BubbleSense:Wireless Sensor Network BasedIntelligent Building Monitoring

Cheng Li1, Forrest Meggers3, Mo Li1, Jithendrian Sundaravaradan2

Fei Xue2, HockBeng Lim2, Arno Schlueter4

1SCE, Nanyang Technological University, Singapore{cli6, limo}@ntu.edu.sg

2Intellisys Laboratory, Nanyang Technological University, Singapore{Jithendrian, XueFei,limhb}@ntu.edu.sg

3LowEx Module, Singapore ETH Center, Singaporemeggers@arch.ethz.ch

4ITA, ETH Zurich, Switzerlandschlueter@arch.ethz.ch

ABSTRACTBuildings consume a great amount of energy. The sustain-ability requirement asks for more efficient energy usage. Thefirst step towards energy efficiency is to understand in de-tail how, when, and where energy is consumed in buildings.Advances in Information and Communication Technologies(ICT), especially the embedded sensing and wireless com-munication techniques, enable an intelligent building mon-itoring for such an understanding. In this paper, we de-sign and deploy a wireless sensor network based monitoringsystem in a building test-bed, composed of two containers(named BubbleZERO). We deploy a variety of sensors, in-cluding temperature, humidity, flow-rate, and CO2 concen-tration sensors, to monitor our new energy efficient HeatingVentilation and Cooling (HVAC) system. We develop a datamanagement system to manage and distribute the harvesteddata to all subscribed users. The system has an user-friendlyweb based interface. Users can access, retrieve, downloadand visualize the data from their internet browsers.

KeywordsBuilding Sense System, Sustainability, Data Management

1. INTRODUCTIONTowards green and sustainable living environments, the en-ergy issue has drawn people’s great attention in the pastdecades. As a major resource consumer, buildings consumea large portion of energy. According to [15], 41% of the en-ergy has been consumed to power different types of facilitiesin buildings in U.S. and the percentage is predicted to in-crease to 45% until 2035. Although a large volume of energyis used for buildings, a survey from U.S. Energy Information

ICT4S 2013: Proceedings of the First International Conference on Infor-mation and Communication Technologies for Sustainability, ETH Zurich,February 14-16, 2013. Edited by Lorenz M. Hilty, Bernard Aebischer,Göran Andersson and Wolfgang Lohmann.DOI: http://dx.doi.org/10.3929/ethz-a-007337628

Administration [16] reports that at least 30% of the buildingenergy usage is wasted. Research studies in [9] suggest thatthe wasted energy could be even more.

In this study, we aim at understanding the limitations ofexisting energy control systems and further develop a moreefficient and sustainable one for the future buildings. Ac-cording to [15], almost half (47%) of the building energy isconsumed for the space temperature control. Therefore, asa pioneer work, we narrow down the energy efficiency designfor the space cooling system in this paper, while the designprinciple can be easily extended for other components of thebuilding.

To approach an energy efficient design, we rely on fine-grained sensory data harvested from the target space. How-ever, sharing a large amount of data, especially in a real-time manner, can be very difficult. Copying data around issurely neither convenient nor efficient. Uploading data toa public server might be a better solution, yet it enforcesusers to retrieve the interested data from a big dataset. Amore intelligent control system needs to organize, store, re-trieve, distribute, and visualize data efficiently and auto-matically. In this study, we deal with the above issue fromfollowing two aspects: the tightly integrated wireless sens-ing and intelligent data management and presenting. Moreprecisely, we build a Wireless Sensor Network (WSN) thatis tightly integrated with various energy consuming devicesand deploy the WSN in a fully configurable test-bed, calledBubbleZERO, composed of two standard containers. Bub-bleZERO is completely configurable and contains a lot ofnew energy efficient facilities inside. To share sensory datato various subscribed groups, we design a data managementframework to achieve instant data distribution. We pushthe harvested data to a data management server and storethem in a well designed database system. We develop anuser-friendly web page based interface to visualize the data.The framework of our system is shown in Figure 1.

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Wireless Sensor System

Data Management System

Data Users

Figure 1: System architecture

Translating our design principle to a practical system, how-ever, entails a variety of challenges. First, measuring dif-ferent types of devices requires integrating many differentkinds of sensors. For instance, the hydraulic system needsvery accurate measurements of temperature and flow-rateat different places, while environment monitoring needs tomeasure humidity and CO2 concentration. Fusing differentkinds of sensors to the wireless node (mote) requires cus-tomized hardware. Second, the communication efficiencyof sensor nodes needs to be guaranteed as well. Since sen-sor nodes might be densely deployed in the room. In ad-dition, other electronic facilities, e.g., Wi-Fi devices, mi-crowave stoves, etc., can interfere with the communicationof sensor nodes, the system needs to ensure an efficient andreliable information delivery with minimal communications.Third, uploading data remotely to a data management sys-tem is also non-trivial. The program needs to deal withvarious situations to mitigate the disruptions of the internetconnection.

There have been initial attempts made to the smart build-ings in previous studies. However, they mainly focus onevaluating or improving the performance of existing systems,and there still exists a rich space to further save the energyin buildings. For example, Jiakang et. al. and Varick et. al.try to cut down the energy consumption of HVAC systemfrom 28% to 20% using occupancy sensors [8, 2]. Jiang et. al.design and deploy an energy audit wireless sensor networkin an active laboratory building in University of California,Berkeley [5, 6]. They provide detailed energy consumptionmap of existing electrical devices in buildings. Dawei et.al. develop a green room management system based wirelesssensor network[10]. They focus on saving energy using ther-mal inertia effect and wireless sensor network. Most of thesesystem are based in existing building, and the flexibility islimited. Our work is different from previous works. By tak-ing advantage of the fully configurable test bed and the lowenergy equipments, the wireless sensor system proposed inthis paper is more tightly integrated with the building andcan provide more detailed energy consumption audit and ef-ficiency information of the building system. The introduced

data management module could benefit more and make fulluse of existing sensing resources.

The contributions of this paper can be summarized as fol-lows.

• We design a wireless sensor network integrated with afully configurable building system test bed. The sys-tem is specifically designed to monitor and evaluatethe building system and is capable of providing de-tailed energy information.

• We develop a data sharing framework. The frameworkcan efficiently organize and store sensory data. Datacan be easily distributed to subscribed users, helpingusers to retrieve, download, visualize and analyze data.

• We have experimented with a prototype system, calledBubbleZERO, within our designed modules and hard-ware in two containers of volume around 80m3. Theexperimental results show that BubbleZERO is capa-ble of capturing the energy consumption of devices ac-curately.

The rest of the paper is organized as follows: In Section 2,we introduce some background about our test bed. The ar-chitecture and design details are given in Section 3. In Sec-tion 4, we present some of our initial measurement results.We conclude this work in Section 5.

2. PROJECT BACKGROUNDSpace heating and cooling account for 47% of energy totalconsumption in buildings [15]. Our first task in this projectis to design and test a new HVAC system that uses muchless energy. The control and operation of heating and cool-ing systems in buildings have been developed from very sim-ple origins. If buildings were too cold, heat was added, andif they were too hot, heat was removed. Today these sim-ple techniques to make buildings comfortable are also oneof the culprits that makes buildings such large energy con-sumers. As new technologies are developed to increase theefficiency of buildings, the intelligence of how these systemsare installed and controlled must also be increased.

We are working in collaboration with a team of buildingsystems researchers to evaluate the potential of low exergybuilding systems in the tropical climate. The increase inintelligence of the system is required to evaluate and deter-mine how best to implement the systems. In terms of thesystem concept, low exergy means that the designs considerthe flows of heat in the building along with the temperatureof those flows. The amount of heat flowing is one measureof performance of the system, but the temperatures of thoseflows independently affect the efficiency of the system due tothe 2nd law of Thermodynamics. Therefore, while evaluat-ing the prototype systems in the tropics, the measurementsof temperatures take on an added importance because wewant to optimize not just the adequate heat removal, butalso the temperatures we use to remove the heat.

The heat is removed from buildings using a refrigeration cy-cle. A chiller runs a compressor that cycles refrigerant from

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a low pressure side where heat can be absorbed from a lowertemperature (inside the building) to a higher pressure sidewhere that heat can then be rejected (outside the building).In a typical system design, the chiller components would besized to move the correct amount of heat out of the buildingto make it cool without much consideration for the operatingtemperatures. This is because in the tropics most coolingis done with air. To use air as a cooling medium, it has tobe dehumidified first. The dehumidification process requiresthe air to be subcooled to a point where an adequate amountof water will condensate out of the air, so that when it heatsup inside the building a comfortable relative humidity fromroughly 40-60% is reached. The subcooling process requiresthe chiller to generate cooling below 10 ◦C, and this lowtemperature reduces the system performance.

In our low exergy system design we are trying to find ways toprovide cooling at higher temperatures, which will minimizethe electricity required to supply the cooling. We achievethis by decoupling the cooling process from the air systemsand the required dehumidification. The cooling load is metby a chilled water circuit that provides cooling at 18 ◦Cthrough a cooling panel with a large surface area. It is stillnecessary to supply fresh air to the building users, and thisair must still be dehumidified at a lower temperature, butthe amount of air is independent of the cooling demand andcan be optimized. But in order to optimize the system op-eration for the tropics we need to measure the performancecharacteristics.

In order to evaluate the operation of the fresh air deliveryand the independent cooling panel, there are many vari-ables that must be measured. The goal is to supply theright amount of fresh air for the users, so we must knowhow many users there are. We must also make sure the airsupplied is properly dehumidified so that any risk of humidair infiltration is mitigated. This is a significant risk becausewith no dehumidification, the cooling panel at 18 ◦C is stillbelow the dew point of typical air in the tropics of around25 ◦C, which means that there will be condensation on thepanel and water could fall from the surfaces on the ceiling.Therefore we need accurate measurements of the air tem-perature and humidity as well as methods to consider thepotential of infiltration in the system.

We have constructed an experimental building and labora-tory, BubbleZERO, where we are testing the prototype lowexergy technologies in Singapore. To operate and evaluatethe systems we have designed an intelligent wireless sensornetwork. This network will be used extensively to measurethe performance of the prototype systems in the laboratory,but as a fully modular wireless network, it can be easilyscaled back for demonstration in the first pilot projects.The BubbleZERO cooling system is made up of a chillerwith two water storage tanks, two sets of radiant coolingpanels and four decentralized air supply units. There arealso a variety of other new systems being tested includingCO2 steered exhaust vents, integrated LED lighting, andspecial LowE coated glazing. The performance of all theseintegrated systems can be steered and measured with wire-less sensor technology. We present in this paper a novelimplementation of such a sensor network along with datacollection and management system for our low exergy high

AirBox Driver

AirBox Driver

AirBox Driver

AirBox Driver

CO 2

Flap

CO 2

Flap

CO2

Flap

CO2

Flap

Hydraulics Sensing

SystemAirbox Sensing system

Environment Sensing

System

Data Collection

System

Temp

erature

Senso

rs

Flow

Rate

Senso

rs

Basic Unit:

Telosb

Figure 2: Sensor deployment

performance building system.

3. SYSTEM DESIGN AND IMPLEMENTA-TION

In this section, we begin with an overview of the system.Then we provide an description of design and implemen-tation of the wireless sensor network system. Finally, weintroduce the design and implementation of the data man-agement system.

3.1 System OverviewTo enable good energy evaluations and energy-efficient build-ing system designs, we design a building monitoring systemcomposed of two parts: Wireless Sensor Network Systemand Data Management System. Wireless sensor networksystem includes various sensors and a base-station. Wirlesssensors are deployed at different places to collect data pe-riodically. Base-station is used to connect the wireless sen-sor network with the data management system. It collectssensor data and transmits to remote data management sys-tem. Data management system stores the received data in aproperly defined data base. It runs at a remote server in theIntelliSys Laboratory in NTU. It also provides a web basedinterface for end users to retrieve, visualize and even anal-ysis the data. Users can get the desired information fromthe web browser. The whole system archtecture is shown inFigure 1.

3.2 Wireless Sensor Network SystemAs discussed earlier in Section 2, our low-exergy based cool-ing system uses water instead of air as the main coolingmedium. The dehumidification process is separated fromcooling process by using some specially designed air han-dling unit-Airbox. Complex hydraulic system is deployedin our BubbleZERO to enable proper function of those newdevices. To run those systems properly and to evaluate theirperformances, specially designed sensing system is needed.The key challenge here is to design a highly accurate, lowcost yet very flexible sensor system. The sensor system needsto be tightly integrated with various devices and building op-erating systems in the test bed. To address these problems,we design a wireless sensor network system. The basic unit

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(a) System architecture

Pumps Flow Sensors Temperature Sensors

(b) Real system layout (c) Sensors and interfaceboards

Figure 3: Hydraulics measurement system

we use to build the system is the open source wireless sensorplatform Telosb [11]. Thanks to the miniature property, wecan easily integrate these Telosb motes with various kinds ofdevices. The event driven open source sensor operating sys-tem TinyOS running on Telosb ensures the energy efficiencyand network flexibility. The low power property enablesour sensor motes to operate continuously for several monthswithout changing batteries. The IEEE 802.15.4 standardbased wireless communication module on the motes enablesa wireless intercommunication, which greatly cuts down thedeployment cost and enables a good scalability. Our wirelesssensor network system is composed of several sub-sensingsystems. Hydraulics sensing system measures the tempera-tures and flow rates of the water in different pipes, as well asenables the evaluation of the power efficiencies of the ceilingpanel cooling system and Airbox air handling system. Air-box sensing system measures the temperatures and humidi-ties of the input and output air, the fan speeds and the powerconsumptions of the Airboxes. Environment sensing systemmeasures indoor and outdoor ambient parameters which in-clude temperatures, humidities, CO2 concentrations at dif-ferent locations. The data collection system collects andstores the data from different sensing spots. Figure 2 showsour detailed sensor deployment. Each sensor is representedwith a Telosb mote in the figure.

3.2.1 Hydraulics sensing systemHydraulics sensing system measures temperatures and flow-rates of the water circulating in the hydraulics system at dif-

ferent spots. The Low-exergy based cooling suggests savingenergy by providing cooling power at much higher tempera-ture. The implementation of such a system is heavily basedon our hydraulics system, which supplies water to the maincooling devices (the ceiling panels) and the dehumidifyingdevice (the Airboxes). Running and efficiency evaluating ofthose devices require an accurate measurement of the cool-ing medium circulating in the hydraulics system. Accordingto thermal theories, the power supplied to a devices can bederived from:

P =dm

dt· ∆T · Cp (1)

Where dmdt

is the flow rate, ∆T is the temperature differencebetween the supplied and returned water, and Cp is a spe-cific constant of the specific cooling medium (water in oursituation). Thus the challenge here is to accurately measurethe flow-rates and temperatures of the water flow throughpipes. Figure 3(a) illustrates the design of our hydraulicbased cooling system. Cold water is pumped out from theclod tank, mixed with the water returned from the device,then supplied to the cooling device. The cooling devices areceiling panels and Airboxes. Such a design enables a fullycontrol of both temperature and flow-rate of water suppliedto the cooling devices, thus enables the proposed low-exergycooling. Figure 3(b) shows the real system deployed in Bub-bleZERO.

As we can see from equation (1), the temperature measure-ment is very important in the system evaluation. Practicalexperience suggests that ∆T can be quite small when thesystem is running. As a result, the accuracy and consis-tence of temperature measurement matter a lot. On theother hand, sensors need to be cheap for a scale deploymentas well. As the on-board sensor on Telosb is neither accu-rate nor cheap, we should find some new sensors suitablefor our usage. Finally we utilize the ADT7410 tempera-ture sensors (up-left of Figure 3(c)). It is an off-the-shelfcheap digital temperature sensor produced by Analog De-vices. It has a good accuracy and is factory calibrated tobe 0.5◦C accurate[1]. More importantly, the accuracy couldbe further improved by a manual calibration in practice.However, integrating this sensor to the Telosb mote is nottrivial since it uses I2C interface to communicate. We paida lot of efforts to design and develop a customized interfaceboard (down-left of Figure 3(c)). The board is capable tointerface up to 16 ADT7410 temperature sensors that makesthe large scale temperature sensor deployment capable, easyand cheap. An Arm cortex M0 micro-controller is used tointerface the temperature sensors through I2C serial commu-nication. It initializes the sensors, reads the temperaturesand then sends data to Telosb mote through UART port.The Telosb mote then forwards the data to the base stationthrough its wireless module.

Flow-rate is another key parameter in the power evalua-tion. We choose the Vision 2000 flow sensor (up-right ofFigure 3(c)) from Remag to measure the flow-rates. Thesensor suits our usage with good accuracy of ±3% and it’shighly repeatable (repeatability better than 0.5%)[12]. Thesensor has an easy-to-use digital interface. It outputs pulseswith a frequency proportional to the flow-rate. To accom-modate the large number of flow sensors in the system and tointerface these sensors to the wireless sensor network, we de-

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sign and build some specialized interface boards(down-rightof Figure 3(c)). Each of those boards could interface up to8 flow sensors. Counting the pulse and then calculating thepulse frequency are performed by a ARM Cortex M3 micro-controller on each board. One Telosb mote is connected toeach interface board. Flow-rate data is sent to Telosb motethrough UART serial communication. Data is later trans-mitted to base station wirelessly by Telosb motes. By sodoing, we can connect our flow-rate sensors to the wirelesssensing network.

3.2.2 Airbox sensing systemAirbox sensing system measures the running parameters ofour air handling units-Airboxes. Space conditioning in trop-ical climates can’t be finished without dehumidification. It isbecause outside air is usually too humid that cooling it downdirectly to the desired temperature will cause condensation.For our case, condensation will appear on the ceiling paneland occupants will be unhappy to find their room make rain.Airbox is a novel device we use for dehumidification in ourBubbleZERO. Figure 4(a) shows the structure of the Airboxand how it work. The basic principle we do dehumidificationremains the same with traditional air conditioning systems.That is cooling the air down to sufficient cold temperatureto condensate out the water and get dry air. However, dif-ferent from the traditional way, we use water as the coolingmedium to dehumidify the air. Cold and dry air is suppliedto the room through the outlets of the Airboxes. To run,control and evaluate these Airboxes, sensing at the rightspots is need. Input and output air parameters includingtemperature and humidity should be monitored. The speedof air flow through the Airbox and the power consumptionof the Airbox itself are some other important parameters.Other important parameters such as the temperature andflow-rate of the water flow through the Airbox are measuredthrough the hydraulic sensing system. We choose SesirionSht75 sensor to monitor input and output air of Airbox.This sensor integrates both temperature and humidity sen-sor on a single small package. Its high accuracy makes itsuitable for our usage. It has high accuracy of 0.3◦C for tem-perature and ±1.8% for humidity at room temperature[14].We connect the sensor into the wireless sensor network alsothrough Telosb motes. Each Telosb mote connects to a pairof sht75 sensors which measures both the input and outputair. The fan speed and power consumption parameters arecollected through RS232 interface of the Airbox controller.Some RS232 level conversion boards are developed to inter-face the Telosb to the Airbox controller. Figure 4(b) showsthe sensor deployment of the Airbox measurement system.

3.2.3 Environment sensing systemThe environment sensing system monitors the ambient pa-rameters. The most sensitive indoor parameters for humanbeings are temperature and humidity. Another importantindoor parameter is CO2 concentration. We use the Sht11sensor onboard Telosb to measure temperature and humid-ity parameters. By deploying Telosb motes at different spotsin the test-bed, we provide fine grained temperature andhumidity distribution information. The sensor accuracy is0.4◦C for temperature and ±1.8% for humidity at 25◦C[13].Firgure 5(a) shows the indoor sensor deployment. Batteriesare used to power these Telosb nodes to give the flexibil-ity of mobility. It means the sensors can be move to others

(a) Airbox

Hot and Humid Air

Cold and Dry Air

Hot Water come out

Cold Water go in

Airbox Controller

Input AirSensor

Output AirSensor

(b) Airbox work flow and sensors

Figure 4: Airbox measurement System

(a) Indoor sensor deploy-ment

(b) CO2 flap

(c) Outdoor sensor deployment

Figure 5: Environment measurement system

spots if needed. The CO2 concentration measurement ismore difficult. We use a device called CO2 flap to performthe measurement. The CO2 flap is connected to the Telosbnode through a RS232 communication port. Telosb readsthe temperate and CO2 information and sends it back to thebase station. The posssible usage of CO2 can be on-demandventilation control. Firgure 5(b) shows the connection of theCO2 flap and the Telosb node.

For the outdoor environment monitoring, we measure thetemperature and humidity merely. We hang some Telosbnodes outside the test bed. A special consideration here isto protect the sensor from the sun and rain, since the suncan heat the sensor up, thus leading to the sensing error,while the rain can damage the humidity sensor. Firgure 5(c)shows our sensor protection solution. We firstly put sensorsin an half cut plastic bottle to protect the sensor from therain. Then we cover the bottle with reflective white paperto shade the sensor from the sun. The deployment is just tohang these sensors around our test-bed.

3.2.4 Data collection systemThe data collection system is composed of a Telosb nodeand a laptop (Figure 6(a)). The Telosb node acts as thebase-station for the sensor network. It receives all the sen-

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(a) Airbox (b) Sensor deployment forAirbox

Figure 6: Airbox measurement System

sor data from other nodes and forwards it to the computerthrough a USB connection. Since the test-bed is small, asimple star-topology can be used to organize the sensor net-work (Figure 6(b)). The computer runs a data collectionprogram to communicate with the Telosb node to collectthe data. The program is developed with the C# program-ming language. It has a GUI interface to display the datain real time. At the same time, it also stores the data infiles and uploads data to remote data management system(descried in Section 3.3) through internet.

3.3 Data Management SystemOur key idea of building the data management system is tomake the precious research data to be published to the com-munity. Furthermore, we also want to help users to retrieveand visualize the data such that they could gain some directideas from the graphs. Building such a system, however isnot easy. Challenges are how to design data transfer proto-col to ensure reliability, how to organize and store the dataproperly to support scalability and how to develop the userinterface to enrich user experiences. We present our designin the following subsections.

3.3.1 Data upload to serverData is recorded as log files in the data collection system.Since the data rate is relatively quite slow in our system,setting up a permanent connection to transmit data to theserver in a real time manner is not efficient. We improve theefficiency by buffering and sending data batches to serverperiodically. Thus our problem here is to design a system tosupport reliable batch-files transmission. There are at leasttwo basic methods to upload file to a remote server: (a) us-ing the file transfer service provided by the remote server,and (b) directly manipulating the remote server if remoteaccess is enabled[4]. In our study, the former approach isadopted. In particular, we developed and deployed a PHPbased file transfer service at the server. Our client data col-lection program uploads data by invoking the PHP script.This solution provides great scalability since the server couldsupport a lot of data sources and provides data storage sup-ports for multiple projects. The advantage of using PHPbased data upload is that data can be instantly processedafter been uploaded by some other PHP scripts deployed atthe server. To ensure the data upload reliability, checksumis used to check correctness and retransmission is made iffail happens.

3.3.2 Data storage at server

Figure 7: Database Schema

After data is received, the server needs to store the data ina fine manner. Storing data as files is surely not a choicesince it can be extremely slow to retrieve data from files.A database system is a better option since it’s designed fordata storing, managing and retrieving. Basically data arestored in tables in the database system, therefore, a simplesolution is to store each sensor’s data as one table. How-ever it is not robust enough because the data managementsystem needs to remember which table is corresponding towhich sensor. Once the data management program collapsedfor certain reasons, the system may lose such data relation-ship information and becomes impossible to record new datato original tables. As a result, the challenge is to design arobust and scalable data storage architecture for the scala-bility purpose.

To handle various sensor types and support extensibility tonew types, the data storage design is not tied to any particu-lar sensor type. It is a generic design of the sensor databasewhose sensors may change over time. Sensor types are repre-sented as relations while sensor data are represented as timeseries [7]. Each individual sensor has a unique ID, whichsimplifies the sensor data access queries. The data are ex-tracted in a unified and predefined way. Figure 7 shows ahigh level database schema. It records not only the sensordata, but also the sensor information. Thus, adding a newsensor simply means adding one row in serval tables. Sen-sor data always go to one main table for recording data ofall sensors. The corresponding relationship is preserved inthe relationship of tables. It also makes the data sharingmuch easier. Retrieving data means a SQL request to theDatabase system. As the SQL request can be easily inte-grated to web pages, we could provide easy to use interfaceto users.

3.3.3 Data Sharing and visualizationThe overall goal of our data management system is to sharethe data. To this end, we develope a web based applica-tion to help users retrieve and visualize the interested data.Users can access data just with an internet browser. Fromthe web interface, user can specify which sensor’s data, whattype of data, what interval of data they want. Our web ap-plication takes these inputs and use Structured Query Lan-

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Figure 8: Hydraulics system measurement result

Figure 9: Environment system measurement result

guage (SQL) to request the data from our database. Thereturned data is transformed to graphical pictures by usingthe Google visualization tool[3]. Users can also downloaddata for a further analysis.

4. RESULT PRESENTATIONIn this section, we present some of our initial measurementresults. Our results for the hydraulics and environment sens-ing system are from data collected from a two day experi-ment. In the experiment, we intend to test the performancethe Airboxes. three Airboxes run at their full speeds dur-ing the test period. The data for the Airboxes measurementsystem is from one of our 40 minutes experiments with oneAirbox. In the experiment, we want to find out the rela-tionship between the Airbox fan speed and the output airtemperature.

Figure 8 shows the measurement result of our hydraulics sys-tem. Temperatures for 16 sensors and flow-rates for 9 flowsensors are shown in the figure. At the start of the exper-iment, temperatures and flow-rates change quickly. Aftersome time, they reach stable states and change slowly alongthe time. The temperatures change along time as the cooling

Figure 10: Airbox system measurement result

load changes, while the flow-rates remain almost constant.Figure 9 shows the ambient environment changes within thetwo day. We plot both inside and outside temperatures andhumidities of different spots. We can see that the outdoorenvironment changes a lot during a day. While our indoorenvironment remains somehow constant due to the condi-tioning of Airboxes. On the other hand, we also find thatAirboxes alone cannot provide enough cooling capacity dur-ing the day. The average indoor temperature rises duringdaytime and drops at night. We also measure the CO2 con-centration. The CO2 concentration is high at the beginningof the experiment because researchers stayed in the test-bedat that time. After their departure, the value falls to a lowand constant value.

Figure 10 depicts the test result of Airbox. In this test, weintended to figure out the relationship between the fan speedand the output air temperature of the Airbox. We keep thewater supply constant and change the speed of the fan ofthe Airbox. We collect data from the Airbox measurementsystem. The result shows that the output air temperaturewill increase as the fan speed increases. They follow a linearrelationship. The data can also help us evaluate the energyefficiency of the Airbox.

Figure 11 is the screen snapshot of our data managementsystem. Figure 11(a) shows the web-based user interfacewith which people can specify the interested data by spec-ifying type, date, etc. The visualization result is shown inFigure 11(b). The visualized result can help researchers getsome rough ideas and quickly evaluate the systems. Theycan further be download from the data set for further anal-ysis.

5. CONCLUSIONSensing is essential for understanding existing building sys-tems, testing new building systems and designing sustain-able buildings for the future. In this paper, we design awireless sensor network that is tightly integrated with vari-ous energy consuming devices in our test-bed. The systemoffers fine grained information for researchers to evaluatethe system performance. We also built a data managementframework to publish our data to all interested users. It has

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(a) User interface

(b) Visualized data

Figure 11: Screen Shots of data management systemuser interface

an easy to use web based interface to help users retrieve andvisualization data. In the future, we plan to install morekinds of sensors in the test-bed to provide more aspects ofinformation. On the other hand, we will find the minimumnecessary amount of sensors that enable us to run the systemat the desired performance.

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[16] U.S. DOE Energy Information Administration.Commercial buildings energy consumption survey,September 2012.

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