Construction & Engineering



Why Siemens is putting AI in charge of its revamped content strategy

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Siemens wants to turn its digital communications platform into one that's as important to consumers as Facebook, and it's starting by getting artificial intelligence to tell its internal authors what to write about. The tech conglomerate believes the sheer scale of its work (which is carried out by more than 350,000 employees worldwide) makes for stories that will interest people outside of the company. However the two heads of its communications department – both less than two years into their respective jobs – are aware that the brand has been historically ineffective at telling these stories, largely due to its distrust in non-traditional media. "We liked to touch things and talk about things – traditional media events were where we bought our a-game," said Stephanie Chalmers, global head of content and newsroom at Siemens. "I had to explain that [non-traditional] channels are way more effective than the ones they were used to.


Employing machine learning to create wear and corrosion resistant metallic glass

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If you combine two or three metals together, you will get an alloy that usually looks and acts like a metal, with its atoms arranged in rigid geometric patterns. But once in a while, under just the right conditions, you get something entirely new: a futuristic alloy called metallic glass. The amorphous material's atoms are arranged every which way, much like the atoms of the glass in a window. Its glassy nature makes it stronger and lighter than today's best steel, and it stands up better to corrosion and wear. Although metallic glass shows a lot of promise as a protective coating and alternative to steel, only a few thousand of the millions of possible combinations of ingredients have been evaluated over the past 50 years, and only a handful developed to the point that they may become useful.


Ambi Climate 2 review: An intelligent alternative for controlling a room air conditioner

PCWorld

Cloud-connected controllers for room air conditioners aren't a new thing, we've previously evaluated devices from Tado and Sensibo. But the Ambi Climate 2 is a cut above those, with a Nest Thermostat-like learning feature that adapts to your expressed preferences. This second-edition Ambi Climate is more ambitious than the original, and it requires that you have an air conditioner that uses a remote control with an LCD display. This isn't the first controller I've encountered with this restriction, but I've sometimes been able to get around it with other models. If your unit doesn't have that feature, the Ambi Climate 2 simply won't work (for now, at least).


Tech Report 5.0: AI Arrives

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Using artificial intelligence (AI) to apply machine learning to planning and constructing buildings is still a theoretical proposition for many AEC firms. But in recent years, as data storage and computational power have expanded, more firms are willing to engage AI as a practical analytics tool. Their ultimate goal for using this platform seems clear: to generate predictive data that provides early hints about future trends and behaviors on everything from interior designs to jobsite safety. For example, co-working real estate giant WeWork is using AI-driven machine learning to forecast how prospective occupants might use co-working and shared spaces, and to assist its design partners in making more optimal choices. These analyses draw data from the company's 200-plus locations worldwide.


AI in construction: What does it mean for the industry? Planning & Building Control Today

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Automated technologies are making their way into the construction industry. As the demand for new buildings reaches an all-time high, construction firms are looking for ways to streamline their projects. The rise of Artificial Intelligence and machine learning technologies make this easier every day. Although the fear of robots taking over is inevitable, there are positive aspects. Upon first glance, these benefits may seem to matter only to GCs or owner-operators, but the benefits reach other construction professions.



Siemens simulation offering hastens the arrival of self-driving cars

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Leveraging advanced, physics-based simulation and innovative sensor data processing technologies, the new Siemens solution is designed to help automakers and their suppliers address this industry challenge with the potential to shave years off the development, verification and validation of self-driving cars. TASS' PreScan simulation environment produces highly realistic, physics-based simulated raw sensor data for an unlimited number of potential driving scenarios, traffic situations and other parameters. The data from PreScan's simulated LiDAR, radar and camera sensors is then fed into Mentor's DRS360 platform, where it is fused in real time to create a high-resolution model of the vehicle's environment and driving conditions. Customers can then leverage the DRS360 platform's superior perception resolution and high-performance processing to test and refine proprietary algorithms for critical tasks such as object recognition, driving policy and more. "Automakers are quickly realizing that physical prototypes and road testing alone cannot reproduce the multitude of complex driving scenarios self-driving cars will encounter.


Robots break new ground in construction industry

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As a teenager working for his dad's construction business, Noah Ready-Campbell dreamed that robots could take over the dirty, tedious parts of his job, such as digging and leveling soil for building projects. Now the former Google engineer is turning that dream into a reality with Built Robotics, a startup that's developing technology to allow bulldozers, excavators and other construction vehicles to operate themselves. "The idea behind Built Robotics is to use automation technology make construction safer, faster and cheaper," said Ready-Campbell, standing in a dirt lot where a small bulldozer moved mounds of earth without a human operator. The San Francisco startup is part of a wave of automation that's transforming the construction industry, which has lagged behind other sectors in technological innovation. Backed by venture capital, tech startups are developing robots, drones, software and other technologies to help the construction industry to boost speed, safety and productivity.


Machine Learning for Construction Safety: A Construction Project Manager's Perspective

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This presentation will review how 360º photography is rapidly changing the way DPR Construction documents both existing conditions and ongoing progress on job sites. We will discuss new workflows related to progress documentation and its benefits. For example, we'll cover scheduling of documentation on a weekly and/or milestone basis to enable virtual quality assurance/quality control walks with architects, engineers, and inspectors. We'll also review workflows for capturing conversations that revolve around actual project locations to assist with radio frequency interference (RFI) creation. We will discuss use for risk mitigation, including documenting existing conditions for design planning/bidding, as well as capture of MEP (mechanical, electrical, and plumbing) rough-in before dry-wall and ceiling close up.