals received and a number of the one or more sensors from which sensor signals were received (Patel: Column 9 lines 20-46, “In some embodiments, the time-series database 435 interprets collected data from multiple input sources (e.g., different sensors) to calculate a risk indicator and/or to detect a risk event. The data (e.g., input signals) from the multiple input sources may be discrete data samples taken at discrete time slots. As an example, consider fire detection by the DAE 400 using multiple sensors, e.g., temperature sensor, smoke sensor, light sensor, and/or CO sensor. Each sensor may periodically send a measured data to the DAE 400. By combing data across multiple APIs (e.g., data from different sensors), the time-series database 435 compares the outcomes (e.g., risk indicators, predicted risk indicators, risk events detection, or potential risk events detection) generated using data from multiple input sources, and identifies a correlation or certain degrees of consistency among the outcomes, and uses the identified correlation or consistency to form a final outcome.”, Column 9 line 47 – Column 10 line 19, “In the example of fire detection, the risk indicator is calculated by comparing the input data (e.g., a measured ambient temperature) with a pre-determined temperature value that indicates a fire breakout, and the pre-determined temperature value may be determined based on the history of the ambient temperature and adjusted to take into consideration of factors such as the time (e.g., afternoon vs. night time) and the season (e.g., winter vs. summer) when the input data is measured. When the calculated risk indicator is larger than a pre-determined risk threshold, which may indicate a high probability (e.g., larger than 85%) of a risk event (e.g., fire breakout), the DAE (e.g., the time-series database 435 of the DAE) declares that the risk event is detected. In embodiments where input data from multiple input sources (e.g., temperature sensors, smoke sensors, light sensors, and CO sensors) are used to detect a risk event, each sensor's data may be used to produce a respective risk indicator and/or a respective temporary risk event detection decision, and the risk indicators and/or the temporary risk event detection decisions from multiple sensors are analyzed and combined by the time-series database 435 to form a final risk indicator and/or to form a final decision regarding detection of the risk event. Rules (e.g., the weighted sum rule, the majority rule) for combining risk indicators and/or the temporary risk event detection decisions are discussed previously and not repeated here.”. One of ordinary skill in the art would see from the cited passages that the system is configured to determine the fire probability based on the number of sensor data points received and the number of sensors they are received from.).
Response to Arguments
Applicant’s arguments, see Pages 8-9, filed on October 8th, 2025, with respect to the 35 U.S.C. § 101 to claims 1, 3-11, and 13-20 have been fully considered and are persuasive. The independent claims 1, 11, and 20 have been amended to recite the limitations “control operation of the autonomous vehicle, based on the one or more fire-indicative conditions”, “controlling operation of the autonomous vehicle, based on the one or more fire-indicative conditions”, and “control operation of the autonomous vehicle, based on the one or more fire-indicative conditions” respectively. These newly amended limitations clearly recite an active control step of the vehicle using the result of the abstract idea. Such a limitation is clearly indicative of integration into a practical application. Therefore, the 35 U.S.C. § 101 to claims 1, 3-11, and 13-20 has been withdrawn.
Applicant’s arguments with respect to claim(s) 1, 11, and 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/N.W.S./ Examiner, Art Unit 3658
/TRUC M DO/ Primary Examiner, Art Unit 3658
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