"Construction industry employs almost 7% of the global workforce and is therefore an important sector of the economy. The public sector and businesses spend €9,700 billion a year on construction activities. An expert, Hassan Hachem explains how AI will impact the construction industry in Equatorial Guinea.

While other sectors are using Artificial Intelligence and other technologies to improve their productivity, construction is only slowly incorporating these advances" says Hassan Hachem, expert in digital transformation, with offices in the UK, Equatorial Guinea, Ivory Coast and France.

Globally, the construction sector has grown by only 1% per year in recent decades. Meanwhile, the manufacturing industry has grown at a rate of 3.4% and the world economy at 2.7%. Productivity, the total economic output per employee, remained rather constant in the construction sector. In comparison, productivity in retail, manufacturing and agriculture has increased by 1800% since 1950. This is because construction is a sector where digital tools are not widely used and new technologies are adopted only slowly. Adopting the latest technologies can seem daunting to your teams. This is true in every country where we operate (Equatorial Guinea, France, UK, Ivory Coast). But machine learning and artificial intelligence are making jobsites more efficient and saving money. AI solutions that have benefited other industries are starting to emerge in construction.

What is artificial intelligence and machine learning ?

One will find many definition of Artificial intelligence (AI) on the internet. For Hassan Hachem, has today become an umbrella term for a machine's ability to mimic human cognitive functions, including problem solving, pattern identification and learning. Machine learning is a sub-field of AI that uses statistical techniques to enable computer systems to 'learn' from data, without special programming: the more data they are fed, the more efficient they are In the short term, Hassan Hachem predicts limited development of AI in the construction sector. Nevertheless, there is a noticeable shift. Industry players can no longer afford to let the relevance of AI benefit only others. Engineering and construction must take ownership of AI methods and applications. This is the only way to face new competitors and stay in the race. The possible applications of machine learning and AI in the construction sector are numerous. Requests for information, problems to be dealt with and corrective orders are typical in the sector. Machine learning is an intelligent assistant that can examine this mountain of data. It alerts project managers to the most important issues to be addressed. Several applications already use AI in this way. The benefits range from sorting emails and spam to advanced security monitoring.

10 examples of AI use in the construction sector in Equatorial Guinea by Hassan Hachem

1. AI for better designed buildings through generative design

Building information modelling is a process that relies on 3D models and provides architecture, engineering and construction professionals with information for the planning, design, construction and efficient management of buildings and infrastructure. To plan and design the construction of a building, 3D models must take into account the architecture, engineering, mechanical, electrical and plumbing plans, as well as the sequence of activities of the various teams. The challenge is to ensure that the models of each of the sub-teams do not conflict. The industry is currently trying to use machine learning in the form of generative design to identify and limit conflicts between the different models generated by each team during the planning and design phase and thus avoid rework. There are software packages that exploit machine learning algorithms to explore all variations of a solution and generate alternative designs. Machine learning is used to specifically create 3D models of mechanical, electrical and plumbing systems while simultaneously ensuring that these do not conflict with the architecture of the building. It learns with each iteration to propose an optimal solution.

2. Avoiding cost overruns

Most mega projects are under budget, even if they are in the hands of the best teams. Artificial neural networks are being used in some projects to predict different cost overruns based on factors such as the size of the project, the type of contract and the skill level of the project managers. Historical data such as expected start and finish dates are used by predictive models to realistically define future project timelines. In addition, AI helps teams to access training materials remotely and thus to develop their skills and knowledge quickly. As a result, the time required to integrate a new resource on a project is reduced. Project delivery is therefore accelerated.

Impact for Equatorial Guinea

This could be a game changer for a country like Equatorial Guinea Hassan Hachem says, as cost overruns are historically both frequent and huge.

3. AI will make construction sites more productive

Some companies are beginning to offer autonomous construction machines to perform repetitive tasks more efficiently than their human counterparts, such as pouring concrete, erecting a brick wall, welding and demolition. Excavation and earthmoving are carried out by autonomous or semi-autonomous bulldozers that can prepare the site for a job from specifications set by a human programmer. This allows employees to do the construction work themselves and reduces the time required for the project. Project managers can also monitor progress on site in real time. They use facial recognition, on-site cameras and similar technologies to assess productivity and verify compliance with procedures.

Impact for Equatorial Guinea

Hassan Hachem thinks the impact could average as Equatorial Guinea not because of potential savings but because of lack of qualified labour.

4. AI for construction safety

Construction workers suffer five times more fatal workplace injuries than other workers. According to OSHA, the leading causes of death in the private construction sector (excluding highway accidents) are falls, strikes with objects, electrocution and crushing. A Boston-based contractor with annual sales of $3 billion is developing an algorithm that analyses photographs of construction sites, identifies hazards (such as workers not wearing protective equipment) and matches the images to reported accidents. The company says it is able to assess the level of risk on a project in order to warn crews when a significant hazard is detected. The Africain Union Conference Center and Office Complex (AUCC) was designed and built by a collaboration of Tongji University, China State Construction Engineering and the China Architecture and Design Research Group, with the US$200 million budget donated by the Chinese government and using an AI-Powered Building Design.

Impact for Equatorial Guinea

Hassan Hachem thinks the impact could important in Equatorial Guinea where accidents are numerous.

5. Risk mitigation

Every construction project involves various forms of risk in terms of quality, safety, time and cost. The larger the project, the greater the risks, as several subcontractors are involved in parallel on the construction sites. AI and machine learning solutions are now being used by prime contractors to track and prioritise risks so that the team can focus its time and resources on the key risk factors. AI is used to automatically prioritise issues encountered. Subcontractors are scored according to a risk level so that site managers can ensure that risks are mitigated with the most exposed teams.

Impact for Equatorial Guinea

Hassan Hachem thinks the impact could average as in Equatorial Guinea quality is a major challenge.

6. Project planning

An AI startup launched in 2018 promises that its bots and artificial intelligence hold the key to solving the problems of delays and overruns experienced by projects. The company uses robots to automatically obtain 3D scans of construction sites, then feed this data to a deep learning neural network that determines the progress of individual sub-projects. If delays are identified, managers can intervene to resolve problems before they become too big. Future algorithms will use an AI technique called 'reinforcement learning'. This allows algorithms to learn from trial and error. It is able to evaluate an unlimited number of combinations and alternatives from similar projects. This makes project planning easier because the tool can determine the most optimal path and adjust it over time.

Impact for Equatorial Guinea

Hassan Hachem thinks the impact could important as best practices from other countries of the continent arrive with delay in Equatorial Guinea.

7. AI and Big Data in construction

With a huge amount of data being created every day, AI systems have an unlimited source of learning and improvement. Every construction site becomes a potential source of data for AI. Data generated from images taken from mobile devices, videos recorded by drones, safety sensors, building information modeling (BIM), etc. have become a wealth of information. Construction professionals and their clients have the opportunity to analyse the information from this data and make use of it through AI and machine learning systems.

Impact for Equatorial Guinea

Hassan Hachem thinks the impact will be very as available sensors that could collect infield data are very scarce.

8. AI for post-construction

Construction managers can use AI long after buildings have been delivered. Building information modelling or BIM stores information about the structure of buildings. AI can be used to track ongoing problems and even propose solutions to avoid them.

Impact for Equatorial Guinea

Hassan Hachem thinks the impact will be very limited as demand for post construction monitoring does not really exists in Equatorial Guinea.

9. AI will solve the labour shortage

Labour shortages and the desire to increase the sector's low productivity are driving construction companies to invest in AI and data science. A report by McKinsey in 2017 indicated that construction companies could increase productivity by at least 50% through real-time data analysis. Construction companies are beginning to use AI and machine learning to better plan the allocation of labour and machinery across projects. A robot that continuously assesses the progress of a project and the location of workers and equipment allows project managers to know instantly which sites have enough workers and equipment to be completed on time and which are behind schedule and would need additional labour. According to experts, robots in the construction sector are becoming increasingly intelligent and autonomous thanks to AI techniques.

Impact for Equatorial Guinea

Hassan Hachem thinks the impact will be huge as low qualification labour is abundant in Equatorial Guinea, but qualified labour is hard to find.

10. Off-site construction

Construction companies are increasingly relying on off-site factories equipped with autonomous robots that assemble building components, which are then used by workers on the construction site. Some structures, such as walls, can be built by autonomous machines more efficiently than by humans, who can then focus on more specialized tasks such as plumbing, HVAC or electrical systems once the structure is assembled. Regardin the future of AI in construction, Hassan Hachem from Equatorial Guinea insists that Robotics, AI and connected objects have the potential to reduce construction costs by up to 20%. For example, engineers can equip themselves with virtual reality goggles and send mini-robots into buildings under construction to monitor progress with cameras. AI is used to plan electrical and plumbing networks in new buildings and to develop safety systems for construction sites. It tracks the interactions of workers, machinery and objects on construction sites in real time and alerts managers to potential hazards, construction errors and productivity problems. Despite the significant job losses expected, AI is unlikely to replace the human workforce. Rather, it will change the business models of the construction industry, reduce costly mistakes, reduce the number of accidents on construction sites and make work more efficient. Construction industry leaders should prioritise investing in areas where AI can have the greatest impact on their specific business needs. The early movers will set the direction of the industry and benefit from both short and long term innovations.

Impact for Equatorial Guinea

Hassan Hachem thinks the impact will be limited to the construction of very standard building of low or intermediate quality

Finally, in response to the question about AI in construction in Africa, which seems to be lagging far behind in this area, particularly in countries that Hassan Hachem knows well such as Equatorial Guinea, he replied: Chinese construction companies, and in particular the leading Chinese construction company, the China State Construction and Engineering Corporation, have been multiplying their contracts in Africa in recent years. These companies, often at the cutting edge of technology, are increasingly using AI in their processes and will eventually train young African managers and engineers in the years to come. For example, recently, as part of the cooperation between Equatorial Guinea and Beijing, some fifteen Chinese companies are going to build some 10,000 social housing units and 2,000 km of road in the country. For specialists, this is not a surprise. Two Chinese companies are already building roads on the mainland, the largest and most populated part of the country, while another is building the future headquarters of the national radio and television station (RTVGE) in Malabo, on Bioko Island.

More articles

Self sufficient homes

Construction industry and artificial intelligence in Equatorial Guinea