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WO2025176271A1 - Procédé de détermination de conformité contractuelle d'un processus industriel et système associé - Google Patents

Procédé de détermination de conformité contractuelle d'un processus industriel et système associé

Info

Publication number
WO2025176271A1
WO2025176271A1 PCT/DK2025/050027 DK2025050027W WO2025176271A1 WO 2025176271 A1 WO2025176271 A1 WO 2025176271A1 DK 2025050027 W DK2025050027 W DK 2025050027W WO 2025176271 A1 WO2025176271 A1 WO 2025176271A1
Authority
WO
WIPO (PCT)
Prior art keywords
data
processing apparatus
data processing
contractual
image data
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
PCT/DK2025/050027
Other languages
English (en)
Inventor
Kasper Koops Kratmann
Per Mathias KAASTRUP-OLSEN
Hans LAUERBERG
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Claviate Aps
Original Assignee
Claviate Aps
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Claviate Aps filed Critical Claviate Aps
Publication of WO2025176271A1 publication Critical patent/WO2025176271A1/fr
Priority to DKPA202530633A priority Critical patent/DK202530633A1/en
Pending legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G—PHYSICS
    • G06—COMPUTING OR CALCULATING; COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V20/00—Scenes; Scene-specific elements
    • G06V20/10—Terrestrial scenes

Definitions

  • the present invention relates to a method of determining contractual compliance of an industrial process comprising acts of colleting sensor data representing event conditions at/or related to the industrial process, inputting the collected data to a data processing apparatus, logging at least a timestamp and a position of the collected data, matching and comparing contractual requirements of the industrial process to at least one event for determining contractual compliance.
  • the events are logged with a time stamp synchronized to an external clock operating a globally unique time system.
  • the present invention also relates to a system configured to perform the method.
  • the present invention further comprises a computer program configured to execute the method and a computer-readable medium configured to store the computer program.
  • the construction or installation process is governed by a contract between the parties, which specifies terms and conditions for payments, project milestones, quality of work, breach of contract, deadline for completion of work, and other information.
  • the construction process normally consists of a plurality of various subtasks that must be completed before the construction is completed.
  • the contractor and sub-contractors must submit a payment claim and supporting documentation for the completed work in accordance with the contract.
  • the client assesses the completed work to verify the payment claim. Any discrepancies between the claimed work and the assessed work are settled in accordance with the terms laid out in the contract. Therefore, there is a desire to monitor the progress of the construction or installation, as well as the completion of subtasks and other key events. For insurance reasons, it may be desired to monitor certain areas or the entire construction site.
  • cameras to capture images of the monitored areas and link boxes, or data loggers, to gather operating data from the construction machinery. Workers may also use logbooks to manually log timestamps, notes, and other information related to the construction progress.
  • objects of interest may be tracked automatically by processing the captured image data using object detection algorithms or machine learning algorithms implemented in a remote server or local data processing unit.
  • object detection algorithms or machine learning algorithms implemented in a remote server or local data processing unit.
  • Such algorithms can be trained and evaluated via various available programming platforms provided by software providers using either open-source datasets or custom datasets.
  • WO 2021/110226 Al discloses a method and system for monitoring an industrial site, comprising a plurality of cameras connected to a data processing apparatus.
  • the raw image data is processed in data processing apparatus by an object detection algorithm, where the detected object is anonymised in the image data and the altered image data is stored in a database for later inspection.
  • This solution focuses on anonymising image data so it may be stored for later analysis.
  • WO 2018/191555 Al discloses a method of recognising repeating actions of an overall assembly line process using deep learning, wherein a neutral network in communication with a long-short term memory are trained to detect actions and compare it to a benchmark process. Abnormalities in the detected actions is determined by the neural network based on the benchmark process, and video snippets of these abnormalities may be stored for later analysis.
  • This solution is designed specifically for monitoring assembly lines for automotive parts or computer parts and uses only two-dimensional data in the data processing.
  • US 11175650 B2 discloses another system for monitoring an assembly line process using sensors arranged at working stations and workers interacting with the working stations.
  • the neural network and long-short term memory are trained to detect objects and actions from the sensors stream using deep learning, which relate to assembly steps of an overall assembly process.
  • the workers or robots may interact with the system at the working stations, e.g., via user terminals.
  • the neural network is configured to generate a set of performance data, which can be compared with a set of reference data. During optimization, operators may access portions of the set of data for optimising the assembly process This solution is designed specifically for real-time monitoring of the assembly of components.
  • US 11321944 B2 discloses a system for monitoring repeating actions in an overall process, where a neural network and long-short term memory are trained to detect actions in video data.
  • the neural network is trained to detect the start, the end, and other details of each action based on the image frames, and to generate statistical data based on the details of the actions. This solution is designed specifically for monitoring assembly lines in a factory.
  • One object of the present invention is to solve the problems of the above-mentioned prior art.
  • Another object of the present invention is to provide a method and system that allows for managing events of an industrial process at an industrial site, including dynamic sites.
  • One object of the present invention is achieved by a method of determining contractual compliance of an industrial process comprising acts of:
  • the at least one event is determined based on at least the sensor data stored in the data processing apparatus and logged with the timestamp and position of the data.
  • one object of the present invention is achieved by a method of managing an industrial site, comprising the steps of:
  • the term “industrial process” is defined as an overall process being performed at the industrial site, wherein the industrial process is composed of a plurality of interrelated operations (or actions) which may be performed in parallel or in a sequential order. Further, a plurality of process segments also referred to as operational states (or tasks) is performed during each operation. Hence the process and the process segments have a duration in time.
  • An event is defined by specific time and may be defined by a combination of conditions or features in the data or a relation between data at the specific time.
  • the timestamp must have an absolute reference to an external clock running a globally unique time system such as coordinated universal time (UTC), international atomic time (TAI), GPS time or similar. This guarantees consistency, accuracy, and resistance to timing discrepancies caused by drift, system latency, or local clock variations.
  • UTC coordinated universal time
  • TAI international atomic time
  • the term “industrial site” should in this case be understood as a site for the production, assembly, installation or handling of units or large structures, or components thereof.
  • the present system and method are particularly suited for, but not limited to, use in the energy sector, such as wind energy, the shipping (freight transport) industry, or the construction industry.
  • the present system and method are also suited for use in factories comprising one or more production lines.
  • the position has an absolute relation to a globally unique geospatial positioning reference system.
  • the method allows for using a local position coordinate system arranged relative to a global position reference system.
  • the position may have a unique and well-defined relation to a globally unique geospatial positioning reference system ensuring absolute and unambiguous location data. This may be achieved by integrating satellite-based navigation system such as GPS or GLONASS, or geodetic reference frames such as WGS84 or ITRF, and additional augmentation sources such as an IMU (inertial measurement unit). By leveraging these positioning references, the system can ensure high accuracy, consistency, and resistance to signal drift or loss, thereby providing a precise and persistent positioning framework.
  • satellite-based navigation system such as GPS or GLONASS, or geodetic reference frames such as WGS84 or ITRF
  • additional augmentation sources such as an IMU (inertial measurement unit).
  • An absolute and unambiguous position ensured by relating to a globally unique geospatial positioning reference system, can also enable relating specific operations, process segments or events to unique object IDs, such as serial numbers. This may be important to document that e.g. a specific construction was completed or serviced. Unambiguous positional data may also be an important data parameter to document the construction and service history of a given object such as a wind turbine both on shore and offshore, combined with e.g. historical meteorological data.
  • the present method may use a set of cameras to monitor the entire industrial site, or sub-areas of particular interest.
  • the placement of the cameras is adapted to the dynamic or static mapping of the site and can easily be changed in accordance with changes to the site mapping. This allows a user of the present system to visually monitor the industrial site, or sub-areas thereof, during the entire industrial process.
  • the captured image data e.g., videos or still pictures, are inputted to a data processing apparatus for data storage and data analysis and evaluation.
  • the image data may be stored in a shared database, or in a dedicated database. This allows the user to access and evaluate image data of the industrial site during the verification process.
  • the mapping of the industrial site preferably has an absolute reference to a globally unique global positioning reference system.
  • a timestamp is used to determine at least one process segment, such as event of the industrial process, in the image data.
  • the image data inputted from each camera may be synchronized with a reference signal, such as a timestamp signal.
  • the timestamp signal may be an internal clock of the data processing apparatus.
  • the timestamp signal may also be a timestamp signal embedded in the image data from one of the cameras or a timestamp signal embedded in position data transmitted from a positioning system.
  • the timestamp signal may be a timestamp signal selected by the user.
  • the timestamp signal may be globally recognised time standard.
  • the reference signal may be specified in the contract established between the parties of the industrial process. This allows for the various data to be synchronized to a reference signal agreed to by the contracting parties.
  • the synchronization may be performed during installation or operation of the present system.
  • the synchronization may also be performed during data processing in the computer unit.
  • the method further comprises the step of determining a position such as a geographical position of at least one object at the industrial site, and optionally tracking said at least one object throughout the industrial site.
  • the position of one or more objects within the industrial site may be determined manually by the user. Further, the user may also manually track the motion of these objects throughout the industrial site. This may be achieved by visually analysing the image data to detect and track objects of interest.
  • the data processing apparatus may instead automatically determine the position of one or more objects within the industrial site.
  • the data processing apparatus may further track the motion of these objects throughout the industrial site.
  • a coordinate system of the industrial site may be stored in the data processing apparatus for determining the (global or local) position of objects within the coordinate system.
  • the position of an object may be determined based on the image data using a localization algorithm implemented in the computer unit. For example, the geographical position of one or more cameras in combination with computer vision-based triangulation may be used to determine the geographical positions of the objects.
  • the computer unit may then use a tracking algorithm to predict and track the positions of the objects within the image data.
  • An example of a geo-localization algorithm is disclosed in the article “Object Tracking and Geo-Localization from Street Images” by Wilson, Daniel et al.
  • a positioning system may communicate with the data processing apparatus for determining the position of one or more objects.
  • the positioning system may transmit position data directly to the data processing apparatus.
  • the position data may be transmitted to a local receiving unit on the object, and then transmitted further from the object to the data processing apparatus. This allows objects to be tracked even if no or limited image data is available.
  • a local positioning unit on the object may transmit a beacon signal to multiple nodes, and then determine its position based on the signal strength or delay of the signals received from the nodes.
  • multiple local positioning units may be arranged relative to the industrial site and the individual objects may act as nodes for reflecting the beacon signals.
  • the position of the objects may be determined using triangulation or multi-lateration and angular measurement.
  • the position data may then be transmitted from the local positioning unit to the data processing apparatus. This allows objects to be tracked even if no or limited reception of global positioning signals is available.
  • the method further comprises the steps of:
  • other data or ‘additional data’ may be understood as sensor data and/or data received from a third party.
  • Additional data may be collected and inputted to the data processing apparatus for data storage and data analysis and evaluation. These additional data may be representative of conditions at or related to the industrial site and may be collected from local sources, external sources, or a combination thereof.
  • the raw inputted data may be stored in the database together with the image data, or in a dedicated database. This allows the user to access different types of data collected from multiple sources, which allows for a more reliable and easier verification of the contractual requirements.
  • the additional data may for example be descriptive of failures, defects, or the like not visible to the cameras or detectable by the sensors or measuring units.
  • the additional data may also be results of trials or tests performed by workers before or during the operation.
  • the inputted data i.e. the other data and the image data
  • the image data and the other data may be synchronized based on a reference signal, such as the above timestamp signal.
  • Other reference signals may also be used for synchronising the inputted data.
  • the structured dataset may be stored in the database together with the image data and raw inputted data, or in a dedicated database. This allows for an easier review of the various types of inputted data for a particular event.
  • the internal clock of the data processing apparatus or the timestamp signal of one of the inputted data signals may be used to verify or correlate the timestamp signal of another inputted data signal.
  • the reference (timestamp) signal may also be added to one or more of the inputted data signals. This allows for the correction of incorrect or missing timestamps in the inputted data.
  • the method further comprises the step of
  • the method further comprises the step of
  • the administrator, or a data analyst, of the present system may manually analyse the structured dataset to determine one or more events, such as events of the industrial process.
  • the administrator may add one or more timestamps and optional comments to mark each event in the image data and/or in the inputted other data.
  • the timestamps and comments may be stored in the database(s) together with the image data and the inputted other data, or in a dedicated database.
  • Events may be determined based on the combination of two or more types of data. This allows for a more accurate detection of events and reduces uncertainties about when events to take and the duration thereof. This in turn allows for more effective verification process.
  • the method further comprises the steps of:
  • the method further comprises the steps of:
  • the present system may also automatically analyse the image data and/or the inputted other data in the computer unit using computer-based algorithms, custom logics, or a combination thereof to determine the events. Alternatively, only a selected subset of the inputted data may be analysed.
  • Computer vision algorithms, feature extraction algorithms or a combination thereof may be implemented in the computer unit and used to analyse the inputted data.
  • the computer vision algorithms may be configured to determine a number of operational states based on the captured image data.
  • the feature extraction algorithms may be configured to determine a number of unique features representative of said operational states based on the inputted other data. This allows the computer unit to automatically detect the operational states of an operation of the industrial process.
  • the computer vision algorithms may comprise an image classification algorithm, which may determine at least one state of process based on the content of the image frames in the image data as a whole.
  • the computer vision algorithms may comprise an optical flow algorithm, which may quantify the motion between two consecutive image frames in the image data.
  • the computer vision algorithms may comprise an action classification algorithm, which may determine at least one type of operational state based on the performed action in the stream of image frames in the image data.
  • the computer vision algorithms may comprise a temporal action localization algorithm, which may determine at least one start, end, and type of operational state based on the stream of image frames in the image data.
  • the computer unit may identify and determine the operational states using feature-based event detection.
  • the computer vision algorithms may also comprise an object tracking algorithm, which may track the motion of one or more objects between consecutive image frames in the image data.
  • a one-stage or multi-stage object detection algorithm, or a semantic segmentation model may further be implemented in the computer unit.
  • the computer unit may use boundary boxes or segmentation masks (regions of interest) to localise and track objects of interest within the image frames in the image data.
  • the computer vision algorithms may also comprise an action detection algorithm, which may determine at least one type of operational state based on the performed object actions in the image frames in the image data.
  • the action detection algorithm may compute or combine special, temporal, and semantic features from the image data. This allows the operational states to be identified and determined in accordance with one or more object classes and action classes stored in the computer unit. This also allows objects as well as various actions to be identified and recognised within the image frames in the image data.
  • the outputs of these computer-based algorithms may then be evaluated in the computer unit using classification algorithms, custom logics, or a combination thereof to determine one or more events.
  • the events may be operations of the industrial process or predetermined events, wherein the parameters thereof may be set up by the user or administrator of the present system.
  • a scaling or weight value may be applied to the outputs of these algorithms, thus making the outputs more suited for clustering and/or filtering during the evaluation.
  • One or more timestamps may be added to the structured dataset to mark each event. This allows the computer unit to automatically detect events based on the image data and/or the inputted additional data.
  • the classification parameters for the events may be set up by the user or administrator of the present system.
  • a scaling or weight value may be applied to the outputs of these algorithms, thus making the outputs more suited for clustering and/or filtering during the evaluation.
  • This allows the computer unit to automatically detect events based on the inputted data.
  • the manually or automatically added timestamps may also be used to identify the image segment of a particular event in the stored image data. Alternatively, a copy of the image segment may be stored together with the structured dataset.
  • the verification of the at least one contractual requirement or at least one claim statement is performed manually based on the at least one events, wherein an output of the verification process is generated based on at least the individual contractual requirements or claim statements.
  • the administrator or data analyst may use the timestamps and optional comments of the detected events to determine any deviations from the contractual requirements or to confirm that the contractual requirements have been met. If deviations are determined, then the administrator or data analyst may review the structured dataset to determine an initial root of the deviation. The administrator or data analyst may finally generate an output of the verification process, i.e. a verification output, based on at least the individual contractual requirements.
  • This verification output may indicate the results of the verification process and optional links to the image data and/or other data in which the deviations are found, as mentioned later. This allows for a more effective verification process as it can be based on a more accurate account of the events. Thereby also reducing any disputes or discussions regarding the fulfilment of a contractual requirement. Conventionally methods are mainly based on interviews, logbooks and other information provided by a single party.
  • the administrator, or the data analyst, of the present system may manually verify one or more claim statements from a user based on the detected events stored in the data processing apparatus.
  • the administrator or data analyst may use the structured dataset and the timestamps and optional comments of the detected events to verify the individual claim statements.
  • the verification output may then be updated, or a new verification output may be generated, based these claim statements.
  • the method further comprises an act of inputting at least one contractual requirement into the data processing apparatus, and wherein said act of comparing the event conditions with the contractual requirement for determining contractual compliance is performed automatically by the computer unit.
  • the act of comparing the event conditions with the contractual requirement for determining contractual compliance includes an act of generating an electronic output, such as a report or a graphic user interface
  • the method further comprises the step of inputting the at least one contractual requirement into the data processing apparatus, wherein said verification of the at least one contractual requirement is performed automatically by the computer unit, which optionally generates an output of the verification process based on at least the individual contractual requirements.
  • the present system may also automatically verify the contractual requirements in the computer unit using computer algorithms, custom logics, or a combination thereof.
  • the contractual requirements may be inputted into the data processing apparatus and stored in the database, or in a dedicated database.
  • the contractual requirements may be inputted as quantifiable measures so that the computer unit is able to determine if the measures have been met. This allows for an automatic verification of the contractual requirements compared to conventional methods.
  • the computer unit may simply compare the timestamps and/or number of detected events with the individual contractual requirements to determine any deviations.
  • the computer unit may also compare one or more of the various signals in the structured dataset with the individual contractual requirements to determine any deviations.
  • a verification signal and an optional dedicated output may be generated by the computer unit for each contractual requirement. This allows for a fast and accurate verification which reduces the amount of manual labour compared to conventional methods.
  • the computer may simply generate a verification output indicating that all contractual requirements are met. If one or more deviations are determined, then the computer unit may generate a dedicated output for each deviation of a contractual requirement, as mentioned later.
  • the other and/or sensor data comprises radio communications between at least two radio communications devices and/or audio signals picked up by at least one microphone which are transmitted to the data processing apparatus, wherein unique voice commands and/or unique audio signals are extracted from said radio communications or audio signals.
  • the operational states of an operation may also be determined based on the radio communications between two or more radio communications devices and/or audio signals pick up at the industrial site.
  • the raw radio communications may be picked up by a radio scanner unit or dedicated radio unit and transmitted to the data processing apparatus and stored in the database for data analysis.
  • One or more microphones may pick up audio signals from the industrial site, wherein the audio signals may include voice communications between workers, various machine sounds, audio alarms, announcements over speakers, weather related sounds, and the like.
  • the raw audio signals may be stored in the database for data analysis.
  • the administrator or data analysis may replay the radio communications or audio signals, alone or in combination with other data, when manually determining the events. This also allows users to review the radio communications or audio signals when settling a contractual requirement or claim statement.
  • One or more audio feature extraction algorithms implemented in the computer unit may detect unique audio signals in the radio communications and/or audio signals.
  • the unique audio signals may be warnings, alarms, machine, or tool related sounds and/or environmental sounds. Noise reduction, filtering, and spectral analysis of the audio signals may be used to extract the unique audio signals.
  • Classifications for unique audio signals or parameters thereof may be set up by the user or administrator of the present system and stored in the computer unit.
  • the audio feature extraction algorithms may be trained to detect unique audio signals such as warning alarms, start or stop of engines or winches, operation of tools, or other characteristic operational sounds. This allows the computer unit to automatically detect unique audio signals associated with or affecting the performance of operations.
  • a transcription (speech-to-text) algorithm may be implemented in the computer unit, wherein the transcription algorithm may perform an automatic transcription of the radio communications.
  • the transcription may then be stored in the database for later analysis. This allows users to review the verbal communication between workers when settling a contractual requirement or claim statement.
  • the operational states may also be determined based on telemetry data from one or more telemetry devices.
  • the telemetry data may be transmitted to the data processing apparatus and stored in the database for data analysis.
  • the telemetry data may be representative of the operating conditions or performance of machines or tools, health conditions of workers, environmental conditions, or the like.
  • the telemetry data may also comprise accelerations from accelerometers, movements from gyroscopes, or compass headings from magnetometers.
  • the position data may form part of the telemetry data.
  • the telemetry data may be standard telemetry data.
  • the administrator or data analysis may analyse the telemetry data, alone or in combination with other data, when manually determining the events.
  • standard telemetry data should be understood as telemetry data that is presented in accordance with an open or globally recognised standard, such as ISO 15143-3. This allows for easy access to third-party data provided by multiple OEMs.
  • One or more feature extraction algorithms implemented in the computer unit may extract unique operational states associated with an operation from the telemetry data.
  • the operational states may be representative of conditions relating to an operation of the industrial process.
  • Reference parameters or thresholds may be set up by the user or administrator of the present system and stored in the computer unit.
  • the selected telemetry signal may be compared to the reference parameters or thresholds in the computer unit, which may be used to detect certain signal characteristics or determine if the telemetry signal is within safe operating conditions.
  • the reference parameters may also be used to detect if machines or tools are turned on, or if certain actions of the machines or tool have commenced. Users of the present system may thus confirm the operating conditions of machines, vehicles, or tools, e.g., in combination with the image data, when settling a contractual requirement or claim statement.
  • the other data and/or sensor data comprises meteorological data from a meteorological unit or system, which is transmitted to the data processing apparatus.
  • the meteorological data from one or more meteorological units or systems may be transmitted to the data processing apparatus and stored in the database.
  • the meteorological data is representative of the environmental conditions relating to the industrial site.
  • the meteorological data may comprise wind speed, temperature, lightning, humidity, precipitation, visibility, cloud cover, air pressure, wave height, wavelength, wave dwell, wave direction, or other relevant weather, wind data, or wave data.
  • the administrator or data analysis may review these environmental conditions, alone or in combination with other data, when manually determining the events.
  • the meteorological data may be actual historical weather data or weather forecasts hereof, as planning decisions often are made based on the forecast.
  • Actual historical weather data can be used to determine e.g., abort scenarios where actual weather conditions exceeded safe working conditions despite the weather forecast predicting safe weather conditions.
  • One or more feature extraction algorithms implemented in the computer unit may extract one or more unique environmental features from the meteorological data.
  • Reference parameters or thresholds may be set up by the user or administrator of the present system and stored in the computer unit.
  • the selected meteorological signal may be compared to the reference parameters or thresholds in the computer unit, which may determine if the meteorological signals is within safe operating conditions.
  • the image data or other data may be combined with the meteorological data to confirm that the actual environmental conditions were within safe working conditions during the events.
  • a training dataset may be used to train the algorithms implemented in the computer unit using machine learning to automatically detect and identify various events.
  • the training dataset may be historic data from a previous industrial site or previous data from the industrial site.
  • the training dataset may comprise the events, the image data, the inputted data, or any combination thereof.
  • the administrator may evaluate the output of the computer unit after each training run and correct any errors and/or missed objects or events in the output. Once the evaluation is completed, a subsequent training run may be performed. The training section may be repeated until an acceptable level of performance is achieved.
  • the method further comprises the steps of:
  • the at least one claim statement is verified based on at least the image data or structured dataset stored in the data processing apparatus, preferably said verification of the at least one claim statement is performed manually or automatically by the computer unit.
  • One or more claim statements may further be inputted into the data processing apparatus by the user or the administrator.
  • the claim statement may relate to a particular contractual requirement or relate to an event or incident not related to any contractual requirements. This allows additional issues or issues not mentioned in the contractual requirements to be added by the user or administrator.
  • Claim statements may be added to existing verification outputs set upon request from one of the users or the administrator.
  • the user or administrator may select the inputted data to be analysed for verification of this claim statement, when manually verifying the claim statement.
  • the computer unit may optionally determine additional events associated with this claim statement, if needed.
  • the computer unit may compare the claim statement to one or more signals of the structured dataset, e.g., the image data, the telemetry data, or meteorological data. This allows claim statements to verified manually or automatically based on the events or structured dataset.
  • a new verification output may be generated manually or by the computer unit based on the claim statement. This allows the user or administrator to include any issues not related to any contractual requirements.
  • said output of the verification process is presented as an electronic output, such as a report or a graphic user interface.
  • the verification output may be accessed via a dedicated website or dashboard module stored in the data processing apparatus, e.g., the computer unit.
  • the verification output may also be presented as a readable report, which can be downloaded or mailed to the user. This allows the users to access and interact with the data processing apparatus via dedicated interfaces.
  • the layout and format structure may be set up by the user or administrator of the present system and stored in the computer unit.
  • the verification output may be determined based on the contractual requirements listed in the contract.
  • the verification output may comprise a dedicated output for each deviation, contractual requirement or claim statement.
  • the verification output may include a link to the image data and/or the other data in which the deviation was found.
  • the verification output may comprise information of industrial site, type of deviation, signals of the inputted data related to the deviation, parties involved, verification signal, signature and/or other relevant information. This allows the results of the verification process to be presented in an adaptable format.
  • the administrator or user may manually enter data into the verification output during the verification process. Alternatively, or additionally, data may be automatically downloaded into the verification output by the computer unit.
  • the computer unit may generate a verification signal, e.g., a standardised verification signal, indicative of whether the respective contractual requirement has been verified, pending, or not verified.
  • the verification signals may be combined with the structured dataset and linked to each contractual requirement or claim statement.
  • the computer unit may further generate a claim statement indicating the type of deviation.
  • the computer unit may comprise a set of standardised claim statements, e.g., symbols or text messages, stored in the database.
  • a standardised claim statement may be selected and linked to a contractual requirement in the structured data set by the computer unit. This allows users to easily recognize and monitor the status of the verification process.
  • the data processing apparatus comprises a client user profile, at least one contractor user profile and optionally at least one supplier user profile, wherein the client, contractor or supplier accesses and interacts with the data processing unit via their respective user profile.
  • a plurality of user profiles each defining the respective user rights may be stored in the computer unit.
  • a dedicated client user profile may define the access and user rights for a client.
  • one or more dedicated contractor user profiles may define the access and user rights for one or more contractors or sub-contractors.
  • one or more dedicated supplier user profiles may define the access and user rights for one or more suppliers.
  • one or more dedicated third-party user profiles may define the access and user rights for one or more third-parties, such as insurance companies, service providers or so on. This allows the respective users of the present system to gain access to the verification output and optionally interact with the data processing apparatus.
  • An administrator or data analyst of the present system may use a dedicated administrator user profile to access the data processing apparatus and change or update the configuration of the computer program.
  • Said update may include retraining the computer unit using an updated training dataset.
  • the user may input comments and/or change the verification status of one or more of the contractual requirements.
  • the user may add comments to a particular contractual requirement and/or upload further information relating to the events of the contractual requirement.
  • the user may request that further signals of the inputted data and/or additional signals are added to the structured dataset.
  • the client, the contractor, the supplier and/or the third-party may add an electronic signature to the structured dataset when a contractual requirement or claim statement has been settled. This allows the users to view which contractual requirements and claim statements are settled and which that are still pending.
  • the computer unit may automatically update the structured dataset so that the users may view the current status of the verification process at all times.
  • One object of the present invention is achieved by a system for determining contractual compliance of an industrial process.
  • the system comprising:
  • a data processing apparatus comprising a computer unit, wherein the sensor(s) is connected to the data processing apparatus via a communications link for inputting the sensor data to the data processing apparatus, and
  • a database configured to store at least the sensor data
  • the database is connected to the data processing apparatus and wherein the data processing apparatus is adapted to execute the steps of any one of the methods described herein.
  • the system comprises at least one camera configured to capture image data of at least a part of the industrial site, the image data comprising a plurality of image frames, wherein the cameras are connected to the data processing apparatus via a communications link for inputting the image data to the data processing apparatus and wherein the database is configured to store at least the image data.
  • one object of the present invention is achieved by a system, comprising the steps of:
  • At least one camera configured to capture image data of at least a part of the industrial site using, the image data comprising a plurality of image frames
  • a data processing apparatus comprising a computer unit, wherein the cameras are connected to the data processing apparatus via a communications link for inputting the image data to the data processing apparatus,
  • a database configured to store at least the image data, wherein the database is connected to the computer unit,
  • This provides an improved system for verifying the contractual requirements of the industrial process performed at the industrial site.
  • the present system allows the contractual requirements indicated in the contract to be verified manually or automatically by the computer unit.
  • Conventional methods of verifying the contractual requirements are associated with some uncertainty as only a limited amount of data may be available. Further, the verification process is often performed manually and is time consuming as it is often difficult to synchronize the available data.
  • the configuration of the present system is versatile and can be adapted to different applications and to changes in the dynamic or fixed mapping at the site.
  • Conventional monitoring systems for high-volume, production sites cannot be used for industrial, low-volume production sites without changes to the setup and to the algorithms in the computer unit. Further, conventional monitoring systems are limited to evaluate the performance at workstations along a production or assembly line, not to verify if the requirements indicated in the contract have been met or not. Further, conventional systems often provide limited possibilities for suppliers and/or sub -contractors to gain access to the verification results or the data used to verify the claim statements or contractual requirements.
  • the cameras are arranged relative to the industrial site to capture image data of the industrial site, or sub-areas thereof, wherein the resolution and frame rate is selected based on the application and type of industrial site.
  • Each camera is connected to the data processing apparatus via a first communications link, e.g., an encrypted communications link.
  • the data processing apparatus comprises a computer unit and at least a database in communication with computer unit, wherein a computer program is implemented on the computer unit and configured to execute the method step described above.
  • the data processing apparatus is configured to communicate with a positioning system via a communications link, wherein the positioning system is configured to input position data to the data processing apparatus.
  • the data processing apparatus may be configured to determine the position of one or more objects within a coordinate system defining the industrial site.
  • the data processing apparatus may further be configured to track the motion of these objects throughout the industrial site using the position data and/or the image data.
  • the data processing apparatus may communicate with a server of a third-party provider, or an integrated positioning system of the present system.
  • the positioning system may be a Global Navigation Satellite System (such as GPS or GLONASS), a Local Positioning System (such as a radio, BLE, WIFI, UWB, or LIFI- based positioning system) or an Indoor Positioning System (such as HPPS).
  • GPS Global Navigation Satellite System
  • LEO Local Positioning System
  • HPPS Indoor Positioning System
  • a plurality of cameras may be positioned relative to the industrial site and angled so that they cover the monitored area from different angles.
  • the inputted image data may be combined in the computer unit to generate a multi-dimensional mapping of the monitored area, e.g., a 2D or 3D map. This allows for a better tracking of the objects as the installation often requires the objects to be moved in multiple directions within the coordinate system before being mounted or assembled to another object or structure.
  • system further comprises:
  • radio communications devices configured to communicate with each other via a radio communications link, the radio communication between the radio communications devices being transmitted to the data processing apparatus, and/or
  • At least one microphone connected to the data processing apparatus, wherein the at least one microphone is configured to pick up audio signals from at least one position at the industrial site, and/or
  • telemetry devices located within the industrial site and/or at least one meteorological unit or system, wherein the telemetry devices and/or the meteorological unit or system are configured to communicate with the data processing apparatus via one or more communications links.
  • the data processing apparatus may be configured to further receive other data from other sources via another communications link, wherein the other data may be representative of conditions at or related to the industrial site.
  • the data processing apparatus may comprise a radio scanner unit configured to scan the radio frequencies used by a plurality of radio communications devices to conduct radio communications between workers.
  • the radio scanner unit may be configured to tune to a particular radio channel used and pick up the raw radio communication between the radio communications devices.
  • a dedicated radio unit may be set up to access the radio channel used, the radio communication between the radio communications devices may then be stored in the database of the data processing apparatus for data analysis.
  • An encryption key may be entered into or stored in the radio scanner unit to access the radio frequencies if encrypted radio channels are used.
  • the radio communications may be conducted via encrypted communications links to prevent unauthorized access to the radio communications.
  • An encrypted communications link may be established between the individual radio communications devices and/or between the radio communications devices and the data processing apparatus.
  • one or more microphones may pick up audio signals from one or more positions at the industrial site, wherein the audio signals may include voice communications between workers, various machine sounds, audio alarms, announcements over speakers, weather sounds, and the like.
  • the audio signals picked up by the microphones may be transmitted to and stored in the database of the data processing apparatus for data analysis.
  • An encrypted communications link may be established between the microphones and the data processing apparatus to prevent unauthorized access to the audio signals.
  • Speed recognition algorithms may be implemented in the computer unit to extract unique voice commands from the radio communications and/or the audio signals, as mentioned earlier.
  • audio feature extraction algorithms may be implemented in the computer unit to extract unique audio signals associated with the performance of an operation and/or other characteristic audio signals that indirectly or directly affect the performance of an operation.
  • classes comprising machine operating sounds may be used for determining machine operating conditions.
  • classes comprising weather related sounds may be used for determining environmental operating conditions.
  • the data processing apparatus may be configured to communicate with a plurality of telemetry devices located within the industrial site for receiving telemetry data.
  • the telemetry data may be provided from a third- party provider.
  • Feature extraction algorithms may be implemented in the computer unit may be used to extract operational states from the telemetry data, such as crane based operational states.
  • the data processing apparatus may establish a wired or wireless communications link with the telemetry devices or a server of the third-party provider. These operational states may also be used to determine one or more operations of the industrial process.
  • the data processing apparatus comprises:
  • dashboard module configured to provide users access to at least the verification output via dedicated user profiles, and/or
  • an API module configured to interact with a server of a third-party service provider for inputting third-party data to the data processing apparatus.
  • the dashboard module is configured to provide users access to at least a generated output from the act of comparing the event conditions with the contractual requirement for determining contractual compliance via dedicated user profiles.
  • a dashboard module may be implemented in the computer unit so that users can access the verification output and optionally the structured dataset via dedicated user profiles.
  • the users may also interact with the data processing apparatus via the dashboard module to download a report of the results of the verification process.
  • the users may also enter comments to the deviations, add claim statements, and/or add further inputted signals to a particular deviation or claim statement via the dashboard module.
  • an API module may be implemented in the computer unit so that third-party service providers may access the data processing apparatus and input third-party data for data analysis.
  • the third-party data may be position data, telemetry data, meteorological data, and/or radio communications.
  • Users may also upload additional data to the data processing apparatus via the API module.
  • This additional data may be analysed manually or automatically by the computer unit to determine events of the industrial process. Alternatively, this additional data may be used to verify a claim statement or contractual requirement manually or automatically.
  • the industrial site is:
  • the present system and method are suited for managing dynamic sites where repetitive events are performed, but the location for these events may change during the overall industrial process.
  • the mapping of such sites may change dynamically due to the large structures, or components thereof, having a size and weight unsuited for high-volume mass production.
  • the dynamic site may be a construction site or an installation site for a large structure (e.g., a wind turbine, a building, or another large structure) where objects are temporary stored between usage or installed directly upon arrival, and where the mapping of the site changes during the construction process.
  • a large structure e.g., a wind turbine, a building, or another large structure
  • the dynamic site may also be a site (such as a temporary site) where various tasks or operations are performed at dedicated areas under controlled environments, and objects are moved between said areas during the industrial process.
  • a site such as a temporary site
  • various tasks or operations are performed at dedicated areas under controlled environments, and objects are moved between said areas during the industrial process.
  • the dynamic site may be a base port for the handling and loading of offsite components before installation.
  • the base port may comprise local assembly and/or production facilities so that the offshore components can be pre-assembled and/or produced onsite at the base port.
  • the dynamic site may also be an installation or shipping vessel where objects must be loaded and stored in predetermined pattern for optimal usage of the available storage space, and where the objects must be installed or unloaded in a particular order.
  • the dynamic site may also be a shipping terminal (such as airports, seaports, or standalone inland terminals), where objects must be loaded or unloaded and optionally stored in predetermined pattern, and where the movement of objects must be coordinated with the loading/unloading process to reduce idle time.
  • the present system and method are also suited for managing factories where a number of repetitive events are performed along each production line during the overall industrial process.
  • the mapping of such sites is fixed and the units, or components thereof, have a size and weight suited for high-volume, mass production.
  • One object of the present invention is achieved by a computer program, comprising instructions which, when loaded and run on the system described above, causes the data processing apparatus to execute the method steps described earlier.
  • the present method is implemented into the data processing apparatus, wherein the computer unit is configured to execute the steps of the present method.
  • This allows the use and training of artificial intelligence, such as neutral networks (e.g., FNN, CNN, RNN, attention networks, DNN, or SNN) using machine learning to automatically determine the events of the industrial process.
  • neutral networks e.g., FNN, CNN, RNN, attention networks, DNN, or SNN
  • One object of the present invention is achieved by a computer-readable medium, having stored thereon the computer program described above.
  • the present computer program is implemented on the computer-readable medium of a remote server (or server network) or local computer unit, thus allowing the data processing and storage to be adapted to desired site configuration and application.
  • a hybrid version of the data processing apparatus may be used where parts of the computer program may be implemented in the remote server and parts of the computer program may be implemented on the local computer unit.
  • the data analysis, the data storage, the data evaluation, the data verification, and the data access and interaction may be implemented on and executed by one or more remote servers or server networks.
  • the present data processing apparatus to be configured as a local-based data service, a remote- or cloud-based data service, or a hybrid data service thereof.
  • the computer-readable medium may be a non-volatile memory or non-volatile storage.
  • One object of the present invention may be achieved by use of the method according to any one of the embodiments disclosed herein to track component installation, maintenance activities, or operational status in the construction and/or service of offshore and/or onshore wind turbines and/or solar farms.
  • One object of the present invention may be achieved by use of the method according to any one of the embodiments disclosed herein to track the construction of large-scale highway bridges and/or tunnels, including but not limited to tunnels excavated through mountainous terrain or immersed tunnels constructed across ocean floors.
  • Fig. 1 shows a block diagram of a first embodiment of the method according to the present invention
  • Fig. 2 shows a first embodiment of the present system according to the present invention
  • Fig. 3 shows a second embodiment of the present system
  • Fig. 4 shows a third embodiment of the present system
  • Fig. 5 shows a fourth embodiment of the present system
  • Fig. 6 shows an example of synchronizing the image data and the other data
  • Fig. 7 shows an example of the structured data set stored in the database
  • Fig. 8 shows an exemplary application of the present system for an offshore site
  • Fig. 9 shows an exemplary application of the present system for an onshore site
  • Fig. 10 shows an exemplary manual configuration of the present system
  • Fig. 11 shows an exemplary semi-automated configuration of the present system
  • Fig. 12 shows an exemplary automated configuration of the present system
  • Fig. 13 shows another example of synchronizing the image data and the other data.
  • Fig. 1 shows a block diagram of a first embodiment of the method according to the present invention.
  • the method is adapted to manage an industrial site where the mapping of the industrial site may change during the industrial process.
  • the frame resolution, shutter speed and other settings of the cameras are optionally adapted to the industrial process performed at the industrial site.
  • the image data is inputted to a data processing apparatus via a communications link, e.g., an encrypted communications link, wherein the image data is processed and analysed 2 as mentioned later.
  • other types of data 3 are further inputted to the data processing apparatus together with the image data 1.
  • the other data 3 and the image data 1 are then processed and analysed 2 in the computer unit of the data processing apparatus.
  • the other data 3 are representative of conditions at or related to the industrial site, and some of the other data 3 may be provided by third-party providers.
  • the other data 3 includes, but is not limited to, location data 3a, telemetry data 3b, acceleration and gyroscopic data 3c, meteorological data 3d, radio communications 3e and logged data 3f. More or fewer types of other data may be inputted to the data processing apparatus depending on the application of the present system.
  • the location data 3a is inputted via a positioning system, such as a global or local positioning system, in communication with the data processing apparatus.
  • the location data 3a is indicative of the locations of one or more objects within the industrial site.
  • the telemetry data 3b and/or the acceleration and gyroscopic data 3c may be inputted directly to the data processing apparatus from sensors or other devices arranged on objects located within the industrial site.
  • the telemetry data 3b and/or the acceleration and gyroscopic data 3c may also be inputted from a third-party provider, which manages the operation of one or more objects, such as cranes, vessels, machines, or the like, within the industrial site.
  • the location data 3a, the telemetry data 3b and/or the acceleration and gyroscopic data 3c may be supplied by the same third-party provider.
  • the meteorological data 3d is inputted via a local meteorological unit or a third-party provider to the data processing apparatus.
  • the meteorological data 3d is representative of the environmental conditions relating to the industrial site.
  • the meteorological data 3d includes, but is not limited to, historical weather data and/or weather forecasts.
  • the contractual requirements 6 defined in a contract between the parties are inputted to the data processing apparatus during the initial setup of the present system.
  • one or more claim statements 7 are further inputted to the data processing apparatus by one or more of said parties.
  • the contractual requirements 6 and the claim statements 7 are then stored in the data for later verification of said contractual requirements 6 and claim statements 7.
  • the detected events 5 are subsequently evaluated by the computer unit to identify any deviations 9 from the contractual requirements 6 or claim statements 7.
  • the administrator of the present system may initially select the inputted data 1, 3 to be used during this verification process based on the contractual requirements 6 and claim statements 7.
  • a verification output is generated by the computer unit at the end of the verification process, indicative of the results.
  • the events 5 as well as the verification output, including the deviations 9, are stored in a database 10.
  • the verification output 9 together with the events 5 may be presented to the user as a report I la or in a dedicated graphic user interface 11b.
  • the user or administrator of the present system is further able to input data from third-party providers via a dedicated API interface 11c.
  • Fig. 2 shows a first embodiment of the system according to the present invention.
  • the data processing apparatus is configured as a hybrid data service, where parts 12’ of the data processing (ref. data analysis and evaluation and verification) are performed locally while other parts 12’ of the data processing are performed remotely.
  • the image data 1 and other data 3 are captured or measured locally 13 using cameras, sensors, or other data recording devices 14a, 14b.
  • the image data 1 and other data 3 are inputted to a local data processing unit where the inputted data 1, 3 are analysed and evaluated 12’ by a local computer unit in the local data processing unit.
  • the inputted data 1, 3 and the events 5 are stored in the local database or in a remote database.
  • the events 5 detected by the local computer unit is transmitted to a remote data processing unit, wherein the events 5 are evaluated remotely 15 for determining any deviations 9 between the events 5 and the contractual requirements 6 or claim statements 7.
  • This remote data processing unit may further receive data 14c inputted from a third- party provider or by one party. This data 14c is then synchronised with the structured dataset for the events 5 by the remote computer unit to determine if the contractual requirements 6 or claim statements 7 are met or not.
  • the verification output from the local computer unit together with the data 14c and the events 5 are then stored in a remote database 10.
  • Users are then able to access the remote data processing apparatus by a dedicated API interface 11c using their respective user profiles.
  • the user can then view or download the events 5 and the verification output by transmitting data requests 16 to the remote data processing apparatus.
  • the user may request corrections or changes to the verification output via the API interface 11c.
  • Fig. 3 shows a second embodiment of the present system.
  • the data processing apparatus is configured as a remote data service, where the data processing 12 is performed remotely.
  • the image data 1 and other data 3 are captured or measured locally 13’ using cameras, sensors, or other data recording devices 14a, 14b.
  • the image data 1 and other data 3 are transmitted to the remote data processing unit, wherein the received data together with the data 14c inputted from third-party providers are analysed and evaluated remotely 15” to determine the events 5.
  • the remote computer unit evaluates the events 5 based on the contractual requirements 6 and claim statements 7 to determine any deviations 9.
  • the remote computer unit generates the verification output.
  • the events 5 and verification output, including deviations 9, are then stored in the remote database 10.
  • Fig. 4 shows a third embodiment of the present system.
  • the data processing apparatus is configured as an alternative remote data service, where the data storage 10 is performed in a remote database 10’ separate from the data processing 12.
  • the computer unit in the remote data processing unit analyses and evaluates the inputted data 1, 3 and determines the events 5.
  • the remote computer unit then verifies the contractual requirements 6 or claim statements 7 based on the events 5 and generates the verification output.
  • the events 5 and the verification output, including the deviations 9, are then transmitted to the remote database 10’ for data storage.
  • the remote database 10’ is in communication with the remote data processing apparatus for accessing the stored data.
  • Fig. 5 shows a fourth embodiment of the present system.
  • the data processing apparatus is configured as a local data service, where the data processing 12 is performed locally.
  • the image data 1 and other data 3 are captured or measured locally 13” using cameras, sensors, or other data recording devices 14a, 14b.
  • the image data 1 and other data 3 are inputted to the local data processing unit, wherein the inputted data together with the data 14c inputted from third-party providers are analysed and evaluated locally 13” to determine the events 5.
  • the events 5 and structured dataset associated with each event 5 are then stored in a local database 10”.
  • the local computer unit verifies the contractual requirements 6 or claim statements 7 based on the events 5 and generates the verification output.
  • the verification output is further stored in the local database 10”.
  • Figs. 6 and 13 show two examples of synchronizing the image data 1 and the other data 3 to form a structured dataset 17.
  • the image data 1 and the other data 3 are synchronised using a timestamp signal 18.
  • the data associated with each event 5 in the structured dataset 17 are synchronised using this timestamp signal 18.
  • the structured dataset 17 along with the events 5 determined by the computer unit are then stored in the database for later verification of the contractual requirements 6 or claim statements 7.
  • Fig. 7 shows an example of the verification output 19 generated by the computer unit.
  • the verification output 19 is presented as a matrix where the relevant inputted data 1, 3 for each event 5 are listed together with the number of deviations 9 determined by the computer unit.
  • the matrix may be changed or altered upon request from the users, wherein the administrator of the present system may control the configuration of the matrix.
  • the matrix comprises information regarding the industrial site and the type of deviation 9 and inputted data 1, 3 related to each deviation 9.
  • the parties can access the data processing unit and manually enter or upload additional data related to the deviation 9 via the API interface 11c. Once the deviation 9 has been settled, the responsible party may then add an electronic signature in the matrix to indicate that this deviation 9 has been settled.
  • Fig. 8 shows an exemplary application of the present system for an offshore site.
  • the industrial site is an offshore site, such as an installation vessel 20 for erection of a wind turbine 21.
  • the installation vessel 20 comprises a crane unit for lifting the various wind turbine components into position relative to each other.
  • Cameras 22 are positioned at predetermined locations on the offshore site, wherein the cameras 22 are used to monitor areas of interest. Other sensors (not shown) are further arranged at the offshore site for inputting other data 3 to the data processing apparatus 23.
  • the operation of at least the crane unit can be monitored using the cameras 22 and the sensors (not shown), wherein image data and measured data of the crane operations are transmitted to the data processing apparatus 23 for data analysis and evaluation, thereby allowing at least events involving the use of the crane unit to be determined by the computer unit in the data processing apparatus 23.
  • the computer unit in the data processing apparatus 23 then verifies the contractual requirements 6 or claim statements 7 based on these events. Subsequently, a verification output 19 is generated by the computer unit indicative whether any deviations 9 were identified or not.
  • Fig. 9 shows an exemplary application of the present system for an onshore site.
  • the industrial site is an onshore site, such as an erection site of a wind turbine 21.
  • the installation involves the use of a crane unit 24 for lifting the various wind turbine components into positions relative to each other.
  • Cameras 22 are positioned at predetermined locations at onshore site, wherein the cameras 22 are used to monitor areas of interest. Other sensors (not shown) are further arranged at the onshore site for inputting other data 3 to the data processing apparatus 23.
  • the operation of at least the crane unit 24 can be monitored using the cameras 22 and the sensors (not shown), wherein image data and measured data of the crane operations are transmitted to the data processing apparatus 23 for data analysis and evaluation.
  • image data and measured data of the crane operations are transmitted to the data processing apparatus 23 for data analysis and evaluation.
  • the computer unit in the data processing apparatus 23 then verifies the contractual requirements 6 or claim statements 7 based on these events. Subsequently, a verification output 19 is generated by the computer unit indicative whether any deviations 9 were identified or not.
  • Fig. 10 shows an exemplary manual configuration of the present system.
  • a first step 25 of the present method at least image data 1 is captured by cameras 22 and inputted to the data processing apparatus 23.
  • other types of data 3 are measured or registered by sensors, measuring units, or the like, where this other data 3 is further inputted to the data processing apparatus 23.
  • the image data 1 and optional other data 3 are transmitted to a database for data storage.
  • the image data 1 and optional other data 3 may be synchronised by a time signal 18, e.g., automatically by a local computer unit.
  • a data analyst accesses the stored data in the database and performs a manual evaluation of the inputted data 1, 3 to determine the events 5.
  • the events 5 and timestamps 18a thereof may be manually added to the image data or entered into the database for storage together with the image data 1 and optional other data 3.
  • the data analyst or a party of the contract manually compares the events 5 to a copy of the contractual requirements 6 and optional claim statements 7 to determine any deviations 9.
  • the data analyst or party manually generates a verification output, e.g., in the form of a report, indicative of whether the contractual requirements 6 and optional claim statements 7 are met or not.
  • the parties are then able to settle any deviations 9 and finally sign off on the verification output.
  • Fig. 11 shows an exemplary semi-automated configuration of the present system.
  • a first step 25 of the present method at least image data 1 is captured by cameras 22 and inputted to the data processing apparatus 23.
  • other types of data 3 are measured or registered by sensors, measuring units or the like, where this other data 3 are further inputted to the data processing apparatus 23.
  • the image data 1 and optional other data 3 are transmitted to a database for data storage.
  • the image data 1 and optional other data 3 are automatically analysed and evaluated by the computer unit in the data processing apparatus 23.
  • the computer unit automatically generates the events 5 and timestamps 18a thereof, which are then stored in the database.
  • a data analyst or party of the contract accesses the stored data in the database and performs a manual comparison of the events 5 to a copy of the contractual requirements 6 and optional claim statements 7 to determine any deviations 9.
  • the data analyst or party manually generates a verification output, e.g., in the form of a report, indicative of whether the contractual requirements 6 and optional claim statements 7 are met or not.
  • Fig. 12 shows an exemplary automated configuration of the present system.
  • a first step 25 of the present method at least image data 1 is captured by cameras 22 and inputted to the data processing apparatus 23.
  • other types of data 3 are measured or registered by sensors, measuring units or the like, where this other data 3 are further inputted to the data processing apparatus 23.
  • the image data 1 and optional other data 3 are transmitted to a database for data storage.
  • the image data 1 and optional other data 3 are automatically analysed and evaluated by the computer unit in the data processing apparatus 23.
  • the computer unit automatically generates the events 5 and timestamps 18a thereof, which are then stored in the database.
  • a third step 31 of the present method the parties are then able to access the data processing apparatus to review the verification output 19 and settle any deviations 9. Once all deviations 9 are settled, then the parties can finally sign off on the verification output 19.

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Abstract

La présente invention concerne un procédé de détermination de la conformité contractuelle d'un processus industriel comprenant les étapes consistant à colleter des données de capteur représentant des conditions d'événement au niveau du processus industriel ou associées à ce dernier, à entrer les données collectées dans un appareil de traitement de données, à enregistrer au moins une estampille temporelle et une position des données collectées, ainsi qu'à mettre en correspondance et à comparer des exigences contractuelles du processus industriel à au moins un événement pour déterminer une conformité contractuelle. Les événements sont enregistrés avec une estampille temporelle synchronisée sur une horloge externe fonctionnant avec un système temporel mondialement unique.
PCT/DK2025/050027 2024-02-21 2025-02-21 Procédé de détermination de conformité contractuelle d'un processus industriel et système associé Pending WO2025176271A1 (fr)

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PCT/DK2024/050031 WO2025176268A1 (fr) 2024-02-21 2024-02-21 Procédé de gestion d'un site industriel et système associé

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