AI is having a transformative effect on global industries. The construction industry, especially in India, could benefit immensely from AI adoption. Despite being worth over $700 billion, the Indian construction industry is one of the least digitised sectors, often plagued with delays, budget overruns, quality issues, and safety lapses.
While a typical construction project goes through phases like Pre-construction, Execution, Closure and Operations, and maintenance etc, Let’s deep dive into how AI and machine learning technologies present opportunities to transform these construction phases and help construction businesses drive efficiency, enhance quality, improve performance, and straighten safety on sites.
Project feasibility study
AI can come to aid in the early stages of construction projects in India, making surveys and feasibility studies faster, more accurate, and cost-effective. By analysing vast amounts of data with machine learning, AI can swiftly assess factors like terrain, climate, and demographics. AI can predict project success by analysing past data, including budgets and timelines. Additionally, it can evaluate environmental impacts, aiding in sustainable decision-making.
Designing
Generative designs offer remarkable potential. AI-generated 2D plans and 3D renders are already a reality and the new age designers have started creating frameworks to instruct the AI to generate, tweak and refine their designs.
Building Information Modeling (BIM) aids Construction professionals in creating 3D models for efficient planning, designing, visualising and detecting clashes in construction projects.
AI can help Architects in creating Models with multiple variations and quick iterations to arrive at flawless designs.
At the same time, Machine learning can help them analyse the vast amount of data to optimise designs for energy efficiency and cost savings.
By leveraging AI-powered design tools, architects and engineers can create sustainable, cost-effective construction designs that meet both functional and aesthetic requirements.
Site management and monitoring
AI-powered site management systems can monitor construction progress in real-time, and identify potential bottlenecks and areas for improvement.
Construction companies can use AI-powered robots equipped with cameras to capture 3D pictures at construction sites. With the help of neural networks, these pictures can be cross-checked with reference to the information from BIM and the bill of materials. The engineers managing large projects utilise this information to keep track of the progress. It also helps identify quality issues at an early stage while keeping a tab on financial information, time schedules and resource allocation.
Safety
AI algorithms can automatically prioritise safety issues based on criticality e.g.: unsafe scaffolding, waterlogging, and personnel lacking essential protective equipment like gloves, helmets, and safety glasses.
It empowers contractors to prioritise projects based on risk rankings and proactively address potential safety concerns, reducing the risk of accidents and associated costs.
Building operation & maintenance
Artificial intelligence is increasingly being integrated into commercial and residential buildings to optimise energy consumption, control environmental factors such as lighting and temperature, and enhance security measures. In the future, we can envision the emergence of cognitive buildings that leverage historical data to analyse and upgrade themselves autonomously.
Personal assistance & training
Completing construction manually can be tedious, time-consuming, and susceptible to errors.
Project managers are at the heart of these construction projects and often finds themselves occupied in assigning work, managing employee records, making informed decisions related to project timelines, resource allocation, and risk management.
AI as a digital assistant to project managers can efficiently automate these mundane tasks, minimising errors and freeing up valuable time of resources so that they can concentrate on specialised areas, strategic planning and problem-solving, enhancing their overall productivity.
Further, AI can be tasked with training construction project managers by simulating various project scenarios and challenges, allowing them to gain practical experience in a safe and controlled environment. Moreover, AI can provide personalised training modules based on the individual’s learning style and pace. It can also analyse performance data to identify areas of strength and weakness, providing targeted feedback to improve skills. Additionally, AI can keep managers updated on the latest industry trends and best practices.
In the wake of AI’s potential to disrupt, the government has to take steps to make sure that the usage does not become detrimental to employment in this sector and also it does not shift the power equation completely towards big private players – who can invest in these technologies.
It’s vital for governments, particularly India, to strategically allocate resources for stack-level AI Infrastructure, set up labs to fine-tune Indian construction project data and build protocols so that project data by private players enrich the stack-level data. This investment is crucial to empower SMEs involved in the construction industry and give them a level playing field against big players. Also, there seems to be an opportunity for Businesses providing AI-powered construction robots & drones as rental services for SMEs who might not be able to afford to invest in R&D or building this hardware.
Looking to the future, the private sector needs to take proactive steps towards digitising the construction industry in India, which still relies heavily on outdated methods and is considered a laggard in terms of technology use. The government, on the other hand, must bolster its incentivization programs to assist private entities in accelerating this transformation. Together, these efforts will catalyse the industry’s evolution towards more efficient, cost-effective, and innovative construction practices.
Puneet Bansal, Co-founder, RDash.
