Patent Issued for System and method for vegetation management risk assessment and resolution (USPTO 11010608)

2021 JUN 24 (NewsRx) -- By a News Reporter-Staff News Editor at Insurance Daily News -- A patent by the inventors Adam, Kevin (Cary, NC, US), Matson, Kris C. (Cary, NC, US), Maynard, Roland (Chapel Hill, NC, US), Nespeca, Mathew C. (Raleigh, NC, US), Owen, Michael (Summerfield, NC, US), Ridgeway, John M. (Fair Haven, NJ, US), Slone, J. Brent (Beckley, WV, US), filed on May 22, 2019, was published online on May 18, 2021, according to news reporting originating from Alexandria, Virginia, by NewsRx correspondents.

Patent number 11010608 is assigned to Bayer CropScience LP (St. Louis, Missouri, United States).

The following quote was obtained by the news editors from the background information supplied by the inventors: “

“Field

“The present disclosure relates generally to vegetation management and control, in particular, to vegetation data capture, maintenance workflow generation, prioritization, passive and continuous monitoring of vegetation, and predictive analysis for vegetation that may be within or adjacent to clearance zones for railway, transportation, utility, pipeline, range & pasture, and industrial sites.

“Description of Related Art

“Vegetation management for clearance zones (railway, transportation, utility, pipeline, range & pasture, and industrial sites) requires a significant amount of time and resources. To clarify, transportation is to be used interchangeably with roads, railroads, roadsides, and/or roadways within this specification. Further, a “clearance zone” is defined as an area of terrestrial and/or riparian land where vegetation is removed either completely or selectively (e.g. removal of specific species or all vegetation growing above a specific height) to achieve specific management goals, including but not limited to the reduction of risk associated with the vegetation. Vegetation control provides a number of benefits to land managers and operators. For instance, improved sight distance for visibility of trains at railroad crossings, trees in close proximity to utility lines, flammable weeds growing near oil wells, or invasive brush growing in rangeland areas. Additionally, in a number of jurisdictions, vegetation clearance is required by law including (and not limited to) these agencies: Federal Railroad Administration (FRA), Federal Highway Administration, United States Department of Agriculture (USDA), and the Federal Energy Regulatory Commission.

“Land managers and operators employ in-house and third-party vegetation control inspectors and engineers who implement vegetation control programs within designated clearance zones. These programs are very time and resource consuming, and are difficult to implement and keep up. Therefore, it would be desirable to have systems and methods that take into account at least some of these issues discussed above, as well as other possible issues.”

In addition to the background information obtained for this patent, NewsRx journalists also obtained the inventors’ summary information for this patent: “In view of the foregoing background, example implementations of the present disclosure are directed to a new way for vegetation risk management assessment, monitoring, and resolution for designated clearance zones and other critical infrastructure, including in more particular examples, active and passive monitoring for the detection of vegetation growth obstructing or at-risk of obstructing a clearance zone, vegetation removal signifying easement encroachment issues or response to mitigative action of vegetation obstruction, incident reporting, risk assessment and determination, corrective action, and corrective action assessment. The present disclosure thus includes, without limitation, the following example implementations.

“The primary objective of the invention is to provide a computer-implemented system and method for vegetation management risk assessment, monitoring and resolution, the system and method comprising of receiving data from active and passive monitoring collections of a vegetation risk. The term “vegetation risk” is being used to refer to any vegetation being located within or adjacent to a right-of-way and/or clearance zone or other critical infrastructure that may pose a risk to the operability of a vehicle, functionality of infrastructure, or safety of workers, passengers, and nearby persons and infrastructure. Further“vegetation risk” is also being used to refer to the data comprising images, video, telemetry data, GPS location, text, audio, and the like, characterizing the vegetation risk. Further, “vegetation risk” is also being used to refer to any vegetation located within or adjacent to a right-of-way and/or clearance zone whose presence could represent a risk to the productivity or utility of that land, an example being a poisonous or non-nutritious plants in a grazed rangeland or pasture. Further, “vegetation risk” is also being used to refer to any removal or other modification of vegetation located within or adjacent to a right-of-way and/or clearance zone or other critical infrastructure that signifies easement encroachment issues (i.e. removal of vegetation to build a structure) or response to mitigative action of vegetation obstruction. As it relates to monitoring, the term ‘active’ refers to data that is derived from direct human interaction such as but not limited to the identification of a vegetation risk and actively entering the data for system/platform consumption. The term ‘passive’ is used to identify data capture that does not require human interaction such as but not limited to data capture via a remote sensing mechanism or mechanisms to pass data or an outcome related to a vegetation risk. Further, the present invention optionally includes one or more systems and methods for uploading the active and/or passive data to a cloud computing system comprised of geospatial servers, database servers, and file servers. In one embodiment of the invention, as active and/or passive data is being uploaded, a data controller is continuously scanning the data to determine, based on set criteria, whether the vegetation requires immediate mitigation action prior to long term storage in the cloud computing system. The long term storage in the cloud computing system includes the ability to store the data for archival purposes and to recall the data as desired thereafter to track historically what data has been associated with the vegetation risk. The geospatial servers additionally provide the location for where the vegetation risk was observed. The set criteria for determining whether the vegetation requires immediate mitigation action can be simply user-defined or user-specified risk tolerance profiles. These may include for example proximity to critical infrastructure, density, frequency of occurrence, magnitude of change required before an alert message is sent or mitigation action is initiated. There is intended no limitation here and the criteria may be as complex and detailed as necessary to provide for effective management of the area of vegetation being managed. Alternatively, the criteria may derived from legal bases such as laws or regulations applicable to the area being managed, and those laws and/or regulations may include international, federal, state or local laws, regulations or statutes. Alternatively still, the criteria may be derived from industry or trade journals, standards or publications and/or may be derived from accepted practices that are applicable to the area where the vegetation is being managed. In yet another embodiment of the present invention, the criteria may be a blend of user specified risk tolerances/profiles, laws, regulations, statutes, industry, trade or other publications or standards applicable to the area of vegetation that is being managed. The criteria may be used to establish an alert system which may range from a single alert to a hierarchy of alerts, and it may also be used to establish the point at which action is taken, and that too may range from a single notice to a hierarchy of stages for how often and how intense the call for action is to manage the risk in the area being managed. The criteria may further be adapted to call for specific action to be taken. For example, the criteria may call for action ranging from a one time simple spraying with an appropriate herbicide to a call for an entire work crew to address the risk, as for example, where the identified risk is a fallen tree or other obstruction calling for a full work crew.

“After the data or outcome is stored in the cloud computing system, it may optionally be used in conjunction with data feeds from public, private, and/or governmental agencies for further analysis and manipulation by end-users or other business logic processors. Further, the active and passive data uploaded, as well as, the data feeds from public, private, and/or government agencies are optionally combined and used as input into a web application, where an end-user can view the vegetation risk, associated attribute data, images, video, audio, and/or geospatial maps that identify the location and context of the vegetation risk. Geospatial data is information that describes the location and attributes of things and has some spatial component to it. The geospatial maps may additionally include related geospatial layers including but not limited to one or more of weather data, wetlands, water features, vegetation layout, land cover type, satellite imagery, historic application data and the like to assist in management and assessment activities related to mitigation strategies for the vegetation risk. Further, in the same implementation of the invention, the web application, receiving status input from executed mitigation strategies on the vegetation risk, alerts the end-user of the completion status and other metrics regarding the vegetation risk and execution strategy. The system and method of the present invention also leverages input data to predict and identify future risk throughout time. Predictive analytics or predictive data refers to learning algorithms that predict vegetation progression and/or regression relative to the clearance zone, provide insights towards identifying the escalation of risk in relation to the clearance zone, and/or provide insights for management urgency and prioritization. Further, predictive analytics or predictive data can be based on or otherwise utilize active data, passive data, historical data, previously predictive data or combinations thereof. This interactive platform, based on mobile and web interactive interfaces, enabled by a cloud data server backend, and supported by computer-based algorithms and artificial intelligence, is herein referred to as the ‘digital risk platform’.

“The current state of the art of management of vegetation incidents in clearance zones ranges broadly, includes many partners and lacks consistent communication and tracking mechanisms, and it is a goal of the present invention to overcome these limitations. For example, in the current state of the art in railroad vegetation management, personnel report vegetation incidents in a variety of manners (verbally, voicemail, email, text) to a vegetation manager which makes it difficult for them to log, track progress, assign work orders to responsible parties and learn from the incidents to modify future management practices. Railroad personnel provide a subjective evaluation of the risk of the incident (type of vegetation, size of vegetation, intensity of vegetation, location to clearance zone) which can result in either an over-estimation of risk, which causes wasted resources as responsible parties prioritize to address the incident or an under-estimation of risk, which causes the railroad to be exposed to additional liability and fines by regulators due to non-compliance with Federal regulations. Railroad personnel approximate the location of incidents using the mile markers on the tracks which results in difficulties re-locating a reported incident for evaluation and resolution by the assigned party. Additionally, railroad personnel and the vegetation manager lack any clarity on the timeline for corrective action, if the incident has already been reported by another person, what corrective action was taken and why the incident occurred.”

There is additional summary information. Please visit full patent to read further.

The claims supplied by the inventors are:

“1. A method to create a real-time standardized vegetation management efficacy assessment system comprising: collecting vegetation surface data; wherein the vegetation surface data comprises images, video, text, audio, GPS location, description, and/or combinations thereof, assessing treatment application efficacy that statistically or relatively compares one or more aspects of pre and post-treatment vegetation conditions via a digital risk platform; comparing, by means of overlaying geospatial data with clearance zone and/or right-of-way surface data to the vegetation surface data to determine the location of vegetation objects that are within or adjacent to the clearance zone and/or right-of-way, thus identifying a vegetation object of interest; predicting vegetation progression and/or regression of the vegetation object of interest relative to an infrastructure using machine learning; assessing work order efficacy that statistically combines treatment application efficacy with planned and actual work order completion via the digital risk platform; assessing post-treatment vegetation risk along corridor segments that statistically compares the rate of vegetation recovery in treated areas via the digital risk platform where automation of an alert signifying the geospatial location where a change has occurred is ranked by end user criteria, said end user criteria being selected as one or more of the group consisting of severity, proximity to critical infrastructure, density, frequency of occurrence, and magnitude of change; wherein historical input data and output generated are used to forecast future vegetation risk and prioritization of management practices based on end user specified risk tolerance profiles; reporting of one or more vegetation risks as they are discovered via the digital risk platform; implementation of a standardized risk evaluation and urgency classification determination, via an algorithm that processes critical attributes to validate a risk categorization; automatically routing an incident to the end user based one or more criteria established by the standardized risk evaluation and urgency classification, via the digital risk platform for creation and execution of a mitigation execution strategy.

“2. The method of claim 1, wherein the critical attributes processed by the algorithm include severity, height, species, location within or adjacent to the clearance zone and the type of hazard the risk imposes.

“3. The method of claim 1, wherein the routing information associated with the one or more vegetation risks uses the GPS location to show the relative location of a vegetation object and classification criteria for rapid incident assessment and escalation where significant risks are present.

“4. A system for the evaluation and mitigation of intrusive vegetation in or proximate a target area comprising: at least one cloud-based computer network; a business logic and operations engine; at least one active data collection subsystem including: at least one active data collector; at least one data storage module communicatively connected to said at least one active data collector and containing criteria comprising at least one vegetative intrusion limit; and at least one data controller communicatively connected to said at least one data storage module and said business logic and operations engine and wherein said at least one data controller preferably continuously scans said at least one data storage module to determine if said at least one vegetative intrusion limit is exceeded; wherein active data comprises vegetative growth in or proximate said target areas, direct user action, mitigation actions, and predictive data; wherein the predictive data is data generated by machine learning using learning algorithms that predict vegetation progression and/or regression relative to the clearance zone; at least one passive data collection subsystem including: at least one passive data collector; at least one data content module communicatively connected to each of said at least one passive data collector and wherein said at least one data content module receives passive data from said at least one data collector and from a plurality of data content generators; at least one security data controller communicatively connected to each of said at least one passive data collector wherein said at least one security data controller verifies each of one or more end users are permitted to access passive data and wherein said at least one security data collector is communicatively connected to said business logic and operations engine; a visualization display unit communicatively connected to said business logic and operations engine wherein said permitted end users may view said active data and said passive data; an alert data composition module operatively connected to said data controller and said visualization display unit wherein said alert data composition module generates at least one alert notification based on said active data from said at least one active data controller and/or said passive data from said visualization display and/or predictive data; a communications controller operatively connected to said alert data composition module wherein said communications controller distributes said at least one alert notification; and, a wireless communication system communicatively connected to said communications controller wherein said wireless communication system capable of transmitting said at least one alert notification to said end users; wherein when present, said at least one alert notification integrates said active and/or passive data and initiates one or more actions to mitigate said vegetative intrusion into said target area.

“5. The system of claim 4, wherein said passive data includes imagery of said target area from one or more of satellite, aerial, drone, LIDAR, and/or ground based sensors.

“6. The system of claim 4, further comprising at least one visual data transformation module wherein imagery data is transformed into images for geospatial vegetation mapping and communicated to a data services module wherein said data services module is communicatively connected to said business logic and operations module.

“7. The system of claim 4, wherein said alert notification includes one or more of vegetation species, vegetation height, vegetation density, location relative to said target area and/or type of hazard in or proximate to said target area.

“8. The system of claim 4, wherein said at least one cloud-based computer network comprises file servers, geospatial servers and/or databases.

“9. The system of claim 4, wherein said at least one cloud-based computer network includes a plurality of cloud-based computer networks.

“10. The system of claim 4, wherein said visualization display unit includes one or more applications selected from a web application and a mobile application, wherein said active data and said passive data is displayed and accessed by said permitted end users.

“11. The system of claim 4, wherein said target area is within, encompasses or is adjacent to a clearance zone and wherein said visualization unit displays compose a three-dimensional display in or around said clearance zone or a subpart thereof.”

URL and more information on this patent, see: Adam, Kevin. System and method for vegetation management risk assessment and resolution. U.S. Patent Number 11010608, filed May 22, 2019, and published online on May 18, 2021. Patent URL: http://patft.uspto.gov/netacgi/nph-Parser?Sect1=PTO1&Sect2=HITOFF&d=PALL&p=1&u=%2Fnetahtml%2FPTO%2Fsrchnum.htm&r=1&f=G&l=50&s1=11010608.PN.&OS=PN/11010608RS=PN/11010608

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