Abstract: Disclosed herein is new software technology for creating and managing a lookahead schedule for a construction project. In one aspect, disclosed herein is a method that involves (1) receiving, from a client station, a request to create an initial lookahead schedule for a project, where the request comprises timeline information for the initial lookahead schedule, (2) after receiving the request, creating the initial lookahead schedule based on the timeline information and a previously-created master schedule for the project, and (3) causing the client station to present a user-interface view that provides a representation of the initial lookahead schedule.

Abstract: Techniques for facilitating automated two-dimensional (2D) clash detection on objects displayed within a 2D view generated from a three-dimensional (3D) model of a construction project involve (1) tracing an intersection of (i) a cross-sectional plane and (ii) two or more objects in the 3D model, (2) based on tracing the intersection, determining respective 2D boundaries of the two or more objects, (3) generating a cross-sectional 2D view that depicts the intersection and includes representations of the respective 2D boundaries of the objects in the 2D view, (4) causing an end-user device to present one or more user interface views for receiving user input indicating a clash detection scope, (5) based on data defining the clash detection scope, identifying any clashes between objects displayed in the generated 2D view, and (6) causing a respective indication of each identified clash to be displayed at the end-user device.

Abstract: An example client device is configured to: (i) access a building information model (BIM) file for a construction project, (ii) obtain an initial list of BIM data objects included in the BIM file, (iii) present, to a user, a visualization of the initial list of BIM data objects, (iv) receive a search query for the list of BIM data objects, (v) after receiving the search query, present, to the user, a visualization of a filtered list of BIM data objects comprising a given subset of BIM data objects that are identified based on the search query, (vi) receive, from the user, a request for an action to be taken for at least one BIM data object that is selected from the filtered list of BIM objects, and (vii) based on the received request, cause the requested action to be taken for the at least one BIM data object.

Abstract: Improved software technology and techniques for enabling creation and management of a customized work breakdown structure (“WBS”) for a specific project may comprise various phases. For instance, a first phase may involve defining an organization-level WBS comprising a first set of customized, multi-dimensional WBS codes that serve as a starting point for the WBS codes to use for projects being handled by the organization, a second phase may involve defining a project-level WBS comprising a second set of customized, multi-dimensional WBS codes to use for a particular project being handled by the organization, and a third phase may involve using the defined project-level WBS to manage certain aspects of the particular project. Further, access to customize WBS variables may be regulated based on user access permissions information indicated by an organization and/or project-level WBS.

Abstract: A smart wearable device for hands-free data capture facilitates documentation of real-time observations and creation of new data objects within a software application based on the observations. Image data depicting one or more physical objects observed by a user of the smart wearable device, voice data indicating a user request related to the physical objects depicted in the image data, and contextual information related to the user and the physical objects depicted in the image data, are used to generate a prompt for input to a generative AI model that is to respond to the user request. Based on the prompt, the generative AI model outputs an application-specific command that is to be carried out by a given software tool of the software application, such as a command to create a new data object of a given type within the software application.

Abstract: The present disclosure is directed to a software tool that facilitates the presentation of a three-dimensional view of a construction project as well as the generation of various types of two-dimensional technical drawings based on this three-dimensional view. In one implementation, the software tool causes a computing device to engage in the following operations. The computing device may receive a user input identifying at least one first mesh and at least one second mesh, determine portions of each identified mesh that intersect with a two-dimensional plane, and generate a two-dimensional drawing including a display of relevant dimensioning information based on the determined portions.

Abstract: An example computing platform is configured to: (i) receive an incoming request to identify relationships between data objects within a construction management software application; (ii) identify an AI agent to handle the incoming request; (iii) generate, via the AI agent, a search query for identifying a candidate set of data objects related to a given data object; (iv) perform a search with the search query to identify the candidate set; (v) generate a prompt comprising a request to determine which of the candidate set are related to the given data object; (vi) pass the prompt to a generative AI model; (vii) receive, from the generative AI model, a prediction of which of the candidate set are related to the given data object; (viii) based on the prediction, determine a final set of data objects related to the given data object; and (ix) send a response identifying the final set.

Abstract: Techniques for performing an automated clash detection analysis on two-dimensional (2D) drawings associated with a given location of a construction project involve obtaining a set of 2D drawings for a construction project and identifying a subset of the 2D drawings that are associated with the given location of the construction project. From the subset of 2D drawings, a first 2D drawing and a second 2D drawing are selected for inclusion in the automated clash detection analysis. Based on respective sets of key points, the first and second 2D drawings are aligned and layered to produce an overlaid view. Objects in each 2D drawing are identified, and the overlaid view is analyzed to identify clashes between objects in the first 2D drawing and objects in the second 2D drawing. Respective visual representations of identified clashes may be displayed for user interaction.

Abstract: A computing platform may obtain a plurality of data files and, for each respective data file of the plurality of obtained data files, obtain contents associated with the respective data file and evaluate the contents associated with the respective data file to determine a respective data structure for the respective data file. The platform may compare the determined respective data structures and thereby identify one or more data structure differences among the determined respective data structures for the data files and, based on the identified one or more data structure differences among the determined respective data structures for the data files, determine a revision history for the plurality of data files. The platform may transmit, to a client station, a communication related to the revision history and thereby cause an indication of the revision history to be presented at a user interface of the client station.

Abstract: Techniques for managing data and data connections for a construction project involve (1) establishing respective data connections between (i) each party-entity data record and a project-entity data record for the construction project, and (ii) each party-entity data record and each respective object-entity data record for the construction project, (2) determining each party's permissions for retaining access to (i) the project-entity data record and (ii) each object-entity data record after a trigger event occurs, and (3) generating (i) respective connection data encoding the party's permissions for retaining access to the project-entity data record to be stored in association with the respective data connection between the party-entity data record and the project-entity data record and (ii) respective connection data encoding the party's permissions for retaining access to each respective object-entity data record in association with the respective data connection between the party-entity data record and the

Abstract: A pattern attaching technique involves (1) obtaining a first collection of data libraries associated with a first set of intersection points among a first set of lines in a first two-dimensional (2D) drawing and a second collection of data libraries associated with a second set of intersection points among a second set of lines in a second 2D drawing and (2) comparing the first collection of data libraries and the second collection of data libraries in order to determine whether the first 2D drawing and the second 2D drawing represent a same portion of a real-world environment. Each data library associated with a given set of intersection points includes location information that describes a respective location of each respective intersection point in the given set of intersection points relative to each other intersection point in the given set of intersection points.

Abstract: A computing platform is configured to (i) receive configuration data defining a permissions group for a construction project, the configuration data indicating a data domain and a set of actions performable on data objects within the data domain that have a particular value for a particular data object attribute, (ii) after receiving the configuration data, receive a data access request, on behalf of a user account, for a data object within the data domain, (iii) determine that the user account is a member of the permissions group, (iv) determine that the data object has the particular data object attribute with the particular value and thereby satisfies the condition, and (v) based on determining that (a) the user account is a member of the permissions group and (b) the data object satisfies the condition, determine that the user account is permitted to perform the set of actions on the data object.

Abstract: A computing system is configured to: (i) create a data science model that is configured to (a) receive a value for a metric that provides insight regarding a party's usage of a software tool of a construction management software application on a construction project and (b) based on an evaluation of the received value for the metric, output a prediction of the party's performance on the construction project and, (ii) after creating the data science model, utilize the data science model to produce a prediction of a given party's performance on a given construction project by inputting a given value for the metric into the data science model and thereby causing the data science model to (a) evaluate the given value of the metric, and (b) based on the evaluation, output the prediction of performance on the given construction project.

Abstract: A computing device is configured to obtain gridline information for a three-dimensional drawing file and generate a two-dimensional view of the three-dimensional drawing file that includes (1) at least one gridline corresponding to the obtained gridline information, (2) at least one intersection between two meshes, and (3) initial dimensioning information involving (a) the at least one gridline and (b) at least one of the two meshes. Based on a user request to adjust a perspective of the two-dimensional view, the computing device adjusts the perspective of the two-dimensional view and thereby generates an updated two-dimensional view that includes updated dimensioning information corresponding to one or more meshes displayed in the updated two-dimensional view.

Abstract: A computing platform is configured to: (i) receive, from a first client station, (a) data related to the first client station and (b) a first image associated with a target location; (ii) based on the received data related to the first client station, determine a location signature associated with the first image; (iii) determine that the location signature associated with the first image has a threshold level of similarity to a location signature associated with a second image that is associated with the target location; (iv) evaluate at least the first image to determine progression of a construction-related activity at the target location; (v) based on the evaluation of at least the first image, determine that the construction-related activity at the target location has progressed a threshold amount; and (vi) transmit, to a second client station, a communication related to progression of the construction-related activity.

Abstract: A computing platform is configured to (i) receive data objects related to a construction project, (ii) add the data objects to a construction knowledge graph as nodes that are connected to other nodes representing other data objects, (iii) determine, via a machine-learning model trained using historic construction project data, a first risk score for a first data object, (iv) determine, via the machine-learning model, a second risk score for a second data object, where the second risk score is based on (a) the first risk score and (b) a degree of separation between the first data object and the second data object in the construction knowledge graph, (v) based on the second risk score, automatically generate a suggested action to be taken with respect to the first data object, and (vi) cause an indication of the suggested action to be displayed at a client station of a user associated with the construction project.

Abstract: A computing platform is configured to (i) load source data comprising (a) a set of log entries of a construction project and (b) a schedule of the construction project, (ii) preprocess the source data, (iii) provide the preprocessed source data as input to a large-language model (LLM) that is configured to generate insights related to progress tracking and thereby determine one or more insights related to progress tracking for the construction project, and (iv) cause the one or more insights to be presented to one or more individuals involved in the construction project.

Abstract: A computing platform is configured to: (i) generate a data object; (ii) initialize a public conversation thread associated with the data object, the public conversation thread is accessible by each of a first group of users; (iii) cause a client device to present an interface for creating one or more limited conversation threads associated with the data object; (iv) after causing the client device to present the interface, receive, from the client device, a request to create a limited conversation thread associated with the data object that is accessible by each of a second group of users, wherein the second group of users is a first subset of the first group of users; and (v) based on the second request, generate the limited conversation thread associated with the data object, wherein the limited conversation thread is accessible by the second group of users.

Abstract: A computer-implemented method for monitoring productivity, health and safety risks posed by activities and objects, and other signals present at industrial sites comprises: receiving data inputs from input devices at an industrial site; selecting a data model that is programmed to detect activities or objects associated with workers or equipment present at the industrial sites; applying the data inputs to the data model to receive output data specifying whether the activities or objects associated with workers or equipment are present at the industrial site; and if they are present: based the output data, determining characteristics of the activities or objects; based on the characteristics, determining whether that the activities or objects cause any productivity, health or safety risks at the industrial site; and if so, generating notifications indicating the health or safety risks at the industrial site.

Abstract: An example computing platform is configured to: obtain a two-dimensional drawing of a portion of a construction project; perform an image processing analysis of the two-dimensional drawing to identify one or more location entities within the two-dimensional drawing; derive embeddings for each location entity in the two-dimensional drawing; based on the derived embeddings, determine relationships between the one or more location entities; and based on the determined relationships between the one or more location entities, generate a location entity data taxonomy that includes each identified location entity as a respective node that is related to at least one other location entity.