564 IEEE/ASME TRANSACTIONS ON MECHATRONICS, VOL. 20, …kresttechnology.com/krest-academic-projects/krest-mtech... · 2015. 8. 5. · 564 IEEE/ASME TRANSACTIONS ON MECHATRONICS, VOL

564 IEEE/ASME TRANSACTIONS ON MECHATRONICS, VOL. 20, NO. 2, APRIL 2015

WSN-Based Smart Sensors and Actuator for PowerManagement in Intelligent Buildings

Nagender Kumar Suryadevara, Student Member, IEEE, Subhas Chandra Mukhopadhyay, Fellow, IEEE, Sean DieterTebje Kelly, and Satinder Pal Singh Gill

Abstract—The design and development of a smart monitoringand controlling system for household electrical appliances in realtime has been reported in this paper. The system principally mon-itors electrical parameters of household appliances such as volt-age and current and subsequently calculates the power consumed.The novelty of this system is the implementation of the control-ling mechanism of appliances in different ways. The developedsystem is a low-cost and flexible in operation and thus can saveelectricity expense of the consumers. The prototype has been exten-sively tested in real-life situations and experimental results are veryencouraging.

Index Terms—Energy management, home automation, intelli-gent control system, wireless sensor network, ZigBee.

I. INTRODUCTION

I T is foreseen that service and personal care wireless mecha-tronic systems will become more and more ubiquitous at

home in the near future and will be very useful in assistivehealthcare particularly for the elderly and disabled people [1].Wireless mechatronic systems consist of numerous spatially dis-tributed sensors with limited data collection and processing ca-pability to monitor the environmental situation. Wireless sensornetworks (WSNs) have become increasingly important becauseof their ability to monitor and manage situational informationfor various intelligent services. Due to those advantages, WSNshas been applied in many fields, such as the military, industry,environmental monitoring, and healthcare [2]–[4].

The WSNs are increasingly being used in the home for energycontrolling services. Regular household appliances are moni-tored and controlled by WSNs installed in the home [5]. Newtechnologies include cutting-edge advancements in informationtechnology, sensors, metering, transmission, distribution, andelectricity storage technology, as well as providing new infor-mation and flexibility to both consumers and providers of elec-tricity. The ZigBee Alliance, wireless communication platformis presently examining Japan’s new smart home wireless systemimplication by having a new initiative with Japan’s Governmentthat will evaluate use of the forthcoming ZigBee, Internet Proto-

Manuscript received May 31 2013; revised October 16, 2013; acceptedJanuary 14, 2014. Date of publication February 4, 2014; date of current versionOctober 24, 2014. Recommended by Technical Editor Y. Li.

The authors are with the School of Engineering and Advanced Tech-nology, Massey University, Palmerston North 4474, New Zealand (e-mail:[email protected]; [email protected]; [email protected]; [email protected]).

Color versions of one or more of the figures in this paper are available onlineat http://ieeexplore.ieee.org.

Digital Object Identifier 10.1109/TMECH.2014.2301716

col (IP) specification, and the IEEE 802.15.4g standard to helpJapan to create smart homes that improve energy managementand efficiency [6].

It is expected that 65 million households will equip with smartmeters by 2015 in the United States, and it is a realistic estimateof the size of the home energy management market [7].

There are several proposals to interconnect various domesticappliances by wireless networks to monitor and control suchas provided in [8], [9]. But the prototypes are verified usingtest bed scenarios. Also, smart meter systems like [9]–[11] havebeen designed to specific usages particularly related to geo-graphical usages and are limited to specific places. Differentinformation and communication technologies integrating withsmart meter devices have been proposed and tested at differentflats in a residential area for optimal power utilization [12], [13],but individual controlling of the devices are limited to specifichouses.

There has been design and developments of smart meterspredicting the usage of power consumption [9]–[13]. How-ever, a low-cost, flexible, and robust system to continuouslymonitor and control based on consumer requirements is at theearly stages of development. In this study, we have designedand implemented a ZigBee-based intelligent home energy man-agement and control service. We used the ZigBee (the IEEE802.15.4 standard) technology for networking and communi-cation, because it has low-power and low-cost characteristics,which enable it to be widely used in home and building envi-ronments [10].

The paper focuses on human-friendly technical solutions formonitoring and easy control of household appliances. The in-habitant’s comfort will be increased and better assistance can beprovided. This paper emphasizes the realization of monitoringand controlling of electrical appliances in many ways.

The developed system has the following distinct features.1) Use of Traic with opto-isolated driver for controlling elec-

trical appliances: Household appliances are controlled ei-ther remotely or automatically with the help of fabricatedsmart sensing unit consisting of triac –BT138 [14].

2) No microprocessor/microcontroller: The design of smartsensing unit does not require a processing unit at the sens-ing end.

3) Flexibility in controlling the appliances: Depending onthe user requirements, appliances can be monitored andcontrolled in different ways. Section III-B discusses aboutthe various options of controlling the devices.

The rest of this paper is organized as follows: Section II dis-cusses the related work and investigation of WSN’s constraints

1083-4435 © 2014 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission.See http://www.ieee.org/publications standards/publications/rights/index.html for more information.

SURYADEVARA et al.: WSN-BASED SMART SENSORS AND ACTUATOR FOR POWER MANAGEMENT IN INTELLIGENT BUILDINGS 565

for home energy management systems; Section III providesdetailed implementation of the developed system; Section IVpresents the experimental results and Section V has concludedand discussed about the future work.

II. RELATED WORK

In this section, we briefly discuss the existing works aboutsmart home systems based on the wireless communication tech-nology. Han et al. [15] proposed a Home Energy ManagementSystem (HEMS) using the ZigBee technology to reduce thestandby power. The suggested system consists of an automaticstandby power cutoff outlet, a ZigBee hub and a server. Thepower outlet with a ZigBee module cuts off the ac power whenthe energy consumption of the device connected to the poweroutlet is below a fixed value. The central hub collects informa-tion from the power channels and controls these power channelsthrough the ZigBee module. The central hub sends the presentstate information to a server and then a user can monitor orcontrol the present energy usage using the HEMS user inter-face. This facility may create some uneasiness for the users.For example, if the users may want low intensity of light, forsome situation but the system will cut the power off leading todarkness.

Gill et al. [16] projected a ZigBee-based home automationsystem. This system consists of a home network unit and a gate-way. The core part of the development is the interoperability ofdifferent networks in the home environment. Less importanceis given to the home automation. Pan et al. [17] recommended aWSN-based intelligent light control system for indoor environ-ments, such as a home for a reduction in energy consumption.In this paper, wireless sensors are responsible for measuringcurrent illuminations and the lights are controlled by applyingthe model of user’s actions and profiles.

Song et al. [18] suggested a home monitoring system usinghybrid sensor networks. The basic concept of this paper is aroaming sensor that moves the appropriate location and partici-pates in the network when the network is disconnected. Suh andKo [19] proposed an intelligent home control system based ona wireless sensor/actuator network with a link quality indicatorbased routing protocol to enhance network reliability. Nguyenet al. [20] have proposed a sensing system for home-based reha-bilitation based on optical linear encoder (OLE); however, it islimited to motion capture and arm-function evaluation for homebased monitoring. Huiyong et al. [21] examined the integrationof WSN with service robot for smart home monitoring system.

The above mentioned home monitoring and controlling sys-tems have limitations with respect to true home automation suchas: 1) energy consumption control mechanism is limited to onlycertain devices like light illuminations, whereas several house-hold appliances can be controlled; 2) energy control is based onfixed threshold power consumption, which may not be applica-ble to different consumers; 3) controlling the home appliancesthrough network management functions, in practice inhabitantrequirements may vary according to their behavior but not withnetwork characteristics. Not a single system has taken into con-sideration of variable tariff of electricity, which is consumedthroughout day and night.

Fig. 1. Functional block diagram of the system.

In this paper, a low-cost, flexible, and real-time smart powermanagement system, which can easily integrate and operatewith the home monitoring systems such as [22] is presented.

III. SYSTEM DESCRIPTION

The system has been designed for measurement of electricalparameters of household appliances. Important functions to thesystem are the ease of modeling, setup, and use. From the con-sumer point of view, electrical power consumption of variousappliances in a house along with supply voltage and current isthe key parameter. Fig. 1 shows the functional description of thedeveloped system to monitor electrical parameters and controlappliances based on the consumer requirements.

The measurement of electrical parameters of home appli-ances is done by interfacing with fabricated sensing modules.The details of the design and development of the sensing mod-ules are provided in the following sections. The output signalsfrom the sensors are integrated and connected to XBee modulefor transmitting electrical parameters data wirelessly. The XBeemodules are interfaced with various sensing devices and inter-connected in the form of mesh topology to have reliable datareception at a centralized ZigBee coordinator. The maximumdistance between the adjacent ZigBee nodes is less than 10 m,and through hopping technique of the mesh topology, reliablesensor fusion data has been performed.

The ZigBee coordinator has been connected through the USBcable of the host computer, which stores the data into a databaseof computer system. The collected sensor fusion data have beensent to an internet residential gateway for remote monitoringand controlling the home environment.

By analyzing the power from the system, energy consump-tion can be controlled. An electricity tariff plan has been setup to run various appliances at peak and off-peak tariff rates.The appliances are controlled either automatically or manually(local/remotely). The smart power metering circuit is connectedto mains 240 V/50 Hz supply. Fig. 2 shows different appliancesconnected to the developed smart sensing system. Fig. 3(a) and(b) shows the fabricated smart sensing measurement system.

A. Measurement of Electrical Parameters

1) Voltage Measurement: The voltage transformer usedin our paper is the 44 127 voltage step-down transformer


Fig. 2. Developed system with different electrical appliances.

manufactured by MYRRA [23]. The striking features includetwo bobbins compartments including self-extinguishing plasticsand very light weight (100 g).

The step-down voltage transformer is used to convert inputsupply of 230–240 V to 10 VRMS ac signal. The secondaryvoltage is rectified and passed through the filter capacitor to geta dc voltage. The details are shown in Fig. 3(a). The availabledc voltage is reduced by a potential divider to bring it withinthe measured level of 3.3 V of the ZigBee. This output signal isthen fed to analog input channel of ZigBee end device. The ac-quired voltage signal is directly proportional to the input supplyvoltage. A voltage regulator is connected to the rectified outputof voltage transformer to obtain the precise voltage supply of3.3 V for the operation of ZigBee and operational amplifier. Thescaling of the signal is obtained from the input versus outputvoltage graph as shown in Fig. 4. The actual voltage is thusobtained as follows:

Vact = m1 × Vmeasured voltage (1)

where m1 is the scaling factor obtained from Fig. 4, Vact is theactual voltage, and Vmeasured voltage is the measured sensingvoltage.

2) Current Measurement: For sensing current, we usedASM010 current transformer manufactured by Talema [24].The main features of this sensor include fully encapsulated PCBmounting and compact size. The circuit design layout for currentmeasurement is shown in Fig. 3(a). In this current sensor, thevoltage is measured across the burden resistor of 50 Ω. The nec-essary filtering and amplification is required to bring the voltagewith the necessary measurement level of ZigBee. The scalingfactors for current measurement for two different ranges of cur-rents are shown in Fig. 5. Two different current transformersare used for two different ranges: 0–1 A and 1–10 A, respec-

Fig. 3. (a) Overall schematic of voltage, current sensing circuit integrated withZigBee module. (b) Designed and developed prototype—electrical appliancespower monitoring and control.

Fig. 4. Scaling factor (m1) of voltage signal.

tively. The actual current is thus obtained from (2). The line wireis connected to the load, which is passing through the currenttransformer. With the use of current transformer, the electricalisolation is achieved which is important in many applications as


Fig. 5. Scaling factor (m2) of current signal.

Fig. 6. Representation of power factor.

well as for the safety of the electronic circuit

Iact = m2 × Vmeasured voltage for current (2)

where m2 is the scaling factor obtained from Fig. 5, differentvalues of m2 to be used for different current transformers. Iact isthe actual current; Vmeasured voltage for current is the measuredsensing voltage for current.

The developed system includes two current transformers; oneis used for the measurements of loads up to 100 W and the othercurrent transformer is used for the measurements of loads from100 to 2000 W. The reason of providing two transformers is toprovide two load outlets at the same sensing node. The numberof turns is increased up to five turns to improve the resolutionof the low current signal. Both outputs from the current trans-formers are fed to the analog input channels of ZigBee.

3) Power Measurement: In order to calculate power of asingle-phase ac circuit, the product of root mean square (RMS)voltage and RMS current must be multiplied by the power factoras given in (3). Power factor is the cosine of the phase angleof voltage and current waveforms as shown in the Fig. 6 for anideal situation

Pact = Vrms × Irms × Pf (3)

where Pact is the actual power, Vrms and Irms are the RMSvalues of voltage and current, respectively, and Pf is the powerfactor.

The output signal of the current transformer completely de-pends on the nature of the connected appliances whether theconnected load is purely resistive, capacitive, or inductive. Inmost of the domestic appliances, the output waveforms are notpure sinusoidal as shown in the following graphs Fig. 7(a)–(d)for different loading conditions. From the graphs, it is inferredthat zero-crossing determination is difficult to measure for someof the appliances and elimination of noise is not trivial. More-over, it is not important for this application to measure powerwith zero error.

Hence, in our paper, instead of measuring power factor, wehave introduced correction factor to normalize the receivedpower with respect to the actual power based on the scalingfactors of the voltage and current measured. The power con-sumed by the appliances is calculated in the computer systemafter receiving voltage outputs from corresponding current andvoltage sensors by the following equation:

Pcal = Vact × Iact × Cf (4)

where Pcal is the calculated power; Vact the output voltage asgiven in (1); Iact the current value as given in (2); and Cf is thecorrection factor.

The term correction factor is introduced to calculate power ac-curately by the system. The correction factor is the ratio of actualpower to the measured power. Correction factor is required forthe power measurement for some loads. This correction factorcan be obtained by plotting graph for calculated power againstthe actual power. Thus, the power is calculated in computer us-ing CSharp programming after receiving voltage outputs fromcorresponding current and voltage sensors.

The prototype has been tested and results achieved for manyhousehold electrical appliances are shown in the following sec-tion. Table I shows the percentage error for all measured pa-rameters with the corresponding references. It is seen that themaximum error is less than 5% for the domestic appliances.From the low percentage error of power, it has been decidedthat power can be calculated without considering power factor.

B. Control of Home Appliances

The current paper is novel in terms of other reported literaturedue to its control features.

1) Smart Power Metering System integrated With Traic: Forswitching on/off of the electrical appliances, we have used atriac-BT138 [14]. This enables the consumer for flexibility incontrolling the devices: The users (inhabitants) have the optionsof switching the device on/off in three different ways.

1) Automatic control: Based on the electricity tariff condi-tions, the appliance can be regulated with the help of smartsoftware. This enables the user to have more cost saving byauto switch off the appliances during the electricity peakhours. The electricity tariff is procured from the websiteof the electricity supply company and is updated at regularintervals.


Fig. 7. Output waveform of current transformer for different appliances.(a) Output waveform of current transformer for 100 W electric bulb, (b) outputwaveform of current transformer for 800 W room heater, (c) output waveform ofcurrent transformer for 60 W electric bulb, and (d) output waveform of currenttransformer for audio device.

TABLE IPERCENTAGE ERROR OF RECEIVED VOLTAGE, CURRENT, AND

MEASURED POWER

2) Manual control: An on/off switch is provided to directlyintervene with the device. This feature enables the user tohave more flexibility by having manual control on the ap-pliance usage without following automatic control. Also,with the help of the software developed for monitoringand controlling user interface, user can control the devicefor its appropriate use. This feature has the higher priorityto bypass the automatic control.

3) Remote control: The smart power monitoring and control-ling software system has the feature of interacting with theappliances remotely through internet (website). This en-ables user to have flexible control mechanism remotelythrough a secured internet web connection. This some-times is a huge help to the user who has the habit ofkeeping the appliances ON while away from house. Theuser can monitor the condition of all appliances and dothe needful.

Thus, the user has the flexibility in controlling the electricalappliances through the developed prototype.

C. Residential IP Gateway: Transmission Over IP

In order to transmit real-time sensed data over the internetfrom the collected computer system, the ZigBee packet infor-mation is to be transformed to the Internet Protocol Version6(IPv6). The key element in the data transformation from Zig-Bee packet is the address translation. This was implemented atthe application gateway, a program for determining the sourceor destination address of a packet that encapsulates a ZigBeepackets’ payload.

The corresponding application gateway program performsthe address transformation mechanism for ZigBee to addressnon-ZigBee nodes. ZigBee is based upon the IEEE 802.14.5protocol, which uses a 64-bit address for each node on a per-sonal area network (PAN) and 16 bits to identify the PAN ID.IPv6 uses 128 bits to address a node on the network, of which48 bits represent the network, 16 bits represent the local net-work (PAN ID), and 64 bits represent the host id (sensor node).Therefore, the node address for the IEEE 802.15.4 can be placedin an IPv6 address, and the PAN ID can be used to identify the


Fig. 8. Address transformation from ZigBee sensing unit to Internet packet.

ZigBee network in an IPv6 address. Fig. 8 shows the addresstransformation of ZigBee and IPv6 packet.

The software used on the internet gateway to transmit dataglobally is the Linux-Open WRT [25]. This is basically routerfirmware software providing the networking architecture to par-ticipate in many types of internetworks. In order to remotelymonitor and control the household appliances the residentialinternet gateway uses the Openwrt software to link to the inter-networking protocol. These networks are embedded into internetrouters and gateways for broadcasting data globally. The senseddata is forwarded through a tunneling and tapping (tun/tap) de-vice driver software. The tun/tap acts as virtual network devicesoftware for bridging and routing functionalities (layer 2 andlayer 3) of Internet Protocol (IPv6).

D. Storage of Data

The ZigBee packets produced at the gateway encapsulatesample data to be sent to windows based internet server. Anapplication on the server receives packets on an arbitrary portand stores the relevant information in the background of MySQLdatabase in the computer.

The database table store information such as source address,time, source channel, and sense data. Rows are added to thistable for each packet received. This allows samples to be sortedby time, sensor node, and sensor channel.

In the present system, programs for address, packet transfor-mations, and data transmission are written using “C” program-ming language, programs for packet reception and data storageare written using “C#,” and Web interface is developed usingPHP Script and Java Scripts.

IV. EXPERIMENTAL RESULTS

The prototype is in operation in a trial home with various elec-trical appliances regularly used by an inhabitant. The followingappliances were tested: room heaters, microwave, oven, toasters,water kettle, fridge, television, audio device, battery chargers,and water pump. In total, ten different electrical appliances wereused in the experimental setup; however, any electrical appli-ance whose power consumption is less than 2000 W can be usedin developed system.

The sampling rate for the fabricated sensing modules wassetup with 50 Hz, so that electrical appliance usages within(less than 10 s) interval of time will be recorded correctly. By

Fig. 9. Smart power monitoring and control system at the residence.

Fig. 10. Graphical user interface of smart power monitoring and control sys-tem at the local residence.

monitoring consumption of power of the appliances, data arecollected by a smart coordinator, which saves all data in the sys-tem for processing as well as for future use. The parameters willbe entered in the data coordinator in software from appliancesinclude voltage, current, and power. These parameters will bestored in a database and analyzed. Collected data will be dis-played on the computer through graphic user interface (GUI)window so that appropriate action can be taken from the GUI.Fig. 9 shows the smart power monitoring and control system ata house where the system is on trial.

The processed voltage, current, and power values are dis-played on the graphical user interface running on a computer.The processed data are accurate and user friendly. The sensingsystem in the sensor node measures the parameters (voltage andcurrent). The raw data (i.e., converted ADC values) are trans-mitted to the coordinator. The computer then collects the datafrom the coordinator and processes them. The computer thenapplies the necessary formulas to get the actual voltage, current,and power consumption of the electrical appliances. The voltageand current readings are processed using C sharp programming.Fig. 10 shows the front end of the smart software system at thelocal residence.


Fig. 11. (a) Website (www.iots2is.org) displaying the real-time informa-tion (power consumption of appliances fridge and laptop). (b) Website(www.iots2is.org) displaying real-time information (power consumption of mi-crowave appliance) and last 24 h usage pattern.

The developed system has software recovery strategies suchas exception-handling, auto restart, and alert text mechanism forsensors failure. The exception handling procedure can handleerrors such as no sensor data reception and high range valuesof analog-to-digital-converted values and computational errorsresulted during the normalization of voltage and current sensedata values. Depending on the inhabitant usages, appliancesconnected by smart sensing units are controlled either by au-tomation based on the tariff conditions or by the inhabitantlocally using GUI and remotely using the website. The tariffconditions refer to the situation wherein unimportant electricalappliances will be automatically switched off by the systemduring high price of the electricity. Fig. 11(a) shows the real-time usage pattern of a fridge on a particular day. Fig. 11(b)depicts the regular usage pattern of an electrical appliance with-out tariff control. The system is easy to use as these devices canbe controlled remotely using the secured website as shown inFig. 12.

Thus, the regular household electrical appliances along withsmart sensing have been internetworked through internetwork-ing technology by integrating ZigBee with IPv6 for better re-mote management of household appliances.

Fig. 12. Secured webpage for controlling appliances remotely after successfulauthorized login.

V. CONCLUSION AND FUTURE WORK

A smart power monitoring and control system has been de-signed and developed toward the implementation of an intelli-gent building. The developed system effectively monitors andcontrols the electrical appliance usages at an elderly home.

Thus, the real-time monitoring of the electrical appliances canbe viewed through a website. The system can be extended formonitoring the whole intelligent building. We aim to determinethe areas of daily peak hours of electricity usage levels and comewith a solution by which we can lower the consumption andenhance better utilization of already limited resources duringpeak hours.

The sensor networks are programmed with various user in-terfaces suitable for users of varying ability and for expert userssuch that the system can be maintained easily and interactedwith very simply. This study also aims to assess consumer’sresponse toward perceptions of smart grid technologies, theiradvantages and disadvantages, possible concerns, and overallperceived utility.

The developed system is robust and flexible in operation. Forthe last three months, the system was able to perform the remotemonitoring and control of appliances effectively. Local and re-mote user interfaces are easy to handle by a novice consumerand are efficient in handling the operations.

In future, the system will be integrated with co-systemslike smart home inhabitant behavior recognitions systems todetermine the wellness of the inhabitant in terms of energyconsumption.

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Nagender Kumar Suryadevara received theB.Tech. degree from Sri Krishnadevaraya University,India, in 1996 and the M.Eng. degree from MaduraiKamaraj University, India, in 1998. He is currentlyworking toward the Ph.D. degree at the School ofEngineering and Advanced Technology, Massey Uni-versity, Palmerston North, New Zealand.

His career has demonstrated consistent successas an administrator and educator at the graduate andpostgraduate education levels in India, Ethiopia, andOman. He is currently involved with the development

of software systems, for a home monitoring project using WSNs. His current re-search interests include domains of wireless sensor networks, internet of things,and real-time data mining.

Subhas Chandra Mukhopadhyay (M’97–SM’02–F’11) received the B.E.E. degree from Jadavpur Uni-versity, India, in 1987, the M.E.E. degree from theIndian Institute of Science, India, in 1989, the Ph.D.degree from Jadavpur University, in 1994, and theD.Eng. degree from Kanazawa University, Japan, in2000, all in electrical engineering.

He is currently a Professor of sensing technologywith the School of Engineering and Advanced Tech-nology, Massey University, Palmerston North, NewZealand. He has more than 25 years of teaching and

research experience. His current research interests include smart sensors andsensing technology, wireless sensor networks, internet of things, electromag-netics, control engineering, etc. He has authored/coauthored over 300 papersin different international journals and conference proceedings, and as bookchapters. He has edited 11 conference proceedings. He has also edited 11 spe-cial issues of international journals as a Lead Guest Editor and 15 books withSpringer-Verlag. He has delivered 200 seminars including keynote, tutorial, andinvited and special seminars in 24 countries.

Prof. Mukhopadhyay has been the recipient of numerous awards throughouthis career and has attracted over NZ $3.6 M on different research projects. Heis a Fellow of the Institution of Engineering and Technology, U.K. He is aTopical Editor of the IEEE SENSORS JOURNAL, an Associate Editor of the IEEETRANSACTIONS ON INSTRUMENTATION AND MEASUREMENTS, and a TechnicalEditor of the IEEE/ASME TRANSACTIONS ON MECHATRONICS. He chairs theIEEE IMS Technical Committee 18 on Environmental Measurements.

Sean Dieter Tebje Kelly received the B.Eng. andM.Eng. degrees from Massey University, PalmerstonNorth, New Zealand.

He is currently with Massey University. His cur-rent research interests include the areas of wirelesssensor networks and internet of things. He is involvedin developing software for embedded devices, devel-oping hardware for sensors, and website develop-ment.

Satinder Pal Singh Gill received the M.Eng. de-gree from Massey University, Palmerston North, NewZealand.

He is currently with Massey University. His cur-rent research interests include electrical and electron-ics engineering, wireless sensor networks, and smartgrids.