Many homeowners and occupants are interested in energy conservation for economical and/or ecological reasons. A number of commercial energy conservation solutions exist on the market today. However, these products contain closed systems and do not provide easy access to much of the raw data needed for more sophisticated analysis. An open source solution would be a great benefit for homeowners and occupants, allowing access to (and custom analysis of) raw power readings. We present a complete open source solution that monitors power, stores raw power readings, and makes provision for an in-home display, that informs stakeholders about energy consumption through a real-time ambient feedback effectively becoming an eco-feedback device.

Keywords: Power Monitoring, In-Home Display, Residential, Open Source, Arduino, RS-485, Modbus, Electric Imp, Energy Conservation

Apparently there were over 1,600 submission and they will be accepting only between 60-80 papers. Those are some odds!

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• The Cognitive Power Meter: Looking Beyond the Smart Meter (eco-sustain.org)

Last week I was honoured to receive recognition by the IEEE. I was elevated to the Senior Member (smIEEE) grade. Quote from the letter:

“Only 8% of the IEEE’s approximately 419,900 members hold this grade, which requires extensive experience, and reflects professional maturity and documented achievements of significance” (Peter W. Staecker, IEEE President & CEO)

A very BIG thanks to all those who supported me and provided references for my application!

As well, I am currently volunteering as the Membership Development Chair for the IEEE Vancouver Section. If you would like to join the IEEE you can sign up here. For those in the Vancouver area, I have four $25-off coupons that any person can use when signing up for a traditional IEEE Membership which I can give out.

The smart meter is often heralded as the key component supporting energy displays that can notify home occupants of their energy usage. But, a smart meter is only a digital power meter with enhanced communications capabilities — it is not actually smart. We need to look beyond the smart meter and define what intelligence is needed to actually make a meter smart. One area with promise is load disaggregation. Load disaggregation can be used to determine what loads contributing to the consumption reading at the smart meter. A smart meter incorporating load disaggregation intelligence can be seen as going beyond the traditional smart meter — what we call a cognitive power meter (c-meter). However, using load disaggregation, in its current form, is not feasible. We critically review the requirements for a c-meter and provide insights as to how load disaggregation research needs to change to make the c-meters a reality.

Keywords: Power Meter, Smart Meter, Load Disaggregation, Cognitive Analysis, Demand Response, Energy Conservation

I will post a link to where you can download the paper soon…

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• Added feature to log readings to SD card
• Added feature to save setting/config to EEPROM using browser
• Modified JSON format and accompany web service
• Perform load testing on hardware
• Sense when network down, when up send all unsent readings

APMR has a new project website (http://smakonin.github.com/APMR/) and the project source code can be down loaded from GitHub (https://github.com/smakonin/APMR).

Special thanks to TJ Moon who worked on this project all summer long!

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Research has shown that small changes in behaviour in how we use our homes can result in substantial energy and water savings. Home automation and the integration of computational intelligence capabilities in the “smart home” are often cited as promising advances in the design and renovation of efficient buildings. However, the design and implementation of such technologies are largely based on energy use simulations, smart automation of the building systems and components for optimal performance rather than on effectively supporting how people use their homes. Additional factors including system complexity and awkward automation can discourage acceptance of smart home technologies. In this paper we propose that technological support for sustainable home use lies in more subtle and contextually appropriate interventions that integrate more informative models of occupant behaviour, provide hybrid levels of automated control, and use ambient sensing for localized decisions. We discuss several cases from our experience in designing sustainable home systems and describe two current design cases for ambient intelligence in home control.

Keywords: Smart Home, Ambient Intelligence; Adaptive Lighting; Circadian Rhythms; Adaptive HVAC.

You can find a PDF of the paper at http://dx.doi.org/10.1109/MPRV.2012.58

Keep your eyes peeled as there are a number of other submissions that I am either waiting on review or in the midst of writing. Write on…

I have been using them for a couple of months now.

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I have been working very hard on my Depth Exam lately and have not had a chance to post much. Until today, when I decided that I wanted to publicly make available a 2010 dataset of a monitored home for use in research on load disaggregation, NILM (non-intrusinve load monitoring or NIALM), Smart Homes, and AAL (ambient assisted living).

This dataset contains ION6200 power meter and Digi Wall Router ambient light/temperature sensors readings; including weather and daylight data. Sensor readings were collected over a ZigBee wireless network at 15 minute intervals. The following published papers used this dataset: 2011hoa and hoa2012.

You can get this and future datasets from here: https://github.com/smakonin/HomeData

Happy Researching!

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• Public Data Sets for NIALM (op106phd.blogspot.ca)

http://makonin.com/report_consumption.html.

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