The value of the AI construction market was estimated to be USD 466.9 million in 2019. Projections estimate that by the year 2025, the market value will skyrocket up to USD 2312.8 million with a compound annual growth rate (CAGR) of 33.87% between 2020 to 2025. Despite not gaining early adoption within the construction sector as in other areas, AI is now ideally positioned to lead transformative reforms within the sector.
The need to improve the efficiency of operations and safeguard the lives of workers are the major drivers of the increasing adoption of AI applications within the sector. As a result, AI is now being deployed to great success across the phases of planning and design, safety, autonomous equipment, as well as monitoring and maintenance. In addition to its application in these areas; AI is breaking down existing communication barriers among the several players involved in the construction process. Today, the AI technology allows architects, designers and contractors gain access to real-time updates and synchronised files related to a project and thus address one of the main challenges in the construction industry.
Across the world, the rate of adoption of AI within the construction sector is not progressing at the same rate. North-America currently sits second in terms of the market size while the Asia-Pacific region has the largest share of the market. This trend will shift in the coming years as North-America is expected to lead the way due to existing labour shortages within the region driving the demand for automated processes. The United States of America is also a prominent hub for construction technology start-ups further contributing to the expected rapid rise of AI within the region. The AI construction market is, by nature, fragmented i.e. a highly competitive market without major dominant players. However, the key players within this industry across the globe include – Smartvid.io (US), Autodesk Inc. (US), Building System Planning Inc. (US), SAP (Germany), Aurora Computer Services (England) etc.
Further lending credence to the growing influence of AI in today’s world is its deployment across various spheres of infrastructure such as telecommunications, railways, roadways, airports, real estate, ports etc.
AI is leading a transformative charge in several ways across the global infrastructure development and construction landscape. With more people moving to urban areas, the need to upgrade urban infrastructure has never been so important. Some of the ways AI and data analytics are contributing include:
1. PROJECT DESIGN AND PLANNING
It goes without saying that the bedrock of any physical infrastructure project is the planning and design phase. It is also a time demanding phase of the project due to the importance of factors such as the functional operation of the infrastructure, architectural feasibility, compliance with building regulations etc. To cut down on some of these hours spent, AI may be applied in the form of generative design – an AI design exploration process. Using historical data of previous infrastructure designs as well as the specific requirements of the current project such as spatial requirements, structure performance, material and other project costs, scheduling etc.; the generative design model then “constructs” a range of design options which the project architects and engineers can further explore. True to the very nature of AI which is to keep learning and adapting, the generative design technology learns from every design it makes to keep getting better at designing structures.
Although human construction experts could utilize data collected from simulations, models and previous projects to improve and innovate with each new construction project, they struggle when there’s so much information to deal with. This is where AI could augment them and process large amount of data to make the process more effective. Building Information Modeling (BIM) software companies, such as Autodesk, started to use AI and machine learning in the BIM process and tools. Nowadays, AI-assisted BIM tools can learn from data, identify patterns and make independent decisions on how to automate and improve on the model building process.
Human life, is quite simply, sacred. As such, technological solutions seek not only to improve operations but also preserve and safeguard human life. Within the infrastructure development sector, safety considerations are at the centre of applications such as USTAAD, an AI-enabled robot fitted with a rotating HD camera. USTAAD was developed by the Indian Railways for the undergear surveillance of train coaches. USTAAD gives a more accurate view than a human can and also allows for real-time monitoring of the parts. It, therefore, minimises human error in detecting faults which may have serious consequences. Predictive solutions may also be applied to forecast the risks, constructability, and structural stability of a wide range of projects. In this regard, SmartVid.io’s Very Intelligent Neural Network for Insight and Evaluation (VINNIE) holds some promise. Using deep learning techniques, VINNIE has demonstrated its capacity to identify safety aberrations such as workers not using hard hats or wearing high visibility clothing. It does this in far less time and with higher accuracy than a human can. However, the range of issues that VINNIE can identify is limited compared to trained human personnel. Technologies like VINNIE will most certainly improve in the near future and its advancement will bode well for human safety.
Every machine created has been to get more done in better ways and in lesser time. AI applications in the construction market are no different. AI algorithms can solve transport linked inefficiencies by optimising transport routes and improving traffic navigation thus helping to save time. Furthermore, the development of AI-powered self-driving construction equipment can take over some of the monotonous tasks such as welding, bricklaying, demolition etc. This frees up time human labour can be put to accomplishing other project progressive tasks. The efficiency of operations may also be found in improving customer service interactions such as Stallion AI’s NLP-powered virtual assistant which help enhance customer experience and boost satisfaction.
4. MONITORING AND MAINTENANCE
Beyond the actual construction process, the role of monitoring and maintenance in the infrastructure development sector cannot be overstated. Internet of Things sensors are already being deployed for the monitoring of the structural integrity of buildings and bridges to identify structural defects. Bentley System’s Reality Modelling Software, ContextCapture, creates a representation of an infrastructure asset in the form of 3D and then maintains it through continuous surveys. Monitoring systems have also been applied through technologies like Siemens Mobility which has a prototype technology that can control traffic lights through the monitoring of traffic density. Within the ports system, maintenance issues are being handled by AI as exemplified by the AI solution for threshold setting and routine centralised cloud monitoring, set up by Adani Ports and Special Economic Zone. On worksites, solutions such as Doxel AI’s AI-powered rugged robots and drones fitted with cameras and LiDAR sensors can match current work progress to the expectations of the client.
With the increasing urbanisation of the world, many governments are leaning towards the integration of AI into infrastructural development to support the vision of having smart cities. Waste management will be an important component of that vision and AI can play a big role. Intelligent water management systems (green space systems) can be developed to respond in real-time to the influence of climate change on urban water in the environment, helping to save and recycle water. By integrating the green space system with sewage and water disposal systems, a circular economy may be developed. In addition, urban comprehensive zones can focus on the development of intelligent waste monitoring and management networks for better control and operations. This waste monitoring system would serve to oversee intelligent waste sorting systems developed to handle dry and wet wastes.
The world is witnessing the subtle but progressive multi-sectoral push of AI. In the infrastructure development sector especially, the jump of the human race towards futuristic systems and structures may be better facilitated. The infrastructure development sector must keep innovating and integrating AI into operations to create a more efficient and safer world.
This article was originally published by the author on LinkedIn: https://www.linkedin.com/pulse/5-ways-artificial-intelligence-transforming-samer-obeidat-mgm/