Big Data and Energy Dashboards.

To Recap: All devices have energy dashboards, The assumption is that the device is in a constant error state while the dashboard represents the optimum operational state. Of course the dashboard could malfunction, but for the sake of this study let us assume it does not. The word device must be defined. it is any entity that consumes energy for the purposes of this research topic. The scope of devices therefore would include, automobiles, household appliances, human beings, animals just to name a few. We will fit these use cases in our research as we progress.

My initial direction was to establish standards for interoperability of energy dashboards. The assumption was that dashboards and devices had to interoperate, so do dashboards and sources of information and interoperability standards would therefore also govern the algorithms that adductively establish what the delta between the dashboard and the device is at any given moment. Further the interoperability standards would establish methods to reduce the error and at the same time develop standards of what the acceptable error would be. Finally since he standards should possess the capability to self moderate or self regulate or even change as it learns.

My initial direction was not explicit about the body of research that has gone into machine learning, semantic web and big data particularly since the year 2000. Google’s approach to indexing the web of billions of documents and Tim Berners Lee’s Semantic web of abductive reasoning came around the same time, however it was only 5 or 6 years later that Doug Cutting and Yahoo opensourced hadoop and mapreduce. Doug/Yahoo’s contribution was a key milestone as it made it possible for parallel computations on embarrassingly large datasets available for collaborative development.

Standards of interoperability for energy dashboards are perfect candidates for embassingly large parallel computational challenges. Assuming that all data is on the web and will be accessible, one can see how a dashboard can establish the size of the error between the device and itself and take action to self correct or alert. it is no more than taking what we do today, to the next step. Let us take a use case of device = Human being today. If we assume the error condition is a stain on white shirt. The device does a search, on google, or any other search engine, assimilates the necessary information on how to correct the error or reduce the error and proceeds with the action.

In the use case above Instructions would be the class, “Removal of”, “Stains”, “from white shirt” would be the features. Once the page rank algorithm generates the highest ranking instructions, the user acts upon it by scanning through the highest page ranks, and acting out the instructions.

if our use case = Refridgerator and let us assume the error condition is that the light bulb does not go out when the door is closed, The Refridgerator could follow a similar model as above. The classifier model still work’s the correction of the error condition might require a trigger to a supply/chain process.

From both use cases, we see Big Data and Energy Dashboards will play a large role in the future of automation and Dashboards for a greener built environment.

Iteration and vocabulary

I have to constantly keep reminding myself about: Standards for Interoperability of Energy dashboards. The key words, Standards and Interoperability are self explanatory. In a society that sells products based on differentiation, interoperability and standards certainly have a place.

Energy Dashboards on the other hand are not so self explanatory.  A simple mathematical model defines the relationship between Energy Dashboards, Standards and Interoperability:
if z=interoperability, x=energy, y=dashboards, interoperability can all be solved for using the z=f(x,y) model.

Every device aka energy source has an energy dashboard. Yes even you. The difference between the device and the dashboard is the error. Error defined as difference between what should be. & what should not be. All devices are assumed to be in a state of error and the dashboard is its perfect state.

Interoperability standards for energy dashboards should limit the error to an acceptable limit and then improve on it by learning. Errors can be of various flavors: Absolute and Relative errors, computational and data errors, Truncation and rounding errors, Forward and backward error and finally sensitivity and conditioning.

Device interaction propagates these errors. The dashboard has to influence the device to limit the error condition to an acceptable limit. The relationship between the dashboard and the device is a state of balance maintained by the tensile strength of the dashboard that is a model of the device in a perfect state and the device in a state of error.

A device could be in a state of error without interacting with other devices. This state is mostly driven by misconfiguration, that the dashboard can easily influence and correct. For the purposes of this study, two primary models will be explored.

1) Device/energy source with zero interaction with other device/energy source
2) Device/energy source with constant interaction with other devices/energy sources

Dashboards for a Greener built environment – moving along

Phase I of the “dashboards for a greener built environment” research project proposes to catalog energy dashboards available in the market place today (see list below) and extrapolate implict standards these dashboards are being built to.

Phase II, will focus on establishing a baseline set of standards from which future energy dashboards can be built to. The goal is to provide for interoperability through open standards and a strong base for ease of adoption of these dashboards by the masses.

STANDARDS act as design constraints and outline interoperability between the ecosystem components. An assumption is made that energy conservation can be achieved through adoption of energy dashboards that promote self correction. Dashboards provide a way to measure and optimize usage. The domain for this study therefore is “Energy Conservation” and the range is any device/gadget/appliance or any act that consumes energy.

Components of the ecosystem for “dashboards for a greener built environment”:
a. The built environment at the micro level – individual housing and at the marco level urban and rural environment,
b. Instrumentation – measures and outputs consumption
c. Appliance engineering – Product design
d. Open data repositories of specification based on which these products are designed
e. Governance

Energy sources that are at the center of the energy conservation discussion include but are not limited to:
a. Water
b. Thermal energy
c. Electrical energy
d. Fossil fuels such as oil, coal and natural gas

The energy dashboard market is gaining momentum in the United States, with companies such as google, microsoft, cisco and utility companies making rapid inroads. The smart grid development is gaining traction which is helping drive development of a dashboard driven conservation culture. Now is the time to develop these standards.

1) EnergyHub: EnergyHub makes a high-end energy dashboard that will offer Google Docs-style spreadsheets and graphs of resource use. http://www.energyhub.com/
2) Tendril: Tendril sells a combo of energy management services, including a wireless in-home energy display, a smart thermostat, a web-based energy portal. http://www.tendrilinc.com/
3) Onzo: London-based Onzo makes a slick-looking energy display and wireless sensor kit that runs on energy harvested from the home electrical cable. http://onzo.com/
4) Agilewaves: Agilewaves‘ Resource Monitor tracks and manages energy, gas and water consumption in real time from web-enabled devices. http://www.agilewaves.com/
5) Google PowerMeter: The search-engine giant told us recently that it is trying to bring PowerMeter, its online energy information tool, to market sometime this year. Google is working with device makers — we’ve reported on GE and Tendril — and hoping to launch with a direct-to-consumer product as well as a utility product
6) The Energy Detective: The Energy Detective (or TED) is one of the few energy management tools that’s already available to consumers.
7) PowerMand: Founded in 2006, Portland, Ore.-based PowerMand makes DreamWatts, a wireless energy management tool that focuses on making smart thermostats effective for cutting energy consumption. http://www.powermand.com/dreamwatts-product
8) Green Energy Options: Cambridge, UK-based Green Energy Options‘ home energy monitoring system, called the Home Energy Hub.

2011 a year for Energy Dashboards and rules

This research project aims to develop STANDARDS for energy dashboards that promote conservation. An assumption is made that energy conservation can be achieved through adoption of energy dashboards that promote self correction. Dashboards provide a way to measure and optimize usage. The domain for this study therefore is “energy conservation” and the range is any device/gadget/appliance or any act that consumes energy.

STANDARDS act as design constraints and outline interoperability between components that makeup the ecosystem.

Components of the ecosystem for energy dashboards:
a. The built environment at the micro level – individual housing and at the marco level urban and rural environment,
b. Instrumentation – measures and outputs consumption
c. Appliance engineering – Product design
d. Open data repositories of specification based on which these products are designed
e. Governance

Energy sources that are at the center of the energy conservation discussion include but are not limited to:
a. Water
b. Thermal energy
c. Electrical energy
d. Fossil fuels such as oil, coal and natural gas

The energy dashboard market is gaining momentum in the United States, with companies such as google, microsoft, cisco and utility companies making rapid inroads. The smart grid development is gaining traction which is helping drive development of these widgets.

This research project aims to extrapolate the implicit interoperability standards these widgets are being designed from today. The goal is to use this data as a basis for developing a comprehensive set of standards that will drive interoperability within the components of the ecosystem and drive adoption of energy dashboards with the eventual goal of conserving energy.

Getting back on track with Energy Dashboards for a Greener built Environment – after being consumed for a whole year

This past year I was consumed by setting up an operations team that could be sold. Of course I was part of the sale and now that the deed is done, I am back thinking about Energy Dashboards for a Greener built environment.

Energy Dashboards
Energy Dashboards

To recap my interest in Energy Dashboards: It is a multi-disciplinary approach to develop template(s) for Energy Dashboards. The approach does not develop dashboards, instead it provides a Open common framework to build interoperable and consistent Energy Dashboards in the future. The disciplines include but are not limited to: The built environment [Architecture/Urban planning], Standards [governance], Instrumentation [measurement of energy input/out by appliances or the environment, Electrical Engineering], Data Repositories [CS, Data minining, Numeric analysis] and Sensors and Transmission of Data [CS and Electrical engineering]

As a concrete example of a Dashboard: Consider a wireless sensor buried in each front yard in the community that transmits amount of water sprinkled and the amount of pesticide in the lawn. The sensor transmits this to the wireless mesh of routers, on its way to a data repository. The repository is transparent and can we viewed as part of a social network. Ultimately, the dashboard is the community view of the data repository.

A year later, I have initiated contact with Western Michigan University, to help me realize this idea that I blogged about back in November 2008, December 2009 and then continued to build upon through my software modelling paper at DePaul. This coming fall the focus will be on preping for Numeric Analysis and Data mining, which actually means I will sit in a couple of calculus classes at KVCC and then follow that up with in Spring at WMU as a Guest Student. Come fall of next year if all goes well, I will be part of a multi-disciplinary team driving the initiative to set templates and Standards for Energy Dashboards for a Greener built Environment.

Inter disciplinary approach:

There are 5 major domains that require to be loosely coupled to make the dream of pervasive “Dashboards for a Greener built environment” a reality. They are summed up in the illustration below. In the end we need standards that drive appliance manufactures to provide instrumentation data that is available to the consumers. We need standards that drive creating of Data repositories that store efficiency data that will be freely available to consumers. We need standards for our built environment that makes adoption of energy conservation a reality.

multi disciplinary approach for Energy Dasboards
multi disciplinary approach for Energy Dasboards

gap in AA in flight customer service

Hi Gerard,
My apologies on the typo on Customer Service, I wanted to make a point, and pass this on to you. You most probably are reading this before any of your exec team. Wish you and you team well.

This was authored by:

American Airlines is the inaugural member of my "Corporate Shit List. " http://r2.ly/sqzj

On Fri, Jan 29, 2010 at 7:52 AM, Terry Fernandez <terry.fernandez@gmail.com> wrote:

Good Morning Gerard,
This morning on Twitter Dave Winer (author of RSS and SOAP), put your company on his twitter shit list. I wrote to you in July of 2009. Your team most probably had other important things to take care of other than CUSTOMER SERVERICE

On Fri, Jul 3, 2009 at 6:12 PM, Terry Fernandez <terry.fernandez@gmail.com> wrote:

Gerard,

I recently returned from a memorable trip to Kenya, a once in a life
time trip for most Americans. On my return leg from Brussels to
Chicago, I experienced the worst customer service from in flight
attendants in all my years of travel.

I made some posts about this on twitter and Facebook, but I believe
your awareness that a problem exists, would make the biggest
difference to correct service issues that I noticed on both legs of
the journey.

My family was flying AA 0089 from Brussels to Chicago on 06/30, I was
in seat 33a. The video screen kept flickering at my seat so I called
the attendant. After 3 attempts without a response, I flagged the
attendant in the aisle who told me that they will “Re-boot” the screen
and that I should not touch it for 15 minutes. After 15 minutes, I
informed the attendant that the problem still existed, at which point
she decided to admonish  me in a loud voice saying “ I told you not to
touch it” , then she turned around and told the second attendant (in a
loud voice) “I don't think he understands English”. The second
attendant then proceeds to talk to me (pausing between each syllable)
that they are not electricians and are not expected to know how these
devices work. I must admit at that moment I truly felt that I was
being treated as a retarded person.

It was very clear that your in flight attendants need a serious
attitude adjustment. The only person who can bring that to them
quickly is you, provided you know a problem exists, hence my note to
you today.

To get to Nairobi, we took American Airlines to Brussels and then
Brussels air to Nairobi, On our way in, there was a consensus among
the family members (we were a party of 7) that American Airlines had
good equipment but the service was a bit sub par and Brussels air had
not so good equipment but great customer service. Sadly my return trip
confirmed our original assessment.

Thank you for listening.

Posted via email from mibdepot