AI products such as Amazon Alexa® and Google Nest Hub® use graph technology to return desired results to you. If you say “Alexa, play me holiday music,” there are a series of decisions made via nodes that enable a result to be generated based on your “intended request.” This type of AI exists within the construction industry. It’s used in project management software such as StratusVue to help improve efficiency on a job site.
What Is A Graph Database?
A graph database uses graphed references for semantical data associations. In an undirected graph, an edge connecting two nodes has a single meaning. In a directed graph, the edges connecting two different nodes have more than one meaning. Graphed data better improves machine learning and artificial intelligence.
So, How Does It Work?
When we think about the premise of connecting two nodes, it becomes a limitless association between every role and stage of a construction project. When we apply that simple premise that Node 1 can be connected to Node 2 (estimating to buyout) and then Node 2 can be connected to Node 3 (buyout to scheduling) and Node 3 can tie to Node 4 (scheduling to pay apps) the world can now associate data and use it like never before.
We are all used to reports, logs, construction documents, contracts, schedules, and plans. There are so many micro-responsibilities within a successful project. We have defined roles that manage each aspect and each role has specific responsibilities.
AI’s responsibility is to learn the nuance and tactics of each of the jobs. This enables teams to focus on building and constructability. Construction’s biggest gains will come from a directed graph that connects two different nodes and can understand the data semantically; or understand it as a seasoned professional would understand documents.
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