Predictive Construction Heat Maps for Schedule and Budget Risk
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Construction projects face inefficiencies in managing vast amounts of information, with no visual tools to convey actionable insights about how specific location-related information influences project status metrics, and stakeholders struggle to intuitively identify schedule or budget-related issues without manually inspecting dispersed data assets.
Innovation Solution
A software technology generates heat maps that visually represent target status dimensions using color scales, determining relationships between data assets and locations, and dynamically updates as new information is added, providing actionable insights and risk detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If construction project data is managed using traditional software applications, then data can be stored and organized, but stakeholders cannot intuitively identify schedule or budget-related issues without manually inspecting dispersed data assets
Solution Approach 1:
The patent transforms dispersed one-dimensional data assets into a two-dimensional spatial heat map representation. Location entities are mapped to spatial positions, and their status values are visualized through color coding, enabling stakeholders to perceive project status at a glance rather than manually inspecting scattered data
Solution Approach 2:
The patent uses color scales to encode status dimension values of location entities. Different colors represent different status levels (e.g., red for critical issues, yellow for warnings, green for normal status), allowing stakeholders to quickly identify problems without reading detailed data
2Loss of information
If visual heat maps are generated to show project status, then actionable insights become intuitive, but the system complexity increases to process and map data assets to location entities
Solution Approach 1:
The patent introduces location entities as intermediary objects that connect data assets to spatial representations. Data assets are associated with location entities, which are then mapped to positions in the heat map, creating a layered intermediary structure that simplifies the transformation from raw data to visual insights
Solution Approach 2:
The patent segments the construction project into discrete location entities (e.g., rooms, areas, sites), each with its own status dimension values. This segmentation allows the system to process and visualize project status in manageable units rather than as a monolithic dataset
3Measurement precision
If machine learning models are used to determine relationships between data assets and location entities, then predictive analytics are enhanced, but processing time and computational resources increase
Solution Approach 1:
The patent uses machine learning models to pre-determine relationships between data assets and location entities during data ingestion or periodic updates. This preliminary processing enables the heat map to be generated quickly when needed, as the heavy computational work of relationship determination is performed in advance
Data Source
AI summary
An example computing platform is configured to: determine, via a first machine-learning model, a relationship between a data asset associated with a construction project and a first location entity associated with the construction project; update the data asset to include an indication of the relationship; receive an indication of a target status dimension and a request to generate a heat map for the construction project; determine, for the first location entity, a first value for the target status dimension based the relationship; generate data indicating the heat map, the heat map comprising a visual representation of the first location entity displayed in a first color along a color scale that represents the first value for the target status dimension; and transmit, to an end-user device, the data indicating the heat map and thereby cause the heat map to be displayed via the second end-user device.