DETAILED ACTION
Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 2/5/26 has been entered.
Notice to Applicant
The following is a Final Office action. In response to Examiner’s Non-Final Rejection of 11/7/25, Applicant, on 2/5/26, amended claims. Claims 1-19 are pending in this application; claims 1-16 and 19 are rejected below; and claims 17-18 are in condition for allowance.
Response to Amendment
Applicant’s amendments are acknowledged.
Reasons for Subject Matter Eligibility under 35 USC 101
The claim 1 overcomes the 101 rejections because the claim is now : a robot which travels automatically along a rail system of the scaffold transport system, along with a sensor to acquire data relating to a component of the robot. The claim is no longer directed to an abstract idea. When viewing the claim as a whole, this when combined with the earlier limitations is viewed as a practical application under step 2a, prong 2, as the claim is viewed as a using a judicial exception in a meaningful way under MPEP 2106.05(e). The same reasons also apply to independent claim 11 and 17 which have similar limitations.
Claim Interpretation
The following is a quotation of 35 U.S.C. 112(f):
(f) Element in Claim for a Combination. – An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The following is a quotation of pre-AIA 35 U.S.C. 112, sixth paragraph:
An element in a claim for a combination may be expressed as a means or step for performing a specified function without the recital of structure, material, or acts in support thereof, and such claim shall be construed to cover the corresponding structure, material, or acts described in the specification and equivalents thereof.
The claims in this application are given their broadest reasonable interpretation using the plain meaning of the claim language in light of the specification as it would be understood by one of ordinary skill in the art. The broadest reasonable interpretation of a claim element (also commonly referred to as a claim limitation) is limited by the description in the specification when 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is invoked.
As explained in MPEP § 2181, subsection I, claim limitations that meet the following three-prong test will be interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph:
(A) the claim limitation uses the term “means” or “step” or a term used as a substitute for “means” that is a generic placeholder (also called a nonce term or a non-structural term having no specific structural meaning) for performing the claimed function;
(B) the term “means” or “step” or the generic placeholder is modified by functional language, typically, but not always linked by the transition word “for” (e.g., “means for”) or another linking word or phrase, such as “configured to” or “so that”; and
(C) the term “means” or “step” or the generic placeholder is not modified by sufficient structure, material, or acts for performing the claimed function.
Use of the word “means” (or “step”) in a claim with functional language creates a rebuttable presumption that the claim limitation is to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites sufficient structure, material, or acts to entirely perform the recited function.
Absence of the word “means” (or “step”) in a claim creates a rebuttable presumption that the claim limitation is not to be treated in accordance with 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph. The presumption that the claim limitation is not interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, is rebutted when the claim limitation recites function without reciting sufficient structure, material or acts to entirely perform the recited function.
Claim limitations in this application that use the word “means” (or “step”) are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action. Conversely, claim limitations in this application that do not use the word “means” (or “step”) are not being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, except as otherwise indicated in an Office action.
This application includes one or more claim limitations that do not use the word “means,” but are nonetheless being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, because the claim limitation(s) uses a generic placeholder that is coupled with functional language without reciting sufficient structure to perform the recited function and the generic placeholder is not preceded by a structural modifier. Such claim limitation(s) is/are: 1) communication module in claim 1 (and claims 2-10 depend from it); 2) evaluation unit in claim 1 and 11 (and claims 2-10, 12-15 depend from 1, 11); 3) time measurement unit in claim 6. Examiner notes “identification means” in claim 8 does not recite any functions, so it does not invoke 112. Examiner notes “common evaluation unit” in claim 9 does not recite any functions, so it is not interpreted under 112f at this time.
Because this/these claim limitation(s) is/are being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, it/they is/are being interpreted to cover the corresponding structure described in the specification as performing the claimed function, and equivalents thereof.
If applicant does not intend to have this/these limitation(s) interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph, applicant may: (1) amend the claim limitation(s) to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph (e.g., by reciting sufficient structure to perform the claimed function); or (2) present a sufficient showing that the claim limitation(s) recite(s) sufficient structure to perform the claimed function so as to avoid it/them being interpreted under 35 U.S.C. 112(f) or pre-AIA 35 U.S.C. 112, sixth paragraph.
1) “communication module… is set up to wirelessly transmit the data acquired by the at least one sensor” in claim 1 – is interpreted as corresponding to the structure in [0018] as published as being a communication device/apparatus in a recording housing/assembly; [0112], FIG. 1 states “The respective recording assembly 14 comprises a recording device 16 having a sensor 18 and a communication module 20.”; the function of “transmit the data” is by “data acquired by the at least one sensor can be sent to the evaluation unit by means of a communication technology using a mobile radio standard… for example, LTE, 5G, or 5G-NR… or LoRaWAN. Thus, “communication module” is interpreted as any device/apparatus using any communication technology.
2) “evaluation unit … set up to receive and evaluate the data” in claim 1 – is interpreted as corresponding to the structure; [0116] as published, FIG. 1 state “The evaluation unit 22 is, for example, an external server which is set up to process the correspondingly received data, that is, the data transmitted by the recording assembly (assemblies) 14.”; the function of “evaluating” the data is not limited to any one method. See e.g. [0089] as published “Based on the data and the evaluation thereof, i.e. the evaluation of the progress of the construction project, it is also possible to analyze whether a construction project has been planned correctly and the cost structure thereof calculated correctly.” Accordingly, “evaluation unit” is interpreted as requiring a computer, such as server, performing correlations/evaluations/mathematical of data collected.
3) “time measurement unit wherein the evaluation unit is set up to determine a time measurement data profile” in claim 6 is interpreted based on [0139-0140] as published and FIG. 2 as referring to a processor/computer/accumulator measuring time such as duration.
Allowable Subject Matter
The 103 rejection for claim 17; and then it’s dependent claim 19, is withdrawn. Claims 17-18 are now allowable over the prior art based on the combination of: 1) robot of a scaffold transport system which travels automatically along a rail system; 2) recording system having a current input interface, a current output interface, at least one sensor arranged between the current input interface and the current output interface in a direction of current flow, 3) a buffer memory to temporarily store the data acquired by the at least one sensor, 4) wherein the recording system is configured to distinguish whether the robot is currently moving up, down, to the left or to the right based on the level of the current consumption.
Claim Rejections - 35 USC § 103
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claim(s) 1-4, 6-7, and 9-15 are rejected under 35 U.S.C. 103 as being unpatentable over Rakhmatulin (US 2020/0095784) in view of Oren (US 2020/0386605).
Concerning claim 1, Rakhmatulin discloses:
A recording system comprising a construction-site machine for transporting construction materials or construction components on a construction site, the construction-site machine (Rakhmatulin – see par 27- the rail elements or the scaffold elements having rail sections form movement paths for the at least one carriage module, along which the carriage module can move in order to transport objects; see par 95 - In FIG. 1, a scaffold transport system 10 is shown; See par 105-108 - In addition to the rail system 12, the scaffold transport system 10 comprises at least one carriage module 28, which is designed to move along the rail system 12; see par 176 - To control the scaffold transport system 10, in particular the movement of the individual carriage modules 28 (see FIG. 1), a system controller 78 is provided), comprising:
a robot of a scaffold transport system which travels automatically along a rail system of the scaffold transport system (Rakhmatulin – see par 54 - The individual carriage modules can thus be formed as robots, the movement processes of which are controlled by the system controller. The system controller can function as a central system unit which actuates the carriage modules. see par 76 - It is thus possible to transport objects efficiently and in an automated manner with the carriage module in a horizontal plane, for example a tier of scaffolding, when the carriage module is moved along the horizontally running rail section. The rail system is formed by the scaffold or at least fastened to the scaffold; see par 176 - To control the scaffold transport system 10, in particular the movement of the individual carriage modules 28 (see FIG. 1), a system controller 78 is provided.);
wherein the robot of the scaffold transport system comprises a recording device arranged on the construction-site machine, wherein the recording device comprises (Rakhmatulin – see par 70 - All of the (captured) data can be stored in a data-processing unit, for example a cloud server; see par 189 - The system controller 78 can access sensor data, which are captured by sensors 82, which are carried, for example, on the individual carriage modules 28, the rail system 12, in particular intersections 24,).
In light of Oren applied below, Oren also discloses:
Oren – see par 14 – remote computer system or a controller can execute blocks of method S100 (See FIG. 1); see par 31 - the smart hook: samples the geospatial position module and records geospatial locations of the smart hook at regular intervals (e.g., once per ten-second interval); samples the altimeter (e.g., at 1 Hz); writes these timestamped 3D geospatial locations to a local rolling buffer (e.g., a one-minute rolling buffer) in local memory; see par 139 – autonomous crane).
Rakhmatulin and Oren disclose:
at least one sensor set up to automatically acquire data relating to a component of the robot (Rakhmatulin – see par 51 – a system controller is provided, which is designed among other things to control the movement of the at least one carriage module along the rail system. The system controller can access sensor values in order to actuate an optimal movement of the at least one carriage module along the rail system; see par 60 - sensors capture corresponding data and transmit these to the system controller or to the system modules which are provided in the respective carriage modules. see par 189 - The system controller 78 can access sensor data, which are captured by sensors 82, which are carried, for example, on the individual carriage modules 28, the rail system 12, in particular intersections 24, and/or the people located on site. see par 63 - the carriage modules can comprise further sensors in addition to the named sensors.
Oren – see par 26 – smart hook has weight sensor, motion sensor and more),
a buffer … which is set up to at least temporarily store the data acquired by the at least one sensor (Rakhmatulin – see par 70 - All of the (captured) data can be stored in a data-processing unit, for example a cloud server).
For entire limitation, Oren discloses:
a buffer “memory” which is set up to at least temporarily store the data acquired by the at least one sensor (Oren – see par 31 - the smart hook: samples the geospatial position module and records geospatial locations of the smart hook at regular intervals (e.g., once per ten-second interval); samples the altimeter (e.g., at 1 Hz); writes these timestamped 3D geospatial locations to a local rolling buffer (e.g., a one-minute rolling buffer) in local memory).
Rakhmatulin and Oren disclose:
a communication module set up to wirelessly transmit the data acquired by the at least one sensor (in [0018] as published as being a communication device/apparatus in a recording housing/assembly; [0112], FIG. 1 states “The respective recording assembly 14 comprises a recording device 16 having a sensor 18 and a communication module 20.”; the function of “transmit the data” is by “data acquired by the at least one sensor can be sent to the evaluation unit by means of a communication technology using a mobile radio standard… for example, LTE, 5G, or 5G-NR… or LoRaWAN. Thus, “communication module” is interpreted as any device/apparatus using any communication technology.
Rakhmatulin – see par 51 - For example, the system controller generates a (two- or three-dimensional) model of the rail system in order to calculate optimized movement paths for the at least one carriage module. The rail system can also be stored by control systems using reference points, in that for example sensors or transmitters are provided at the intersections. See par 177-178 - By means of the system controller 78, the individual carriage modules 28 are actuated, wherein the system controller 78 can be formed as a central unit, which communicates with the carriage modules 28, or as a decentralized unit, which comprises several control modules which communicate with each other, in order together to form the system controller 78. In the case of the decentralized variant, the carriage modules 28 each comprise a control module, for example, wherein the carriage modules 28 communicate with each other. [0178] In the embodiment shown, a hybrid form is provided according to which the system controller 78 comprises a central control unit 80 (See e.g. FIG. 1 ) and the individual carriage modules 28 each comprise control modules 81, which all communicate with each other), and
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see also Oren – see par 23 - The smart hook can then: transmit lift event records to a local computing device and/or to a remote computer system for storage; see FIG. 5, par 26 – smart hook includes… wireless communication module to transmit raw data)
a housing in which the at least one sensor, the buffer memory, and the communication module are accommodated (Rakhatulin – see FIG. 1, see par 178 - individual carriage modules comprising control modules 81; see par 189 - sensors 82 carried on carriable modules 28, the rail system;
see also Oren – see par 21 - The smart hook (or the remote computer system) can: assign (and update) a buffer distance for a particular object carried by the smart hook event based on data collected by sensors in the smart hook during a lift event; see par 23 - The smart hook can then: transmit lift event records to a local computing device and/or to a remote computer system for storage, see par 31 - the smart hook: samples the geospatial position module and records geospatial locations of the smart hook at regular intervals (e.g., once per ten-second interval); samples the altimeter (e.g., at 1 Hz); writes these timestamped 3D geospatial locations to a local rolling buffer (e.g., a one-minute rolling buffer) in local memory; see par 35 - The smart hook can store this list of object types in local memory),
wherein the recording system further comprises an evaluation unit set up to receive and evaluate the data transmitted by the communication module and correlate the data with a mass of the construction materials or construction components transported by the robot (for ‘evaluation unit’ - Applicant’s [0116] as published, FIG. 1 state “The evaluation unit 22 is, for example, an external server which is set up to process the correspondingly received data, that is, the data transmitted by the recording assembly (assemblies) 14.”; the function of “evaluating” the data is not limited to any one method. See e.g. [0089] as published “Based on the data and the evaluation thereof, i.e. the evaluation of the progress of the construction project, it is also possible to analyze whether a construction project has been planned correctly and the cost structure thereof calculated correctly.” [0036] as published states “The measurement sensor can also measure how long the construction-site machine moves and thus indicate the height of the construction project. Thus, it can be determined how fast the construction project progresses and how high the productivity on the construction site is, and at what points.”
Rakhmatulin see par 67 - For example, during operation, the scaffold transport system, in particular the at least one carriage module, collects data on the process of the erection of the scaffold, such as the quantity of transported weight, waiting times of at least one worker and/or of the at least one carriage module, type of activity, time required for loading or unloading the at least one carriage module, time required for transporting scaffold parts and inactive time, start of the working time and end of the working time, …, in particular the system controller, and further data generated by sensors. See par 79 - the carriage modules 28 are designed to transport at least double their tare weight as a load, for example a load of at least approx. 60 kg in the case of a tare weight of 30 kg, wherein the carriage modules 28 can usually transport loads of more than 100 kg; see par 17 - The smart hook (or the remote computer system) can then: retrieve load handling specifications for objects carried by the smart hook during lift events; track motion of these objects during these lift events; verify that motion of these objects during these lift events falls within these load handling specifications; and then issue alarms and serve notifications—such as to a crane operator, a site manager, and/or personnel nearby;
See also Oren - see par 23 - the smart hook can then: transmit lift event records to a local computing device and/or to a remote computer system for storage, construction activity timeline generation, and/or insight extraction; see par 140 - The systems and methods described herein can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The instructions can be executed by computer-executable components integrated with the application, applet, host, server),
wherein the evaluation unit is set up to apply data analysis technologies and/or machine learning techniques to correlate the data acquired by the at least one sensor with the mass of construction materials and/or construction components transported by the construction-site machine (Rakhmatulin – see par 66 - The system controller can possess artificial intelligence or machine-learning technologies, so that it can learn automatically during operation.
Oren – see par 15 - For example, the smart hook (or the remote computer system) can implement template matching, deep learning, and/or artificial intelligence techniques to distinguish different types of objects lifted by the separation membrane, such as including: a long steel beam based on a linear increase in load measured by the weight sensor in the smart hook as the beam is lifted and low-amplitude natural vibrations between 100 Hz and 1000 Hz measured by a motion sensor… ; … In these examples, the smart hook (or the remote computer system) can generate a lift event for each of these loads. For each of these lift events, the smart hook can also store: a maximum (or “peak”) weight measured by the weight sensor during the lift event; geospatial locations output by the geospatial position module when the load was first detected and then unloaded; and altitudes output by an altimeter in the smart hook when the load was first detected and then unloaded. Furthermore, when the concrete hopper is then unloaded, lifted away from the drop-off location, and returned to the pickup location, the smart hook (or the remote computer system) can record a change in weight of the concrete hopper as an amount of concrete delivered to this drop-off location and write this amount of concrete to the corresponding lift event record. see par 17 - The smart hook (or the remote computer system) can then: retrieve load handling specifications for objects carried by the smart hook during lift events; track motion of these objects during these lift events; verify that motion of these objects during these lift events falls within these load handling specifications; and then issue alarms and serve notifications—such as to a crane operator, a site manager, and/or personnel nearby—in real time when motion of these objects falls outside of their prescribed load handling specifications or approaches limits defined in these prescribed load handling specifications. see par 59 - In the foregoing implementations, the autonomous vehicle can additionally or alternatively execute artificial intelligence, machine learning, and/or deep learning techniques to: ingest timeseries load and/or motion data, etc. recorded as the object is lifted by the smart hook; and output a confidence score or rank for a type of the object carried by the smart hook; see par 61 - The smart hook can also calculate a sloshing frequency of the concrete hopper, such as by implementing Fourier analysis to extract a sloshing frequency from a motion signal and/or a load signal captured during this period. ).
Both Rakhmatulin and Oren are analogous art as they are directed to monitoring lift events at construction sites and autonomous components (see Rakhmatulin Abstract, par 54 (carriage modules formed as robots); Oren Abstract, par 139 (Autonomous cranes)). Rakhmatulin discloses that captured data can be stored in a data-processing unit, for example, a cloud server (See par 70) and that its controller can process artificial intelligence or machine-learning technologies (See par 66). Oren improves upon Cohen by disclosing placing data in memory related to buffer, showing a number of different modules that can be executed by a computer, all as a “recording assembly,” communicating with a remote computer system (e.g. Oren par 24, 140 – a server) and using artificial intelligence to distinguish different types of objects lifted as well as when objects fall outside load handling specifications and sloshing frequency based on motion signal and/or load signal (See Oren par 15, 17, 59, 61). One of ordinary skill in the art would be motivated to further include identifying memory related to buffer and communicating to a server and using artificial intelligence to analyze loads transported to efficiently improve upon the storing of data in a cloud server and the “artificial intelligence” in Rakhmatulin.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of controlling carriages formed as robots in a scaffolding environment in Rakhmatulin to further have memory related to buffer and computer executed modules as disclosed in Oren, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable and there is a reasonable expectation of success.
Concerning claim 2, Rakhmatulin discloses:
The recording system according to claim 1, wherein the at least one sensor is a movement direction sensor, which is set up to detect the direction of movement of the component of the robot ([0032-0034, 143-145] – movement direction sensor may be designed as an air pressure sensor; … movement direction sensor can be an acceleration sensor and/or a gyroscope Rakhmatulin discloses the limitations based on broadest reasonable interpretation in light of the specification – see par 62 – capture data from sensors; sensors include “acceleration and/or gyro sensors”; see par 53 - The system controller can comprise a real-time position detection unit, which is designed to detect the positions of people, for example workers, and/or of carriage module(s) automatically. The system controller can accordingly co-ordinate the movements of the individual carriage modules automatically in order to prevent collisions or interference between the carriage modules and/or the workers;
Oren also discloses – see par 26 – a motion sensor (e.g. a gyroscope, accelerometer) configured to output signals representing accelerations and/or angular velocities of the smart hook), or a measurement sensor, which is set up to detect a performance parameter of the component of the robot ([0035, 0148] as published - If the sensor is configured as a measurement sensor, corresponding performance parameters of the component of the construction-site machine can be detected. The performance parameter may be electrical performance parameters, for example electrical power, electrical current and/or electrical voltage, or mechanical performance parameters, for example torque, force, work and/or mechanical power.
Examiner notes “measurement sensor” is in alternative, and is not required at this time
Nonetheless, Oren discloses describes the limitations based on broadest reasonable interpretation in light of the specification - a sensor that detects a “force” –see par 26 - a weight sensor (e.g., a load cell) interposed between the crane loop and the lifting hook and configured to output a signal representing a tensile force between the crane loop and the lifting hook; see par 15 - the smart hook can also store: a maximum (or “peak”) weight measured by the weight sensor during the lift event).
Obvious to combine for the same reasons as claim 1 above.
Concerning claim 3, Rakhmatulin and Oren disclose:
The recording system according to claim 1, wherein the evaluation unit is an external server that is formed separately from the recording device (Oren – see par 24 – blocks of method S100 can be executed by a computer system, a remote computer system, remote from the smart hook, broadcast by the smart hook during operation at the construction site. The wireless gateway—such as located inside a cab or near a base of the crane—can then return these data to a remote computer system (e.g., a remote server) via a computer network; see par 140 - The systems and methods described herein can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The instructions can be executed by computer-executable components integrated with the application, applet, host, server).
Obvious to combine for the same reasons as claim 1 above.
Concerning claim 4, Rakhmatulin discloses:
The recording system according to claim 1, wherein the recording assembly, via the evaluation unit, is configured to evaluate the data in real time (Rakhmatulin – see par 53 - The system controller can comprise a real-time position detection unit, which is designed to detect the positions of people, for example workers, and/or of carriage module(s) automatically.
Oren – see par 135 - remote computer system can also update the manager portal to reflect these metrics, such as in real-time during the lift event or upon conclusion of the lift event).
Concerning claim 6, Rakhmatulin discloses:
The recording system according to claim 1, wherein the recording system comprises a time measurement unit, wherein the evaluation unit is set up to determine a time measurement data profile of the data acquired by the sensor (based on Applicant’s [0139-0140] as published and FIG. 2, “time measurement unit” interpreted as referring to a processor/computer/accumulator measuring time such as duration.
Rakhmatulin – see par 67 - during operation, the scaffold transport system, in particular the at least one carriage module, collects data on the process of the erection of the scaffold, such as the quantity of transported weight, waiting times of at least one worker and/or of the at least one carriage module, type of activity, time required for loading or unloading the at least one carriage module, time required for transporting scaffold parts and inactive time, start of the working time and end of the working time, time and number of safety problems identified by the scaffold transport system, in particular the system controller, and further data generated by sensors;
see also Oren – see par 39 - the smart hook can: sample the weight sensor; convert outputs of the weight sensor into weight magnitudes; and write these timestamped weight magnitudes—along with motion data read from motion sensors, geospatial location data, and altitude—to a local rolling buffer (e.g., a one-minute rolling buffer) see par 133 - calculate an in-air time based on a duration between initial loading and final unloading of the object; ] The systems and methods described herein can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The computer-executable component can be a processor but any suitable dedicated hardware device can (alternatively or additionally) execute the instructions.).
Obvious to combine for the same reasons as claim 1 above.
Concerning claim 7, Rakhmatulin discloses:
The recording system according to claim 1, wherein the sensor is arranged on a movable component of the robot which serves to transport the construction materials or the construction components (Cohen – See FIG. 1, 6 showing S100, where machine is “crane”; movable component is smart hook; see par 34-35, FIG. 6 - the computer system can interface with a smart hook—installed on a lift hook of a crane (describing a “construction-site machine”)—to receive lift event data as materials and tools are rigged to the crane at pickup locations on the construction site and unloaded from the crane at other drop-off locations on the construction site; see par 79 - The smart hook can additionally or alternatively derive lift event metrics from these data and write these metrics to the lift event record. Smart hook can: identify a floor or level number and a wing or region of a building where the load was delivered based on the geospatial location and altitude of the smart hook (describing a movable component, a hook, of the crane machine) when the object was unloaded and the site map; calculate an in-air time based on a duration between initial loading and final unloading of the object).
Concerning claim 9, Rakhmatulin discloses:
The recording system (Rakhmatulin – see par 50 - According to an embodiment, several carriage modules are provided. . The individual carriage modules can carry different objects depending on which load-bearing unit is arranged on the corresponding carrier section of the carriage module. A continuous flow of material can hereby be achieved, since several carriage modules are moving simultaneously in the rail system with correspondingly loaded load-bearing units.) according to claim 1, comprising a plurality of construction-site machines, wherein the sensor is arranged on a movable component of the respective construction-site machine which serves to transport the construction materials or the construction components (Rakhmatulin – see par 52 - The sensors can be external sensors, which have been attached to the corresponding rail elements or at least have been allocated to the rail elements retrospectively; see par 189 - The system controller 78 can access sensor data, which are captured by sensors 82, which are carried, for example, on the individual carriage modules 28, the rail system 12, in particular intersections 24).
wherein the evaluation unit is provided to which the corresponding sensors of the plurality of construction-site machines transmit their data respectively, and wherein the evaluation unit evaluates the respectively acquired data and makes it available centrally” (Applicant’s [0151] as published states “The common evaluation unit 22 may also be cloud-based, cooperating with a plurality of recording assemblies 14 to obtain corresponding data from different construction sites”
Rakhmatulin –see par 70 - All of the (captured) data can be stored in a data-processing unit, for example a cloud server;
See also Oren – see par 14 – remote computer system or a controller can execute blocks of method S100 (See FIG. 1); see par 139 – autonomous crane; see par 17 - The smart hook (or the remote computer system) can then: retrieve load handling specifications for objects carried by the smart hook during lift events; track motion of these objects during these lift events; verify that motion of these objects during these lift events falls within these load handling specifications; and then issue alarms and serve notifications)
Obvious to combine for the same reasons as claim 1 above.
Concerning claim 10, Cohen discloses:
The recording system according to claim 1, wherein a mobile terminal is provided which is set up to acquire additional data and to transmit it to the evaluation unit (Rakhmatulin – see par 69 - The workers who work with the scaffold transport system can be equipped with a portable device so that steps, elevation and further data are captured and/or recorded. The data can be synchronized with the at least one carriage module.)
Concerning claim 11, Rakhmatulin discloses:
A method of analyzing a construction project (Rakhmatulin – see par 67 - the scaffold transport system, in particular the at least one carriage module, collects data on the process of the erection of the scaffold, such as the quantity of transported weight, waiting times of at least one worker and/or of the at least one carriage module, type of activity, time required for loading or unloading the at least one carriage module, time required for transporting scaffold parts and inactive time, start of the working time and end of the working time), comprising steps of:
-providing a construction-site machine for transporting construction materials and/or construction components on a construction site (Rakhmatulin – see par 27- the rail elements or the scaffold elements having rail sections form movement paths for the at least one carriage module, along which the carriage module can move in order to transport objects), the construction-site machine comprising
a robot of a scaffold transport system, which travels automatically along a rail system of the scaffold transport system (Rakhmatulin - see par 54 - The individual carriage modules can thus be formed as robots, the movement processes of which are controlled by the system controller. see par 95 - In FIG. 1, a scaffold transport system 10 is shown; See par 105-108 - In addition to the rail system 12, the scaffold transport system 10 comprises at least one carriage module 28, which is designed to move along the rail system 12; see par 176 - To control the scaffold transport system 10, in particular the movement of the individual carriage modules 28 (see FIG. 1), a system controller 78 is provided), and
a recording device arranged on the robot of the construction-site machine (Rakhmatulin – see par 70 - All of the (captured) data can be stored in a data-processing unit, for example a cloud server; see par 189 - sensors 82 carried on carriable modules 28, the rail system;
see also Oren – see par 14 – remote computer system or a controller can execute blocks of method S100 (See FIG. 1); see par 31 - the smart hook: samples the geospatial position module and records geospatial locations of the smart hook at regular intervals (e.g., once per ten-second interval); samples the altimeter (e.g., at 1 Hz); writes these timestamped 3D geospatial locations to a local rolling buffer (e.g., a one-minute rolling buffer) in local memory; see par 139 – autonomous crane) having at least one sensor (Rakhmatulin – see par 63 - see par 63 - the carriage modules can comprise further sensors in addition to the named sensors) a buffer … which is set up to at least temporarily store the data acquired by the at least one sensor (Rakhmatulin – see par 70 - All of the (captured) data can be stored in a data-processing unit, for example a cloud server).
For entire limitation, Oren discloses:
a buffer “memory” which is set up to at least temporarily store the data acquired by the at least one sensor (Oren – see par 31 - the smart hook: samples the geospatial position module and records geospatial locations of the smart hook at regular intervals (e.g., once per ten-second interval); samples the altimeter (e.g., at 1 Hz); writes these timestamped 3D geospatial locations to a local rolling buffer (e.g., a one-minute rolling buffer) in local memory).
Rakhmatulin and Oren disclose:
and a communication module (Rakhmatulin – [as in claim 1] see par 51 ; See par 177-178 - By means of the system controller 78, the individual carriage modules 28 are actuated, wherein the system controller 78 can be formed as a central unit, which communicates with the carriage modules 28, or as a decentralized unit, which comprises several control modules which communicate with each other, in order together to form the system controller 78.),
-acquiring data relating to a component of the robot used in the construction project in an automatic manner via the sensor of the robot (Rakhmatulin see par 67 - For example, during operation, the scaffold transport system, in particular the at least one carriage module, collects data on the process of the erection of the scaffold, such as the quantity of transported weight, waiting times of at least one worker and/or of the at least one carriage module, type of activity, time required for loading or unloading the at least one carriage module, time required for transporting scaffold parts and inactive time, start of the working time and end of the working time, …, in particular the system controller, and further data generated by sensors.),
-transmitting the acquired data to an evaluation unit (Rakhmatulin [same as cl. 1] – see par 67; See par 70 - All of the (captured) data can be stored in a data-processing unit, for example a cloud server; see par 79
See also Oren - see par 23 - the smart hook can then: transmit lift event records to a local computing device and/or to a remote computer system for storage, construction activity timeline generation, and/or insight extraction; see par 140 - The systems and methods described herein can be embodied and/or implemented at least in part as a machine configured to receive a computer-readable medium storing computer-readable instructions. The instructions can be executed by computer-executable components integrated with the application, applet, host, server), and
evaluating the transmitted data to obtain evaluation results, the transmitted data being correlated with a mass of construction materials or construction components transported by the robot to evaluate progress of the construction project or construction-site machine data being derived from the transmitted data to take machine-specific data of the robot into account (Examiner notes there is an alternative here -it only requires one of “evaluate progress” or “construction-site machine… into account”
Rakhmatulin [as in cl. 1] – see par 67, 70, 79, par 174 - Because of the automated scaffold transport system 10, the objects are transported efficiently since the transporting is effected in an automated manner. If several carriage modules 28 are used, in addition a constant flow of material is guaranteed, since material can be provided at a desired rate in spite of long distances.
See also Oren [as in cl. 1] - see par 23 - the smart hook can then: transmit lift event records to a local computing device and/or to a remote computer system for storage, construction activity timeline generation, and/or insight extraction; see par 140, see par 187 - t can be provided that the system controller 78 comprises artificial intelligence or machine-learning technologies which make it possible for the actuation of the carriage modules 28 to become more efficient and/or more autonomous in the course of the operation of the scaffold transport system 10; see par 192 - If a two-dimensionally closed rail system area 26 has been created, a continuous flow of material can be provided, in that, for example, several carriage modules 28 are operated at the same time by means of the system controller 78 (see FIG. 1)).
wherein the evaluation unit is set up to apply data analysis technologies and/or machine learning techniques to correlate the data acquired by the at least one sensor with the mass of construction materials and/or construction components transported by the construction-site machine (Rakhmatulin [same as cl. 1] – see par 66 - The system controller can possess artificial intelligence or machine-learning technologies, so that it can learn automatically during operation.
Oren [same as cl. 1] – see par 15 - For example, the smart hook (or the remote computer system) can implement template matching, deep learning, and/or artificial intelligence techniques to distinguish different types of objects lifted; see par 17 - The smart hook (or the remote computer system) can then: retrieve load handling specifications for objects carried by the smart hook during lift events; track motion of these objects during these lift events; verify that motion of these objects during these lift events falls within these load handling specifications; and then issue alarms and serve notifications—such as to a crane operator, a site manager, and/or personnel nearby—in real time when motion of these objects falls outside of their prescribed load handling specifications or approaches limits defined in these prescribed load handling specifications. see par 59 - In the foregoing implementations, the autonomous vehicle can additionally or alternatively execute artificial intelligence, machine learning, and/or deep learning techniques to: ingest timeseries load and/or motion data, etc. recorded as the object is lifted by the smart hook; and output a confidence score or rank for a type of the object carried by the smart hook; see par 61 - The smart hook can also calculate a sloshing frequency of the concrete hopper, such as by implementing Fourier analysis to extract a sloshing frequency from a motion signal and/or a load signal captured during this period).
Obvious to combine for the same reasons as claim 1 above.
Concerning claim 12, Rakhmatulin discloses providing a flow of material at a “desired rate” (See par 174) and using artificial intelligence to make actuation of carriage modules more efficient in operation of scaffold transport system (See par 187).
Oren discloses:
The method according to claim 11, wherein the transmitted data is extrapolated during evaluation (Oren – see par 54 - the smart hook predicts that an object is one of a formwork and a rebar structure based on a weight and motion of the object during lifting.)
Obvious to combine for the same reasons as claim 1 above. In addition, Rakhmatulin discloses providing a flow of material at a “desired rate” (See par 174) and using artificial intelligence to make actuation of carriage modules more efficient in operation of scaffold transport system (See par 187). Oren improves upon Rakhmatulin by performing data analysis on data such as weight that is collected.
Concerning claim 13, Rakhmatulin discloses using machine learning to become more efficient in the course of operation of the scaffold transport system (See par 187).
Oren discloses:
The method according to claim 11, wherein the evaluation results of several construction projects are collected or evaluation results of at least one already completed construction project are used in the analysis of the at least one construction project (Oren – see par 27 - the smart hook may follow a general contractor or site manager to various job sites over time in order to supply load-related insights to the general contractor or site manager over time.).
Obvious to combine for the same reasons as claim 1 above. In addition, Rakhmatulin discloses using machine learning to become more efficient in the course of operation of the scaffold transport system (See par 187). Oren improves upon Rakhmatulin by disclosing that multiple site information can be collected to supply more insights over time.
Concerning claim 14, Rakhmatulin discloses:
The method according to claim 11, wherein the evaluation results are used to monitor a current project planning, to perform a future project planning, to predict maintenance periods of the construction-site machine, or to generate recommended actions (claim in alternative – Rakhmatulin – see par 198 - the system controller 78 can monitor the battery status of the carriage modules 28 and actuate them such that they are automatically moved to a charging point when the charge status is critical;
Oren – see par 27 - the smart hook may follow a general contractor or site manager to various job sites over time in order to supply load-related insights to the general contractor or site manager over time. see par 35 - the remote computer system can return a list of object types that represents objects that the crane is likely to lift—via the smart hook—during a current work period. The smart hook can store this list of object types in local memory and/or adjust local object models to reflect a high probability or expectation that the smart hook will interface with objects of these types during the upcoming work period. see par 114 - the smart hook can also insert a recommendation for an action to recover from the motion event. For example, if the pendulum amplitude of the object exceeds a threshold pendulum amplitude or if the resonance amplitude of the object exceeds a resonance amplitude threshold, the smart hook can: insert—into the notification—a prompt to lower the object and/or retract the trolley toward the rotation table (e.g., to reduce torque on the base of the crane)).
Obvious to combine for the same reasons as claim 1 and claim 13 above.
Concerning claim 15, Rakhmatulin and Oren disclose:
The method according to claim 11, wherein historical data from a plurality of construction-site machines or historical data from a plurality of sources are used in the analysis of the construction project (Oren – see par 27 - the smart hook may follow a general contractor or site manager to various job sites over time in order to supply load-related insights to the general contractor or site manager over time).
Obvious to combine for the same reasons as claim 1 and 13 above.
Claim 5 is rejected under 35 U.S.C. 103 as being unpatentable over Rakhmatulin (US 2020/0095784) in view of Oren (US 2020/0386605), as applied to claims 1-4, 6-7, and 9-15 above, and further in view of Lim (KR 20130142299).
Concerning claim 5, Rakhmatulin discloses moving carriage modules to a charging point when charge status is critical (See par 198). Oren discloses having a weight sensor (e.g. load cell) interposed between the crane loop and the lifting hook (See par 29).
Lim discloses:
The recording system according to claim 1, wherein a current input interface and a current output interface are provided, wherein the at least one sensor is arranged between the current input interface and the current output interface in a direction of current flow (Lim – see page 3, 2nd paragraph – current sensor unit 30 is connected to the power supply 10, and serves to output a current signal corresponding to a predetermined ratio to the amount of current input to the drive unit 20. See page 3, 3rd paragraph - That is, by including the current sensor unit 30 according to the present invention, it is possible to detect a change in the amount of current injected in accordance with the hoist load; see page 4, 2nd paragraph - as the load increases, the magnitude of the initial current is almost constant, but the generation time is long, and the magnitude of the steady current increases in proportion to the load amount, as the current shape and waveform characteristics of both are different from those of FIG. 9).
Rakhmatulin, Oren, and Lim are analogous art as they are directed to monitoring lift events at construction sites (see Cohen Abstract; Lim Abstract). Rakhmatulin discloses moving carriage modules to a charging point when charge status is critical (See par 198). Oren discloses having a weight sensor (e.g. load cell) interposed between the crane loop and the lifting hook (See par 29). Lim improves upon Rakhmatulin and Oren by disclosing having current flow through sensor, where the sensor is measuring weight of what’s being lifted. One of ordinary skill in the art would be motivated to further include electrical connection for a sensor measuring weight to efficiently improve upon the electrical system of Rakhmatulin that includes a sensor overload detection (e.g. pressure – par 62) as carriage modules transport different masses (e.g. 100 kg) and the weight sensor from Oren.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of controlling carriages formed as robots in a scaffolding environment in Cohen and have a memory related to buffer and computer executed modules in Oren, to further have arrangement for current flowing through a sensor as disclosed in Lim, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable and there is a reasonable expectation of success.
Claim 8 is rejected under 35 U.S.C. 103 as being unpatentable over Rakhmatulin (US 2020/0095784) in view of Oren (US 2020/0386605), as applied to claims 1-4, 6-7, and 9-15 above, and further in view of Wang (US 2020/0086481).
Concerning claim 8, Rakhmatulin discloses that the individual carriage modules each comprise control modules 81, which all communicate with each other (See par 178). Oren discloses having crane identifier (See par 116) and its smart hook can include other sensors such as an RFID reader (see par 26).
Wang discloses:
The recording system according to claim 1, wherein an identification means is provided on the robot, wherein the identification means is connected to the communication module (Applicant’s specification [0058, 0065, 0175] as published give examples of Bluetooth, RFID, NFC tag for connecting between “identification means and communication module” Wang – see par 39 - The control mechanism is configured to control the operating state of the lifting robot 10. The detection component is configured to detect the operating state of the lifting robot 10 and the external environmental state. see par 59 - In order to identify and control each lifting robot 10, each lifting robot 10 has a unique number.).
Rakhmatulin, Oren, and Wang analogous art as they are directed to monitoring lift events and autonomous components (see Rakhmatulin Abstract, par 54 (carriage modules formed as robots); Oren Abstract, par 139 (Autonomous cranes); Wang Abstract, par 39). Rakhmatulin discloses that the individual carriage modules each comprise control modules 81, which all communicate with each other (See par 178). Oren discloses having crane identifier (See par 116) and its smart hook can include other sensors such as an RFID reader (see par 26). Wang improves upon Rakhmatulin and Oren by disclosing having each robot have its own unique number for identifying and controlling each lifting robot. One of ordinary skill in the art would be motivated to further include using identification of each robot that is communicated to another computing device for control to efficiently improve upon the individual carriage modules each communicating with each other in Rakhmatulin (See par 178) and RFID (par 26) or identifiers (See par 116) in Oren.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of controlling carriages formed as robots in a scaffolding environment in Rakhmatulin to further have identifiers as disclosed in Oren, and to further have unique numbers for identifying and controlling robots in Wang, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable and there is a reasonable expectation of success.
Claims 16 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Rakhmatulin (US 2020/0095784) in view of Oren (US 2020/0386605), as applied to claims 1-4, 6-7, and 9-15 above, and further in view of Dinius (US 2021/0197376).
Concerning claim 16, Rakhmatulin discloses moving carriage modules to a charging point when charge status is critical (See par 198). Oren discloses having a weight sensor (e.g. load cell) interposed between the crane loop and the lifting hook (See par 29). Oren discloses “the smart hook can monitor an orientation of the object, such as: by implementing dead reckoning techniques to interpret pitch and roll orientations of the object based on timeseries motion data collected by the motion sensor” and “The smart hook can then estimate a probability of partial or total load loss as a function of (e.g., proportional to): pitch and roll orientations relative to a nominal position in a horizontal plan” (See par 86).
Dinius discloses:
The recording system according to claim 1, wherein the recording system is configured to determine a current consumption profile of the construction- site machine by recording a current consumption over time (Dinius – see par 37 - The operational cycles of the spatiotemporal controller may vary depending on processing power of the robot, desired granularity over robotic movements, and/or power consumption. FIG. 3 conceptually illustrates an example of spatiotemporal controller 310 of a robot completing waypoint 320 from a spatiotemporal plan by continuously executing different instance objectives 330 that partition the overall task or objective of waypoint 320 into minute actuator movements or operations that are updated at each operational cycle of spatiotemporal controller 310.), and wherein the recording system is configured to distinguish whether the construction-site machine is currently moving up, down, to the left or to the right based on the level of the current consumption (Dinius – see par 42 - For example, each instance objective of the first subset of instance objectives 340 may include spatiotemporal controller 310 gradually increasing power that is provided to the robot's drive motors from 0 amperes (A) to 5 A. Spatiotemporal controller 310 may control the drive motor by adjusting other operational parameters (e.g., voltage and current) of the drive motor, or by issuing commands (e.g., reach a particular revolutions per minute, reach a particular velocity, etc.) that the drive motor responds to with adjusted operational parameters. See par 43 - During the first subset of instance objectives 340, the robot may be unable to cover 0.2 feet at each instance objective, and may instead cover, on average, 0.1 feet at each instance objective. Spatiotemporal controller 310 may compensate for the short distance traversed during execution of the first subset of instance objectives 340 by bringing the robot to a speed at which it may cover 0.5 feet with each instance objective of a subsequent second subset of instance objectives 350. For instance, spatiotemporal controller 310 may increase power to the drive motors of the robot while continuously monitoring a velocity receiver, accelerometer, speedometer, or other speed sensor to determine whether the robot is moving a desired amount of distance during execution of each instance objective).
Rakhmatulin, Oren, and Dinius are analogous art as they are directed to monitoring events and autonomous components (see Cohen Abstract; Dinius Abstract, par 13, 17). Rakhmatulin discloses moving carriage modules to a charging point when charge status is critical (See par 198) and “the system controller generates a (two- or three-dimensional) model of the rail system in order to calculate optimized movement paths for the at least one carriage module. The rail system can also be stored by control systems using reference points, in that for example sensors or transmitters are provided at the intersections” (See par 51). Oren discloses having a weight sensor (e.g. load cell) interposed between the crane loop and the lifting hook (See par 29); and using motion sensor and estimating an orientation (See par 86). Dinius improves upon Rakhmatulin and Oren by disclosing measuring and adjusting the amount of current and electrical power for a robot to reach a desired distance. One of ordinary skill in the art would be motivated to further include measuring and adjusting the amount of current and electrical power for a robot to reach a desired distance to efficiently improve upon the electrical system that is attempting to calculate “optimized movement paths” of Rakhmatulin and the motion sensor and estimated orientation from Oren.
Accordingly, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the system and method of controlling carriages formed as robots in a scaffolding environment in Rakhmatulin and have a memory related to buffer and computer executed modules in Oren, to further measure and adjust electrical amperes to move a robot a desired amount of distance as disclosed in Dinius, since the claimed invention is merely a combination of old elements, and in combination each element merely would have performed the same function as it did separately, and one of ordinary skill in the art would have recognized that the results of the combination were predictable and there is a reasonable expectation of success.
Concerning claim 19, Rakhmatulin and Oren and Dinius disclose:
The recording system according to claim 16, wherein the sensor is a current sensor (Dinius – see par 18 – voltage sensor, electric current sensor may be available on a robot).
Obvious to combine for the same reasons as claim 1 and claim 16 above. In addition, one of ordinary skill in the art would be motivated to further include voltage or electric sensor to efficiently improve upon the sensors of Rakhmatulin and Oren.
Response to Arguments
Applicant's arguments filed 2/5/26 have been fully considered but they are not persuasive and/or are moot in view of the new rejections.
Applicant argues that “portable device” in Rakhmatulin is on a worker (pointing to paragraph 69, 179) and Rakhmatulin cannot disclose “recording system” in amended claim. Remarks, pages 8-9. In response, Examiner respectfully disagrees. The arguments are moot in view of the revised rejection necessitated by the amendments.
Applicant argues that Rakhmatulin does not disclose “evaluation unit correlating sensor data with mass” (pointing to paragraphs 67, 70, and 79) because this is “in a data processing unit.” Remarks, page 9. In response, Examiner respectfully disagrees. The arguments are moot in view of the revised rejection necessitated by the amendments.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to IVAN R GOLDBERG whose telephone number is (571)270-7949. The examiner can normally be reached 830AM - 430PM.
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/IVAN R GOLDBERG/Primary Examiner, Art Unit 3619
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