Artificial Intelligence in Construction Part II: Image Recognition and Sensors-on-Site
In this article, we continue our series on artificial intelligence (AI) in construction. Here we address image recognition and sensors-on-site. This technology uses cameras and other sensors to assess vast quantities of video, pictures, and other recorded conditions from worksites. Such technology has the potential to: (1) monitor worksite conditions for safety risks and hazards; (2) enhance equipment and material management, boosting productivity; and (3) improve worker safety by identifying unsafe behavior to inform future training priorities.
Firms can leverage machine-learning techniques with image recognition programs to keep workplaces accident free and increase work efficiency. For example, Suffolk, a Boston-based general contractor with about $4 billion in annual revenue, is already developing predictive algorithms to monitor safety risks. Suffolk collected over 700,000 images, taken from over 360 job sites in the last 10 years, and uploaded them to startup Smartvid.io’s cloud-based platform. The algorithm analyzed the images to identify safety hazards, like workers not wearing proper protective equipment. Suffolk plans to expand the algorithm also to identify tripping hazards from tools and equipment lying around on sites. The algorithm will then compare the images scanned with Suffolk’s accident records to inform future training opportunities.
Suffolk is also exploring ways to use sensors-on-site and the internet of things to improve work efficiency. The advantage of having real-time data from connected devices is that workers can easily locate equipment on the job site and contractors can track materials from suppliers. Workers will not only find the tools and equipment they need on site faster, but more importantly, they will also know whether the tools are currently in use. Contractors will be able to track the location and arrival of important materials like concrete supply trucks en route to job sites. Knowing where available tools are and exactly when critical materials will arrive can reduce downtime and increase productivity through better planning and resource allocation.
In the future, image recognition and sensor-on-site technology coupled with machine-learning techniques could also be applied to assess issues with quality control. By analyzing real-time data from sites, engineers can potentially detect defects in design. Catching project design deviations earlier creates a better opportunity to rectify them and limit any associated costs. With frequent monitoring, engineers may be able to detect the potential for critical failures or events with enough warning to limit, or even prevent, the occurrence. This can be applied not only to structures, but also heavy machinery.
A 2017 McKinsey report estimated that construction firms could increase productivity by as much as 50% through real-time analysis of data. The desire to capitalize on this opportunity to boost the industry’s generally low productivity is compelling construction firms to invest in AI. As construction companies incorporate more AI and machine learning into their business and worksites, new legal concerns associated with this implementation will arise. Some unanswered legal questions are the allocation of risk, responsibility for malfunctions and resultant damages, and the confidentiality and privacy of the data.
A primary concern for construction industry stakeholders will be what new duties and responsibilities will accrue to those who implement and use such technology. With the potential to identify safety hazards or unsafe working conditions, an open question arises: Who has the duty to observe or monitor the information? How closely and actively must sensors be monitored? Will there be a duty to act upon identified risks, or merely a duty to disclose? Will using this technology contribute to a party’s constructive knowledge regarding unsafe conditions that result in injuries or potential failures to meet contractual obligations? When something does fail, who will be responsible for repairs or the costs? How will the data be stored, who has access to it, and how will privacy and confidentiality be secured? In summary, contractors may unknowingly be opening themselves up to additional risks, liability, and greater responsibility with the information this technology provides. While most of these questions can be addressed through careful contractual drafting, stakeholders will have to think through these questions and possibilities. To reach acceptable risk allocation as AI usage in construction increases, parties should be prepared to negotiate these terms in any agreement very carefully.
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