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Why New Daedalus?

Daedalus was the mythical great architect and artificer of the classical world. Today, embedded intelligence is enabling the most profound changes in the way we create and use buildings since his day.

Building Intelligence meets the Intelligent Building. The Intelligent Building negotiates with the Intelligent Grid. How will this transform how we interact with the physical world?

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Abstract the Interfaces

If we are going to build very large systems, we will need to break it into self managing units, and build systems of systems. There is too much complexity and variability to establish any type of top-down order on embedded systems. Even if we could define the “optimum system”, we could still not use it for something as large as the power grid.

Suppose we did. Suppose we picked a technology and said “This is what each building shall have!” In 20 years we would still be trying to get all systems upgraded – and we would be mandating 20 year old technology. We simply cannot make rigid decisions for anything so large, so extended, and maintained by so many people.

We can only manage such a large scale by hiding complexity. We must hide complexity by defining certain simple big picture interactions that encompass all the little decisions. We will never get support for central coordination if by doing so, we remove personal control from systems. To define these simple actions, we need to reach for commonly agreed upon semantics to describe the operations we want systems to follow.

I want to place Intelligent Buildings as fully actualized agents on an Intelligent Grid. To do that, I hope to leverage the Building Information Model (NBIMS) to discover abstract interfaces to the point-by-point complexity of the underlying control systems. Rather than create these abstract interfaces from scratch, I hope that the pre-existing interfaces between the Building Model and Energy Models could be a good starting point. I want to avoid the complexity of introducing Yet Another Acronym and Yet Another Interface, and thereby avoid increasing complexity.

Abstract interfaces that hide rather than reveal complexity are the key. Here is an example from within oBIX discussions. When we discussed abstract interfaces for scheduling, each control system developer quickly claimed that “scheduling systems algorithms are quite complex, and there nearly impossible to align.” Spirited discussions ensued about factoring how long it takes to air condition a room in advance. Should we factor in humidity. and on. and on.

But there is already a standard for scheduling. We each receive ICAL invitations to meetings scheduled on the internet. ICAL is a W3 specification, meaning it is defined by the same folks who define how we display web pages. Our personal systems know how to adjust for where we are in the world, including such local oddities as when Daylight Savings Time begins. Each of us considers whether we have to drive to the meeting, or fly, or simply be near a phone. Those details are not the concern of the interface but of each participant and of the complex systems we represent. I want to simply invite the conference room or class room to an event on a certain date, with a certain number of attendees anticipated.

If these questions are answered correctly, they expand the value of capital assets by extending their ability to provide services and amenities to the owners and tenants, not merely to avoid costs. An Energy Model consists of Envelope, Weather, and System Operations. An abstract interface that works for energy modeling could be re-usable in tuning System Operations in response to Weather Predictions to improve quality of service provided. It becomes the basis for external system analytics to enable predictive maintenance and thereby economically provide enhanced reliability.

Abstract interfaces are the first step to defining services. Services are the key to continental-scale integration. Services allow for internal intelligence to support local imperatives. We can call that local intelligence an Agent. Agents are the key to large scale interaction, because they can assume responsibility for local operating details. Semantics are important, because we must have some common vocabulary to communicate with the local agents.

It almost goes without saying that any agent would be offended if you tried to communicate past its semantic surface. Even your kids will get in trouble if, instead of asking for money on a Saturday night, or perhaps even volunteering for chores, they reach directly right into your wallet. The surfaces of services must be inviolate.

And that is how we will handle the complexity of integrating a continental-scale power grid with its end nodes.

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