DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Response to Arguments
Applicant's arguments filed 06 October 2025 have been fully considered but they are not persuasive.
The Applicant argues that Stanley does not teach the device including a geotracking software, such that the entity that is located closest to the coordinate location having the critical threat level is alerted to eliminate the critical threat. The Examiner respectfully disagrees. Stanley discloses determining a category of vegetation danger and each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using specialist equipment, to using normal (non-insulated) tools without any need to work in the vicinity of the conductor. It is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/ network operators prior to a physical site inspection. This would reduce the time to complete the remedial action and the associated cost of Customer Minutes Lost (CML – a measurement related to the number of people affected by an outage and the duration of that outage) (paragraph [0087]). Furthermore, Stanley discloses that typically, a ‘network operator’ is responsible for any outages resulting from such damage, these entities often employ contractors to monitor a particular stretch of conductor and pruning or removal of vegetation as necessary (paragraph [0003]). The invention of Stanley allows the utility conductors to be able to be monitored via a drone, those images are then analyzed for any vegetation that may be encroaching onto the conductors, and the system will categorize that risk in a statement of work, which is then sent to the most appropriate personnel for remedial action (paragraph [0109]). The contractors carry a device containing a GPS which allows the network operators to know their whereabouts and be able to update the work orders once completed (paragraphs [0021] and [0121]). When the most appropriate personnel are selected, one would select the best and closest contractor (most appropriate personnel) available to complete the work to ensure the work will be done in a timely manner. Therefore, Stanley broadly meets the claimed limitations and the rejection is maintained.
Claim Rejections - 35 USC § 102
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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 1-9 and 11-19 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Stanley (U.S. Patent Application Publication 2017/0277953).
Regarding claim 1, Stanley discloses a method for determining a threat level for vegetation overgrowth comprising: receiving geographic data and a first LIDAR imagery data of a coordinate location from a satellite (Figs. 2 and 7; paragraph [0089] – data relating to the conductors and neighboring vegetation is determined at least in part from LiDAR data at step 202, for example taken from an aircraft flying over the conductor – alternatively, or additionally, this data may be determined from satellite LiDAR data; paragraph [0091] – in use LiDAR data is collected as described above, preferably augmented with aerial images and/or GPS data so that the LiDAR data can be overlayed onto a map (for example, Google Maps and/or the network operator’s existing mapping system) – in one example, an aircraft flies directly over the path of a conductor, collecting information regarding the conductor and its immediate vicinity); storing the geographic data and the first LIDAR imagery data of the coordinate location in a database installed on a server coupled to a network (Figs. 2 and 7; paragraph [0036] – there is provided a system for categorizing vegetation at risk as potential impact vegetation, the system comprising: a server comprising a central memory (optionally in a form of a database) containing data related to a target object and neighboring vegetation; a mobile device operable to record data relating to said target object and/or vegetation; wherein the server is operable to receive said data from said mobile device so as to categorize said vegetation in said memory – by categorizing the vegetation in the memory based on data relating to said target object and/or vegetation from the mobile device, an accurate and up-to-date model of the vegetation and/or target object can be provided; paragraph [0089] – data relating to the conductors and neighboring vegetation is determined at least in part from LiDAR data at step 202, for example taken from an aircraft flying over the conductor – alternatively, or additionally, this data may be determined from satellite LiDAR data; paragraph [0091] – in use LiDAR data is collected as described above, preferably augmented with aerial images and/or GPS data so that the LiDAR data can be overlayed onto a map (for example, Google Maps and/or the network operator’s existing mapping system) – in one example, an aircraft flies directly over the path of a conductor, collecting information regarding the conductor and its immediate vicinity); assigning a first threat level to the first LIDAR imagery data (Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category); receiving the geographic data and a second LIDAR imagery data from the coordinate location from the satellite (Figs. 2 and 7; paragraph [0089] – data relating to the conductors and neighboring vegetation is determined at least in part from LiDAR data at step 202, for example taken from an aircraft flying over the conductor – alternatively, or additionally, this data may be determined from satellite LiDAR data; paragraph [0091] – in use LiDAR data is collected as described above, preferably augmented with aerial images and/or GPS data so that the LiDAR data can be overlayed onto a map (for example, Google Maps and/or the network operator’s existing mapping system) – in one example, an aircraft flies directly over the path of a conductor, collecting information regarding the conductor and its immediate vicinity; paragraph [0111] – Figs. 5(c) and 5(d) show an example map overlayed with polygons similar to Fig. 5(a), this particular stretch having been scanned twice, each scan temporally separated by approximately one year (2013, and 2014) – the two sets of data can be compared so as to determine the growth rate of the vegetation in that area (accounting for vegetation that has been cut – this information would be stored by the system) – various indicators of the growth rate are shown as attributes 518 in Fig. 5(c) – once the growth rate has been determined for a particular element of vegetation, it is then possible to extrapolate into the future so as to determine when a particular element of vegetation may interfere with a conductor; paragraph [0116] – it will be appreciated that more than two scans of the same area could be used to improve the accuracy of the growth model, and that the scans may be temporally separated by more or less than one year, for example by one or two growing seasons, preferably by at least one growing season – furthermore, data from similar vegetation (for example, those experiencing a similar climate) may be applied to other vegetation so as to provide an indication of future growth); storing the geographic data and the second LIDAR imagery data of the coordinate location in the database (Figs. 2 and 7; paragraph [0036] – there is provided a system for categorizing vegetation at risk as potential impact vegetation, the system comprising: a server comprising a central memory (optionally in a form of a database) containing data related to a target object and neighboring vegetation; a mobile device operable to record data relating to said target object and/or vegetation; wherein the server is operable to receive said data from said mobile device so as to categorize said vegetation in said memory – by categorizing the vegetation in the memory based on data relating to said target object and/or vegetation from the mobile device, an accurate and up-to-date model of the vegetation and/or target object can be provided; paragraph [0089] – data relating to the conductors and neighboring vegetation is determined at least in part from LiDAR data at step 202, for example taken from an aircraft flying over the conductor – alternatively, or additionally, this data may be determined from satellite LiDAR data; paragraph [0091] – in use LiDAR data is collected as described above, preferably augmented with aerial images and/or GPS data so that the LiDAR data can be overlayed onto a map (for example, Google Maps and/or the network operator’s existing mapping system) – in one example, an aircraft flies directly over the path of a conductor, collecting information regarding the conductor and its immediate vicinity); assigning a second threat level to the second LIDAR imagery data (Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category); determining a critical threat level from the first LIDAR imagery data and the second LIDAR imagery data (Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category); alerting a device coupled to the network of the critical threat level, the device being owned by an entity (Figs. 2, 6, 7, 13, and 14; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0011] – the assigning of a remedial action may comprise outputting a statement of suggested remedial action based on said data relating to said target vegetation – outputting a statement of suggested remedial action allows for more efficient management of the vegetation – the statement of suggested remedial action may comprise a recommendation of resource allocation for completing the said remedial action – the resources may comprise at least one of: personnel, equipment, and time; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0109] – based on this information, a statement of work may be sent to a contractor assigning remedial action (step 212), detailing what needs to be done to the vegetation corresponding to that particular polygon – such statements of work may be generated automatically by the system or manually by an operator; paragraph [0143] – Fig. 14 shows a screen shot/print out of the work instructions that are supplied to a contractor), and wherein the device includes a geotracking software, such that the entity that is located closest to the coordinate location having the critical threat level is alerted to eliminate the threat (Stanley: Figs. 2, 6, 7, 13, and 14; paragraph [0003] – typically, a ‘network operator’ is responsible for any outages resulting from such damage; these entities often employ contractors to monitor a particular stretch of conductor and pruning or removal of vegetation as necessary; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0011] – the assigning of a remedial action may comprise outputting a statement of suggested remedial action based on said data relating to said target vegetation – outputting a statement of suggested remedial action allows for more efficient management of the vegetation – the statement of suggested remedial action may comprise a recommendation of resource allocation for completing the said remedial action – the resources may comprise at least one of: personnel, equipment, and time; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0109] – based on this information, a statement of work may be sent to a contractor assigning remedial action (step 212), detailing what needs to be done to the vegetation corresponding to that particular polygon – such statements of work may be generated automatically by the system or manually by an operator; paragraph [0118] – the contractor is supplied with a mobile device 600 – GPS 610; paragraph [0121] – using the mobile device 600, a contractor images vegetation that has undergone remedial work (record new vegetation data, step 216) – the GPS unit 610 and accelerometer 608 determine the position and orientation respectively of the device 608; this information (potentially together with a distance measurement to the target vegetation) means that the target vegetation can be accurately identified on the central vegetation database (memory) formed of LiDAR data; paragraph [0143] – Fig. 14 shows a screen shot/print out of the work instructions that are supplied to a contractor; once the work order is received, the contractor can head to the location to perform the work required); dispatching the entity to the coordinate location to eliminate the threat (Figs. 2, 6, 7, 13, and 14; paragraph [0003] – typically, a ‘network operator’ is responsible for any outages resulting from such damage; these entities often employ contractors to monitor a particular stretch of conductor and pruning or removal of vegetation as necessary; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0011] – the assigning of a remedial action may comprise outputting a statement of suggested remedial action based on said data relating to said target vegetation – outputting a statement of suggested remedial action allows for more efficient management of the vegetation – the statement of suggested remedial action may comprise a recommendation of resource allocation for completing the said remedial action – the resources may comprise at least one of: personnel, equipment, and time; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0109] – based on this information, a statement of work may be sent to a contractor assigning remedial action (step 212), detailing what needs to be done to the vegetation corresponding to that particular polygon – such statements of work may be generated automatically by the system or manually by an operator; paragraph [0118] – the contractor is supplied with a mobile device 600; paragraph [0143] – Fig. 14 shows a screen shot/print out of the work instructions that are supplied to a contractor; once the work order is received, the contractor can head to the location to perform the work required).
Regarding claim 2, Stanley discloses all of the limitations as previously discussed with respect to claim 1 including that wherein the geographic data further includes a utility distribution network (Stanley: Figs. 2, 5(a)-5(h), and 7; paragraph [0089] – data relating to the conductors and neighboring vegetation is determined at least in part from LiDAR data at step 202, for example taken from an aircraft flying over the conductor – alternatively, or additionally, this data may be determined from satellite LiDAR data; paragraph [0091] – in use LiDAR data is collected as described above, preferably augmented with aerial images and/or GPS data so that the LiDAR data can be overlayed onto a map (for example, Google Maps and/or the network operator’s existing mapping system) – in one example, an aircraft flies directly over the path of a conductor, collecting information regarding the conductor and its immediate vicinity).
Regarding claim 3, Stanley discloses all of the limitations as previously discussed with respect to claims 1 and 2 including that wherein an electrical current flowing through the utility distribution network is insulated when the critical threat level is determined (Stanley: paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection).
Regarding claim 4, Stanley discloses all of the limitations as previously discussed with respect to claims 1 and 2 including that wherein the first threat level is a measurement of a vegetation in relation to the utility distribution network (Stanley: Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category).
Regarding claim 5, Stanley discloses all of the limitations as previously discussed with respect to claims 1-3 including that wherein the second threat level is a measurement of the vegetation in relation to the utility distribution network (Stanley: Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category).
Regarding claim 6, Stanley discloses all of the limitations as previously discussed with respect to claim 1, 2, and 4 including that wherein the critical threat level is a change in measurement between the first threat level and the second threat level in relation to the utility distribution network (Stanley: Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category).
Regarding claim 7, Stanley discloses all of the limitations as previously discussed with respect to claim 1 including that wherein the critical threat level is determined by a processor installed on the server (Stanley: Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0036] – server – wherein the server is operable to receive said data from said mobile device so as to categorize said vegetation in said memory – by categorizing the vegetation in the memory based on data relating to said target object and/or vegetation from the mobile device, an accurate and up-to-date model of the vegetation and/or target object can be provided; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category).
Regarding claim 8, Stanley discloses all of the limitations as previously discussed with respect to claim 1 including that wherein the entity is a utility line worker (Stanley: Figs. 2, 6, 7, 13, and 14; paragraph [0003] – typically, a ‘network operator’ is responsible for any outages resulting from such damage; these entities often employ contractors to monitor a particular stretch of conductor and pruning or removal of vegetation as necessary; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0011] – the assigning of a remedial action may comprise outputting a statement of suggested remedial action based on said data relating to said target vegetation – outputting a statement of suggested remedial action allows for more efficient management of the vegetation – the statement of suggested remedial action may comprise a recommendation of resource allocation for completing the said remedial action – the resources may comprise at least one of: personnel, equipment, and time; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0109] – based on this information, a statement of work may be sent to a contractor assigning remedial action (step 212), detailing what needs to be done to the vegetation corresponding to that particular polygon – such statements of work may be generated automatically by the system or manually by an operator; paragraph [0118] – the contractor is supplied with a mobile device 600; paragraph [0143] – Fig. 14 shows a screen shot/print out of the work instructions that are supplied to a contractor; once the work order is received, the contractor can head to the location to perform the work required).
Regarding claim 9, Stanley discloses all of the limitations as previously discussed with respect to claim 1 including that wherein the entity is a utility distribution and power organization (Stanley: Figs. 2, 6, 7, 13, and 14; paragraph [0003] – typically, a ‘network operator’ is responsible for any outages resulting from such damage; these entities often employ contractors to monitor a particular stretch of conductor and pruning or removal of vegetation as necessary; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0011] – the assigning of a remedial action may comprise outputting a statement of suggested remedial action based on said data relating to said target vegetation – outputting a statement of suggested remedial action allows for more efficient management of the vegetation – the statement of suggested remedial action may comprise a recommendation of resource allocation for completing the said remedial action – the resources may comprise at least one of: personnel, equipment, and time; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0109] – based on this information, a statement of work may be sent to a contractor assigning remedial action (step 212), detailing what needs to be done to the vegetation corresponding to that particular polygon – such statements of work may be generated automatically by the system or manually by an operator; paragraph [0118] – the contractor is supplied with a mobile device 600; paragraph [0143] – Fig. 14 shows a screen shot/print out of the work instructions that are supplied to a contractor; once the work order is received, the contractor can head to the location to perform the work required).
Regarding claim 11, Stanley discloses a non-transitory computer-readable medium on which is recorded a computer program, the program comprising executable instructions, that when executed, perform a method for determining a threat level for vegetation overgrowth comprising: receiving geographic data and a first LIDAR imagery data of a coordinate location from a satellite (Figs. 2 and 7; paragraph [0089] – data relating to the conductors and neighboring vegetation is determined at least in part from LiDAR data at step 202, for example taken from an aircraft flying over the conductor – alternatively, or additionally, this data may be determined from satellite LiDAR data; paragraph [0091] – in use LiDAR data is collected as described above, preferably augmented with aerial images and/or GPS data so that the LiDAR data can be overlayed onto a map (for example, Google Maps and/or the network operator’s existing mapping system) – in one example, an aircraft flies directly over the path of a conductor, collecting information regarding the conductor and its immediate vicinity); storing the geographic data and the first LIDAR imagery data of the coordinate location in a database installed on server coupled to a network (Figs. 2 and 7; paragraph [0036] – there is provided a system for categorizing vegetation at risk as potential impact vegetation, the system comprising: a server comprising a central memory (optionally in a form of a database) containing data related to a target object and neighboring vegetation; a mobile device operable to record data relating to said target object and/or vegetation; wherein the server is operable to receive said data from said mobile device so as to categorize said vegetation in said memory – by categorizing the vegetation in the memory based on data relating to said target object and/or vegetation from the mobile device, an accurate and up-to-date model of the vegetation and/or target object can be provided; paragraph [0089] – data relating to the conductors and neighboring vegetation is determined at least in part from LiDAR data at step 202, for example taken from an aircraft flying over the conductor – alternatively, or additionally, this data may be determined from satellite LiDAR data; paragraph [0091] – in use LiDAR data is collected as described above, preferably augmented with aerial images and/or GPS data so that the LiDAR data can be overlayed onto a map (for example, Google Maps and/or the network operator’s existing mapping system) – in one example, an aircraft flies directly over the path of a conductor, collecting information regarding the conductor and its immediate vicinity); assigning a first threat level to the first LIDAR imagery data by a processor installed on the server (Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category); receiving the geographic data and a second LIDAR imagery data from the coordinate location from the satellite (Figs. 2 and 7; paragraph [0089] – data relating to the conductors and neighboring vegetation is determined at least in part from LiDAR data at step 202, for example taken from an aircraft flying over the conductor – alternatively, or additionally, this data may be determined from satellite LiDAR data; paragraph [0091] – in use LiDAR data is collected as described above, preferably augmented with aerial images and/or GPS data so that the LiDAR data can be overlayed onto a map (for example, Google Maps and/or the network operator’s existing mapping system) – in one example, an aircraft flies directly over the path of a conductor, collecting information regarding the conductor and its immediate vicinity; paragraph [0111] – Figs. 5(c) and 5(d) show an example map overlayed with polygons similar to Fig. 5(a), this particular stretch having been scanned twice, each scan temporally separated by approximately one year (2013, and 2014) – the two sets of data can be compared so as to determine the growth rate of the vegetation in that area (accounting for vegetation that has been cut – this information would be stored by the system) – various indicators of the growth rate are shown as attributes 518 in Fig. 5(c) – once the growth rate has been determined for a particular element of vegetation, it is then possible to extrapolate into the future so as to determine when a particular element of vegetation may interfere with a conductor; paragraph [0116] – it will be appreciated that more than two scans of the same area could be used to improve the accuracy of the growth model, and that the scans may be temporally separated by more or less than one year, for example by one or two growing seasons, preferably by at least one growing season – furthermore, data from similar vegetation (for example, those experiencing a similar climate) may be applied to other vegetation so as to provide an indication of future growth); storing the geographic data and the second LIDAR imagery data of the coordinate location in the database (Figs. 2 and 7; paragraph [0036] – there is provided a system for categorizing vegetation at risk as potential impact vegetation, the system comprising: a server comprising a central memory (optionally in a form of a database) containing data related to a target object and neighboring vegetation; a mobile device operable to record data relating to said target object and/or vegetation; wherein the server is operable to receive said data from said mobile device so as to categorize said vegetation in said memory – by categorizing the vegetation in the memory based on data relating to said target object and/or vegetation from the mobile device, an accurate and up-to-date model of the vegetation and/or target object can be provided; paragraph [0089] – data relating to the conductors and neighboring vegetation is determined at least in part from LiDAR data at step 202, for example taken from an aircraft flying over the conductor – alternatively, or additionally, this data may be determined from satellite LiDAR data; paragraph [0091] – in use LiDAR data is collected as described above, preferably augmented with aerial images and/or GPS data so that the LiDAR data can be overlayed onto a map (for example, Google Maps and/or the network operator’s existing mapping system) – in one example, an aircraft flies directly over the path of a conductor, collecting information regarding the conductor and its immediate vicinity); assigning a second threat level to the second LIDAR imagery data by the processor (Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category); determining a critical threat level from the first LIDAR imagery data and the second LIDAR imagery data by the processor (Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category); alerting a device coupled to the network of the critical threat level, the device being owned by an entity (Figs. 2, 6, 7, 13, and 14; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0011] – the assigning of a remedial action may comprise outputting a statement of suggested remedial action based on said data relating to said target vegetation – outputting a statement of suggested remedial action allows for more efficient management of the vegetation – the statement of suggested remedial action may comprise a recommendation of resource allocation for completing the said remedial action – the resources may comprise at least one of: personnel, equipment, and time; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0109] – based on this information, a statement of work may be sent to a contractor assigning remedial action (step 212), detailing what needs to be done to the vegetation corresponding to that particular polygon – such statements of work may be generated automatically by the system or manually by an operator; paragraph [0143] – Fig. 14 shows a screen shot/print out of the work instructions that are supplied to a contractor), and wherein the device includes a geotracking software, such that the entity that is located closest to the coordinate location is alerted to eliminate the critical threat (Stanley: Figs. 2, 6, 7, 13, and 14; paragraph [0003] – typically, a ‘network operator’ is responsible for any outages resulting from such damage; these entities often employ contractors to monitor a particular stretch of conductor and pruning or removal of vegetation as necessary; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0011] – the assigning of a remedial action may comprise outputting a statement of suggested remedial action based on said data relating to said target vegetation – outputting a statement of suggested remedial action allows for more efficient management of the vegetation – the statement of suggested remedial action may comprise a recommendation of resource allocation for completing the said remedial action – the resources may comprise at least one of: personnel, equipment, and time; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0109] – based on this information, a statement of work may be sent to a contractor assigning remedial action (step 212), detailing what needs to be done to the vegetation corresponding to that particular polygon – such statements of work may be generated automatically by the system or manually by an operator; paragraph [0118] – the contractor is supplied with a mobile device 600 – GPS 610; paragraph [0121] – using the mobile device 600, a contractor images vegetation that has undergone remedial work (record new vegetation data, step 216) – the GPS unit 610 and accelerometer 608 determine the position and orientation respectively of the device 608; this information (potentially together with a distance measurement to the target vegetation) means that the target vegetation can be accurately identified on the central vegetation database (memory) formed of LiDAR data; paragraph [0143] – Fig. 14 shows a screen shot/print out of the work instructions that are supplied to a contractor; once the work order is received, the contractor can head to the location to perform the work required); dispatching the entity to the coordinate location to eliminate the threat by the processor (Figs. 2, 6, 7, 13, and 14; paragraph [0003] – typically, a ‘network operator’ is responsible for any outages resulting from such damage; these entities often employ contractors to monitor a particular stretch of conductor and pruning or removal of vegetation as necessary; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0011] – the assigning of a remedial action may comprise outputting a statement of suggested remedial action based on said data relating to said target vegetation – outputting a statement of suggested remedial action allows for more efficient management of the vegetation – the statement of suggested remedial action may comprise a recommendation of resource allocation for completing the said remedial action – the resources may comprise at least one of: personnel, equipment, and time; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0109] – based on this information, a statement of work may be sent to a contractor assigning remedial action (step 212), detailing what needs to be done to the vegetation corresponding to that particular polygon – such statements of work may be generated automatically by the system or manually by an operator; paragraph [0118] – the contractor is supplied with a mobile device 600; paragraph [0143] – Fig. 14 shows a screen shot/print out of the work instructions that are supplied to a contractor; once the work order is received, the contractor can head to the location to perform the work required).
Regarding claim 12, Stanley discloses all of the limitations as previously discussed with respect to claim 11 including that wherein the geographic data further includes a utility distribution network (Stanley: Figs. 2, 5(a)-5(h), and 7; paragraph [0089] – data relating to the conductors and neighboring vegetation is determined at least in part from LiDAR data at step 202, for example taken from an aircraft flying over the conductor – alternatively, or additionally, this data may be determined from satellite LiDAR data; paragraph [0091] – in use LiDAR data is collected as described above, preferably augmented with aerial images and/or GPS data so that the LiDAR data can be overlayed onto a map (for example, Google Maps and/or the network operator’s existing mapping system) – in one example, an aircraft flies directly over the path of a conductor, collecting information regarding the conductor and its immediate vicinity).
Regarding claim 13, Stanley discloses all of the limitations as previously discussed with respect to claim 11 including that wherein an electrical current flowing through the utility distribution network is insulated when the critical threat level is determined (Stanley: paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection).
Regarding claim 14, Stanley discloses all of the limitations as previously discussed with respect to claim 11 and 12 including that wherein the first threat level is a measurement of a vegetation in relation to the utility distribution network (Stanley: Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category).
Regarding claim 15, Stanley discloses all of the limitations as previously discussed with respect to claims 11 and 13 including that wherein the second threat level is a measurement of the vegetation in relation to the utility distribution network (Stanley: Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category).
Regarding claim 16, Stanley discloses all of the limitations as previously discussed with respect to claims 11 and 14 including that wherein the critical threat level is a change in measurement between the first threat level and the second threat level in relation to the utility distribution network (Stanley: Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category).
Regarding claim 17, Stanley discloses all of the limitations as previously discussed with respect to claim 11 including that wherein the critical threat level is determined by a processor installed on the server (Stanley: Figs. 1-3; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0009] – the method may comprise determining an updated risk category for said vegetation in dependence on said ground observation; and updating said memory with said risk category – by updating said risk category, an accurate and up-to-date record of the state of the vegetation is afforded; paragraph [0014] – the risk category may correspond to a set of regulations – in one example, four categories of risk are provided, each corresponding to a different level or type of risk posed by the vegetation – a greater or lower number of categories may be provided, for example two categories corresponding to no risk (or negligent risk) and some risk; paragraph [0036] – server – wherein the server is operable to receive said data from said mobile device so as to categorize said vegetation in said memory – by categorizing the vegetation in the memory based on data relating to said target object and/or vegetation from the mobile device, an accurate and up-to-date model of the vegetation and/or target object can be provided; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0094] – the next step 210 is to categorize each polygon of vegetation compared to relevant legislation or guidelines – for example the categories described above with reference to Fig. 1 – following this categorization stage, each polygon is depicted according to its category – as shown in Fig. 5(a); paragraph [0096] – risk category).
Regarding claim 18, Stanley discloses all of the limitations as previously discussed with respect to claim 11 including that wherein the entity is a utility line worker (Stanley: Figs. 2, 6, 7, 13, and 14; paragraph [0003] – typically, a ‘network operator’ is responsible for any outages resulting from such damage; these entities often employ contractors to monitor a particular stretch of conductor and pruning or removal of vegetation as necessary; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0011] – the assigning of a remedial action may comprise outputting a statement of suggested remedial action based on said data relating to said target vegetation – outputting a statement of suggested remedial action allows for more efficient management of the vegetation – the statement of suggested remedial action may comprise a recommendation of resource allocation for completing the said remedial action – the resources may comprise at least one of: personnel, equipment, and time; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0109] – based on this information, a statement of work may be sent to a contractor assigning remedial action (step 212), detailing what needs to be done to the vegetation corresponding to that particular polygon – such statements of work may be generated automatically by the system or manually by an operator; paragraph [0118] – the contractor is supplied with a mobile device 600; paragraph [0143] – Fig. 14 shows a screen shot/print out of the work instructions that are supplied to a contractor; once the work order is received, the contractor can head to the location to perform the work required).
Regarding claim 19, Stanley discloses all of the limitations as previously discussed with respect to claim 11 including that wherein the entity is a utility distribution and power organization (Stanley: Figs. 2, 6, 7, 13, and 14; paragraph [0003] – typically, a ‘network operator’ is responsible for any outages resulting from such damage; these entities often employ contractors to monitor a particular stretch of conductor and pruning or removal of vegetation as necessary; paragraph [0007] – a method of categorizing vegetation as potential impact vegetation on a target object, the method comprising: determining data relating to target vegetation; determining data relating to the target object; categorizing said vegetation into one of a plurality of different risk categories in dependence on said data relating to target vegetation and said data relating to the target object; and optionally assigning a remedial action to said vegetation in dependence on said categorization – by categorizing said vegetation into one of a plurality of different risk categories more efficient operation of vegetation management is afforded; paragraph [0011] – the assigning of a remedial action may comprise outputting a statement of suggested remedial action based on said data relating to said target vegetation – outputting a statement of suggested remedial action allows for more efficient management of the vegetation – the statement of suggested remedial action may comprise a recommendation of resource allocation for completing the said remedial action – the resources may comprise at least one of: personnel, equipment, and time; paragraph [0087] – each category of vegetation danger has different remedial actions, ranging from having to de-power the conductor and using special equipment, to using normal (e.g. non-insulated) tools without any need to work in the vicinity of the conductor – it is thus useful for contractors to be able to know the category of vegetation so that they can deploy the appropriate personnel and tools and potentially to request permission from land-owners/network operators prior to a physical site inspection; paragraph [0109] – based on this information, a statement of work may be sent to a contractor assigning remedial action (step 212), detailing what needs to be done to the vegetation corresponding to that particular polygon – such statements of work may be generated automatically by the system or manually by an operator; paragraph [0118] – the contractor is supplied with a mobile device 600; paragraph [0143] – Fig. 14 shows a screen shot/print out of the work instructions that are supplied to a contractor; once the work order is received, the contractor can head to the location to perform the work required).
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Appel et al. (U.S. Patent Application Publication 2021/0034866) discloses a method for managing tree risk and when a tree has a condition above the acceptable threshold, transmitting the notification to a team equipped to remediate the condition of the tree (paragraph [0003]). Furthermore, the risk program 132 may transmit a notification to a team via the notification client 142 of the dispatch device 140 (step 318). The risk program 132 may select a team equipped to confirm the determination of a tree having a tree risk that poses a hazard (e.g., greater than the acceptable threshold) and perform appropriate action to remediate the condition of the determined and confirmed tree. The risk program 132 may select the team using a proximity standard (e.g., a team closest to the tree), a schedule before the team is dispatched, etc. (paragraph [0063]).
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to HEATHER R JONES whose telephone number is (571)272-7368. The examiner can normally be reached Mon. - Fri.: 9:00am - 5:00pm.
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/HEATHER R JONES/Primary Examiner, Art Unit 2481
December 24, 2025