Patent Description:
The present disclosure relates generally to systems and methods for locating and identifying buried utilities. More specifically, but not exclusively, the disclosure relates to systems and methods for uniquely identifying buried utilities in a multi-utility region.

Magnetic field sensing locating devices (interchangeably referred as "locating devices", "utility locators", or simply "locators") have been used for many years to locate utilities that are buried or obscured from plain sight. Such conventional locating devices are generally hand-held locators capable of sensing magnetic fields emitted from hidden or buried utilities (e.g., underground utilities such as pipes, conduits, or cables) or other conductors and processing the received signals to determine information about the conductors and the associated underground environment.

Such conventional locating devices, though useful, fail to uniquely and precisely identify buried utilities in situations where a wide variety of buried utilities are installed in close proximity to each other. Also, such conventional locating devices often detect "false" locate signals in instances where several other above-ground or underground metallic objects are installed in vicinity of the buried utilities due to interference caused by such surrounding objects.

<CIT> discloses a known method for measuring buried ferromagnetic objects. <CIT> discloses a known multiple-sensor subsurface imaging data visualizing method for detecting and locating underground utilities.

Accordingly, there is a need in the art to address the above-described as well as other problems.

This disclosure relates generally to systems and methods for locating and identifying buried utilities. More specifically, the disclosure relates to systems and methods for uniquely identifying buried utilities in a multi-utility region. The disclosure further relates to mapping uniquely identified buried utilities on a geographical map of the multi-utility region.

In another aspect, the present disclosure relates to a method for uniquely identifying buried utilities in a multi-utility region according to claim <NUM>.

Various additional aspects, features, and functionality are further described below in conjunction with the appended Drawings.

The present application may be more fully appreciated in connection with the following detailed description taken in conjunction with the accompanying drawings, wherein:.

The term "buried utilities" as used herein refers not only to utilities below the surface of the ground, but also to utilities that are otherwise obscured, covered, or hidden from direct view or access (e.g. overhead power lines, underwater utilities, and the like). In a typical application a buried utility is a pipe, cable, conduit, wire, or other object buried under the ground surface, at a depth of from a few centimeters to meters or more, that a user, such as a utility company employee, construction company employee, homeowner or other wants to locate, map (e.g., by surface position as defined by latitude/longitude or other surface coordinates, and/or also by depth), measure, and/or provide a surface mark corresponding to it using paint, electronic marking techniques, images, video or other identification or mapping techniques.

The term "utility data" as used herein, may include, but is not limited to, data pertaining to presence or absence, position, depth, current flow, magnitude, phase, and/or direction, and/or orientation of underground utility lines. The utility data may include a plurality of location data points each indicative of location information pertaining to a buried utility (interchangeably referred to as a "buried utility line"), and associated characteristics of the buried utility. The utility data may also include timestamps associated with the location data points. Further, the utility data may include information about soil properties, other changes in properties of pipes or other conductors in time and/or space, quality metrics of measured data, and/or other aspects of the utility and broadcast signals and/or the locate environment. The utility data may also include data received from various sensors, such as motion sensors, temperature sensors, humidity sensors, light sensors, barometers, sound, gas, radiation sensors, and other sensors provided within or coupled to the locating device(s). The utility data further includes data received from ground tracking device(s) and camera element(s) provided within or coupled to the locating device(s). The utility data may be in the form of magnetic field signals radiated from the buried utility.

The term "magnetic field signals" or "magnetic fields" as used herein may refer to radiation of electromagnetic energy at the locate area. The magnetic field signals may further refer to radiation of electromagnetic energy from remote transmission sources measurable within the locate area, typically at two or more points. For example, an AM broadcast radio tower used by a commercial AM radio station may transmit a radio signal from a distance that is measurable within the locate operation area.

The terms "filter," "digital filter," or "logic filter" as used herein may refer to processing of sampled input signals utilizing mathematical algorithms to transform sampled input signals to a more desirable output. Such desirable output may include but is not limited to noise suppression, enhancement of selected frequency ranges, bandwidth limiting, estimating the value of an unknown quantity or quantities, or the like. Exemplary filters may include but are not limited to direct Fourier transforms (DFT), Kalman filters, and the like.

The term "electronic device" as used herein refers to any device or system that can be operated or controlled by electrical, optical, or other outputs from a user interface device. Examples of user electronic devices include, but are not limited to, vehicle-mounted display devices, navigation systems such as global positioning system receivers, personal computers, notebook or laptop computers, personal digital assistants (PDAs), cellular phones, computer tablet devices, electronic test or measurement equipment including processing units, and/or other similar systems or devices. In a particular embodiment of the present disclosure, the electronic device may include a map application, which is a software stored on a non-transitory tangible medium within or coupled to the electronic device configured to receive, send, generate, modify, display, store, and/or otherwise use or manipulate a map or its associated objects.

As used herein, the term "map" or "geographical map" refers to imagery, diagrams, graphical illustrations, line drawings or other representations depicting the attributes of a location, which may include maps or images containing various dimensions (i.e. two dimensional maps or images and/or three dimensional maps or images). These may be vector or raster objects and/or combinations of both. Such depictions and/or representations may be used for navigation and/or relaying information associated with positions or locations, and may also contain information associated with the positions or locations such as coordinates, information defining features, images or video depictions, and/or other related data or information. For instance, the spatial positioning of ground surface attributes may be depicted through a series of photographs or line drawings or other graphics representing a location. Various other data may be embedded or otherwise included into maps including, but not limited to, reference coordinate information such as latitude, longitude, and/or altitude data, topographical information, virtual models/objects, information regarding buried utilities or other associated objects or elements, structures on or below the surface, and the like. The maps may depict a probability contour indicative of likelihood of presence of the buried utilities at a probable location, and other associated information such as probable orientation and depth of the buried utilities. Alternatively or additionally, the map may depict optimized locations of the buried utilities along with associated information such as orientation and depth of the buried utilities.

The term "cluster" as used herein refers to sampled data that may be grouped by some property or characteristic as well as group or pattern of properties or characteristics. Such clusters may generally refer to some similarity in property or characteristic of sampled data. Such properties and characteristics may include but are not limited to measured magnetic field signals relative to orientation, azimuthal angle, depth, position, current, frequency, phase, or the like. It is also noted that the cluster analysis methods described within the present disclosure, also referred to herein as "k-means clustering" or "clustering", describe one method to determine the presence and location of utility lines. Within locating operations other like methods, such as hierarchical clustering methods or other filtering, may instead or additionally be used to locate utility lines.

The term "communicatively coupled" as used herein may refer to a link for exchange of information between locating devices, remote servers, and/or other system devices. Such a link may be transmitted via wire or cable or wirelessly, for instance, through Wi-Fi, Bluetooth, or using like wireless communication devices or protocols. Such communicative couplings may occur in real-time or near-real time or in post process. For instance, in some embodiments the locating device(s) may connect wirelessly to one or more remote servers for exchanging data in real-time or near-real time for processing and further use at the locating device(s). In other embodiments, locating data may be stored within the locating device and later transferred to a server or other computing device for processing. Such post processed data may then be downloadable by the same or other locating devices for future use. In yet further embodiments, a combination of real-time or near-real time exchange of data and storage of data for post processing may occur. For instance, some data may be exchanged in real-time or near-real time to one or more remote servers whereas other data is stored at the locating device for later transfer and post processing at a server or other computing device.

As used herein, the term, "exemplary" means "serving as an example, instance, or illustration. " Any aspect, detail, function, implementation, and/or embodiment described herein as "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects and/or embodiments.

The present disclosure relates generally to systems and methods for locating and identifying buried utilities. More specifically, but not exclusively, the disclosure relates to systems and methods for uniquely identifying buried utilities in a multi-utility region where a wide variety of buried utilities are installed in a close distance from each other. The disclosure further relates to mapping such uniquely identified buried utilities on a geographical map of the multi-utility region.

In one aspect, the systems and methods may include a magnetic field sensing locating device (interchangeably referred to as a "locating device") having one or more antenna nodes or antennas, a receiver circuit coupled to the antenna nodes including a receiver input, an electronic circuity, a receiver output, and a processing unit including one or more processing elements coupled to the receiver output. The antenna nodes may sense magnetic fields emitted from the buried utilities and generate antenna output signals corresponding to the sensed magnetic fields. The antenna output signals may be received at the receiver circuit and processed to generate receiver output signals, which may be provided to the processing unit.

At the processing unit, a location identification module may process the receiver output signals to identify data pertaining to the buried utilities. The location identification module may, for example, eliminate noise or false magnetic field signals, i.e., signals that do not pertain to any of the buried utilities from the receiver output signals, to identify the data (hereinafter referred to as "utility data") that pertains to the buried utilities. The utility data may include, for example, a plurality of location data points where each data point is indicative of location information pertaining to at least one of the buried utilities in the multi-utility region.

These location data points may be received by a utility classification module at the processing unit to generate a plurality of clusters, where each cluster may include a set of location data points sharing common characteristics (e.g., substantially same depth, orientation, alignment, and the like). The generated clusters may exhibit one or more patterns (e.g., electrical characteristics including frequency spectrum, power spectrum unique to specific buried utilities) which may be subsequently identified by the utility classification module and may be utilized to classify the clusters for uniquely identifying or characterizing each of the buried utilities. The location data points in a cluster may be correlated, spatially and in a time domain, to trace location of each of the buried utilities facilitating the identified buried utilities with their corresponding traced locations to be mapped on a geographical map of the multi-utility region.

According to various aspects of the present disclosure, the systems and methods may include one or more vehicle-mounted magnetic field sensing locating devices and/or hand-carried magnetic field sensing locating devices, to uniquely identify and map buried utilities in conjunction with a remote server/system communicatively coupled to the locating devices, in real-time or during post-processing.

Details of the locating devices referred herein, additional components, methods, and configurations that may be used in conjunction with the embodiments described subsequently herein are disclosed in co-assigned patent applications including <CIT>, entitled OMNIDIRECTIONAL SONDE AND LINE LOCATOR; <CIT>, entitled A BURIED OBJECT LOCATING AND TRACING METHOD AND SYSTEM EMPLOYING PRINCIPAL COMPONENTS ANALYSIS FOR BLIND SIGNAL DETECTION; <CIT>, entitled SONDES FOR LOCATING UNDERGROUND PIPES AND CONDUITS; <CIT>, entitled COMPACT SELF-TUNED ELECTRICAL RESONATOR FOR BURIED OBJECT LOCATOR APPLICATIONS; <CIT>, entitled INDUCTIVE CLAMP FOR APPLYING SIGNAL TO BURIED UTILITIES; <CIT>, entitled LOCATOR WITH APPARENT DEPTH INDICATION; <CIT>, entitled MULTI-SENSOR MAPPING OMNIDIRECTIONAL SONDE AND LINE LOCATORS; <CIT>, entitled COMPACT LINE ILLUMINATOR FOR LOCATING BURIED PIPES AND CABLES; <CIT>, entitled SINGLE AND MULTI-TRACE OMNIDIRECTIONAL SONDE AND LINE LOCATORS AND TRANSMITTER USED THEREWITH; <CIT>, entitled MULTI-SENSOR MAPPING OMNIDIRECTIONAL SONDE AND LINE LOCATORS AND TRANSMITTER USED THEREWITH; <CIT>, entitled ADAPTIVE MULTICHANNEL LOCATOR SYSTEM FOR MULTIPLE PROXIMITY DETECTION; <CIT>, entitled PORTABLE LOCATOR SYSTEM WITH JAMMING REDUCTION; <CIT>, entitled SMART PERSONAL COMMUNICATION DEVICES AS USER INTERFACES; <CIT>, entitled AN UNDERGROUND UTILITY LOCATOR WITH A TRANSMITTER, A PAIR OF UPWARDLY OPENING POCKETS AND HELICAL COIL TYPE ELECTRICAL CORDS; <CIT>, entitled PRE-AMPLIFIER AND MIXER CIRCUITRY FOR A LOCATOR ANTENNA; <CIT>, entitled HIGH-Q SELF TUNING LOCATING TRANSMITTER; <CIT>, entitled RECONFIGURABLE PORTABLE LOCATOR EMPLOYING MULTIPLE SENSOR ARRAY HAVING FLEXIBLE NESTED ORTHOGONAL ANTENNAS; <CIT>, entitled BURIED OBJECT LOCATOR SYSTEM EMPLOYING AUTOMATED VIRTUAL DEPTH EVENT DETECTION AND SIGNALING; <CIT>, entitled SYSTEMS AND METHODS FOR LOCATING BURIED OR HIDDEN OBJECTS USING SHEET CURRENT FLOW MODELS; <CIT>, entitled SYSTEM AND METHOD FOR LOCATING BURIED PIPES AND CABLES WITH A MAN PORTABLE LOCATORAND A TRANSMITTER IN A MESH NETWORK; <CIT>, entitled QUAD-GRADIENT COILS FOR USE IN LOCATING SYSTEMS; <CIT>, entitled MULTI-FREQUENCY LOCATING SYSTEMS AND METHODS; <CIT>, entitled SMART PAINT STICK DEVICES AND METHODS; <CIT>, entitled DOCKABLE TRIPODAL CAMERA CONTROL UNIT; <CIT>, entitled DUAL SENSED LOCATING SYSTEMS AND METHODS; <CIT>, entitled LOCATOR ANTENNA WITH CONDUCTIVE BOBBIN; <CIT>, entitled DUAL ANTENNA SYSTEMS WITH VARIABLE POLARIZATION; <CIT>, entitled OMNI-INDUCER TRANSMITTING DEVICES AND METHODS; <CIT>, entitled OPTICAL ROUND TRACKING APPARATUS, SYSTEMS AND METHODS; <CIT>, entitled USER INTERFACES FOR UTILITY LOCATORS; <CIT>, entitled SONDE DEVICES INCLUDING A SECTIONAL FERRITE CORE STRUCTURE; <CIT>, entitled WEARABLE MAGNETIC FIELD UTILITY LOCATOR SYSTEM WITH SOUND FIELD GENERATION; <CIT>, entitled PIPE MAPPING SYSTEM; <CIT>, entitled Locator and Transmitter Calibration System; <CIT>, entitled UTILITY LOCATOR TRANSMITTER DEVICES, SYSTEMS, AND METHODS WITH DOCKABLE APPARATUS; <CIT>, entitled UTILITY LOCATING SYSTEMS WITH MOBILE BASE STATION; <CIT>, entitled INDUCTIVE CLAMP DEVICES, SYSTEMS, AND METHODS; <CIT>, entitled ELECTRONIC MARKER DEVICES AND SYSTEMS; <CIT>, entitled NULLED-SIGNAL LOCATING DEVICES, SYSTEMS, AND METHODS; <CIT>, entitled ECONOMICAL MAGNETIC LOCATOR APPARATUS AND METHOD; <CIT>, entitled GROUND TRACKING APPARATUS, SYSTEMS, AND METHODS; <CIT>, entitled GROUND-TRACKING DEVICES AND METHODS FOR USE WITH A UTILITY LOCATOR; <CIT>, entitled MARKING PAINT APPLICATOR FOR USE WITH PORTABLE UTILITY LOCATOR; <CIT>, entitled GROUND-TRACKING DEVICES FOR USE WITH A MAPPING LOCATOR; <CIT>, entitled HAPTIC DIRECTIONAL FEEDBACK HANDLES FOR LOCATION DEVICES; <CIT>, entitled METHODS AND SYSTEMS FOR SEAMLESS TRANSITIONING IN INTERACTIVE MAPPING SYSTEMS; <CIT>, entitled MARKING PAINT APPLICATOR FOR PORTABLE LOCATOR; <CIT>, entitled BURIED OBJECT LOCATOR APPARATUS AND SYSTEMS; <CIT>, entitled SELF-STANDING MULTI-LEG ATTACHMENT DEVICES FOR USE WITH UTILITY LOCATORS; <CIT>, entitled OPTICAL GROUND TRACKING APPARATUS, SYSTEMS, AND METHODS; <CIT>, entitled TRACKABLE DIPOLE DEVICES, METHODS, AND SYSTEMS FOR USE WITH MARKING PAINT STICKS; <CIT>, entitled SYSTEMS AND METHODS FOR UNIQUELY IDENTIFYING BURIED UTILITIES IN A MULTI-UTILITY ENVIRONMENT; <CIT>, entitled GROUND-TRACKING SYSTEMS AND APPARATUS; <CIT>, entitled LOCATING DEVICES, SYSTEMS, AND METHODS USING FREQUENCY SUITES FOR UTILITY DETECTION; <CIT>, entitled PHASE-SYNCHRONIZED BURIED OBJECT TRANSMITTER AND LOCATOR METHODS AND APPARATUS; <CIT>, entitled PHASE SYNCHRONIZED BURIED OBJECT LOCATOR APPARATUS, SYSTEMS, AND METHODS; <CIT>, entitled IMAGE-BASED MAPPING LOCATING SYSTEM; <CIT>, entitled KEYED CURRENT SIGNAL UTILITY LOCATING SYSTEMS AND METHODS; <CIT>, entitled GRADIENT ANTENNA COILS AND ARRAYS FOR USE IN LOCATING SYSTEMS; <CIT>, entitled OMNI-INDUCER TRANSMITTING DEVICES AND METHODS; <CIT>, entitled UTILITY LOCATING SYSTEMS, DEVICES, AND METHODS USING RADIO BROADCAST SIGNALS; <CIT>, entitled MAGNETIC SENSING BURIED OBJECT LOCATOR INCLUDING A CAMERA; <CIT>, entitled SYSTEMS AND METHODS FOR ELECTRONICALLY MARKING AND LOCATING BURIED UTILITY ASSETS; <CIT>, entitled SYSTEMS AND METHODS FOR ELECTRONICALLY MARKING , LOCATING, AND DISPLAYING BURIED UTILITY ASSETS; <CIT>, entitled UTILITY LOCATOR TRANSMITTER APPARATUS AND METHODS; <CIT>, entitled DIPOLE-TRACKED LASER DISTANCE MEASURING DEVICE; <CIT>, entitled METHODS AND APPARATUS FOR HIGHSPEED DATA TRANSFER EMPLOYING SELF-SYNCHRONIZING QUADRATURE AMPLITUDE MODULATION (QAM); <CIT>, entitled BURIED UTILTY MARKER DEVICES, SYSTEMS, AND METHODS; <CIT>, entitled USER INTERFACES FOR UTILITY LOCATOR; <CIT>, entitled SYSTEMS AND METHODS FOR LOCATING BURIED OR HIDDEN OBJECTS USING SHEET CURRENT FLOW MODELS; <CIT>, entitled UTILITY LOCATORS WITH RETRACTABLE SUPPORT STRUCTURES AND APPLICATIONS THEREOF; <CIT>, entitled UTILITY LOCATING APPARATUS AND SYSTEMS USING MULTIPLE ANTENNA COILS; <CIT>, entitled UTILITY LOCATORS WITH PERSONAL COMMUNICATION DEVICE USER INTERFACES; <CIT>, entitled SYSTEMS AND METHODS FOR DATA TRANSFER USING SELF-SYNCHRONIZING QUADRATURE AMPLITUDE MODULATION (QAM); <CIT>, entitled MAGNETIC UTILITY LOCATOR DEVICES AND METHODS; <CIT>, entitled INDUCTIVE CLAMP DEVICES, SYSTEMS, AND METHODS; <CIT>, entitled NULLED-SIGNAL UTILITY LOCATING DEVICES, SYSTEMS, AND METHODS; <CIT>, entitled SYSTEMS AND METHODS FOR LOCATING AND/OR MAPPING BURIED UTILITIES USING VEHICLE-MOUNTED LOCATING DEVICES; and <CIT>, entitled BORING INSPECTION SYSTEMS AND METHODS. The above applications may be collectively denoted herein as the "co-assigned applications".

The following exemplary embodiments are provided for the purpose of illustrating examples of various aspects, details, and functions of the present disclosure; however, the described embodiments are not intended to be in any way limiting. It will be apparent to one of ordinary skill in the art that various aspects may be implemented in other embodiments within the scope of the present invention, which is solely defined by the appended claims.

The present disclosure relates to systems and methods for uniquely identifying buried utilities in a multi-utility region, and further relates to mapping the uniquely identified buried utilities.

In one aspect, the present disclosure relates to uniquely identifying each individual buried utility from amongst a plurality of buried utilities.

In another aspect, the present disclosure relates to uniquely and precisely identifying each buried utility in a multi-utility region where a plurality of buried utilities are present in a close proximity to each other.

In another aspect, the present disclosure relates to uniquely identifying buried utilities in a situation where one or more buried utilities cross over another buried utility or utilities.

In another aspect, the present disclosure relates to uniquely and precisely identifying buried utilities in a multi-utility region where a plurality of buried utilities are present, and additionally a plurality of other metallic/electrically conductive objects other than the utilities are present in proximity of the buried utilities.

In another aspect, the present disclosure relates to mapping the uniquely identified buried utilities on a geographical map of the multi-utility region.

In another aspect, the present disclosure relates to systems and methods for uniquely identifying buried utilities using a magnetic field sensing locating device which may be a hand-carried locating device or a vehicle-mounted locating device.

In another aspect, the present disclosure relates to systems and methods for uniquely identifying buried utilities using a plurality of magnetic field sensing locating devices including hand-carried locating devices, vehicle-mounted locating devices, or a combination of thereof.

In another aspect, the present disclosure relates to systems and methods for uniquely identifying buried utilities using one or more magnetic field sensing locating devices and a remote server communicatively coupled to such locating devices to receive data collected at the magnetic field sensing devices, to process the received data, remotely, to uniquely identify buried utilities, and to transmit information about uniquely identified buried utilities to respective user electronic devices associated with the magnetic field sensing locating devices.

In another aspect, the present disclosure relates to systems and methods for uniquely identifying buried utilities using one or more magnetic field sensing locating devices and a remote server communicatively coupled to such locating devices to receive data collected at the magnetic field sensing devices, to process the received data, remotely, to uniquely identify buried utilities, and to transmit information about uniquely identified buried utilities for remote viewing, planning, decisions and design purposes.

In another aspect, the present disclosure relates to systems and methods for uniquely identifying buried utilities utilizing one or more magnetic field sensing locating devices, or a combination of the magnetic field sensing locating devices and a remote server, to sense the magnetic fields emitted from the buried utilities, and to process the sensed magnetic fields in real-time or near-real time or in post processing to uniquely identify the buried utilities.

In another aspect, the present disclosure relates to a system for uniquely identifying buried utilities in a multi-utility region. The system may include a magnetic field sensing locating device including one or more antenna nodes to sense magnetic fields emitted from a plurality of buried utilities and provide antenna output signals corresponding to the sensed magnetic fields.

The system may further include a receiver circuit having a receiver input to receive the antenna node output signals, an electronic circuitry to process the received antenna node output signals, and a receiver output to provide receiver output signals corresponding to the received magnetic field signals.

The system may furthermore include a processing unit having one or more processing elements coupled to the receiver output to receive the receiver output signals. The processing elements may further be coupled to a location identification module to process the receiver output signals and identify utility data pertaining to the plurality of buried utilities from the receiver output signals. The utility data may include a plurality of location data points each indicative of location information pertaining to at least one of the buried utilities and its associated characteristics. The processing elements may also be coupled to a utility classification module to receive the location data points, generate a plurality of clusters, each including a set of location data points sharing common characteristics, and classify the clusters based on one or more patterns exhibited by the clusters to uniquely identify each of the buried utilities.

In another aspect, the present disclosure relates to a system for uniquely identifying and mapping buried utilities in a multi-utility region. The system may include one or more magnetic field sensing locating devices including one or more vehicle-mounted magnetic field sensing locating devices and/or hand-carried magnetic field sensing locating devices to sense magnetic field signals emitted from buried utilities. The sensed magnetic fields signals are processed to determine utility data, a plurality of location data points each indicative of location information pertaining to at least one of the buried utilities and associated characteristics of the at least one of the buried utilities. The utility data may be provided to a remote server/system communicatively coupled to the locating devices. The remote server includes a utility classification module to generate, based on the received location data points, a plurality of clusters where each cluster may include a set of location data points sharing common characteristics. The utility classification module may further identify one or more patterns exhibited by each of the generated clusters and correlate those clusters based on the patterns to uniquely identify and locate each of the buried utilities.

The invention relates to a method for uniquely identifying buried utilities in a multi-utility region. The method includes sensing magnetic fields emitted from buried utilities upon moving a magnetic field sensing locating device over a multi-utility region and identifying them, based on the magnetic fields utility data pertaining to the buried utilities. The utility data includes a plurality of location data points where each location data point is indicative of location information pertaining to one or more buried utilities, timestamp(s) associated therewith, and one or more characteristics of such buried utilities.

The method further includes generating a plurality of clusters based on the identified location data points where each cluster includes a set of location data points sharing common characteristics. These clusters may exhibit one or more patterns which are identified and used for classifying the clusters to uniquely identify the buried utilities. The method also includes correlating the location data points in these clusters, spatially and in a time domain, to trace location of the uniquely identified buried utilities and to map the traced location of the uniquely identified buried utilities on a geographical map of the multi-utility region.

Referring to the figures now, <FIG> illustrate embodiments of a system 100A and 100B for uniquely identifying buried utilities in a multi-utility region, embodying the principles and concepts of the present disclosure.

The system 100A of <FIG> and the system 100B of <FIG> includes a magnetic field sensing locating device <NUM> (interchangeably referred to as a "locating device") to detect buried utilities <NUM> in a multi-utility region. The locating device <NUM>, according to various embodiments of the present disclosure, may be a hand-carried locating device <NUM> carried by a technician <NUM> as shown in the <FIG>, or a vehicle-mounted locating device <NUM> mounted at a suitable position on a vehicle <NUM> as shown in the <FIG>.

Although embodiments of the vehicle-mounted locating device <NUM> described hereinafter in the description and appended drawings refer to one or more locating devices <NUM> being mounted on, particularly, terrestrial vehicles, this description and/or drawings are not intended to be construed in a limiting sense. The vehicle <NUM> may be any kind of a motor assisted user-propelled vehicle or a self-propelled vehicle capable of supporting one or more locating devices <NUM> thereon. Examples may include terrestrial vehicles, submarine vehicles, aerial vehicles, or a combination thereof, including, but not limited to, cars, trucks, sport utility vehicles (SUVs), motorcycles, boats, ships, low flying drones, or the like.

The system 100A and 100B of <FIG> and <FIG> respectively may further include one or more active transmitters <NUM> with one or more inductive clamp devices <NUM> and/or direct connect clips and/or like devices for inductively or directly or capacitively coupling signal to target utility line(s) (e.g., buried utilities <NUM>). Additionally, one or more induction stick devices <NUM> or like induction devices may be provided for inducing signal onto buried utilities <NUM>. Within the system 100B of <FIG>, for instance, the vehicle <NUM> may include an inductive device (not illustrated) to induce signal onto nearby utility lines.

As illustrated in both <FIG> and <FIG>, one or more AM radio broadcast towers <NUM> and/or other sources of electromagnetic signals (e.g., powerlines, transformers, or the like) may likewise generate signals that may couple to buried utilities <NUM> and reradiate a magnetic signal measurable at the locating device <NUM>. For instance, the signals <NUM> emitted from buried utilities <NUM> may be active signals from the transmitter <NUM> and/or induction stick device <NUM> and/or present in the utility line (e.g., such as the electromagnetic signal inherently emitted from current flow through a powerline or line for telecommunications <NUM>) and/or may be coupled via other electromagnetic signal transmitters (e.g., overhead powerlines, AM radio broadcast towers <NUM>, or the like) that may be measured at the locating device <NUM>.

Still referring to <FIG> and <FIG>, when the locating device <NUM> is moved over the multi-utility region, the locating device <NUM> may measure magnetic fields emitted from a plurality of buried utilities <NUM>. In general, besides buried utilities <NUM>, the sensed magnetic fields may also include magnetic fields emitted from other buried or above ground conductors or metallic objects (hereinafter referred to as "buried objects") such as jammers, rebar in concrete, railroad spurs, ground pipe alignment, poles, and the like, buried in proximity of the buried utilities <NUM>. The locating device <NUM>, in accordance with the present subject matter, processes such measured magnetic fields, whereby the processing includes distinguishing the magnetic fields that pertain to the buried utilities <NUM> from those emitted from other buried objects based on evaluation of various parameters, including but not limited to, magnitude of the magnetic fields, gradients of the magnetic fields (e.g. gradients in a horizontal direction of the magnetic fields), and angle of elevation of the magnetic fields.

In an embodiment, such parameters are evaluated periodically or at regular intervals (in real-time, near real-time, or post processing) as the locating device <NUM> or the vehicle <NUM> having the locating device <NUM> attached thereto is moved along the path of the buried utilities <NUM>. For example, as shown in the <FIG>, when the locating device <NUM> or the vehicle <NUM> having the locating device <NUM> attached thereto is moved at regular intervals, say, at intervals "a," "b," and "c", magnitude of the magnetic fields, angle of elevation of the magnetic fields and gradients may be determined at each of such intervals "a," "b," and "c". As an instance, gradients may be determined from tensor derivatives of a signal's magnetic field vector, hereinafter referred to as "gradient tensors" "T1," "T2," and "T3" based on the magnetic field vectors (BUp1, BLow1), (BUp2, BLow2), and (BUp3, BLow3), where BUp1, BUp2, and BUp3 correspond to magnetic field vectors derived from the upper antenna nodes respectively, and BLow1, BLow2, and BLow3 correspond to magnetic field vectors derived from the lower antenna nodes respectively.

Subsequent to evaluation of such parameters (e.g., magnitude of the magnetic fields, gradients of the magnetic fields, and angle of elevation of the magnetic fields), a determination may be made whether such parameters related to the magnetic fields are within their respective predefined range. Based on the determination, the magnetic fields having corresponding parameters in their predefined range are identified as buried utilities, and other magnetic fields are eliminated as noise. After processing, utility data pertaining to the buried utilities are identified from the magnetic fields that pertain to the buried utilities.

In some embodiments, the locating device <NUM> may include electronic marker excitation device(s) (not shown) provided either as an in-built device or a separate device coupled to the locating device <NUM>, which may be actuated to excite various pre-existing electronic marks (e.g., Underground field identification/Radio Frequency Identification tags, marker devices or balls) buried in proximity to the buried utilities, in order to identify the buried utilities and utility data associated therewith.

The locating device <NUM> may also include imaging device(s), such as camera modules (not shown) that may detect other non-electronic pre-existing marks, such as paint marks to identify the buried utilities and associated utility data. The utility data, thus identified, as a result of processing and additionally as a result of detection of pre-existing marks includes, amongst other data, a plurality of location data points each of which indicates location information pertaining to a buried utility <NUM> at a geographical instance of the multi-utility region. The location information indicated by the location data point may refer to an absolute position of the buried utility <NUM> at the geographical instance capable of being represented in a three dimensional universal coordinate system.

Based on these location data points, the locating device <NUM> generates a plurality of clusters each of which includes a set of location data points sharing common characteristics. The term "cluster" as used herein refers to sampled data that may be grouped by some property or characteristic as well as a group or pattern of properties or characteristics. The clusters may generally refer to some similarity in property or characteristic of sampled data. The characteristics include underground depth, orientation, alignment, and placement relative to other objects, azimuthal of measured fields, current/power and rate of change, frequency, phase or phase change ratio, and the like.

The generated clusters may exhibit one or more patterns, which, in the context of the present subject matter, may be understood as unique characteristics associated with the buried utilities that are capable of distinguishing one buried utility from other buried utilities. The patterns include electrical characteristics such as frequency spectrum and power spectrum, harmonics data (e.g., odd harmonics, even harmonics, or a combination thereof), rebroadcast frequencies, and the like. Based on such patterns, the locating device <NUM> classifies the clusters to uniquely identify the buried utilities <NUM>.

In some embodiments, the locating device <NUM> may carry out further analysis and/or processing to determine more granular level details associated with the buried utilities. For instance, if a power line is identified as a buried utility, further analysis may indicate that the power line is a main AC power distribution line.

As further illustrated in <FIG>, a power line, such as the AC power distribution line previously described, may have harmonics having different power spectra, as represented graphically in power spectra 190A, 190B, and 190C. Each power line harmonic spectra 190A, 190B, and/or 190C may have a distinct fingerprint or signature. The clustering methods described herein may classify the fingerprint of the power line harmonic spectra 190A, 190B, and/or 190C allowing each associated utility line to be uniquely identified.

It is to be noted that the specific clustering method(s) described herein may be some method(s) to determine the presence and location of utility lines. However, other methods such as hierarchical clustering or other filtering methods/techniques may additionally be used to locate utility lines, without deviating from the scope of the present disclosure.

Referring back to <FIG> and <FIG>, according to one aspect, the locating device <NUM> further generates an individual cluster quality metric for each of the clusters expressing how different the location data points in a cluster are from the location data points in other clusters. The locating device <NUM> may further generate a common cluster quality metric based on the individual cluster metrics expressing how different a cluster is from other clusters. Such a common cluster quality metric as referred herein may be understood as a metric that represents a measure of the quality of differentiation between the clusters. Alternatively or additionally, the locating device <NUM> may generate an individual cluster quality metric for each of the clusters expressing how similar the location data points in the cluster are with the location data points in other clusters, and may further generate a common cluster quality metric based on the individual cluster metrics expressing how similar a cluster is to other clusters. Based on one or more of such cluster quality metrics and the detected patterns, the locating device <NUM> identifies the clusters that are representative of a common buried utility, and process such clusters to uniquely identify each of the buried utilities.

Once the buried utilities are uniquely identified, the locating device <NUM> may correlate the location data points in the clusters both spatially and in a time domain, to trace the location of the identified buried utilities <NUM>. Additionally, the locating device <NUM> may determine if a utility being traced has changed to a different utility to precisely trace each of the buried utilities. The identified buried utility and its traced location may be mapped on a geographical map of a multi-utility region to assist users in finding the location. The mapping may include aligning the buried utilities on a base map (e.g., pre-existing geographical map) of the multi-utility region, or vice-versa.

In some embodiments, the locating device <NUM> may also include a rangefinder device(s) that may be actuated to measure relative distance between various reference objects such as landmarks, curbs, sidewalks, and poles, in the vicinity of the traced location of the buried utilities <NUM>. Such reference objects and their distance information from the buried utilities may be also be mapped onto the geographical map of the multi-utility region, to further assist the user in finding the location, or may simply be used to accurately align the buried utilities on the base map of the multi-utility region.

Embodiments of the locating device <NUM> and its associated components are now described with reference to the <FIG> and <FIG>.

As shown in the <FIG>, the locating device <NUM> may include a body <NUM> which may be configured in a variety of different shapes and/or sizes. The body <NUM> may include a head unit <NUM>, and a central mast <NUM>, along with associated mechanical components, such as hardware, connectors, etc. Further, the locating device <NUM> may include one or more antenna nodes such as the lower antenna node <NUM> and the upper antenna node <NUM>, molded to be coupled around the central mast <NUM>, or disposed on or within the body <NUM> in various configurations.

Each of the antenna nodes <NUM> and <NUM> may include an antenna configuration of multiple coils. The antenna nodes <NUM> and <NUM> may each include a node housing such as node housing <NUM> and node housing <NUM>, and an antenna assembly such as the dodecahedral antenna assembly <NUM> illustrated in <FIG> and the omnidirectional antenna assembly <NUM> also illustrated in <FIG>. As further illustrated in <FIG>, each antenna assembly <NUM> and <NUM> may be supported by an antenna array support structure <NUM> or <NUM>. Alternately, or in addition, one or more of the antenna nodes may be a gradient antenna node. Likewise, in other locating device embodiments a different number of antenna nodes having different antenna assembly configurations may be used. For example, in certain embodiments, the antenna node may include one or more dodecahedral antenna node including twelve antenna coils and a gradient antenna node including two or more antenna coils.

In one embodiment, an interior omnidirectional antenna array may be provided and supported by the antenna assembly positioning a plurality of coils of an omnidirectional antenna array in orthogonal directions. The interior omnidirectional antenna array may include, for example, three orthogonally oriented antenna coils. Additionally, a gradient antenna array may be provided and supported by the antenna assembly positioning a plurality of coils of the gradient antenna array circumferentially about the omnidirectional antenna array. The gradient antenna may include, for example, two diametrically opposed pairs of gradient antenna coils. Alternatively, the gradient antenna coils may include two gradient antenna coils and two dummy coils. The two gradient antenna coils may be co-axial. In some embodiments, the two gradient antenna coils may be oriented orthogonally.

Referring again to <FIG>, the head unit <NUM> of the locating device <NUM> may include a receiver circuit having analog and/or digital electronic circuitry to receive and process signals from antennas and other inputs, such as audio inputs, camera signals, and the like. Head unit <NUM> may further include display unit <NUM>, control and/or user interface components, such as one or more visual displays, speakers and/or headphone interfaces, switches, touchscreen elements, one or more camera elements, such as cameras <NUM>, and the like. The camera elements may include, for example, a pair of outward cameras projecting downwardly to record imagery of the ground (locate area) where utilities are buried. A battery <NUM> may further connect to the locating device <NUM> providing electrical power thereto.

The electronic circuitry may include one or more processing units, which refers to a device or apparatus configured to carry out programmable steps and/or other functions associated with the methods described herein by processing instructions, typically in the form of coded or interpreted software instructions. For instance, a processing unit as described may be a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, memory elements, or any combination(s) thereof designed to control various locator functions, such as those described subsequently herein.

The electronic circuitry may further include a plurality of sensing units, including but not limited to, motion sensors, such as accelerometers, gyroscopes, magnetometers, altimeters, other inertial sensors, temperature sensors, humidity sensors, light sensors, barometers, sound, gas, radiation sensors, and the like. Further, the electronic circuitry may include Bluetooth radios, Wi-Fi, and/or other wireless communication devices, cameras and/or other imaging sensors, audio sensors or recorders, global positioning satellite (GPS) sensors, global navigation satellite system (GNSS), or other satellite navigation sensors incorporated therein.

The locating device <NUM> may also include a ground tracking device <NUM> coupled to the central mast <NUM> for tracking positions such as translational and rotational movements of the locating device <NUM> with respect to the ground. The ground tracking device <NUM> may be a stereo optical ground tracking device having one or more imagers for tracking ground features of the utility path which may be utilized to track the positions of the locating device <NUM>. These ground features may be correlated in time to determine height of the locating device <NUM> from the ground surface and various other measurements. Further, the ground features may be correlated in time to calculate motion vectors facilitating precise determination of translational movements and rotations of the locating device. The determined height, translational movements and rotations, may be used to determine depth and orientation of the buried utility <NUM> (<FIG> and <FIG>).

An exemplary block diagram of the locating device <NUM> may be seen in <FIG>. As shown in the <FIG>, the locating device <NUM> may include one or more antenna nodes <NUM> and <NUM> and a receiver circuit <NUM> coupled to the antenna nodes <NUM> and <NUM>. The receiver circuit <NUM> may include a receiver input <NUM>, an electronic circuitry <NUM>, and a receiver output <NUM>. The locating device <NUM> may further include a processing unit <NUM> coupled to the receiver circuit <NUM>, a sensing unit <NUM> having a plurality of sensors coupled to the processing unit <NUM>, a storage unit <NUM> that may be an internal memory or an external memory (e.g. a USB) coupled to the processing unit <NUM>, an audio unit <NUM> coupled to the processing unit <NUM>, and a display unit <NUM> also coupled to the processing unit <NUM>.

The processing unit <NUM> may include one or more processing elements <NUM>, such as a user interface (UI) processor (not shown) coupled to the audio unit <NUM> and the display unit <NUM>, a data processor (not shown) coupled to the UI processor and the storage unit <NUM> (e.g. a USB), a motion processor (not shown) having sensing unit <NUM> coupled to the data processor, and a field-programmable gate array (FGPA, not shown) having associated digital filter(s), such as Discrete Fourier Transform (DFT) filter(s) coupled to the data processor and the antenna nodes <NUM> and <NUM>. The processing unit <NUM> may further include a location identification module <NUM>, a timing circuit <NUM>, and a utility classification module <NUM> coupled to the processing elements <NUM>.

According to one aspect, the antenna nodes <NUM> and <NUM> are configured to sense magnetic fields that may include active magnetic field signals directly associated with the buried utility, such as active transmitters bleed off signals, and passive magnetic field signals (e.g., broadcast signal) radiated from a radio broadcast station (e.g., AM radio station), which when encountering a portion of a buried utility, induces a current in the buried utility that generates an electromagnetic field around the buried utility, or other induced magnetic field signals induced by induction device(s), such as an induction stick (not shown). In an example, the magnetic fields may be sensed at different frequencies and/or different bandwidths. Besides buried utilities, the sensed magnetic fields may also include magnetic fields emitted from other metallic or conductive objects buried in a close proximity to the buried utilities. Upon sensing, the antenna nodes <NUM> and <NUM> provide antenna output signals, which are subsequently received by the receiver input <NUM> and provided to the electronic circuitry <NUM> for processing. After processing, the electronic circuity <NUM> provides the processed signals to the receiver output <NUM> which may then provide the processed signals as receiver output signals to the processing unit <NUM>. Also, the sensing units may be configured to sense various parameters associated with the movement of the locating device <NUM> and/or movement of the vehicle carrying the locating device <NUM>, and provide, in response to the sensing, sensor data to the processing unit <NUM>.

At the processing unit <NUM>, one or more processing elements <NUM> may be configured to process the receiver output signals that include sensed magnetic fields and the sensor data obtained from the sensing unit <NUM> utilizing the location identification module <NUM> coupled to the processing elements <NUM>. The processing carried out by the location identification module <NUM> may include distinguishing the magnetic fields that pertain to the buried utilities <NUM> from noise or false magnetic field signals emitted by jammers or other metallic or conductive objects buried in a close proximity to the buried utilities <NUM> (<FIG> and <FIG>) based on evaluation of various parameters including, not in a limiting sense, magnitude of the magnetic fields, gradients of the magnetic fields (e.g. gradients in a horizontal direction of the magnetic fields), and angle of elevation of the magnetic fields.

Upon distinguishing the magnetic fields, the location identification module <NUM> may eliminate the magnetic fields emitted by general noise, self-noise or false signals emitted by other metallic or conductive objects and consider only those magnetic fields that pertain to the buried utilities <NUM> (<FIG> and <FIG>) to generate or identify utility data pertaining to the buried utilities, whereby the utility data includes a plurality of location data points indicative of location information pertaining to the buried utilities at various geographical instances of the multi-utility region. The utility data also includes associated characteristics of the buried utilities <NUM> (<FIG> and <FIG>) and one or more timestamps generated by the timing circuit <NUM> for associating with the location data points. The timestamps may include a calendar date and a time registered with a predefined degree of accuracy, say, accuracy to second, millisecond, and/or nanosecond. In one example, the timing circuit may include a clock (not shown) that is adjusted automatically based on a timing signal provided by a remote master clock operating according to a UTC (Coordinated Universal Time).

The utility data may additionally include information related to presence or absence, position, depth, current flow, magnitude, phase, and/or direction, and/or orientation of underground utility lines and/or other conductors, information about soil properties, other changes in properties of pipes or other conductors in time and/or space, quality metrics of measured data, and/or other aspects of the utility, and/or the locate environment, as well as data received from various sensing units such as motion sensors, such as accelerometers, gyroscopes, magnetometers, altimeters, and the like, temperature sensors, humidity sensors, light sensors, barometers, sound, gas, radiation sensors, and other sensors provided within or coupled to the locating device(s) <NUM>. Also, the utility data may include data received from ground tracking device(s).

In some embodiments, subsequent to distinguishing the magnetic fields and identifying the magnetic fields that pertain to the buried utilities <NUM> (<FIG> and <FIG>), further processing such as sampling of the magnetic fields that pertain to the buried utilities <NUM> (<FIG> and <FIG>) may be carried out using discrete Fourier transform (DFT) filter(s). Sampling for the magnetic fields directly emitted from the buried utilities <NUM> may be carried out, for example, at a first predefined sampling rate (e.g., sampling rate from <NUM>-<NUM>), and sampling for the magnetic fields radiated from a radio broadcast station such as those broadcast from AM broadcast radio tower <NUM>, which produces the electromagnetic field around the buried utilities <NUM> (<FIG> and <FIG>) may be carried out at a second predefined sampling rate (e.g., <NUM>). Subsequent to the distinguishing and sampling, a plurality of location data points may be identified.

The identified location data points may be received and processed by the utility classification module <NUM> to generate a plurality of clusters of location data points, whereby each of the clusters includes a set of location data points sharing common characteristics, including, substantially same underground depth, orientation, alignment, and placement relative to other objects, and the like. In an embodiment, the utility classification module <NUM> may generate clusters utilizing a conventionally known k-means clustering technique described in the book titled "<NPL>et al. However, in other embodiments, other known clustering or filtering methods/techniques may be utilized to generate the clusters.

The generated clusters may exhibit one or more patterns which are identified by the utility classification module <NUM> and are used to classify the clusters to uniquely identify or characterize the buried utilities <NUM> (<FIG> and <FIG>). For instance, the clusters "A" and "B" both may exhibit a pattern "X, " which may, for the purpose of this example, be spectral signatures that match with spectral signatures of an electricity line. Accordingly, the clusters "A" and "B" are classified as the electricity line. The patterns as referred to herein may include frequency spectrum depicting harmonics (e.g. odd harmonics and/or even harmonics) and/or rebroadcast frequencies, power spectrum, relative changes in the frequency and power spectrum, as well as phase or relative phase to other measured signals, etc. In one example, a pattern showing high relative power levels of <NUM> and relatively low amplitudes of higher powerline harmonics is most likely a main/larger AC power distribution line. In another example, a pattern showing high relative power of <NUM> and also potentially <NUM> and <NUM> is likely to be <NUM> phase distribution. In another example, a pattern showing <NUM> (single phase rectifier) and/or <NUM> (<NUM> phase rectifier) and low levels of AM coupling may be a cathodic protected pipe line. Also if an active multi-frequency transmitter is connected, then the power and phases of the higher frequencies will change quickly with distance away from the connection point depending on the utility type. Further, a utility that shows a lot of <NUM>, <NUM>, <NUM>, <NUM>, even harmonics may be connected to electronic equipment using rectifiers and switching power supplies. Broad band signals in the <NUM>-<NUM> range may be traffic signal control loops.

According to the invention, the utility classification module <NUM> generates one or more cluster quality metrics, and uniquely identifies each of the buried utilities based on such cluster quality metrics and detected patterns. Upon identification of the buried utilities, the utility classification module <NUM> correlates the location data points in the clusters spatially and in a time domain to trace the location of uniquely identified buried utilities <NUM>. Referring to the above cited example, the utility classification module <NUM> correlates the location data points in the clusters "A" and "B" according to geographical locations of the location data points and associated timestamps to trace the location of the electricity line.

<FIG> illustrate embodiments of a system <NUM> for uniquely identifying buried utilities in a multi-utility region.

As shown in the <FIG>, the system <NUM> includes one or more locating devices <NUM>, which may be hand-carried locating devices <NUM> and/or vehicle-mounted locating devices <NUM> communicatively coupled to a remote server/system <NUM> via a suitable wireless communication technology or via stored data transfer. The system <NUM> may further include one or more positioning devices <NUM> such as a high precision global position system (GPS) antennas, Global Navigation Satellite System (GNSS) antennas, or the like, operably coupled to the one or more locating devices <NUM>. These positioning devices <NUM> may be attached directly to the locating devices <NUM> and/or may be built into the locating devices <NUM> in a suitable form. The system <NUM> may further include active transmitter(s) <NUM> with one or more inductive clamp devices <NUM> for coupling signal to a target utility line such as buried utilities <NUM> measurable at the locating devices <NUM>.

Further, the system <NUM> may include other passive or active signal sources such as one or more AM broadcast radio towers <NUM>, induction stick devices <NUM>, or the like. System <NUM> may further include a vehicle <NUM> having multiple locating devices <NUM> for measuring magnetic field signals. One or more inductive device (not illustrated) may be mounted on the vehicle for inducing signal onto nearby utility lines. The signals <NUM> illustrated as emitting from buried utilities <NUM> may be active signals from the transmitter <NUM> and/or induction stick device <NUM> and/or present in the utility line (e.g., such as the electromagnetic signal inherently emitted from current flow through a powerline or line for telecommunications <NUM>) and/or may be coupled via other electromagnetic signal transmission sources (e.g., overhead powerlines, AM radio broadcast towers <NUM>, or the like) that may be measured at the locating device <NUM>.

Turning to <FIG>, the remote server <NUM> as described above may include a database <NUM>, which may be an internal repository implemented within the remote server <NUM>, or an external repository associated with the remote server <NUM>. The remote server <NUM> may be any electronic system/device capable of computing, such as a computer, a server, a cluster of computers or servers, cloud computing, server farm, server farms in different locations, etc. The remote server <NUM> may include multiple and separate components that may be electrically connected or interfaced with one another as appropriate.

In an embodiment, the remote server <NUM> may be implemented in a cloud environment where the remote server <NUM> may correspond to a cloud server operably coupled to the locating devices <NUM>, and the database <NUM> may correspond to a cloud database coupled to the cloud server. The remote server <NUM> may be accessible to one or more electronic devices associated with the locating devices <NUM>, a vehicle carrying the locating device <NUM>, and/or its user/operator, via a communication link, which may include a satellite communication, or any type of network or a combination of networks. For example, network may include a local area network (LAN), a wide area network (WAN) (e.g., the Internet), a metropolitan area network (MAN), an ad hoc network, a cellular network, a radio network, or a combination of networks.

The electronic device may include a display device (e.g. a display unit <NUM> provided on the locating device <NUM> or a separate display device remotely coupled to the locating device <NUM>), and a computing device or a wireless telecommunications device such as smart phone, personal digital assistant (PDA), wireless laptop, a notebook computer, a navigational device (e.g. a global positioning system (GPS) device), or any portable device capable of displaying and/or manipulating the maps or executing a navigation application. The electronic devices may further include vehicle mounted display devices. In one example, the remote server may include a software application hosted thereon, which is accessible by the electronic device. In another example, the remote server may provide proprietary programs or applications (apps) executable on each of the electronic devices.

As shown in the <FIG>, one or more locating devices <NUM> coupled to one or more remote servers <NUM> includes, amongst other components, a location identification module <NUM> to identify utility data from magnetic fields sensed by the locating devices <NUM>. The utility data includes a plurality of location data points indicative of location information pertaining to the buried utilities at various geographical instances of the multi-utility region. The locating devices <NUM> may also include one or more positioning devices <NUM> associated thereto, to convert location information indicated by the location data points into an absolute position capable of being represented in a universal coordinate system (e.g., in terms of latitude and longitude). The identified location data points may be provided to the remote server <NUM>.

The remote server <NUM> may include a processing unit <NUM>, a memory <NUM> coupled to the processing unit <NUM>, interface(s) <NUM>, a utility classification module <NUM> coupled to the processing unit <NUM>, and a mapping module <NUM> coupled to the processing unit <NUM>. The remote server <NUM> may further include the database <NUM> configured to centrally maintain the utility data obtained from one or more locating devices <NUM>. The database may either be an external database coupled to the remote server <NUM>, or an internal database implemented within the memory <NUM> of the remote server <NUM>.

The processing unit <NUM> may include a single processor, or multiple processors, all of which could include multiple computing units. The processor(s) may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, field-programmable gate arrays (FPGA), and/or any devices that manipulate signals based on operational instructions. Among other capabilities, the processor(s) is configured to fetch and execute computer-readable instructions and data stored in the memory.

The memory <NUM> may include any computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes.

The interface(s) <NUM> may include input/output interfaces and a graphical user interface enabling a user to communicate with the remote server by requesting and receiving information therefrom.

The utility classification module <NUM> and the mapping module <NUM> may be different modules that may include, amongst other things, routines, programs, objects, components, data structures, or software instructions executable by the processing unit <NUM> to perform particular tasks or methods of the present disclosure.

Upon receiving the utility data including location data points from the locating devices <NUM>, the processing unit <NUM> within the remote server <NUM> may process the locating data points utilizing the utility classification module <NUM> coupled to the processing unit <NUM>. As described in the foregoing, in addition to the location data points, the utility data also includes characteristics of the buried utilities associated with each of the location data points, and one or more timestamps associated with the location data points. Based on such characteristics, the utility classification module <NUM> clusters the location data points into a plurality of clusters <NUM>, whereby each of the clusters <NUM> includes a set of location data points sharing common characteristics.

The clusters <NUM> may exhibit one or more patterns <NUM> which are identified by the utility classification module <NUM>. Based on such patterns <NUM>, the utility classification module <NUM> classifies the clusters <NUM> to uniquely identify the buried utilities <NUM>. Data (e.g., classification data <NUM>) obtained as a result of classification may be stored in the database <NUM>. Further, the utility classification module <NUM> correlates the location data points in the clusters <NUM>, spatially and in a time domain based on the timestamps, to trace the location of the uniquely identified buried utilities <NUM>. The traced location may be probable location(s) of a buried utility, or an optimized location of a buried utility. The probable location(s) may be determined, for example, based on applying a pre-configured probability estimation algorithm on the correlated location data points, and/or the optimized location may be determined, for example, based on applying a preconfigured optimization algorithm on the correlated location data points. In some embodiments, the utility classification module <NUM> may utilize a combination of preconfigured algorithms to first determine probable location(s) of the buried utilities and then derive an optimized location of the buried utilities therefrom.

<FIG> illustrates an embodiment of a method <NUM> for uniquely identifying buried utilities.

The method <NUM> may be initiated at block <NUM>, where the method <NUM> includes sensing magnetic fields upon moving a magnetic field sensing locating device over a multi-utility region that is comprised of a plurality of buried utilities (such as the multi-utility region <NUM> illustrated in <FIG>). For example, one or more locating devices <NUM> (<FIG> and <FIG>) including hand carried magnetic field sensing locating devices (<FIG>) and/or vehicle-mounted locating devices (locating device <NUM> of <FIG>), or a combination thereof, may be moved over the multi-utility region (such as multi-utility region <NUM> of <FIG>) to be searched to sense magnetic fields emitted therefrom. The sensed magnetic fields may include magnetic fields emitted by the buried utilities and/or those emitted by the other metallic or conductive objects buried in proximity to the buried utilities such as rebar in concrete, railroad spurs, ground pipe alignment, and the like.

At block <NUM>, the method <NUM> includes identifying utility data pertaining to the plurality of buried utilities from the sensed magnetic fields, wherein the utility data comprises a plurality of location data points. The locating device(s) <NUM> (<FIG> and <FIG>) may include a processing unit and associated modules, configured to process the sensed magnetic fields to identify only those magnetic fields that pertain to the buried utilities <NUM> (<FIG> and <FIG>). The processing may include evaluating various parameters including, not in a limiting sense, magnitude of the magnetic fields, gradients of the magnetic fields (e.g., in a horizontal direction), and angle of elevation of the magnetic fields and determining whether such parameters related to the magnetic fields are within their respective predefined range. Based on the determination, the magnetic fields having corresponding parameters in their predefined range are identified as buried utilities, and other magnetic fields are eliminated as noise signals.

The processing may further include identifying, using a digital filter, a subset of the collected magnetic fields as a sliding window, and thereafter moving the sliding window through the magnetic fields collected at various geographical instances of the multi-utility region to test whether the magnetic fields at each of such geographical instances are outliers of the magnetic fields in the sliding window. The magnetic fields that are tested as outliers may be identified to be those that are emitted from the buried utilities, and other magnetic fields may be ignored or eliminated as noise. Subsequent to processing, utility data pertaining to the buried utilities is identified from the magnetic fields that pertain to the buried utilities. The utility data includes a plurality of location data points indicative of location information pertaining to the buried utilities at various geographical instances of the multi-utility region.

At block <NUM>, the method <NUM> includes generating a plurality of clusters based on the identified location data points, wherein each of the clusters includes a set of location data points sharing common characteristics. The locating device(s) <NUM> (<FIG> and <FIG>) and/or a remote server <NUM> (<FIG> and <FIG>) coupled to the locating device(s) may process the identified location data points. The processing includes clustering sets of location data points that share common characteristics into a plurality of clusters using a clustering method/ technique. The clustering method, in one example, may be a k-means clustering method. The clustering may be performed in real-time or near real time. The processing further includes generating one or more cluster quality metrics used for distinguishing the clusters from each other.

At block <NUM>, the method <NUM> includes identifying one or more patterns exhibited by the clusters. The locating device(s) <NUM> (<FIG> and <FIG>) and/or the remote server <NUM> (<FIG> and <FIG>) may identify one or more patterns exhibited by the clusters. In the context of the present disclosure, the term "patterns" may be understood as one or more unique characteristics of the buried utility capable of distinguishing the buried utility from other buried utilities. The patterns may be identified in real-time or during post processing.

At block <NUM>, the method <NUM> includes classifying the clusters based on the patterns to uniquely identify each of the buried utilities. The locating device(s) <NUM> (<FIG> and <FIG>) and/or the remote server <NUM> (<FIG> and <FIG>) are configured to classify the clusters based on the identified patterns to uniquely identify or characterize the buried utilities. The locating device(s) <NUM> (<FIG> and <FIG>) and/or the remote server <NUM> (<FIG> and <FIG>), classify the clusters based further on the cluster quality metrics to uniquely identify each of the buried utilities. The classification may be performed in real-time or during post-processing.

At block <NUM>, the method <NUM> includes correlating the location data points in the clusters, spatially and in a time domain, to trace location of the uniquely identified buried utilities. The locating device(s) <NUM> (<FIG> and <FIG>) and/or the remote server <NUM> (<FIG> and <FIG>) are configured to obtain the geographical location information (e.g. latitude and longitude) and timestamps associated with the location data points, and correlate the location data points in the clusters both spatially and in a time domain to organize/arrange the location data points to trace the location of the uniquely identified buried utilities.

At block <NUM>, the method <NUM> may include mapping the buried utilities and corresponding traced locations on a geographical map of the multi-utility region. The locating device(s) <NUM> (<FIG> and <FIG>) and/or remote server <NUM> (<FIG> and <FIG>) may be configured to map the buried utilities and their corresponding locations on the geographical map of the multi-utility region, which may be transmitted to users on their respective electronic devices. Mapping may include aligning the buried utilities on a base map (e.g. pre-existing geographical map) of the multi-utility region based on the traced location or vice-versa.

<FIG> illustrates an example of a multi-utility region <NUM>, which is an intersection having a plurality of buried utilities <NUM> buried therein in a close distance from each other. In this example, one or more locating devices <NUM>, such as a hand-carried locating device and/or vehicle-mounted locating device, may be moved over the multi-utility region <NUM> to search for the buried utilities <NUM>. In general, the presence of a buried utility is detected by the locating device upon sensing magnetic fields from a surface of a geographical region. However, the magnetic fields sensed by the locating device <NUM> may not necessarily be emitted only from buried utilities. The magnetic fields may also be emitted from other metallic or conductive objects buried in proximity to the buried utilities. Therefore, the magnetic fields that are sensed by the locating device(s) <NUM> may include magnetic fields emitted by the buried objects and/or those emitted by the other buried objects.

According to various embodiments of the present disclosure, the locating device(s) <NUM> may include a processing unit and associated modules for processing the sensed magnetic fields and identifying only those magnetic fields that pertain to the buried utilities <NUM>. The processing may include determining magnitude of the magnetic fields, evaluating gradients in a horizontal direction of the magnetic fields, measuring angle of elevation of the magnetic fields, and the like, to eliminate the noise, i.e., the magnetic fields emitted from other metallic or conductive objects that are not utilities. After processing, for example, of noise elimination (see <FIG>), utility data pertaining to the buried utilities may be identified. The utility data may include a plurality of location data points indicative of location information pertaining to the buried utilities at various geographical instances of the multi-utility region <NUM>.

The locating device(s) <NUM> (<FIG>, <FIG>, and <FIG>) and/or a remote server <NUM> (<FIG> and <FIG>) coupled to the locating device(s) <NUM> (<FIG>, <FIG>, and <FIG>) process the identified location data points based on a clustering algorithm to generate a plurality of clusters each including a set of location data points that share common characteristics. In some embodiments, a k-means clustering algorithm may be used for clustering the location data points. The k-means clustering is a distance-based clustering algorithm partitioning a data set into a predetermined number of clusters "k. " The k-means clustering algorithm finds a locally optimum way to cluster the dataset into "k" partitions so as to minimize the average difference between the mean of each cluster (cluster centroid "X") and every member of that cluster. The difference is measured by a distance metric such as Euclidean or Cosine distance metric. For example, the "Cluster <NUM>, " "Cluster <NUM>, " "Cluster <NUM>, " "Cluster <NUM>, " "Cluster <NUM>, " "Cluster <NUM>, " and "Cluster <NUM>" are formed, as may be seen in the <FIG>. Such clusters may be formed as a result of execution of the k-means clustering algorithm graphic <NUM> depicted in <FIG>, wherein "K" represents the number of clusters, which is <NUM> in this example, and "X" represents the centroid.

For each of the clusters, the locating device(s) <NUM> (<FIG>, <FIG>, and <FIG>) and/or the remote server <NUM> (<FIG> and <FIG>) may identify one or more patterns exhibited by such clusters. A pattern may be a unique characteristic of the buried utility line. As illustrated in <FIG>, the following patterns are identified: "Pattern W, " "Pattern X, " "Pattern Y, " and "Pattern Z. " Based on such patterns, the clusters may be classified. As shown, "Cluster <NUM>" and "Cluster <NUM>" are classified according to "Pattern W, " which is indicative of a buried utility "Gas Pipeline A. " Further, "Cluster <NUM>" and "Cluster <NUM>" are classified according to "Pattern X," which is indicative of a buried utility "Electricity Line B. " Further, "Cluster <NUM>" is classified according to "Pattern Y, " which is indicative of a buried utility "Telephone Line C, " and finally "Cluster <NUM>" and "Cluster <NUM>" are classified according to "Pattern Z, " which is indicative of a buried utility "Fiber Optic Cable D.

Once each of the buried utilities is uniquely identified, the locating device(s) <NUM> (<FIG>, <FIG>, and <FIG>) and/or the remote server <NUM> (<FIG> and <FIG>) correlates the location data points in the clusters to trace the location of the buried utilities. The location tracing may be used for mapping the uniquely identified buried utilities on a geographical map <NUM> (<FIG>) of the multi-utility region <NUM>. The mapping may be carried out by the mapping module <NUM> associated with the locating device(s) and/or the remote server.

<FIG>, <FIG>, and <FIG> illustrate exemplary geographical maps generated by the mapping module <NUM>.

As shown in <FIG>, the geographical map may include probability contour(s) 434A, 434B, 434C, and/or 434D indicative of probable location(s) of the buried utilities. In an embodiment, when a particular probability contour 434A, 434B, 434C, or 434D is selected on the geographical map <NUM>, the geographical map <NUM> may additionally display probability scores associated with the selected probability contour 434A, 434B, 434C, or 434D. The probability score may be in the form of a percentage, or another suitable form. As an instance, a probability score of <NUM>% may indicate that there is <NUM>% probability that the buried utility is within the region depicted by the probability contour.

As shown in <FIG>, the probability contours 434A, 434B, 434C, and/or 434D may be a combination of individual contours defined by separate clusters, which may connected (e.g., by a dotted line) on a geographical map <NUM> to indicate probability of the individual connected contours to be the same utility. Such probability contours may also have probability scores associated therewith.

As shown in <FIG>, the geographical map <NUM> may be an optimized map indicative of optimized locations 436A, 436B, 436C, and/or 436D of each of the buried utilities.

In some embodiments, the geographical map may be a heat map whereby a hierarchy of gradient and/or gradient tensor values may be represented by color, shading, patterns, and/or other representation of measured gradients at locations within the map. Further, the geographical map may be a user navigable map depicting the buried utility/utilities <NUM> (<FIG>, <FIG>, and <FIG>) within the multi-utility region, and directing a user to the desired buried utilities. The geographical map may include images and/or videos of the buried location(s) to assist the user with finding the location.

In certain embodiments, the geographical map may additionally include reference data to nearby objects, such as landmarks, curbs, sidewalks, poles, and survey markers, to further assist the user in finding the location. For this purpose, one or more rangefinder devices, such as a laser rangefinder (not shown) may be provided with the locating device <NUM> (<FIG>, <FIG>, and <FIG>) either as an in-built device or a separate device coupled to the locating device <NUM> (<FIG>, <FIG>, and <FIG>). Such rangefinder device(s) detect one or more reference objects in the vicinity of the buried utilities, and determine, at each of the location data points, an orientation and/or placement of the locating device <NUM> (<FIG>, <FIG>, and <FIG>) relative to the reference objects, which is stored as reference data into the locating device <NUM>. The mapping module <NUM> (<FIG>) associated with the locating device <NUM> (<FIG>, <FIG>, and <FIG>) may receive this reference data and subsequently map or tag the reference data with the buried utilities and their traced locations on the geographical map to further assist the users in precisely locating the buried utilities.

Further, in certain embodiments, one or more cameras or other optical sensors used as mark reader devices (not shown) may be provided with the locating device <NUM> (<FIG>, <FIG>, and <FIG>) either as an in-built device or a separate device coupled to the locating device <NUM> (<FIG>, <FIG>, and <FIG>), to detect/read pre-existing markers including paint marks. Likewise, the locating device <NUM> (<FIG>, <FIG>, and <FIG>) may include a buried marker device exciter and/or buried marker device reader either as an in-built device or a separate device optionally coupled to the locating device <NUM> (<FIG>, <FIG>, and <FIG>) to excite and detect/read buried electronic markers such as radio frequency identification/underground field identification tags or other marker devices/balls associated with buried utilities, to collect additional information pertaining to the buried utilities. Such additional information may also be mapped or tagged to corresponding buried utilities and their traced locations on the geographical map. Further, such information may allow the buried utilities to be aligned to a base map of the multi-utility region or vice versa.

The geographical map, thus generated, may be transmitted to respective one or more electronic user devices <NUM> (<FIG>) associated with the locating devices <NUM> (<FIG>, <FIG>, and <FIG>). Alternatively, the traced location of the buried utilities <NUM> (<FIG>, <FIG>, and <FIG>) and associated reference data and/or additional information obtained from markers may be overlaid or mapped to a pre-existing map of the multi-utility region preloaded onto the electronic user device(s) <NUM> (<FIG>). Data (e.g., mapping data <NUM>, <FIG>) related to the uniquely identified buried utilities, traced location of such buried utilities, and/or the generated geographical map may be stored into the database <NUM> (<FIG>).

It is to be understood that the order in which the method <NUM> (<FIG>) is described is not intended to be construed as a limitation, and any number of the described method blocks can be combined in any order to implement the method, or alternative methods. Additionally, individual blocks may be deleted from the method without departing from the scope of the invention, which is solely defined by the appended claims.

In one or more exemplary embodiments, the functions, methods, and processes described may be implemented in whole or in part in hardware, software, firmware, or any combination thereof. Computer-readable media include computer storage media.

By way of example, and not limitation, such computer-readable media can include RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.

The various illustrative functions, modules, and circuits described in connection with the embodiments disclosed herein with respect to locating and/or mapping, and/or other functions described herein may be implemented or performed in one or more processing units or modules with a general purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a field programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components, or any combination thereof designed to perform the functions described herein.

The disclosures are not intended to be limited to the aspects shown herein, but are to be accorded the full scope consistent with the specification and drawings, wherein reference to an element in the singular is not intended to mean "one and only one" unless specifically so stated, but rather "one or more. As an example, "at least one of: a, b, or c" is intended to cover: a; b; c; a and b; a and c; b and c; and a, b and c.

Claim 1:
A method for uniquely identifying buried utilities or utilities that are hidden from direct view or access (<NUM>) in a multi-utility region, the method comprising:
sensing magnetic fields upon moving a magnetic field sensing locating device (<NUM>) over a multi-utility region comprising a plurality of said utilities;
identifying utility data pertaining to the plurality of said utilities from the sensed magnetic fields, wherein the utility data comprises a plurality of location data points each indicative of location information pertaining to at least one of the said utilities and one or more characteristics of the at least one of the said utilities;
generating a plurality of clusters (<NUM>) based on the identified location data points, wherein each of the clusters includes a set of location data points sharing common characteristics of one or more of depth, orientation and alignment;
characterized in that the method further comprises :
identifying one or more patterns (<NUM>), including one or more of: a frequency spectrum, a power spectrum, a harmonics pattern, a rebroadcast frequencies pattern, a spectral signature, relative changes in the frequency and power spectrum, and phase or relative phase to other measured signals, exhibited by each of the plurality of clusters;
generating a cluster quality metric for the plurality of clusters (<NUM>);
classifying the clusters, based on the one or more patterns and the cluster quality metric, to uniquely identify the said utilities; and
correlating the location data points in the clusters, spatially and in a time domain, based at least on timestamps associated with the location data points, to trace location of the uniquely identified said utilities.