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 .
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
Claims 16-30 are rejected under 35 USC 112(b) as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor regards as the invention.
Claim 16
Claim 16 recites “The diagnostic method of an activity of a crane for…”; there is insufficient antecedent basis for this limitation. The examiner notes that the applicant likely intended to recite “A diagnostic method…” and that an amendment of this form would enable the withdrawal of this rejection. Additionally, dependent claims 17-30 are also rejected under 35 USC 112(b) by virtue of their dependence from claim 16.
Claims 18
Claim 18 recites “…wherein the at least one internal anomaly (A1) comprises…”. Claim 18 includes the identifier (A1), while its parent, claim 17, does not. This leaves the scope of Claim 18 indefinite because it is unclear what impact, if any, including the identifier (A1) has. The examiner respectfully suggests that the label A1 should appear either each time the element “the at least one internal anomaly” is recited, or not at all.
Furthermore, claim 18 recites “…the equipment called faulty equipment…”; there is insufficient antecedent basis for this limitation.
Claim 21
The phrases "such as" and “for example” render the claim indefinite because it is unclear whether the limitations following the phrases are part of the claimed invention. See MPEP § 2173.05(d).
Claim 25
The recited list “…wherein the at least one organizational anomaly is identified from at least one of the following data among the crane data: data representative of a presence or activity of the crane operator in the crane, maneuver counting data, data representative of a stop controlled by an anti-collision system, cycle counting data load lifting, data representative of pause time between two maneuvers, data representative of types of maneuver, data representative of a crane type” renders the claim indefinite as it is unclear whether the list is intended to end with the word “and” or the word “or”.
Claim Rejections - 35 USC § 101
35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Evaluating whether a claim is eligible subject matter under 35 U.S.C. 101 adheres to the following eligibility analysis procedure:
Step 1: The examiner determines whether then claim belongs to a statutory category. See MPEP § 2016(III).
Step 2A, prong 1: The examiner evaluates whether the claim recites a judicial exception. As explained in MPEP § 2106.04(II), a claim “recites” a judicial exception when the judicial exception is “set forth” or “described” in the claim.
Step 2A, prong 2: The examiner evaluates whether the claim as a whole integrates the recited judicial exception into a practical application of the exception. This evaluation is performed by:
identifying whether there are any additional elements recited in the claim beyond the judicial exception, and
evaluating those additional elements individually and in combination to determine whether the claim as a whole integrates the exception into a practical application.
Step 2B: The examiner evaluates if additional elements of the claim provide an inventive concept (also called "significantly more" than the recited judicial exception).
Claims 16-30 are rejected under 35 USC 101 for being directed to an abstract idea without significantly more.
Claim 16 (a method claim)
Step 2A-I: This claim recites a judicial exception, namely a mathematical algorithm for processing data from a crane to detect drops in activity and associated anomalies, comprising the following steps:
for each activity period, processing the work data to calculate a work time of the crane during the activity period, and comparison of said work time with at least one activity threshold to determine whether said activity period is a drop in activity period or not
for each drop in activity period, processing crane data and environmental data associated at least with said drop in activity period to identify at least one anomaly of the construction site or the crane, which anomaly being associated with said drop in activity period
Step 2A-II: The claim does not integrate the recited mathematical algorithm into a practical application, as the mere performance of the algorithm itself does not improve crane safety or reduce the frequency of drop in activity periods.
Step 2B: The claim language recites the following additional elements:
detecting crane data coming from equipment of the crane comprising at least work data representative of a crane work implementing at least one maneuver of at least one structural element of the crane
detecting environmental data representative of a construction site environment comprising at least climatic data
logging by activity period of crane data and environmental data in…
…a remote database
However, additional elements (a), (b), and (c) are essential data gathering steps necessary for the performance of the recited mathematical algorithm and therefore do not amount to significantly more. Furthermore, additional element (d) is a generic computer component recited to perform its generic computer function, namely that of a datastore, and therefore does not amount to significantly more.
The dependent claims 17-25 and 29-30 are also rejected under 35 USC 101 for reciting an abstract idea without significantly more as they inherit the limitations of their parents claim(s) and do not set forth any further additional elements that amount to significantly more, instead only further elaborating upon the recited algorithmic steps and/or about the type of data detected.
Claim 26 (a method claim)
Step 2A-I: This claim recites a judicial exception as it inherits the limitations of its parent claim (claim 16).
Step 2A-II: The claim does not integrate the recited mathematical algorithm into a practical application as the mere performance of the algorithm itself does not improve crane safety or reduce the frequency of drop in activity periods.
Step 2B: The claim language recites the following additional element:
a remote analysis system, in communication with or comprising the remote database
However, this additional element (a) is merely a generic computer system configured for the analysis and processing of data via generic computer functions, in communication with or comprising the remote database, which itself has been previously determined to be a generic computer component configured to perform its generic computer function. Hence, this additional element does not amount to significantly more.
Dependent claim 27 merely further expands on the generic computer functions to be performed by the remote analysis system and thus is also rejected under 35 USC 101.Claim 28 (a method claim)
Step 2A-I: This claim recites a judicial exception, namely the mathematical algorithm recited in its parent claim (claim 16).
Step 2A-II: This claim does not integrate the recited mathematical algorithm into a practical application as the mere performance of the algorithm itself does not improve crane safety or reduce the frequency of drop in activity periods.
Step 2B: The claim language recites the following additional element:
a generation, or a display, or both, of an analysis report comprising, for the or each drop in activity period, information specific to the at least one identified anomaly
However, the generation and/or the display of an analysis report in additional element (a) is extra-solution activity carried out on the resultant data from the performance of the recited mathematical algorithm and therefore does not amount to significantly more. An example from MPEP § 2106.05(g) of court-recognized insignificant extra-solution data display and analysis: “’Selection information, based on types of information and availability of information in a power-grid environment, for collection, analysis and display’, Electric Power Group, LLC v. Alstom S.A., 830 F.3d 1350, 1354-55, 119 USPQ2d 1739, 1742 (Fed. Cir. 2016)”.
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.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 16-19 and 24-28 are rejected under 35 U.S.C. 103 as being unpatentable over Wiethorn, Jim D. (US 20220058890 A1, hereinafter Wiethorn) in view of Danel et al. (Proposal for Tower Crane Productivity Indicators Based on Data Analysis in the Era of Construction 4.0, Buildings, 2021, 11(1):21. https://doi.org/10.3390/buildings11010021; hereinafter Danel) and Jussel et al. (US 20180018641 A1, hereinafter Jussel).
Claim 16
Wiethorn discloses a diagnostic method of an activity of a crane (Abstract — “The crane risk logic apparatus receives crane data from the load moment indicator and determines various data analytics, such as, lift angle data, allowable capacity data, operator override data, anti-two-block activation data, operational time data, lift cycle count data, lift classification data, slewing speed data, wind speed data, warning message data, error message data, and winch direction and speed data for each crane lift cycle. The data analytics may be utilized to inform a crane operator evaluation or a crane maintenance schedule for the crane, for example.”; collecting activity data to inform a maintenance schedule is a diagnostic method), said diagnostic method implementing at least the following steps: detecting crane data coming from equipment of the crane ([0004] — “The CRL apparatus receives crane data from mechanical devices and the load moment indicator and determines various data analytics…”), and comprising at least work data representative of a crane work implementing at least one maneuver of at least one structural element of the crane ([0004] — “The CRL apparatus receives crane data from mechanical devices and the load moment indicator and determines various data analytics, such as, lift angle data, allowable capacity data, operator override data, anti-two-block activation data, operational time data, lift cycle count data, lift classification data, slewing speed data…”; lifting and slewing necessitate maneuvering of structural elements; that these analytics could be computed means the crane data would comprise at least work data representative of such); detecting environmental data representative of a construction site environment, and comprising at least climatic data ([0004] — “The CRL apparatus receives crane data from mechanical devices and the load moment indicator and determines various data analytics, such as… wind speed data, warning message data, error message data…”; [0023] — “Additionally, each of the various data analytics 160 may also include Global Positioning System (GPS) data such as date-stamped location.”); and logging of crane data and environmental data in a remote database ([0040] — “The methodology starts at block 300 with the CRL apparatus located on a crane and in communication with a cloud-based CRL server having access to a CRL database. … At block 308, the CRL apparatus receives LMI data, which the CRL apparatus sends to the CRL server with data analytics at block 310.”; Fig. 6 — The data sent in block #310 is crane data; recall that the environmental data is included in the crane data).
Wiethorn fails to teach a diagnostic method of an activity of a crane for a detection and a classification of a drop in activity period of said crane in a construction site among several activity periods (AP); logging by activity period of crane data and environmental data in a remote database; for each activity period, processing the work data to calculate a work time of the crane during the activity period, and comparison of said work time with at least one activity threshold to determine whether said activity period is a drop in activity period or not; for each drop in activity period, processing crane data and environmental data associated at least with said drop in activity period to identify at least one anomaly of the construction site or the crane, which anomaly being associated with said drop in activity period.
Danel discloses detection and a classification of a drop in activity period of a crane (Section 4.4 — “Finally, 31.02% of the time, the crane was ‘Stationary when empty’. This state was divided into two categories: more than 1 min (23.76%) and less than 1 min (7.26%). It is considered that below one minute of immobility, this time is linked to the hook/unhook phase and is not lost.”; the method discloses detecting a drop in activity (stationary when empty) period and classifying it into one of two categories) in a construction site (Abstract — “This article proposes a methodology to measure the productivity of a construction site through the analysis of tower crane data.”) among several activity periods (AP) (Section 4.4 — “Figure 9 represents the utilization of the tower crane day by day during the entire construction project”); for each activity period, processing work data to calculate a work time of the crane during the activity period (Section 4.4, Figure 10 — Work data is processed to calculate the total percentage of time worked in an activity period; Section 4.4 — “According to Figure 10, 25.89% of the time was used to move objects among the job site locations. Then, percentages were nearly the same when the crane was “Stationary when loaded” (21.48%) and “In motion when empty” (21.62%)… Finally, 31.02% of the time, the crane was “Stationary when empty”. This state was divided into two categories: more than 1 min (23.76%) and less than 1 min (7.26%). It is considered that below one minute of immobility, this time is linked to the hook/unhook phase and is not lost.”), and comparison of said work time with at least one activity threshold (Section 4.4 — “Finally, 31.02% of the time, the crane was “Stationary when empty”. This state was divided into two categories: more than 1 min (23.76%) and less than 1 min (7.26%).”) to determine whether said activity period is a drop in activity period or not (Section 4.4 — “This state was divided into two categories: more than 1 min (23.76%) and less than 1 min (7.26%). It is considered that below one minute of immobility, this time is linked to the hook/unhook phase and is not lost. In the literature, crane activity indicators exist. To compare our results with the previous work, our ‘Stationary when empty > 60 secs’ becomes ‘idling’…”; idling is a drop in activity period). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to include the steps disclosed by Danel in the method disclosed by Wiethorn in order to better understand how work is performed within a certain time interval by logging crane data by activity period and processing it as disclosed by Danel.
Together, the combination of Wiethorn and Danel still fails to teach for each drop in activity period, processing crane data and environmental data associated at least with said drop in activity period to identify at least one anomaly of the construction site or the crane, which anomaly being associated with said drop in activity period.
Jussel discloses using crane data for the detection of anomalies ([0033] — “The process data of the machine cycles and the machine reports are looked at both separately and in combination with one another for the preparation and are searched for patterns, anomalies and irregularities.”; the machine from which the process data originates is a crane, see [0026] — “FIG. 2 depicts a plan view of an exemplary machine in accordance with the present disclosure along with loading and unloading points of the machine…”). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to use the crane data and environmental data associated with a drop in activity period as disclosed by the combination of Wiethorn and Danel to identify an anomaly as disclosed by Jussel in order to improve crane safety by enabling the diagnostic method to detect potential failures (Jussel, [0009] — “For example, after a determination of a failure, an anomaly such as an operation of a component above permitted limit values that occurred long before the time of failure can thus also be considered as causal for the failure of the component.”).
Claim 17
The combination of Wiethorn, Danel, and Jussel fails to teach wherein the at least one anomaly comprises at least one internal anomaly of the crane reflecting a technical failure of the crane and identified from the crane data.
Jussel further discloses at least one anomaly that comprises at least one internal anomaly of a crane reflecting a technical failure of a crane (Jussel, [0026] — “FIG. 2 depicts a plan view of an exemplary machine in accordance with the present disclosure along with loading and unloading points of the machine…”; the exemplary machine is a crane; Jussel, [0032] — “Furthermore, reports of the machine independent of these process data are recorded that are transmitted to the same central location (database) and are optionally synchronized with the process data. These reports generated by the machine can, for example, be overload reports of a machine, a report on an empty tank, reports on problems with sensors, reports on defects in the system and/or status reports from assistance systems. This further information can be searched for sequential patterns or anomalies to permit additional conclusions.”) and identified from crane data (Jussel, [0032] — “Furthermore, reports of the machine independent of these process data are recorded that are transmitted to the same central location (database) and are optionally synchronized with the process data. These reports generated by the machine can, for example, be overload reports of a machine, a report on an empty tank, reports on problems with sensors, reports on defects in the system and/or status reports from assistance systems. This further information can be searched for sequential patterns or anomalies to permit additional conclusions.”; the reports would originate from the crane). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to identify at least one internal anomaly of the crane as further disclosed by Jussel in order to improve safety on a crane on which the method disclosed by Wiethorn, Danel, and Jussel is deployed by enabling detection of potential technical failures.
Claim 18
The combination of Wiethorn, Danel, and Jussel fails to teach wherein the at least one internal anomaly (Al) comprises at least one hardware, software or communication fault of one of the equipment called faulty equipment, identified from crane data from said faulty equipment.
Jussel further discloses at least one internal anomaly that comprises at least one hardware (Jussel, [0032] — “Furthermore, reports of the machine independent of these process data are recorded that are transmitted to the same central location (database) and are optionally synchronized with the process data. These reports generated by the machine can, for example, be overload reports of a machine, a report on an empty tank, reports on problems with sensors, reports on defects in the system and/or status reports from assistance systems.”; the reports disclose the existence of hardware faults), software or communication fault of one of the equipment called faulty equipment, identified from crane data from said faulty equipment (Jussel, [0032] — “Furthermore, reports of the machine independent of these process data are recorded that are transmitted to the same central location (database) and are optionally synchronized with the process data. These reports generated by the machine can, for example, be overload reports of a machine, a report on an empty tank, reports on problems with sensors, reports on defects in the system and/or status reports from assistance systems. This further information can be searched for sequential patterns or anomalies to permit additional conclusions.”; the information would originate from the crane and/or its faulty components). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to include a hardware fault as further disclosed by Jussel in the at least one internal anomaly identified by the method disclosed by Wiethorn, Danel, and Jussel in order to better understand how the anomaly corresponds to the technical failure.
Claim 19
The combination of Wiethorn, Danel, and Jussel discloses identifying anomalies from crane data (Jussel, [0033] — “The process data of the machine cycles and the machine reports are looked at both separately and in combination with one another for the preparation and are searched for patterns, anomalies and irregularities.”; the machine from which the process data originates is a crane, see Jussel, [0026] — “FIG. 2 depicts a plan view of an exemplary machine in accordance with the present disclosure along with loading and unloading points of the machine…”) but fails to teach wherein the at least one anomaly comprises at least one use anomaly reflecting non-compliant use of the crane.
Jussel further discloses identifying anomalies from data reflecting non-compliant use of a crane ([0032] — “These reports generated by the machine can, for example, be overload reports of a machine, a report on an empty tank, reports on problems with sensors, reports on defects in the system and/or status reports from assistance systems. This further information can be searched for sequential patterns or anomalies to permit additional conclusions.”; the machine is a crane; overloading a crane constitutes non-compliant use). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to identify an anomaly from the crane data as disclosed by Wiethorn, Danel, and Jussel that comprises at least one use anomaly reflecting a non-compliant use of the crane as disclosed by Jussel in order to improve crane safety by diagnosing, in the method disclosed by Wiethorn, Danel, and Jussel, potential overloading of the crane by an operator before a failure occurs.
Claim 24
The combination of Wiethorn, Danel, and Jussel discloses identifying anomalies from crane data (Jussel, [0032] — “Furthermore, reports of the machine independent of these process data are recorded that are transmitted to the same central location (database) and are optionally synchronized with the process data. These reports generated by the machine can, for example, be overload reports of a machine, a report on an empty tank, reports on problems with sensors, reports on defects in the system and/or status reports from assistance systems. This further information can be searched for sequential patterns or anomalies to permit additional conclusions.”), but fails to teach wherein the at least one anomaly comprises at least one organizational anomaly reflecting low profitability of the crane usage.
Wiethorn separately contemplates crane data in relation to profitability ([0037] — “Additionally, by way of example, the crane report reports modules 260 may generate crane usage reports that allow an owner to determine actual hours of use for financial evaluation of each crane. By way of further example, the crane report modules 260 may also provide detailed records about the service times and hours of each crane. Such records may be an asset for insurances purposes and stored at a main office of the owner.”; a financial evaluation is a determination whether a crane is profitable). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to perform a financial evaluation of the crane usage data as disclosed by Wiethorn and, if the financial evaluation shows low profitability, to identify from the crane usage data an anomaly as disclosed by the combination of Wiethorn, Danel, and Jussel (an anomaly in crane usage data constitutes an organizational anomaly) in order to better understand how inefficient crane usage results in lower profitability.
Claim 25
While rejected under 112(b) for being indefinite, for the sake of compact prosecution the examiner will assume the recited list to end with an “or” statement so that the claim may be analyzed bona fide under the prior art.
The combination of Wiethorn, Danel, and Jussel further discloses wherein the at least one organizational anomaly is identified from at least one of the following data among the crane data: data representative of a presence or activity of the crane operator in the crane (Wiethorn, [0037] — “By way of further example, the crane report modules 260 may also provide detailed records about the service times and hours of each crane.”; service times and hours disclose the presence of an operator in the crane), maneuver counting data, data representative of a stop controlled by an anti-collision system, cycle counting data load lifting, data representative of pause time between two maneuvers, data representative of types of maneuver, data representative of a crane type.
Claim 26
The combination of Wiethorn, Danel, and Jussel further discloses a remote analysis system (Wiethorn, [0030] — “In another embodiment, following the receipt of the data analytics, the CRL server 110 is caused via the processor 220 to evaluate the crane using the data analytics. The processor-executable instructions may cause the CRL server 110 to generate a report, such as the operator report 118 or the crane report 120.”, the CRL server is an analysis system; Wiethorn, [0034] — “Furthermore, in some embodiments, the CRL application 250 is provided as part of a server-based solution or a cloud-based solution. In some such embodiments, the application is provided via a thin client. That is, the application runs on a server while a user interacts with the application via a separate machine remote from the server.”, the CRL server is remote) in communication with or comprising the remote database (Wiethorn, [0040] — “The methodology starts at block 300 with the CRL apparatus located on a crane and in communication with a cloud-based CRL server having access to a CRL database.) and discloses the processing of work data to determine whether each activity period is a drop in activity period or not in claim 16 (Danel, Section 4.4, Figure 10 — Work data is processed to calculate the total percentage of time worked in an activity period; Danel, Section 4.4 — “This state was divided into two categories: more than 1 min (23.76%) and less than 1 min (7.26%). It is considered that below one minute of immobility, this time is linked to the hook/unhook phase and is not lost. In the literature, crane activity indicators exist. To compare our results with the previous work, our ‘Stationary when empty > 60 secs’ becomes ‘idling’…”; idling is a drop in activity period) and the processing of crane data and environmental data to associate with each drop in activity period the at least one corresponding anomaly in claim 16 (Jussel, [0033] — “The process data of the machine cycles and the machine reports are looked at both separately and in combination with one another for the preparation and are searched for patterns, anomalies and irregularities.”).
The combination of Wiethorn, Danel, and Jussel discloses a remote analysis system in communication with or comprising the remote database, but fails to disclose the processing of work data, crane data and environmental to determine whether each activity period is a drop in activity period or not and to associate with each drop in activity period the at least one corresponding anomaly and fails to disclose wherein the remote analysis system implements said processing.
Danel discloses the processing of work data to determine whether each activity period is a drop in activity period or not (Danel, Section 4.4, Figure 10 — Work data is processed to calculate the total percentage of time worked in an activity period; Danel, Section 4.4 — “This state was divided into two categories: more than 1 min (23.76%) and less than 1 min (7.26%). It is considered that below one minute of immobility, this time is linked to the hook/unhook phase and is not lost. In the literature, crane activity indicators exist. To compare our results with the previous work, our ‘Stationary when empty > 60 secs’ becomes ‘idling’…”; idling is a drop in activity period) and Jussel discloses the processing of crane data and environmental data to associate with each drop in activity period the at least one corresponding anomaly (Jussel, [0033] — “The process data of the machine cycles and the machine reports are looked at both separately and in combination with one another for the preparation and are searched for patterns, anomalies and irregularities.”). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to use crane data and environmental data disclosed by Jussel in combination with work data disclosed by Danel in determining whether each activity period is a drop in activity period or not and to use the work data disclosed by Danel in combination with the crane data and environmental data in associating with each drop in activity period the at least one corresponding anomaly, respectively, to better understand how environmental factors and crane conditions affect the activity of a crane and how the work performed and/or capable of being performed by the crane affects the type of anomaly that may be associated with a drop in activity period.
The combination of Wiethorn, Danel, and Jussel discloses a remote analysis a remote system in communication with or comprising the remote database and the processing of work data, crane data and environmental data to determine whether each activity period is a drop in activity period or not and to associate with each drop in activity period the at least one corresponding anomaly, but still fails to disclose wherein the remote analysis system performs said processing.
It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to implement a remote analysis system in communication with or comprising the remote database as disclosed by Wiethorn which implements the processing of work data, crane data and environmental data to determine whether each activity period is a drop in activity period or not and to associate with each drop in activity period the at least one corresponding anomaly as disclosed by Danel and Jussel in order to improve the processing time of the data in the diagnostic method by taking advantage of the server disclosed by Wiethorn, since servers have better processing capabilities.
Claim 27
The combination of Wiethorn, Danel, and Jussel fails to teach wherein the remote analysis system structures the crane data and the environmental data in a same predefined format.
Danel further discloses storing data in CSV (comma separated values) format (Section 3.2.2 — “Manual exports generate comma-separated values (CSV) files, in which each line is a data record. Every value is stored as plain text, whereas it exists, for example, “datetime” or “numeric” type bringing the true meaning of the stored value. A formatting step is then needed to translate text into values.”; the CSV structure is predefined). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to structure the crane data and the environmental data disclosed by the combination of Wiethorn, Danel, and Jussel as CSV files to take advantage of their simplicity and innate human-readability (plain-text data is human-readable).
Claim 28
The combination of Wiethorn, Danel, and Jussel further discloses displaying data (Wiethorn, [0025] — “The display 216, which is optional, provides an electronic device for the visual display of information.”), but fails to teach wherein the diagnostic method implements, subsequent to the processing of crane data and environmental data of each drop in activity period, a generation, or a display, or both, of an analysis report comprising, for the or each drop in activity period, information specific to the at least one identified anomaly.
Jussel discloses generating an analysis report ([0011] — “In accordance with a further development of the disclosure, the process data are combined with independent reports generated by the machine itself, with the independent reports generated by the machine optionally being transmitted to the database for this purpose.”). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to generate, and then display as disclosed by Wiethorn, an analysis report as disclosed by Jussel for each drop in activity period disclosed by the combination of Wiethorn, Danel, and Jussel in claim 16 comprising information specific to the at least one identified anomaly corresponding to the drop in activity period, also disclosed by the combination of Wiethorn, Danel, and Jussel in claim 16, in order to better organize the anomaly and drop in activity period data by consolidating relevant information into a single report and improving crane safety by displaying the analysis report to the crane operator to alert them of potential hazards.
Claims 20-22 are rejected under 35 USC 103 as being unpatentable over Wiethorn, Danel, and Jussel in view of Radlov et al. (Analysis of Accidents with Tower Cranes on Construction Sites and Recommendations for their Prevention, IOP Publishing, October 2020, https://doi.org/10.1088/1757-899X/951/1/012025)
Claim 20
The combination of Wiethorn, Danel, Jussel, and Radlov discloses identifying anomalies from sensor data selected from the crane data (Jussel, [0032] — “Furthermore, reports of the machine independent of these process data are recorded that are transmitted to the same central location (database) and are optionally synchronized with the process data. These reports generated by the machine can, for example, be overload reports of a machine, a report on an empty tank, reports on problems with sensors, reports on defects in the system and/or status reports from assistance systems. This further information can be searched for sequential patterns or anomalies to permit additional conclusions.”; the reports (crane data) disclosed by Jussel in the combination are generated from sensors, see Jussel, [0039] — “Sensors 24 may include, for example, sensors detecting process data reflecting the condition of machine 1 or the condition of components of machine 1.”) and coming from at least one sensor of the crane (Jussel, [0039] — “Sensors 24 may include, for example, sensors detecting process data reflecting the condition of machine 1 or the condition of components of machine 1.”), but fails to teach wherein the at least one use anomaly comprises at least one mounting anomaly reflecting a mounting, or an adjustment, or both, of equipment non-compliant or not suitable for the construction site.
According to the provided specification, a “mounting anomaly” constitutes an anomaly “…reflecting poor installation of the crane 2, and/or an adjustment of its structural, functional or ballast elements”, see Specification, page 15, lines 24-26.
Radlov further discloses accidents resulting from anomalies reflecting a mounting, or an adjustment, or both, of equipment non-compliant or not suitable for the construction site (Section 2 — “…accidents occurred during installation, dismantling or extension of the crane tower/boom - 29 accidents (34% of the total number). These are accidents that occur during lifting, turning or assembly/disassembly of large and heavy components of the tower crane structure. The technologies and procedures for assembly/disassembly and extension of the boom/tower of the tower crane in most cases require the implementation of a complex sequence of steps that are associated with the performance of work at height. These complex activities are usually associated with a long duration of operations and require a large number of staff, which creates additional preconditions for human error, leading to severe consequences”; the preconditions would constitute anomalies). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to identify an anomaly from sensor data selected from crane data coming from at least one sensor of the crane as disclosed by Wiethorn, Danel, Jussel, and Radlov, that comprises at least one use anomaly reflecting a mounting, or an adjustment, or both, of equipment non-compliant or not suitable for the construction site as disclosed by Radlov in order to improve crane safety by diagnosing, in the method disclosed by Wiethorn, Danel, Jussel, and Radlov, potential mounting and/or installation issues because they are the most common cause of major accidents (Radlov, Section 2, Figure 1 — Erection/Dismantling/Extending accidents (mounting accidents) are the most common cause of the majority of major accidents, at 34%).
Claim 21
The combination of Wiethorn, Danel, Jussel, and Radlov discloses identifying anomalies from work data (Jussel, [0032] — “These reports generated by the machine can, for example, be overload reports of a machine, a report on an empty tank, reports on problems with sensors, reports on defects in the system and/or status reports from assistance systems. This further information can be searched for sequential patterns or anomalies to permit additional conclusions.”; the machine is the crane), such as for example speed data of at least one structural element of the crane or overload data (Jussel, [0032] — “These reports generated by the machine can, for example, be overload reports of a machine, a report on an empty tank, reports on problems with sensors…”) but fails to teach wherein the at least one use anomaly comprises at least one control anomaly reflecting non-compliant control of the crane by a crane operator during maneuvers.
Radlov discloses accidents resulting from anomalies reflecting non-compliant control of the crane by a crane operator during maneuvers (Section 2 — “…accidents caused by improper use of the crane (mistake made by the operator and/or riggers) – 6 accidents (7% of the total). They are mainly related to: lifting stuck loads, overloading the crane, impact/interaction between two cranes on the same construction site, etc. Possible prerequisites that create conditions for the occurrence of such accidents are: insufficient qualification of the crane operator and/or the riggers, poor quality of the construction supervision on the site, etc.”; the prerequisites would constitute anomalies). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to identify an anomaly from the work data, as disclosed by the combination of Wiethorn, Danel, Jussel, and Radlov, that comprises at least one control anomaly reflecting non-compliant control of the crane by a crane operator during maneuvers as further disclosed by Radlov in order to improve crane safety by diagnosing non-compliant control of the crane to avoid potential accidents.
Claim 22
The combination of Wiethorn, Danel, and Jussel discloses identifying anomalies from crane data (Jussel, [0032] — “Furthermore, reports of the machine independent of these process data are recorded that are transmitted to the same central location (database) and are optionally synchronized with the process data. These reports generated by the machine can, for example, be overload reports of a machine, a report on an empty tank, reports on problems with sensors, reports on defects in the system and/or status reports from assistance systems. This further information can be searched for sequential patterns or anomalies to permit additional conclusions.”).
However, the combination of Wiethorn, Danel, and Jussel fails to teach wherein the at least one anomaly comprises at least one climatic anomaly reflecting an extreme and identified climatic condition from climatic data selected from environmental data.
Radlov discloses accidents resulting from anomalies reflecting extreme and identified climatic conditions (Section 2 — “…accidents occurred as a result of external natural influences - 15 accidents (18% of the total). Of these accidents, 2 were caused by earthquakes, and the remaining 13 were due to strong winds. Some of the accidents caused by strong winds are related to the omission to provide the free rotation of the crane boom during the wind load, as well as to the incorrect position of the boom (angle of inclination) in the tower cranes with luffing boom…”). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to identify an anomaly from environmental data (which includes the climatic data) as disclosed by the combination of Wiethorn, Danel, and Jussel that comprises at least one climatic anomaly reflecting an extreme and identified climatic condition as disclosed by Radlov in order to improve the safety of a crane on which the diagnostic method is implemented by identifying climatic anomalies for the operator that result in a significant portion of crane accidents (Radlov, Section 2 — “…accidents occurred as a result of external natural influences - 15 accidents (18% of the total)…”).
Claim 23 is rejected under 35 USC 103 as being unpatentable over Wiethorn, Danel, and Jussel in view of Shely et al. (US 20180346294 A1, hereinafter Shely).
Claim 23
The combination of Wiethorn, Danel, and Jussel discloses the climatic data comprising wind speed data (Wiethorn, [0004] — “The CRL apparatus receives crane data from mechanical devices and the load moment indicator and determines various data analytics, such as… wind speed data, warning message data, error message data…”), but fails to disclose wherein the climatic data comprises temperature data and hygrometric data.
Shely discloses assessing temperature data and hygrometric data for crane safety ([0109] — “Using virtual safety spheres around load 60 enables LHP module 50 and base stations 28 and/or 30 to assess the quality of air, temperature, humidity, etc. about load 60 in these spheres. In some embodiments, more spheres may be added and used by LHP module 50 to define different safety criteria about load 60.”; humidity data is hygrometric data; the virtual spheres are zones of load safety). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to include temperature data and hygrometric data as disclosed by Shely in the climatic data as disclosed by the combination of Wiethorn, Danel, and Jussel in order to better ensure crane and load safety by more-fully representing the conditions of the surrounding environment in the performance of the method.
Claim 29 is rejected under 35 USC 103 as being unpatentable over Wiethorn, Danel, and Jussel in view of Kimura (US 20220026888 A1).
Claim 29
The combination of Wiethorn, Danel, and Jussel fails to teach wherein, for each activity period, the activity threshold for said activity period corresponds to an average value of the work time of several activity periods before said activity period, or after said activity period, or both.
Kimura discloses an average value of the work time of activity periods before a particular activity period (Fig. 6, #S21 — This plot shows a probability distribution of past cycle times (work time of activity periods) along with a labeled, particular activity period; it is inherent that a probability distribution has an average value). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to use an average value in a probability distribution corresponding to the work times of past activity periods taught by Kimura as the activity threshold taught by the combination for the advantage of improving the generality of the method in classification of drop in activity periods by enabling the method to understand what constitutes normal activity versus a drop in activity on any crane on which the diagnostic method is deployed.
Claim 30 is rejected under 35 USC 103 as being unpatentable over Wiethorn, Danel, and Jussel in view of Oetken et al. (US 20200117201 A1, hereinafter Oetken).
Claim 30
The combination of Wiethorn, Danel, and Jussel fails to teach wherein the environmental data comprise, in addition to climatic data, topographical data representative of the surrounding topography.
Oetken discloses topographical data representative of a surround topography of a construction site ([0041] — “Control station 50 can be configured to link location data for work area 104 with electronic data indicative of the topography of construction site 70… Work area 104 within display screen 146 can include topographical features of construction site 70 to define a terrain map 154.”). It would have been obvious to a person having ordinary skill in the art, before the effective filing date of the claimed invention, to include topographical data representative of the surround topography as disclosed by Oetken in addition to climatic data in the environmental data disclosed by the combination of Wiethorn, Danel, and Jussel in order to better represent the surroundings of the construction site and potential hazards from uneven terrain.
Prior Art
The prior art made of record and not relied upon is considered pertinent to the applicant’s disclosure:
Oren et al. (US 20200386605 A1), Method for Tracking Lifting Events at a Construction Site
Claeys, Xavier (US 20190084809 A1), Dynamic Optimization of a Crane Load Curve
Claeys et al. (US 20180093868 A1), Anti-Sway Crane Control Method with a Third-Order Filter
Aoki, Toshihisa (US 20160225199 A1), Machine-Position-Information Management System, Crane, and Data Management Apparatus
Claeys, Xavier (DE 102015100669 A1), Anti-Pendulum Control Procedure with Adjustable Support for the Transport of an Anchored Load
Conclusion
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/RYAN JAMES STEAR/Examiner, Art Unit 2857
/ARLEEN M VAZQUEZ/Supervisory Patent Examiner, Art Unit 2857
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