Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
This action is in response to papers filed on 7/8/2026.
Claims 1, 6, 10, and 15 have been amended.
No claims have been cancelled.
No claims have been added.
Claims 1-15 are pending.
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 7/8/2026 has been entered.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 1-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Step 1:
The claims are directed to a process (method as introduced in Claim 10), and/or an apparatus (Claims 1 and 6), thus Claims 1-15 fall within one of the four statutory categories. See MPEP 2106.03.
Step 2A, Prong 1:
The claimed invention recites an abstract idea according to MPEP §2106.04. The independent claims which recite the following claim limitations as an abstract idea, are underlined below.
Claims 1, 6 ,and 10 recite (as represented by the language of Claim 6):
a network interface configured to receive Internet of Things (loT) device logs from IoT devices that exist at a scene of a particular crime, the network interface also configured to receive a list of evidence used in past prosecutions for crimes similar to the particular crime, wherein the IoT device logs comprise logs of events that happened at the crime scene that were detected by the IoT devices, and the list of evidence used in past prosecutions comprises a list of events that were mentioned in the past prosecutions , wherein the network interface is also configured to receive images from cameras that exist at the scene of the particular crime, and the list of evidence used in past prosecutions for similar crimes comprises a list of objects that were mentioned in the past prosecutions;
a processor executing code that instructs the processor to:
receive, within a range of the incident time and based on detection of the particular crime being a specified crime type via an IoT control app, the IoT device logs from the network interface;
receive the list of evidence used in the past prosecutions;
compare the events that happened at the crime scene according to IoT operating states logged by the IoT devices via the IoT device logs with events that were mentioned in the evidence used in the past prosecutions in order to identify a triggering time sequence and triggering time duration of the IoT devices;
receive the images from the network interface;
identify objects within the images;
compare the identified objects to objects that were mentioned in the evidence used in the past prosecutions;
identify a triggering time sequence and triggering time duration of the IoT devices based on IoT operating states logged by the IoT devices via the IoT device logs;
determine that the triggering time sequence and the triggering time duration of the IoT devices comprises an order, manner of use, and time of use of each of the IoT devices that was accessed relative to the crime scene
identifying, based on a comparison of the list of objects according to similar IoT device logs in past prosecutions with objects within the images, particular evidence having a highest weighted importance score, wherein the similar IoT device logs are similar to the IoT device logs due to the triggering time sequence and the triggering time duration;
provide a recommendation to a user to search for the particular evidence based on the comparison of the events that happened at the crime scene to the events that were mentioned in the evidence ; and
provide a recommendation to a user to search for the particular evidence based on the highest weighted importance score.
The underlined claim limitations as emphasized above, as drafted, recite a process that, under its broadest reasonable interpretation covers the performance of managing personal behavior or relationships or interactions between people in the form of providing recommendations for actions to be performed based on comparisons with attributes of similar events. Other than reciting a computer implementation, nothing in the claim elements precludes the step from encompassing the managing of personal behavior or relationships or interactions between people which represents the abstract idea of certain methods of organizing human activity. But for the recitation of generic implementation of computer system components, the claimed invention merely recites a process for comparing attributes of a crime with attributes of previous crimes to determine useful or relevant evidence and provide recommendations.
Step 2A, Prong 2:
This judicial exception is not integrated into a practical application. In particular, the claims recite additional elements such as:
an apparatus;
a network interface configured to receive loT device logs from IoT devices (including data contained in the logs, such as events, objects, operating states, etc.1)
the network interface is also configured to receive images from cameras;
IoT control app; and
a processor executing code that instructs the processor to receive and compare the log and image data;
In particular, the additional elements cited above beyond the abstract idea are recited at a high-level of generality and simply equivalent to a generic recitation and basic functionality that amount to no more than mere instructions to apply the judicial exception using generic computer technology components.
1 The data in the logs merely represent the data used for comparison and does not impart any significant technical limitations. As a non-limiting example, the “IoT operating states logged” is nothing more than particular data that was collected and the operating status of any device does not provide any technical limitations.
Accordingly, since the specification describes the additional elements in general terms, without describing the particulars, the additional elements may be broadly but reasonably construed as generic computing components being used to perform the judicial exception (see specification at [014] and [059], see also [028], the IoT control app is merely an app that is used to setup and interact with and control devices and does not provide any significant improvement or practical application in its use). These claimed additional elements merely recite the words “apply it" (or an equivalent) with the judicial exception, or merely include instructions to implement an abstract idea on a computer, or merely using a computer as a tool to perform an abstract idea, as discussed in MPEP 2106.05(f).
Thus, the additional claim elements are not indicative of integration into a practical application, because the claims do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e)). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea and the claims are directed to an abstract idea.
Step 2B:
The claims do not include additional elements, individually or in combination, that are sufficient to amount to significantly more than the judicial exception. As discussed above with respect to integration of the abstract idea into a practical application, the additional element amounts to no more than mere instructions to apply the exception using generic computer components. Mere instructions to apply an exception using a generic computer component cannot provide an inventive concept at Step 2B. Thus, the claim is not patent eligible.
Dependent Claims:
Claims 2-5, 7-9, and 11-15 recite further elements related to the data comparison and recommendation providing steps of the parent claims. These activities fail to differentiate the claims from the related activities in the parent claims and fail to provide any material to render the claimed invention to be significantly more than the identified abstract ideas, as outlined below.
Claims 2, 7, and 11 recite “wherein the processor also executes code that instructs the processor to: weight the evidence used in the past prosecutions based on how often the evidence was mentioned during trial; and wherein the recommendation comprises a recommendation to search for the particular evidence that was mentioned the most at trial”, which further specifies additional steps relating to the comparison and recommendation steps of the parent claims, but does not lead toward eligibility. The additional weighting steps and specific types of recommendations are part of the abstract idea and merely reciting that they are performed by a processor does not integrate the abstract idea into a practical application or provide an inventive concept.
Claims 3, 8, and 12 recite “wherein the recommendation comprises a recommendation to search for evidence of events that were mentioned in the evidence used in the past prosecutions but were not mentioned in the events that happened at the crime scene”, which further specifies additional steps relating to the comparison and recommendation steps of the parent claims, but does not lead toward eligibility. Specific types of recommendations are part of the abstract idea does not integrate the abstract idea into a practical application or provide an inventive concept.
Claims 4 and 13 recite material that is included in at least independent Claim 6 and is therefore addressed by the independent claim rejections provided above.
Claims 5, 9, and 14 recite “wherein the recommendation comprises a recommendation to search for objects that were mentioned in the evidence used in the past prosecutions but that were not identified in the images from the crime scene”, which further specifies additional steps relating to the comparison and recommendation steps of the parent claims, but does not lead toward eligibility. Specific types of recommendations are part of the abstract idea does not integrate the abstract idea into a practical application or provide an inventive concept.
Claim 15 recites “wherein the step of comparing the events that happened at the crime scene to the events that were mentioned in the evidence used in the past prosecutions, comprises comparing an IoT device type, an loT device operating state, a triggering time sequence, and the triggering time”, which recites specific types of data to compare, but does not make the claims any less abstract. The specific types of data for comparing is part of the abstract idea and merely using those particular attributes does not integrate the abstract idea into a practical application or provide an inventive concept.
The claims do not provide any new additional limitations or meaningful limits beyond abstract idea that are not addressed above in the independent claims therefore, they do not integrate the abstract idea into a practical application nor do they provide significantly more to the abstract idea. Thus, after considering all claim elements, both individually and as a whole, it has been determined that the claims do not integrate the judicial exception into a practical application or provide an inventive concept. Therefore, Claims 2-5, 7-9, and 11-15 are ineligible.
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, 4-7, 9-11, and 13-15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Verdejo et al. (Pub. No. US 2018/0150750 A1) in view of Liu et al. (CN 115577077 A) in further view of Yeoh et al. (Pub. No. US 2021/0176317 A1) in further view of Wu (CN 111353307 A).
In regards to Claim 1, Verdejo discloses:
An apparatus comprising:
a network interface configured to receive Internet of Things (loT) device logs from IoT devices that exist at a scene of a particular crime at an incident time…to receive images from cameras that exist at the scene of the particular crime, wherein the IoT device logs comprise logs of events that happened at the crime scene that were detected by the IoT devices, ([0035]; [0045]; Fig. 1E; Fig. 2, surveillance system may include multiple connected devices including multiple cameras for capturing image and video data, the multiple devices/cameras collecting data and transmitting it to the analytics system/server represents an internet of things; [0011], surveillance systems (such as the multiple cameras and image capture devices previously cited can capture video/images/audio for review at a later time (indicating device logs) and can detect criminal activity (criminal activity occurring would represent a crime scene, see also [0001]; [0032]; [0033]; [0061], the IoT devices can be used to detect criminal activity (crime scenes) and/or used to investigate crimes))
a processor executing code that instructs the processor to: ([0002]; [0047])
receive the IoT device logs and the images from the network interface; ([0046], systems includes a communication interface for transmitting data between components of the networked system (network interface); [0059]; etc., the data logged by the devices include image data and associated metadata (such as time, location, etc.); [0011]; etc., the image and associated data can be used for review at a later time, indicating that the data/images captured by the devices is “logged”; [0045], the surveillance system (IoT devices) send data to the analytics system (which includes applications for analyzing the data, including identifying event types), it is noted that “IoT control app” is merely a label for the app and the app in Verdejo performs the same functions as described in the claims)
receive [indication of] of evidence used in the past [criminal events]; ([0020]; [0044]; [0058], historical event data (including items/objects or events at a crime scene) can be stored a nr retrieved [material regarding lists of evidence and past prosecutions is addressed by the Liu, explained below])
compare the events that happened at the crime scene to the events that were [also identified in past criminal events]; ([0085], provides an example of comparing events between the historic criminal event and current crime scene, such as “entering through a window”, etc. [material regarding evidence mentioned in past prosecutions is addressed by the Liu, explained below])
identify, based on a comparison of the list of objects with objects within the images, particular evidence having a score; ([0083], determines a score related to a correlation (comparisons) of current events and/or objects to those in past events; [0085], comparisons to past crimes including tools (objects); [0066], terms related to events and context of events re made into alit; [0082], terms can represent objects identified in images (see also [006]; [0020]; [0068]; [0069], further material connecting objects in images, context of events, and terms, which are then used to make the lists); [0020], compares collected data (collected from IoT surveillance devices) based on comparable times of incidents and comparison of collected data)
provide a recommendation to a user to [perform an action] based on the comparison of the events that happened at the crime scene to the events that were [also identified in past criminal events]; ([0122], recommendations are made for actions to be taken based on similarities between the current event and similar historical events (see also [0123]-[0128]))
Verdejo discloses the above method/system for comparing current crime scenes to historic crime events. As shown above, Verdejo includes matching events and items/objects to events and items in the records of the historic crime events. Verdejo does not explicitly disclose that these events and items/objects are mentioned in past prosecutions or using lists of evidence, however Liu teaches:
a list of evidence used in past prosecutions for crimes similar to the particular crime, and the list of evidence used in past prosecutions comprises a list of events and a list of objects that were mentioned in the past prosecutions; (Abstract; page 1, line 21-page 2, line 4; page 3, lines 15-24, 36-40, evidence data regarding historical cases and evidence used in those cases is correlated to the current investigation to make recommendations regarding evidence to collect (the reference to a procuratorate indicates use in a prosecution and/or trial); Abstract; page 3, lines 15-24, also discloses that multiple kinds of evidence can be referenced and the use of natural language processing on records demonstrates a “list” (at minimum a record that would include natural language and list kinds of evidence related to historical case within it), in addition to the abstract, NLP, text, and records are discussed throughout the reference; page 5, lines 13-28, the past related cases include items/objects and events (one example being a knife (item) and some being killed (event))
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of Verdejo so as to have included a list of evidence used in past prosecutions for crimes similar to the particular crime, as taught by Liu in order to ensure that relevant evidence is collected and handled properly to avoid any potential issues that would delay or interrupt prosecution (Liu, Abstract; page 1, line 21-page 2, line 4; page 2, lines 35-39; page 3, lines 32-51, etc.).
Additionally, Verdejo discloses the above method/system for making recommendations regarding actions to be taken in response to the identification of similarities between the crime scene and historic crime event. Verdejo does not explicitly disclose that the actions include specific evidence to collect, however Liu teaches:
provide a recommendation to a user to search for the particular evidence based on the comparison of the events that happened at the crime scene to the events that were mentioned in the evidence; (at least page 3, lines 36-40, recommends types of evidence to search for and/or collect and how to do so)
Verdejo discloses the recommendation of actions to be taken, including in regards to a crime scene, as described above.
Verdejo demonstrates that the ability to recommend actions (including recommendations to law enforcement or investigators in regards to crime events) based on comparison of evidence between historic events and a current event was known in the prior art before the effective filing date of the claimed invention.
Liu further demonstrates that recommended actions can be recommendations for evidence to collect and how to do so in order to ensure that the evidence is collected properly and useable, as described above.
Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself- that is in the substitution of the recommendation of evidence to look for and/or collect of the secondary reference for the recommendation of any actions to be performed in the primary reference.
Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
Verdejo/Liu discloses the above method/system for comparing current crime scenes to historic crime events. Additionally, Verdejo teaches device data including manner of use (see at least [0014]; [0045], audio recording, video recording, image capture, etc. as evidenced by the type of media collected), receiving the IoT device logs from the network interface (as described above), and comparing logs with historical logs to identify similarities (as described above). Verdejo/Liu does not explicitly use of a triggering time sequence and a triggering time duration of the IoT devices disclose, but Yeoh teaches:
receive, within a range of the incident time and based on detection of the particular crime being a specified crime type via an IoT control app, the IoT device logs from the network interface; ([0045], the data used to identify IoT device data to collect (log data includes data collected by the IoT device, operating state of the IoT device, etc.), includes incident type and time periods; [0037], “In another embodiment, the electronic computing device may broadcast a probe signal to request IoT devices 130 connected to a particular wireless router to respond with its identifier.”, identifier is used to collect additional information (including log data), indicating that the computing device includes IoT control software (it is noted that “IoT control app” is merely a label for the app and the app in Verdejo performs the same functions as described in the claims))
compare the events that happened at the crime scene according to IoT operating states logged by the IoT devices via the IoT device logs with events that were [also identified in past event data] in order to identify a triggering time sequence and triggering time duration of the IoT devices; ([0036]; [0037], uses information from previously mentioned data (conversations with law enforcement etc., this previously mentioned data would be used in the same manner as the trial data in Verdejo/Liu for the purposes of identifying time triggers, regardless of how it is acquired (previous trials, conversations, etc.), statements made by witnesses or other parties are a type of evidence, ; [0019]; 0039]; [0040], the operating states of IoT devices are collected in the historical (log) data, including signal strength as affected by movement of object and/or IoT position, this fluctuating of signal strength is used to indicate that the IoT device observed activity related to evidence (“…a change in the spatial position of the IoT device 130 may affect the signal strength corresponding to the signal received by the IoT device 130 from a wireless router and this in turn may affect the RSSI value captured at the IoT device 130. The signal strength may either drop or increase depending at least on the physical positions of the IoT device 130 and the wireless router and associated environmental factors. Similarly, when an object (e.g., a person) passes by the IoT device or moves back and forth relative to a position of the IoT device 130, a signal strength corresponding to a signal received by the IoT device 130 from the wireless may either drop or increase depending at least on the physical positions of the IoT device 130, the object, and the wireless router.”), identifies data (images, etc.) captured by the IoT devices during an identified time period, including when the data was collected and the duration of the strength fluctuation (the duration of the strength fluctuation indicates how long the IoT device was effected by position of object movement (device operating state), indicating a triggering time duration of the device operating state (time period in which the device was triggered); [0044], a pattern of an object movement (evidence) is created based on data collected from the multiple IoTs and related to different locations/areas and timestamps, one of ordinary skill in the art would recognize that in order to determine the pattern of movement, it would involve ordering the events (locations/movements of the object), therefore the data would be arranged in order based on the times and fluctuations in signal strengths (triggering as described above) indicating a time sequence in which the devices are triggered)
identify a triggering time sequence and triggering time duration of the IoT devices based on IoT operating states logged by the IoT devices via the IoT device logs; ([0036]; [0037]; [0039]; [0040]; [0044], as described above, the operating states of the IoT devices are recorded and compared to previously collected evidence data. The pre-collected evidence data includes timeframes and locations. This timeframe and location data is used to determine IoT devices that were present and to determine the times and durations for which the IoT devices were triggered (using signal strength fluctuations). The determination of the movement pattern of objects indicates that the IoT device data is also analyzed in a sequential manner (such as the order and duration in which each device is recording to determine the movement pattern of the object)
determine that the triggering time sequence and the triggering time duration of the IoT devices comprises an order and time of use of each of the IoT devices that was accessed relative to the crime scene; ([0036]; [0037]; [0039]; [0040]; [0044], as described above, the operating states of the IoT devices are recorded and compared to previously collected evidence data. The pre-collected evidence data includes timeframes and locations. This timeframe and location data is used to determine IoT devices that were present and to determine the times and durations for which the IoT devices were triggered (using signal strength fluctuations). The determination of the movement pattern of objects indicates that the IoT device data is also analyzed in a sequential manner (such as the order and duration in which each device is recording to determine the movement pattern of the object).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of Verdejo/Liu so as to have included receive, within a range of the incident time and based on detection of the particular crime being a specified crime type via an IoT control app, the IoT device logs from the network interface; compare the events that happened at the crime scene according to IoT operating states logged by the IoT devices via the IoT device logs with events that were [also identified in past event data] in order to identify a triggering time sequence and triggering time duration of the IoT devices; identify a triggering time sequence and triggering time duration of the IoT devices based on IoT operating states logged by the IoT devices via the IoT device logs; and determine that the triggering time sequence and the triggering time duration of the IoT devices comprises an order and time of use of each of the IoT devices that was accessed relative to the crime scene, as taught by Yeoh in order to ensure that relevant evidence is collected and no important evidence is missed (Yeoh, [0002]; Liu, Abstract; page 1, line 21-page 2, line 4; page 2, lines 35-39; page 3, lines 32-51, etc.).
Verdejo/Liu discloses the above method/system for comparing current crime scenes to historic crime events. As shown above, Verdejo includes matching events and items/objects to events and items in the records of the historic crime events and scoring items/evidence based on the correlations (including objects). Additionally, Liu teaches applying a statistical algorithm to determine probability and correlation degree of types of evidence items (page 3, lines 22-27, probability and correlation degrees are determined for evidence types/items to be used for recommendation of evidence to collect, high correlation degrees and thresholds can indicate importance of evidence for generating recommendations (it is noted that Verdejo also uses thresholds for scoring the correlations between past and current evidence, see Verdejo, [0083])). Verdejo does not explicitly disclose that recommended items/objects are based on a highest weighted importance score, however Wu teaches:
identify, based on a comparison of the list of objects with objects within the images, particular evidence having a highest weighted importance score; (page 4, lines 4-29, each piece of evidence is scored based on weights for the evidence, the weights based on importance of the evidence to outcomes of legal procedures)
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of Verdejo/Liu so as to have included use of a highest weighted importance score, as taught by Wu in order to ensure that the most pertinent and useful evidence is collected (Wu, page 4, lines 18-21; Liu, page 3, lines 32-40). One of ordinary skill in the art would understand how to apply the importance weights used in the scoring method of Wu to the correlation scores in Verdejo/Liu to identify a highest weighted importance score, and the reference demonstrate the required skill to do so.
In regards to Claims 2, 7, and 11, Verdejo/Liu discloses the above method/system for comparing crime data to data in previous prosecutions in order to make recommendations for evidence. Additionally, Liu teaches:
weight the evidence used in the past prosecutions based on how often the evidence was mentioned during trial; and wherein the recommendation comprises a recommendation to search for the particular evidence that was mentioned the most at trial (page 3, lines 15-27, the types of evidence for a history case are analyzed, including the number of times an evidence was used in the case, the evidence types are compared to determine a probability of a degree of correlation between the history case and the current case (probability of a degree of correlation can represent a weight when comparing different correlation degrees of different types of evidence), the recommendation result in determined based on the elements proportion/ratio value and a threshold (Examiner is interpreting the use of correlation degree, proportion/ration value, and threshold as a manner of determining which types of evidence are the most relevant and/or useful, since these calculations are based on counting the number of each kind of evidence used, the recommendation would include at least the piece of evidence that was most used and highest weighted)
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of system of Verdejo so as to have included weight the evidence used in the past prosecutions based on how often the evidence was mentioned during trial; and wherein the recommendation comprises a recommendation to search for particular evidence that was mentioned the most at trial so as to have included weight the evidence used in the past prosecutions based on how often the evidence was mentioned during trial; and wherein the recommendation comprises a recommendation to search for particular evidence that was mentioned the most at trial, as taught by Liu in order to ensure that relevant evidence is collected and handled properly to avoid any potential issues that would delay or interrupt prosecution (Liu, Abstract; page 1, line 21-page 2, line 4; page 2, lines 35-39; page 3, lines 32-51, etc.).
In regards to Claims 4, 6, and 13, Verdejo discloses:
An apparatus comprising:
a network interface configured to receive Internet of Things (loT) device logs from IoT devices that exist at a scene of a particular crime at an incident time, wherein the IoT device logs comprise logs of events that happened at the crime scene that were detected by the IoT devices, ([0035]; [0045]; Fig. 1E; Fig. 2, surveillance system may include multiple connected devices including multiple cameras for capturing image and video data, the multiple devices/cameras collecting data and transmitting it to the analytics system/server represents an internet of things ; [0011], surveillance systems (such as the multiple cameras and image capture devices previously cited can capture video/images/audio for review at a later time (indicating device logs) and can detect criminal activity (criminal activity occurring would represent a crime scene, see also [0001]; [0032]; [0033]; [0061]), the IoT devices can be used to detect criminal activity (crime scenes) and/or used to investigate crimes)
wherein the network interface is also configured to receive images from cameras that exist at the scene of the particular crime, ([0035]; [0045]; Fig. 1E; Fig. 2, surveillance system may include multiple connected devices including multiple cameras for capturing image and video data, the multiple devices/cameras collecting data and transmitting it to the analytics system/server represents an internet of things ; [0011], surveillance systems (such as the multiple cameras and image capture devices previously cited can capture video/images/audio for review at a later time (indicating device logs) and can detect criminal activity (criminal activity occurring would represent a crime scene (see also [0001]; [0032]; [0033]; [0061], the IoT devices can be used to detect criminal activity (crime scenes) and/or used to investigate crimes)
a processor executing code that instructs the processor to: ([0002]; [0047])
receive the IoT device logs from the network interface; ([0046], systems includes a communication interface for transmitting data between components of the networked system (network interface); [0011], can detect a type of event, including criminal activity (it is noted that one of ordinary skill in the art would understand that, in order to identify criminal events, the system/method would be required to be able to identify multiple types of criminal events as different types of criminal events would have different characteristics); [0045], the surveillance system (IoT devices) send data to the analytics system (which includes applications for analyzing the data, including identifying event types), it is noted that “IoT control app” is merely a label for the app and the app in Verdejo performs the same functions as described in the claims)
receive [indication of] of evidence used in the past [criminal events]; ([0020]; [0044]; [0058], historical event data (including items/objects or events at a crime scene) can be stored a nr retrieved [material regarding lists of evidence and past prosecutions is addressed by the Liu, explained below])
compare the events that happened at the crime scene according to events that were [also identified in past criminal events]; ([0085], provides an example of comparing events between the historic criminal event and current crime scene, such as “entering through a window”, etc. [material regarding evidence mentioned in past prosecutions is addressed by the Liu, explained below])
receive the images from the network interface; [0046], systems includes a communication interface for transmitting data between components of the networked system (network interface))
identify objects within the images; ([0085], can identify tools being used in the criminal event)
compare the identified objects to objects that were [also identified in past criminal events]; ([0085], provides an example of comparing events between the historic criminal event and current crime scene, such as “entering through a window”, etc. [material regarding evidence mentioned in past prosecutions is addressed by the Liu, explained below])
identify, based on a comparison of the list of objects according to similar IoT device logs in past [similar events] with objects within the images, particular evidence having a score, wherein the similar IoT device logs are similar to the IoT device logs due to the [time data]; ([0083], determines a score related to a correlation (comparisons) of current events and/or objects to those in past events; [0085], comparisons to past crimes including tools (objects); [0066], terms related to events and context of events re made into alit; [0082], terms can represent objects identified in images (see also [006]; [0020]; [0068]; [0069], further material connecting objects in images, context of events, and terms, which are then used to make the lists); [0020], compares collected data (collected from IoT surveillance devices) based on comparable times of incidents and comparison of collected data)
provide a recommendation to a user to [perform an action] based on the comparison of the events that happened at the crime scene to the events that were [also identified in past criminal events]; ([0122], recommendations are made for actions to be taken based on similarities between the current event and similar historical events (see also [0123]-[0128]))
Verdejo discloses the above method/system for comparing current crime scenes to historic crime events. As shown above, Verdejo includes matching events and items/objects to events and items in the records of the historic crime events. Verdejo does not explicitly disclose that these events and items/objects are mentioned in past prosecutions or using lists of evidence, however Liu teaches:
a list of evidence used in past prosecutions for crimes similar to the particular crime, and the list of evidence used in past prosecutions comprises a list of events that were mentioned in the past prosecutions; (Abstract; page 1, line 21-page 2, line 4; page 3, lines 15-24, 36-40, evidence data regarding historical cases and evidence used in those cases is correlated to the current investigation to make recommendations regarding evidence to collect (the reference to a procuratorate indicates use in a prosecution and/or trial); Abstract; page 3, lines 15-24, also discloses that multiple kinds of evidence can be referenced and the use of natural language processing on records demonstrates a “list” (at minimum a record that would include natural language and list kinds of evidence related to historical case within it), in addition to the abstract, NLP, text, and records are discussed throughout the reference; page 5, lines 13-28, the past related cases include items/objects and events (one example being a knife (item) and some being killed (event))
and the list of evidence used in past prosecutions for similar crimes comprises a list of objects that were mentioned in the past prosecutions; (page 5, lines 13-28, the record/list of past prosecutions includes items/objects and events (one example being a knife (item) and some being killed (event))
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of Verdejo so as to have included a list of evidence used in past prosecutions for crimes similar to the particular crime, and the list of evidence used in past prosecutions comprises a list of events that were mentioned in the past prosecutions and the list of evidence used in past prosecutions for similar crimes comprises a list of objects that were mentioned in the past prosecutions, as taught by Liu in order to ensure that relevant evidence is collected and handled properly to avoid any potential issues that would delay or interrupt prosecution (Liu, Abstract; page 1, line 21-page 2, line 4; page 2, lines 35-39; page 3, lines 32-51, etc.).
Additionally, Verdejo discloses the above method/system for making recommendations regarding actions to be taken in response to the identification of similarities between the crime scene and historic crime event. Verdejo does not explicitly disclose that the actions include specific evidence to collect, however Liu teaches:
provide a recommendation to a user to search for the particular evidence based on the comparison of the events that happened at the crime scene to the events that were mentioned in the evidence; (at least [page 3, lines 36-40, recommends types of evidence to search for and/or collect and how to do so)
Verdejo teaches the recommendation of actions to be taken, including in regards to a crime scene based on correlation scores to previous cases, as described above ([0122], recommendations are made for actions to be taken based on similarities between the current event and similar historical events (see also [0123]-[0128]))
Verdejo demonstrates that the ability to recommend actions (including recommendations to law enforcement or investigators in regards to crime events) based on comparison of evidence between historic events and a current event was known in the prior art before the effective filing date of the claimed invention.
Liu further demonstrates that recommended actions can be recommendations for evidence to collect and how to do so in order to ensure that the evidence is collected properly and useable, as described above.
Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself- that is in the substitution of the recommendation of evidence to look for and/or collect of the secondary reference for the recommendation of any actions to be performed in the primary reference.
Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
It is noted that the process for determining recommendations would be the same whether based on compared events or compared objects, or compared logs. This process would be performed in the same manner within the combined invention of the prior art reference (whether comparing events, objects, logs, or any combination) and Applicant’s claims do not provide any differentiation between how the process for comparing events for making recommendations is performed and how the process for comparing objects for making recommendations is performed.
Verdejo/Liu discloses the above method/system for comparing current crime scenes to historic crime events. Additionally, Verdejo discloses the ability to identify data related to the IoT devices, such as device type and time data (from Claim 15, [0015]; [0017]; [0059], “camera identifier”, “time of occurrence”, “…a location of a device that captured the media item, a time the media item was captured, or a device identifier of the device that captured the media item…”, etc.), manner of use (see at least [0014]; [0045], audio recording, video recording, image capture, etc. as evidenced by the type of media collected), receiving the IoT device logs from the network interface (as described above), and comparing logs with historical logs to identify similarities (as described above). Verdejo/Liu does not explicitly use of a triggering time sequence and a triggering time duration of the IoT devices disclose, but Yeoh teaches:
receive, within a range of the incident time and based on detection of the particular crime being a specified crime type via an IoT control app, the IoT device logs from the network interface; ([0045], the data used to identify IoT device data to collect (log data includes data collected by the IoT device, operating state of the IoT device, etc.), includes incident type and time periods; [0037], “In another embodiment, the electronic computing device may broadcast a probe signal to request IoT devices 130 connected to a particular wireless router to respond with its identifier.”, identifier is used to collect additional information (including log data), indicating that the computing device includes IoT control software (it is noted that “IoT control app” is merely a label for the app and the app in Verdejo performs the same functions as described in the claims))
compare the events that happened at the crime scene according to IoT operating states logged by the IoT devices via the IoT device logs with events that were [also identified in past event data] in order to identify a triggering time sequence and triggering time duration of the IoT devices; ([0036]; [0037], uses information from previously mentioned data (conversations with law enforcement etc., this previously mentioned data would be used in the same manner as the trial data in Verdejo/Liu for the purposes of identifying time triggers, regardless of how it is acquired (previous trials, conversations, etc.), statements made by witnesses or other parties are a type of evidence, ; [0019]; 0039]; [0040], the operating states of IoT devices are collected in the historical (log) data, including signal strength as affected by movement of object and/or IoT position, this fluctuating of signal strength is used to indicate that the IoT device observed activity related to evidence (“…a change in the spatial position of the IoT device 130 may affect the signal strength corresponding to the signal received by the IoT device 130 from a wireless router and this in turn may affect the RSSI value captured at the IoT device 130. The signal strength may either drop or increase depending at least on the physical positions of the IoT device 130 and the wireless router and associated environmental factors. Similarly, when an object (e.g., a person) passes by the IoT device or moves back and forth relative to a position of the IoT device 130, a signal strength corresponding to a signal received by the IoT device 130 from the wireless may either drop or increase depending at least on the physical positions of the IoT device 130, the object, and the wireless router.”), identifies data (images, etc.) captured by the IoT devices during an identified time period, including when the data was collected and the duration of the strength fluctuation (the duration of the strength fluctuation indicates how long the IoT device was effected by position of object movement (device operating state), indicating a triggering time duration of the device operating state (time period in which the device was triggered); [0044], a pattern of an object movement (evidence) is created based on data collected from the multiple IoTs and related to different locations/areas and timestamps, one of ordinary skill in the art would recognize that in order to determine the pattern of movement, it would involve ordering the events (locations/movements of the object), therefore the data would be arranged in order based on the times and fluctuations in signal strengths (triggering as described above) indicating a time sequence in which the devices are triggered)
identify a triggering time sequence and triggering time duration of the IoT devices based on IoT operating states logged by the IoT devices via the IoT device logs; ([0036]; [0037]; [0039]; [0040]; [0044], as described above, the operating states of the IoT devices are recorded and compared to previously collected evidence data. The pre-collected evidence data includes timeframes and locations. This timeframe and location data is used to determine IoT devices that were present and to determine the times and durations for which the IoT devices were triggered (using signal strength fluctuations). The determination of the movement pattern of objects indicates that the IoT device data is also analyzed in a sequential manner (such as the order and duration in which each device is recording to determine the movement pattern of the object)
determine that the triggering time sequence and the triggering time duration of the IoT devices comprises an order and time of use of each of the IoT devices that was accessed relative to the crime scene; ([0036]; [0037]; [0039]; [0040]; [0044], as described above, the operating states of the IoT devices are recorded and compared to previously collected evidence data. The pre-collected evidence data includes timeframes and locations. This timeframe and location data is used to determine IoT devices that were present and to determine the times and durations for which the IoT devices were triggered (using signal strength fluctuations). The determination of the movement pattern of objects indicates that the IoT device data is also analyzed in a sequential manner (such as the order and duration in which each device is recording to determine the movement pattern of the object).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of Verdejo/Liu so as to have included receive, within a range of the incident time and based on detection of the particular crime being a specified crime type via an IoT control app, the IoT device logs from the network interface; compare the events that happened at the crime scene according to IoT operating states logged by the IoT devices via the IoT device logs with events that were [also identified in past event data] in order to identify a triggering time sequence and triggering time duration of the IoT devices; identify a triggering time sequence and triggering time duration of the IoT devices based on IoT operating states logged by the IoT devices via the IoT device logs; and determine that the triggering time sequence and the triggering time duration of the IoT devices comprises an order and time of use of each of the IoT devices that was accessed relative to the crime scene, as taught by Yeoh in order to ensure that relevant evidence is collected and no important evidence is missed (Yeoh, [0002]; Liu, Abstract; page 1, line 21-page 2, line 4; page 2, lines 35-39; page 3, lines 32-51, etc.).
Verdejo/Liu/Yeoh discloses the above method/system for comparing current crime scenes to historic crime events. As shown above, Verdejo includes matching events and items/objects to events and items in the records of the historic crime events and scoring items/evidence based on the correlations (including objects). Additionally, Liu teaches applying a statistical algorithm to determine probability and correlation degree of types of evidence items (page 3, lines 22-27, probability and correlation degrees are determined for evidence types/items to be used for recommendation of evidence to collect, high correlation degrees and thresholds can indicate importance of evidence for generating recommendations (it is noted that Verdejo also uses thresholds for scoring the correlations between past and current evidence, see Verdejo, [0083])). Verdejo/Liu/Yeoh does not explicitly disclose that recommended items/objects are based on a highest weighted importance score, however Wu teaches:
identify, based on a comparison of the list of objects with objects within the images, particular evidence having a highest weighted importance score; (page 4, lines 4-29, each piece of evidence is scored based on weights for the evidence, the weights based on importance of the evidence to outcomes of legal procedures)
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of Verdejo/Liu/Yeoh so as to have included use of a highest weighted importance score, as taught by Wu in order to ensure that the most pertinent and useful evidence is collected (Wu, page 4, lines 18-21; Liu, page 3, lines 32-40).
The combination of references disclose the ability to determine recommendations for actions to perform (including identifying objects to collect) based on correlations scores and the ability to determine the weighted importance of evidence items, as shown above. One of ordinary skill in the art would understand how to apply the importance weights used in the scoring method of Wu to the correlation scores in Verdejo/Liu to identify a highest weighted importance score, as it would involve merely identifying the highest score among the various scores, and the references demonstrate the required skill to do so. Therefore, the combination of Verdejo, Liu, Yeoh, and Wu demonstrate the ability to provide a recommendation to a user to search for a particular based on the highest weighted importance score, as outlined in the above rejection.
In regards to Claims 5, 9, and 14, Verdejo/Liu discloses the above method/system for comparing crime data to data in previous prosecutions in order to make recommendations for evidence. Additionally, Liu teaches:
wherein the recommendation comprises a recommendation to search for objects that were mentioned in the evidence used in the past prosecutions but that were not identified in the images from the crime scene (page 5, lines 21-23, the types of evidence can include fingerprints and hair, one of ordinary skill in the art would recognize that these types of evidence would be commonly used evidence in many types of crimes and likely not visibly identifiable in captured images)
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of system of Verdejo so as to have included wherein the recommendation comprises a recommendation to search for objects that were mentioned in the evidence used in the past prosecutions but that were not identified in the images from the crime scene, as taught by Liu in order to ensure that relevant evidence is collected and handled properly to avoid any potential issues that would delay or interrupt prosecution (Liu, Abstract; page 1, line 21-page 2, line 4; page 2, lines 35-39; page 3, lines 32-51, etc.).
In regards to Claims 10 and 15, Verdejo discloses:
A method comprising:
receive Internet of Things (loT) device logs from IoT devices that exist at a scene of a particular crime, wherein the IoT device logs comprise logs of events that happened at the crime scene that were detected by the IoT devices, ([0035]; [0045]; Fig. 1E; Fig. 2, surveillance system may include multiple connected devices including multiple cameras for capturing image and video data, the multiple devices/cameras collecting data and transmitting it to the analytics system/server represents an internet of things ; [0011], surveillance systems (such as the multiple cameras and image capture devices previously cited can capture video/images/audio for review at a later time (indicating device logs) and can detect criminal activity (criminal activity occurring would represent a crime scene (see also [0001]; [0032]; [0033]; [0061], the IoT devices can be used to detect criminal activity (crime scenes) and/or used to investigate crimes)
receiving images from cameras that exist at the scene of the particular crime; ([0035]; [0045]; Fig. 1E; Fig. 2, surveillance system may include multiple connected devices including multiple cameras for capturing image and video data, the multiple devices/cameras collecting data and transmitting it to the analytics system/server represents an internet of things; [0011], surveillance systems (such as the multiple cameras and image capture devices previously cited can capture video/images/audio for review at a later time (indicating device logs) and can detect criminal activity (criminal activity occurring would represent a crime scene, see also [0001]; [0032]; [0033]; [0061], the IoT devices can be used to detect criminal activity (crime scenes) and/or used to investigate crimes))
comparing the events that happened at the crime scene to the events that were [also identified in past criminal events]; ([0085], provides an example of comparing events between the historic criminal event and current crime scene, such as “entering through a window”, etc. [material regarding evidence mentioned in past prosecutions is addressed by the Liu, explained below])
identify, based on a comparison of the list of objects with objects within the images, particular evidence having a score; ([0083], determines a score related to a correlation (comparisons) of current events and/or objects to those in past events; [0085], comparisons to past crimes including tools (objects); [0066], terms related to events and context of events re made into alit; [0082], terms can represent objects identified in images (see also [006]; [0020]; [0068]; [0069], further material connecting objects in images, context of events, and terms, which are then used to make the lists))
Verdejo discloses the above method/system for comparing current crime scenes to historic crime events. As shown above, Verdejo includes matching events and items/objects to events and items in the records of the historic crime events. Verdejo does not explicitly disclose that these events and items/objects are mentioned in past prosecutions or using lists of evidence, however Liu teaches:
a list of evidence used in past prosecutions for crimes similar to the particular crime, and the list of evidence used in past prosecutions comprises a list of events and a list of objects that were mentioned in the past prosecutions; (Abstract; page 1, line 21-page 2, line 4; page 3, lines 15-24, 36-40, evidence data regarding historical cases and evidence used in those cases is correlated to the current investigation to make recommendations regarding evidence to collect (the reference to a procuratorate indicates use in a prosecution and/or trial); Abstract; page 3, lines 15-24, also discloses that multiple kinds of evidence can be referenced and the use of natural language processing on records demonstrates a “list” (at minimum a record that would include natural language and list kinds of evidence related to historical case within it), in addition to the abstract, NLP, text, and records are discussed throughout the reference; page 5, lines 13-28, the past related cases include items/objects and events (one example being a knife (item) and some being killed (event))
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of Verdejo so as to have included a list of evidence used in past prosecutions for crimes similar to the particular crime, and the list of evidence used in past prosecutions comprises a list of events that were mentioned in the past prosecutions, as taught by Liu in order to ensure that relevant evidence is collected and handled properly to avoid any potential issues that would delay or interrupt prosecution (Liu, Abstract; page 1, line 21-page 2, line 4; page 2, lines 35-39; page 3, lines 32-51, etc.).
Additionally, Verdejo discloses the above method/system for making recommendations regarding actions to be taken in response to the identification of similarities between the crime scene and historic crime event. Verdejo does not explicitly disclose that the actions include specific evidence to collect, however Liu teaches:
provide a recommendation to a user to search for particular evidence based on the comparison of the events that happened at the crime scene to the events that were mentioned in the evidence; (at least [page 3, lines 36-40, recommends types of evidence to search for and/or collect and how to do so)
Verdejo teaches the recommendation of actions to be taken, including in regards to a crime scene based on correlation scores to previous cases, as described above ([0122], recommendations are made for actions to be taken based on similarities between the current event and similar historical events (see also [0123]-[0128]))
Verdejo demonstrates that the ability to recommend actions (including recommendations to law enforcement or investigators in regards to crime events) based on comparison of evidence between historic events and a current event was known in the prior art before the effective filing date of the claimed invention.
Liu further demonstrates that recommended actions can be recommendations for evidence to collect and how to do so in order to ensure that the evidence is collected properly and useable, as described above.
Since each individual element and its function are shown in the prior art, albeit shown in separate references, the difference between the claimed subject matter and the prior art rests not on any individual element or function but in the very combination itself- that is in the substitution of the recommendation of evidence to look for and/or collect of the secondary reference for the recommendation of any actions to be performed in the primary reference.
Thus, the simple substitution of one known element for another producing a predictable result renders the claim obvious.
It is noted that the process for determining recommendations would be the same whether based on compared events or compared objects. This process would be performed in the same manner within the combined invention of the prior art reference (whether comparing events, objects, or both) and Applicant’s claims do not provide any differentiation between how the process for comparing events for making recommendations is performed and how the process for comparing objects for making recommendations is performed.
Verdejo/Liu discloses the above method/system for comparing current crime scenes to historic crime events. Additionally, Verdejo teaches device data including manner of use (see at least [0014]; [0045], audio recording, video recording, image capture, etc. as evidenced by the type of media collected), receiving the IoT device logs from the network interface (as described above), and comparing logs with historical logs to identify similarities (as described above). Verdejo/Liu does not explicitly use of a triggering time sequence and a triggering time duration of the IoT devices disclose, but Yeoh teaches:
receive, within a range of the incident time and based on detection of the particular crime being a specified crime type via an IoT control app, the IoT device logs from the network interface; ([0045], the data used to identify IoT device data to collect (log data includes data collected by the IoT device, operating state of the IoT device, etc.), includes incident type and time periods; [0037], “In another embodiment, the electronic computing device may broadcast a probe signal to request IoT devices 130 connected to a particular wireless router to respond with its identifier.”, identifier is used to collect additional information (including log data), indicating that the computing device includes IoT control software (it is noted that “IoT control app” is merely a label for the app and the app in Verdejo performs the same functions as described in the claims))
compare the events that happened at the crime scene according to IoT operating states logged by the IoT devices via the IoT device logs with events that were [also identified in past event data] in order to identify a triggering time sequence and triggering time duration of the IoT devices; ([0036]; [0037], uses information from previously mentioned data (conversations with law enforcement etc., this previously mentioned data would be used in the same manner as the trial data in Verdejo/Liu for the purposes of identifying time triggers, regardless of how it is acquired (previous trials, conversations, etc.), statements made by witnesses or other parties are a type of evidence, ; [0019]; 0039]; [0040], the operating states of IoT devices are collected in the historical (log) data, including signal strength as affected by movement of object and/or IoT position, this fluctuating of signal strength is used to indicate that the IoT device observed activity related to evidence (“…a change in the spatial position of the IoT device 130 may affect the signal strength corresponding to the signal received by the IoT device 130 from a wireless router and this in turn may affect the RSSI value captured at the IoT device 130. The signal strength may either drop or increase depending at least on the physical positions of the IoT device 130 and the wireless router and associated environmental factors. Similarly, when an object (e.g., a person) passes by the IoT device or moves back and forth relative to a position of the IoT device 130, a signal strength corresponding to a signal received by the IoT device 130 from the wireless may either drop or increase depending at least on the physical positions of the IoT device 130, the object, and the wireless router.”), identifies data (images, etc.) captured by the IoT devices during an identified time period, including when the data was collected and the duration of the strength fluctuation (the duration of the strength fluctuation indicates how long the IoT device was effected by position of object movement (device operating state), indicating a triggering time duration of the device operating state (time period in which the device was triggered); [0044], a pattern of an object movement (evidence) is created based on data collected from the multiple IoTs and related to different locations/areas and timestamps, one of ordinary skill in the art would recognize that in order to determine the pattern of movement, it would involve ordering the events (locations/movements of the object), therefore the data would be arranged in order based on the times and fluctuations in signal strengths (triggering as described above) indicating a time sequence in which the devices are triggered)
identify a triggering time sequence and triggering time duration of the IoT devices based on IoT operating states logged by the IoT devices via the IoT device logs; ([0036]; [0037]; [0039]; [0040]; [0044], as described above, the operating states of the IoT devices are recorded and compared to previously collected evidence data. The pre-collected evidence data includes timeframes and locations. This timeframe and location data is used to determine IoT devices that were present and to determine the times and durations for which the IoT devices were triggered (using signal strength fluctuations). The determination of the movement pattern of objects indicates that the IoT device data is also analyzed in a sequential manner (such as the order and duration in which each device is recording to determine the movement pattern of the object)
determine that the triggering time sequence and the triggering time duration of the IoT devices comprises an order and time of use of each of the IoT devices that was accessed relative to the crime scene; ([0036]; [0037]; [0039]; [0040]; [0044], as described above, the operating states of the IoT devices are recorded and compared to previously collected evidence data. The pre-collected evidence data includes timeframes and locations. This timeframe and location data is used to determine IoT devices that were present and to determine the times and durations for which the IoT devices were triggered (using signal strength fluctuations). The determination of the movement pattern of objects indicates that the IoT device data is also analyzed in a sequential manner (such as the order and duration in which each device is recording to determine the movement pattern of the object).
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of Verdejo/Liu so as to have included receive, within a range of the incident time and based on detection of the particular crime being a specified crime type via an IoT control app, the IoT device logs from the network interface; compare the events that happened at the crime scene according to IoT operating states logged by the IoT devices via the IoT device logs with events that were [also identified in past event data] in order to identify a triggering time sequence and triggering time duration of the IoT devices; identify a triggering time sequence and triggering time duration of the IoT devices based on IoT operating states logged by the IoT devices via the IoT device logs; and determine that the triggering time sequence and the triggering time duration of the IoT devices comprises an order and time of use of each of the IoT devices that was accessed relative to the crime scene, as taught by Yeoh in order to ensure that relevant evidence is collected and no important evidence is missed (Yeoh, [0002]; Liu, Abstract; page 1, line 21-page 2, line 4; page 2, lines 35-39; page 3, lines 32-51, etc.).
Verdejo/Liu/Yeoh discloses the above method/system for comparing current crime scenes to historic crime events. As shown above, Verdejo includes matching events and items/objects to events and items in the records of the historic crime events and scoring items/evidence based on the correlations (including objects). Additionally, Liu teaches applying a statistical algorithm to determine probability and correlation degree of types of evidence items (page 3, lines 22-27, probability and correlation degrees are determined for evidence types/items to be used for recommendation of evidence to collect, high correlation degrees and thresholds can indicate importance of evidence for generating recommendations (it is noted that Verdejo also uses thresholds for scoring the correlations between past and current evidence, see Verdejo, [0083])). Verdejo/Liu/Yeoh does not explicitly disclose that recommended items/objects are based on a highest weighted importance score, however Wu teaches:
identify, based on a comparison of the list of objects with objects within the images, particular evidence having a highest weighted importance score; (page 4, lines 4-29, each piece of evidence is scored based on weights for the evidence, the weights based on importance of the evidence to outcomes of legal procedures)
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of Verdejo/Liu/Yeoh so as to have included use of a highest weighted importance score, as taught by Wu in order to ensure that the most pertinent and useful evidence is collected (Wu, page 4, lines 18-21; Liu, page 3, lines 32-40).
The combination of references disclose the ability to determine recommendations for actions to perform (including identifying objects to collect) based on correlations scores and the ability to determine the weighted importance of evidence items, as shown above. One of ordinary skill in the art would understand how to apply the importance weights used in the scoring method of Wu to the correlation scores in Verdejo/Liu to identify a highest weighted importance score, as it would involve merely identifying the highest score among the various scores, and the references demonstrate the required skill to do so. Therefore, the combination of Verdejo, Liu, Yeoh, and Wu demonstrate the ability to provide a recommendation to a user to search for a particular based on the highest weighted importance score, as outlined in the above rejection.
Claim(s) 3, 8, and 12 is/are rejected under 35 U.S.C. 103 as being unpatentable over Verdejo in view of Liu in further view of Yeoh in further view of Wu in further view of Lim et al. (Pub. No. US 2018/0182170 A1).
In regards to Claims 3, 8, and 12, Verdejo/Liu/Yeoh/Wu discloses wherein the recommendation comprises a recommendation to search for evidence of events that were mentioned in the evidence used in the past prosecutions, as described above in the rejections of the parent claims. The method/system Verdejo/Liu/Yeoh/Wu described above compares crime scene data to past prosecution data in order to make recommendations for evidence, including Liu’s calculations of correlation degree, proportion/ration value, number of each kind of evidence used etc. in order to determine what evidence is the most relevant and/or useful, as described above. Verdejo/Liu/Wu does not explicitly disclose, but Lim teaches:
wherein the recommendation comprises a recommendation to search for evidence [that was] not mentioned in the events that happened at the crime scene ([0003]; [0051] and related table, the search plan for evidence searching can be updated based on “no expected evidence found” and can be related to a case type, expected evidence is comparable to the relevant evidence calculated and recommended in Liu (the most relevant evidence for a case type would represent evidence expected to be found/collected at crime scenes for that case type), an expected evidence type not found at a crime scene would be comparable to “not being mentioned”, for example evidence not identified/recovered from a crime scene would not be mentioned in a crime scene report (or incident report or other related type of report), “Auto enlarge search area & recalculate & auto assign to each user-investigator when not enough evidence/no expected evidence found. Search pattern thoroughness based on crime type & expected evidence size…”)
It would have been obvious to one of ordinary skill in the art, before the effective filing date of the claimed invention, to have modified the system of system of Verdejo/Liu/Yeoh/Wu so as to have included wherein the recommendation comprises a recommendation to search for evidence [that was] not mentioned in the events that happened at the crime scene, as taught by Lim in order to ensure that relevant evidence is collected and handled properly to avoid any potential issues that would delay or interrupt prosecution (Lim, [0051] and related table; Liu, Abstract; page 1, line 21-page 2, line 4; page 2, lines 35-39; page 3, lines 32-51, etc.).
Additional Prior Art Identified, but not Relied Upon
Bell (WO 2009007703 A2). Discloses weighting evidence based on importance (see at least page 8, line 29-page 9, line 28)
Hodge (Pub. No. US 2019/0114472 A1). Discloses the capture of crime scene evidence and comparisons to previous investigations (see at least [0051]; [0053])
Montisci (Pub. No. US 2021/0241924 A1). Discloses the comparison of crime scene events to historical data for similar events (see at least [0067]; Claim 5, including a suicide and open window example similar to the example provide in Applicant’s specification at [012] and [013])
Seaman et al. (Pub. No. US 2007/0112713 A1). Discloses the linking of criminal cases based on similarity (see at least [0029]; [0030]-[0032])
Touma et al. (AU 2013201326 A1). Discloses a system for validating incident reports related to crime scenes, the incident reports including evidence reports (see at least [003]; [004]; [007]; 021]; [042]; [052]; [056]; [065]; [066]; Claim 1)
Response to Arguments
Applicant’s arguments filed 7/8/2026 have been fully considered but they are not persuasive.
I. Rejection of Claims under 35 U.S.C. §101:
Step 2A, Prong 1: Applicant argues that the claimed invention improve the functioning of a camera as an improvement to the technological field of video camera based criminal investigations and that the claimed invention integrate the alleged abstract idea into a practical application, however, Applicant fails to provide evidence to demonstrate how/why the claims would provide the alleged technological improvement or identify the alleged practical application. It is not clear how the functioning of a camera is improved as it merely captures and transmits data. It is not clear how the claimed invention “controls the release of IoT Device logs” in an improved manner. The claims merely receive logs based on certain criteria, but provide no significant technical detail regarding how this would be performed in a significant manner or provide an improvement/practical application.
The claims are directed to analyzing a crime scene to determine what evidence should be collected (including the most relevant and important based on historical data). This represents the organizing of human behavior. Humans perform the activities of analyzing crime scenes and determining what evidence to collect. This can include understanding of what evidence would be more pertinent or important based on previous crimes and prosecution outcomes. This expertise in understanding important evidence can come from research or training on the part of the investigators. The claimed invention performs collecting, recording, or otherwise managing data corresponding to this behavior. The claimed invention merely automates this process of and expertise performed by humans (behaviors). There is no indication that the collection and organizing of this evidence is improved in any particular manner. The specification merely asserts that this would be beneficial, but does not provide sufficient evidence to demonstrate how these benefits are achieved in a meaningful manner (improvement, practical application, etc.)
Step 2A, Prong 2: Applicant again argues that the claimed invention provides an improvement to the technology, field of art, and provides a practical application. However, Applicant merely provides a discussion of what the claim does and asserts that it provides the alleged improvements. Applicant does not provide clear evidence or support to demonstrate how/why the alleged improvements would be achieved in a manner that is significantly more than the identified abstract ideas. Applicant merely cites claim steps and intended benefits (including in the cited specification sections).
Applicant argues that the claimed invention improves the evidentiary video analytic capability of such video cameras, however, the video cameras in the claims are not performing such analytics and merely provide images. It is not clear how the cameras/devices or camera/device functionality would be improved in a manner that is significantly more than the abstract ideas. For example, Applicant asserts that IoT devices are improved via controlled release of logs, including operating state data, and that these provide for better identification of similar IoT logs. However, this merely discusses what the IoT devices do (release logs, i.e. transmit the data) or the type of data in the logs (operating state data), but does not demonstrate how the device is improved. Merely controlling the device or using particular data does not improve the device. Additionally, the camera (nor other IoT devices) does not generate video analytics of recommendation, it only captures and transmits data.
Step 2B: Applicant does not clearly identify or explain how the alleged additional elements provide a more efficient mechanism for identifying high weighted evidence. The claims merely identify the highest weighted evidence based on a number of times it is mentioned during a trial (as recited in dependent claims). The claims do not tie this to the additional claim elements in a significant technical manner. For example, a user could simply look at how many times it was mentioned in a transcript. The processes in the claims do not indicate how a weight or importance score are determined (independent claims) or how a count of mentions is determined using the log comparisons (in some depending claims). The log identification and comparisons are only used to identify evidence that was mentioned, not any weighting criteria or importance score.
It is also noted that well-understood, routine, conventional activity rationales are not currently applied in the above rejections and that Applicant has not provided evidence to demonstrate that the claim elements, alone or in combination, are not well-understood, routine, conventional activity.
See MPEP 2106.05(a), Improvements to the Functioning of a Computer or To Any Other Technology or Technical Field (“If it is asserted that the invention improves upon conventional functioning of a computer, or upon conventional technology or technological processes, a technical explanation as to how to implement the invention should be present in the specification. That is, the disclosure must provide sufficient details such that one of ordinary skill in the art would recognize the claimed invention as providing an improvement. The specification need not explicitly set forth the improvement, but it must describe the invention such that the improvement would be apparent to one of ordinary skill in the art. Conversely, if the specification explicitly sets forth an improvement but in a conclusory manner (i.e., a bare assertion of an improvement without the detail necessary to be apparent to a person of ordinary skill in the art), the examiner should not determine the claim improves technology.”).
II. Rejection of Claims under 35 U.S.C. §103:
Applicant’s arguments with respect to Claim(s) 1-15 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.
Applicant's arguments fail to comply with 37 CFR 1.111(b) because they amount to a general allegation that the claims define a patentable invention without specifically pointing out how the language of the claims patentably distinguishes them from the references.
In response to applicant's arguments against the references individually, one cannot show nonobviousness by attacking references individually where the rejections are based on combinations of references. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981); In re Merck & Co., 800 F.2d 1091, 231 USPQ 375 (Fed. Cir. 1986).
Conclusion
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/S.D.S/July 25, 2026
/LYNDA JASMIN/Supervisory Patent Examiner, Art Unit 3629
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