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Construction & Engineering


How artificial intelligence (AI) will help Autodesk expand in the metaverse

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We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. For the 40-year-old Autodesk -- known for its design and creation software (including AutoCAD) used by professionals in industries including architecture, engineering, construction, manufacturing and entertainment -- artificial intelligence (AI) has become a must to help boost creativity and collaboration. "A common theme is helping the designer," said Tonya Custis, director of artificial intelligence research at Autodesk, whose team includes 15 AI research scientists based in San Francisco, Toronto and London. But AI will also help Autodesk expand in the metaverse. According to Custis, Autodesk's use of AI is also helping to tackle challenges around "geometry understanding" -- to help contextualize the geometric world around us -- which will be "super-important" as the metaverse expands, in terms of speeding up animation and CGI processes, as well as in architecture and engineering.


StackPath

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Top 5 Data Driven Design news this week.

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Welcome to the Association of Data-Driven Design roundup. We aim to share a summary of current information and news on Data-Driven Design practices within the construction industry. Please get in touch if you have any ideas, suggestions or have something to share. Cobe uses Spacemaker's AI software to future-proof its designs. Artificial Intelligence in Urban Planning and Design book looks worth a read.


Wall Painting Robot saves thousands of painters' lives

#artificialintelligence

According to American construction safety statistics, about 20% of worker deaths in the United States occur in the construction industry, but construction workers only account for 6% of the American workforce. For the fatal construction industry statistics, one-fifth of the deaths of American workers occurred in the construction industry. As for the Non-Fatal Construction Injuries, The construction industry accounts for 6% of all injuries that result in lost days of work. As a result, it is estimated that fatal construction injuries cost the United States $ 5 billion every year in terms of medical care, lost income, reduced quality of life for family members and lost production. The total cost of workplace injury exceeds $ 170 billion per year.[NSC] Workers' compensation claims for nonfatal falls account for $2.5 billion annually.


Automation is not enough: Buildings need AI-powered smarts

#artificialintelligence

We are excited to bring Transform 2022 back in-person July 19 and virtually July 20 - 28. Join AI and data leaders for insightful talks and exciting networking opportunities. Buildings have been one of the most voracious users of IoT devices. Smart buildings, in particular, use connected devices to measure everything from temperature, lighting, air quality, noise, vibration, occupancy levels and energy consumption -- and that's just the very tip of the iceberg. Building automation is big and getting bigger, with well over 6 million commercial buildings in the U.S. alone and an estimated 2.2 billion connected devices deployed. The global market for building automation systems in 2022 will reach about $80 billion.


Machine learning in concrete science: applications, challenges, and best practices - npj Computational Materials

#artificialintelligence

Concrete, as the most widely used construction material, is inextricably connected with human development. Despite conceptual and methodological progress in concrete science, concrete formulation for target properties remains a challenging task due to the ever-increasing complexity of cementitious systems. With the ability to tackle complex tasks autonomously, machine learning (ML) has demonstrated its transformative potential in concrete research. Given the rapid adoption of ML for concrete mixture design, there is a need to understand methodological limitations and formulate best practices in this emerging computational field. Here, we review the areas in which ML has positively impacted concrete science, followed by a comprehensive discussion of the implementation, application, and interpretation of ML algorithms. We conclude by outlining future directions for the concrete community to fully exploit the capabilities of ML models.


AI in Construction - How Artificial Intelligence is Paving the Way for Smart Construction

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Artificial Intelligence has definitely made our lives easier in multiple ways. We can access multiple benefits right through our smartphones with the power of digital assistants like Google Assistant, Siri, Alexa, and more. In today's world, multiple industries such as healthcare, e-commerce, financial services, etc., are leveraging the benefits of AI to the fullest of its potential. The technology has helped businesses grow in leaps and bounds with improved quality, security, and efficiency. However, it is observed that engineering and construction are lagging behind in implementing artificial intelligence and machine learning solutions.


Extreme sports move over: Hardhat cameras coming to the job site

ZDNet

Greg Nichols covers robotics, AI, and AR/VR for ZDNet. A full-time journalist and author, he writes about tech, travel, crime, and the economy for global media outlets and reports from across the U. A company that uses construction workers as roving cameramen to analyze progress on the job site has secured $60 million in Series C funding. Buildots, whose growth is tracking a broader technological turn in the practically neolithic construction sector, will use the cash to expand its product offering in a bid to be the management suite of choice for construction oversight. Construction accounts for 13% of the world's GDP, but while other traditional industries, like manufacturing, have increased productivity over the years, productivity has remained almost stagnant in the building sector.


Multi-task Learning for Concurrent Prediction of Thermal Comfort, Sensation, and Preference

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Therefore, researchers and engineers have proposed numerous computational models to estimate thermal comfort (TC). Given the impetus toward energy efficiency, the current focus is on data-driven TC prediction solutions that leverage state-of-the-art machine learning (ML) algorithms. However, an indoor occupant's perception of indoor thermal comfort (TC) is subjective and multi-dimensional. Different aspects of TC are represented by various standard metrics/scales viz., thermal sensation (TSV), thermal comfort (TCV), and thermal preference (TPV). The current ML-based TC prediction solutions adopt the Single-task Learning approach, i.e., one prediction model per metric. Consequently, solutions often focus on only one TC metric.


The robot landscapers that 3D printed a park in China

Mashable

Developed by AICT (Advanced Intelligent Construction Technology), this 5,500-square-meter park is a testament to the massive impact 3D printing has had in the construction industry. The park is located in Shenzhen, China and looks like an attempt to blur the lines between nature and cement into a oasis-like hybrid.