MUETSenses: A Wireless Sensor NetworkBased Indoor Environment Monitoring System

Baloch J A, Ahmed S, Shigrii S, Bhatti J RDepartment of Computer Systems Engineering

Mehran University of Engineering & Technology, Jamshoro, Sindh, Pakistan.Email: javed.baloch@faculty.muet.edu.pk

Abstract— A novel approach to the design of a WirelessSensor network (WSN) based indoor environment moni-toring system, which parses data in real time, on demandand periodically is presented. The aim of this system is tomonitor indoor environment remotely, through an androidapplication. The system comprises of Crossbow Iris motes,MTS 400 Sensor board, MIB 520 data accusation boarddesigned by UC Berkley and Intel, and a base station tomonitor environmental parameters such as light, pressurehumidity and temperature. The system exploits mote viewsoftware to acquire data from the wireless sensors network.At the back-end, a database has been developed to loadthe data from mote view and the system pushes data fromthe database to an android application designed for thesystem. The system enables users to monitor the indoorenvironment parameters on their android smartphones.

Index Terms— Indoor Environment Monitor-ing;Wireless Sensor Network and Android.

I. INTRODUCTION

Wireless Sensor Networks (WSNs) typically com-prise of a large number of sensor nodes. Every sensornode is connected to a single or several nodes tosense attributes of the phenomena. A sensor node hasa number of components an electronic circuit, whichinterfaces the battery source, a radio transceiver anda micro controller. Sensor nodes may vary in sizedepending on the application they are used in. WirelessSensor Networks could be deployed on a large scale for,monitoring environment, over a battlefield for militaryreconnaissance and surveillance, in open environmentsfor rescue and search operations, for condition basedmaintenance in factories, for infrastructure monitoringin buildings, and at medical centers for health moni-toring. To deploy sensor nodes several schemes maybe selected from uniform regular deployment of sensornodes to irregular random deployment of nodes. Themobility of nodes could be stationary or the nodescould be mobile or a combination of both. Sensor nodesare assumed to be self configurable by nature, which

enables sensor nodes to maximize the network lifetime.In a standard setting, users could get information froma Wireless Sensor Network by inserting queries andcollecting results from the base station, which worksas an interface between the users and network [1].

Wireless sensor networks is an emerging area, re-search is being carried out world wide for the expansionand implementation of such networks in nearly everywalk of life. Extensive research has been conducted onthe constraints of WSNs that are the limited resources.The research aims to present a wireless sensor networkbased indoor environment monitoring system.

II. RELATED WORK

Environmental monitoring has been carried out con-ventionally, employing a limited number of expensiveand accurate sensing units.The results of such systemswere retrieved straight from the sensing units. WirelessSensor networks provide an alternate solution, wherea large number of sensor nodes is deployed. Althoughindividual nodes have low precision, the network on thewhole has far better spatial resolution, with immediatelyaccessible data [2]. A sensor network comprises ofsensor nodes, densely deployed either very close to thephenomenon or inside it. The low cost, flexibility, faulttolerance, high sensing fidelity and rapid deploymentfeatures of WSNs generate several exciting applicationareas for remote sensing [3].

A large number of environmental monitoring projectshave been completed so far. Research has been car-ried out employing WSNs to observe very hostile anddangerous environment of the Tungurahua volcano. Re-searchers positioned a sensor network inside the volcanoto observe the volcanic eruptions employing acousticsensors of low frequency, data of 54 hours was gathered[4]. The LOFAR project [5] exploits WSNs for precisionagriculture. The initial research conducted on largescale applications, of WSNs in the area of EnvironmentMonitoring was the Great-Duck Island [6-7] a projectof the university of California Berkley, United States ofAmerica.

ISAP2015 Copyright (C) 2015 IEICE888

A. Outdoor environmental Monitoring

Outdoor monitoring applications typically includehabitat monitoring, hazardous chemical detection, earth-quake detection, monitoring traffic, volcano eruptions,weather forecasting and flood detection. Sensor net-works are now being immensely used in precisionagriculture. Monitoring the temperature and moistureof the soil is among the most significant application ofWSNs in agriculture. Environment monitoring, forecast-ing and warning of landslides are an essential feature,for saving lives and assets from devastation. There arethree fundamental ways for monitoring the landslide,visual, surveying and instrumentation [8].

B. Indoor Environmental Monitoring

Indoor monitoring applications generally includemonitoring of offices and buildings. Such applicationsinvolve sensing light, temperature, humidity and airquality. Mostly Zigbee protocol is used in indoor net-works for connecting motes and sending data, becauseof its lower power consumption.

III. SYSTEM DESCRIPTION

Work places and buildings expose the inhabitants to avariety of environmental factors including heat, pressureand humidity, which need to be monitored closely asthey may pose a serious threat. The existing systems areweb based, complex in nature and unscalable. Mobileplatforms are moving at a tremendous pace and manymanufacturers are opting for mobile applications formost of their products. MUETSenses aims to deliver,an economical, scalable system that could be deployedwith ease. The system employs programmed motes, abase station, a server and an android device.

A. System Architecture

The system architecture of MUETSenses is shownin Figure 1. The System comprises of sensor nodes,base station and a server. Sensor nodes are programmedthrough NesC language and mesh topology is usedbetween motes for sharing and sending data. The Zigbeeprotocol is used between motes as it has efficientprocessing. The base station gets the data from all themotes. The base station is responsible for forwarding thedata to the server where the data is processed. The endusers could access the processed data available at theserver from the android application on their handhelddevices.

B. Hardware Description

The hardware used in this project for monitoringenvironment includes Iris motes MTS 400, SensingBoards and Mib520 Data acquisition board. Iris moteswere used for collecting data from the sensor boards.

Fig. 1. System Architecture

MTS 400 sensing boards on which different sensors aremounted were used for sensing environmental param-eters, MIB 520 data accusation board was used as thebase station, where all sensors send data and MIB 520was responsible to send data to database.

C. Software Description

The entire project is based on software platforms andprogramming languages. The platform and program-ming languages include:

• Mote Config• Mote view• Eclipse• NesC• Java• Php MyAdminMote config was used to load programs in motes. The

NesC language was used for programming the sensorsand visualizing the data coming from different typesof sensors. The Mote view software was used for thetransmission of information to the server. The designand the implementation of the android application, wascompleted on the Eclipse IDE. Java was used for codingand PHP MyAdmin managed the data stored in thedatabase.

IV. INTERFACING

Sensors are sophisticated devices that are used tosense and measure the non-physical elements. Differenttypes of sensors are used for measuring a range ofparameters, which are converted into electrical signalfor further processing. Sensors are required to have ahigh accuracy as a marginal error may have an extremeeffect. Sensors could be classified in different groupsbased on their nature and functionality. A number ofsensors could be mounted on a single board.

Iris motes are used in this project. The IRIS moteis a 2.4 GHz module, used to deploy a low-power

889

Fig. 2. Interfacing Motes

wireless sensor networks. The motes feature numerousnew capabilities that enhance the functionality ofwireless sensor networks. The motes are required to beprogrammed for operation. There are two methods forprogramming the motes.

• Local programming• Remote programming

In this project motes are programmed using the tech-nique of local programming. The MTS400 sensor wasintegrated with IRIS mote and readings were observedthrough the base station, which was connected to thehost PC. The interfacing is shown in Figure 2, the basestation and sensor node is shown and the usb port showsthe connectivity to the server.

V. RESULTS & DISCUSSION

Sensor nodes were deployed in the department ofComputer Systems, Mehran University, Pakistan at dif-ferent locations to sense a range of environmental fac-tors. Environmental factors including temperature, pres-sure and humidity were monitored employing MUET-Senses.

In Figure 3. the network topologies of sensor nodesplaced in the laboratories are shown. In Figure 4(A),Figure 4(B) and Figure 4(C) the data obtained from sen-sors is shown in the form of histograms. The histogramssummarize the distribution of sensors data. The x-axisshows the data and the y-axis shows the percentagefor the instances for each sensors values. In figure 4(a)different values of temperature are present on the x-axis,which sensors sensed during a given time interval ofnode deployment and y-axis is shows the percentage ofparticular values occurring in a time interval. Variationsoccur in the histogram as a result of the continuouschange in the temperature. The histogram shows the

Fig. 3. (a) Humidity topology (b) Pressure topology (c) LightTopology (d) Temperature Topology

Fig. 4a. Temperature Histogram

Fig. 4b. Pressure Histogram

Fig. 4c. Humidity Histogram

890

Fig. 5. Android Application

Fig. 6. Sensor’s result

value in a particular instance and irregularity in theenvironment could be observed. The peak values showsthat particular value of temperature is observed in mostof the deployment time. Similarly In figure 4(b) and4(c) pressure and humidity graphs are presented whichshow the variation in pressure and humidity of theenvironment. The variations in color represent the valueof sensors deployed in various places. Figure 5. showsthe user interface of the android application and Figure6. shows the data obtained on the android application,which is the novelty of the system. The applicationdisplays the environmental conditions of the locationwhere sensors nodes were deployed.

VI. CONCLUSION

MUETSenses: A Wireless Sensor Network BasedIndoor Environment Monitoring System has been devel-oped successfully by using Crossbow sensor kit. Sensornodes were deployed in labs of computer system de-partment to sense a range of environmental parameterssuch as light, humidity, pressure and temperature. Priorto deployment the sensor nodes were programmed and

configured. Mote View software was used to visualizethe histogram, chart, scatter plot and topology of thesensor nodes. Through the android application it ispossible to monitor the environment remotely, providedan internet connection is readily available. The appli-cation is capable to show the different environmentalparameters and cater to the needs of the end user.

VII. FUTURE WORK

A range of features may be added to the applicationsuch as smart alerts, notifications that appear when aset threshold is reached and haptic feedback could alsobe introduced. The sensor nodes may be programmedto control the environment as well as monitoring it.

This system could also be made energy efficient byprogramming the sensor nodes in such a way that thesensor nodes remain in sleep mode and sense data onlywhen required. The introduction of this feature couldincrease the network lifetime of the sensor nodes.

REFERENCES

[1] Chung W., Oh S., 2006, “Remote monitoring systemwith wireless sensors module for room environ-ment”, Sens. Act. B: C Chem, 113, 6470.

[2] Huang, H., Xiao, S., Meng, X., and Xiong, Y., “ARemote Home Security System Based on WirelessSensor Network and GSM Technology”, Proceed-ings of 2010 Second International Conference onNetworks Security Wireless Communications andTrusted Computing (NSWCTC), Vol. 1, April 2010.

[3] Ian F. Akyildiz, Weilian Su, Yogesh Sankara sub-ramaniam, and Erdal Cayirci, “A Survey on Sen-sor Networks”, Communication, Magazine, IEEE,40(8):102-114, August 2002.

[4] Werner-Allen, G., Johnson, J., Ruiz, M., Lees, J.,Welsh, M.,“Monitoring volcanic eruptions with awireless sensor network”, In 2nd European Work-shop on WSNs, pp. 108-120, 2005.

[5] Baggio, A., “Wireless Sensor Networks in Preci-sion Agriculture”, In ACM Workshop Real-WorldWSNs, 2005.

[6] A. Mainwaring, D. Culler, J. Polastre, R. Szewczyk,and J. Anderson, ”Wireless sensor networks forhabitat monitoring”,Proceedings of the 1st ACMinternational workshop on Wireless sensor networksand applications, pp. 8897, 2002.

[7] R. Szewczyk, A. Mainwaring, J. Polastre, J. An-derson, and D. Culler, “An analysis of a largescale habitat monitoring application” in Proceedingsof the 2nd international conference on Embeddednetworked sensor systems, pp. 214226, 2004

[8] Lynn, M. and Bobrowsky, P. “The landslide hand-book - A guide to understanding landslides”, Re-ston, Virginia, U.S. Geological Survey 2008.

891