Hello BIMfans,
Welcome to ‘Is It Smart?’, the blog series where I have a look at the smart technology installed within Tŷ Crempog to explore the power of BIM Level 2, PropTech, and the Internet of Things (IOT).  This week, I take a look at Smart Meters.

Those of you who follow me on Twitter will know that I have been trying to get Smart Meters for a long time.  In fact, I was put on Ecotricity‘s ‘priority list’ (Priority, Ha!) back in May 2016.  It has taken almost 18 months to arrange and complete the installation, but now I finally have Smart Meters installed!

What is it?

Because of policy managed by the UK Government’s Department for Business, Energy & Industrial Strategy (BEIS), around 26 million existing homes might will have Smart Meters installed by the year 2020.  These installations are being completed through the national energy providers.  In my case, Ecotricity (eventually) arranged the installation through a licensed third-party, SMS Plc.

So, what is a Smart Meter?  Well, a lot of excellent information is provided on the Smart Energy GB website on What Is A Smart Meter, as well as the Ecotricity website on What is Smart.  In short, they are gas and electricity meters which communicate with a national energy supplier; removing the need to provide meter readings.  They also provide real-time information about energy use, allowing the occupant (me) to better manage my energy.  This is normally done through an additional appliance, the in-house display (IHD).  Mine is currently sat in 002: Living Room next to my Google Home.

How does it work?

To be honest they are pretty straightforward.  Smart Meters function in the exact same way as regular meters do but also have a sim card included.  Mine are about the same size as my existing meters, so all SMS Plc had to do was do a straight swap.

Once installed, they effectively ‘text’ the energy use to my in-house display and to Ecotricity every 30 minutes or so.  Note:  After publishing this post, I was told about a few people who could not have smart meters installed because of poor mobile reception around their homes.  It is a shame that they cannot connect to the internet.

How Did I Model It?

To fully capture this installation I needed to model two new objects.  Under the Industry Foundation Class (IFC) Schema, electricity and gas meters are included under IfcFlowMeter.  I had already modelled my existing meters, so using these I formed two objects based on the Smart Meters‘ overall geometry.

Due to the low level of graphical detail used, the object files are only around 300KB each. The files were named following the BS 8541-1 naming convention to:

• Secure_FlowMeter_Liberty-EG4v-10; and
• Secure_FlowMeter_Liberty-100

Using the requirements set out in my Data Requirements, I populated these objects with the information needed to manage my Smart Meters.  Within these objects, I have captured information such as: Installation information, barcode, and serial number.

When used in collaboration with my IFC Export mapping text file, my Smart Meters are populating all of the relevant COBie fields I require; fantastic.

Is It Smart?

Smart Meters barely tick any of the right boxes to be considered smart.

• Data In:  With a direct connection to the flow of energy, they are able to consistently collect information.  In addition, the in-house display can receive messages from the energy provider for the occupants, so it is able to receive data over the network too.  However, there is no option to customize or inform it using any other information, so the input of data is quite limited.
• Data Out:  With a mobile network connection, they are able to consistently communicate information.  This information is also sent to the in-house display where it is stored for up to thirty days, allowing occupants to review historic energy use.  However, there is no option to export this information, so the output of data is quite limited.  Note:  Researching online, the export of this information may become available in a future firmware update.
• Connectivity:  Unfortunately, this is where it really falls short.  There are no options to connect these devices.  The connectivity is so poor, the readings don’t even appear in the official Ecotricity App.

The Potential

Much like my other smart products, there is no method to import information from my information model into my Smart Meters.  For example, I’m sure that information regarding where they are in my home, as well as house type, room areas and the volume of my home would provide additional value to an energy provider.

However, the real potential is in getting access to the energy use data outside of the in-house display.  If energy use data could be exported, I could then enrich it with local weather data and occupancy times; producing a rich dataset to form information about energy use patterns.

The Verdict

Is It Smart? The answer is No, with a shocking IQ of 50!

Since the smart meter roll-out was first announced, I knew I wanted to have Smart Meters for Tŷ Crempog.  However, energy meters that simply project readings onto another display can hardly be considered smart.  To be perfectly honest, the installation of these meters has had no impact whatsoever on how my home is managed.  NOTE:  Smart Meters have received a lot of criticism as they haven’t been producing the savings expected.  It has also resulted in the Ecotricity App being uninstalled, as it no longer provides any valuable information.

And there you have it.  This week my Smart Meters proved to be quite dumb.  Tune in next time where we take a look at another piece of smart technology and ask one simple question; Is It Smart?

Hello BIMfans,
Welcome to ‘Is It Smart?’, the blog series where I have a look at the smart technology installed within Ty Crempog to explore the power of BIM Level 2, PropTech, and the Internet of Things (IOT).  This week, I take a look at my Google Home.

What is it?

The Google Home is a hands-free smart (Wi-Fi) enabled speaker powered by the Google Assistant.  I currently have it installed in 002: Living Room as it is the most frequently occupied room in my home.  It has a built-in speaker and microphone which will listen out for the trigger phrase “OK Google” and then attempt to execute any command it hears.

 How does it work?

Once you have registered any service or device from Google‘s range of Compatible Partners, all you have to do is speak; It’s as easy as that!

So have I have gotten my Google Home to:

• Provide me with a weather update;
• Challenge guests to a trivia quiz;
• Traffic updates;
• Instant fight debate arbitrator;
• Play music through my Spotify account;
• Control my Nest Thermostat; and
• Control my Philips Hue bulbs.

For example, have a look at this short video on how I can use my Google Home to control the Philips Hue in my living room.

 How Did I Model it?

Under the Industry Foundation Class (IFC) Schema, a smart speaker isn’t included (who’d have guessed?), so I did what I always do in a situation like this; asked Twitter.

As you can see, at the time I produced this object, the preferred type was CommunicationAppliance.  This makes sense as while it does include a speaker (Making it AudioVisual) it’s main role is to communicate with other devices on my behalf.  So, using an electrical equipment family, I created two revolve solids and a void extrusion to create its unique shape.  Due to the low level of graphical detail used the object file is only around 400KB.  The file was named following the BS8541-1 naming convention to:

Google_CommunicationAppliance_GoogleHome

Using the requirements set out within my Data Requirements, I populated this Communication Appliance object with the information needed to manage my Google Home.  Within this object, I have captured information such as: Installation information, bar code, serial number, replacement cost and warranty information.  Note:  Much like my Nest Thermostat, my Google Home is one of the few items I manage within its warranty period.

When used in collaboration with my IFC Export mapping text file, my Google Home is populating all of the relevant COBie fields I require; fantastic.

Is it Smart?

Google Home ticks many of the right boxes to be considered smart.

• Data In:  With a Wi-Fi connection and a passive listening system, Google Home has a consistent method it can collect data.  In addition, through the mobile app it can control other devices and apply nicknames; which apply to the voice commands.
• Data Out:  Using the power of the internet, Google Home can provide me almost any information.  It also remembers each command it is given to help it improve its functionality, so I have a record of what has been asked.
• Connectivity:  The real power of Google Home is in its ability to connect with other devices.  So far I have it connected to my BBC, IFTT, and Spotify services as well as my Nest Thermostat, and Philips Hue bulbs.  Meaning that I can create customizable commands, set alarms, and even add events to my calendar using just two magic words; “Ok Google“.

The Potential

Much like my other smart products, there is no method to automate taking information from my information model into my Google Home.  For example, I have had to manually add the component names of my products as Nicknames (without special characters) so that each product can be controlled by its unique reference.

If only this process could be automated, then my smart products could use a lot of the good information I have collected to make them even smarter.

The Verdict

Is It Smart? The answer is Yes, with an Impressive IQ of 120!

Since it was first announced, I knew I wanted to have a Google Home, and I am glad to say that it has not disappointed.  While fairly simple in function, it has had a positive impact on my home.

And there you have it.  This week my Google Home proved to be quite smart.  Tune in next time where we take a look at my Philips Hue installation and ask one simple question; Is It Smart?

Hello BIMfans,
Welcome to ‘Is It Smart’, a blog series where I have a look at the smart technology installed within Ty Crempog as I explore the power of BIM level 2, PropTech, and the Internet of Things (IOT).  This week, I take a look at my Amazon Dash Buttons.

What is it?

The Amazon Dash Button is a Wi-Fi enabled device, linked to specific products on Amazon.  When you are starting to run low of a product, you simply press the button and an order will be placed and delivered using the details you have provided.

How Does it Work?

Using an Amazon account, you register the Amazon Dash Button as a device (like you would a Kindle).  Once the device is registered, you are able to select a product from the shortlist Amazon supports for your branded button (ie I can’t get my Andrex Button to deliver Velvet or Cushelle).

Once all of this has been completed, pressing the button sends a command over WI-FI to place an order for that product; it’s as simple as that.  The button also has a fail-safe that stops someone from pressing it multiple times by as default only allowing a single active order.

How Did I Model it?

Under the Industry Foundation Class (IFC) Schema, there is no obvious IFC Type, so I did what I always do in a situation such as this; ask Twitter.

Following the voting, the majority of people thought that it should be a Communication Appliance.  However, I have overruled this verdict and used  SwitchingDevice_MomentarySwitch (Sorry!).  I did this as my Amazon Dash Buttons have no ‘position’ and simply trigger an action to occur; making them switches.

Similar to my Nest Thermostat I used a face based generic model to create my object, but this time I have modelled the object as a solid oval.  Due to the low level of graphical detail used the object file is only around 296KB.  The file was named following the BS8541-1 naming convention to:

Amazon_SwitchingDevice_DashButton

Using the requirements set out within my Data Requirements, I populated this object with the data needed to manage my Amazon Dash Buttons.  Capturing information such as: Installation data, serial number, replacement cost, and warranty information.

Is it Smart?

The Amazon Dash Button, unfortunately, doesn’t really tick the right boxes to be considered smart.

• Data in: Without any sensors, the data input method on the Amazon Dash Button is the button itself which means that the ONLY way to active it is by physically pressing the button.  Also annoyingly, the buttons settings can only be edited through the mobile app, and these settings are rather limited.  For example, there is no way to rename my buttons despite being able to name other devices on my account.

  

• Data out:  There is also little data available from the device.  Aside from the default order history held on an Amazon account, no other information is available apart from a confirmation email received after the button is pressed.
• Connectivity: Due to the proprietary nature of the service, it is no surprise that it offers little connectivity.  These buttons are basically physical Do Buttons, but without any connectivity to other applications.  Of course, that hasn’t stopped some people from thinking of Amazon Dash Button Hacks.

The Potential

Currently, this use of these buttons is very limited.  If Amazon had opened up the button’s so that it could connect with IFTTT, then it would blow their potential wide open allowing for activation through triggers as well as physical presses.  This would also have the benefit of allowing recipes to store a log of when the buttons where pressed, which could then be used for settings future budgets as there would be a record of how often the buttons are pressed (or triggered).

The Verdict

Is it Smart?  The answer is no, with an IQ of only 70.

The Amazon Dash Buttons sounded pretty interesting when they were first released, however, after fitting a couple into my home I am disappointed at how little information I get out and put into them.  Compared to other smart home products, it seems odd how isolated the Amazon Dash Buttons are especially when you consider how connected something like Amazon Echo is.   The biggest disappointment is how I am forced to select only a few products from a pick-list.  This meant that only bulk orders could be selected which came as quite a surprise when they arrived.

And there you have it, This week my Amazon Dash Buttons didn’t prove very smart.  Tune in next time when I consider my Google Home and ask one simple question; Is It Smart?

Hello BIMfans,
Welcome to ‘Is It Smart?‘, a blog series where I have a look at the smart technology within installed Ty Crempog as I explore the power of BIM Level 2 and the Internet of Things (IoT).   This week, I take a look at my Nest Thermostat.

What is it?

The Nest Thermostat is an electronic, programmable, Wi-Fi enabled thermostat that learns from real-time use to optimize heating.  I currently have it installed in 002: Living Room as it is the most frequently occupied room in my home.  It has a series of built-in sensors that measure temperature as well humidity, motion, and ambient light.

How Does it Work?

When installed, the Nest Thermostat is connected over Wi-Fi to the boiler via an additional device called Heat Link which bypasses the boiler controls.

Quite simply, the big number in the middle is the programmed temperature (19) and the gauge shows the current temperature (21).  When the current temperature drops below the programmed temperature the heat link is activated; telling the boiler to run on full.  Once the programmed temperature is reached, a signal is sent to the heat link to deactivate the boiler and the cycle repeats indefinitely.

How Did I Model it?

Under the Industry Foundation Class (IFC) Schema, a thermostat isn’t included (it doesn’t appear until IFC4) so I have had to resort to IfcSensorType.  So, using a face based generic model I created a hollow cylinder and two inserts to represent the thermostat.  Due to the low level of graphical detail used the object file is only around 316KB.  The file was named following the BS8541-1 naming convention to:

Nest_Sensor_LearningThermostat 

Note:  Strangely, IfcUnitaryControlElement is included within BS8541-1, but not in the IFC2x3TC1 schema.  So for consistency, I haven’t used it.

Using the requirements set out within my Data Requirements, I populated this object with the data needed to manage my thermostat.  Capturing information such as: Installation information, bar code, serial number, replacement cost and warranty information.  NOTE, my thermostat is one of the few items I manage within its warranty period.

When used in collaboration with my IFC Export mapping text file, my thermostat is populating all of the relevant COBie fields I require; fantastic.

Is it Smart?

The Nest Thermostat ticks many of the right boxes to be considered smart.

• Data In:  With a number of sensors, a Wi-Fi connection, and both physical and digital interfaces methods there is a wealth of ways that it can collect data.  As a result, the thermostat learns about the space, proving an estimated amount of time needed to take effect based on past data.  In addition, Nest stores a heating programme for your home and maintains an activity log.

• Data Out:  Each month, Nest also provides owners with a report detailing how long the heating has been on as well as an update about the performance of my devices.  If you want more sophisticated data out of your nest, the API can be accessed here.

• Connectivity:  The ease that the Nest Thermostat can connect to other devices is a real strength.  Other products included within the ‘Works with Nest‘ category are able to access information from the Nest Thermostat.  For example, as a security feature, my Philips Hue bulbs will intermittently switch on/off in the evenings if my thermostat is set to ‘Away’.  In addition, as discussed in a previous post, through the use of IFTTT my thermostat can trigger (and be triggered) by other events.  Currently when my thermostat is set to ‘Home’, I receive a welcome home message in addition to any tweets from @TyCrempog when it is too hot or too cold.

The Potential

Currently, there is no method to automate the exchange of information to my Nest Thermostat from my information model; but this doesn’t have to be the case.  For example, within my Architectural model, there is a lot of good information that the Nest Thermostat could take advantage of including: Facility Name, Space Name, Area, & Volume and perhaps even external object thermal transmittance.

The verdict

Is It Smart? The answer is Yes, with an Impressive IQ of 130!

Since we had planned to buy our first home, the Nest Thermostat had always been on my shopping list and may very well have been the first purchase I made.  I’m glad to say it has not disappointed.

Since programming in a compromised heating schedule, I have barely had to touch the Thermostat control for the past 12 months.  While fairly simple in function, the Nest Thermostat has a lot of data being considered in the background, coupled with an impressive list of connectable products and regular reporting, it was always going to do well.

And there you have it, This week my Nest Thermostat has proved to be quite smart.  Tune in next time when I consider my Amazon Dash and ask one simple question; Is It Smart?