Overview
Australia’s construction industry is a cornerstone of the country’s economy, accounting for approximately 8% of GDP, as well as playing a crucial role in infrastructure provision, housing provision, and urban planning. However, the industry is facing major challenges, including rising labour costs and material shortages. Consequently, it is essential that the industry take advantage of the latest breakthroughs in AI technology to deliver improved safety, efficiency, quality control and sustainability.
Improved Project Design and Planning
AI tools which use historic data to plan future projects efficiently can minimise factors such as timeframes, costs, and human error to a significant degree. Three specific examples of this include:
- Generative Design: Not only can architects and engineers use generative AI to optimise designs based on cost, environmental factors, project requirements, efficiency, and sustainability; those plans can be shared with the supply chain, allowing for full responsiveness in real time.
- Predictive Analysis: AI algorithms can analyse historical project data to predict project timelines, costs, and potential risks.
- Task automation: AI can be trained to automate repetitive, time-consuming tasks such as data entry, inventory management, logistics, and document processing – freeing up human talent for more complex tasks.
Risk Management
Risk management, including the recognition and mitigation of legal, strategic, financial and security threats to the organisation, is a vital component of construction projects, making it a prime candidate for AI integration. This can take two forms: the mitigation of physical safety threats on site, and data analysis to identify risk more generally.
- AI-powered Sensors: AI-driven cameras, drones, and other sensors can interpret images and data to recognise worker safety hazards in real time. By issuing warnings for non-compliance with safety protocols, AI allows site managers to respond quickly to developing safety threats even when working remotely.
- Risk Prediction: By analysing current plans against historic data, AI-driven algorithms can detect patterns and signs of risk that human analysts might overlook. This can flag potential risks in the preliminary stages before they compound into problems that pose a threat to the successful completion of a project.
Quality Control
The success of a project is dependent on more than simply planning and risk management; analysis and the use of AI tools as the project unfolds, help to ensure that all the careful planning pays off. Construction projects which may take months or even years to complete can be derailed along the way due to several unexpected factors. AI can be used to support managers’ decision making in real time, helping to keep projects on time and to budget.
- Real-time Monitoring: AI modelling of the project as it unfolds over time can provide early detection of anomalies or deviations from plans before they escalate. This allows project managers to step in and take action to keep the project on track before serious problems arise.
Project Management and Collaboration
Efficiency is a matter of data. Things such as lead time for the procurement and delivery of materials, equipment usage optimisation, and worker allocation – all require prior knowledge of how long processes take, and the manpower, tools, and materials needed to complete them. By analysing prior jobs and monitoring projects as they progress, AI can provide this data in a format that supports management and collaborative decision-making throughout the supply chain.
- Resource allocation: AI-driven data analysis is perfectly placed to assist project managers in scheduling, the creation of customised workflows, and budget control.
- Education and Training: Historically, the construction industry has relied on entrants to the industry building up experience over an extended time, but this approach is fraught with pitfalls. AI-driven apps can assist newcomers to the industry to learn on the job, by providing support in decision-making through suggested best practices and predictive modelling.
- Documentation: Correct documentation helps ensure transparency and accountability and is useful for maintenance and auditing. However, it can be time consuming to produce. AI platforms have already been developed which can photograph progress on-site and categorise the information in an easily accessible format, allowing managers to remotely monitor progress and compliance.
Sustainability
The construction industry has transformed the way it operates in recent years, incorporating principles and practices designed to increase sustainability at every level of the construction process. From assisting with the utilisation of sustainable designs and incorporation of green materials, to supporting the adoption of sustainable building standards and technologies, AI can be used to assess and mitigate the environmental impacts of construction projects.
- Design Optimisation: In addition to cost and planning efficiency, AI can be used to analyse and model building designs to maximise environmental efficiency, supporting engineers and architects in making design decisions that comply with green building standards.
- Materials production: Machine learning has already played a crucial role in helping researchers to increase the durability of materials while reducing their environmental impact. Further advances are likely, with continued use of AI algorithms.
- Energy Efficiency: A key AI technology in the sustainability arena, smart metres and systems use real-time monitoring and data to allocate energy efficiently. These include smart Heating, Ventilation and Air Conditioning (HVAC) systems, lighting controls, and electricity metres, among other technologies.
The Current Generation of AI-Driven Tech is Just the Beginning
For the last 20 years, Intergy has been leading the way, helping clients integrate the latest IT advances into their workflows. As AI develops, we will continue to bring best practice to the construction industry, developing custom made apps that utilise AI to increase efficiency and outcomes.
