SYSTEM, MACHINE, AND METHOD FOR MONITORING AND MITIGATING WORKSITE MACHINE COLLISION

TECHNICAL FIELD

[0001]The present disclosure relates, in general, to detecting machine collisions. More particularly, the present disclosure related to a system, a machine, and a method for monitoring and mitigating worksite machine collisions.

BACKGROUND

[0002]Typically, a worksite such as an underground mine site presents a challenging environment for movement of machines due to undesirable and unpredictable worksite conditions including, but not limited to, limited availability of space for the machines to move, uneven operating roads or pathways, limited illumination of the pathways, presence of operator blind spots along the pathways, tunnel wall protrusions, and obstructions such as rocks along the operating pathways. As a result, the machines operating in the mine site tend to get damaged during the movement due to inadvertent abrasions against tunnel wall protrusions, or collisions with other machines or mine site structures. Repeated instances of such machine damage or collisions may warrant unscheduled maintenance or repair of the machines or the mine sites, thereby causing unnecessary downtimes, loss of productivity, and increase in production costs. Therefore, it may be desirable to mitigate such instances of machine damage or collisions within the mine site to improve a lifespan of the machines, productivity, and operation efficiency, and minimize machine or site maintenance costs.

[0003]U.S. Pat. No. 11,963,065, herein referred to as “the US '065 reference”, relates to a system that processes information associated with a potential collision of a vehicle to reliably determine whether a collision occurred and/or determine one or more characteristics of the collision. In response to obtaining information, the system analyses the data describing the movement of the vehicle before and/or after a time associated with the potential collision. The system carries out the analysis using a trained classifier that classifies the vehicle movement data into one or more classes. If a collision is determined to be likely, the system triggers one or more actions based on the characteristics of the collision. The US '065 reference merely discloses a collision detection system for the vehicle for inferring whether the collision has occurred and ensuring that remedial actions are taken thereafter. However, in addition to detection or inferring such collisions, it may also be necessary to prevent or mitigate such collisions within the worksite.

SUMMARY

[0004]In one aspect of the present disclosure, a system for mitigating worksite machine collisions is disclosed. The system includes a processor and a memory for storing instructions that when executed by the processor, causes the processor to receive at least one input from at least one monitoring device associated with at least one machine operating within a worksite. The processor is also configured to detect at least one collision event associated with the at least one machine corresponding to at least one work area of a plurality of work areas within the worksite based on the at least one received input. Further, the processor is configured to determine a severity of the at least one detected collision event corresponding to the at least one work area based on a model. In addition, the processor is configured to identify, via the model, at least one collision zone within the worksite based on the determined severity. The at least one collision zone includes at least one collision zone work area of the plurality of work areas. Furthermore, the processor is configured to perform, via the model, at least one corrective action based on the at least one identified collision zone.

[0005]In another aspect of the present disclosure, a machine including a processor, memory, and at least one monitoring device is disclosed. The processor is configured to receive at least one input from the at least one monitoring device. The processor is also configured to detect at least one collision event associated with the at least one machine corresponding to at least one work area of a plurality of work areas within the worksite based on the at least one received input. Further, the processor is configured to determine a severity of the at least one detected collision event corresponding to the at least one work area based on a model. In addition, the processor is configured to identify, via the model, at least one collision zone within the worksite based on the determined severity. The at least one collision zone includes at least one collision zone work area of the plurality of work areas. Furthermore, the processor is configured to perform, via the model, at least one corrective action based on the at least one identified collision zone.

[0006]In yet another aspect of the present disclosure, a method for mitigating worksite machine collisions is disclosed. The method includes receiving at least one input from at least one monitoring device associated with at least one machine operating within a worksite. The method also includes detecting at least one collision event associated with the at least one machine corresponding to at least one work area of a plurality of work areas within the worksite based on the at least one received input. Further, the method includes determining a severity of the at least one detected collision event corresponding to the at least one work area based on a model. In addition, the method includes identifying, via the model, at least one collision zone within the worksite based on the determined severity. The at least one collision zone includes at least one collision zone work area of the plurality of work areas. Furthermore, the method includes performing, via the model, at least one corrective action based on the at least one identified collision zone.

BRIEF DESCRIPTION OF DRAWINGS

[0007]FIG. 1 is an exemplary illustration of an environment in accordance with which various embodiments of the present disclosure may be implemented;

[0008]FIGS. 2-3 are exemplary illustrations of monitoring devices provided in a machine employed in the environment of FIG. 1, in accordance with embodiments of the present disclosure;

[0009]FIG. 4 is a schematic block diagram of an exemplary machine system of the machine employed in the environment of FIG. 1 for mitigating worksite machine collisions, in accordance with the embodiments of the present disclosure;

[0010]FIG. 5 is an exemplary flowchart of the machine system of FIG. 4 detecting a longitudinal machine collision of the machine employed in the environment of FIG. 1, in accordance with the embodiments of the present disclosure;

[0011]FIG. 6 is a schematic block diagram of an exemplary monitoring system employed in the environment of FIG. 1 for mitigating worksite machine collisions, in accordance with the embodiments of the present disclosure; and

[0012]FIG. 7 is a flowchart of an exemplary method for mitigating worksite machine collisions, in accordance with the embodiments of the present disclosure.

DETAILED DESCRIPTION

[0013]Reference will now be made in detail to specific embodiments or features, examples of which are illustrated in the accompanying drawings. Generally, corresponding reference numbers may be used throughout the drawings to refer to the same or corresponding parts, e.g., 1, 1′, 1″, 101 and 201 could refer to one or more comparable components used in the same and/or different depicted embodiments.

[0014]Referring to FIG. 1, an environment 100, herein referred to as ‘worksite 100’, including one or more machines, for example, 105-1, 105-2, 105-3, and 105-4, and a system 110 for mitigating worksite machine collisions is disclosed. Examples of the worksite 100 include, but are not limited to, an underground mine site, a construction site, and a quarry. Examples of the machines, for example, 105-1, 105-2, 105-3, and 105-4 include, but are not limited to, haul trucks, water trucks, loaders, excavators, shovels, and tractors. In an embodiment, the system 110 corresponds to a machine system, for example, 115-1, 115-2, 115-3, 115-4 provided in each machine of the machines, for example, 105-1, 105-2, 105-3, 105-4. In another embodiment, the system 110 corresponds to a monitoring system 120 in communication with the machines, for example, 105-1, 105-2, 105-3, and 105-4 via a network 125. Examples of the machine system, for example, 115-1, 115-2, 115-3, 115-4 and/or the monitoring system 120 include, but are not limited to, computers, laptops, mobile devices, handheld devices, personal digital assistants (PDAs), tablet personal computers, digital notebook, wearables, and other electronic devices known to persons skilled in the art for performing functions consistent with the present disclosure. In embodiments, the machines, for example, 105-1, 105-2, 105-3, and 105-4 are in direct communication with each other via the network 125. Examples of the network 125 include, but are not limited to, a Local Area Network (LAN), a Wireless Local Area Network (WLAN), a Small Area Network (SAN), a Wi-Fi Direct Network and a telecommunication network including, but not limited to, a fourth generation (4G) and a fifth generation (5G) cellular network. In embodiments, the machines, for example, 105-1, 105-2, 105-3, and 105-4 may also be in indirect communication with each other via the network 125 and the monitoring system 120.

[0015]In embodiments, the worksite 100 may also include one or more electronic devices, for example, 130-1, 130-2, 130-3, and 130-4 associated with the machines, for example, 105-1, 105-2, 105-3, and 105-4 respectively. In embodiments, the electronic devices, for example, 130-1, 130-2, 130-3, 130-4 may be employed by operators operating the machines, for example, 105-1, 105-2, 105-3, and 105-4 respectively. Examples of the electronic devices, for example, 130-1, 130-2, 130-3, 130-4 include, but are not limited to, computers, laptops, mobile devices, handheld devices, personal digital assistants (PDAs), tablet personal computers, digital notebook, wearables, and other electronic devices known to persons skilled in the art for performing functions consistent with the present disclosure. In embodiments, the machines, for example, 105-1, 105-2, 105-3, and 105-4 include one or more monitoring devices, for example, 135-1, 135-2, 135-3, and 135-4 respectively. Examples of the monitoring devices, for example, 135-1, 135-2, 135-3, and 135-4 include, but are not limited to, one or more inertial measurement units, one or more cameras, and one or more sensors or sensing and/or transmitting devices. Examples of the sensors include, but are not limited to, Global Positioning System (GPS) sensors or tracking units, impact or touch sensors, and motion sensors. Examples of the sensing and/or transmitting devices include, but are not limited to, machine localizer systems configured to transmit or receive radio signals. In embodiments, the monitoring devices, for example, 135-5, 135-6 are also provided in one or more work areas, for example, 140-1, 140-2 within the worksite 100. Examples of the monitoring devices, for example, 135-5, 135-6, in the work areas, for example, 140-1, 140-2, include, but are not limited to, area localizer systems configured to transmit or receive radio signals. In embodiments, the monitoring devices, for example, 135-1, 135-2, 135-3, 135-4, 135-5, 135-6 are in communication with the machine system 115 and/or in communication with the monitoring system 120 via the network 125. In embodiments, the monitoring devices may also correspond to the electronic devices, for example, 130-1, 130-2, 130-3, 130-4 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 respectively.

[0016]Referring to FIGS. 2-3, exemplary illustrations of the inertial measurement units, for example, 205-1 and 205-2 provided as the monitoring devices, for example, 135-1 in each machine, for example 105-1, of the machines, for example, 105-1, 105-2, 105-3, and 105-4 is disclosed. In embodiments, a first inertial measurement unit, for example, 205-1 is provided in a front end, for example, a front portion of a chassis, of each machine, for example, 105-1. In embodiments, a second inertial measurement unit, for example, 205-2 is provided in a rear end, for example, a rear portion of the chassis, of each machine, for example, 105-1. It will be appreciated by those with ordinary skill in the art that multiple inertial measurement units such as 205-1, 205-2 may also be provided at different locations on the machine 105-4. The inertial measurement unit is an electronic device that includes, but is not limited to, one or more accelerometers, gyroscopes, and/or magnetometers. The inertial measurement unit is configured to measure and transmit one or more aspects associated with machine movements including, but not limited to, a specific force or acceleration of a machine, for example, 105-1, an angular rate, and an orientation of the machine, for example, 105-1. In embodiments, the inertial measurement units, for example, 205-1 and 205-2 are configured to measure machine accelerations in three orthogonal directions, for example, the lateral, longitudinal, and vertical directions defined in a Cartesian co-ordinate system, for example, in X, Y, and Z directions respectively. In an exemplary embodiment, each inertial measurement unit, for example, 205-1 includes at least one ±20 g accelerometer (not shown) having an accelerometer resolution of 2922 micro-g/second{circumflex over ( )}2, where g corresponds to acceleration due to gravity, ±20 g corresponds to a measurement range of 20 g of the accelerometer, and the resolution corresponds to a minimum change in acceleration measured by the accelerometer. In embodiments, each accelerometer within each inertial measurement unit, for example, 205-1 is contained within an enclosure (not shown) for protection against physical damage and high-pressure. In embodiments, the enclosure may be rigid and securely attached to a body (not shown) of each machine, for example, 105-1 to improve accuracy in acceleration measurements. In embodiments, an accelerometer output in a form of one or more accelerometer signals is provided to an anti-aliasing filter (not shown) provided in an analog-to-digital converter (not shown) to remove undesirable frequencies of vibrations such as, but not limited to, engine noise, from the accelerometer signal(s) and preserve desirable frequencies, for example, the frequencies associated with road roughness data, upon digitization. The road roughness data includes a roughness index that corresponds to a measure of undulation or deformation of a ground surface recorded per unit length of a path, for example, P1 or P2.

[0017]Referring again to FIG. 1, the system 110 is configured to receive at least one input from at least one monitoring device, for example, 135-4, associated with at least one machine, for example, 105-4 operating within the worksite 100. In embodiments, the system 110 is also configured to detect at least one collision event associated with the at least one machine, for example, 105-4 corresponding to at least one work area, for example, 140-2, 140-3, 140-4, 140-5 of the work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6 within the worksite 100 based on the at least one received input. In embodiments, a first path, for example, P1 within the worksite 100 is defined by one or more work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6 to be traversed by one or more machines, for example, 105-1, 105-2, 105-3, 105-4, in a sequence. It will be apparent to those with ordinary skill in the art that a reversed sequence of the work areas, for example, 140-6, 140-5, 140-4, 140-3, 140-2, 140-1 of the sequence may also define a second path, for example, P2 within the worksite 100. In embodiments, the second path P2 and the first path P1 may be same or different. In some embodiments, the second path P2 may include one or more work areas, for example, 140-7, different from the work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6. Further, the system 110 is configured to determine a severity of the at least one detected collision event corresponding to the at least one work area, for example, 140-2, 140-3 based on a model such as, but not limited to, one or more machine learning and/or artificial intelligence models. In addition, the system 110 is configured to identify, via the model, at least one collision zone, for example, 145-1, 145-2, 145-3, within the worksite 100 based on the determined severity. In embodiments, the at least one collision zone, for example, 145-1, 145-2, 145-3, includes at least one collision zone work area of the plurality of work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6. In embodiments, the at least one collision zone work area includes the work area(s), for example, 140-3, 140-4, 140-5 associated with the detected collision events. Furthermore, the system 110 is configured to perform, via the model, at least one corrective action based on the at least one identified collision zone, for example, 145-3, 145-4, 145-5. In embodiments, the corrective action may include, but not limited to, providing alerts, notifications, recommendations, and/or instructions to the machines, for example, 105-1, 105-2, 105-3, and 105-4, and/or the electronic devices 130-1, 130-2, 130-3, 130-4 regarding the at least one detected collision event, the determined severity and/or the at least one identified collision zone, for example, 145-1, 145-2, 145-3, and/or modifying one or more machine parameters including, but not limited to, machine speed associated with the machine(s), for example, 105-3 based on a proximity of the machine(s), for example, 105-3 to the at least one detected collision zone, for example, 140-3. One or more components of the system 110 and respective functions performed by each component of the system 110 will be described in detail hereinafter.

[0018]Referring to FIGS. 1 and 4, an exemplary block diagram of the system 110 corresponding to the machine system, for example, 115-4 for mitigating worksite machine collisions is disclosed. The machine system 115-4 includes a machine system bus 405 or other communication mechanism for communicating information, and a machine system processor 410 coupled with the machine system bus 405 for processing information. The machine system 115-4 also includes a machine system memory 415, such as a random-access memory (RAM) or other dynamic storage device, coupled to the machine system bus 405 for storing information and instructions to be executed by the machine system processor 410. The machine system memory 415 can be used for storing temporary variables or other intermediate information during execution of instructions to be executed by the machine system processor 410. The machine system, for example, 115-4 further includes a read only memory (ROM) 420 or other static storage device coupled to the machine system bus 405 for storing static information and instructions for the machine system processor 410.

[0019]In addition, the machine system, for example, 115-4 includes a machine system storage unit 425, such as a magnetic disk or optical disk, coupled to the machine system bus 405. The machine system storage unit 425 may store information associated with the machine, for example, 105-4. The information may include, but is not limited to, a type of the machine, a utility associated with the machine, at least one machine dimension such as a weight, height from a ground surface, a length, and/or a width of the machine, a current location of the machine, a machine identification associated with the machine, a map of the worksite 100 and a location of one or more work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6 (see FIG. 1), within the worksite 100 and on the map. The machine system storage unit 425 may also store work area condition data and/or historical data associated with the work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6 respectively. Examples of the work condition data include, but are not limited to, a ground surface data, a temperature data, and work area warning data. Examples of the historical data include, but are not limited to, information associated with historical collisions events detected or reported, a count of the historical collision events detected or reported, and a severity of each historical collision event detected or reported corresponding to each work area of the work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6. In embodiments, the machine system storage unit 425 is also configured to store one or more predefined or preset values, settings, and/or thresholds corresponding to one or more measurements such as, but not limited to, lateral and/or longitudinal acceleration data, received from the monitoring device(s), for example, 135-4. In embodiments, the machine system storage unit 425 is also configured to store one or more current or historical measurements including, but not limited to, the lateral and/or longitudinal acceleration data, received from the monitoring device(s), for example, 135-4. In embodiments, the machine system storage unit 425 may also store one or more machine learning, artificial intelligence, logical, and/or conditional modules, algorithms, and/or models, referred to hereinafter as the ‘model’. It may be understood that the information stored in the machine system storage unit 425 may be accessed by the machine system processor 410 via the machine system memory 415 to perform one or more functions.

[0020]The machine system, for example, 115-4 can be coupled via the machine system bus 405 to a machine system display unit 430, such as a light emitting diode (LED) and a liquid crystal display (LCD) for displaying information. One or more machine system input devices 435 are coupled to machine system bus 405 for communicating information and command selections to the machine system processor 410. In some embodiments, at least one input device of the machine system input devices 435 may be included in the machine system display unit 430, for example a touch screen that facilitates detection of multi-touch inputs from the user via the machine system display unit 430. In embodiments, the machine system input devices 435 may also correspond to peripheral input devices that may be paired with the machine system, for example, 115-4 via Bluetooth, Wi-Fi, Wi-Fi direct, or as a hardware connection such a USB peripheral to the machine system, for example, 115-4. Examples of the peripheral input devices include, but are not limited to, a joystick, machine seat controls, a gamepad, a keyboard, a mouse, a gesture-controlled device, or a wearable device such as, for example, a smart watch. In embodiments, the machine system input devices 435 may also include a microphone (not shown) configured to received audio inputs or instructions. In embodiments, the machine system input devices 435 may also include alphanumeric and other keys. Another type of machine system input devices is an input control 440, such as a mouse, a trackball, or cursor direction keys for communicating direction information and command selections to the machine system processor 410 and for controlling cursor movement on the machine system display unit 430. Additional examples of the machine system input devices 435 include, but are not limited to, a switch, a button, a lever, a joystick, a keyboard, the machine system display unit 430, and a remote-control device, such as, the electronic device, for example, 130-1, in communication with the machine system processor 410 via the network 125 and the machine system transceiver 445.

[0021]Various embodiments are related to the use of machine system for example, 115-4 for implementing the techniques described herein. In one embodiment, the techniques are performed by the machine system, for example, 115-4 in response to the machine system processor 410 executing instructions included in the machine system memory 415. Such instructions can be read into the machine system memory 415 from another machine-readable medium, such as the machine system storage unit 425. Execution of the instructions included in the machine system memory 415 causes the machine system processor 410 to perform the process steps described herein.

[0022]The term “machine-readable medium” as used herein refers to any medium that participates in providing data that causes a machine to operate in a specific fashion. In an embodiment implemented using the machine system, for example, 115-4, various machine-readable medium is involved, for example, in providing instructions to the machine system processor 410 for execution. The machine-readable medium can be a storage media. Storage media includes both non-volatile media and volatile media. Non-volatile media includes, for example, optical or magnetic disks, such as machine system storage unit 425. Volatile media includes dynamic memory, such as the machine system memory 415. All such media must be tangible to enable the instructions carried by the media to be detected by a physical mechanism that reads the instructions into a machine. Common forms of machine-readable medium include, for example, a floppy disk, a flexible disk, hard disk, magnetic tape, or any other magnetic medium, a CD-ROM, any other optical medium, punch cards, paper-tape, any other physical medium with patterns of holes, a RAM, a PROM, and EPROM, a FLASH-EPROM, any other memory chip, or cartridge.

[0023]In another embodiment, the machine-readable medium can be a transmission media including coaxial cables, copper wire and fibre optics, including the wires that include the machine system bus 405. Transmission media can also take the form of acoustic or light waves, such as those generated during radio-wave and infra-red data communications. Examples of machine-readable medium may include, but are not limited, to a carrier wave as described hereinafter or any other medium from which the machine system, for example, 115-4 can read, for example online software, download links, installation links, and online links. For example, the instructions can initially be carried on a magnetic disk of a remote computer. The remote computer can load the instructions into its dynamic memory and send the instructions over a telephone line using a modem. A modem local to the machine system, for example, 115-4 can receive the data on the telephone line and use an infra-red transmitter to convert the data to an infra-red signal. An infra-red detector can receive the data carried in the infra-red signal and appropriate circuitry can place the data on the machine system bus 405. The machine system bus 405 carries the data to the machine system memory 415, from which the machine system processor 410 retrieves and executes the instructions. The instructions received by the machine system memory 415 can optionally be stored in the machine system storage unit 425 either before or after execution by the machine system processor 410.

[0024]The machine system, for example, 115-4 also includes a machine system transceiver 445 coupled to the machine system bus 405. The machine system transceiver 445 provides a two-way data communication coupling with one or more electronic control modules (ECMs) (not shown), one or more monitoring devices, for example, 135-4 associated with the machine, for example, 105-4, and/or one or more electronic devices, for example, 130-4 associated with the machine, for example, 105-4. In embodiments, the machine system transceiver 445 can be an integrated service digital network (ISDN) card or a modem to provide a data communication connection to a corresponding type of telephone line. As another example, the machine system transceiver 445 can be a local area network (LAN) card to provide a data communication connection to a compatible LAN. Wireless links can also be implemented. In any such implementation, the machine system transceiver 445 sends and receives radio, electrical, electromagnetic, or optical signals that carry digital data streams representing various types of information.

[0025]In embodiments, the machine system processor 410 may be capable of executing the computer instructions stored in the machine system memory 415 to perform one or more functions. In embodiments, the machine system processor 410 may include one or more machine system control units, for example, 450, 455, 460, 465, 470 to perform the one or more functions. For example, the machine system processor 410 may include a monitoring unit 450, a detection unit 455, a determination unit 460, an identification unit 465, and an action unit 470. In embodiments, the machine system control units 450, 455, 460, 465 470 correspond to and/or include hardware and/or software components respectively and may be configured to perform respective functions. In embodiments, the machine system control units 450, 455, 460, 465 470 may implement the model(s) stored in the machine system storage unit 425 to perform the respective functions. It will be apparent to those with ordinarily skilled in the art that, in embodiments, the components 405-445 of the machine system, for example, 115-4 and the machine system control units 450-470 are also included in each machine system of the machine systems, for example, 115-1, 115-2, 115-3. For purposes of clarity and understanding, the functions performed by the monitoring device(s) 135-4 and the machine system control units 450-470 provided in the machine system 115-4 of the machine 105-4 and the functions performed by the electronic device(s) 130-4 associated with the machine 105-4 will be explained in detail hereinafter. It will be apparent to those with ordinary skill in the art that that the monitoring device(s) 135-1, 135-2, 135-3 and the machine system control units 450-470 provided in the machine systems 115-1, 115-2, 115-3 of the machines 105-1, 105-2, 105-3 respectively are also configured to perform the same functions as the monitoring device(s) 135-4 and the machine system control units 450-470 provided in the machine system 115-4 of the machine 105-4. Similarly, it will also be apparent to those with ordinary skill in the art that the electronic devices 130-1, 130-2, 130-3 associated with the machines 105-1, 105-2, 105-3 respectively are also configured to perform the same functions as the electronic device 130-4 associated with the machine 105-4.

[0026]The monitoring unit 450 is configured to receive at least one input from the monitoring device(s) 135-4 associated with the machine 105-4 operating within the worksite 100. In embodiments, the monitoring unit 450 is configured to receive the at least one input in real-time or periodically. In embodiments, the monitoring unit 450 is configured to monitor the machine 105-4 operating within the worksite 100 based on the received input(s). Examples of the received input(s) include, but are not limited to, a current location or work area of the machine 105-4 within the worksite 100, one or more measurements received from the monitoring device(s) 130-4, a distance or proximity of the machine 105-4 to one or more work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6. Examples of the received measurement(s) include, but are not limited to, lateral and/or longitudinal acceleration data associated with the machine 105-4. The lateral acceleration corresponds to a rate of change of a velocity of the machine 105-4 perpendicular to the direction of travel of the machine 105-4. The longitudinal acceleration corresponds to a rate of change of a velocity of the machine 105-4 along the direction of travel of the machine 105-4. In embodiments, the monitoring unit 450 is configured to determine each work area, for example, 140-2, 140-3, 140-4, 140-5 of the plurality of work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6 traversed by the machine 105-4 within the worksite 100 over a predefined period or at a given point in time. In embodiments, the monitoring unit 450 is also configured to determine the received input(s) corresponding to each determined work area, for example, 140-5 traversed by the machine 105-4. As an example, the monitoring unit 450 may be configured to receive and monitor global positioning system (GPS) coordinates associated with the machine 105-4 via the monitoring device(s) 135-4 such as the GPS sensor(s)/tracking unit in real-time and is configured to determine the work area(s), for example, 140-5 traversed by the machine 105-4 based on the GPS coordinates received. As another example, the monitoring unit 450 may be configured to receive radio signals from the monitoring devices, for example, 135, 136 such as the area localizer systems in the work areas, for example, via the monitoring device(s) 135-4 such as the machine localizer systems in real-time and is configured to determine the work area(s), for example, 140-5 traversed by the machine 105-4 based on the radio signals received from the area localizer systems. The monitoring unit 450 may also be configured to receive one or more measurements via the monitoring device(s) 135-4 such as the inertial measurement unit(s) in real-time and correlate the received measurements(s) to the corresponding determined work area(s), for example, 140-5. In some embodiments, the monitoring system 120 may also be configured to receive and monitor the GPS coordinates associated with the machine 105-4. In such embodiments, the monitoring system 120 may be configured to determine each work area traversed by the machine 105-4 over the predefined period and/or in real-time. Further, in such embodiments, the monitoring system 120 may also be configured to provide the determined work area(s), for example, 140-2, 140-2, 140-3, 140-4, and/or 140-5, traversed by the machine 105-4 to the monitoring unit 450. In embodiments, the monitoring unit 450 is configured to provide the determined work area(s), for example, 140-5 and the received input(s) from the monitoring device(s), for example, 135-4 corresponding to the determined work area(s), for example, 140-5 to the detection unit 455.

[0027]In embodiments, the detection unit 455 is configured to detect at least one collision event associated with the machine 105-4 corresponding to at least one work area, for example, 140-5 of the plurality of work areas, for example, 140-2, 140-3, 140-4, 140-5, within the worksite 100 based on the at least one received input. In embodiments, the detection unit 455 configured to analyze the at least one received input corresponding to each determined work area, for example, 140-2, 140-3, 140-4, 140-5 traversed by the machine 105-4 and detect the collision event(s) associated with the machine 105-4 corresponding the determined work area(s), for example, 140-5 based on the analysis. In embodiments, the detection unit 455 is configured to determine an anomaly in the at least one received input and determine the at least one collision event based on the determined anomaly. In embodiments, the detection unit 455 may be configured to compare the received input(s) with predefined or preset values, settings, and/or thresholds, referred to hereinafter as ‘predefined input thresholds’, or one or more previously received input(s) stored in the machine system storage unit 425 and determine the anomaly based on the comparison. For example, the detection unit 455 may compare the received input(s) such as, but not limited to, the lateral and/or longitudinal acceleration data with the predefined input thresholds or previously received input(s) associated with the lateral and/or longitudinal acceleration data. The detection unit 455 may then be configured to detect the collision event(s) for instances when the received input(s) exceed the predefined input thresholds. Similarly, the detection unit 455 may also be configured to detect the collision event(s) for instances when a variation or difference between the received input(s) and the previously received input(s) is less than or greater than one or more predefined input variation thresholds. The predefined input variation thresholds correspond to thresholds associated with the variation or the difference between the receive input(s). In embodiments, the predefined input variation thresholds may also be indicative of an upper limit of a deviation from the predefined input thresholds.

[0028]In embodiments, the detection unit 455 is also configured to determine a position of the monitoring device(s) 135-4 associated with the received input(s). In embodiments, the detection unit 455 is configured to determine one or more collision points or locations on the machine 105-4 based on the detected collision event(s), the received input(s), and/or the determined position of the monitoring device(s) 135-4. In embodiments, the detection unit 455 is configured to determine a longitudinal collision at one or more first portions, for example, a front side or a back side, of the machine 105-4 along a direction of motion of the machine 105-4 or a lateral collision at one or more second portions, for example, a first lateral side or a second lateral side, of the machine 105-4 transverse to the direction of motion of the machine 105-4 based on the determined collision point(s) and the determined position of the monitoring device(s) 135-4. For example, the detection unit 455 is configured to determine the lateral collision including, but not limited to, scraping of a machine body of the machine 105-4 against an object or a lateral wall, at the one or more lateral sides of the machine 105-4 and the longitudinal collision including, but not limited to, a collision of the machine 105-4 with an object, a wall, or another machine, at the front side or the back side of the machine 105-4. The detection unit 455 is configured to determine the lateral collision based on the lateral acceleration data. The lateral acceleration in the machine 105-4 occurs when the machine 105-4 is moving/turning at a constant velocity ‘V’ around a corner, for example, C3 along a path, for example, P1, with a radius of ‘R’ and a unit of measurement of the lateral acceleration is meters per second square (m/s²) or gravitational force units (g). In embodiments, the detection unit 455 is configured to determine the lateral acceleration in the machine 105-4 using an equation, a_Y=V(r+β*), wherein a_Y is the lateral acceleration, V is the constant velocity, r is a yaw rate, and β* is a slip rate. The yaw rate ‘r’ of the machine 105-4 is a rate at which the machine 105-4 rotates around a vertical axis (not shown) of the machine 105-4. The slip rate β* corresponds to a rate of change in slip ratio. The slip ratio corresponds to a difference between an actual measured speed of the machine 105-4 and a calculated speed, expressed as a percentage of the actual measured speed. The detection unit 455 is configured to determine the lateral collision of the machine 105-4 when the determined lateral acceleration is greater than a predefined lateral acceleration. For example, the predefined lateral acceleration for a yaw rate of 42 degrees and a velocity of 30 kilometers per hour is less than or equal to 1 g. The detection unit 455 may determine the current yaw rate and the machine speed based on the received input(s), and may detect the lateral collision, such as a lateral wall collision, for instances when the determined lateral acceleration is greater than 2 g lateral acceleration. In embodiments, the detection unit 455 is also configured to determine the lateral side of the machine 105-4 associated with the lateral collision. In embodiments, one or more first monitoring devices like the monitoring device(s) 135-4 are provided in the first lateral side of the machine 105-4 and one or more second monitoring devices like the monitoring device(s) 135-4 are provided in the second lateral side of the machine 105-4. In embodiments, the monitoring unit 450 may be configured to receive one or more inputs from the first monitoring device(s) or the second monitoring device(s) and provide the received inputs to the detection unit 455. In embodiments, the detection unit 455 may be configured to determine the position of the first and/or second monitoring devices associated with the received input(s). In embodiments, the detection unit 455 is configured to determine the lateral acceleration corresponding to the received inputs from the first monitoring device(s) or the second monitoring device(s). In embodiments, the detection unit 455 is configured to associate the determined lateral acceleration corresponding to the received inputs from the first monitoring device(s) to the first lateral side of the machine 105-4 based on the determined position of the first monitoring device(s). Similarly, the detection unit 455 is configured to associate the determined lateral acceleration corresponding to the received inputs from the second monitoring device(s) to the second lateral side of the machine 105-4 based on the determined position of the second monitoring device(s).

[0029]In embodiments, the detection unit 455 is also configured to determine the longitudinal collision based on the longitudinal acceleration data. The longitudinal acceleration is correlated to the machine velocity of the machine 105-4 in the direction of travel of the machine 105-4. The detection unit 455 is configured to determine a change in the machine velocity of the machine 105-4 in the direction of travel based on the received input(s) and based on the comparison with the previously determined machine velocity of the machine 105-4. The detection unit 455 is also configured to determine the longitudinal acceleration or a longitudinal deceleration based on the determined change in the machine velocity. The longitudinal deceleration corresponds to a rate at which the machine 105-4 decelerates. In embodiments, the detection unit 455 may detect the longitudinal collision, such as a longitudinal wall collision, for instances when the determined machine velocity is equal to zero or less than the previously determined machine velocity by a predefined threshold velocity and/or when the longitudinal deceleration greater than a predefined threshold deceleration is determined. For example, the detection unit 455 may detect the longitudinal collision at a front portion of the machine 105-4 for instances when the previously determined machine velocity is positive, the current determined machine velocity is equal to zero, and/or the determined longitudinal deceleration is greater than 2 g. Similarly, the detection unit 455 may detect the longitudinal collision at a rear portion of the machine 105-4 for instances when the previously determined machine velocity is negative and the current determined machine velocity is greater than zero, and/or the current determined longitudinal acceleration is greater than a predefined longitudinal acceleration and a previously determined longitudinal acceleration.

[0030]Referring to FIGS. 1 and 5, an exemplary flowchart of the detection unit 455 detecting the longitudinal collision at the front portion of the machine 105-4 is disclosed. At block 505, the detection unit 455 (see FIG. 4) is configured to start the detection of the longitudinal collision. At block 510, the detection unit 455 is configured to receive one or more inputs from the monitoring device(s), for example, 135-4 such as the inertial measurement unit provided in the machine 105-4. The received input(s) is in a form of an analog signal having a frequency of, for example, 100 hertz. At block 515, the detection unit 455 is configured to downsample the received input(s) from, for example, 100 hertz, to, for example, 50 hertz via, for example, the anti-aliasing filter (not shown). The downsampling refers to a process of reducing an amount of data for analysis, storage, and/or processing and thereby, minimizes usage of bandwidth and resources for processing the data. At block 520, the detection unit 455 is configured to determine the longitudinal acceleration/deceleration of the machine 105-4 based on the downsampled data. Further, at block 520, the detection unit is also configured to determine whether the determined longitudinal deceleration is greater than, for example, 5 g. If the determined longitudinal deceleration is greater than the predefined longitudinal deceleration of, for example, 5 g, the detection unit 455 is configured to execute block 525 else the detection unit 455 is configured to execute the block 505. At block 525, the detection unit 455 is configured to determine the machine velocity of the machine 105-4 based on the downsampled data and/or the determined longitudinal deceleration. Further, at block 525, if the determined machine velocity is less than the predefined machine velocity of, for example, 5 kilometers per hour, the detection unit 455 is configured to execute block 530 else the detection unit 455 is configured to execute the block 505. At block 530, the detection unit 455 is configured to determine and validate the longitudinal collision of the machine 105-4 at the front portion of the machine 105-4 based on the determined longitudinal deceleration (for example, greater than 5 g) and the determined machine velocity (for example, less than 5 kilometers per hour) and execute a block 535 to end the detection of the longitudinal collision.

[0031]Referring again to FIGS. 1 and 4, the determination unit 460 is configured to determine a severity of the at least one collision event detected corresponding to the at least one work area, for example, 140-5 by the detection unit 455. In embodiments, the determination unit 460 may determine the severity based on the model such as, but not limited to, the machine learning and/or artificial intelligence model(s). In embodiments, the determination unit 460 is configured to implement the model to analyze the received input(s) from the monitoring device(s), for example, 135-4 to determine the severity. In embodiments, the determination unit 460 is also configured to implement the model to analyze historical collision events associated with one or more machines, for example, the machines 105-1, 105-2, 105-3, 105-4 corresponding to the at least one determined work area, for example, 140-2, 140-3, 140-4, 140-5. In embodiments, the determination unit 460 is also configured to implement the model to analyze one or more machine dimensions of the machines, for example, 105-1, 105-2, 105-3, 105-4. It will be appreciated that the determined severity corresponding to the machines, for example, 105-1, 105-2, 105-3, 105-4, with different dimensions may be same or different. In embodiments, the determination unit 460 is also configured to implement the model to analyze the historical received input(s) including, but not limited to, historical lateral and/or longitudinal acceleration data, and/or historical machine velocity associated with the machines, for example, the machines 105-1, 105-2, 105-3, 105-4 corresponding to the historical collision events and/or the at least one determined work area, for example, 140-5. In embodiments, the determination unit 460 may be configured to determine the severity as a ‘low severity’ collision event or a ‘high severity’ collision event based on the analysis of the received input(s), the historical collision events, the machine dimensions, and/or the historical received input(s).

[0032]As an example, the determination unit 460 may implement the model to analyze the received input(s) including, but not limited to, the lateral/longitudinal acceleration data and the machine velocity, in response to the collision event associated with machine 105-4 detected by the detection unit 455 corresponding to the work area 140-5. The determination unit 460 may be configured to implement the model to determine at least one historical collision event determined as ‘high severity’ collision event associated with the machine 105-1 corresponding to the work area 140-5, at least one historical collision event determined as ‘low severity’ collision event associated with the machine 105-2 corresponding to the work area 140-5. The determination unit 460 may be configured to implement the model to determine and compare at least one dimension of the machines 105-1, 105-2, and 105-4. Further, the determination unit 460 may be configured to implement the model to determine the severity based on the analysis of the historical received input(s) including, but not limited to, historical lateral and/or longitudinal acceleration data, and/or historical machine velocity associated with the machines 105-1, 105-2. Based on the analysis of the received input(s), the historical collision events, the machine dimensions, and/or the historical receive input(s), the determination unit 460 may be configured to implement the model to determine the detected collision event as the ‘low severity’ collision event or the ‘high severity’ collision event corresponding to the work area 140-5.

[0033]In embodiments, the determination unit 460 is configured to receive one or more machine inputs from other machines, for example, 105-1, 105-2, and 105-3 via the machine system transceiver 445 and the network 125. Examples of the received machine inputs include, but are not limited to, the work area(s) traversed by the machines, for example, 105-1, 105-2, and 105-3, the detected collision events and the determined severity of the detected collision events corresponding to the work area(s), for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6 traversed by the machines, for example, 105-1, 105-2, and 105-3, one or more historical collision events associated with the machines, for example, 105-1, 105-2, and 105-3 corresponding to the work area(s), and the one or more machine dimensions of the machines, for example, 105-1, 105-2, 105-3, one or more historical received input(s) including, but not limited to, historical lateral and/or longitudinal acceleration data, and/or historical machine velocity associated with the machines, for example, the machines 105-1, 105-2, 105-3 corresponding to the historical collision events and/or the traversed work area(s). In some embodiments, the determination unit 460 may also be configured to receive the machine inputs associated with the other machines, for example, 105-1, 105-2, and 105-3 via the monitoring system 120 and the network 125. In embodiments, the determination unit 460 is configured to store the received machine inputs in the machine system storage unit 425.

[0034]In embodiments, the determination unit 460 is also configured to implement the model to determine the severity as the ‘low severity’ collision event or the ‘high severity’ collision event based on one or more predefined severity thresholds associated with the worksite 100 and/or the at least one determine work area, for example, 140-5. For example, the predefined input thresholds associated with the received input(s) including the lateral/longitudinal acceleration data and/or the machine velocity of the machine 105-4 for each work area, for example, 140-2, 140-3, 140-4, 140-5 and/or the worksite 100 may be stored in the machine system storage unit 425. In embodiments, the predefined input thresholds associated with the lateral/longitudinal acceleration data and/or the machine velocity of other machines, for example, 105-1, 105-2, 105-3 corresponding to different work areas in different worksites may also be stored in the machine system storage unit 425. In embodiments, the determination unit 460 is configured to compare the predefined input thresholds with the current measurements such as, but not limited to, the current lateral/longitudinal acceleration data and/or the current machine velocity determined based on the received input(s). In embodiments, the determination unit 460 is configured to determine the severity of the collision event based on the comparison. In embodiments, the determination unit 460 is configured to determine a deviation of the current determined lateral/longitudinal acceleration data and/or the machine velocity from the predefined input thresholds. The predefined severity thresholds correspond to thresholds associated with the deviation corresponding to each work area and/or each worksite and may be indicative of an upper limit of the deviation from the predefined input thresholds. As an example, the determination unit 460 may be configured to determine a first detected collision event of the machine 105-4 corresponding the work area 140-2 as the ‘low severity’ collision event when the determined longitudinal deceleration is equal to the predefined input threshold of, for example, 5 g and a second detected collision event of the machine 105-4 corresponding to the work area 140-3 as the ‘high severity’ collision event when the determined longitudinal deceleration is greater than or equal to the predefined severity threshold of, for example, 10 g. The predefined severity threshold of, for example, 10 g corresponds to the upper limit of the deviation, for example, 5 g from the predefined input threshold of, for example, 5 g.

[0035]In embodiments, the determined severity may be indicative of an expected extent of damage to the machine 105-4 at the determined work area(s). For example, the ‘low severity’ collision event may be indicative of minor damages to the machine 105-4 such as, but not limited to, scraping of a machine body of the machine 105-4 against an object or a lateral wall. Similarly, the ‘high severity’ collision event may be indicative of major damages to the machine 105-4 such as, but not limited to, a collision of the machine 105-4 with the object or a wall.

[0036]The identification unit 465 is configured to identify, via the model, at least one collision zone, for example, 145-1, 145-2, 145-3 within the worksite 100 based on the determined severity. In embodiments, the at least one collision zone, for example, 145-1, 145-2, 145-3, includes at least collision work area of the plurality of work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6 traversed by the machines, for example, 105-1, 105-2, 105-3, and/or 105-4. The at least one collision work area corresponds to the at least one determined work area, for example, 140-3, 140-4, 140-5 of the plurality of work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6 traversed by the machine 105-4. In embodiments, the at least one collision work area includes the determined work area(s), for example, 140-3, 140-4, and 140-5 with the determined severity greater than the determined severity corresponding to other work areas, for example, 140-2 traversed by the machine 105-4. In embodiments, the at least one collision work area includes the work areas, for example, 140-3, 140-4, and 140-5 with the determined severity corresponding to the ‘high severity’ collision events. For example, the work areas 140-3, 140-4, 140-5 associated with the detected collision events determined as the ‘high severity’ collision events may correspond to the collision zones 145-1, 145-2, 145-3 respectively. In some embodiments, the work areas 140-3, 140-4, 140-5 associated with the detected collision events determined as the ‘high severity’ collision events may also correspond to a single collision zone (not shown).

[0037]In embodiments, the identification unit 465 is configured to identify the at least one collision zone, for example, 145-1, 145-2, 145-3 based on the model. In embodiments, the identification unit 465 is configured to implement the model to analyze the historical collision events determined as, for example, ‘high severity’ collision events and a count of the determined historical collision events associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 corresponding to the at least one traversed work area, for example, 140-2, 140-3, 140-4, 140-5. In embodiments, the identification unit 465 is also configured to implement the model to analyze the one or more machine dimensions of the machines, for example, 105-1, 105-2, 105-3, and 105-4. In embodiments, the identification unit 465 is also configured to implement the model to analyze the historical received input(s) including, but not limited to, historical lateral and/or longitudinal acceleration data, and/or historical machine velocity associated with the machines, for example, the machines 105-1, 105-2, 105-3, 105-4 for each historical collision event determined as, for example, ‘high severity’ collision event corresponding to each traversed work area, for example, 140-2, 140-3, 140-4, 140-5. In embodiments, the identification unit 465 is also configured to implement the model to analyze each path, for example, P1, P2 in each worksite, for example, the worksite 100 traversed by the machine 105-4 and the one or more path details associated with each path, for example, P1, P2. Examples of the path details include, but are not limited to, a curvature of the path, for example P1 extending along the work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6 and one or more work areas, for example, 140-3, 140-4, 140-5, associated with detected collisions events in the path. In embodiments, the identification unit 465 is configured identify the collision zone(s) based on the analysis of historical collision events determined as ‘high severity’ collision events, the count of the historical collision events in each work area, for example, 140-3, the machine dimensions, the path(s), for example, P1, P2 and/or path details.

[0038]As an example, the identification unit 465 may implement the model to analyze at least one historical collision event determined as ‘high severity’ collision event associated with the machines, for example, 105-1, 105-2, 105-3, and/or 105-4 corresponding to the work area, for example, 140-5. The identification unit 465 may be configured to implement the model to determine and compare at least one dimension of the machines 105-1, 105-2, and 105-4. Further, the identification unit 465 may be configured to implement the model to analyze the historical received input(s) including, but not limited to, historical lateral and/or longitudinal acceleration data, and/or historical machine velocity associated with the machines, for example, 105-1, 105-2, 105-3, and/or 105-4. The identification unit 465 may be configured to implement the model to analyze the path(s), for example, P1 and/or P2 and the path details associated with the path(s). Based on the analysis of the historical collision events, the machine dimensions, the historical receive input(s), the path(s), and/or the path details, the identification unit 465 may be configured to implement the model to determine the collision zone(s). For example, the identification unit 465 may be configured to determine the work areas 140-3, 140-4, 140-5 as the collision zones 145-1, 145-2, 145-3 within the worksite 100 respectively based on the analysis.

[0039]The action unit 470 is configured to perform, via the model, at least one corrective action based on the at least one identified collision zone, for example, 140-3. In embodiments, the action unit 470 is configured to determine at least one cause of the at least one detected collision event based on the at least one received input and/or the model. In embodiments, the action unit 470 is configured to determine the cause of the at least one collision event determined as the ‘high severity’ collision event. In embodiments, the action unit 470 is configured to determine the cause of the at least one collision event corresponding to each collision zone, for example, 145-1, 145-2, 145-3. In embodiments, the action unit 470 is configured to determine the at least one corrective action based on the at least one determined cause. In embodiments, the action unit 470 is configured to perform a first corrective action by providing the at least one identified collision zone, for example, 145-3 via a display, for example, the machine system display unit 430 and/or the electronic device, for example, 130-4 associated with the machine 105-4 via a network 125. In embodiments, the action unit 470 is configured to perform the first corrective action by providing the at least one identified collision zone to the other machines, for example, 105-1, 105-2, 105-3 and/or the monitoring system 120. In embodiments, the action unit 470 is configured to perform a second corrective action by determining a current location of the machine 105-4 and/or a current path, for example, P1 traversed by the machine 105-4 within the worksite 100 based on the at least one received input by the monitoring unit 450. In embodiments, the action unit 470 is also configured to perform the second corrective action by monitoring a proximity of the machine 105-4 to the at least one identified collision zone, for example, 145-3 based on the determined current location. Further, the action unit 470 is configured to perform the second corrective action by detecting a movement of the machine 105-4 towards the at least one identified collision zone, for example, 145-1, 145-2, 145-3 based on the monitored proximity. In addition, the action unit 470 is configured to perform the second corrective action by providing at least one alert to the machine 105-4, and/or the electronic device 130-4 associated with the machine 105-4 based on the monitored proximity and the detected movement. In embodiments, the action unit 470 is configured to provide the alerts as visual alerts, audio alerts, audio-visual alerts, tactile or haptic alerts via one or more output devices (not shown) provided in the machine 105-4. Examples of the output devices include, but are not limited to, the machine system display unit 430, one or more machine alarm systems, one or more machine illumination devices, one or more lighting systems, one or more machine haptic systems, and one or more tactile control systems. In embodiments, the action unit 470 is configured to provide the alert when the monitored proximity of the machine 105-4 to the collision zone, for example, 145-3 is equal to or less than a predefined distance between the machine 105-4 and the collision zone, for example, 145-3.

[0040]For example, the action unit 470 may determine the current location as the work area 140-6 and a current path of the machine 105-4 as P2. The action unit 470 may determine the proximity of the machine 105-4 to the identified collision zone 145-3 and detect the movement of the machine 105-4 towards the identified collision zone 145-3. The action unit 470 may then perform the second corrective action by providing the alert to the machine 105-4 via the machine system display unit 430, and/or the electronic device 130-4 associated with the machine 105-4 based on the detected movement and when monitored proximity is equal to 2 kilometers from the identified collision zone 145-3.

[0041]In embodiments, the action unit 470 is configured to perform a third corrective action by modifying at least one machine parameter associated with the machine 105-4 based on the monitored proximity and the detected movement. For example, the action unit 470 may be configured to minimize an engine speed of the machine 105-4. In embodiments, the action unit 470 is configured to perform a fourth corrective action by providing at least one recommendation, instruction, or information to the machine 105-4 or an operator of the machine 105-4 via the machine system display unit 430, the electronic device 130-4 associated with the machine 105-4, or a display unit (not shown) provided in or in proximity to the at least one identified collision zone, for example, 145-3. For example, the action unit 470 may provide a recommendation to reduce the engine speed of the machine 105-4 via the machine system display unit 430 or provide information related to the identified collision zone, for example, 145-3 such as, but not limited to, one or more objects/obstructions lateral and/or longitudinal to the direction of travel of the machine 105-4 in the identified collision zone, for example, 145-3 on the display unit (not shown) in proximity to the identified collision zone, for example, 145-3 based on the detected collision event(s). In embodiments, the action unit 470 is configured to perform a fifth corrective action by assigning or directing the machine 105-4 for repair or maintenance based on the at least one detected collision event and/or the determined severity. In embodiments, the action unit 470 is configured to assign or direct the machine 105-4 for repair or maintenance for instances when the determined severity associated with the identified collision zones, for example, 145-1, 145-2, 145-3 corresponds to the ‘high severity’ collision event and/or when the count of the detected collision event(s) corresponding to the identified collision zones, for example, 145-1, 145-2, 145-3 exceeds a predefined safety count. For example, the action unit 470 is configured to assign or direct the machine 105-4 for repair or maintenance for instances when the detected collision event(s) is determined to be the ‘high severity’ collision event by the determination unit 460 corresponding to identified collision zones 145-1, 145-2, 145-3 consecutively. In embodiments, the action unit 470 is also configured to perform a sixth corrective action by assigning the at least one work area or the at least one identified collision zone, for example, 145-3 for repair or maintenance based on the at least one detected collision event and/or the determined severity. For example, the action unit 470 is also configured to assign the collision zone 145-3 for instances when the detected collision event(s) is determined as the ‘low severity’ and/or ‘high severity’ collision event by the determination unit 460 or when the count of the detected collision event(s) corresponding to the collision zone 145-3 exceeds the predefined safety count.

[0042]In embodiments, the action unit 470 is configured to perform a seventh corrective action by providing a visual indication of the at least one detected collision point or location on the machine 105-4 by the detection unit 455 on a display, for example, the machine system display unit 430 and/or the electronic device, for example, 130-4 associated with the machine 105-4 via the machine system transceiver 445 and the network 125. For example, the action unit 470 is configured to perform the seventh corrective action by indicating the frontal, rear, or lateral collision of the machine 105-4 based on the received input(s) via the monitoring unit 450. In embodiments, the action unit 470 is configured to perform an eighth corrective action by providing at least one collision alert on a display, for example, the machine system display unit 430 and/or the electronic device, for example, 130-4 associated with the machine 105-4 via the machine system transceiver 445 and the network 125 indicating the at least one detected collision event by the detection unit 455 and/or the determined severity by the determination unit 460. In embodiments, the action unit 470 is also configured to perform the eighth corrective action by providing a tactile or haptic alert, via the one or more machine haptic systems provided in the machine 105-4, to, for example, one or more machine controls or the machine system input devices 435 provided in the machine 105-4 indicating the at least one detected collision event by the detection unit 455 and/or the determined severity by the determination unit 460. In embodiments, the action unit 470 is also configured to perform the eighth corrective action by providing the at least one collision alert to other machines, for example, 105-1, 105-2, 105-3 via the network 125. In embodiments, the action unit 470 is configured to provide the collision alert(s) in real-time.

[0043]In embodiments, it may also be contemplated that the electronic devices, for example, 130-1, 130-2, 130-3, 130-4 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 respectively may also include the same components and control units as the machine system, for example, 115-4 and perform the same functions as the machine system, for example, 115-4 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 respectively. For example, the electronic device 130-4 associated with the machine 105-4 may receive the one or more input(s) from the monitoring device(s) 135-4 and be configured detected the collision event(s) associated with the machine 105-4 based on the receive input(s). The electronic device 130-4 may also be configured to determine the severity of the detected collision event(s) and identify the collision zone(s), for example, 145-3 within the worksite 100 based on the determined severity. In addition, the electronic device 130-4 may also be configured to perform the same first, second, third, fourth, fifth, sixth, seventh, and the eighth corrective actions as the machine system, for example, 115-4 based on the identified collision zone(s), for example, 145-3 and/or the detected collision event(s).

[0044]Referring to FIGS. 1 and 6, an exemplary block diagram of the system 110 corresponding to the monitoring system 120 of FIG. 1 for mitigating worksite machine collisions is disclosed. In embodiments, the monitoring system 120 includes similar components as the machine system, for example, 115-4 of FIG. 4. For example, the monitoring system 120 includes a monitoring system bus 605, a monitoring system processor 610, a monitoring system memory 615, a read only memory (ROM) 620, a monitoring system storage unit 625, a monitoring system display unit 630, one or more monitoring system input devices 635, a monitoring system input control 640, and a monitoring system transceiver 645. The monitoring system storage unit 625 may store similar data and/or information associated with the machines, for example, the machines 105-1, 105-2, 105-3, 105-4, the work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6, and/or the worksite 100 as the machine system storage unit 425. In embodiments, the monitoring system storage unit 625 may also store one or more similar machine learning, artificial intelligence, logical, and/or conditional modules, algorithms, and/or models as the machine system storage unit 425. The monitoring system transceiver 645 provides a two-way data communication coupling with one or more electronic control modules (ECMs) (not shown), one or more monitoring devices, for example, 135-1, 135-2, 135-3, 135-4 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4, and/or one or more electronic devices, for example, 130-1, 130-2, 130-3, 130-4 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 respectively. It will be apparent to those with ordinary skill in the art that, in embodiments, the monitoring system 120 may implement one or more machine learning, artificial intelligence, logical, and/or conditional operations, modules, algorithms, and/or models stored in the monitoring system storage unit 625 to perform similar functions as machine system 115-4 of FIG. 4 via the monitoring system processor 610. Further, it will also be apparent to those with ordinary skill in the art that the components of the monitoring system 120 are configured to communicate with each other and perform similar functions as the corresponding components of the machine system, for example, 115-4 of FIG. 4. For example, the monitoring system processor 610 includes monitoring system control units 650, 655, 660, 665, 670 configured to perform similar functions as the machine system control units 450, 455, 460, 465, 470 (see FIG. 4) of the machine system 115-4 of FIG. 4. It will be appreciated that one or more functions performed by the monitoring system 120 described hereinafter is indicative of the functions performed by the monitoring system control units 650, 655, 660, 665, 670 of the monitoring system 120. In addition, it will also be apparent to those with ordinary skill in the art that the machine system 115-4 of FIG. 4 is configured to perform one or more functions corresponding to the machine 105-4 and the monitoring system 120 is configured to perform similar functions as the machine system 115-4 corresponding to the one or more machines, for example, 105-1, 105-2, 105-3, 105-4.

[0045]For example, the monitoring system 120 is configured to receive at least one input from at least one monitoring device, for example, 135-1, 135-2, 135-3, 135-4 associated with at least one machine, for example, 105-1, 105-2, 105-3, 105-4, operating within the worksite 100. In embodiments, the monitoring system 120 is configured to receive the at least one input in real-time or periodically. In embodiments, the monitoring system 120 is configured to monitor the at least one machine, for example, 105-1, 105-2, 105-3, 105-4 operating within the worksite 100 based on the received input(s). In embodiments, the monitoring system 120 is also configured to determine each work area, for example, 140-2, 140-3, 140-4, 140-5 of the plurality of work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6 traversed by the machines, for example, 105-1, 105-2, 105-3, 105-4 within the worksite 100 over a predefined period or at a given point in time. In embodiments, the monitoring system 120 is also configured to determine the received input(s) corresponding to each determined work area traversed by the machines, for example, 105-1, 105-2, 105-3, 105-4. In embodiments, the monitoring system 120 is configured to detect at least one collision event associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 corresponding to at least one work area, for example, 140-5 of the plurality of work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6, within the worksite 100 based on the at least one received input. In embodiments, the monitoring system 120 is configured to analyze the at least one received input corresponding to each determined work area, for example, 140-2, 140-3, 140-4, 140-5 traversed by the machines, for example, 105-1, 105-2, 105-3, 105-4 and detect the collision event(s) associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 corresponding the determined work area(s) based on the analysis. In embodiments, the monitoring system 120 is also configured to determine one or more collision points or locations on the machines, for example, 105-1, 105-2, 105-3, 105-4 based on the detected collision event(s) and the received input(s). For example, the monitoring system 120 is configured to determine a lateral collision at one or more lateral sides of the machines, for example, 105-1, 105-2, 105-3, 105-4 and a longitudinal collision at a front portion or a rear portion of the machines, for example, 105-1, 105-2, 105-3, 105-4.

[0046]The monitoring system 120 is also configured to determine a severity of the at least one collision event detected corresponding to the at least one work area for each machine, for example, 105-1, 105-2, 105-3, 105-4. In embodiments, the monitoring system 120 may determine the severity based on the model such as, but not limited to, the machine learning and/or artificial intelligence model(s). In embodiments, the monitoring system 120 is configured to implement the model to analyze the received input(s) from the monitoring device(s), for example, 135-1, 135-2, 135-3, 135-4 to determine the severity. In embodiments, the monitoring system 120 is also configured to implement the model to analyze historical collision events associated with one or more machines, for example, the machines 105-1, 105-2, 105-3, 105-4 corresponding to the at least one determined work area, for example, 140-2, 140-3, 140-4, 140-5. In embodiments, the monitoring system 120 is also configured to implement the model to analyze one or more machine dimensions of the machines, for example, 105-1, 105-2, 105-3, 105-4 to determine the severity. In embodiments, the monitoring system 120 is also configured to implement the model to analyze the historical received input(s) including, but not limited to, historical lateral and/or longitudinal acceleration data, and/or historical machine velocity associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 corresponding to the historical collision events and/or the at least one determined work area, for example, 140-5. In embodiments, the monitoring system 120 may be configured to determine the severity as a ‘low severity’ collision event or a ‘high severity’ collision event based on the analysis of the received input(s), the historical collision events, the machine dimensions, and/or the historical receive input(s). In embodiments, the monitoring system 120 is also configured to determine the severity as the ‘low severity’ collision event or the ‘high severity’ collision event based on the model and/or one or more predefined severity thresholds associated with the worksite 100 and/or the at least one determine work area.

[0047]The monitoring system 120 is also configured to identify, via the model, at least one collision zone, for example, 145-1, 145-2, 145-3 within the worksite 100 based on the determined severity for each detected collision event corresponding to each machine, for example, 105-1, 105-2, 105-3, 105-4. In embodiments, the monitoring system 120 is configured to identify the at least one collision zone, for example, 145-1, 145-2, 145-3 based on the model. In embodiments, the monitoring system 120 is configured to implement the model to analyze the historical collision events determined as, for example, ‘high severity’ collision events and a count of the determined historical collision events associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 corresponding to the at least one traversed work area, for example, 140-2, 140-3, 140-4, 140-5. In embodiments, the monitoring system 120 is also configured to implement the model to analyze the one or more machine dimensions of the machines, for example, 105-1, 105-2, 105-3, 105-4. In embodiments, the monitoring system 120 is also configured to implement the model to analyze the historical received input(s) associated with the machines, for example, the machines 105-1, 105-2, 105-3, 105-4 for each detected historical collision event determined as, for example, ‘high severity’ collision event corresponding to each traversed work area, for example, 140-2, 140-3, 140-4, 140-5. In embodiments, the monitoring system 120 is also configured to implement the model to analyze each path, for example, P1, P2 in each worksite, for example, the worksite 100 traversed by the machines, for example, 105-1, 105-2, 105-3, 105-4. In embodiments, the monitoring system 120 is configured determine the collision zone(s) based on the analysis of historical collision events determined as ‘high severity’ collision events, the count of the historical collision events, the machine dimensions, and/or the path(s), for example, P1, P2.

[0048]The monitoring system 120 is also configured to perform, via the model, at least one corrective action based on the at least one identified collision zone. In embodiments, the monitoring system 120 is configured to determine at least one cause of the at least one detected collision event based on the at least one received input. In embodiments, the monitoring system 120 is configured to determine the cause of the at least one collision event determined as the ‘high severity’ collision event. In embodiments, the monitoring system 120 is configured to determine the cause of the at least one collision event corresponding to each collision zone, for example, 145-1, 145-2, 145-3 for each machine, for example, 105-1, 105-2, 105-3, 105-4. In embodiments, the monitoring system 120 is configured to determine the at least one corrective action based on the at least one determined cause. In embodiments, the monitoring system 120 is configured to perform a first corrective action by providing the at least one identified collision zone via a display, for example, the monitoring system display unit 630, one or more machine system display units, for example, 430 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4, and/or the electronic devices, for example, 130-1, 130-2, 130-3, 130-4 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 respectively via the network 125. In embodiments, the monitoring system 120 is configured to perform the first corrective action by providing the at least one identified collision zone to the machines, for example, 105-1, 105-2, 105-3, 105-4 via the network 125. In embodiments, the monitoring system 120 is configured to perform a second corrective action by determining a current location of the machines, for example, 105-1, 105-2, 105-3, 105-4 and/or a current path traversed by the machines within the worksite 100 based on the at least one received input from the machines respectively. In embodiments, the monitoring system 120 is also configured to perform the second corrective action by monitoring a proximity of each machine, for example, 105-1, 105-2, 105-3, 105-4 to the at least one identified collision zone, for example, 145-1, 145-2, 145-3 based on the determined current location. Further, the monitoring system 120 is configured to perform the second corrective action by detecting a movement of the machines, for example, 105-1, 105-2, 105-3, 105-4 towards the identified collision zone(s), for example 145-1, 145-2, 145-3 based on the monitored proximity. In addition, the monitoring system 120 is configured to perform the second corrective action by providing at least one alert to the machines, for example, 105-1, 105-2, 105-3, 105-4, and/or the electronic devices, for example, 130-1, 130-2, 130-3,130-4 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 based on the monitored proximity and the detected movement. In embodiments, the monitoring system 120 is configured to provide the alerts as visual alerts, audio alerts, audio-visual alerts, and/or tactile alerts via one or more output devices (not shown) provided in the machines, for example, 105-1, 105-2, 105-3, 105-4 respectively. In embodiments, the monitoring system 120 is configured to provide the alert when the monitored proximity of the machines, for example, 105-1, 105-2, 105-3, 105-4 to the collision zone, for example, 145-1, 145-2, 145-3 is equal to or less than a predefined distance between the machines, for example, 105-1, 105-2, 105-3, 105-4 and the collision zone, for example, 145-1, 145-2, 145-3.

[0049]For example, the monitoring system 120 may determine the current location of the machine 105-3 as the work area 140-2 and a current path of machine 105-3 as P1. The monitoring system 120 may determine the proximity of the machine 105-3 to the identified collision zone 145-1 and detect the movement of the machine 105-3 towards the identified collision zone 145-1. The monitoring system 120 may then perform the second corrective action by providing the alert to the machine 105-3 via, for example, the machine system display unit of the machine 105-3, and/or the electronic device 130-3 associated with the machine 105-3 based on the detected movement and when monitored proximity ranges between, for example, 50 to 100 meters. Similarly, the monitoring system 120 may determine the current location of the machine 105-4 as the work area 140-6 and a current path of the machine 105-4 as P2. The monitoring system 120 may determine the proximity of the machine 105-4 to the identified collision zone 145-3 and detect the movement of the machine 105-4 towards the identified collision zone 145-3. The monitoring system 120 may then perform the second corrective action by providing the alert to the machine 105-4 via the machine system display unit 430, and/or the electronic device 130-4 associated with the machine 105-4 based on the detected movement and when the monitored proximity is equal to, for example, 2 kilometers.

[0050]In embodiments, the monitoring system 120 is configured to perform a third corrective action by modifying at least one machine parameter associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 based on the monitored proximity and the detected movement. For example, the monitoring system 120 may be configured to minimize an engine speed of the machines, for example, 105-1, 105-2, 105-3, 105-4 when the machines are proximate to the collision zone, for example, 145-1, 145-2, 145-3. In embodiments, the monitoring system 120 is configured to perform a fourth corrective action by providing at least one recommendation, instruction, or information to the machines, for example, 105-1, 105-2, 105-3, 105-4 or an operator of the machines via the respective machine system displays, the electronic devices, for example, 130-1, 130-2, 130-3, 130-4 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4, or a display unit (not shown) provided in or in proximity to the at least one identified collision zone, for example, 145-3. For example, the monitoring system 120 may provide a recommendation to reduce the engine speed of the machine 105-4 via the machine system display of the machines, for example, 105-3, 105-4 or provide information related to the identified collision zones, for example, 145-1, 145-3 such as, but not limited to, one or more objects/obstructions lateral and/or longitudinal to the direction of travel of the machines, for example, 105-3, 105-4 in the identified collision zones, for example, 145-1, 145-3 on the display unit (not shown) in proximity to the identified collision zones, for example, 145-1, 145-3. In embodiments, the monitoring system 120 is configured to perform a fifth corrective action by assigning or directing one or more machines, for example, 105-1, 105-2, 105-3, 105-4 for repair or maintenance based on the at least one detected collision event and/or the determined severity. In embodiments, the monitoring system 120 is also configured to perform a sixth corrective action by assigning the at least one work area or the at least one identified collision zone, for example, 145-1, 145-3 for repair or maintenance based on the at least one detected collision event and/or the determined severity.

[0051]In embodiments, the monitoring system 120 is configured to perform a seventh corrective action by providing a visual indication of the at least one determined collision locations on the machines, for example, 105-1, 105-2, 105-3, 105-4 on a display, for example, the respective machine system display units of the machines and/or the electronic devices, for example, 130-1, 130-2, 130-3, 130-4 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 respectively via the network 125. In embodiments, the monitoring system 120 is configured to perform an eighth corrective action by providing at least one collision alert on a display, for example, the machine system display units of the machines, for example, 105-1, 105-2, 105-3, 105-4, and/or the electronic devices, for example, 130-1, 130-2, 130-3, 130-4 associated with the machines, for example, 105-1, 105-2, 105-3, 105-4 respectively via the network 125 indicating the at least one detected collision event and/or the determined severity corresponding to each machine. In embodiments, the monitoring system 120 is also configured to perform the eighth corrective action by providing the at least one collision alert to the machines, for example, 105-1, 105-2, 105-3, 105-4 indicating the detected collision event and/or determined severity associated with one or more machines, for example, 105-1, 105-2, 105-3, 105-4 corresponding to one or more work areas, for example, 140-1, 140-2, 140-3, 140-4, 140-5, 140-6, 140-7. In embodiments, the monitoring system 120 is configured to provide the collision alert(s) in real-time. It will be appreciated that the monitoring system 120 is configured to perform the same functions as the machine system, for example, 115-4 and additional functions as described herein. Further, it will also be apparent that the monitoring system 120 is also configured to perform any additional functions included in or associated with each function performed by the machine system, for example, 115-4.

INDUSTRIAL APPLICABILITY

[0052]Referring to FIGS. 1 and 7, a method 700 for mitigating worksite machine collisions within the worksite 100 performed by the system 110 as shown in FIG. 4 and/or FIG. 6 is disclosed. At step 705, the system 110 receives at least one input from at least one monitoring device, for example, 135-1 associated with at least one machine, for example, 105-1, operating within the worksite 100. At step 710, the system 110 detects at least one collision event associated with the at least one machine, for example, 105-1 corresponding to at least one work area, for example, 140-4, of a plurality of work areas, for example, 140-1, 140-2, 140-3, 140-5, 140-6, 140-7 within the worksite 100 based on the at least one received input. At step 715, the system 110 determines a severity of the at least one detected collision event corresponding to the at least one work area, for example, 140-5, based on a model. At step 720, the system 110 identifies, via the model, at least one collision zone, for example, 145-1, 145-2, 145-3 within the worksite 100 based on the determined severity. The at least one collision zone, for example, 145-1 includes at least one collision work area, for example, 140-5 of the plurality of work areas. At step 725, the system 110 performs, via the model, at least one corrective action based on the at least one identified collision zone, for example, 145-1.

[0053]It will be apparent to those with ordinary skill in the art that the machines, for example, 105-1, 105-2, 105-3, 105-4, the system 110 corresponding to the machine system, for example, 115-1, 115-2, 115-3, 115-4, or the monitoring system 120, and the method 700 of the present disclosure help in detecting one or more collision events at one or more work areas, for example, 140-5 within the worksite 100. Further, the machines, for example, 105-1, 105-2, 105-3, 105-4, the system 110, and the method 700 of the present disclosure also help in identifying the ‘low severity’ collision events and the ‘high severity’ collision events associated with the machines, for example, 105-1, 105-2, 105-3, 105-4, having different dimensions at different work areas, for example, 140-2, 140-3, 140-4, 140-5 and/or on different paths, for example, P1, P2 within the worksite 100. The machines, for example, 105-1, 105-2, 105-3, 105-4, the system 110, and the method 700 of the present disclosure also help in identifying different collision zones, for example, 145-1, 145-2, 145-3, within the worksite 100. Further, the machines, for example, 105-1, 105-2, 105-3, 105-4, the system 110, and the method 700 of the present disclosure also help in implementing one or more corrective actions based on the determined severity of the detected collision events and/or the identified collision zones, for example, 145-1, 145-2, 145-3. Further, the machines, for example, 105-1, 105-2, 105-3, 105-4, the system 110, and the method 700 of the present disclosure also enable operators of the machines to identify the detected collision event(s), the collision location(s) on the machine, and the collision zones, for example, 145-1, 145-2, 145-3 within the worksite 100 and/or in each path, for example, P1 within the worksite 100. The machines, for example, 105-1, 105-2, 105-3, 105-4, the system 110, and the method 700 of the present disclosure further enable different corrective actions such as, but not limited to, providing the collision zones to machines, providing one or more recommendations or instructions associated with collision zones, providing alerts to machines approaching the collision zones, providing alerts of detected collision events and/or the determined severity of each collision event to the machines, providing collision locations on each machine based on the detected collision event, modifying machine parameters such as the machine speed of the machines, and/or providing alerts to one or more display units in proximity to the identified collision zones, to be taken based on the identified collision zones. The machines, for example, 105-1, 105-2, 105-3, 105-4, the system 110, and the method 700 of the present disclosure also help ensure that the repair and maintenance of the machines, for example, 105-1, 105-2, 105-3, 105-4 involved in the detected collision events and/or the works areas, for example, 140-3, 140-4, 140-5 associated with the collision zones, for example, 145-1, 145-2, 145-3 respectively is conducted in a timely manner to reduce production downtimes. It can be appreciated that based on the detection of the collision events, the determination of the severity, the identification of the collision zones, and performing the corrective actions, the machines, for example, 105-1, 105-2, 105-3, 105-4, the system 110, and the method 700 of the present disclosure help mitigate the worksite collision events within the worksite 100.

[0054]Unless explicitly stated, the use of the singular to describe a component, structure, or operation does not exclude the use of plural such components, structures, or operations or their equivalents. The use of the terms “a” and “an” and “the” and “at least one” or the term “one or more,” and similar references herein are to be construed to cover both the singular and the plural, unless otherwise indicated herein. The use of the term “at least one” followed by a list of one or more items (for example, “at least one of A and B” or one or more of A and B”) is to be construed to mean one item selected from the listed items (A or B) or any combination of two or more of the listed items (A and B; A, A and B; or A, B and B), unless otherwise indicated herein. Similarly, as used herein, the word “or” refers to any possible permutation of a set of items. For example, the phrase “A, B, or C” refers to at least one of A, B, C, or any combination thereof, such as any of: A; B; C; A and B; A and C; B and C; A, B, and C; or multiple of any item such as A and A; B, B, and C; A, A, B, C, and C; etc.

[0055]It will be apparent to those skilled in the art that various modifications and variations can be made to the method and/or system of the present disclosure without departing from the scope of the disclosure. Other embodiments will be apparent to those skilled in the art from consideration of the specification and practice of the method and/or system disclosed herein. It is intended that the specification and examples be considered as exemplary only, with a true scope of the disclosure being indicated by the following claims and their equivalent.