Artificial intelligence has arrived in the construction industry. The report Artificial Intelligence in the Construction Industry 2020-2025 by Global Market Insights, Inc. found that the global AI market in the construction industry is estimated to reach a value of $4.5 billion by 2025, driven by the rising demand for automated and efficient construction processes. It has emerged as a technology that has the potential to completely transform our industry. As we enter the next frontier of construction technology, it is critical to understand what artificial intelligence is and how it offers unique solutions to advance the construction industry's productivity and performance. Additionally, the increasing demand for AI-based solutions, such as automated building information modelling (BIM), is expected to fuel the market growth.
This article provides an overview of artificial intelligence in preconstruction. We'll look at how AI can help businesses improve their decision-making and strategic preconstruction planning processes.
What exactly is artificial intelligence (AI)?
The data-rich, complex modern construction environment provides an opportunity for businesses that can harness data, generate intelligible insights, and make sound strategic decisions. Following years of development and imagination, artificial intelligence is gaining traction in the construction industry.
AI is now a reality as a result of advances in computing power, algorithms that follow precise steps, large sets of data produced by the industry, and innovations in the systems that combine these advances. The time has come to understand and integrate AI into your business.
Artificial intelligence is not a new concept, with roots dating back to the 1950s. A pioneer in the field, Arthur Samuel, defined it as "the field of study that gives computers the ability to learn without being explicitly programmed." In other words, artificial intelligence (AI) involves computers and systems that learn from experience. The goal of AI is to make machines do things that humans currently do, but better and faster.
Deep Learning, Machine Learning, and Artificial Intelligence
Artificial intelligence is a branch of data science that combines computer technology with massive amounts of data to solve problems. You may have encountered AI while conducting a voice search with Amazon's Alexa or Apple's Siri. AI is also used by search engines to collect and retrieve relevant information based on user queries. Videos recommended by YouTube or Netflix are AI-powered results that recommend titles based on your preferences and viewing habits.
Although the terms machine learning and artificial intelligence are frequently used interchangeably, they are not completely interchangeable. Machine learning is a subset of AI that learns from experience, adapts, and improves performance without being explicitly programmed.
Deep learning is a third area of artificial intelligence that is receiving a lot of attention right now. Deep learning is designed to extract the most value from our way of processing information, as is all AI. Our brains use neural networks, which are groups of brain cells that help us process information by connecting signals. Deep learning employs artificial neural networks to process large amounts of data and solve problems with little assistance from humans. These artificial intelligence networks are valued for their ability to handle lots of data, continue to improve as it trains and learns, and solve complex issues. These artificial intelligence networks are valued for their ability to handle large amounts of data, improve as they train and learn, and solve complex problems.
Preconstruction Artificial Intelligence
Before a commercial construction project can begin, a variety of people and teams from various disciplines and expertise must collaborate and plan how the project will proceed. Preconstruction refers to the phases of construction that occur before the actual construction work begins. Preconstruction involves building owners, architects and engineers, trade contractors, general contractors, building product manufacturers, and many others.
By identifying and addressing the sequence of people and events that will get the project completed, the preconstruction process in commercial construction helps to ensure that the project is completed on time, within budget, and to the client's satisfaction.
Solid foundational work in preconstruction, like the projects being built, has a significant impact on the overall strength of the project. Preconstruction stages differ depending on variables such as the type of structure or project (e.g., hotel, school, road, or bridge), project delivery methods, the scope of work involved, and whether the project is public or private.
AI in Project Preconstruction
The preconstruction project stages outlined below provide a framework for the steps before construction begins, as well as how artificial intelligence is changing how this planning is carried out.
Pre-Design: The conceptual design, initial project planning, project development, and feasibility studies are all part of this phase. The project team typically starts with the structure's concept, then conducts a site analysis to identify potential obstacles and develops a plan to address them. This phase also includes the creation of a preliminary or working project scope and budget.
AI in the pre-design or initial project planning and development phase is beneficial for feasibility studies to determine the viability of a project. Risks can be identified and analysed using a variety of data, including financial data, market data, and data on the project's potential environmental impact. Risk analysis can help you decide whether or not to proceed with the project. At this stage, AI is a powerful tool because it provides thoroughness and accuracy, as well as a general lack of bias.
Design Development
This phase entails the creation of detailed design documents that will guide the project. Architectural, structural, mechanical, electrical, and plumbing plans are among the documents included in this stage.
The design development phase of the project development process is critical. It entails developing the conceptual design into a more detailed and buildable design, progressing from broad concepts to more specific ones. Many important decisions that will shape the final project are made during the design development phase, including cost, energy efficiency, and overall functionality. Artificial intelligence can help in this phase by developing new tools and techniques to improve the efficiency and quality of the design development process.
Construction Documents
The development of final construction documents, such as detailed construction plans, building product specifications, and contract documents, is included in this phase. The construction schedule, which outlines the sequence and expected duration of all activities required to complete the project, is nearing completion.
AI-based tools can be used to automate the process of extracting, analysing, and processing data from construction documents. Natural language processing (NLP), for example, can be used to analyse project requirements and generate a detailed project scope document based on two-dimensional construction plans such as PDF files. NLP has been around for over a half-century and is the component of AI that understands and interprets written and spoken human language. When compared to the tedium of traditional methods, such as manual data entry or spreadsheet calculations, this can save time and resources.
Bidding and Negotiation
During this phase, the plans are distributed for bidding to trades, contractors, and manufacturers. The project team will go over the bids, negotiate with contractors, and choose the best bid. This is the critical phase for general contractors and trade contractors, which includes producing and delivering detailed takeoffs and estimates in order to submit a competitive bid.
Trade contractors, general contractors, and building supply manufacturers evaluate the scope of the project, identify opportunities to pursue, analyse bidding strategies, and determine which projects will succeed.
AI can help trade contractors streamline processes, automate repetitive tasks like takeoffs, and speed up decisions like vetting profitable projects.
Permitting and Approvals: During this phase, the construction documents are submitted to the appropriate governmental agencies for review and approval. In this phase, artificial intelligence is used to validate building code compliance and manage the building permit process.
Finalize Preconstruction
This phase includes contract finalisation, contractor mobilisation, and the start of construction activities. Profitability for trades, general contractors, and building product manufacturers is dependent on effective preconstruction planning and strategic decision-making.
The construction schedule, which outlines the sequence and expected duration of all activities required to complete the project, is nearing completion.
Because of the nature of the project, the inherent need for effective communication and collaboration among teams, and local and national regulations, among other things, the preconstruction stages can become more complex. Time and budget constraints are always make-or-break factors in a profitable construction project. AI technology has the potential to improve performance throughout the preconstruction lifecycle.
Where Else Are AI and Construction Collaborating?
Aside from preconstruction, AI is a technology that is enabling improvements in performance and safety in other areas of construction. Here are a few examples:
Predictive maintenance: Artificial intelligence (AI) can be used to analyse data from building systems such as HVAC and electrical systems in order to predict when maintenance is required and prevent equipment failure.
Site safety: AI-powered cameras and sensors (including some that workers can wear) can monitor construction sites for potential safety hazards and alert workers and managers to potential hazards.
Robotics: AI and machine learning efficiency have found their way into robotic bricklaying, welding, and even 3D printing entire structures.
Project management: AI can optimise labour and material allocation, making construction task scheduling more efficient and cost-effective.
Quality control: AI-powered cameras and sensors can monitor construction work quality, detect defects, and alert workers and managers to issues that need to be addressed.
Building performance: Artificial intelligence (AI) could be used to analyse data from building systems in order to improve energy efficiency, indoor air quality, and other performance metrics. Building efficiency simulation with AI, for example, enables the identification of potential energy-depriving areas for better design and construction.
Enhancer of Knowledge and Insight
It is common to hear that computers programmed to think like humans pose a threat to people's jobs. However, construction is inherently dependent on vast institutional and individual knowledge, which AI cannot replace. AI does not have the capability that humans do where human judgement is involved, which we know is everywhere throughout the construction project lifecycle.
Certain roles and responsibilities are more likely to change as AI is implemented. AI combined with a company's organisational knowledge will provide significantly more strategic opportunities than those who do not implement the technologies to streamline performance and make better data-driven decisions.
AI in Construction Has a Bright Future
As more AI-based tools and techniques are integrated into workflows, the present and future of AI in the construction industry look promising. AI is expected to become an even more integral part of the construction process as technology advances, helping to improve efficiency, reduce costs, and improve construction performance outcomes. AI has arrived in the construction industry, are you ready?!
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