Method and apparatus for a construction site

Abstract

A method for processing construction site data includes receiving data identifying spatial units and the state of progress in first and second time domains 100, 102. Progress information for the spatial units is determined from this data and is classified into predefined state categories, where each category is assigned with a distinctive graphical symbol 104. A visualisation of the progress information for the spaces based on the classification and symbols is generated 106 and displayed on a graphical user interface 108. The invention also envisages the method being carried out using at least one processor and at least one memory including computer program code. The progress of activities may be determined based on image or sensor data from the construction site, possibly captured via a camera (10, figure 3), or via input in user terminals. Scheduling information relating to activities may be obtained from a memory to determine progress information.

Description

This disclosure relates to methods and apparatuses for a construction site. A construction site, for example a building site can have various subprojects, or tasks, to be completed. Various resources are used for performing the tasks at the same or different times and locations at the site. The resources can comprise, for example individuals or teams such as specialist electricians, plumbers, carpenters, bricklayers, decorators, mechanics, ground workers, and so on specialised skill organisation(s) and their equipment, materials and so on needed to perform various specific tasks on the construction site in accordance with overall construction plan. A construction project can comprise a large number of operators which are dependent on the progress and resources of each other to be able timely and efficiently to perform the tasks of the construction project in accordance with the planned construction schedule. On the other hand, the tasks can be performed and resources used reasonably autonomously. Unexpected events may occur preventing or at least delaying performance of at least some of the tasks. E.g., one delayed or non-performed task in one location can affect a number of other locations and tasks, and therefore seriously affect the progress of the construction project, unless the situation is addressed, e.g., through rescheduling some of the activities. Managing a construction site can be a challenging task. In accordance with an aspect there is provided a method for processing construction site related data, comprising: receiving data comprising information identifying spatial units at a construction site and indicative state of progress of activities in a first time domain in the identified spatial units, determining progress information for the identified spatial units based on the received data and information indicative of state of progress of activities in the identified spatial units in a second time domain, classifying the determined progress information for the identified spatial units into predefined state categories, wherein each state category is assigned with a distinctive graphical symbol, generating a visualisation of the progress information for the identified spatial units based on the classification and the distinctive graphical symbols, and displaying the distinctive graphical symbols on a graphical user interface. In accordance with a more specific aspect the method may comprise determining state of progress of at least one activity as a ratio to completion of the activity. The first time domain and the second time domain may comprise distinct first and second time periods. The first time period can be later than the second time period. Determining the progress information may comprise comparing progress in the first time period and the second time period. Determining of progress information for the identified spatial units may further comprise obtaining from at least one memory scheduling information relating to activities in the identified spatial units. Data may be received from at least one data collecting device located at the construction site. Determining the state of progress of the activities may be based on image data and / or sensor data received from the construction site. Image data may be captured by at least one camera apparatus at the construction site. Data indicative of progress of activities may comprise information of at least one of tasks, components of tasks, groups of tasks and / or groups of components of tasks. Classifying into predefined categories may comprise determining at least one of: the pace of production in a spatial unit has increased; the pace of production in a spatial unit has remained the same; activity in a spatial unit has started but the space has not progressed; the pace of production in a spatial unit has decreased; activities in a spatial unit have been completed; selected activities in a spatial unit have been completed; and / or activities in a spatial unit have not progressed for a specific period of time. Any of the states can be identified both for overall activities and for a selected set of activities, and any of the predefined categories can apply either to all activities in a spatial unit or selected activities in a spatial unit. The method may further comprise applying a margin threshold to avoid false classifications due to inaccuracies in input data. In accordance with another aspect there is provided an apparatus comprising at least one processor, and at least one memory including computer program code, wherein the at least one memory and the computer program code are configured, with the at least one processor, to: receive data comprising information identifying spatial units at a construction site and indicative state of progress of activities in a first time domain in the identified spatial units, determine progress information for the identified spatial units based on the received data and information indicative of state of progress of activities in the identified spatial units in a second time domain, classify the determined progress information for the identified spatial units into predefined state categories, wherein each state category is assigned with a distinctive graphical symbol, generate instructions for visualisation of the progress information for the identified spatial units based on the classification and the distinctive graphical symbols, and cause display of the distinctive graphical symbols on a graphical user interface. An apparatus may be provided that is configured to determine state of progress of at least one activity as a ratio to completion of the activity. The first time domain and the second time domain comprise distinct first and second time periods, the first time period being later than the second time period. The apparatus may be configured to determine the progress information based on comparison of progress in the first time period and progress in the second time period. The apparatus may be configured to obtain from the at least one memory scheduling information relating to activities in the identified spatial units and determine progress information for the identified spatial units based on the obtained scheduling information. The apparatus may be configured to receive data from at least one data collecting device located at the construction site and determine progress information for the identified spatial units based on the data from the data collecting device. The apparatus may be configured to determine the state of progress of the activities based on image data received from the construction site. The image data may be captured by at least one camera apparatus located at the construction site. The apparatus may be configured to determine the state of progress of the activities based on sensor data received from the construction site. Data indicative of progress of activities may comprise information of at least one of tasks, components of tasks, groups of tasks and / or groups of components of tasks. The apparatus may be configured to classify the progress into one of the predefined state categories based on determination of at least one of: the pace of production in a spatial unit has increased; the pace of production in a spatial unit has remained the same; activity in a spatial unit has started but the space has not progressed; the pace of production in a spatial unit has decreased; activities in a spatial unit have been completed; selected activities in a spatial unit have been completed; or activities in a spatial unit have not progressed for a specific period of time. Any of the predefined categories can apply either to all activities in a spatial unit or selected activities in a spatial unit. The apparatus may be configured to apply a margin threshold to avoid false classifications due to inaccuracies in input data. The apparatus may be configured to send data for presentation of the display of the distinctive graphical symbols on a graphical user interface of a mobile device. Computer software products may also be provided for implementing the herein described tasks. Certain more detailed aspects are evident from the detailed description. Various exemplifying embodiments of the invention are illustrated by the attached drawings. Steps and elements may be reordered, omitted, and combined to form new embodiments, and any step indicated as performed may be caused to be performed by another device or module. In the Figures: Fig. 1 illustrates an example of a project environment and certain elements of an architecture where the invention can be embodied; Fig 2. shows an example of a data processing apparatus; Fig.3 shows an example of data gathering apparatus; Fig. 4 shows a flowchart in accordance with an example; Fig. 5 shows examples of graphical symbols; and Figs. 6 and 7 show examples of graphical user interfaces. The following description gives an exemplifying description of some possibilities to practise the herein disclosed invention. Although the specification may refer to “an”, “one”, or “some” examples or embodiment(s) in several locations of the text, this does not necessarily mean that each reference is made to the same example of embodiment(s), or that a particular feature only applies to a single example or embodiment. Single features of different examples and embodiments may also be combined to provide other embodiments. Fig. 1 illustrates in form of a highly schematic plan view a construction site 1. Various activities are performed by various resources in the construction site. A plurality of per se autonomous operators 3 can simultaneously and independently perform the various activities. The construction site 1 can comprise a plurality of localised work areas denoted by rectangles 2 and referred to hereinafter interchangeably as spatial units or spaces. Terms spatial unit and space are used herein to mean a defined individual area of the construction site, for example a room, an apartment, a section, a floor, a common area, a riser, a staircase, a corridor, and so on. Activities on the site referred hereinafter as tasks are performed in the spaces in accordance with an overall construction plan. A task may also comprise a suboperation which can be understood as a unit of work by appropriate resources. Resources active in spaces 2 are denoted by dots 3 in Fig. 1. The resources can include workforce, equipment and materials needed for the performance of the task from start to finish in accordance with the planned construction schedule. Performance of the tasks requires resources such as, for example skilled individuals or construction teams (“trades”) with specialised skills capable of performing the specific tasks. For example, a construction site can involve a large number of different tasks which consume variable amounts of resources, time and effort to complete. Non-limiting examples of tasks on a building site include tiling, flat ductwork installation, internal walls drylining, decorating, underfloor heating installation, electrical wiring, fire alarm cabling, and so on. A component of a task refers to a granular and visually identifiable unit of work done as part of a task. Spotlight is an issue related to the execution of a component identified by a progress management system. A space can comprise one or more smaller spaces. For example, a floor or another larger section of a construction site can comprise all rooms and other areas of that floor or section. Spaces may also partially overlap. For example, an open plan kitchen area and a living room area can partially overlap. Space blocks 4 and 6 in Fig. 1 illustrate such partial overlap. Fig. 1 also illustrates how resource 5 is performing a task in space 4 such that it may interfere with the resource 7 performing its assigned task at overlapping space 6. Although the spaces may be clearly physically separated, e.g., by walls, ceilings and floors, the spaces may nevertheless have at least a logical relation in the sense that a task in a space may prevent anything else done in another space. For example, work on a corridor or staircase may prevent performance of tasks in rooms accessed through the corridor or staircase. Work on a floor may prevent work on a space below and / or above, for example for safety reasons. Other areas may also be involved in a construction site which are not necessarily the subject of any actual construction work but the optimal use of which is nevertheless desired. For example, hoist areas are spatial units inside the building used as a storage for material and so on and crane-to-building connections during the construction project. A non-finished task can prevent another task to be started in the same or related space. The prevention may be a total block or at least hinder the other task to such extent that it is not feasible to perform the other task as planned. Any delay in completing one task may mean that one or more other tasks are also delayed. The impact of the one non-completed task may quickly start affecting many other tasks and spaces. Therefore, a system enabling quick response to any issues arising while also indicating areas of smooth progress would assist the task of managing a construction site. The following describes a system for generating easy and quick to understand visual displays of progress in a construction site. A central data processing apparatus 20 provides a platform for the system. The data processing apparatus can comprise, for example, a server. The required data processing may also be provided virtually in cloud environment. The data processing apparatus 20 can be configured to store in a memory thereof a workflow or scheduling model configured for the construction site in accordance with a construction plan. The model can be configured to describe the various tasks, relationships between the tasks, the spaces 2 in the construction site and use of resources 3 in the spaces to perform the tasks in accordance with the construction plan. The model can be updated as the work progresses. The platform can be provided in the form of a web application configured to allow user interaction. The platform generates graphical user interfaces that allow users to view data on a quick to comprehend visual overview of spaces in a construction site. The users will be able to see, for example, a weekly change in pace of production and stalling tasks per space. Changes in the progress are calculated by means of an algorithm configured to calculate changes in the pace of production. Any stalling tasks for spaces and neutral states can also be identified. The pace of production is understood as the rate at which activities on the site are progressing. Stalling tasks or spaces refers to tasks or spaces in which no progress has been identified over a period of time but where the work had previously started. The stalling progress can be determined for various specific activities. A filtering of trades, tasks, or components may be provided. Stalling of progress can be determined for the overall aggregate of all activities, a set of activities, or a single activity. Fig. 2 shows a schematic example of the internal components of the data processing apparatus 20 that are adapted for providing the necessary data storage and data processing to implement the herein described functions. The data processing components 90 can comprise at least one memory 91 for software code for the algorithm and records 95 needed for the calculations, at least one data processor unit 92, 93 and at least one input / output interface 94. Via the interface the apparatus can be coupled to the other devices of the system. The interface may also be provided with or connected to a reader of a physical data carrier. The processor unit(s) can be configured to execute an appropriate software code to provide the necessary functions. Data can be collected from the construction site in different ways and from different sources. Various sensors and other data collection devices 11 may be provided in the construction site for collecting data indicative of progress and any possible issues preventing planned progress in the spaces. Data is communicated from the data gathering devices to the data processing apparatus 20 via data connections 22. The data processing apparatus 20 is configured to receive and process data input regarding the spaces, tasks and resources in the construction site to provide information of the progress at the construction site and overall scheduling control. More detailed examples of possibilities for data collection at the construction site will be given later. Data input may also be received from user terminals 8,9 via data connections 23. The user terminals can comprise mobile devices carried by the workforce on the site. For example, smart mobile phones and / or laptop or tablet computers can be used for this purpose. The devices 8, 9 can run an appropriate software code and / or application to provide the necessary user interfaces and functionalities for the data input by the user and communication with the central data processing apparatus 20. Data connections 22 and 23 between the data processing apparatus 20 and devices 8, 9 and 11 can be fixed line connections or at least in part wireless connections. The connections may be via a data network connection, for example via an Internet Protocol (IP) based data network, local area network (LAN) connections (e.g., Wireless LAN) or direct connections. Data may be transferred from the data collecting and / or input devices to the data processing apparatus also by a physical data carrier, e.g., by means of a memory card, USB stick, connecting the user terminal devices 8, 9 via a cable to the data processing apparatus 20 and so forth. The data input identifies a specific at least one space in the construction site and comprises information indicative of the status of the identified at least one space. The input can also include other information, for example about readiness of dependent resources like drawings, materials, heavy machinery and other equipment and workforce. For the identification purposes each space is assigned with a unique identifier. The data processing apparatus can analyse the data input. The analysis can take into account information from the memory / database, for example data obtained from a scheduling model configured to describe the tasks, timelines thereof, relationships between the different tasks and spaces and use of resources in accordance with the construction plan. The data processing apparatus 20 can be configured to adapt the model based on any determined changes and / or alternative use(s) of the resource(s) or any other changes that affect use of resources at the construction site. The adaptation of the model can be done in substantially real time, on request, or periodically. The model can be created based on plans and prior knowledge and experiences. The model can be adapted based on inputs for various scheduling, rescheduling and reporting operations. The model can be configured to relate the various spaces, tasks, components, resources and timelines. Dependencies can be inferred from the model for the tasks that need to be carried out so that the construction project is completed on time, budget and specification. Each task can be mapped to a specific spatial unit in which the task has to be carried out. Each task can be assigned to a timeline in which it shall be carried out in the relevant spatial unit. The timeline for a task can include start time (e.g., date and / or hour), duration and end time. A task’s connections to other relevant tasks in the sequence of tasks in the spatial unit can be defined by a type of dependency. Tasks in one spatial unit can also be defined as related to or dependent on a task in a different spatial unit. Types of dependencies can be defined, for example, based on start and completion of the task: Finish to Start, Finish to Finish, Start to Finish, and Start to Start. The data processing apparatus can generate notifications. The notifications can be displayed on the graphical user interface 21 of the data processing apparatus 20 and / or communicated to the terminal devices 8, 9 provided with mobile communication capabilities at the site for display via the data connections 23. Examples of the notifications and accordingly displayed user interfaces will be explained later. Fig. 3 is a schematic view of an example of a data collection system that can be used for gathering data indicative of the state of a spatial unit at the site. The system comprises an imaging apparatus configured to capture images of a spatial unit. More particularly, Fig. 3 shows camera apparatus 10 rotatably mounted on a ground-plane 12. It shall be appreciated the camera apparatus can also be mobile. The rotation of the camera apparatus on a plane is denoted by arrow 18. The camera apparatus can be configured to capture panoramic or spherical 360 degree images of the space comprising objects 15, 16 and store and / or send the captured digital image data for use by the data processing apparatus. The image data can be transferred immediately or periodically to the data processing apparatus 20. A more detailed explanation of such a possible data input generating imaging apparatus can be found from publication GB2592583. Instead of a 360 degree camera, a simpler image capturing apparatus, for example a static camera capturing views of more limited angle, may be used. The camera apparatus can comprise any image capturing apparatus capable of producing image data of the space. For example, a mobile device such as a mobile phone, smart phone or a table computer may be used. The images may be taken from for example a closed space such as a room, a floor, a corridor, an open space such as an outdoor view and so forth. The camera apparatus is shown to comprise a data processing unit 14 configured to control the operation of the camera. The processor apparatus may also perform at least some of the image processing, image alignment tasks and so forth. The camera apparatus is connected via a data communication link 22 to the data processing apparatus 20 providing the scheduling system via appropriate interfaces (not shown for clarity). The data processing apparatus 20 can be arranged to process image data captured by and obtained from a number of camera apparatus. The processing can be arranged to occur substantially in real time or periodically. Transfer of image data to the data processing apparatus 20 is denoted in Fig. 3 by dashed arrow 22. It is noted that at least a part of the processing may be distributed between separate data processing devices and / or may occur in the camera device. Other types of data collection devices can be utilised. For example, humidity and / or temperature sensors can be provided at the construction site for use in determining conditions and progress of tasks in the spaces. In accordance with a more specific example, humidity sensors are used to detect when a space has dried enough after a task such as concreting or painting or for the next task to start. Temperature sensors may be used to detect when the spatial units start remaining warm enough, for example to detect when heating system is operational and / or windows are mounted. Fig. 4 shows an example of a method for visualising a construction site. At step 100 data comprising information identifying spatial units at the construction site and indicative state of progress of activities in a first time domain in the identified spatial units is received. Progress information is determined at step 102 for the identified spatial units based on the received data and information indicative of state of progress of activities in the identified spatial units in a second time domain, the determined progress information for the identified spatial units is classified at step 104 into predefined state categories, each state category being assigned with a distinctive graphical symbol. A visualisation of the progress information for the identified spatial units is generated at step 106 based on the classification and the assigned distinctive graphical symbols. The distinctive graphical symbols are then presented at 108 on a graphical user interface. State of progress of at least one activity can be determined as a ratio to completion of the activity. The first time domain and the second time domain may comprise distinct time periods, the first time period being later than the second time period. The period can be a predefined number of days, for example five days, a week, ten days, a fortnight, a calendar month and so on. Information enabling determination of the state of progress of activities in the identified spatial units can be stored in a database. Determining of progress information for the identified spatial units can take into account said stored information. In accordance with a more specific example a platform provides an overall aggregate visualisation of change in pace of production per spaces, relative to one or more previous weeks and overlaid with spotlights. Spaces in which a task had previously started, but there has been no new progress for a number of weeks (Stalling Spaces) can also be visualised with spotlights. Spaces that are not stalling may also be visualised with spotlights. The overall pace of production for a filtered selection relative to the previous weeks can be graphically presented. The number of spotlights on the site that have been newly identified by the data collecting arrangement, the number of spotlights resolved in the previous week, and the number of outstanding previously known spotlights can also be presented. The number of stalled spaces can be presented as well. Visual indication of pace, newly raised issues and stalling spaces can be displayed for filtered queries. The filtering can be, e.g., by trades, tasks and components. The algorithm can calculate scores for tasks that are progressing and stalling based on using data such as a difference between the progression of activities in a space in time domain, for example based on the most recent week and the previous week or weeks. This can be based on the data of the actual progress of tasks and components received from the site. The data can be updated and scanned periodically, for example hourly, daily, weekly or fortnightly by the system. The calculations can also take into account whether work on a space had previously started. This can be based on the received information of the actual progress of tasks and components and updated periodically in the system. Falsely identified stalling tasks may be harmful, e.g., because these may lead to misleading communications with and between the construction teams, confusion and / or can mask the true high priority alerts that need to be actioned. Therefore, false alarms should be avoided, or at least the number thereof minimised. In accordance with a possibility the number of false positives for stalling tasks is reduced by configuring the algorithm to filter out spaces where no images were scanned and consequently received for a predefined period of time, for example for the previous week. To optimise the operation in a situation where the system has no image or other data to process in order to determine the state of progress, and cannot objectively decide either way, a possibility is to consider to take a positive view and not assume stalling. A note may be shown to users to indicate that no images are available. If no images are available based on which to estimate whether the space is stalling or not, it can be misleading to conclude that the space is stalling. A claim that a space is stalling may result non-optimal use of time and resources on following up on the perceived issue because there may be no visual evidence that the performance in the space is stalling. Spaces that have been completed previously can also be filtered out as there is no need for a decision regarding ongoing work to be made. Spaces in which the only remaining work consists of known leave-downs, for example, outstanding work indicated as being performed later in the sequence because it is not a blocker to other work (i.e., a sequence of work that has been moved forward without it being completed but which needs to be finished eventually) can be filtered out as well. This information can be derived from the existence of a spotlight for pending rework for the same component as the outstanding activity. A space can be considered a stalling space if works had started in the space and then stopped, as that may indicate issues that may need to be addressed, and a note may be given to highlight to the construction team how long the space has not been worked on. Spaces in which work had not previously started may also be filtered out in certain circumstances. If works had never been started in a space, the policy rule can be that it is not considered a stalling space, since not all spaces on site start progressing simultaneously and the inactivity may not be severe enough to be cause for concern. For example, if the construction process is progressing from the lower floors upwards, it is likely that the top floors will remain inactive for multiple weeks until it is time for them to be worked on. This is simply a result of the way the process is structured and not an indication of any underlying issues, so it would be a false alarm to highlight these spaces as stalling. The users may also be able to filter the visual representations into different categories such as 1) All trades (aggregate data) 2) Specific Trades 3) Specific Tasks and 4) Specific Components. Thresholds to filter out false stalling notifications can be provided. The thresholds can be dimensioned to prevent or at least minimise false flags due to reasons such as rounding or negligible differences in progress. In accordance with an example an algorithm is configured to categorise the spaces into different state categories based on data from the construction site and data regarding previous progress in the site. The classification may be for the following six states: 1) The space has progressed in the past week and the pace of production has increased. 2) The space has progressed in the past week and the pace of production is the same. 3) Activity in the space had started earlier but the space has not progressed in the past week. 4) The space has progressed in the past week and the pace of production has decreased. 5) Work for the filtered selection in the space was completed in the past week. 6) The filtered selection of activities had previously started in the space but has not progressed in the space for a specific / calculated number of weeks. (The number of weeks can be defined differently for different activities and spaces.) 7) The space has progressed in the past week (This state can be used to indicate states 1,2 and 4 above on a more general level). Fig. 5 shows examples of possible graphical symbols visualising the states on a graphical user interface accordingly. Symbol 40 denotes a space that has progressed in the past week and the pace of production has increased. Symbol 41 denotes a space that has progressed in the past week and the pace of production is the same. Symbol 42 denotes a space where activity in the space had started earlier but the space has not progressed in the past week. Symbol 43 denotes a space that has progressed in the past week but also that the pace of production has decreased. Symbol 44 denotes that the scheduled work for the filtered selection in the space was completed in the past week. A group of symbols can be assigned for denoting stalling spaces. These can be displayed in a specific stalling space view. Symbol 45 denotes a space where a filtered selection of activities has not progressed in the space for a specific / calculated number of weeks, the alert being given as a lower priority alert. The specific / calculated number of weeks can be is displayed to the users as this information can assist in the decision making and be beneficial for the productivity of the project. Symbol 46 denotes a space where the filtered selection of activities has not progressed in the space for a number of weeks. This symbol can be used for a higher priority alert. Symbol 47 indicates that the space is not stalling and has progressed in the past week. Symbol 47 is configured to serve as a general indication that a space has progressed as opposed to stalled. Symbol 47 is beneficial in allowing users to compare stalled vs. progressed, without the additional visual noise of the other pace-related states. That is, symbol 47 can be used to show the contrast between spaces with at least some progress and stalling spaces. The computations underlying symbol 47 can be similar to computations for symbols 40, 41 and 43, symbol 47 serving a different purpose on the graphical interface. This is similar to how symbol 42, “no progress”, can have a similar underlying computations to symbols 45 and 46, “stalled for n weeks”. A further category of symbols and views into which the status information can be mapped are neutral indications. The neutral indications can be for status indications that are not critical and / or relevant at the given time. Neutral states do not require an immediate action in the context of the construction site. For example, if a space is complete, no further action is needed, so it is not necessary to bring it to the users’ attention. In Fig. 5 example symbol 48 can be configured for spaces where a filtered selection of activities had been completed in the previous weeks. Symbol 49 denotes that the filtered selection of activities is not tracked in the space. Symbol 50 denotes that the filtered selection of activities has not started in the space. Symbol 51 denotes state where no visual data for the space has been received for the selected / analysed week. The visual effect can be emphasised by use of colours. For example, red for high priority indication and green and / or orange. Orange colour can be used for medium-priority alerts, e.g., pace that has decreased and would need attention from the user whereas green can be used for spaces where no specific attention is needed. The following describes detailed examples of computations by an algorithm to determine various categories of state of progress at a construction site. The algorithm can take into account different policies regarding severity of events, actions, progress and non-activity information. In the examples, the numerical values for thresholds are given as percentages. All percentages specified in the calculations represent the percentage of completion of the tracked activity. E.g., 100% means that the activity is fully completed. The ratio can also be expressed differently, e.g., in scale of 0 to 1, or 1 to 10. The progress of production however can be defined by means of any appropriate values, including cost or unit of value like m3 or m2 etc. that can be used to represent actual progress of activities on a construction site. The values used for the determinations such as the percentages can be defined based on input data from the construction site, such as periodic visual scans of the construction site and sensor data. The percentages can be defined by a project progress tracking system. The project progress tracking system and the herein described visualisation system can be provided as an integrated system. The data processing apparatus 90 of Fig. 2 can be provided with a project tracking module 92 for processing the input data received via interface 94 and performing the percentage computations and a visualisation module 93 for the classification and generation of appropriate visual user interfaces. A model of the project can be created to setup the system in the beginning of the project. The model can be stored as a record 95 in a database 91 of the data processing apparatus 90. The model can comprise a list of tracked activities and definitions what the completion (100%) of those activities requires and / or looks like. It can also be defined in which spaces the activities need to happen. The initial setup can be based on prior knowledge combined with project documentation, e.g., drawings and specifications, mock-ups, prototypes and so on. The model can be created based on expert knowledge, for example knowledge of architects, civil engineers and mechanical engineers and other specialists that is confirmed with users on the site. Over the course of the construction project the system can then track progress at the construction site. The tracking can be based on image data and / or sensor data, appropriate measures against the completed state, whether a component (the most granular visually identifiable or otherwise verifiable activity) has started, progressed, is nearly complete or fully complete. Machine learning can be used to make the tracking more efficient. The training of the machine learning algorithm can be based on work done by in-house construction experts whose knowledge is used to train the machine learning algorithms based on input from a number of sites. This can be provided so that the process can be made more scalable once the algorithms reach a high enough level of confidence. Spotlights, i.e., issues related to the tracked components and visible in images can also be identified during the tracking process. Once estimated, percentages for components can be aggregated into percentages for tasks. In practice, this can be provided based on groupings of the components. Tasks can be configured to match the timeline items in the project schedule provided by users. The tasks can also be defined by the management system as sensible standard groupings of activities (e.g., different Mechanical, Electrical and Plumbing (MEP) works systems, Finishes, etc.). Components can be assigned with corresponding trades, depending on which activity is executed by which trade on the site. This allows aggregation of the percentage of completion for a particular Trade. The total progress for a particular space can, likewise, be computed as the aggregate of completion of all activities that are planned to happen in that space. The aggregated totals can take weights into account. For example, raw percentages may be multiplied by a weight value representing how much the individual activities factor into the total. This can be based on factors such as the relative importance of the activities on site, how long they take to complete, etc. In accordance with a specific example of determining the percentages, flat ductwork and ductwork connection are two components aggregated into a single task. Completing flat ductwork may account for 90% of the total for the associated task, while a ductwork connection may only represent 10% of the total because it is smaller and / or takes less time to install and / or is less critical to unblock. In this context unblocking refers to an activity where workforce can be distributed in a way that allows the activity to be completed. When comparing, e.g., the bulk of ductwork and ductwork connection, a portion of the main ductwork will need to be completed before other work can start, whereas connections can be installed afterwards and are not necessarily stopping other work from being started in the interim. For weighting, this means that one can count the task as “nearly done” even if the connections are unfinished, since the main part, i.e., the part that would block any other work from starting, is finished and the sequence can progress. Therefore, if flat ductwork is 100% complete, the aggregate task will be 90% complete. The remaining 10% is not critical and the policy can allow the subsequent task(s) to start. Some of the definitions of completion or other aspects of the project setup may change based on user feedback. The percentages can be recalculated to account for the changes. The following describes more detailed examples of computations by the algorithm to determine various categories of state of progress at a construction site. In the example a “week” means “past week”. A “selected week” means a specific selected week. The selected week can be selected through the interface. E.g., a user can select ‘cumulative progress (week)’ to see the cumulative progress in the selected week. Selection of ‘cumulative progress (week-1)’ gives cumulative progress in the week prior to the selected week, ‘cumulative progress (week-2)’ gives cumulative progress in the two weeks prior to the selected week and so on. The term ‘progression (week)’ = cumulative progress (week) - cumulative progress (week-1) refers to the difference between progress in the selected week and progress in the previous week. The ‘progression (week-1)’ = cumulative progress (week-1) - cumulative progress (week-2) refers to the difference between progress in the previous week and progress in the week before the previous week. A relatively small margin threshold can be set to avoid false positives due to inaccuracies such as rounding, negligible differences and so on. For example, margin threshold values in the order of 0.1 or 0.2% can be set. The margin threshold can also be for passing from one weekly pace state to another. A separate margin threshold may be used for this. The value thereof may or may not be the same as used for determining stalling spaces. In the examples described below, 0.2% is used for both thresholds but different values may also be used. It is noted that the margin threshold values given herein are only examples, and other values may also be used. The exact value of the thresholds may be changed in accordance with varying conditions, with user feedback, level of granularity and so on. The calculations in the below example are applicable to any filtered set of activities for a space (All, Single Trade, Task, Component). For any space displayed in the building overview it can be determined that the space has progressed in the past week and the pace of production has increased from the previous week by the algorithm determining that ‘progression (week)’ - progression (week-1) >threshold (0.2%) That is, the space has progressed more in the selected week than in the week prior to the selected week. The threshold can be defined as having a small margin of 0.2% rather than zero to avoid false positives due to rounding or negligible differences. To exemplify this further, in a selected week, progress has jumped from 30% to 40% (delta = 10%) and in the previous week, it had progressed from 25% to 30% (delta = 5%). Thus it can be computed 10%-5% = 5% >0.2% and the algorithm can conclude that the pace of production has increased. The algorithm can also determine that a space has progressed in the past week and the pace of production has remained the same based on progression (week) >threshold (0.2%) AND threshold (-0.2%) <( progression (week) - progression (week-1)) <threshold (0.2%) That is, the space has progressed approximately the same amount in the selected week and in the week prior to the selected week. The error margin thresholds are defined as -0.2 and 0.2 in this example rather than relying on strict zero margin to avoid false positives due to rounding or negligible differences. Example of this is when in a selected week, the progress has jumped from 30% to 40% (delta = 10%) and in the previous week, it had progressed from 20% to 30% (delta = 10%). Thus 10%-10% = 0% which is <0.2% and >-0.2%, and it can be determined that the pace has remained the same. Instances where the space has progressed in the past week while the pace of production has decreased can be determined based on: progression (week) - progression (week-1) <- threshold (-0.2%) For example, in case where the current week progress has jumped from 30% to 40% (delta = 10%) and the previous week the space had progressed from 10% to 30% (delta = 20%), the algorithm can be based on computation: 10%-20% = -10% <-0.2% —► pace has decreased Instances where activities in a space that had started earlier but then the space has not progressed in the past week as expected can be identified based on: cumulative progress (week) >1% AND progression (week) <threshold (0.2%) That is, an activity had previously passed the threshold for “in progress”, for example 1% or 2% rather than 0% to avoid false positives due to negligible increases in activity and activity has not had any meaningful uptick in progress in the selected week. Instances where work for a filtered selection in a space was completed in the past week can be identified based on: cumulative progress (week) >99.99% AND cumulative progress (week-1) <99.99% In here 100% is the maximum. The threshold is set to 99.99% rather than 100% to account for any small rounding discrepancies. Example of this is where in the previous week the cumulative progress was 90% (i.e., not finished) and in the selected week this jumped from 90% to 100%, meaning the activities were finished in the space within the selected week. Stalling spaces / tasks / trades can be identified, e.g., such that a filtered selection of activities has not progressed in the space for a number of weeks: cumulative progress (week) >1% AND cumulative progress (week) -cumulative progress (week-n) <threshold (0.2%) That is, an activity had previously started and passed the threshold for “in progress”, which is 1% rather than 0% to avoid false positives due to negligible increases in activity, and the activity has not had any meaningful uptick in progress in the n past weeks. For example, in a selected week the cumulative progress is 30% and in the previous week (n=1, as in week-1) it was also 30%. 30%-30%=0 <0.2. It can be determined that there has been no meaningful progress for one week. According to another example, in a selected week, cumulative progress is 30% and in the 2 weeks prior (n=2, i.e., week-2), it was also 30%; 30%-30%=0 <0.2. It can be determined that there has been no meaningful progress for two weeks. In accordance with a possibility the threshold may be multiplied by the number of weeks looked back from the selected week to allow for a 0.2 threshold for every calculated week. A maximum value of parameter n can be set for which the above condition is true. For example, if cumulative progress (week) - cumulative progress (week-6) = 10% >0.2%*6 that would mean that the space had progressed for the filtered activities compared to week-6. This means that for n = 6 it can be determined that the condition is false and the last n value for which the system registers no progress (for which the condition can be determined as true) is n = 5. This can be considered to mean that the activities in the space have not progressed in 5 weeks. The interface can then inform the user the space has been stalling for 5 weeks. Neutral states can be identified, e.g., based on determination indicative that the scheduled tasks are completed. A filtered selection of activities can be considered having been completed in a space in the weeks preceding the selected week when cumulative progress (week-1) >99.99%. That is, the progress was already at the completion indicating 100% before the selected week even started. Instances where a filtered selection of activities has not started in a space can be determined for example based on: cumulative progress (week) <1% and was never >1% It can also be determined that no visual data is captured and / or received for the space in the past week. Lack of images for the space available for the past or a selected week can be considered to mean that the imaging apparatus has been moved after completion of works in the space or pausing of works for some reason. Lack of image data can also happen because the area is not accessible for a site scanner, for example a person who takes images with a mobile 360 camera on site. For example, there can be other equipment in the way, doors are locked, sensitive flooring or similar works are ongoing and so on, preventing entrance to the space and allowing only the construction workers working on the task to be in the space. An area may also be outside of scope because of contractual reasons, e.g., it has been agreed that floors 1-7 no longer need to be scanned. This may happen when the works are complete or have not started yet, or when the works are paused and it is agreed that no visual scanning is provided for a period of time. Figs. 6 and 7 show examples of the generated overviews presented on a graphical user interface. The used symbols are those shown in Fig. 5. Fig. 6 a display gives an overview of progress in a building site. In the graphical presentation at the central section of the display each floor is divided into spatial units. Graphical progress status symbols are displayed to those units for which the status information has been determined. It can be immediately seen from the display that for some reason the progress has slowed in a couple of spatial units on Floor 6 and that several units on Floor 6 are progressing as before. Floor 5 is progressing faster than before. The upper floors (8 and above) have not progressed at all, i.e., are stalling for some reason. A listing of spotlights is given on the right side of the screen. Fig. 7 is an example of a display of an overview of stalling spatial units. The symbols presented in the centre section of the display gives more insight of the units indicated as stalling on the display of Fig. 6. More particularly, in the example the length of time of the stall is indicated. The seriousness of the stall can be highlighted, e.g., by coloured and / or flashing symbols. The disclosed project visualisation system can provide an efficient visualisation tool for construction projects. Construction project teams can quickly identify any risks of delays in specific areas of a construction site. The system also enables immediate warnings about stalling tasks in the spaces. The system can assist in decision making and support optimum project delivery through visualisation of states of various tasks performed in parallel at different areas of the construction site. Users can be presented on a graphical user interface an easy-to-understand visual overview of the state of the construction site. The overview can be presented whenever needed or periodically. For example, a day-on-day or week-on-week change in the pace of progress at the construction site may be displayed. This allows the users to have a quick understanding of the current activity trends on site and identify early warning signs of stalling work that could cause loss of productivity. In accordance with a possibility the platform providing the scheduling comprises an internet application that allows user interaction. The data processing and the scheduling model can be provided in a virtual server environment, i.e., in the “cloud”. Input information can be received by the platform from data gathering devices via the Internet. Users can input information about their progress and / or events preventing the planned progress through their individual terminals. For example, mobile terminals can be provided with an appropriate application for data input. The application can be adapted for ad-hoc input of information of, e.g., details of any events preventing performance of the task, on-site decisions made to relocate resources to another space on the site, progress reports, images and videos and so on. User may also be allowed to export data from the platform, for example detailed plans and instructions and / or progress reports of other tasks. A graphical user interface may be provided by means of user devices where users can see in a single view the spaces and tasks that are available for each resource across the entire construction site. The users can then use the displayed and visualised information to efficiently reallocate the resources in order to avoid waste of time, resources and materials on the site. The user interface (UI) can be used for visualising blocked areas on the construction site. The UI can also visualise the impact of a blocking task or incidence and the impact performance of tasks available in available spaces would have on the construction project. User input can be provided, for example to specify known reason(s) for blockages in blocked areas, number of available workforce and / or amount of other quantifiable resources for a specific trade, status of drawings, availability and status of materials on the construction site, and so on. Basic form of visualising a blocked area may include visualising data of the blocked spatial units, tasks and trades in the user interface. Additional support can be provided by visual evidence, e.g., an image which can be a 360 degree image captured periodically or an image captured by the on-site users using their terminals with digital cameras. Design readiness for a task, part of a task or a space can also be visualised through integration with a document management and control system. Visualisation of blocked and available spaces and / or design readiness can further include drawings, mock-up images of or actual images captured from the spaces, site maps, and other illustrative and easy to analyse guidance adapted for practical needs in a construction site type environment. These can be opened by selecting the graphical symbol presenting the classified state of the space. Using the data input, the algorithm can look up for instances of tasks in individual spaces where their actual progress is below a threshold indicating no or unacceptably low activity. These tasks may prevent other tasks in affected spaces from starting. Alternative task(s) may need to be determined to prevent the problem from spreading. The various embodiments and their combinations or subdivisions may be implemented as methods, apparatuses, or computer program products. According to an aspect at least some of the data processing functionalities are provided in virtualised environment. Methods for downloading computer program code for performing the same may also be provided. Computer program products may be stored on non-transitory computer-readable media, such as memory chips, or memory blocks implemented within the processor, magnetic media such as hard disk or floppy disks, and optical media such as for example DVD and the data variants thereof, CD, magnetic disk, or semiconductor memory. Method steps may be implemented using instructions operable to cause a computer to perform the method steps using processor apparatus and memory. Computer readable instructions may be stored on any computer-readable media, such as memory or non-volatile storage. The data processing apparatus may be provided by means of one or more data processors. The functions may be provided by separate processors or by an integrated processor. The data processors may be of any type suitable to the local technical environment, and may include one or more of general purpose computers, special purpose computers, microprocessors, digital signal processors (DSPs), application specific integrated circuits (ASIC), gate level circuits and processors based on multi core processor architecture, as non-limiting examples. The data processing may be distributed across several data processing modules and / or provided in a virtual environment. While various aspects of the invention may be illustrated and described as block diagrams, flow charts, or using some other pictorial representation, it is well understood that these blocks, apparatus, systems, techniques or methods described herein may be implemented in various combinations in, as non-limiting examples, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof. The various aspects and features discussed above can be combined in manners not specifically shown by the drawings and / or described above. The foregoing description provides by way of exemplary and non-limiting examples a full and informative description of exemplary embodiments and aspects of the invention. However, various modifications and adaptations falling within the spirit and scope of this disclosure may become apparent to those skilled in the relevant arts in view of the foregoing description, when read in conjunction with the accompanying drawings and the appended claims.

Claims

1. A method for processing construction site related data, comprising: receiving data comprising information identifying spatial units at a construction site and indicative state of progress of activities in a first time domain in the identified spatial units,determining progress information for the identified spatial units based on the received data and information indicative of state of progress of activities in the identified spatial units in a second time domain,classifying the determined progress information for the identified spatial units into predefined state categories, wherein each state category is assigned with a distinctive graphical symbol,generating a visualisation of the progress information for the identified spatial units based on the classification and the distinctive graphical symbols, anddisplaying the distinctive graphical symbols on a graphical user interface.

2. A method according to claim 1, comprising determining state of progress of at least one activity as a ratio to completion of the activity.

3. A method according to claim 1 or 2, wherein the first time domain and the second time domain comprise distinct first and second time periods, the first time period being later than the second time period.

4. A method according to claim 3, wherein determining the progress information comprises comparing progress in the first time period and the second time period.

5. A method according to any preceding claim, wherein the determining of progress information for the identified spatial units further comprises obtaining from at least one memory scheduling information relating to activities in the identified spatial units.

6. A method according to any preceding claim, comprising receiving data from at least one data collecting device located at the construction site.

7. A method according to any preceding claim, comprising determining the state of progress of the activities based on image data and / or sensor data received from the construction site.

8. A method according to claim 7, comprising capturing image data captured by at least one camera apparatus at the construction site.

9. A method according to any preceding claim, wherein the data indicative of progress of activities comprises information of at least one of tasks, components of tasks, groups of tasks and / or groups of components of tasks.

10. A method according to any preceding claim, wherein the classifying comprises determining at least one of:the pace of production in a spatial unit has increased;the pace of production in a spatial unit has remained the same;activity in a spatial unit has started but the space has not progressed;the pace of production in a spatial unit has decreased;activities in a spatial unit have been completed;selected activities in a spatial unit have been completed; and / oractivities in a spatial unit have not progressed for a specific or calculated period of time.

11. A method according to any preceding claim, comprising applying a margin threshold to avoid false classifications due to inaccuracies in input data.

12. An apparatus comprising at least one processor, and at least one memory including computer program code, wherein the at least one memory and the computer program code are configured, with the at least one processor, to:receive data comprising information identifying spatial units at a construction site and indicative state of progress of activities in a first time domain in the identified spatial units,determine progress information for the identified spatial units based on the received data and information indicative of state of progress of activities in the identified spatial units in a second time domain,classify the determined progress information for the identified spatial units into predefined state categories, wherein each state category is assigned with a distinctive graphical symbol,generate instructions for visualisation of the progress information for the identified spatial units based on the classification and the distinctive graphical symbols, andcause display of the distinctive graphical symbols on a graphical user interface.

13. An apparatus according to claim 12, configured to determine the state of progress of at least one activity as a ratio to completion of the activity.

14. An apparatus according to claim 12 or 13, wherein the first time domain and the second time domain comprise distinct first and second time periods, the first time period being later than the second time period.

15. An apparatus according to claim 14, configured to determine the progress information based on comparison of progress in the first time period and progress in the second time period.

16. An apparatus according to any of claims 12 to 15, configured to obtain from at least one memory scheduling information relating to activities in the identified spatial units and determine progress information for the identified spatial units based on the obtained scheduling information.

17. An apparatus according to any of claims 12 to 16, configured to receive data from at least one data collecting device located at the construction site and determine progress information for the identified spatial units based on the data from the data collecting device.

18. An apparatus according to claim 17, configured to determine the state of progress of the activities based on image data received from the construction site.

19. An apparatus according to claim 18, wherein the image data is captured by at least one camera apparatus located at the construction site.

20. An apparatus according to any of claims 17 to 19, configured to determine the state of progress of the activities based on sensor data received from the construction site.

21. An apparatus according to any of claims 12 to 20, wherein the data indicative of progress of activities comprises information of at least one of tasks, components of tasks, groups of tasks and / or groups of components of tasks.

22. An apparatus according to any of claims 12 to 21, configured to classify the progress into one of the predefined state categories based on determination of at least one of:the pace of production in a spatial unit has increased;the pace of production in a spatial unit has remained the same;activity in a spatial unit has started but the space has not progressed;the pace of production in a spatial unit has decreased;activities in a spatial unit have been completed;selected activities in a spatial unit have been completed; and / oractivities in a spatial unit have not progressed for a specific or calculated period of time.

23. An apparatus according to any of claims 12 to 22, configured to apply a margin threshold to avoid false classifications due to inaccuracies in input data.

24. An apparatus according to any of claims 12 to 23, configured to send data for presentation of the display of the distinctive graphical symbols on a graphical user interface of a mobile device.

25. A computer program comprising program code means adapted to perform the steps of any of claims 1 to 11 when the program is run on a processor.

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