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Adaptive Designs with Distributed Intelligent Systems: Building Design Applications

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This paper discusses and demonstrates an integration of embedded electronic systems utilizing distributed sensors and localized actuators to increase the adaptability and environmental performance of a building envelope. It reviews state-of-the-art technologies utilized in other fields that could be adopted into smart building designs. The case studies adopt the Internet of Things (IoT) framework based on machine-to-machine (M2M) communication protocols as a potential solution for embedded building systems. stract here by clicking this paragraph.
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Adaptive Designs with Distributed Intelligent Systems
Building Design Applications
Andrzej Zarzycki1
1New Jersey Institute of Technology, USA
1andrzej.zarzycki@njit.edu
This paper discusses and demonstrates an integration of embedded electronic
systems utilizing distributed sensors and localized actuators to increase the
adaptability and environmental performance of a building envelope. It reviews
state-of-the-art technologies utilized in other fields that could be adopted into
smart building designs. The case studies discussed here, sensors are embedded in
construction assemblies provide a greater resolution of gathered data with a finer
degree of actuation. These case studies adopt the Internet of Things (IoT)
framework based on machine-to-machine (M2M) communication protocols as a
potential solution for embedded building systems. stract here by clicking this
paragraph.
Keywords: Adaptable Designs, Arduino Microcontrollers, ESP8266, Smart
Buildings, Internet of Things
INTRODUCTION
The concept of an adaptive building envelope as a
performance enhancer has been in use for a long
time. Façade elements such as sunscreens, win-
dow shutters, or removable window sashes helped
to adapt to climatic and seasonal changes by aug-
menting building use and its performance. While
these elements were dynamic in nature-opening and
closing shutters or louvers--architects usually refer to
them as passive environmental techniques for man-
aging building performance because of the manual
nature of their operations. The inclusion of mechani-
cal and electrical systems within a building, and more
recently embedded electronic intelligence that con-
nects automated control systems with networked
data sets and environmental sensing, changed this
passive approach to an active and dynamic frame-
work. Elements like shutters and sun louvers continu-
ously and in real time adjust to external environmen-
tal conditions in the attempt to optimize indoor cli-
mate based on preprogrammed algorithms.
With the introduction of building environmen-
tal control systems, the automation started to con-
trol temperature, air quality, and lighting levels.
These automated controls not only provided in-
creased comfort for living but also translated into
more energy-efficient and environmentally friendly
buildings (Guillemin 2001). However, automated
controls were often structured around a central con-
trol dashboard system with a limited number of sens-
ing points delivering the same solution to a broad
number of space conditions. A more deliberate and
fine-tuned approach to building controls that goes
beyond the size of a single room into the scale of in-
TOWARDS SMARTER CITIES | Concepts and Strategies - Volume 1 - eCAADe 34 |681
dividual building components is needed.
While buildings and cities are increasingly filled
with smart objects and devices that monitor traffic,
track inventories, or respond to occupants, building
assemblies themselves do not demonstrate a similar
level of interactivity and autonomy (Achten, 2015).
There is an opportunity to extend these smart and in-
terconnected device networks into the very matter of
buildings and their assemblies.
This paper discusses and demonstrates an inte-
gration of embedded electronic systems utilizing dis-
tributed sensors and localized actuators to increase
the adaptability and environmental performance of
a building envelope. It reviews state-of-the-art tech-
nologies utilized in other fields that could be adopted
into smart building designs. The case studies dis-
cussed here, sensors embedded in construction as-
semblies, provide a greater resolution of gathered
data with a finer degree of actuation. These case
studies adopt the Internet of Things (IoT) framework
based on machine-to-machine (M2M) communica-
tion protocols as a potential solution for embedded
building systems.
FROM AUTOMATED TO INTELLIGENT NET-
WORKS
Building automation is a centralized and automatic
control of lighting, heating, and cooling, as well as
other systems including security, fire, and occupant
safety, through a building automation system (BAS)
or building management system (BMS). The goals
of a BAS are improved efficient operation of build-
ing systems, including reduction in energy use and
operating costs, as well as increased occupant com-
fort and the life cycle of the building. Recently con-
structed buildings include some sort of BAS/BMS,
and many older buildings have been retrofitted with
these systems. BASs/BMSs include software and
hardware architecture that integrates controls for all
or most building systems within one dashboard (in-
terface). They are offered by many established com-
panies, such as Siemens, Honeywell, and Cisco, that
already manufacture various building environmen-
tal system equipment. While these systems are ef-
fective and deliver significant cost savings (˜20%) as
compared to non-BAS/BMS buildings [1] , they in-
clude various levels of autonomy and intelligence. In
many cases, they respond to matrix-oriented algo-
rithms without understanding the real-time consid-
erations of building occupants or building assembly
conditions. Furthermore, BASs/BMSs are usually im-
plemented in non-residential buildings where a sin-
gle owner or interested party is in control of central-
ized building systems.
While building automation is an example of the
smart environment approach and is often referred
to as the framework behind intelligent buildings, it
currently limits itself to controlling already mecha-
nized and electric/electronic devices such as heating
and cooling systems, without necessary broader im-
plementation of embedding sensors and actuators
into building components and assemblies. It is par-
tially because BASs/BMSs are developed by compa-
nies that manufacture building system components
and their controls (HVAC or air handling units), not by
construction companies or building component fab-
ricators. They facilitate an improved performance of
installed equipment, not necessarily of the building
itself. What is needed in the next wave of transfor-
mation of the building industry and buildings them-
selves (Osman 2005), and is advocated in this paper,
is to develop technologies that integrate and take ad-
vantage of the embedded systems within building
assemblies. Windows, doors, floors, and wall panels
all could and should function as part of the building
digital interface, sensing user and environmental in-
puts as well as actuating desired spatial outcomes.
ADAPTATION OF INTERNET OF THINGS
FOR BUILDING ASSEMBLIES
Smart and connected devices are objects embedded
with microcontrollers, sensors, and actuators, with
connectivity that allows data exchanges between the
product and its environment, user, manufacturer,
and other products and systems. They allow for en-
hanced interactions with people and other objects,
682 |eCAADe 34 - TOWARDS SMARTER CITIES | Concepts and Strategies - Volume 1
utilizing radio-frequency identification (RFID) tags or
wireless networks. Connectivity enables certain ca-
pabilities of the product to exist outside its physical
form as part of a larger data set (cloud). Collected
data can be analyzed to inform decision-making and
enable operational efficiencies of the product and
the entire system. As envisioned by Mark Weiser in
his Scientific American article titled "The Computer
for the Twenty-First Century" (1991), "When almost
every object either contains a computer or can have
a tab attached to it, obtaining information will be
trivial." BAS/BMS platforms discussed earlier are of-
ten beneficiaries of these collected data points-tabs
attached to physical objects. The IoT is the network
of smart objects with embedded technologies able
to communicate, sense, and interact with the out-
side environment (Kortuem et al. 2010). However,
this network of smart and interconnected devices
provides opportunities for greater interoperability
and resiliency of the entire system, with data com-
ing from and access to individual subcomponents-
devices and objects-as compared to BASs/BMSs.
In addition to sensing and actuation, smart sys-
tems incorporate decision-making abilities, utilizing
previously gathered data in a predictive or adaptive
manner that often employs machine learning algo-
rithms. In these cases, the "smartness" of the sys-
tem is attributed to autonomous operation meeting
its performance and user satisfaction expectations.
While current BAS/BMS platforms follow an estab-
lished (pre-programmed) set of rules, the expecta-
tion is that the underlying reasoning (algorithm) for
smart systems would adapt over time based on envi-
ronmental and user feedback.
PROPERTIES OF SMART OBJECTS AND EN-
VIRONMENTS
While smart objects can function autonomously and
perform complex performance optimizations or user
tracking, they do not necessarily need to exhibit in-
telligence in the sense of artificial intelligence (AI).
As such, the term "smart objects" is a rather inclu-
sive category of object types, from those that per-
form basic building automation, such as traditional
sensor-based (or even mechanical) thermostats or
automated louver systems, to sophisticated and pre-
dictive devices such as the Nest thermostat utilizing
machine learning algorithms.
Independently of their level of autonomy and
"smartness," smart objects commonly exhibit the fol-
lowing three typologies or design dimensions:
Awareness is a smart object's ability to under-
stand (that is, sense, interpret, and react to)
events and human activities occurring in the
physical world.
Representation refers to a smart object's ap-
plication and programming model-in particu-
lar, programming abstractions.
Interaction denotes the object's abilit y tocon-
verse with the user in terms of input, output,
control, and feedback (Kortuem et al. 2010,
31).
These three design dimensions are further organized
into three types:
Activity-Aware Smart Objects: An activity-
aware object can record information about
work activities and its own use.
Policy-Aware Smart Objects: A policy-aware
object is an activity-aware object that can in-
terpret events and activities with respect to
predefined organizational policies.
Process-Aware Smart Objects: Processes play
a fundamental role in industrial work manage-
ment and operation. A process is a collection
of related activities or tasks that are ordered
according to their position in time and space
(Kortuem et al. 2010, 32-34).
While these typologies are rather general, Das and
Cook (2005) define smart environment with more nu-
ance as having the following features:
1. Remote Control of Devices: the ability to con-
trol devices remotely or automatically.
2. Device Communication: the ability of devices
to communicate with each other, share data,
TOWARDS SMARTER CITIES | Concepts and Strategies - Volume 1 - eCAADe 34 |683
and retrieve information from outside sources
over the Internet or wireless communication
infrastructure.
3. Sensory Information Acquisition/Dissemina-
tion: the ability of sensors to share informa-
tion and make low-level decisions.
4. Enhanced Services by Intelligent Devices: in-
cludes context and location awareness.
5. Predictive and Decision-Making Capabilities:
full automation and adaptation that rely on
the machine learning, or acquiring informa-
tion that allows the software to improve its
performance.
CURRENT IMPLEMENTATIONS OF INTER-
NET OF THINGS
M2M Communication
M2M communication forms the basis for IoT. It is
routinely used for remote monitoring and controls,
including traffic, inventory, and transportation fleet
management, and for robotic applications, includ-
ing autonomous vehicles. Big Belly trash bins [2],
a waste and recycling management system, utilize
M2M communication to message for trash pickup
when the bin is full. Similarly, vending machines can
track purchases, record customer preferences, and
inform a distributor when a particular inventory is
running low. [3]
MQTT [4] stands for MQ Telemetry Transport and
is an M2M and IoT connectivity protocol designed
as an extremely simple and lightweight publish/sub-
scribe messaging transport utilizing a client-broker
relationship structure. Individual clients can be both
publishers and subscribers, providing or acting upon
provided sensor data. The broker is counterpart to a
MQTT client and is responsible for receiving all mes-
sages, processing them, deciding which client may
be interested in them, and then sending messages to
subscribed clients.
MQTT is suitable for wireless networks that expe-
rience varying levels of latency due to occasional low-
bandwidth or unreliable connections. A design ap-
proach minimizes network bandwidth and device re-
source requirements to ensure communication relia-
bility and some degree of assurance of delivery. This
approach is particularly effective in the context of
interconnected IoT devices with limited bandwidth
and battery.
Currently, neither IoT nor M2M platforms have
standardized connected device protocols, with many
systems custom-built to facilitate particular tasks or
utilize certain devices. Once the adoption of IoT and
M2M devices becomes more prevalent, manufactur-
ers will need to agree on standards for device-to-
device communications. Security and safety are sig-
nificant concerns associated with IoT and M2M com-
munication, since many original systems were not
designed as open Internet-connected networks. [5]
Wireless Communication Technologies
Wireless mesh network topology allows for each
node to relay data for the entire network. All mesh
nodes participate in the distribution of data, which
provides a number of benefits over traditional net-
works, where a small number of wired access points
or wireless hotspots connect users and control all
communication. A distributed nature of mesh net-
work communication makes them (1) highly adapt-
able and expandable, as individual mesh nodes can
be added to or removed from the network; (2) able
to support high data demands, as each node is con-
nected to multiple other nodes and each device par-
ticipating in the network would function as a node;
(3) reliable and resilient sources of wireless connec-
tivity for a broad range of public safety applications,
as an off-line or damaged device would be super-
seded by other nodes and communication routes;
and (4) less expensive than traditional networks, as
they require less wiring and can service significantly
larger areas.
The disadvantages of mesh networks include the
complexity associated with their management and
potentially high initial capital investment if not uti-
lizing already existing device infrastructure.
The implications for embedded environments
684 |eCAADe 34 - TOWARDS SMARTER CITIES | Concepts and Strategies - Volume 1
are that a broad distribution of wireless communica-
tion devices would not only benefit from mesh net-
works but also benefit the network itself by provid-
ing a dense grouping of nodes, mitigating one of
the main disadvantages of mesh networks. However,
adaption of mesh networks would mean that the cur-
rent implementation of many IoTtechnologies would
have to be rethought once a critical mass of embed-
ded components was to be implemented in build-
ings. The relevance of mesh networks to embedded
environments becomes particularly important when
considering larger-urban and regional-scales of de-
sign. While buildings could effectively function with
an access point approach, cities and open spaces
could be better served with mesh networks.
Specific Technology Considerations
The core of the IoT concept is inter-device communi-
cation achieved through wireless connectivity (usu-
ally Wi-Fi) and/or high-frequency radio communica-
tions such as LoRa radios. Both technologies could
be used in the client-server or mesh network con-
figurations. As such, IoT networks can be struc-
tured hierarchically or with peer-to-peer connectiv-
ity. The benefits of Wi-Fi-based communication in-
cludes the ability to connect to already established
networks, and through these networks to the In-
ternet, as well as communicating with other Wi-Fi-
enabled devices such as smartphones and tablets.
This approach is popular, since it uses personal mo-
bile devices as control dashboards and data inputs.
Wi-Fi-based IoT could function as part of the larger
Internet-connected network, providing remote ac-
cess and data sharing, or could also function as an
independent and isolated network in either client-
server or mesh network configurations. It provides
high data transfer rates as compared to other radio
communication options, but it also comes with a lim-
ited coverage area.
LoRa [6] radio-based wide area networks pro-
vide the opportunity for long-distance communica-
tions suitable for monitoring urban-scale infrastruc-
ture with a range of up to 5 km, and even 10 km. A
high range and coverage area is offset by extremely
low data rates as compared to Wi-Fi networks. How-
ever, this may be acceptable for IoT applications that
are not data transfer heavy, such as sporadic (ev-
ery couple of seconds or minutes) reporting from a
weather station or of the temperature of a road sur-
face. LoRa radio modules use 868- and 900-MHz ISM
bands, which make them suitable for global applica-
tions, as these are commonly shared radio frequen-
cies. These frequencies have less interference and at-
tenuation than the highly populated Wi-Fi spectrum
(2.4 and 5 GHz).
The main benefit of long-range radios as com-
pared to WiFi networks is the low number of radio
nodes necessary to provide the coverage for large ar-
eas such as cities and rural regions. However, the low
data transfer rates make LoRa radios more suitable for
communicating low volumes of data from individual
sensors or actuators.
Figure 1
ESP8266 module
with a motor shield.
ESP8266: System of Chip Solution
One of the recent approaches to IoT, particularly in
the do-it-yourself (DIY) community, involves ESP8266
chip-based architecture. ESP8266 is implemented in
a number of designs and can be integrated with sen-
sor and actuator shields (Figure 1). ESP8266 com-
bines functionalities of the microcontroller and Wi-
TOWARDS SMARTER CITIES | Concepts and Strategies - Volume 1 - eCAADe 34 |685
Fi communication module (2.4 GHz, 802.11 b/g/n,
supporting WPA/WPA2) in a simple system-on-a-chip
(SoC) design. ESP8266 is a highly integrated SoC so-
lution with 16 general-purpose input/output (GPIO)
pins, analog-to-digital conversion (10-bit ADC), Inter-
Integrated Circuit (I²C), Serial Peripheral Interface
(SPI), I²S interfaces with DMA (sharing pins with
GPIO), UART (on dedicated pins, plus a transmit-only
UART that can be enabled on GPIO2), and pulse-
width modulation (PWM). It is running at 80 MHz (or
overclocked to 160 MHz). Most recent ESP-12F mod-
ules are FCC (USA) and CE (EU) approved. For those
using the Arduino platform, the ESP8266 chip allows
for a convenient migration path to IoT architecture.
It is also compatible with NodeMCU [7] open-source
IoT platform and the Lua scripting language.
Figure 2
ESP8266 module
with an analog
multiplexer
(74HC4051 Texas
Instruments)
provides additional
analog inputs to
connect an array of
sensors.
As a very capable processor and communication
module ESP8266 is an intentionally highly compact
design with only a single analog input. While this
may be a limitation in some sensor implementa-
tions it can be resolved with an additional analog-
to-digital converter (ADC) or an analog multiplexer
(Figure 2). However, in most applications there is
no need to up-size the original ESP8266 module,
since most IoT implementations use compact, single-
functionality modules that address a singular sensing
or actuation functionality, such as the monitoring of
temperature and moisture, or an actuation of individ-
ual relays, motors, or lights.
Node-RED: Interfacing with Internet of
Things
Node-RED is an event-processing engine and an
open-source visual editor (Figure 3) for wiring the
IoT developed by IBM. It integrates hardware de-
vices, APIs, and online services in ways easy to inter-
face by lowering technical experience requirements
and allowing developers to focus on creating ap-
plications rather than on coding. It allows for vari-
ous forms of IoT system management without having
an in-depth understanding of underlying technolo-
gies. The Node-RED eco-system uses drag-and-drop
"nodes" that represent components of a larger sys-
tem such as wireless devices, software platforms, and
Web services that are to be connected. It also offers
various functionalities ranging from simple passing
of data payloads or a simple debug to more involved
MQTT client handling or posting HTTP GET requests.
Like many other visual editors, it does not take away
the need for scripting, but it significantly reduces the
need for it.
The Node-RED implementation uses a Web
browser, which is usually hosted in a server such as
a Raspberry Pi module (MQTT broker). It allows for
administration of the entire network (MQTT clients)
without the need to reprogram individual controllers
with sensors and actuators. The management and
controls can be accessed remotely from any Web-
capable device.
Figure 3
Node-RED: visual
editor with
interconnected
nodes allows for
easy management
of a large number
of IoT devices,
services, and
programs.
686 |eCAADe 34 - TOWARDS SMARTER CITIES | Concepts and Strategies - Volume 1
Figure 4
Transparent Touch
Interface project
using a rigid and
flexible base
focused on
embedding smart
systems into the
conventional
building materials.
PLUG-AND-PLAY BUILDING ASSEMBLIES
A critical aspect of future embedded assemblies is
a plug-and-play (PnP) architecture of building com-
ponents. What we have come to expect from com-
puters and electronic devices is their ability to in-
terface with other objects without a need for sig-
nificant user involvement or understanding of tech-
nology. The same should apply to building com-
ponents, their ability to get connected and inte-
grated into an overall framework of a smart build-
ing. A window, or any other building component,
should be able to localize itself and recognize its
role within the overall building, as well as its perfor-
mance and users' expectations toward it. The history
and building knowledge should be passed to, or at
least accessible to, newly installed components for
self-configuration and performance optimization. In
this instance, mass-produced building components
would need to be localized and reconciled within
their assembly, respond to their physical and spa-
tial configurations-windows facing south may need
to perform differently than those facing north-and
understand regional and microclimatic conditions.
Thanks to embedded technologies, generic manu-
factured building components would adapt to local
circumstances and acquire highly specialized proper-
ties, possibly hard-reconfiguring their original com-
position.
An important part of these embedded systems
will be an integration of wireless communication
with a localization protocol, possibly using RFID/NFC
tags and energy sources or storage. While this may
seem like a lot packed into a window or an individual
building component, current material research sup-
ports future implementations of these designs. For
example, translucent lithium-ion batteries charged
with sunlight, developed by researchers at Stan-
ford University [8,9], could be integrated into glaz-
ing or frit panels and provide the necessary energy
to power embedded components. However, glazing
and other visually present components need to sat-
isfy not only technological but also aesthetic and user
experience considerations. Skeletouch, developed
by Hiroyuki Kajimoto (2012), is an example of hep-
tic/tactile display that uses transparent glass plate
with electrodes to provide a tactile feedback to users.
While this particular project implements the tactile
display as an overlay to a smartphone's video dis-
play, the same technology could be applied to build-
ing glazing as part of building user interface. A sim-
ilar investigation was part of the Transparent Touch
Interface project (Figure 4) that looked into devel-
oping transparent and flexible printed circuit board
(PCB)-like components that would respond to touch
using an MPR121 capacitive sensor controller mod-
ule driven by an I2C interface (Figure 5).
TOWARDS SMARTER CITIES | Concepts and Strategies - Volume 1 - eCAADe 34 |687
Figure 5
A capacitive sensor
controller
integration with a
mirror as a possible
user interface (UI)
for IoT applications.
Figure 6
Temperature
sensing LED faucet;
an example of
building user
interface.
MACHINE LEARNING
To optimize user comfort, minimize operational cost,
and adapt to occupant needs, smart buildings must
rely upon sophisticated tools for intelligence behav-
ior and performance such as learning, anticipation,
and decision making. These predictions can only be
based on past behavioral and occupancy patterns
and on occupants' interaction with sensing devices
such as motion detectors, light controls, or video
monitors.
Then recorded data can be used to build sophis-
ticated statistical models that can be used in predic-
tion algorithms.
BUILDING AS DYNAMIC INTERFACE
While distributed sensor systems provide a dense
network of data input points, the same channels of
communication can be used to actuate and inter-
face with building occupants. Embedded systems
not only provide localized intelligence in materials
and objects but, more importantly, can serve as an
informational and control interface: an interface that
provides on-demand functionalities and contextual-
izes knowledge. This is evident not only in the Trans-
parent TouchI nterface and Skeletouch projects men-
tioned earlier, utilizing touch-based inputs or tactile
feedback, but also in many current consumer prod-
ucts, such as LED faucets and showerheads relating
water temperature to light color (Figure 6), with em-
bedded devices providing users with the relevant
feedback.
While smart environments-buildings and cities-
are initially intended to increase performance and
efficiencies (Nakama et al. 2015) as well as to en-
hance user experience, there are many other side
benefits to technologies deployed in smart environ-
ments. Sensing and actuating technologies em-
bedded into buildings are compatible and can in-
terface with autonomous mobility agents, not only
providing navigational clues but also facilitating au-
tonomous wheelchair driving. Similarly, the local-
ization techniques that are used to track and inter-
act with building occupants can also be deployed
to assist nonhuman robotic agents during building
construction and post-occupancy phases (Schwartz
2015).
ESP8266: CASE STUDIES
A number of the technologies discussed above were
implemented and tested in adaptive façade and
building assembly prototypes developed as part of
academic and research work at the New Jersey In-
stitute of Technology (NJIT) (Figure 7). While ini-
tially a number of "smart" prototypes used Arduino
microcontrollers to interface sensors and actuators,
and for data communication, it quickly became ev-
ident that for some of the projects a more robust
microcontroller eco-system with wireless communi-
cation would be required. A number of projects
adopted the ESP8266 chip for its integrated micro-
controller and WiFi capabilities. Most of the projects
used a small number of controllers (3-4) but one
of the projects tested twelve concurrently reporting
ESP8266 units continuously connected and access-
ing outside Internet services with a minimal band-
688 |eCAADe 34 - TOWARDS SMARTER CITIES | Concepts and Strategies - Volume 1
Figure 7
Adaptive façade
and building
assembly
prototypes
developed as part
of academic and
research work to
test embedded
systems. From the
left: Adaptive
Facade 1 and 2,
Algae Bio-Facade,
and Adaptive Media
Facade projects.
width impact on the WiFi network. During heavy
data transfers on the same WiFi network (large file
downloads and uploads) module connection time-
outs would be a common occurrence with no effec-
tive data transfer between modules and the cloud
database. While this could be associated with a data
loss, these situations could have been resolved with
additional code establishing protocols that would
verify received communication. In the context of the
research projects, this was not necessary since any
unreceived data from environmental sensors (light,
temperature) would have been updated within a
short period of time. An important finding was that
once the WiFi bandwidth became available again,
ESP8266 modules were able to resume the commu-
nication with no impact on the functionality or sta-
bility of the system. Similar tests with Arduino Uno
and Ethernet Shield showed that connection time-
outs often resulted in an unresponsive module and
the need to reboot a microcontroller.
While client reporting of sensor data may be in-
frequent (every couple of minutes) the connection to
clients handling various actuators may require much
faster response time particularly when a human in-
put is involved. This need is further compounded
considering the pull nature of client communication
protocol implemented in discussed prototypes-data
could not have been pushed into a client, only a
client could have pulled it by establishing a connec-
tion. To reduce the time between data pullings, the
client would have to be continuously or frequently
connected to the network, which could impact net-
work efficiency. Again, this configuration was tested
with twelve ESP8266 modules. The results showed
a highly reliable configuration with only occasional
communication interactions, which resulted in a cou-
ple of seconds' delay of the actuation time of one of
the modules.
One of the embedded prototype projects re-
quired several analog inputs. To extend a basic
ESP8266 module a shield was designed with a 12-bit
ADC (Figure 8) that allowed for greater precision in
Figure 8
ESP8266/WeMos D1
Mini shields
developed as part
of the Adaptive
Building
Componentes at
NJIT to extend and
augment base
module
functionalities: (A)
sensor and servo
extension shield, (B)
12-bit ADC shield
extends a number
of analog inputs
and increases the
range of values to
12 bits, and (C) a
motion (PIR),
temperature
(DHT22), and
illumination level
[Lux] (TSL2561)
sensor shield.
Gerber file and
additional info at
emergentmat-
ter.org.
reading analog inputs 4096 (2ˆ12) as compared to
Arduino's 1024 (2ˆ10) values. This is particularly
useful with very precise measurements or in cases
when one would like to cover a wide range of val-
ues as would be the case in measuring noise levels
and mapping them to decibels (dB)-another research
project currently underway in the lab.
Only some of the projects that implemented the
ESP8266 chipset with WiFi communication used a
Node-RED implementation with Raspberry Pi. The re-
mainder deployed a conventional WiFi network con-
nected to the Internet and HTML/PHP connections
to MySQL databases. The majority of the projects
TOWARDS SMARTER CITIES | Concepts and Strategies - Volume 1 - eCAADe 34 |689
stayed within the HTML/PHP and MySQL platform
partially for a legacy reasons and partially to provide
a parallel testing environment to compare ESP8266
and Arduino Uno with Ethernet Shield implementa-
tions.
CONCLUSION
This paper and the projects discussed therein inves-
tigate strategies to shift from individual smart object
or smart assembly implementations to orchestrate
larger intelligent systems for architectural applica-
tions. This means, in most cases, leaving behind the
familiar territory of Arduino and getting involved in
interfacing various building systems and assemblies,
integrating them with databases and mining data
with machine learning algorithms. While this may
feel like stepping outside of established notions of
architecture, embedded systems provide new tools
to redefine human-made environments and design
more efficient and resource-considerate buildings.
ACKNOWLEDGEMENTS
The following projects are the research contributions
from NJIT students:
1. Transparent Touch Interface project devel-
oped by Anthony Samaha (Figures 4 and 5)
2. Adaptive Façade 1 developed by Jorge Cruz,
Alan Mera, and Carlos Rodrigues (Figure 7 left)
3. Adaptive Façade 2 developed by Daniel Bel-
tran and Patryk Kleba (Figure 7 second from
the left)
4. Algae Bio-Façade developed by Samantha
Bard, Mary Lopreiato, and Libertad McLellan
(Figure 7 center panel)
5. Adaptive Media Façade developed by An-
thony Morrello and Anthony Samaha (Figure
7 right panel)
6. ESP8266 shields designed by George Hahn
(Figure 8) supported by a Facutly Seed Grant
from NJIT.
Additional information about discussed projects in-
cluding a PCB designs and Gerber file with can be ac-
cessed at www.emergentmatter.org
REFERENCES
Achten, H 2015 'Closing the Loop for Interactive Archi-
tecture - Internet of Things, Cloud Computing, and
Wearables', Proceedings of eCAADe 2015
Das, S and Cook, D 2005 'Designing Smart Environments:
A Paradigm Based on Learning and Prediction', in
Pattern Recognition and Machine Intelligence: PReMI
Guillemin, A and Morel, N 2001, 'An innovative lighting
controller integrated in a self-adaptive building con-
trol system', Energy and Buildings, 33(5), p. 477–487
Kajimoto, H 2012 'Skeletouch: Transparent Electro-
Tactile Display for Mobile Surfaces', Proceedings SA
'12 SIGGRAPH Asia 2012 Emerging Technologies, Arti-
cle No. 21, ACM New York, NY, USA
Kortuem, G, Kawsar, F, Fitton, D and Sundramoor,V 2010,
'Smart Objects as Building Blocks for the Internet of
Things', IEEE Internet Computing, 14 (1), p. 44–51
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of Building Information Management System with
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ite', International Journal of Architectural Computing,
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[1] www.siemens.com/energyefficiency
[2] www.bigbelly.com/solutions/stations/
[3] www.bizjournals.com/bizjournals/how-to/technolo
gy/2015/04/the-internet-of-things-is-transfor
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[4] www.mqtt.org
[5] www.zdnet.com/article/m2m-and-the-internet-of-t
hings-how-secure-is-it/
[6] www.lora-alliance.org/
[7] www.nodemcu.com/index_en.html
[8] www.nature.com/news/2011/110725/full/news.2011.
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[9] www.technologyreview.com/s/424802/a-battery-
you-can-see-through/
690 |eCAADe 34 - TOWARDS SMARTER CITIES | Concepts and Strategies - Volume 1
... An open source framework and relatively low technological expertise entry point make these tools highly effective in architectural research and prototype development. This can be seen in a number of academic research projects with an active student engagement (Figure 1), such as adaptive facades (Zarzycki 2016) or the Sensing Wall (Zarzycki 2017) developed a sensing building skin for real-time building performance monitoring. The sensing wall relied on an array of thermistors (heat sensors) and used wireless communication protocols to transfer and real-time visualize data. ...
... On the hardware side, it utilizes force sensing resistors and RFID shields/tags to measure and keep track of dishes (Figures 3 and 4). These examples relate and are directly applicable to the plug-and-play (PnP) building assembly concept (Zarzycki 2016) and are analogous to technologies used to power adaptive façade prototypes discussed in the same paper. ...
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... On a short distance of up to 10 m, most IoT hardware, smartphones, and tablets implement the Bluetooth classes 2 or 3 to be connected directly [9]. Standard iBeacons [10,11] have an approximate range of 70 meters for the peer-to-peer Bluetooth low energy (BLE) communication. For longer distances, the client-server and/or wireless mesh network architectures [12] are applied. ...
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... On a short distance of up to 10 m, most IoT hardware, smartphones, and tablets implement the Bluetooth classes 2 or 3 to be connected directly [9]. Standard iBeacons [10,11] have an approximate range of 70 meters for the peer-to-peer Bluetooth low energy (BLE) communication. For longer distances, the client-server and/or wireless mesh network architectures [12] are applied. ...
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Full-text available
Over 253 million people across the world today are estimated to be blind or visually impaired. White canes and guide dogs remain the most preferred methods of aid despite the availability of smart technologies and over a hundred assistive electronic devices developed within the last three decades. The main sticking points are unaffordability, implementation of different technologies in one device, and integration with the existing network. The developed assistive device is designed to overcome these obstacles. It is low-cost and priced competitively at USD 70. It is based on the palm-sized computer Raspberry Pi 3 B with Pi camera and ultrasonic sensor HC-SR04, and it features MQTT IoT protocol allowing it to communicate with other intelligent eHealth agents. The basic functionalities of the device are measurement of the distance to the nearest obstacle using the detector HC-SR04 and recognition of human faces by the OpenCV and face recognition module of Adam Geitgey. Objects and places around the B&VI are indicated by the Bluetooth devices of classes 1-3 and iBeacons. Intelligent eHealth agents cooperate with one another to efficiently route data from/to clients in the smart city mesh network via MQTT and BLE protocols. The presented soft-/hardware was successfully tested and accorded a score of 95.5%.
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Skeletouch: Transparent Electro- Tactile Display for Mobile SurfacesSmart Objects as Building Blocks for the Internet of Things
  • H Kajimoto
  • G Kortuem
  • F Kawsar
  • Sundramoor Fitton
Kajimoto, H 2012 'Skeletouch: Transparent Electro- Tactile Display for Mobile Surfaces', Proceedings SA '12 SIGGRAPH Asia 2012 Emerging Technologies, Article No. 21, ACM New York, NY, USA Kortuem, G, Kawsar, F, Fitton, D and Sundramoor, V 2010, 'Smart Objects as Building Blocks for the Internet of Things', IEEE Internet Computing, 14 (1), p. 44–51
Humanoids 'Performing' Manufacturing
  • M Schwartz
  • R Frias
  • Dolgener Cantu
  • Stoffel Saul
  • J Park
Schwartz, M, Frias, R, Dolgener Cantu, E, Stoffel Saul, G and Park, J 2014 'Humanoids 'Performing' Manufacturing', Proceedings of Workshop on Humanoid Robots and Creativity at IEEE-RAS, Humanoids 2014
Designing Smart Environments: A Paradigm Based on Learning and Prediction' , in Pattern Recognition and Machine Intelligence: PReMI Guillemin, A and MorelAn innovative lighting controller integrated in a self-adaptive building control system
  • S Das
  • D Cook
Das, S and Cook, D 2005 'Designing Smart Environments: A Paradigm Based on Learning and Prediction', in Pattern Recognition and Machine Intelligence: PReMI Guillemin, A and Morel, N 2001, 'An innovative lighting controller integrated in a self-adaptive building control system', Energy and Buildings, 33(5), p. 477–487
Skeletouch: Transparent Electro-Tactile Display for Mobile Surfaces
  • H Kajimoto
Kajimoto, H 2012 'Skeletouch: Transparent Electro-Tactile Display for Mobile Surfaces', Proceedings SA '12 SIGGRAPH Asia 2012 Emerging Technologies, Article No. 21, ACM New York, NY, USA