Dec
08
2018
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Why you need a supercomputer to build a house

When the hell did building a house become so complicated?

Don’t let the folks on HGTV fool you. The process of building a home nowadays is incredibly painful. Just applying for the necessary permits can be a soul-crushing undertaking that’ll have you running around the city, filling out useless forms, and waiting in motionless lines under fluorescent lights at City Hall wondering whether you should have just moved back in with your parents.

Consider this an ongoing discussion about Urban Tech, its intersection with regulation, issues of public service, and other complexities that people have full PHDs on. I’m just a bitter, born-and-bred New Yorker trying to figure out why I’ve been stuck in between subway stops for the last 15 minutes, so please reach out with your take on any of these thoughts: @Arman.Tabatabai@techcrunch.com.

And to actually get approval for those permits, your future home will have to satisfy a set of conditions that is a factorial of complex and conflicting federal, state and city building codes, separate sets of fire and energy requirements, and quasi-legal construction standards set by various independent agencies.

It wasn’t always this hard – remember when you’d hear people say “my grandparents built this house with their bare hands?” These proliferating rules have been among the main causes of the rapidly rising cost of housing in America and other developed nations. The good news is that a new generation of startups is identifying and simplifying these thickets of rules, and the future of housing may be determined as much by machine learning as woodworking.

When directions become deterrents

Photo by Bill Oxford via Getty Images

Cities once solely created the building codes that dictate the requirements for almost every aspect of a building’s design, and they structured those guidelines based on local terrain, climates and risks. Over time, townships, states, federally-recognized organizations and independent groups that sprouted from the insurance industry further created their own “model” building codes.

The complexity starts here. The federal codes and independent agency standards are optional for states, who have their own codes which are optional for cities, who have their own codes that are often inconsistent with the state’s and are optional for individual townships. Thus, local building codes are these ever-changing and constantly-swelling mutant books made up of whichever aspects of these different codes local governments choose to mix together. For instance, New York City’s building code is made up of five sections, 76 chapters and 35 appendices, alongside a separate set of 67 updates (The 2014 edition is available as a book for $155, and it makes a great gift for someone you never want to talk to again).

In short: what a shit show.

Because of the hyper-localized and overlapping nature of building codes, a home in one location can be subject to a completely different set of requirements than one elsewhere. So it’s really freaking difficult to even understand what you’re allowed to build, the conditions you need to satisfy, and how to best meet those conditions.

There are certain levels of complexity in housing codes that are hard to avoid. The structural integrity of a home is dependent on everything from walls to erosion and wind-flow. There are countless types of material and technology used in buildings, all of which are constantly evolving.

Thus, each thousand-page codebook from the various federal, state, city, township and independent agencies – all dictating interconnecting, location and structure-dependent needs – lead to an incredibly expansive decision tree that requires an endless set of simulations to fully understand all the options you have to reach compliance, and their respective cost-effectiveness and efficiency.

So homebuilders are often forced to turn to costly consultants or settle on designs that satisfy code but aren’t cost-efficient. And if construction issues cause you to fall short of the outcomes you expected, you could face hefty fines, delays or gigantic cost overruns from redesigns and rebuilds. All these costs flow through the lifecycle of a building, ultimately impacting affordability and access for homeowners and renters.

Startups are helping people crack the code

Photo by Caiaimage/Rafal Rodzoch via Getty Images

Strap on your hard hat – there may be hope for your dream home after all.

The friction, inefficiencies, and pure agony caused by our increasingly convoluted building codes have given rise to a growing set of companies that are helping people make sense of the home-building process by incorporating regulations directly into their software.

Using machine learning, their platforms run advanced scenario-analysis around interweaving building codes and inter-dependent structural variables, allowing users to create compliant designs and regulatory-informed decisions without having to ever encounter the regulations themselves.

For example, the prefab housing startup Cover is helping people figure out what kind of backyard homes they can design and build on their properties based on local zoning and permitting regulations.

Some startups are trying to provide similar services to developers of larger scale buildings as well. Just this past week, I covered the seed round for a startup called Cove.Tool, which analyzes local building energy codes – based on location and project-level characteristics specified by the developer – and spits out the most cost-effective and energy-efficient resource mix that can be built to hit local energy requirements.

And startups aren’t just simplifying the regulatory pains of the housing process through building codes. Envelope is helping developers make sense of our equally tortuous zoning codes, while Cover and companies like Camino are helping steer home and business-owners through arduous and analog permitting processes.

Look, I’m not saying codes are bad. In fact, I think building codes are good and necessary – no one wants to live in a home that might cave in on itself the next time it snows. But I still can’t help but ask myself why the hell does it take AI to figure out how to build a house? Why do we have building codes that take a supercomputer to figure out?

Ultimately, it would probably help to have more standardized building codes that we actually clean-up from time-to-time. More regional standardization would greatly reduce the number of conditional branches that exist. And if there was one set of accepted overarching codes that could still set precise requirements for all components of a building, there would still only be one path of regulations to follow, greatly reducing the knowledge and analysis necessary to efficiently build a home.

But housing’s inherent ties to geography make standardization unlikely. Each region has different land conditions, climates, priorities and political motivations that cause governments to want their own set of rules.

Instead, governments seem to be fine with sidestepping the issues caused by hyper-regional building codes and leaving it up to startups to help people wade through the ridiculousness that paves the home-building process, in the same way Concur aids employee with infuriating corporate expensing policies.

For now, we can count on startups that are unlocking value and making housing more accessible, simpler and cheaper just by making the rules easier to understand. And maybe one day my grandkids can tell their friends how their grandpa built his house with his own supercomputer.

And lastly, some reading while in transit:

Dec
04
2018
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Cove.Tool wants to solve climate change one efficient building at a time

As the fight against climate change heats up, Cove.Tool is looking to help tackle carbon emissions one building at a time.

The Atlanta-based startup provides an automated big-data platform that helps architects, engineers and contractors identify the most cost-effective ways to make buildings compliant with energy efficiency requirements. After raising an initial round earlier this year, the company completed the final close of a $750,000 seed round. Since the initial announcement of the round earlier this month, Urban Us, the early-stage fund focused on companies transforming city life, has joined the syndicate comprised of Tech Square Labs and Knoll Ventures.

Helping firms navigate a growing suite of energy standards and options

Cove.Tool software allows building designers and managers to plug in a variety of building conditions, energy options, and zoning specifications to get to the most cost-effective method of hitting building energy efficiency requirements (Cove.Tool Press Image / Cove.Tool / https://covetool.com).

In the US, the buildings we live and work in contribute more carbon emissions than any other sector. Governments across the country are now looking to improve energy consumption habits by implementing new building codes that set higher energy efficiency requirements for buildings. 

However, figuring out the best ways to meet changing energy standards has become an increasingly difficult task for designers. For one, buildings are subject to differing federal, state and city codes that are all frequently updated and overlaid on one another. Therefore, the specific efficiency requirements for a building can be hard to understand, geographically unique and immensely variable from project to project.

Architects, engineers and contractors also have more options for managing energy consumption than ever before – equipped with tools like connected devices, real-time energy-management software and more-affordable renewable energy resources. And the effectiveness and cost of each resource are also impacted by variables distinct to each project and each location, such as local conditions, resource placement, and factors as specific as the amount of shade a building sees.

With designers and contractors facing countless resource combinations and weightings, Cove.Tool looks to make it easier to identify and implement the most cost-effective and efficient resource bundles that can be used to hit a building’s energy efficiency requirements.

Cove.Tool users begin by specifying a variety of project-specific inputs, which can include a vast amount of extremely granular detail around a building’s use, location, dimensions or otherwise. The software runs the inputs through a set of parametric energy models before spitting out the optimal resource combination under the set parameters.

For example, if a project is located on a site with heavy wind flow in a cold city, the platform might tell you to increase window size and spend on energy efficient wall installations, while reducing spending on HVAC systems. Along with its recommendations, Cove.Tool provides in-depth but fairly easy-to-understand graphical analyses that illustrate various aspects of a building’s energy performance under different scenarios and sensitivities.

Cove.Tool users can input granular project-specifics, such as shading from particular beams and facades, to get precise analyses around a building’s energy performance under different scenarios and sensitivities.

Democratizing building energy modeling

Traditionally, the design process for a building’s energy system can be quite painful for architecture and engineering firms.

An architect would send initial building designs to engineers, who then test out a variety of energy system scenarios over the course a few weeks. By the time the engineers are able to come back with an analysis, the architects have often made significant design changes, which then gets sent back to the engineers, forcing the energy plan to constantly be 1-to-3 months behind the rest of the building. This process can not only lead to less-efficient and more-expensive energy infrastructure, but the hectic back-and-forth can lead to longer project timelines, unexpected construction issues, delays and budget overruns.

Cove.Tool effectively looks to automate the process of “energy modeling.” The energy modeling looks to ease the pains of energy design in the same ways Building Information Modeling (BIM) has transformed architectural design and construction. Just as BIM creates predictive digital simulations that test all the design attributes of a project, energy modeling uses building specs, environmental conditions, and various other parameters to simulate a building’s energy efficiency, costs and footprint.

By using energy modeling, developers can optimize the design of the building’s energy system, adjust plans in real-time, and more effectively manage the construction of a building’s energy infrastructure. However, the expertise needed for energy modeling falls outside the comfort zones of many firms, who often have to outsource the task to expensive consultants.

The frustrations of energy system design and the complexities of energy modeling are ones the Cove.Tool team knows well. Patrick Chopson and Sandeep Ajuha, two of the company’s three co-founders, are former architects that worked as energy modeling consultants when they first began building out the Cove.Tool software.

After seeing their clients’ initial excitement over the ability to quickly analyze millions of combinations and instantly identify the ones that produce cost and energy savings, Patrick and Sandeep teamed up with CTO Daniel Chopson and focused full-time on building out a comprehensive automated solution that would allow firms to run energy modeling analysis without costly consultants, more quickly, and through an interface that would be easy enough for an architectural intern to use.

So far there seems to be serious demand for the product, with the company already boasting an impressive roster of customers that includes several of the country’s largest architecture firms, such as HGA, HKS and Cooper Carry. And the platform has delivered compelling results – for example, one residential developer was able to identify energy solutions that cost $2 million less than the building’s original model. With the funds from its seed round, Cove.Tool plans further enhance its sales effort while continuing to develop additional features for the platform.

Changing decision-making and fighting climate change

The value proposition Cove.Tool hopes to offer is clear – the company wants to make it easier, faster and cheaper for firms to use innovative design processes that help identify the most cost-effective and energy-efficient solutions for their buildings, all while reducing the risks of redesign, delay and budget overruns.

Longer-term, the company hopes that it can help the building industry move towards more innovative project processes and more informed decision-making while making a serious dent in the fight against emissions.

“We want to change the way decisions are made. We want decisions to move away from being just intuition to become more data-driven.” The co-founders told TechCrunch.

“Ultimately we want to help stop climate change one building at a time. Stopping climate change is such a huge undertaking but if we can change the behavior of buildings it can be a bit easier. Architects and engineers are working hard but they need help and we need to change.”

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