Written by: AI & Architecture

Construction Project Risks Management With AI and ML

Construction is huge and risky. Every construction project is different from the other and needs to be approached differently because of the dangers associated with it. Managing and identifying these risks can be dubious, but not impossible with the rise of technology that is AI and ML. Any mistake when construction is taking place can disrupt and derail the whole project.

There is a history of buildings that were brought down due to a single mistake made during construction. For example In East London, on May 16, 1968, a match stick set off the breakdown of a huge 22-story building. Ivy Hodge, a 56-year-old living on the eighteenth floor, rose and tried to lit her stove, the flash from the match set off an overwhelming gas blast. Many floors collapsed to the ground.

The structure was, in reality, new, its development finished only five days preceding the breakdown. Shockingly, just four residents died in the calamity, while 17 were hurt. Even though the structure was remade and the joints fortified, many couldn’t trust the building.

In order

To identify and manage dangers, one needs to the various type of risks associated with these projects of the construction industry. They can be environmental, contractual, operational, or financial. They can also be either internal or external factors. They include:

  1. Fluctuating material cost. This may lead to contractors using less or low-quality materials.
  2. Unskilled labor. Having unskilled workers on the site can lead to poor decisions.
  3. Risky site conditions. This may make construction to take place on a groud that is not firm and can be affected by earthquakes.
  4. Accidents and injuries can be caused by safety hazards.
  5. Incomplete and poor implementation of defined scope and structure designs.
  6. Corruption and theft in construction sites.
  7. Mismanagement of construction projects.
  8. Construction managers don’t have real-time feedback on progress and quality, unlike their manufacturing counterparts. This makes it hard for them to measure how much work can be completed or if it is being done according to the book.
  9. Labour productivity in the construction industry hardly changes.

These demerits come to fruition and they can affect cost, performance, and schedules which may lead to conflict and delays of the project down the road. Fortunately with technology, proper planning, and good project management its very easy to overcome these challenges and risks.

Doxel is a robot that combines artificial intelligence and machine learning to prevent this from happening. It uses AI technology and computer vision system to give managers real-time feedback on quality schedules, and budget. It is a manufacturing control room for the construction industry.

How does the technology behind it work? Doxel has HD cameras and LIDAR which helps the autonomous devices to scan every corner of the construction site.

The Doxel exclusive AI algorithm forms the visual data, assesses the quality, and measures how much material has been used accurately.

The merit of Doxel technology.

Autonomous AI-based technology. Many technologies out there only captures data on 3D design and leaving the rest to workers on the site to implement the rest. This makes managers keep patrolling the sites trying to fix everything and keeping all plans on track.

Doxel is an AI breakthrough system that uses utilizes visualized captured data to control, inspect quantities and qualities. This game-changer AI robot solution gives real-time quality reports and accurate progress of the construction process.

When it comes to measuring the project budget and schedule, the software gives updates with high accuracy and progress.

The startup is facing early challenges because computer vision algorithms are affected by high-intensity lighting, density and cluttering components. Visibility, occlusion and scattered building materials affect the software negatively. This made the inventors switch from 2d computer vision techniques which requires a lot of datasets to 3d which utilizes fewer datasets for training.

The invention is phenomenally working magically well. Saurabh Ladha the founder of Doxel is proud of his successful and great ending. He has helped in the invention that will tackle challenges that construction face.