Systems and methods for operating vehicle lifts

Abstract

A vehicle lift system comprising a frame and a carrier configured for carrying a vehicle, the frame comprising a controller configured for operating the carrier, the controller being in communication with a control console comprising an input mechanism in communication with the controller for causing carrier motion comprising ascent, descent and stop. The system comprises at least one camera being configured with a line of sight for facial observation to generate facial observation data, based on which the controller is configured to stop motion of the carrier. Furthermore, the system comprises at least one camera being positioned with respect to the frame and the at least one camera having a line of sight to the operating volume, the at least one camera being in communication with the controller and a machine learning application to determine a dynamic No-Go Zone and also detect when the No-Go Zone is being violated.

Description

[0001] Systemsand Methods for Operating Vehicle Lifts

[0002] Field of the I nvention

[0003] Disclosed are systems and methods for operating vehicle lifts and more particularly to improving the user and property safety when operating vehicle lifts.

[0004] Background

[0005] Vehicle lifts or hoists are common in vehicle repair shops, vehicle inspection facilities, vehicle manufacturing factories, including for passenger vehicles and commercial vehicles such as trucks and buses. Other types of products may be lifted by hoist for inspections and operations underneath them. In many circumstances, for example, human repair and inspectors spend substantial time underneath vehicles and the like on hoists. Considering the weight and size of such vehicles and the like that are perched on hoists, were there a malfunction of the hoist, such as tipping of the vehicle off the hoist, grave bodily injury to those workers is possible.

[0006] There are various types of hoists for vehicle lifts. FIGs. 1 through 5 show four vehicle lift type variations. FIG. 1 illustrates a four-post type with runways. FIG. 2 illustrates a scissor lift type with runways. FIG. 3 depicts another configuration, being a mobile column lift type hoist. FIG. 4 illustrates a two-post lift type with pivoting support arms. FIG. 5 illustrates the underside of a vehicle held up with the two-post lift type with pivoting support arms. There are further variations on hoist types which are intended to be included in this discussion.

[0007] In Australia, it is estimated that there are approximately thirty thousand (30,000) workshops with one-hundred fifty thousand (150,000) hoists. It is further estimated that in total there may be multiple incidents each day involving at least injury of a worker or damage to property from hoist mishaps. It would be beneficial were there a manner in which to avoid hoist mishaps.There is a need to address the above, and / or at least provide a useful alternative.

[0008] Summary

[0009] Disclosed is a vehicle lift system including a frame and a carrier configured for carrying a vehicle, the frame comprising a controller configured for operating the carrier, the controller being in communication with a control console including an input mechanism in communication with the controller for causing carrier motion comprising ascent, descent and stop, the system including that the control console includes at least one optical sensor being configured with a line of sight for facial observation to generate facial observation data, that the controller includes an automatic input mechanism to control the carrier the controller being configured to disable carrier motion and based upon the absence of facial observation data received from the at least one optical sensor, the controller being configured to stop motion of the carrier.

[0010] The controller may comprise a processor which is configured to generate facial observation data from signals received from the optical sensor.

[0011] The optical sensor may be a camera.

[0012] The facial observation data may comprise an image of a face for identification of an operator.

[0013] The facial observation data may comprise gaze direction and attention index.

[0014] Also disclosed is a vehicle lift system including a frame supported relative to the ground and including a carrier configured for carrying a vehicle, the frame including a controller configured for operating the carrier, the controller having controller data and being in communication with a control console including an input capability in communication with the controller, the input being configured to cause carrier motion comprising ascent, descent and stop, the frame and carrier characterised by an operating volume relative to the ground, the system including, at least one camera being positioned with respect to theframe and the at least one camera having a line of sight to the operating volume, the at least one camera being in communication with the controller, the at least one camera receiving operating volume data from its line of sight to the operating volume, the at least one camera in communication with a machine learning application, the machine learning application being configured to receive operating volume data from the camera and to determine a No-Go Zone, the machine learning application being in communication with the controller to adjust controller data to incorporate the No-Go Zone, the controller being configured to receive visual data from the at least one camera in which the No-Go Zone is violated and the controller being configured to cause the carrier motion to stop when the controller determines that the at least one camera’s visual data represents that the No-Go Zone is violated.

[0015] Violation of the no-go zone may comprise the presence of an unauthorized object or person in the controller-identified No-Go Zone.

[0016] The operating volume data may comprise size and shape of the operating area of the vehicle lift.

[0017] The operating volume data may be dynamically updated from results of the machine learning.

[0018] Boundaries of the No-Go zone may be dynamically updated from results of the machine learning.

[0019] The system may comprise an alarm for alerting an operator of the presence of an unauthorised object or person in the No-Go Zone.

[0020] The system may further comprise a tilt and stability monitoring system comprising one or more sensors attached to the vehicle or vehicle lift as the vehicle is engaged with the vehicle lift, the sensors being operably coupled to the controller and configured to generate vehicle stability data.The sensors may be adapted to measure one or more of the following as the vehicle is being lifted: distance to ground; shock and vibration magnitude during movement; Tilt or incline change; drop or acceleration change, and attachment of the sensors.

[0021] The system may further comprise a lift arm restraint monitoring system comprising one or more sensors adapted to attached to the vehicle lift or in the vicinity of the vehicle lift, the sensors being operably coupled to the controller and configured to generate lift arm restraint engagement data.

[0022] Additionally disclosed is a method of a vehicle lift system comprising a frame and a carrier configured for carrying a vehicle, the frame including a controller configured for operating the carrier, the controller being in communication with a control console including an input mechanism in communication with the controller for causing carrier motion comprising ascent, descent and stop, the method including providing the control console with at least one camera being configured with a line of sight for facial observation to generate facial observation data, providing the controller with an automatic input mechanism to control the carrier the controller being configured to disable carrier motion, providing a mechanism based upon the absence of facial observation data received from the at least one camera, for the controller to be configured to stop motion of the carrier.

[0023] Furthermore, disclosed is a method of a vehicle lift system comprising a frame supported relative to the ground and including a carrier configured for carrying a vehicle, the frame including a controller including electrical controls configured for operating the carrier, the controller having controller data and being in communication with a control console including an input capability in communication with the controller, the input being configured to cause carrier motion comprising ascent, descent and stop, the frame and carrier characterised by an operating volume relative to the ground, the method including providing at least one camera being positioned with respect to the hoist frame and the at least one camera having a line of sight to the operating volume, the at least one camera being in communication with the controller, providing that the at least one camera is configured to receive operating volume data from its line of sight to the operating volume, providing the at least one camera is in communication with a machine learning application,the machine learning application being configured to receive operating volume data from the camera and to determine a No-Go Zone, providing that the machine learning application is in communication with the controller to adjust controller data to incorporate the No-Go Zone, providing that the controller is configured to receive visual data from the at least one camera in which the No-Go Zone is violated and providing that the controller is configured to cause the carrier motion to stop when the controller determines that the at least one camera’s visual data represents that the No-Go Zone is violated.

[0024] Brief Description of the Drawinos

[0025] In order that the disclosure may be more easily understood, an embodiment will now be described, by way of example only, with reference to the accompanying drawings, in which:

[0026] FIG. 1 illustrates a four-post type with runways;

[0027] FIG. 2 illustrates a scissor lift type with runways;

[0028] FIG. 3 depicts another configuration, being a mobile column lift type vehicle lift;

[0029] FIG. 4 illustrates a two-post lift type with pivoting support arms;

[0030] Fl G. 5 illustrates the above side of a vehicle held up with the two-post lift type with pivoting support arms;

[0031] FIG. 6 depicts the two-post lift type vehicle lift 101 with pivoting support arms;

[0032] FIG. 7 depicts the two-post lift type with a vehicle super-imposed upon the operating area outline;

[0033] FIG. 8 depicts the two-post lift type with a vehicle super-imposed upon an operating volume;FIG. 9 is a close-up view of the control console;

[0034] FIG. 10 depicts the disclosed systems and method;

[0035] FIG. 11 depicts a flow chart for an aspect of the disclosed systems and methods;

[0036] FIG. 12 depicts a flow chart for an aspect of the disclosed systems and methods;

[0037] FIG. 13 illustrates a high-level diagram of the at least four disclosed systems and methods;

[0038] FIG. 14 depict example physical characteristics of the bay area camera;

[0039] FIG. 15 depict example physical characteristics of the control console camera;

[0040] FIG. 16 depicts exemplar No-Go Zone of the lift depicted in FIG. 1 with a bay camera placement;

[0041] FIG. 17 depicts exemplar No-Go Zone of the lift depicted in FIG. 2 with a bay camera placement;

[0042] FIG. 18 depicts exemplar No-Go Zone of the lift depicted in FIG. 3 with a bay camera placement;

[0043] FIG. 19 depicts a tilt and stability monitoring system in accordance with an embodiment; and

[0044] FIG. 20 depicts a vehicle lift arm restraint monitoring system in accordance with an embodiment.Detailed ion

[0045] A vehicle lift or hoist comprises a frame and a carrier. The carrier of a two post lift comprises load carrying arms and that of a four post lift comprises a runway. The vehicle lift further comprises a driving means e.g. electric, hydraulic, mechanical screw or pneumatic means. The vehicle lift also comprises a hoist control console which controls the operation of the hoist.

[0046] A lift control console may be manually manoeuvred by a vehicle lift operator. A vehicle lift control console may be located in various positions in the workshop area depending on type of vehicle lift. The vehicle lift operator is positioned in front of the control console and is required to maintain visual view of the vehicle lift as it is operated, thus moving the vehicle lift up and down. If the hoist operator is not paying complete attention to the vehicle lift situation and circumstances, for example, by looking away for a moment, the vehicle lift operator may miss that a person is under a loaded hoist. Injury or even death of a fellow worker may occur. Less grave consequences of a vehicle lift operator looking away while manually operating the vehicle lift control console may be that property may have been left under a vehicle lift while it is lowered, damaging the property.

[0047] FIG. 6 depicts the two-post lift type vehicle lift 101 with pivoting support arms (illustrated in FIGs. 4 and 5) with an operating area outline 103 in two-dimensions, in this case 2.5 metres by 7.5 metres. FIG. 7 depicts the two-post lift type 101 with a vehicle 102 superimposed upon the operating area outline 103 of the two-post lift type hoist101. Also depicted are two columns 105 and two pivoting arms 107.

[0048] The operating area 103 in shown FIG., 7 is two dimensions of a volume 109 which is shown in FIG. 8. The vertical dimension 111 varies as the vehicle lift moves up and down. The parameter of an operating area 103 (operating volume 109 being shown in FIG. 8) of a particular vehicle lift configuration 101, situation and circumstances may be altered bymachine learning which is an ongoing process for that particular operating area 103 to establish a No-Go Zone.

[0049] It is understood that each work area of the roughly one-hundred and fifty thousand vehicle vehicle lifts are in operation in Australia have their own particular vehicle lift configurations, situations and circumstances. Each particular vehicle lift configurations, situations and circumstances may be of different types, for different types of work including different types of tools, numbers of workers to name a few variable parameters. It is understood that as the machine learning for each vehicle lift101 progresses, variable parameters may be added. Furthermore, it is understood that the system (see FIG. 10) described herein may include variable parameters as particular vehicle lift configurations, situations and circumstances are added to the system or deleted from the system.

[0050] The presently disclosed systems and methods include at least bay area (zone) camera 113 in a position that captures an operating volume 109 for both transmission to a machine learning application and surveillance of the No-Go Zone while work by workers is underway, such visual data being received by the controller 115. 11 is understood that more than one zone camera may be utilised from various positions and various capabilities may be utilised such as having lenses to perceive wide angles, to zoom in and out, and other features. The zone camera 113, for example, may capture motion and / or stills.

[0051] It is understood that the machine learning capability may be any suitable capability. Machine learning algorithms are currently undergoing substantial development in the field of artificial intelligence. Accordingly, it is understood that any one of many suitable machine learning algorithms are within the scope of this discussion.

[0052] Machine learning tools may be available, for example, based upon the various articles below:

[0053] Design and Optimization of I ndoor Space Layout Based on Deep Learning Yingfei SunFirst published: 23 February 2022

[0054] https: / / doi.org / 10.1155 / 2022 / 2114884

[0055] Academic Editor: Hasan Ali Khattak

[0056] This article is part of Special Issue:

[0057] • Advanced Artificial Intelligence Technologies for Service Enhancement on the Internet of Medical Things

[0058] Learning indoor space perception

[0059] Andreas Sedlmeier & Sebastian Feld

[0060] Mobile Information Systems Wiley Online Library

[0061] Pages 179-214 | Received 02 Jul 2018, Accepted 11 Oct 2018, Published online: 08 Nov 2018

[0062] Sedlmeier, A., & Feld, S. (2018). Learning indoor space perception. Journal of Location Based Services, 12(3-4), 179-214. https: / / doi.org / 10.1080 / 17489725.2018.1539255 • https: / / doi.Org / 10.1080 / 17489725.2018.1539255

[0063] Anomaly analysis on indoor office spaces for facility management using deep learning methods

[0064] Author links open overlay panelYooSeok Junga, TaeWook Kanga, Chanjun ChunbJournal of Building Engineering

[0065] Volume 43, November 2021 , 103139

[0066] https: / / doi.org / 10.1016 / j .jobe.2021 .103139

[0067] PinSout: Automatic 3D Indoor Space Construction from Point Clouds with Deep Learning

[0068] Authors: Taehoon Kim, Wijae Cho, Akiyoshi Matono, Kyoung-Sook Kim

[0069] SIGSPATIAL '20: Proceedings of the 28th International Conference on Advances in Geographic Information Systems

[0070] Pages 211 - 214

[0071] https: / / doi.org / 10.1145 / 3397536.3422343

[0072] Published: 13 November 2020Predicting the global structure of indoor environments: A constructive machine learning approach

[0073] • Published: 28 April 2018

[0074] • Volume 43, pages 813-835, (2019)

[0075] Luperto, M., Amigoni, F. Predicting the global structure of indoor environments: A constructive machine learning approach. Auton Robot 43, 813-835 (2019). https: / / doi.Org / 10.1007 / s10514-018-9732-7

[0076] Also depicted in FIG. 8 is control console 117. As mentioned, the control console operator utilises the control console 117 for causing ascent or descent of a vehicle lift in a situation similar to that shown in FIG. 8. In another aspect of the present disclosure, the control console 117 which includes an operator detection optical sensor e.g. camera 118 is depicted in Fl G. 9. I n this embodiment, the operation detection optical sensor is a camera. I n other embodiments, it may be any other type of suitably optical sensor which can detect a face and / or facial features.

[0077] FIG. 9 is a close-up view of the control console 117 shown in FIG. 8. It is understood that any suitable configuration of features of the control console 117 is within the scope of this discussion. An operator detection camera 118 is shown and will be discussed in more detail below. The display screen 119 is a user interface which may be of any suitable type, for example, a touch screen much like that of a mobile device. The exclamation point shown on the display screen may alert a control console operator that an unauthorised object is present in the No-Go Zone (also discussed below). An audible alarm may alert the control console operator of the presence of an unauthorised object or person in the No-Go Zone by alarm 121 .

[0078] An on / off button 125 and a power and state indicator light, green for active, red for inactive, yellow indicating a system fault 127 may be included. The on / off button may be a soft push which allows the hoist system to be turned from active to inactive. The hoist system may return to active control on the next power cycle (off / on), or after the defined timeperiod has lapsed. Additionally, an internal override switch allows to be overridden in the event of failure.

[0079] FIG. 10 depicts aspects of the disclosed systems and methods. A system is shown in FIG.

[0080] 10 including a vehicle lift frame 105. Refer to FIG. 8 for a carrier 107 configured for carrying a vehicle 102 that defines an initial operating volume 131 . The vehicle lift frame 105 may support a controller 115 including electrical controls configured for operating the carrier 107 (of FIG. 8).

[0081] The area in the rectangular box 116 is known as a power unit assembly that includes electric motor, hydraulic pump, oil reservoir. These items are a common standard operating configuration on a hydraulic vehicle lift. Ascent and descent of the vehicle lift are controlled by the hoist or lift control system. On an electro-hydraulic vehicle lift, the ascent and descent is controlled by the power unit. Please note the invention is not limited to electro hydraulic vehicle lifts, but all types of vehicle lift.

[0082] The area in the rectangular box 118 is the operator control of the vehicle lift. This includes button for operating the drive of the motor and lowering handle used for releasing hydraulic pressure and in turn lowering the lift.

[0083] The disclosed controller 115 and the control console 117 are together a control system (depicted in FIG. 13) to the vehicle lift, while each of controller 115 and control console 117 operate independently of one another, providing independent inputs to the power unit.

[0084] The controller 115 being in communication with a control console 117 includes an input mechanism in communication with the controller 115 for causing carrier 107 motion including its ascent, descent and stopping. In one aspect of the disclosed systems and methods, the system depicted in Fl G. 10 includes a control console 117 including a console camera 118 being configured with a line of sight for facial observation to generate facial observation data.The control system (depicted in FIG. 13) includes processing circuitry capable of carrying out calculations and logic. It is a type of computer. The processing of controller 115 determines if the area is safe for the lift to operate and either allows the lift controls mentioned above as power unit to operate normally or in turn interrupts the operation of the controls in the presence of risk.

[0085] Control console 117 is the user interface for the system. It has both input and output function and also includes processing circuitry capable of carrying out calculations and logic. Each of the controller 115 and the control console 117 operate independently but make up the controls system (depicted in FIG. 13).

[0086] FIG. 11 depicts a flowchart for an aspect of the disclosed systems and methods. Upon vehicle lift activation 141 by an operator 133 (depicted in FIG. 10) the camera 118 of the control console 117 may detect 143 a person’s face within its field of vision such that the camera 118 is configured with a line of sight 119 for facial observation to generate facial observation data. Facial observation data can include information not just on presence or absence of facial features but also of on gaze direction and attention index created through facial orientation and presence. Data representing matter detected by the camera 118 is sent 145 to the controller 115, the controller 115 configured with an automatic input (not shown) to control the carrier 107, the controller 115 being configured to disable carrier 107 motion, thus stopping the carrier 107.

[0087] The controller determines 147 if the facial observation data is present in the data sent by the console camera 118. If the facial observation data is present, the controller continues 149 operation whereby the control console camera 118 continues to detect a person’s face in its field of vision 143, creating a loop 151 . If the controller determines 147 that there is an absence of desired facial observation data present, based upon the signals received from the camera 118, the controller 115 discontinues 153 the operation, thus stopping motion of the carrier 107.Facial recognition software may be used to determine a particular person’s facial features. Facial recognition means may conduct face gaze analysis to understand hoist user alertness and safe operation with attention on the region of interest or NO-GO ZONE during operation. Detection of a face and recognition to identify a person can be a first step. A next step can include user facial structure analysis including specifically confirmation of eye motion and orientation.

[0088] However, simpler embodiments can include a less sophisticated software to determine that a person’s face is detected, regardless of their identity.

[0089] Returning to FIG. 10, the operator 133 is facing away from the control console 117 and thus there is no facial observation data received from the camera 118 by the controller 115. FIG. 10 illustrates that the camera 118 detects only the back of the head of the operator 133, therefore, in this case, the controller 115 discontinues the operation of the vehicle lift 101 , thus stopping the motion of the carrier 107. To accommodate operators having different heights so that the face of the operator is within the console camera’s 118 line of sight 119, the control console’s 117 position may be adjustable, automatic and / or manual.

[0090] Fl G. 12 illustrates another aspect of the disclosed systems and methods such being another determination for the controller 115 to discontinue operation of the carrier 107. Disclosed systems include the controller 115 being in communication with the control console 117 including a manual input mechanism being configured to cause carrier motion including ascent, descent and stop, the hoist frame and carrier initially establishing an operating volume relative to the ground. (It is understood that some vehicle lift operate over a pit so the ground is below ground level.) To establish the operating volume, at least one zone camera 113 collects data of the operating volume 151 as illustrated in FIG. 8. The zone camera data may be sent 153 to the Cloud over the Internet for a machine learning application 155 to determine a No-Go Zone in an on-going process - until conditions are met for the on-going process to terminate, periodically or otherwise. The machine learning program instead and / or concurrently may be locally located as well, not requiring Internet dispatchment. The machine learning application 155 is in communication with thecontroller 115 to adjust 157 controller data expectations and the camera 113 (if necessary) to coincide with the No-Go Zone.

[0091] Returning to FIG. 10 which depicts that there is an object 135 not originally within the initial operating volume 109 but later introduced within the operating volume 109. The machine learning application which may be running in the background while the hoist is in operation may incorporate the objection 135 into No-Go Zone data. Controller data expectations may include the objection 135. As the process is on-going, a new objection 137 may be introduced into the No-Go Zone, therefore the machine learning application may determine 155 a subsequent No-Go Zone. Were a vehicle to enter an otherwise unoccupied No-Go Zone for repairs and the like, a hoist area sensor 138 may communicate 139 with the controller 115 or other device to rely on the No-Go Zone stored by the controller 115 or other device.

[0092] Returning to FIG. 11 , as mentioned above, were a vehicle to enter an otherwise unoccupied No-Go Zone, the hoist area sensor 138 may detect 159 a vehicle’s movement toward a carrier. When the carrier is engaged with the vehicle, the carrier can operate. In the event that the hoist area camera 113 provides visual data to the controller 115 or other device that there may be a violation of the No-Go Zone 165, for example, a person is too close to the vehicle as it is ascending, the carrier may automatically stop or discontinue operation 167. Thus, the controller 115 is configured to receive 165 visual data from the at least one camera in which the No-Go Zone may be violated and the controller 115 is configured to cause the carrier 107 motion to stop when there is the possibility that the No-Go Zone is violated.

[0093] Were the carrier 107 to stop moving either up or down when an unauthorised object or person is detected in the No-Go Zone, once the operator confirms that the system recognised unauthorised object is either removed or is okay to be in its position 169, the control console operator acknowledges safety (see FIG. 9 and which may be illuminated because the hoist stopped moving) to resume the hoist’s prior operation. To acknowledge safety, the operator activate the override in accordance with the hardware or software ofthe system. For example, the operator can press an illuminated button 123, and / or can confirm by an acknowledgement on a touch screen and / or can provide a specific voice control.

[0094] As described above, the disclosed systems and methods, in conjunction with machine learning determining a No-Go Zone, are capable of determining the presence of an unintentional person and / or object in the No-Go Zone. When a person and / or object enters the No-Go Zone and / or is present in the No-Go Zone, movement of the carrier 107 is blocked by the controller 115 or other device.

[0095] The No-Go Zone is a three-dimensional zone that may be shaped as a wall, circle, sphere, dome, or any other appropriate shape. The No-Go Zone can be shaped with one or more boundaries. For example, in one embodiment the No-Go Zone may be directly under, in front, behind and either side of the lifting device and its carried load. It is understood that other examples of the shape and size of the No-Go Zone can be envisaged.

[0096] The disclosed systems and method may be configured for adjusting the boundaries of the No-Go Zone utilising an interface system configured for adjusting the boundaries of the No-Go Zone in addition to or by utilising a machine learning application, rendering the No-Go Zone dynamic in size and / or shape. As an example, through machine learning the system enables adjustment in response to the actual height of the carrier and / or the presence of a vehicle in the disclosed lifting system.

[0097] As described above, the system may include a warning system configured for providing a warning signal and / or control signal in response to an unintentional object in the defined area of operation, the No-Go Zone. By providing a warning system, appropriate warning and / or control signals can be generated. A warning signal can be provided to an operator, for example on the controller, to a mobile device such as a phone or tablet computer. Also, a warning can be provided to a supervisor or other person or system. A control signal can be provided to the controller and the lifting system can be interrupted I blocked until the person and / or object has been removed from the No-Go Zone.FIG. 13 illustrates a high-level diagram of the at least four systems and methods described in this disclosure. The two camera systems mentioned above, the first shown as the console camera 118 and the second shown as at least one bay area camera 113 provide data to the controller 115. A tilt module monitoring system 200 and an arm restraint monitoring system 300 (discussed further below) also provide information to the controller 115. The user interface of the control console 117 being in communication with the controller and other features of the described systems and methods, provide an activation relay 171 or a safety interlock system which is connected to the primary control interface of a hoist, to activate, slow, speed up, or stop the lift control system 173 in view of the No-Go Zone 132.

[0098] FIGs. 14 and 15 depict example physical characteristics of the bay area camera 113 and the control console camera 118. The bay area camera 113 in particular may be housed within a sturdy housing as it may receive impacts from incidences in the lift area. The console camera 118 may be embedded into the control console 117 interface. Any suitable cameras are within the scope of this discussion.

[0099] Again, referring to FIGs. 8 and 10, the camera 113 may be in communication with controller 115 via the use of convenient technologies such as cable, or wireless, for example by Bluetooth. Referring to FIGs. 9 and 10, camera 118 likewise may be in communication with controller 115 via the use of convenient technologies such as cable, or wireless, for example by Bluetooth.

[0100] FIGs. 16, 17 and 18 depicts exemplar No-Go Zones 132 of lifts depicted in FIGs. 1 , 2 and 3, with exemplar placements of the bay cameras 113 within the No-Go Zones 132 (depicted in 2-dimensional characterisations, the 3-dimensional characterisations occur as the lift moves up and down and are within the scope of this discussion).

[0101] Within the scope of this discussion, additional features may be provided. For example, the controller 115 may have an override function, wherein the monitoring system hasdetermined an unintentional person and / or object in the No-Go Zone, however the operator may intentionally perform operations with the lifting system. For example, in some cases, in a zone directly under and / or around the lifting system, the No-Go Zone, there may be the need for intentional presence of an object while operating the lifting system. The controller may have an override function, allowing the user to switch the No-Go Zone alarm to inactive. The user protection system will return to active control on the next power cycle (off / on) , or after the defined time period has lapsed. The defined time period for the device to return to active state may be determined by the controller.

[0102] As described above, the carrier (lifting) system provides an operator detection system including camera and system with what may be a rudimentary facial feature algorithm or may be a more advance facial recognition and machine learning capability. By providing an operator detection feature at the control console 117 as described above, the carrier (lifting) system may be protected with a No-Go Zone status initiated in response to failure of the facial feature algorithm to recognise the desired facial features e.g. operator gaze analysis and awareness / alertness captured by the console camera 118 at the control console 117.

[0103] As described above, an unauthorised person and / or person not facing the carrier (lift) system (see FIG. 10) attempts to operate the lift system, movement of the carrier 107 is blocked by the controller 115. Beneficially, safety may be increased. For example, in one embodiment of a no-go status at the control console 117, the carrier (lift) system movement of the carrier may be blocked by the controller 115 when an operator 133 is not directly facing and observing the console 117 as well as its carried load (see Fl G. 8) .

[0104] As with the No-Go Zone of the carrier system, the control console system may undergo machine learning. The control console 117 system may adjust the conditions of the No-Go Zone status, rendering the No-Go Zone status dynamic in control. Additionally, the operator detection system may include a reporting system configured for providing a time and date stamp record of operation for the lifting system and the operator 133 behaviour while operating the control console 117. By providing a reporting system, appropriate operation and / or control signals may be generated. A report can be provided to an operator,for example on the controller, to a mobile device such as a phone, watch, ring or tablet computer. Also, a report can be provided to a supervisor or other person or system. A control signal may be provided to the controller and the carrier (lifting) system can be interrupted I blocked until action has taken from the report. Also, the carrier (lifting) system may be interrupted I blocked until the operator has acknowledged the controllers intervention I block for example.

[0105] The system can be either retrofitted as to an existing vehicle lift or can be incorporated into new vehicle lift design.

[0106] The vehicle lift system may also provide a load stability detection capability. When a load stability detection feature of the presently disclosed systems and methods detects instability of the lifting systems carried load, a warning signal may be provided to an operator, for example on the control console 117, to a mobile device such as a phone, watch, ring or tablet computer. Also, a warning can be provided to a supervisor or other person or system. A control signal may be provided to the controller 115 so the carrier (lifting) system may be interrupted I blocked until carried 107 load has been stabilised.

[0107] For example, wireless sensors can be attached to the vehicle and or lift carrier which provide secondary safety and direct tilt / imbalance stability indications. The attachment can be provided by various means including magnetic, suction or any suitable fastening means. The tilt detection sensor system can also be used to train future Al machine learning algorithms and implement continuous MLOps improvements to recognition and detection with relation to vehicle stability.

[0108] Additionally, movement of the carrier may be interrupted I blocked until the operator has acknowledged the controllers intervention I block for example. The load stability detection system may be configured for adjusting the conditions of the warning system, for example by machine learning processing, adjusting the conditions of the load stability detection warning system, rendering the stability detection warning system dynamic in control.I n an embodiment shown in Fig. 19, the vehicle hoist system can comprise a tilt and stability monitoring subsystem 200 configured for attachment to the vehicle positioned on the carrier. The subsystem 200 comprising a magnetic attachment mechanism adapted to secure the subsystem to a surface of the vehicle, the subsystem 200 comprising at least one tilt sensor 210 configured to generate vehicle stability data indicative of angular deviation of the vehicle relative to the carrier or ground, the subsystem 200 being configured to transmit the sensor data wirelessly to the controller 115.

[0109] The tilt and stability monitoring subsystem 200 can further comprise at least one sensor configured to detect shock, vibration, or displacement of the vehicle, and wherein the controller 115 is configured to derive stability or imbalance thresholds based on the transmitted vehicle stability data and to disable or prevent carrier motion when the thresholds are exceeded. In the illustrated embodiment, sensors 210 have a number of outputs and are adapted to sense:

[0110] Distance to ground;

[0111] Shock and vibration magnitude;

[0112] Tilt or incline change;

[0113] Drop or acceleration change, and

[0114] Attachment of the sensors e.g. magnetic attachment.

[0115] The sensors 210 are also adapted to be recharged on the safety controller 115 described above, which has a power unit providing power to a rechargeable battery means of the sensor system, in an embodiment.

[0116] The tilt and stability monitoring subsystem 200 can be configured to generate vehicle stability indices based on angular deviation, vibration, or displacement data, and wherein the controller is configured to enter a lockout state when the stability indices exceed predetermined safe limits.

[0117] The tilt and stability monitoring subsystem 200 can further comprise a data-logging mechanism configured to record the sensor data over time, including data generated priorto, during, and after a detected instability event, the recorded data being retained for subsequent diagnostic or safety review.

[0118] Furthermore, the recorded sensor data can be configured to be stored in a non-volatile memory associated with the subsystem 200 or controller 115, the recorded data comprising incident information suitable for post-event analysis to determine the cause or sequence of events associated with vehicle instability or a vehicle fall.

[0119] I n an embodiment, the controller 115 of the vehicle hoist system be configured to combine visual data from the at least one bay area camera 113 and / or console camera 118 with the sensor data from the tilt and stability monitoring subsystem 200 to determine hazardous conditions. The controller 115 can be configured to prevent or stop carrier motion when the combined data indicates a condition of unsafe vehicle support or instability.

[0120] Examples of various operating modes of the above disclosed systems and methods, when implemented, will now be described.

[0121] Operating mode: SYSTEM OFF

[0122] While in this state, the control system of the vehicle lift is powered off, the vision systems (e.g. the cameras 113, 118 and controller 115) are inactive, and the interlock relay is preventing the lift from operating.

[0123] The system leaves this state when the user presses the ON push button, which activates the vision systems and active monitoring.

[0124] After initial power ON, the vision system will assess whether the lift is on the lowered position and if the mechanical lock is engaged. Then it will transition to one of the following states:

[0125] • ON and IDLE: If the lift is in the lowered position, with or without a car detected.• Lift raised lock engaged: If the lift is raised and the pressure sensing detects that the weight of the car is resting on the mechanical lock.

[0126] • Lift raised lock disengaged: If the lift is raised and the pressure sensing detects that the mechanical lock is not engaged properly.

[0127] Operating mode: ON and IDLE

[0128] While in this state, no active safety monitoring is running, and the lift is allowed to operate. However, the vision system is active and can be used to detect the presence of a car and / or read its license plate.

[0129] Operating mode: LIFT OPERATING

[0130] The system enters this state when the lift is moving up or down. While in this state, object tracking, imbalance detection and operator monitoring are active.

[0131] The vision systems will trigger an action if:

[0132] • The operator fails to monitor the lift’s no-go zone.

[0133] • Any object enters the no-go zone.

[0134] • An imbalance is detected, and a fall is imminent.

[0135] The action can be triggering an alarm (sound and light) and / or applying the safety interlock system to stop the ascent or decent of the lift.

[0136] Once the operator stops the ascent or decent of the lift, the system will transition to the “Lift Raised Lock Disengaged” state.

[0137] Operating mode: LIFT RAISED LOCK DISENGAGED

[0138] The system enters this state when the lift is not moving, and the pressure sensing detects that the weight of the car is not yet resting on the mechanical lock.While in this state, the system will expect the hydraulic pressure to be released in order to engage the mechanical lock within a defined period.

[0139] Object tracking, imbalance detection and operator monitoring are active in this state and are used to trigger alarms using the same criteria as in the Lift Operating state.

[0140] If the pressure is not released after the predefined time, the system will trigger an alarm.

[0141] Once the mechanical lock is engaged, the system will transition to the Lift Raised Lock Engaged state.

[0142] Operating mode: LIFT RAISED LOCK ENGAGED

[0143] The system enters this state when it determines that it is safe to work under the lifted car, that is, when the weight of the car rests on the mechanical lock.

[0144] While in this state, object tracking and imbalance detection are active. The system will prevent the hydraulic pump from operating if there are any person or objects in the zone, this will prevent the mechanical lock from being released, so the car cannot be lowered.

[0145] An imminent fall due to imbalance detection will also trigger an alarm in this state.

[0146] The system will leave this state when the operator activates the hydraulic pump to disengage the mechanical lock and will transition to the Lift Operating state.

[0147] Operating mode: ERROR CONDITION DETECTED

[0148] The system will fail safe if any fault condition is detected anywhere in the system. These could be due to a system malfunction or environmental conditions preventing the system from operating correctly, for example, a blocked or dirty camera unable to monitor the no-go zone.The system can further comprise an alarm system that can execute the following actions:

[0149] • Alarm sound via speaker.

[0150] • RGB LED Flash pattern with a colour depending on the alarm.

[0151] • Warning message on GUI screen to provide further information about the nature of the alarm to the operator.

[0152] • Relay / solenoid output to interlock the lift operation, so the hydraulic pump can be stopped if required.

[0153] The system will implement an alarm override function to ignore alarms for a given period. The override is activated via an GUI button press and hold to confirm and it can be deactivated at any time by the operator. The override will be deactivated automatically after the predefined period.

[0154] Other ways of implementing the disclosed systems and methods are envisaged.

[0155] I n another embodiment, the hoist system can further comprises an arm restraint monitoring subsystem 300 configured to monitor the engagement of a vehicle lift arm restraint system during vehicle lift operation; an example of which is shown in Figure 20.

[0156] The arm restraint monitoring subsystem 300 comprises a sensor array and or optical capture system 320, that can be attached to the vehicle lift carrier or in the vehicle lift work bay to monitor the engagement of the vehicle lift arm restraint system 310. The subsystem 300 includes a communication interface for exchanging sensor data and or field of view data with the controller 115 via the use of cable, or wireless connections e.g. via Bluetooth. The controller 115 is configured to receive the sensor data and or field of view data and to determine proper or improper engagement of the vehicle lift arm restraint system 300. When the controller 115 determines that the transmitted data indicates a condition of improper arm restraint engagement, or engagement beyond a predetermined safe range, the controller 115 is configured to disable or prevent carrier motion and enforce a safety lockout state until acceptable arm restraint engagement is restored.Additionally, the subsystem 300 is configured to record real-time sensor and or field of view data for diagnostic and safety auditing purposes. The recorded data is retained in an incident-logging mechanism configured to preserve sensor and or field of view data and controller data before, during, and after an event indicative of the vehicle lift arm restraint engagement. This recorded dataset enables post-incident reconstruction and review analogous to a flight-recorder or “black-box” to assist in determining causation, procedural compliance, and safety-system operation during repair or maintenance events.

[0157] I n an embodiment, the vehicle lift system can further comprise an arm restraint monitoring subsystem configured for attachment to the vehicle lift carrier or in the vehicle lift work bay, the subsystem comprising an attachment mechanism adapted to secure the subsystem to a surface of the vehicle lift carrier or in the vehicle lift work bay, the subsystem comprising at least one sensor and or optical capture system configured to generate sensor data and or field of view data indicative of engagement of the vehicle lift arm restraint system, the subsystem being configured to transmit the sensor data and or field of view data via cable, or wirelessly e.g. via Bluetooth.

[0158] In an embodiment the arm restraint monitoring subsystem comprises at least one sensor and or optical capture system configured to detect engagement of the vehicle lift arm restraint system, and wherein the controller is configured to derive vehicle lift arm restraint engagement thresholds based on the transmitted sensor data and or field of view data, and to disable or prevent carrier motion when the thresholds are exceeded.

[0159] The arm restraint monitoring subsystem is configured to generate vehicle lift arm restraint system engagement position based on sensor data and or field of view data, and wherein the controller is configured to enter a lockout state when the engagement indices exceed predetermined safe limits.

[0160] The arm restraint monitoring subsystem further comprises a data-logging mechanism configured to record the sensor data and or field of view data over time, including datagenerated prior to, during, and after a detected vehicle lift arm restraint engagement event, the recorded data being retained for subsequent diagnostic or safety review.

[0161] The recorded sensor data and or field of view data is configured to be stored in a nonvolatile memory associated with the subsystem or controller, the recorded data comprising incident information suitable for post-event analysis to determine the cause or sequence of events associated with a vehicle lift arm restraint engagement event.

[0162] The controller is configured to combine visual data from the at least one camera with the sensor data and or field of view data from the arm restraint monitoring subsystem to determine hazardous conditions, and wherein the controller is configured to prevent or stop carrier motion when the combined data indicates a condition of unsafe vehicle lift arm restraint engagement.

[0163] Many modifications of the above embodiments will be apparent to those skilled in the art without departing from the scope of the present disclosure.

[0164] Throughout this specification and the claims which follow, unless the context requires otherwise, the word “comprise”, and variations such as “comprises” and “comprising”, will be understood to imply the inclusion of a stated integer or step or group of integers or steps but not the exclusion of any other integer or step or group of integers or steps.

[0165] The reference in this specification to any prior publication (or information derived from it), or to any matter which is known, is not, and should not be taken as an acknowledgment or admission or any form of suggestion that that prior publication (or information derived from it) or known matter forms part of the common general knowledge in the field of endeavour to which this specification relates.

Claims

CLAIMS:1 . A vehicle lift system comprising a frame and a carrier configured for carrying a vehicle, the frame comprising a controller configured for operating the carrier, the controller being in communication with a control console comprising an input mechanism in communication with the controller for causing carrier motion comprising ascent, descent and stop, the system comprising:the control console comprising at least one optical sensor being configured with a line of sight for facial observation to generate facial observation data;the controller comprising an automatic input mechanism to control the carrier the controller being configured to disable carrier motion; andbased upon the absence of desired facial observation data received from the at least one optical sensor, the controller being configured to stop motion of the carrier.

2. The vehicle lift system of claim 1 wherein the controller comprises a processor which is configured to generate facial observation data from signals received from the optical sensor.

3. The vehicle lift system of claim 1 wherein the optical sensor is a camera.The vehicle lift system of claim 1 wherein the facial observation data comprises an image of a face for identification of an operator.

4. The vehicle lift system of claim 1 , wherein the facial observation data comprises gaze direction and attention index.

5. A vehicle lift system comprising a frame supported relative to the ground and comprising a carrier configured for carrying a vehicle, the frame comprising a controller configured for operating the carrier, the controller having controller data and being in communication with a control console comprising an input capability in communication with the controller, the input being configured to cause carrier motion comprising ascent, descent and stop, the frame and carrier characterised by an operating volume relative to the ground, the system comprising:at least one camera being positioned with respect to the frame and the at least one camera having a line of sight to the operating volume, the at least one camera being in communication with the controller;the at least one camera receiving operating volume data from its line of sight to the operating volume;the at least one camera in communication with a machine learning application, the machine learning application being configured to receive operating volume data from the camera and to determine a No-Go Zone;the machine learning application being in communication with the controller to adjust controller data to incorporate the No-Go Zone:the controller being configured to receive visual data from the at least one camera in which the No-Go Zone is violated; andthe controller being configured to cause the carrier motion to stop when the controller determines that the at least one camera’s visual data represents that the No-Go Zone is violated.

6. The vehicle lift system of claim 7, wherein violation of the no-go zone comprises the presence of an unauthorized object or person in the controller-identified No-Go Zone.

7. The vehicle lift system of claim 7, wherein the operating volume data comprises size and shape of the operating area of the vehicle lift.

8. The vehicle lift system of claim 7, wherein the operating volume data is dynamically updated from results of the machine learning.

9. The vehicle lift system of claim 7, wherein boundaries of the No-Go zone are dynamically updated from results of the machine learning.

10. The vehicle lift system of claim 7, wherein the system comprises an alarm for alerting an operator of the presence of an unauthorised object or person in the No- Go Zone.11 . The vehicle lift system of claim 7, wherein the system further comprises a tilt and stability monitoring system comprising one or more sensors attached to the vehicle or vehicle lift as the vehicle is engaged with the vehicle lift, the sensors being operably coupled to the controller and configured to generate vehicle stability data.

12. The vehicle lift system of claim 12, wherein the sensors are adapted to measure one or more of the following as the vehicle is being lifted: distance to ground; shock and vibration magnitude during movement; Tilt or incline change; drop or acceleration change, and attachment of the sensors.

13. The vehicle lift system of claim 7, wherein the system further comprises a lift arm restraint monitoring system comprising one or more sensors adapted to attach to the vehicle lift or in the vicinity of the vehicle lift, the sensors being operably coupled to the controller and configured to generate lift arm restraint engagement data.

14. A method of using a vehicle lift system comprising a frame and a carrier configured for carrying a vehicle, the frame comprising a controller configured for operating the carrier, the controller being in communication with a control console comprising an input mechanism in communication with the controller for causing carrier motion comprising ascent, descent and stop, the method comprising:providing the control console with at least one camera being configured with a line of sight for facial observation to generate facial observation data;providing the controller with an automatic input mechanism to control the carrier the controller being configured to disable carrier motion; and providing a mechanism based upon the absence of facial observation data received from the at least one camera, for the controller to be configured to stop motion of the carrier.

15. A method of using vehicle lift system comprising a frame supported relative to the ground and comprising a carrier configured for carrying a vehicle, the frame comprising a controller comprising electrical controls configured for operating the carrier, the controller having controller data and being in communication with a control console comprising an input capability in communication with the controller, the input being configured to cause carrier motion comprising ascent,descent and stop, the frame and carrier characterised by an operating volume relative to the ground, the method comprising:providing at least one camera being positioned with respect to the frame and the at least one camera having a line of sight to the operating volume, the at least one camera being in communication with the controller;providing that the at least one camera is configured to receive operating volume data from its line of sight to the operating volume;providing the at least one camera is in communication with a machine learning application, the machine learning application being configured to receive operating volume data from the camera and to determine a No-Go Zone;providing that the machine learning application is in communication with the controller to adjust controller data to incorporate the No-Go Zone:providing that the controller is configured to receive visual data from the at least one camera in which the No-Go Zone is violated; andproviding that the controller is configured to cause the carrier motion to stop when the controller determines that the at least one camera’s visual data represents that the No-Go Zone is violated.

Images