Buildings as live Entities

Buildings as live Entities
Marius Ghercioiu
Cores Electronic LLC, Austin, Texas, USA
ABSTRACT
A weather station is a measurement device that is placed outside a building and measures
environment related parameters like temperature, atmospheric pressure, air humidity, light, wind,
etc. The name “weather station” is very generic and it covers a large variety of sensors that can
monitor the environment. Weather station sensors are farther connected to a data acquisition board
in a computer or even better to a Wi-Fi tag which digitizes the signal and sends digitized data to the
application software. Traditional PC-based application software, like LabVIEW, will show weather
station data on the computer screen as a graph which will probably display a succession of dots
where each dot stands for the currently registered temperature or humidity value (Figure 1).
Figure 1. Classical graphical display of measured data
Display of weather information in these applications is made independent of the building itself. A
more novel approach to this application would be to consider the weather station as being a sensory
extension of the building‟s IoT nervous system and consequently have the application software
and presentation of data serve this paradigm that we named “Buildings as live Entities”. If we go
this way we are creating an environment where the building has its own identity in the Internet of
Things space, and it can participate in “conversations” with humans and other objects. For this
vision to become reality, we need the building to have a combination of “skills” which would allow
it to interact with the surrounding environment and also to express its “feelings” by using images
and/or sound.
First, we need the building to be capable of displaying information on its walls. Building walls
made of glass become interactive displays of information sourced by Cloud based Services
or simply from the Internet. There is a very good YouTube video describing this idea at
http://www.youtube.com/watch_popup?v=6Cf7IL_eZ38&vq=medium
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Secondly, we need a technology like Multi-Sensory Moving Art which connects images to
sensor measurements and by that can enable buildings to express “feelings” describing their
interaction with the environment.
Figure 2 shows an example of a home which has walls connected to the Internet and Multi-Sensory
Moving Art running on the living room wall.
Figure 2: Wind data displayed by building as an artistic display
This is where we want to be at the end of the article. I will show how starting from a weather station
that displays information in a PC-based application, we can work our way towards the “Building as
a live Entity” shown in Figure 2. The weather station becomes a sensory extension of the building
which has Internet connected walls running Multi-Sensory Moving Art to display “feelings” driven
by information from sensors outside.
INTRODUCTION
Distributed and remote measurements are done using wireless modules or nodes. These modules
may use Bluetooth, ZigBee, Wi-Fi, or serial proprietary communication protocols and firmware that
may support hopping, meshing, TCP/IP, serial bit banging etc. In the PC-based data acquisition
model, wireless measurement nodes send data to a PC running the application software. Another
alternative is for the wireless modules to send data straight to the Internet via off-the-shelf access
points. This very simple decision – to send digitized data straight into the Internet – if adopted, then
not only is the wireless hardware freed from the confines of cabling, the software is no longer
relegated to a specific box or PC. Instead measurement front ends connect to the Internet and a Web
page or a Web widget becomes the instrument, which users can access from anything that can surf
the Web.
The Tag4M Wi-Fi tag, shown in Figure 3, is a very good example of a cable replacement
measurement device which can send sensor measurements to the Internet and Web Pages. The
Tag4M Wi-Fi tag is a Wi-Fi RFID active tag with measurement capabilities that is intended to be
used to build wireless measurement solutions for a wide range of applications. Sensors are
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connected to tag I/O terminal blocks. The tag is a complete Wi-Fi and networking solution,
incorporating a 32-bit CPU, a memory unit, eCos real-time operating system, UDP and TCP/IP
stack, an analog sensor interface, a power management unit, hardware cryptographic accelerator and
a real time clock (G2 Microsystems1, 2009). The tag has very small dimensions (4.7 cm x 7.0 cm),
light weight, and it is battery powered.
Figure 3. Tag4M Wi-Fi tag data acquisition system.
A sensor becomes a Cloud Instrument (Ghercioiu, 2011) when:
- The sensor is connected to a wireless tag such as the Tag4M Wi-Fi tag,
- The tag digitizes the data to send it on to an Access Point, where the data is routed to the Internet
and a server IP,
- Here a customized engine is collecting the data for feed into applications like metering, charting,
control, analysis, modeling, data mining, etc. with display on web page Instruments and other web
widgets.
Cloud Instrumentation (Ghercioiu, 2011) has been introduced to define Internet based
instrumentation as opposed to PC-based instrumentation, and it represents the family of all cloud
instruments which route digitized sensor data to the Internet for computation, simulation,
modelling, analysis and presentation. The following diagram graphically illustrates this concept
(Figure 4).
Figure 4. Generic Cloud Instrument (Ghercioiu, 2011).
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A federation of sensors connected to Web Page Instruments running on a wide range of devices can
provide any number of services: from a simple data presentation to an alarming service that sends a
text message or tweet or even a correcting signal to the sensor tag; a metering service that calculates
consumption and costs; a database service that stores data; machine health monitoring, home-based
medical supervision and many others in what will become an enormous application space. What is
even more important than the diversity of applications, is that with processing taking place in the
cloud, information from all these applications can be shared, data-mined and refined using
behavioral algorithms to detect patterns that can help us make predictions and define strategies for a
better life together.
CONTENT
The Weather Station
A weather station extension (Figure 5) has been built for the Tag4M Wi-Fi tag. The weather station
is a measurement device which monitors the environment using sensors connected to a Wi-Fi tag
which digitizes the signal and sends data to the application software.
Figure 5. Weather station extension.
This weather station was populated with the following sensors: LX1972 light sensor, the HIH-5030
Humidity sensor, the TC1046VNB temperature sensor, and the MP3H6115A Pressure sensor. Its
board schematic (Figure 6, Folea 2008) includes, besides circuitry for the sensors, a voltage
reference component, REF3030, which is used to regulate power to sensors and to improve
measurement accuracy.
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Figure 6. Schematic of the weather station extension board.
One of the sensors on the weather station extension board is the TC1046VNB temperature sensor
which can accurately measure temperature in the range from -40°C to +125°C generating a linear
voltage output with a 6.25mV/°C slope (Microchip, 2004). Figure 7(Folea, 2008) shows a sample of
the sensor output signal corresponding to over 5 days of continuous monitoring.
Figure 7. Temperature sensor, measurement data.
Another sensor on the weather station extension board is the HIH-5030 humidity sensor
(Honeywell, 2010). The humidity output signal converted to units of humidity displayed as a graph
is presented in Figure 8 (Folea, 2008).
Figure 8. Humidity sensor, measurement data.
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The weather station is populated with the LX1972 light sensor. Output signal from the light sensor
extension is presented in Figure 9 (Folea, 2008). The LX1972 is a low cost silicon light sensor
which emulates the human eye producing a spectral response. The response is produced at 520nm,
with IR response less than 5%, of the peak response, above 900nm. According to (Microsemi,
2005) it is usable at ambient light from 1 to more than 5000 Lux.
Figure 9. Light sensor, measurement data.
The weather station is populated with the MP3H6115A6U pressure sensor (Freescale
Semiconductor, 2009). The following is an example of a measured atmospheric pressure for a
period of 5 consecutive days.
Figure 10. Pressure sensor, measurement data.
Another sensor that could be placed on the weather station board is a dust air density detector
module, the GP2Y1010AU0F. This is a dust sensor based on an optical sensing system. The basic
principle on which the sensor detects dust is by quantifying reflected light of dust in the air using an
infrared emitting diode (IRED) and a phototransistor which are diagonally positioned inside the
device (Sharp, 2006). The sensor has high sensitivity in detecting very small dust particles (like the
ones contained in cigarette smoke) and also the capability to distinguish house dust and smoke.
Figure 11 presents the schematic our dust air density detector module. The sensor extension module
containing the dust air density detector is presented in Figure 12 (Folea, 2008).
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Figure 11. Dust air density sensor schematic
Figure 12. Dust air density sensor, PCB and measurement data.
Another sensor, the last one we want to present here, is monitoring wind speed and direction, using
the WS-2310-15 sensor (La Crosse Technology, 2002). This is a serial sensor which sends data in a
compact serial package with the following format:
1
START
1 0 1
1
DIRECTION
0 1 2 3
0
1
2
3
SPEED
4 5 6 7
8
DIRECTION
9 10 11 0 1 2 3
The wind sensor has a digital input command line to control its state. We need to be able to turn the
sensor On/OFF in order to reduce its power consumption. Once the sensor is turned off, it takes
about 2 to 2.5 seconds for the sensor to boot up and send the first output values. Wind speed values
from this sensor are shown in Figure 13 (Folea, 2008). The sample corresponds to a session of
continuous monitoring for a 5 days period.
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Figure 13. Wind speed, measurement data.
Sensor readings of wind direction are presented in Figure 14 (Folea, 2008). The numerical values
represent wind direction as in: North(N) = 1, North-East(NE) = 3, East(E) = 5, etc, etc.
Figure 14. Wind direction, measurement data.
The Cloud Instrument
When working on an idea like “Building as a live Entity” we need to project how future
measurement technologies will look, not as much the sensing part but what we do with digitized
data in terms of analysis and presentation. The cloud computing space looks appealing because it
sits on top of all real physical space and looks very much like a giant data repository for everything
that is collected and needs to be processed, data-mined and presented on a very large scale. Greater
adoption by consumers facing applications like environmental monitoring, electricity use, building
automation, grid applications, biomedical, spread of diseases, viruses, seismic, hurricane and
tornado monitoring, so forth, will push forward the use case of cloud based measurement
applications where things that need to be monitored are very dense, wide spread, and Web enabled.
A sensor becomes a Cloud Instrument(Ghercioiu, 2011) when it is connected to a wireless tag such
as a Wi-Fi tag. The tag digitizes the data to send it on to an access point, where the data is routed to
the Internet and a server IP. Here a customized engine is collecting data to feed into applications
like metering, charting, control, analysis, modeling, data mining, and so forth, with display on Web
page and Web widget instruments. Figure 15 shows the components of a Cloud Instrument.
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Figure 15. The Cloud Instrument.
The Web Page Instrument reads Port 50007 of the server computer, decodes UDP data packets at
this port, converts digital data into sensor units, sends tag commands if any, and displays sensor
data in a web page. When the Tag4M tag is powered, and assuming that it has been associated with
a local Access Point, then it automatically gets displayed in the Web Page Instrument (an example
is posted at http://demo.tag4m.com). This display contains the following information: tag MAC or
tag name, temperature in degrees C as measured on the tag board, measurement values from 0-10V,
4-20mA, AI-0, 1, 2, and DIO0, 1, 2, 3 tag channels, battery voltage, RSSI (Received Signal
Strength Indicator) and tag sleep time. The Web Page Instrument will display all Tag4M tags that
are live and associated with access points.
As an example of sensor to Web Page Instrument application, let us look at temperature data from a
10K3A1A thermistor that is connected to channel AI-0 of a Tag4M Wi-Fi tag with MAC address
ending in 2886. The tag will be configured for channel AI-0 measurement by clicking on the tag
MAC which will open the tag configuration panel (Figure 16).
Figure 16. The Web Page Instrument – Tag configuration panel.
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The Web Page Instrument is now reading digitized voltage values from channel AI-0 that is
populated with a thermistor (Figure 17). The application may run in the cloud or on a private server
and the location of the tag/sensor can be anywhere as long as the Web Page Instrument sees the tag.
Figure 17. The Web Page Instrument – Tags configured and running.
The reading on channel AI-0 is 4320.67Ohms which corresponds to 46.05 Deg C. We can now
build a small web widget that gets thermistor data feeds from the Web Page Instrument and displays
temperature. We named such an application a widget instrument.
The Widget Instrument (Ghercioiu, 2011) can be embedded and executed within any web page or
media site. The idea of building and using widget instruments is to be able to focus on individual
sensor displays, build a standalone application that gets feeds of that specific sensor data from the
Web Page Instrument and either displays this data as it is or scaled into temperature like in this
simple example.
Figure 18. The thermistor Widget Instrument.
The unique features of a Widget Instrument are small size and embedded in a web page, media site
or smart phone user interface. The widget instrument display can also be an artistic image as seen in
the picture below (Figure 19).
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Figure 19. Example of thermistor widgets: artistic image and number display.
This idea of creating web widgets that associate artistic images to sensor measurements leads us
into art applications of cloud instrumentation. We will discuss this subject in a separate chapter, as
we would like to first present the relationship between cloud instrumentation and cloud computing.
Cloud Instrumentation is just one of the many applications of cloud computing. Generally, cloud
computing customers do not own the physical infrastructure, avoiding capital expenditure by
renting usage from a third-party provider. They consume resources as a service and pay only for
resources that they use. If we apply this model to a measurement application, the cloud provider
will host the Web Page Instrument and Widget Instrument while the customer will embed one or
both of these instruments into his web or media site. An example of sensor widgets embedded into a
media site can be seen at http://sensedin.blogspot.com/.
Access Points will play a much larger role, not only for routing sensor data but also for hosting and
routing application code. Innovation will also take place in the domain of Web page instrument
thanks to tools such as Web page instrument builders and updaters. Cluster Web pages can include
widgets for portable Wi-Fi platforms, running wave-type applications that move data from page to
page to follow the progress of a physical process. We are working our way towards an
„instrumentation cloud‟ where not only the sensors but also the logging, analysis and control
programs, and widget instrument deployment and display can be anywhere you want them.
Multi-Sensory Moving Art
The cloud instrument concept brings closer together, maybe more than ever before, two of
humanity‟s most driving engines which are art and technology. This just makes perfect sense
because as we move through life and interconnect with objects we generate data, lots of data, which
tells stories about our lives. We believe the art we create needs to capture these stories, just like
instruments do, but using more warm and human images to reflect our interaction with the world
around us. This thought brings us back to the idea of art applications of cloud instrumentation.
Ghercioiu and artist Arlissa Vaughn defined a new type of art, named Multi-Sensory Moving Art
(video explanation at http://www.youtube.com/watch?v=FKdQCygws8A), which uses a digital
sensor frame to associate images with sensor readings. The digital sensor frame is a cloud
instrument that feeds an art widget application.
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Figure 20. Cloud Instrument feeds art.
Multi-Sensory Moving Art is dynamic and therefore able to continuously tell a developing story,
just like an instrument, but on an artistic level. The following is a description of Multi-Sensory
Moving Art that uses a wind sensor.
Generally speaking the major difference between a wind sensor and a temperature sensor is the
dynamics of the phenomenon. Temperature is a very slow and linear developing phenomenon.
Therefore, art driven by temperature will be very slow changing. If the temperature reading does not
change or it takes a long time to change, art does not change, the frame will continuously show the
image or sequence of images associated to that temperature value. Wind is more dynamic and also
very unpredictable. Wind is definitely not a linear developing phenomenon. Wind can change very
quickly! It can go from very calm to extreme speed and also from blowing North-to-South to Northto-SouthWest or South-to-NorthEast, etc.
In this experiment we are monitoring wind using a sensor named WS-2310-15 made by La Crosse
Technology. Wind, as measured with this sensor, has two parameters: speed and direction. The tag
will continuously read these two parameters and send them to a digital sensor frame hosting the art
images.
The wind sensor (Figure 21) used in this experiment has the following components:
1) A larger palette, actually named a wind-vane, that determines wind direction, and
2) A wind-fan that measures wind speed.
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Figure 21. Wind sensor.
The wind sensor has a controller inside a cylinder as seen in the above pictures. The unit measures
wind speed and wind direction and sends the data, as digital values (numbers), via a long cable to
the Tag4M Wi-Fi tag (Figure 22).
Figure 22. Wind sensor connected to Tag4M Wi-Fi tag.
When wind blows into the wind sensor the wind-vane and wind-fan start moving and their
movement generates signals that the controller uses to determine wind speed and direction.
The wind-vane measures wind direction. Wind will position this palette into one of the directions
shown in Figure 23.
The controller associates numbers to wind direction, values from 0 to 15, where
1) Direction = 0, 1, 2 means wind blowing North-to-South,
2) Direction = 3, 4, 5, 6, means wind blowing NE-to-SW,
3) Direction = 7, 8, 9 means wind blowing East-to-West,
4) Direction = 10, 11, 12 means wind blowing SE-to-NW,
5) Direction = 13, 14, 15 means wind blowing South-to-North.
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Figure 23. Wind direction.
The wind-fan measures wind speed which can be a number between 0 (no wind) to 60 meters/sec
(very high wind).
Art driven by wind has two degrees of freedom, which means that it can change based on wind
direction and wind speed. The tag reads the wind sensor and gets values for direction and speed.
These two values are used by the digital sensor frame to select the correct sequence of illustrations
and also the correct timing between consecutive images inside that sequence in order to illustrate
this moment‟s wind movement. The sequence of illustrations runs. It may take 6 seconds to finish
the current run. During the sequence run wind may change direction and speed. These changes will
not be reflected by the currently running art until the art cycle repeats itself. The art cycle contains
the following steps:
- tag reads sensor values,
- tag sends values to digital frame,
- digital frame chooses a sequence of images and timing between consecutive images inside
this sequence,
- digital frame runs the sequence of images until the end,
- start cycle from the beginning: tag reads sensor value etc.
We are now able to give art driven by wind a more complete definition: Art driven by wind is a
continuous story told in sequences of artistic images driven by discrete sampling of two wind
parameters: direction and speed.
Wind Direction controls the direction of movement inside the art (Figure 24). Art objects can move
in any of the directions 1, 2, … 5 that the wind sensor can measure. These five directions are
predefined and each of the directions is associated with sequence of images that moves in that
direction. Only predefined sequences that are associated with one of the wind directions 1 to 5 are
allowed and can run inside the digital sensor frame.
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Figure 24: Wind directions on the art canvas.
A sequence of images, once chosen to run, will completely run its images, from start to finish even
if the wind changes while the sequence is running. Wind direction can also be used just as a
differentiator between art sequences.
When building his/her art sequences the artist needs to think about both direction and speed,.
Direction is very straight forward, but the idea of speed or what happens with the images at higher
speed will probably be more difficult to incorporate in art. There is an open field of expression for
art at higher wind speed, maybe something special happens, a new object or a deformed object, etc.,
and that special thing cannot be seen at lower speed. When wind speed is 0 the art is static. It may
be the last image from the previous sequence or one image that is always used when there is no
wind, or maybe a blank screen, etc.
The art images (Figure 25) of the very first piece of art driven by wind have been created by artist
Arlissa Vaughn, link at http://arlissawind.temperatureavatar.com/.
Figure 25: Art driven by wind by Arlissa Vaughn.
Building walls become interactive displays
Building walls made of glass become interactive displays of information coming from the Internet
(Figure 26). There is a very good YouTube video posted by Corning at
http://www.youtube.com/watch_popup?v=6Cf7IL_eZ38&vq=medium that describes this idea.
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Figure 26: Building walls as Internet connected displays of information (by Corning)
Inside her live building, Jennifer is using her bedroom glass wall (Figure 27) to enter her
favorite clothing store, which recognizes and welcomes her back. The store gives Jennifer
access to a menu of choices but also, and this is very personal to Jennifer, the wall displays
current temperature outside Jennifer‟s home as an artistic image that matches very well
Jennifer‟s aesthetic feelings of the moment and this makes Jennifer very happy and more in
the mood of visiting the store today. The image below illustrates a progression of
temperature from morning to night as a cross-pollination fantasy (by artist Alana Perlin
with
Marius
Ghercioiu
2011,
original
presentation
at
http://alanaperlin.temperatureavatar.com/ ).
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Figure 27: Jennifer is visiting her favorite clothing store
Jennifer can also enter her own Multi-Sensory Moving Art gallery (Figures 28 and 29) and open
some of her favorite art. Jennifer‟s gallery uses a digital sensor frame that is connected to the
weather station outside her building and turns sensor data into information that is manipulated to
present Jennifer‟s favorite art. The Digital Sensor Frame also runs on the Jennifer‟s iPad2 making
this device a wall sample or a digital canvas that is connected to sensors. Artists can now display
their multi-sensory moving art work in private galleries that run on collectors‟ private home walls.
(Marius Ghercioiu - 2011, original presentation at http://tag4m.blogspot.com/ ).
Figure 28. Jennifer’s private Multi-Sensory Moving Art gallery
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Figure 29. Jennifer’s private Multi-Sensory Moving Art gallery
When Jennifer clicks on Arlissa Vaughn‟s Wind Test icon, the art starts running driven by the wind
sensor outside her home (Figure 30). This accomplishment brings us to the end of our road.
Jennifer‟s home is an example of Building as live Entity, a home which has walls connected to the
Internet and displaying Multi-Sensory Moving Art, which is wind driven by sensors outside the
building and the art belongs to Jennifer‟s private gallery.
Figure 30: Jennifer’s home displays Wind driven art by artist Arlissa Vaughn
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FUTURE RESEARCH DIRECTIONS
We are interested in pursuing the cloud instrumentation idea and building more web based
applications and also specialized widgets that incorporate data processing. We are working our way
towards a community of tag users who all contribute widget instruments. There is a direct
connection between the community of Cloud Instrumentation and the Internet of Things movement.
We enable sensor to become objects in the Internet space and by that bring measurement
capabilities to the Internet of Things. We will also pursue the art driven by sensors movement,
Multi-Sensory Moving Art, by working with artists to create such art. This work also ties into the
Internet of Things because it enables art work to be dynamic, and to participate and have an identity
on the Internet. Static images are beautiful and masters for centuries have perfected this
“technology” to unbelievable levels of beauty. Multi-Sensory Moving Art is adding a new
dimension to the art of illustrations and drawings with the concept of a moving illustration or live
painting that tells a story about an entity‟s natural changes correlated to sensor readings. Imagine a
combination of sensors located in different places, monitoring different entities and sending data to
Cloud Art Applications. There is huge field open for innovation here. I am inviting painters and
illustrators from all over the world to join this art movement and create their own art using this
technology.
CONCLUSION
We started our journey with the weather station and Tag4M Wi-Fi tag. As we built sensor
attachments to the tag to monitor environmental parameters and wrote application software we
realized that the concept of PC-based instrumentation does not serve well the “Buildings as live
Entities” idea. Therefore we defined a new type of measurement instrument named Cloud
Instrument. The set of all cloud instruments became a space named Cloud Instrumentation which is
open to all specialized software vendors to offer solutions for metering, charting, data logging, data
mining, etc., all benefiting from digitized sensor data brought into the Cloud by Wi-Fi tags. Then
we decided to make the Weather Station a sensory extension of the building which is also capable
of interactively displaying Internet related information on its glass walls. Further on, this brought
the idea of Multi-Sensory Moving Art which is art driven by sensor measurements and displayed on
the wall. At this point we accomplished our goal of defining and giving an example of a building as
a live entity.
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