ResearchArticle WSN4QoL: A WSN-Oriented Healthcare System

Research ArticleWSN4QoL A WSN-Oriented Healthcare System Architecture

S Tennina1 M Di Renzo2 E Kartsakli3 F Graziosi1 A S Lalos3 A Antonopoulos4

P V Mekikis3 and L Alonso3

1 WEST Aquila Srl University of LrsquoAquila 67100 Lrsquo Aquila Italy2 Supelec CNRS 91192 Paris France3 Department of Signal Theory and Communications (TSC) Technical University of Catalunya (UPC) 08034 Barcelona Spain4CTTC Castelldefels 08860 Barcelona Spain

Correspondence should be addressed to S Tennina tenninawestaquilacom

Received 11 December 2013 Accepted 17 February 2014 Published 6 May 2014

Academic Editor Sana Ullah

Copyright copy 2014 S Tennina et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

People worldwide are getting older and this fact has pushed the need for designing new more pervasive and possibly cost effectivehealthcare systems In this field distributed and networked embedded systems such as wireless sensor networks (WSNs) are themost appealing technology to achieve continuous monitoring of aged people for their own safety without affecting their dailyactivities This paper proposes recent advancements in this field by introducing WSN4QoL a Marie Curie project which involvesacademic and industrial partners from three EU countries The project aims to propose newWSN-based technologies to meet thespecific requirements of pervasive healthcare applications In particular in this paper the system architecture is presented to copewith the challenges imposed by the specific application scenarioThis includes a network coding (NC)mechanism and a distributedlocalization solution that have been implemented on WSN testbeds to achieve efficiency in the communications and to enableindoor people tracking Preliminary results in a real environment show good system performance that meet our expectations

1 Introduction

Medical experts agree on the projections that forecast inthe next couple of decades the population aged over 65years to increase from 69 to 120 worldwide and inparticular from 155 to 243 in Europe [1] with anaverage worldwide life-span expected to extend another10 years by 2050 [2] The growing number of older adultsincreases the demands on the public healthcare system andon medical and social services Increased life expectancyreflects in part the success of public healthcare interventions[3] but public healthcare programs must now respond tothe challenges created by this achievement including thegrowing burden of chronic illnesses injuries and disabilitiesand increasing concerns about future care-giving andhealthcare costs [4] A study of Frost and Sullivan [4] hasclearly indicated that in almost all countries worldwidehealthcare spending per capita is rising faster than percapita income If current trends hold by 2050 healthcare

spending is expected to double claiming 20ndash30of gross domestic product (GDP) for some economiesand 20 by 2015

In this context new technologies that can help seniors liveat home longer provide a ldquowin-winrdquo effect both improvingquality of life and potentially saving enormous amountsof money The forecast above clearly highlights the com-pelling need of delivering high-quality care to a rapidlygrowing population of elderly while reducing the overallhealthcare costs Until recently the cost of providing acontinuous patient monitoring flow of patientsrsquo data frompatientsrsquo homes to care providers was prohibitive mainlybecause it requires continuous in-person patient moni-toring through specially trained care givers available fulltime or dedicated communication and appropriate deviceinfrastructures

Nowadays with the increasing availability of broadbandtechnology at home along with wireless networks and awide range of consumer health electronics an end-to-end

Hindawi Publishing CorporationInternational Journal of Distributed Sensor NetworksVolume 2014 Article ID 503417 16 pageshttpdxdoiorg1011552014503417

2 International Journal of Distributed Sensor Networks

infrastructure has begun to emerge enabling new ldquopervasivehealthcarerdquo applications more often shortly termed as ldquoe-Healthrdquo applications The availability of these networks andthe widespread use of mobile devices make two-way contin-uous interactions between patients and their care providersfeasible regardless of physical location

On the other hand the use of information and com-munication technologies to facilitate and improve healthcareand medical services involves the use of appropriate devicesboth on patients and embedded in the living environmentResearchers and educators predict that these gadgets willsoon turn the home into a medical nurse keeping recordon everything from pill-taking routines to signs of imminentcrises

For seniors the benefits of an idealized medical smarthome are physical psychological and emotional Aging inplace means continuing with familiar routines while healthdata detection of critical conditions and remote control ofcertain medical treatments are wirelessly made available todoctors caregivers and concerned family [5] For societythe bonuses include significantly reduced health care costsand happier elders Consequently it is natural to expectthat consumers will embrace in-home technologies preciselybecause they can potentially save them money on the cost ofunnecessary time-consuming doctor visits thus not jeopar-dizing their daily life activities

On this subject this paper aims to present theWSN4QoLproject [6] which involves the design of wireless sensornetworks (WSNs) specifically suited to meet healthcareapplication requirements WSN4QoL is a 3-year projectstarted at the end of 2011 and still ongoing With theintent of bringing together experts from industry andacademia it proposes the use of advanced WSN tech-nologies for pervasive healthcare applications In particu-lar it aims at providing network coding (NC) for multi-hopcooperative diversity in the data communication pro-tocol as well as distributed localization algorithms to meetthe specific requirements of WSNs-enabled healthcare appli-cations namely energy-efficiency low-latency data reliabil-ity context-awareness and security Extensive performanceanalysis of the proposed solutions is given through numericalsimulations as well as proofs-of-concept in real-world exper-iments through the implementation into real healthcaredevices

The rest of the paper is organized as follows Section 2overviews the full system architecture presenting the designchallenges offered by the general reference scenario whileSection 3 puts particular emphasis on the key elements ofthe communication protocol stack and the middleware ofservices offered to the application designers Sections 4 and5 present the NC and the localization testbeds respec-tively that have been implemented to evaluate the solutionsproposed in real(istic) environments Section 6 deals with asummary of current research efforts with similar objectivesto WSN4QoL Finally Section 7 concludes the paper witha view on some of the open issues to be addressed asongoing and future work in the remainingWSN4QoL projectperiod

2 WSNs System Architecture Designfor E-Health

WSNs are distributed networked embedded systems whereeach node combines sensing computing communicationand storage capabilities They have emerged as a newnetworking environment that provides end-users withintelligence and a better understanding of the environmentBecause of their wide variety of applications it is envisionedthat in the near future WSNs will become an integralpart of our everyday lives [7] WSNs are wireless ad hocnetworks composed of inexpensive nodes with sensingcapabilities and a limited number of data sink nodes Thesenodes communicate among each other by forming multihopwireless networks and by maintaining connectivity in acentralized or a distributed manner The network topologyis in general dynamic since the connectivity among thenodes may vary with nomadic and mobile nodes

21 Challenges Although fundamental research results onWSNs theory and practice have been achieved for manydifferent applications for example traffic monitoring plantmonitoring in agriculture and infrastructure monitoringthe application of this technology to e-Health poses someunique application-specific challenges and constraints Inparticular the efficient design of a WSNs-enabled pervasivehealthcare system is characterized by the following intrinsicdifferences with respect to ldquogeneral-purposerdquo WSNs designwhich require special attention [8] (i) The devices havelimited available energy resources as they have a very smallform factor (ii) A low transmit power per node is neededto minimize interference and to cope with health concerns(iii) The devices are located on the human body whichcan be in motion WSNs for e-Health should therefore berobust against frequent changes in the network topologyand channel variability (iv) Data mostly consist of medicalinformation hence high reliability and low delaylatencyare required (v) Stringent security mechanisms are requiredto ensure the private and confidential character of data(vi) Context-awareness through cooperative localization inoutdoors and indoors is crucial to enable a prompt reactionin case of emergency (vii) The devices are in general veryheterogeneousTheymay have very different demands ormayrequire different resources of the network in terms of datarates power consumption and reliability

Along these lines the main research objective ofWSN4QoL is to provide fundamental research advancesproof-of-concepts and real-life implementations on themainenabling technologies forWSNs-aided e-Health applicationsMore specifically disruptive techniques such as cooperativewireless communications protocols and distributed algo-rithms are investigatedThe proposed solutions are designedoptimized and implemented in real-devices by taking intoaccount the specific requirements of e-Health energy effi-ciency low-latency delivery of data data reliability andsecurity In more detail the research objectives ofWSN4QoLinclude the following (i) to design a protocol stack archi-tecture which can accommodate a variety of protocols

International Journal of Distributed Sensor Networks 3

Bluetooth

PDAlaptop

Receive data via Bluetoothtransmit data via IEEE 802154

Receive data via IEEE 802154transmit data via internet

Internet

Doctor

Ambient sensors(relays)

Wireless bodyarea network

Figure 1 Reference healthcare 3-tier system architecture

algorithms and sensor devices for pervasive healthcare appli-cations (ii) to develop energy-efficient and performance-guarantee cooperative protocols and NC schemes for WSNs-enabled pervasive healthcare applications (iii) to proposeadvanced distributed localization protocols and algorithmsspecifically suited for the scenarios (eg indoors) envisagedby WSNs-enabled pervasive healthcare applications (iv) toconceive effective efficient and resilient security solutionsfor the proposed algorithms and protocols (v) to implementand assess the performance of the protocol stack in a WSNtestbed and (vi) to integrate the proposed solutions in realdevices and validate them in real working environments

22 Reference Scenario Similar to other works in literature(eg [9 10]) the reference system architecture proposed inthis project is as depicted in Figure 1 It is a three-tier systemarchitecture where at the lowest tier (Tier-1) a Bluetooth-enabled WBAN connects sensors to a local collector (iea hub) which can be a portable embedded PC or a PDAThe hub needs to communicate withWBAN devices througha Bluetooth radio module and then send measurementsreports towards a residential gateway through a ZigBeeIEEE802154 based multihopWSN (Tier-2)The gateway is able toperform local computation and forward data to the public IP-basednetwork (Tier-3) towards the professional caregivers forreal-time analysis

In recent work [11ndash13] we proposed alternatives to theBluetooth for the communications among the devices form-ing the WBAN at the Tier-1 Nevertheless in the WSN4QoLproject our focus is on the efficient data transmission overthe WSN network at the Tier-2 as well as supporting real-time people localization in a fully distributed way

3 System Protocol Stack

Figure 2 shows the intended communication protocol stackfor the WSN of the reference scenario in Figure 1 Movingfrom the bottom the protocol stack is composed of thefollowing entities

(a) IEEE 802154 MAC Layer This layer is responsible for theaccess to the wireless medium for transmission and receptionof the frames for both mobile patients and fixed relay nodes

Among the options offered by the IEEE 802154 standard[14] we have chosen to refer to the non-beacon-enabledmodethat is the fully asynchronousmodeThis choice is motivatedby the fact that nodes can have variable duty cycle especiallythe mobile ones that is those carried by the patients In theclassical scenario where patientrsquos data need to be collectedat a central station the asynchronous mode offered by thisstandard allows for flexibility in accessing the medium onlywhen patientsrsquo data are available and a transmission needs


Middleware

Application

Network

MAC

Networkcoding Security Localization

MLME SAP MCPS SAP

MCPS DATArequestMCPS DATAindication

MLME RESETrequestMLME SETxMLME SCANrequest

Customized APIs

High level APIs

Figure 2 Communication protocol stack on top of the IEEE 802154 standard Basic interfaces are also shown

to occur For the majority of time the radio interface ofthese nodes can be kept off or in a low-consumption state tosave the energy of the batteries Moreover the synchronousmode would have required association (and disassociation)mechanisms to allow the nodes to join the network priorto communication resulting in a severe limitation on thenodesrsquo mobility Furthermore to exploit the power of NCmechanisms for energy savings and network throughputgains (Section 4) messages sent by the mobile nodes need tobe transmitted in broadcast thus without a prior associationmechanism

Finally along this line the basic commands and eventsoffered by the MAC to the upper layer are for packet trans-mission and reception and to set some specific parameterssuch as the frequency channel and the transmission poweras well as the primitive to scan the IEEE 802154 channels forenergy and activity detection

(b) Network Layer Since the asynchronousmode of theMAClayer is chosen this layer is responsible for keeping thesynchronization among the fixed relay nodesThis is achievedby sending synch packets Unlike IEEE 802154 beaconframes synchmessages are not requested to be periodic theirtransmission can be scheduled with an adaptive duty cyclebased on the environmental conditions (eg the presenceof patients in the area or not) although for keeping theirscheduling a mechanism inspired by the time division clusterscheduling [15] can be implemented

Synch packets are fundamental to allow for minimizingthe collisions among the messages sent by the mobile nodesby defining a superframe structure constituted of time slotswhere each mobile node is allowed to transmit based onsome policy rule Finally they are requested to implementboth NC schemes and distributed localization algorithms aswill be detailed in the next sections

Besides the synchronization the network layer is alsoin charge of assigning the network addresses to the nodesUsually the radio interface of a node has an address whichis worldwide unique as a serial number assigned by the

manufacturer In the case of IEEE 802154 radios theseaddresses are 64 bits long and can be used for the commu-nication with any other node (extended address) Anotheroption is for a node to get a network address which is only16 bits long assigned according to some policy and used tocommunicatewith the other nodes of the samenetwork(shortaddress)

Shortly the extended address mechanism is used by themobile nodes The fixed relays are usually placed in strategicpositions to ensure the best coverage of the environmentand form a network with a static topology Consequentlythese nodes can be assigned with the addresses defined byfor example the ZigBee Distributed Address AssignmentMechanism This addressing mechanism assumes that nodesare organized into a tree and divides the address spaceinto blocks assigning each block to each node of the treeThe advantage of using short addresses in this way for therelay nodes is the fact that they do not need to maintainrouting tables to forward incoming data simply looking at theaddress they are able to recognize if the packet has to be sentupwards or downwards along the tree Finally also packetsto the mobile nodes are assumed to be sent in broadcastthis is still reasonable since it is assumed that the networktraffic from the residential gateway to any patient (related toany actuation such as for example automatic regulation ofan insulin pump) is less frequent than the reverse direction(patientrsquos monitored data collection)

The commands and events offered by this layer to theupper modules are customized based on the reference modelwe assume (ZigBee) with the addition of those elementsneeded to implement the services at the middleware layer

(c) Middleware Services This layer represents an interfacebetween the underlying protocol stack and the applicationlayer and is the core of the novelties introduced within theframe of WSN4QoL project

Themiddleware encompasses three major blocks (i) NC(ii) distributed localization (iii) securityThese blocks exploitthe services offered by the underlying protocol stack entities


to provide a high-level application programming interface(API) to the application developers

The NC entity is in charge of providing efficiency in wire-less communications By means of appropriate combinationsof two or more packets into a single one and NC-awarerouting mechanisms at the lower layer a relay node is ableto reduce the amount of traffic over the network withoutlosing data Section 4 will present the basic building blocksdeveloped withinWSN4QoL to demonstrate the efficiency ofa binary XOR-based network coding scheme in a scenariowith two sources one relay and one destination (ie amultiple access relay channel scenario) as compared to thecase where the relay node simply forwards the receivedpackets In general the proposed protocol stack allows foradopting multicast (and geographic) routing mechanismsat the network layer [16 Chapter 6] which are well suitedfor supporting NC schemes more complex than the binaryXOR-based ones including for example the random linearnetwork coding (RLNC) [17]

The distributed localization block deals with the onlineestimation of the geographical position of a mobile node inthe environment Associating a spatial reference with everycommunication between the patients and the remote caregivers is of paramount importance whether in home or hos-pital environments especially in case of alarms conditions Asbetter detailed in Section 5 the relay nodes emit their synchpackets and doing so they play the role of anchor or referencenodes that is it is supposed they know their own positionand they include this information in such packets A mobilenode is then able to estimate its own position by relying onthe information gathered from the surrounding nodes

The security block monitors the acknowledgement pack-ets exchanged at the network layer among the nodes to iden-tify potential threats or nodes malfunctioning and instructthe MAC layer to encrypt frames based on the securityfeatures offered by the IEEE 802154 standard Details aboutthis block are out-of-scope of this paper where the focus isswitched to the other two elements described in the nextsections

(d) Application Layer This last layer mainly focuses ongathering measurements from the sensors and data com-pression Although the WSN4QoL project also proposes lowcost compress sensing techniques which exploit some keycharacteristics of the biometric data transmitted in order toprovide energy-efficient telemonitoring solutions this layeris out-of-scope of the present paper Interested readers canfind further details in our project website [6]

Next sections will present the implementation and exper-imental results of a binary XOR-based NC scheme and thedistributed localization algorithm Table 1 summarizes themain features of the WSN platforms used for the tests

4 Network Coding

To achieve efficient measurements reporting through theambient relay network the most viable solution is theapplication of NC techniques [18 19] In the preliminaryimplementation done in the frame of the WSN4QoL project

PktA

A

C

D

PktC

PktB

B

Figure 3 Scenario for efficient communications Nodes A and Bare mobile local hubs node C is a fixed relay and node D is thedestination

the scenario illustrated in Figure 3 has been implementedin the available testbed In this scenario two nodes Aand B are mobile nodes carried by two patients a relaynode C has a fixed position and D is the destination ofthe measurements reports that are sent by the two sourcenodes In the considered scenario to further claim the gainsintroduced by the NC techniques it is supposed that thedestination node does not send back any feedback either tothe relay or to the sources

41 Implementation Figure 4 presents the timings charac-terizing the scenario of Figure 3 In particular Figure 4(a)presents the case of the baseline scenario and Figure 4(b) thecase with NC

The relay C is responsible for defining the networkscheduling among the source nodes A and B by periodicallybroadcasting the synch packets The source nodes are pro-grammed to send a message in their appropriate time slotsthat is node A sends its data after Tslot and node B sendsits data after 2lowastTslot In the baseline scenario node C thenforwards the received data from A to the destination afterTslot and data from B after another Tslot then it broadcastsa new synch packet and the process is iterated In the NCscenario instead of forwarding the two messages the nodeC transmits to the destination a single message which is thecombination of the two messages from A and B based on abinary XOR operation In both cases upon the reception ofevery synch the destination checks what it has received in thesuperframe just concluded and updates the network statistics

The main advantage of the NC against the baselinescenario is that the relay node forwards a single packet insteadof two resulting in larger energy savings and the higherthroughput since the synch is sent every 4lowastTslot instead of5lowastTslot


Table 1 WSN platforms testbeds features

Item Specification DescriptionTelosB CC2430Processor

Model Texas Instruments MSP430F1611 Intel 805116 bit 32 bit

Memory48KB 128KB Program flash10KB 8KB Data RAM1MB mdash External Flash

ADC 12 bit8 channels

Interface UART SPI I2C Two programmable USARTsUSB 21 GPIO

RadioRF Chip Texas Instruments CC2420 IEEE 802154 24GHz Wireless Module

Frequency Band 24GHzndash2485GHz IEEE 802154 compliant ch11ndashch26

Sensitivity minus95 dBm typical

Transfer Rate 250Kbps

RF Power minus252 dBmndash06 dBm Software Configurable

Range 120m (outdoor)20ndash30m (indoor)

Current DrawRX 188mATX 174mA

Sleep mode 1 uA

Antenna PCB Antenna Dipole Antenna

Both scenarios have been coded and tested over aWSN testbed composed by TelosB nodes [20] (Table 1)programmed with the TinyOS operating system [21] andimplemented as protocol layer(s) on top of the OfficialTinyOS 154MAC [22 23]The nodes of the baseline scenariohave been configured to run on the channel 25 of the IEEE802154 standard while the nodes of the NC scenario runon the channel 26 this is done in order to have the twonetworks working at the same time and test them in the sameconditions

To monitor in real time the network behaviour and theperformance a graphical user interface (GUI) has also beenimplemented and is shown in Figure 5 It shows (i) the nodesrsquotransmissions (ii) the values of the sensors readings and (iii)the residual of the batteries which are data encoded in thetransmitted packets as well as the performance metrics ofthe network including (iv) throughput or goodput (ie theamount of sensors measurements successfully delivered tothe destination in the unit of time) (v) packet loss and (vi)energy consumption

42 Results Compared to the classical relay scenario wherenode C forwards the received packets in two distinct slotsthe NC scheme allows for achieving better performance interms of joint packet loss ratio (PLR) and data goodputIn particular the scenario of Figure 3 implemented on themobile WSN testbed as described in the previous sectionwas used in an indoor environment such as a residential

apartment to run several tests by varying the transmissionpower levels between minus252 dBm and 06 dBm While source2 nodes of both testbeds were kept in a fixed position source1 nodes of both networks were carried by a person who waswalking at approximately constant speed over a preplannedclosed path crossing the rooms of the apartment resulting ina time of a lap of around 5 minutes and repeating the path atleast 10 times for each experiment

Although the PLR shows similar performance betweenthe scenario with NC and the one with classical forwardingthe tests demonstrated that NC can achieve gains rangingfrom 32 to 68 in terms of instantaneous goodput Inparticular Figure 6 reports the goodput averaged over thewhole experiments (ie all the laps for each transmissionpower) and for different values of the Tslot ranging from200ms to 800ms (Figure 4) As it is evident the NC showsalways gains with respect to the baseline (relay-only) scenariofor all the values of Tslot and all the transmission powerlevels Moreover analyzing the behavior with respect to thetransmission power both testbeds show similar performanceand this further confirms that the two testbeds result insimilar performance in terms of PLR

Although in this preliminary testbed the simple XOR-based NC scheme has been implemented over a singlerelay scenario future ongoing activities are focused on theenhancement of this mechanism in the cases where the ambi-ent network is composed by several relay nodes includingmultihop communications [24]


Synch Synch

SynchSynch

Data 1

Data 1

Data 2

Tslot

Tslot

Tslot

Tslot

Source A Source B Relay C Destination D

Data 2

Tslot

(a) Baseline scenario relay forwards two messages

Xor(Data 1 Data 2)

Tslot

Tslot

Tslot


Tslot

Data 2

Data 1

Synch

Synch Synch

Synch

(b) Network coding relay broadcasts a single message

Figure 4 Timings of the multiaccess relay channel scenario as depicted in Figure 3

Figure 5 Graphical user interface tomonitor network performancefor network coding testbed

0

05

1

15

2

25

3

06

Goo

dput

(pkt

s)

Transmission power (dBm)

Goodput multiaccess relay channel

NC 200msNC 400msNC 800ms

RL 200msRL 400msRL 800ms

minus04 minus79 minus252

+48

Figure 6 Goodput comparison inmultiaccess relay channel scenar-ios with network coding and relay only

5 Distributed Localization

The aim of this section is to present the ongoing activityfor indoor people localization in the WSN4QoL project Thealgorithm we refer to is detailed in [25] It is an anchor-basedalgorithm which means it runs in a scenario where severalfixed anchor nodes that is nodes knowing a priori their posi-tions based on a common reference systemof coordinates aredeployed in the environment and periodically broadcast theirpositions A second set of nodes is mobile and called blindsince they need to estimate their own positions accordingto the same reference system of coordinates by relying onthe data they are able to gather from the anchors and theenvironment The algorithm is also range-based since theblinds estimate their positions by first computing the distancewith respect to the anchors available

51 Implementation Figure 7 shows a typical home envi-ronment where a set of anchor nodes are fixed and havebeen deployed in the rooms of the house In such anenvironment a measurement campaign of the received signalstrength (RSS) from the anchors in several points has beenconducted with the intention of building an RSS-to-distancerelation curve that is an RSS-based ranging model used toestimate the distance between any pair of nodes from an RSSmeasurement

Typically the calibration activity to compute the parame-ters of the model is performed offline and in a static contextthen the system needs to run in an environment which ismore dynamic for example with people moving around orchanges in the furniture and so on As a consequence RSSpropagation parameters are strongly environment dependentand usually show big fluctuations which suggest that usingany fixed and outdated estimate for the channel parameterscertainly yields less accurate estimates of distances and thusof final positions To cope with this problem an anchor-aideddynamic and adaptive estimation of the signal propagationparameters has been previously proposed and can be easilyimplemented [26] as shown in Figure 8

In particular the relays-anchors put in the synch packetsthe RSS received from other anchors in their communication


Figure 7 Indoor environment equipped with anchor nodes (blue squares) and RSS measurement points (green circles)

1

1

3

5

6

RSSI

RSSI RSSI RSSI RSSI

RSSIRSSI RSSI

RSSI

RSSI

RSSI

RSSI

RSSI RSSI RSSIRSSI

RSSI

(1 2) (1 3)(1 2) (1 3)

A1

2 (2 1)

A2

3 (3 1) (3 4) (3 5) (3 6)

(3 1) (3 4) (3 5) (3 6)

A4

4 (4 3)RSSI

6 (6 3)

(6 3)

RSSI5 (5 3)

(5 3)

A3SN

A6

A5A

n

[D(1 3) RSSI(1 3)]

Distance

X2 Y2

X1 Y1

X3 Y3

X5 Y5

X6 Y6

X6Y6

X5 Y5

X4Y4

X3 Y3

X1 Y1

Figure 8 Anchor-aided dynamic and adaptive estimation of the ranging model


Octets 2 1 410 0561014 Variable 2Framecontrol

Sequencenumber

Addressingfields security

header

Auxiliary Datapayload FCS

MHR MAC payload MFR

Node unique address

Position RSSIs

Figure 9 IEEE 802154 data frame used by anchors with localization-oriented payload

Figure 10 Graphical user interface to monitor network perfor-mance for Localization testbed

range Figure 9 shows how the IEEE 802154 data frame isused for the anchors to transmit their positions includingalso the RSS data needed for implementing the dynamic andadaptive ranging model estimation

Every mobile node in the area receives these packets andis then able to correlate the distance among the available andknown anchor nodes with their respective RSS so that theranging model can be reconstructed as formulated in [26]

The implementation has been done on TelosB nodes [20]running the TinyOS operating system [21] for the anchornodes and an IEEE 802154-compatible platform for themobile node such as the Texas Instruments CC2430 [27]which has the same radio interface of the TelosB nodes(Table 1)

Similar to what has been done for the NC testbedto monitor in real time the network behaviour and theperformance a GUI has been implemented and is shownin Figure 10 It allows for configuring at deployment timethe position of the anchor nodes and then shows (i) thenodesrsquo activities (ii) the residual of the batteries which aredata encoded in the transmitted packets for every nodeand (iii) the statistics of the localization estimations for themobile node such as (iv) instantaneous position estimation(v) covariance ellipse (with a 70 confidence interval) of thelast 5 estimations and (vi) the ranging parameters estimatedby the mobile node

52 Results Figure 11 presents preliminary results of thelocalization of a blind node placed in several points in theenvironment of Figure 7The blind node has been left in eachposition for 5 minutes resulting in at least 100 localizationestimations

It is evident that better topological conditions (ie wheresurrounded by the anchors) lead to better localization accura-cies and stability (ie little average errors and low variabilityamong estimations) Overall the average localization errorover the area of 60m2 is below 25m which results in a room-level accuracy which matches the requirements for e-Healthapplications Nevertheless there exist few critical situationson the borders These issues can be solved by improvingthe coverage of the anchor nodes Along this line radiopropagation simulation software (eg [28]) will provide theoptimal anchorsrsquo number and positions

6 End-to-End Solutions and Testbeds

After having presented the solutions proposed within theWSN4QoL project this section overviews the state of the artin the field of WSN-based systems for pervasive healthcareapplications pointing out the main innovation aspects thatthe WSN4QoL project proposes

61 Motivation Before proceeding to give an overview ofthe solution and testbed in literature an interesting visionof e-Health remote monitoring systems as given in [29 30]is worth mentioning In these works authors classify thetelecare applications as an instance of the broader cyberphysical world (CPW) where a tight integration of sensingcomputation and communication elements concur to thedefinition of the system In this line several exciting researchchallenges and opportunities arise and might stimulate newresearch activities in the emerging areas of CPW conver-gence

In general nowadays these technologies still require thedevelopment of reliable scalable and evolvable systems invarious application domains They should hide unnecessarycomplexities inherent to CPW such as heterogeneity and dis-tribution and support rapid implementation of applicationand runtime reconfiguration and resource management tomeet functional and nonfunctional requirements One of the


163

5

1

545m492m

204m

144m

038m

054m

148m

136m249m

1998400

161

162

3

9

2

7

165

164

166

8

13

5998400

3998400

9998400

7998400

2998400

13998400

8998400

6

6998400

Figure 11 Localization results in the scenario of Figure 7 Average localization errors and covariance ellipses are also shown

key elements focuses on the study of methods and techniquesthat can be used to investigate the structure and evolution ofthe dynamics of human behavior under the lens of pervasivecomputing In this perspective the sociotechnical nature ofthe CPW convergence calls for novel and interdisciplinaryresearch approaches mixing ICT (information and commu-nication technologies) expertise with lessons learned fromapplied psychology sociology medicine complexity scienceand so forth

Along this line wearable computing (WC) for remoteassistance is one of the best examples where this mul-tidisciplinary approach takes the most promising advan-tages The maturity of WC can be demonstrated by severalprojects showing its main application domains Monitoringthe wearerrsquos vital signs promises improved treatment andreduction of medical costs Many projects are aiming at apreventive lifestyle and early diagnosis by focusing on theintegration of healthcare more seamlessly into everyday life

Nevertheless [29] stresses the fact that several researchchallenges have still to be met in this field In particular thelarge-scale production of smart clothes requires scaled-upmanufacturing processes to exploit economy of scale effectsIn addition web-based data gatheringmethods (eg [31 32])are supportive in fusing heterogeneous sensor modalitiesand in the automatic annotation of data streams Moreovermajor challenges arise for data privacy and security indesigning algorithms and protocols to protect the senseddata against unwanted collection and distribution of personalinformation

The work in [33] summarizes the most recent develop-ments in the field of wearable sensors and systems relevantto the field of health and wellness safety home rehabilitationassessment of treatment efficacy and early detection ofdisorders The integration of wearable and ambient sensorsis discussed in the context of achieving home monitoring ofolder adults and subjects with chronic conditions Particular

emphasis is given to the analysis of the key enabling tech-nologies to broaden the wearable systems for patientsrsquo remotemonitoring Among these we underline the new advancesin the sensors miniaturizationrsquos technologies and low-powermicrocontrollers and radios which can be integrated intosystem-on-chip implementations and enable e-textile basedsystems (such as [34]) or unobtrusive wearable devices (suchas [35]) Mobile phone technology played the major role inthe pervasiveness of remote monitoring systems since smartphones are broadly available and easily act as informationgateways to central stations through mobile telecommuni-cation standards such as 4G Moreover mobile devices canalso function as information processing units Reference[33] concludes that the past and ongoing research towardachieving remote monitoring of older adults and subjectsundergoing clinical interventions will soon face the need forestablishing business models to make them effective in themarket to cover the costs However we believe that also anew area of research should involve the definition of newcommunication standards for the interoperability among theplethora of authorities as stressed by similar other surveyssuch as [36]

On the other hand [37] presents a range of wire-less communication technologies and standards (ie IEEE802151 Bluetooth ZigBeeIEEE 802154 Ultra-wide-band(UWB) medical implant communication services (MICS)and IEEE 802156 Task Group) It lists their current lim-itations by dividing the platforms into implantable andon-body devices In particular the integration of wirelesstechnologies intomedical devices such as insulin pumps andon-body cardiac monitoring devices has many benefits butalso poses many challenges including (i) enabling the securetransmission of the collected private data (ii) preventionof electromagnetic interference between different wirelessdevices and compatibility with the remaining circuitry and(iii) compatibility with and safety of the biological tissues


In this perspective although security and privacy are wellinvestigated in the literature and well taken into accountin the projects we believe that the latter two issues arestill too often widely neglected Of particular interest is theconstraint posed by the last one Besides the power andsmall size requirements implantable devices also need to becompatible with biological tissues in order to prevent possibleinfection and rejection of the device by the biological tissueCompared to implantable devices on-body devices are lessprone to the biocompatibility constraint However it is worthnoting that also in this case long-term skin contact withsuch devices can cause different forms of skin irritationsThus on-body devices should also either be developed withbiocompatible materials or be truly noninvasive where noskin contact is required for the acquisition of the desireddata

62 Testbeds The authors in [38 39] provide two examplesof ECG telemonitoring implementation testbeds Reference[38] focuses on the extension of the Standard Communi-cation Protocol for Computer-assisted Electrocardiography(SCP-ECG) which provides standardized communicationamong different ECG devices and information systems to beincluded in health monitoring systems The paper describesthe implementation of the new protocol as a software com-ponent in a five-month pilot period of health telemonitoringsystem (HTS) including 27 patients The testbed they used toshow the feasibility of their proposed enhancements includesall the elements of a telecare system In particular a wearabledata acquisition system consisting of several sensors (egECG NiBP SPO

2 Pulse Rate Temperature and PLE) is

equipped with a Bluetooth radio a GPS receiver and a per-sonal digital assistant (PDA) with mobile ADSL capabilitiesThe PDA automatically organizes the data gathered from thesensors and other information manually inserted by the userinto the data structure defined by the protocol A remotehealth monitoring system (RHMS) is implemented on a PCon the expertrsquos site and is able to store present andprocess theacquired data from the PDA The PDA communicates withthe RHMS using fixed and mobile ADSL

Although the suitability of the protocol has been clearlyshown security aspects are merely taken into account bythe use of data encoded transmissions while user identifi-cation of the involved people (ie individuals techniciansphysicians etc) is performed through a simple log-in screenrequiring user ID and password

On the contrary [39] explicitly focuses on the implemen-tation of security techniques in similar ECG-based telecareapplications even if the scope of the paper is limited to thesensing device Namely a secure cross-layer-based minia-turized BSN platform has been developed It consists of aprocessing unit and a radio transmission unit with a sensorboard and a local battery power supply or energy scavengesupply The design of such platform puts particular emphasison resource-awareness that is it adopts a joint unequalresource allocation (ie transmission power and data rate)and real-time selective encryption according to the channelstatus

In [40] a body posture model and an unsupervised learn-ing and clustering algorithm have been proposed to recon-struct different stationary postures An extensive validationhas been performed through a BSN composed by Freescalenodes [41] equipped with 3-axis accelerometers These nodesare firmly attached through bands to four limbs to measurethe posture of arms and legs with two accelerometers on eachlimb and report through a wireless single-hop ZigBee radiothe measurements to a central station Experimental resultsdemonstrate that the proposed system can achieve very highclassification accuracy and is able to recognize complicatedstationary postures

The authors in [42] use a pair of Shimmer motes [43]Shimmer is a wireless sensor platform programmed inTinyOS [21] characterized by a small form factor that canrecord and transmit physiological and kinetic data in realtime using the most well-known communication technolo-gies such as Bluetooth or IEEE 802154 The chosen deviceincorporates a triaxial accelerometer a microcontroller andan IEEE 802154 radio transceiver One mote is used asa wearable device while another is attached directly to aPC acting as a base station Since the proposed methodto extract features from acceleration measurements is notcomputationally intensive the filtering technique has beenimplemented directly on the wearable device in order tocommunicate with the base station only when alarms occurand then save batteries

In a slightly different scenario that is military missionsand monitoring of soldiers the contribution of [44] is theconcept and implementation of a closed-loop end-to-endreal-time on-body prediction system for reducing healthrisks due to uncompensable heat stress (UHS) This involvesgathering physiological data (multipoint skin temperature)and postural information (multipoint body acceleration)for the purpose of autonomous real-time modelling andprediction One of the central concepts driving this systemdevelopment is that data processing must be performed bysystem devices mounted on the body to achieve a better real-time closed-loop control Autonomous operation is essentialbecause a long-range radio link to a central location mightnot necessarily be available A relatively powerful hardwareplatform is thus required to support real-time on-body dataprocessing which also enables two control loops An innerloop implements local actuation namely notifying alarms tothe user or automatically taking some actions such as coolingthe body An outer loop involves the communication with aremote station for for example mission plan change or thereturn to the base to install new cooling systems Similarapproaches can be easily implemented in more traditionalcivil scenarios for remote patient monitoring

Another simple yet efficient Internet-based telecareremote monitoring system is presented in [45] where thefocus is on a remote-controlled home mechanical ventilation(HMV) system which is progressively being used to treatpatients with severe chronic respiratory failure Contrary tothe most conventional settings the system designed avoidsany high order information technology architecture It isbased on a simple and low cost data transfer server (DTS)that grants the Internet connection to most commercially


available ventilators through the GPRS network The devicecaptures ventilation signals (eg pressure flows volumeleaks and oxygen saturation) and controls the ventilatorsettings The DTS is built upon an embedded system board(a Linux-enabled FOX board [46]) equipped with a GPRSmodem and a commercial USB flash memory It operates asa web server with its own address and password With suchan approach an independent point-to-point (from patienthome to HMV provider) communication is establishedTherefore the HMV provider (being a hospital service or aprivate practice physician) can receive real-time or previouslyrecorded ventilation data in uplink and modify the settingsin downlink by simply connecting via Internet to theindividual web address of the DTS at the patientrsquos homeensuring this way the closed-loop control

A remote and mobile patient monitoring service archi-tecture using heterogeneous wireless access in which eachpatient is equipped with a remote monitoring device with aheterogeneous wireless transceiver is presented in [8] Whilethe system architecture is not a novelty since authors proposethat a mobile patient can use different types of wirelesstechnologies (eg WiMAX-based WMAN and WiFi-basedWLAN technologies) to transfer monitored biosignal datato the healthcare center the most innovative aspect in thiscontribution is the formulation as a constrained Markovdecision process (CMDP) of the problem on the e-Healthservice provider side who has to pay to the wireless networkservice provider a certain number of connections to bereserved for the patients Using stochastic programmingtechniques the optimal number of reserved connections canbe determined to minimize the cost of the e-Health serviceprovider under randomness of connection demand due to themobility of the patients Also at the patient-attached devicethe transmission scheduling of biosignal data with differentpriority is optimized to minimize the connection cost andsatisfy the delay requirements

In the frame of coupling wearable BANs with classi-cal WSNs for environmental monitoring [9] presents astudy of a healthcare architecture for monitoring elderlyor chronic people in their residence Figure 12 sketchesthe reference network architecture where wearable sensorsystem (composed by a single belt of sensors) communicateswith powerful mobile computing devices through Bluetoothand the wireless sensor network through ZigBee The higherpart of the architecture includes communication technologiessuch as cellular-based networks and WiFi (or even WiMax)Although similar to WSN4QoLrsquos reference scenario sketchedin Figure 1 this architecture differs from that since patientssensors and ambient living WSN nodes form two dis-tinct subnetworks Nevertheless as in WSN4QoL the studyinvolves a real implementation of the proposed architecturein different scenarios including nursing-house home andhospital environments Besides the security aspects related tothe communication of patientsrsquo data the paper shows that thearchitecture is flexible enough to allow for querying the fixedwireless sensor network nodes and the mobile BANs overheterogeneous communication technologies Authors alsostressed that a tighter integration between the wireless sensornetwork and the wearable systems can be achieved through

the use of 6LoWPAN technologies and that biomedicalsensor positioning would be crucial to detect the location ofpeople at any place and any time [47]

In this line the work of [10 48ndash50] where the paradigmof the Internet of Things that is 6LoWPAN is applied tohealthcare and BSN systems is worth mentioning In par-ticular while [47] focuses on simulation results to assess theperformance of a proposed distributed handover procedureto support body sensors mobility and continuous access inthe other papers preliminary implementations approachesin TinyOS [21] are illustrated with particular emphasis onhandling mobility and inter-BSNs communications

Achieving location of the patients is one of the goals ofthe work presented in [10] and sketched in Figure 13 In thispaper however it is supposed that a wearable system builtupon smart shirts such as [34] is completely hardware-independent from the positioning subsystem built upondevices that each patient is also supposed to carry Both sub-systems communicatewith an IEEE 802154-enabledwirelesssensor network acting as distribution network between theterminals (patients) and the gateway to the public Internet-based network Once again however the two subsystems(sensor measurements reporting and patientsrsquo localization)are independent of each other while in WSN4QoL the goalis to make them converge into a single network able tosupport different services simultaneously The prototype hasbeen implemented and tested in a real-world scenario withinhospital facilities by equipping up to ten patients with thisequipment andpositive feedbackwas received by the hospitalpersonnel paving the way to future applications

The two-tier architecture is also the basis to the workpresented in [51 52] where scalability performance is eval-uated considering the IEEE 802154 at the lower tier andWLANIEEE 80211 at the upper tier of a healthcare mon-itoring system End-to-end packet delay and packet accesstime to WLAN have been evaluated as a function of thenumber of concurrent BANs (up to 50) Authors claim thatthere is need for choosing carefully network parametersbecause the interaction of high-data-rate streams such asEEG with lower-rate streams such as EKG or blood pressuredata causes some unwanted effects on the packet jitter of thelatterMoreover in [53] an overall comparison betweenGPRSand WLAN communication technologies for the higher tierof the system architecture is presented The study clearlyshows that GPRS and WLAN have complementary powerand delay profiles GPRS has lower power consumption tokeep network connectivity and send data but delays mightbe high whereas WLAN has higher energy cost but lowerdelays Finally the paper [54] where amapping of the qualityof service requirements for e-Health on the QoS classes of3GPP networks is presented is worth mentioning

A different technological approach is pursued in [5556] In this work to solve the issues related to RF interfer-ences authors investigate the potentiality of using infraredcommunication for data transmissions in mobile healthcarecontexts Simulation of scenarios of line of sight and diffuseconfigurations show that it is theoretically possible to achieveoptimal outage probabilities with very low transmissionpower which would help improve the energy efficiency of


Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station

Bluetooth ZigBeeSensor network

tier

Mobile computingnetwork tier

Back-end networktier

GPRS3G WiFi

Wearablesensorsystem

Figure 12 Healthcare system hierarchical network architecture in wireless sensor networks [9]

Smart shirt 1

Smart shirt 2

Smart shirt 3

Healthcare monitoringsubsystem

WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP

Figure 13 Healthcare monitoring and location systems [10]


such systems However although promising these resultsneed to be confirmed by experimental trials still far to beachieved

7 Conclusions

In this paper the WSN4QoL project has been described withparticular emphasis on its challenges and objectives in thearea of proposing efficient WSN-based solutions for perva-sive healthcare applications NC techniques and distributedpeople localization mechanisms have been implemented onrealWSN testbeds Preliminary tests in real working environ-ments gave promising results in line with our expectations

Future work will include the implementation of the pro-posed solutions in real medical devices as well as repeatingthese tests on a larger scale testbed Overall we believe thatthe intelligent implementation of the solutions proposed ina self-organized WSN will pave the way for a pervasivehealthcare system that is free of economic burdens and is ableto focus on the real needs of patients regardless of their agespan

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

Acknowledgments

This research was supported by the European Commissionunder the Marie Curie IAPP WSN4QoL project Grantno IAPP-GA-2011-286047 An earlier version of this paperappeared in the Proceedings of the IEEE 15th InternationalConference on e-Health Networking Application amp Services(HealthCom) 2013 [57]

References

[1] ldquoMidyear population by age and sexrdquo International databaseTable 094

[2] ldquoReport of the second world assembly on agingrdquo Tech RepUnited Nations Madrid Spain 2002

[3] K Kinsella and V Velkoff ldquoAn aging world 2001rdquo seriesp9501-1 US Census Bureau US Government Printing OfficeWashington DC USA 2001

[4] httpwwwhhmglobalcomknowledge-bankarticleshealth-spending-projections-through-2015-changes-on-the-horizon

[5] ETSI ldquoMachine to Machine Communications (M2M) UseCases ofM2MApplications for eHealthrdquoDraftTR 102732 v0412011

[6] ldquoWsn4qol Wireless sensor networks for quality of liferdquo 2014httpwwwwsn4qoleu

[7] P Harrop and R Das ldquoWireless sensor networks (wsn) 2012ndash2022 forecasts technologies playersmdashthe new market forubiquitous sensor networks (usn)rdquo Tech Rep IDTechEx 2012

[8] H Alemdar and C Ersoy ldquoWireless sensor networks forhealthcare a surveyrdquo Computer Networks vol 54 no 15 pp2688ndash2710 2010

[9] Y M Huang M Y Hsieh H C Chao S H Hung and J HPark ldquoPervasive secure access to a hierarchical sensor-basedhealthcare monitoring architecture in wireless heterogeneousnetworksrdquo IEEE Journal on Selected Areas in Communicationsvol 27 no 4 pp 400ndash411 2009

[10] G Lopez V Custodio and J I Moreno ldquoLOBIN E-textile andwireless-sensor-network-based platform for healthcare moni-toring in future hospital environmentsrdquo IEEE Transactions onInformation Technology in Biomedicine vol 14 no 6 pp 1446ndash1458 2010

[11] B Otal L Alonso and C Verikoukis ldquoHighly reliable energy-saving mac for wireless body sensor networks in healthcaresystemsrdquo IEEE Journal on Selected Areas in Communicationsvol 27 no 4 pp 553ndash565 2009

[12] K Prabh F Royo S Tennina and T Olivares ldquoBanmac anopportunistic mac protocol for reliable communications inbody area networksrdquo inProceedings of the IEEE 8th InternationalConference onDistributedComputing in Sensor Systems (DCOSSrsquo12) pp 166ndash175 2012

[13] E Ibarra A Antonopoulos E Kartsakli and C VerikoukisldquoEnergy harvesting aware hybrid mac protocol for wbansrdquo inProceedings of the IEEE 15th International Conference on e-Health Networking Applications Services (Healthcom rsquo13) pp120ndash124 2013

[14] Institute of Electrical and Electronics Engineers ldquoIEEE Std802154-2006 IEEE Standard for Information technologymdashTelecommunications and information exchange betweensystemsmdashLocal and metropolitan area networksmdashSpecificrequirements Part 154 Wireless Medium Access Control(MAC) and Physical Layer (PHY) Specifications for Low-RateWireless Personal Area Networks (WPANs)rdquo Institute ofElectrical and Electronics Engineers New York NY USA2006

[15] A Koubaa A Cunha and M Alves ldquoA time division beaconscheduling mechanism for IEEE 802154zigbee cluster-treewireless sensor networksrdquo in Proceedings of the 19th EuromicroConference on Real-Time Systems (ECRTS rsquo07) pp 125ndash135 July2007

[16] S Tennina A Koubaa R Daidone et al ldquoIEEE 802154 andZigBee as enabling technologies for low-power wireless systemswith quality-of-service constraintsrdquo in Briefs in Electrical andComputer Engineering p 464 Springer 2013

[17] T Ho M Medard R Koetter et al ldquoA random linear networkcoding approach to multicastrdquo IEEE Transactions on Informa-tion Theory vol 52 no 10 pp 4413ndash4430 2006

[18] R Bassoli H Marques J Rodriguez K Shum and R TafazollildquoNetwork coding theory a surveyrdquo IEEE CommunicationsSurveys Tutorials vol 15 pp 1950ndash1978 2013

[19] R Ahlswede N Cai S-Y R Li and R W Yeung ldquoNetworkinformation flowrdquo IEEE Transactions on Information Theoryvol 46 no 4 pp 1204ndash1216 2000

[20] Telosb mote platform httpwwwmemsiccom[21] Tinyos 2012 httpwwwtinyosnet[22] J-H Hauer ldquoTkn154 An IEEE 802154 macmdashimplementation

for tinyos 2rdquo Tech Rep TKN-08-003 Technical UniversityTelecommunication Networks Group Department Telecom-munication Networks (TKN) Berlin Germany 2009

[23] J-H Hauer R Daidone R Severino et al ldquoPoster abstract anopen-source ieee 802154 mac implementation for tinyos 21rdquoin Proceedings of the 8th European Conference onWireless SensorNetworks (EWSN rsquo11) Bonn Germany 2011


[24] A Antonopoulos and C Verikoukis ldquoNetwork-coding-basedcooperative ARQ medium access control protocol for wirelesssensor networksrdquo International Journal of Distributed SensorNetworks vol 2012 Article ID 601321 9 pages 2012

[25] S Tennina M D Renzo F Graziosi and F Santucci ldquoEsd anovel optimisation algorithm for positioning estimation ofwsnsin gps-denied environmentsmdashfrom simulation to experimenta-tionrdquo International Journal of Sensor Networks vol 6 pp 131ndash156 2009

[26] S Tennina M di Renzo F Graziosi and F Santucci ldquoLocatingzigbee nodes using the tis cc2431 location engine a testbedplatform and new solutions for positioning estimation of wsnsin dynamic indoor environmentsrdquo in Proceedings of the 1stACM International Workshop onMobile Entity Localization andTracking in GPS-Less Environments (MELT rsquo08) pp 37ndash42 NewYork NY USA September 2008

[27] Chipcon ldquoC2430dk development kit datasheetrdquo 2009 httpwwwticom

[28] ldquoWinprop software packagerdquo 2013 httpwwwawe-communi-cationscom

[29] M Conti S K Das C Bisdikian et al ldquoLooking ahead inpervasive computing challenges and opportunities in the era ofcyberphysical convergencerdquo Pervasive and Mobile Computingvol 8 no 1 pp 2ndash21 2012

[30] K-D Kim and P R Kumar ldquoCyber-physical systems a perspec-tive at the centennialrdquoProceedings of the IEEE vol 100 pp 1287ndash1308 2012

[31] H-H Ku and C-M Huang ldquoWeb2OHS a Web20-basedomnibearing homecare systemrdquo IEEE Transactions on Informa-tion Technology in Biomedicine vol 14 no 2 pp 224ndash233 2010

[32] H Jumaa P Rubel and J Fayn ldquoAn XML-based frameworkfor automating data exchange in healthcarerdquo in Proceedings ofthe 12th IEEE International Conference on e-Health NetworkingApplication and Services (Healthcom rsquo10) pp 264ndash269 July 2010

[33] S Patel H Park P Bonato L Chan and M Rodgers ldquoAreview of wearable sensors and systems with application inrehabilitationrdquo Journal of NeuroEngineering and Rehabilitationvol 9 pp 1ndash17 2012

[34] M di Rienzo P Meriggi F Rizzo et al ldquoTextile technologyfor the vital signs monitoring in telemedicine and extremeenvironmentsrdquo IEEE Transactions on Information Technology inBiomedicine vol 14 no 3 pp 711ndash717 2010

[35] XSENS ldquoXsens researchrdquo 2012 httpwwwxsenscomtechno-logyresearch

[36] L Lhotska O Stepankova M Pechoucek B Simak andJ Chod ldquoICT and eHealth projectsrdquo in Proceedings of theTechnical Symposium at ITU Telecom World (ITU WT rsquo11) pp57ndash62 October 2011

[37] T Yilmaz R Foster and Y Hao ldquoDetecting vital signs withwearablewireless sensorsrdquo Sensors vol 10 no 12 pp 10837ndash10862 2010

[38] G J Mandellos M N Koukias I S Styliadis and D K Lym-beropoulos ldquoE-SCP-ECG + protocol an expansion on SCP-ECG protocol for health telemonitoringpilot implementationrdquoInternational Journal of Telemedicine andApplications vol 2010Article ID 137201 17 pages 2010

[39] H Wang D Peng W Wang H Sharif H-H Chen and AKhoynezhad ldquoResource-aware secure ECG healthcare moni-toring through body sensor networksrdquo IEEE Wireless Commu-nications vol 17 no 1 pp 12ndash19 2010

[40] M Xu A Goldfain A R Chowdhury and J DellostrittoldquoTowards accelerometry based static posture identificationrdquoin Proceedings of the IEEE Consumer Communications andNetworking Conference (CCNC rsquo2011) pp 29ndash33 2011

[41] ldquoRd3965mma7660fc Zstar3 featuring the mma7660fcrdquo 2012httpwwwfreescalecomwebappspssiteprod summaryjspcode=RD3965MMA7660FC

[42] S Abbate M Avvenuti G Cola P Corsini J Light and AVecchio ldquoRecognition of false alarms in fall detection systemsrdquoin Proceedings of the IEEE Consumer Communications andNetworking Conference (CCNC rsquo2011) pp 23ndash28 January 2011

[43] ldquoShimmer Wireless sensor solutionsrdquo 2012 httpwwwshim-mer-researchcom

[44] R Rednic J Kemp E Gaura and J Brusey ldquoNetworked bodysensing enabling real-time decisions in health and defenceapplicationsrdquo in Proceedings of the International Conference onAdvanced Computer Science and Information Systems (ICACSISrsquo11) pp 17ndash23 December 2011

[45] R L Dellaca A Gobbi L Govoni D Navajas A Pedottiand R Farre ldquoA novel simple internet-based system for realtimemonitoring and optimizing homemechanical ventilationrdquoin Proceedings of the International Conference on eHealthTelemedicine and Social Medicine (eTELEMED rsquo09) pp 209ndash215 February 2009

[46] ldquoAcme systemsrdquo 2012 httpwwwacmesystemsit[47] J Caldeira J Rodrigues and P Lorenz ldquoToward ubiquitous

mobility solutions for body sensor networks on healthcarerdquoIEEE Communications Magazine vol 50 pp 108ndash115 2012

[48] D Singh U S Tiwary and W-Y Chung ldquoIP-based ubiquitoushealthcare systemrdquo in Proceedings of the International Confer-ence on Control Automation and Systems (ICCAS rsquo08) pp 131ndash136 October 2008

[49] D Singh H-P Kew U S Tiwary H-J Lee and W-Y ChungldquoGlobal patient monitoring system using IP-enabled ubiquitoussensor networkrdquo in Proceedings of the WRI World Congress onComputer Science and Information Engineering (CSIE rsquo09) pp524ndash528 April 2009

[50] A J JaraM A Zamora andA F G Skarmeta ldquoAn architecturebased on internet of things to support mobility and securityin medical environmentsrdquo in Proceedings of the 7th IEEEConsumer Communications and Networking Conference (CCNCrsquo10) pp 1ndash5 January 2010

[51] J Misic and V B Misic ldquoBridge performance in a multitierwireless network for healthcare monitoringrdquo IEEE WirelessCommunications vol 17 no 1 pp 90ndash95 2010

[52] J Misic and V Misic ldquoBridging between ieee 802154 and IEEE80211b networks for multiparameter healthcare sensingrdquo IEEEJournal on Selected Areas in Communications vol 27 no 4 pp435ndash449 2009

[53] K Wac M Bargh B-J van Beijnum R Bults P Pawarand A Peddemors ldquoPower- and delay-awareness of healthtelemonitoring services the mobihealth system case studyrdquoIEEE Journal on Selected Areas in Communications vol 27 no4 pp 525ndash536 2009

[54] L Skorin-Kapov and M Matijasevic ldquoAnalysis of QoS require-ments for e-Health services and mapping to evolved packetsystem QoS classesrdquo International Journal of Telemedicine andApplications vol 2010 Article ID 628086 18 pages 2010

[55] S S Torkestani N Barbot S Sahuguede A Julien-Vergonjanne and J P Cances ldquoPerformance and transmissionpower bound analysis for optical wireless based mobile


healthcare applicationsrdquo in Proceedings of the IEEE 22ndInternational Symposium on Personal Indoor and Mobile RadioCommunications (PIMRC rsquo11) pp 2198ndash2202 September 2011

[56] S S Torkestani A Julien-Vergonjanne and J P CancesldquoMobile healthcare monitoring in hospital based on diffuseoptical wireless technologyrdquo in Proceedings of the IEEE 21stInternational Symposium on Personal Indoor and Mobile RadioCommunications (PIMRC rsquo10) pp 1055ndash1059 September 2010

[57] S Tennina E Kartsakli andA Lalos ldquoWsn4qol wireless sensornetworks for quality of liferdquo in Proceedings of the IEEE 15thInternational Conference on e-Health Networking Application ampServices (HealthCom rsquo13) Lisbon Portugal 2013

Submit your manuscripts athttpwwwhindawicom

VLSI Design

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

International Journal of

RotatingMachinery


Hindawi Publishing Corporation httpwwwhindawicom

Journal ofEngineeringVolume 2014


Shock and Vibration


Mechanical Engineering

Advances in


Civil EngineeringAdvances in

Acoustics and VibrationAdvances in



Electrical and Computer Engineering

Journal of


Distributed Sensor Networks


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

SensorsJournal of


Modelling amp Simulation in EngineeringHindawi Publishing Corporation httpwwwhindawicom Volume 2014


Active and Passive Electronic Components


Chemical EngineeringInternational Journal of

Control Scienceand Engineering

Journal of


Antennas andPropagation




Navigation and Observation


Advances inOptoElectronics


Volume 2014

RoboticsJournal of



infrastructure has begun to emerge enabling new ldquopervasivehealthcarerdquo applications more often shortly termed as ldquoe-Healthrdquo applications The availability of these networks andthe widespread use of mobile devices make two-way contin-uous interactions between patients and their care providersfeasible regardless of physical location

On the other hand the use of information and com-munication technologies to facilitate and improve healthcareand medical services involves the use of appropriate devicesboth on patients and embedded in the living environmentResearchers and educators predict that these gadgets willsoon turn the home into a medical nurse keeping recordon everything from pill-taking routines to signs of imminentcrises

For seniors the benefits of an idealized medical smarthome are physical psychological and emotional Aging inplace means continuing with familiar routines while healthdata detection of critical conditions and remote control ofcertain medical treatments are wirelessly made available todoctors caregivers and concerned family [5] For societythe bonuses include significantly reduced health care costsand happier elders Consequently it is natural to expectthat consumers will embrace in-home technologies preciselybecause they can potentially save them money on the cost ofunnecessary time-consuming doctor visits thus not jeopar-dizing their daily life activities

On this subject this paper aims to present theWSN4QoLproject [6] which involves the design of wireless sensornetworks (WSNs) specifically suited to meet healthcareapplication requirements WSN4QoL is a 3-year projectstarted at the end of 2011 and still ongoing With theintent of bringing together experts from industry andacademia it proposes the use of advanced WSN tech-nologies for pervasive healthcare applications In particu-lar it aims at providing network coding (NC) for multi-hopcooperative diversity in the data communication pro-tocol as well as distributed localization algorithms to meetthe specific requirements of WSNs-enabled healthcare appli-cations namely energy-efficiency low-latency data reliabil-ity context-awareness and security Extensive performanceanalysis of the proposed solutions is given through numericalsimulations as well as proofs-of-concept in real-world exper-iments through the implementation into real healthcaredevices

The rest of the paper is organized as follows Section 2overviews the full system architecture presenting the designchallenges offered by the general reference scenario whileSection 3 puts particular emphasis on the key elements ofthe communication protocol stack and the middleware ofservices offered to the application designers Sections 4 and5 present the NC and the localization testbeds respec-tively that have been implemented to evaluate the solutionsproposed in real(istic) environments Section 6 deals with asummary of current research efforts with similar objectivesto WSN4QoL Finally Section 7 concludes the paper witha view on some of the open issues to be addressed asongoing and future work in the remainingWSN4QoL projectperiod

2 WSNs System Architecture Designfor E-Health

WSNs are distributed networked embedded systems whereeach node combines sensing computing communicationand storage capabilities They have emerged as a newnetworking environment that provides end-users withintelligence and a better understanding of the environmentBecause of their wide variety of applications it is envisionedthat in the near future WSNs will become an integralpart of our everyday lives [7] WSNs are wireless ad hocnetworks composed of inexpensive nodes with sensingcapabilities and a limited number of data sink nodes Thesenodes communicate among each other by forming multihopwireless networks and by maintaining connectivity in acentralized or a distributed manner The network topologyis in general dynamic since the connectivity among thenodes may vary with nomadic and mobile nodes

21 Challenges Although fundamental research results onWSNs theory and practice have been achieved for manydifferent applications for example traffic monitoring plantmonitoring in agriculture and infrastructure monitoringthe application of this technology to e-Health poses someunique application-specific challenges and constraints Inparticular the efficient design of a WSNs-enabled pervasivehealthcare system is characterized by the following intrinsicdifferences with respect to ldquogeneral-purposerdquo WSNs designwhich require special attention [8] (i) The devices havelimited available energy resources as they have a very smallform factor (ii) A low transmit power per node is neededto minimize interference and to cope with health concerns(iii) The devices are located on the human body whichcan be in motion WSNs for e-Health should therefore berobust against frequent changes in the network topologyand channel variability (iv) Data mostly consist of medicalinformation hence high reliability and low delaylatencyare required (v) Stringent security mechanisms are requiredto ensure the private and confidential character of data(vi) Context-awareness through cooperative localization inoutdoors and indoors is crucial to enable a prompt reactionin case of emergency (vii) The devices are in general veryheterogeneousTheymay have very different demands ormayrequire different resources of the network in terms of datarates power consumption and reliability

Along these lines the main research objective ofWSN4QoL is to provide fundamental research advancesproof-of-concepts and real-life implementations on themainenabling technologies forWSNs-aided e-Health applicationsMore specifically disruptive techniques such as cooperativewireless communications protocols and distributed algo-rithms are investigatedThe proposed solutions are designedoptimized and implemented in real-devices by taking intoaccount the specific requirements of e-Health energy effi-ciency low-latency delivery of data data reliability andsecurity In more detail the research objectives ofWSN4QoLinclude the following (i) to design a protocol stack archi-tecture which can accommodate a variety of protocols


Bluetooth

PDAlaptop



Internet

Doctor












Middleware

Application

Network

MAC


MLME SAP MCPS SAP



Customized APIs

High level APIs



















4 Network Coding


PktA

A

C

D

PktC

PktB

B




















Sleep mode 1 uA









Synch Synch

SynchSynch

Data 1

Data 1

Data 2

Tslot

Tslot

Tslot

Tslot


Data 2

Tslot


Xor(Data 1 Data 2)

Tslot

Tslot

Tslot


Tslot

Data 2

Data 1

Synch

Synch Synch

Synch




0

05

1

15

2

25

3

06

Goo

dput

(pkt

s)






+48









1

1

3

5

6

RSSI

RSSI RSSI RSSI RSSI

RSSIRSSI RSSI

RSSI

RSSI

RSSI

RSSI

RSSI RSSI RSSIRSSI

RSSI

(1 2) (1 3)(1 2) (1 3)

A1

2 (2 1)

A2

3 (3 1) (3 4) (3 5) (3 6)

(3 1) (3 4) (3 5) (3 6)

A4

4 (4 3)RSSI

6 (6 3)

(6 3)

RSSI5 (5 3)

(5 3)

A3SN

A6

A5A

n

[D(1 3) RSSI(1 3)]

Distance

X2 Y2

X1 Y1

X3 Y3

X5 Y5

X6 Y6

X6Y6

X5 Y5

X4Y4

X3 Y3

X1 Y1




Sequencenumber


header


MHR MAC payload MFR

Node unique address

Position RSSIs














163

5

1

545m492m

204m

144m

038m

054m

148m

136m249m

1998400

161

162

3

9

2

7

165

164

166

8

13

5998400

3998400

9998400

7998400

2998400

13998400

8998400

6

6998400





























Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of



Bluetooth

PDAlaptop



Internet

Doctor












Middleware

Application

Network

MAC


MLME SAP MCPS SAP



Customized APIs

High level APIs



















4 Network Coding


PktA

A

C

D

PktC

PktB

B




















Sleep mode 1 uA









Synch Synch

SynchSynch

Data 1

Data 1

Data 2

Tslot

Tslot

Tslot

Tslot


Data 2

Tslot


Xor(Data 1 Data 2)

Tslot

Tslot

Tslot


Tslot

Data 2

Data 1

Synch

Synch Synch

Synch




0

05

1

15

2

25

3

06

Goo

dput

(pkt

s)






+48









1

1

3

5

6

RSSI

RSSI RSSI RSSI RSSI

RSSIRSSI RSSI

RSSI

RSSI

RSSI

RSSI

RSSI RSSI RSSIRSSI

RSSI

(1 2) (1 3)(1 2) (1 3)

A1

2 (2 1)

A2

3 (3 1) (3 4) (3 5) (3 6)

(3 1) (3 4) (3 5) (3 6)

A4

4 (4 3)RSSI

6 (6 3)

(6 3)

RSSI5 (5 3)

(5 3)

A3SN

A6

A5A

n

[D(1 3) RSSI(1 3)]

Distance

X2 Y2

X1 Y1

X3 Y3

X5 Y5

X6 Y6

X6Y6

X5 Y5

X4Y4

X3 Y3

X1 Y1




Sequencenumber


header


MHR MAC payload MFR

Node unique address

Position RSSIs














163

5

1

545m492m

204m

144m

038m

054m

148m

136m249m

1998400

161

162

3

9

2

7

165

164

166

8

13

5998400

3998400

9998400

7998400

2998400

13998400

8998400

6

6998400





























Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of



Middleware

Application

Network

MAC


MLME SAP MCPS SAP



Customized APIs

High level APIs



















4 Network Coding


PktA

A

C

D

PktC

PktB

B




















Sleep mode 1 uA









Synch Synch

SynchSynch

Data 1

Data 1

Data 2

Tslot

Tslot

Tslot

Tslot


Data 2

Tslot


Xor(Data 1 Data 2)

Tslot

Tslot

Tslot


Tslot

Data 2

Data 1

Synch

Synch Synch

Synch




0

05

1

15

2

25

3

06

Goo

dput

(pkt

s)






+48









1

1

3

5

6

RSSI

RSSI RSSI RSSI RSSI

RSSIRSSI RSSI

RSSI

RSSI

RSSI

RSSI

RSSI RSSI RSSIRSSI

RSSI

(1 2) (1 3)(1 2) (1 3)

A1

2 (2 1)

A2

3 (3 1) (3 4) (3 5) (3 6)

(3 1) (3 4) (3 5) (3 6)

A4

4 (4 3)RSSI

6 (6 3)

(6 3)

RSSI5 (5 3)

(5 3)

A3SN

A6

A5A

n

[D(1 3) RSSI(1 3)]

Distance

X2 Y2

X1 Y1

X3 Y3

X5 Y5

X6 Y6

X6Y6

X5 Y5

X4Y4

X3 Y3

X1 Y1




Sequencenumber


header


MHR MAC payload MFR

Node unique address

Position RSSIs














163

5

1

545m492m

204m

144m

038m

054m

148m

136m249m

1998400

161

162

3

9

2

7

165

164

166

8

13

5998400

3998400

9998400

7998400

2998400

13998400

8998400

6

6998400





























Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of









4 Network Coding


PktA

A

C

D

PktC

PktB

B




















Sleep mode 1 uA









Synch Synch

SynchSynch

Data 1

Data 1

Data 2

Tslot

Tslot

Tslot

Tslot


Data 2

Tslot


Xor(Data 1 Data 2)

Tslot

Tslot

Tslot


Tslot

Data 2

Data 1

Synch

Synch Synch

Synch




0

05

1

15

2

25

3

06

Goo

dput

(pkt

s)






+48









1

1

3

5

6

RSSI

RSSI RSSI RSSI RSSI

RSSIRSSI RSSI

RSSI

RSSI

RSSI

RSSI

RSSI RSSI RSSIRSSI

RSSI

(1 2) (1 3)(1 2) (1 3)

A1

2 (2 1)

A2

3 (3 1) (3 4) (3 5) (3 6)

(3 1) (3 4) (3 5) (3 6)

A4

4 (4 3)RSSI

6 (6 3)

(6 3)

RSSI5 (5 3)

(5 3)

A3SN

A6

A5A

n

[D(1 3) RSSI(1 3)]

Distance

X2 Y2

X1 Y1

X3 Y3

X5 Y5

X6 Y6

X6Y6

X5 Y5

X4Y4

X3 Y3

X1 Y1




Sequencenumber


header


MHR MAC payload MFR

Node unique address

Position RSSIs














163

5

1

545m492m

204m

144m

038m

054m

148m

136m249m

1998400

161

162

3

9

2

7

165

164

166

8

13

5998400

3998400

9998400

7998400

2998400

13998400

8998400

6

6998400





























Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of
















Sleep mode 1 uA









Synch Synch

SynchSynch

Data 1

Data 1

Data 2

Tslot

Tslot

Tslot

Tslot


Data 2

Tslot


Xor(Data 1 Data 2)

Tslot

Tslot

Tslot


Tslot

Data 2

Data 1

Synch

Synch Synch

Synch




0

05

1

15

2

25

3

06

Goo

dput

(pkt

s)






+48









1

1

3

5

6

RSSI

RSSI RSSI RSSI RSSI

RSSIRSSI RSSI

RSSI

RSSI

RSSI

RSSI

RSSI RSSI RSSIRSSI

RSSI

(1 2) (1 3)(1 2) (1 3)

A1

2 (2 1)

A2

3 (3 1) (3 4) (3 5) (3 6)

(3 1) (3 4) (3 5) (3 6)

A4

4 (4 3)RSSI

6 (6 3)

(6 3)

RSSI5 (5 3)

(5 3)

A3SN

A6

A5A

n

[D(1 3) RSSI(1 3)]

Distance

X2 Y2

X1 Y1

X3 Y3

X5 Y5

X6 Y6

X6Y6

X5 Y5

X4Y4

X3 Y3

X1 Y1




Sequencenumber


header


MHR MAC payload MFR

Node unique address

Position RSSIs














163

5

1

545m492m

204m

144m

038m

054m

148m

136m249m

1998400

161

162

3

9

2

7

165

164

166

8

13

5998400

3998400

9998400

7998400

2998400

13998400

8998400

6

6998400





























Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of



Synch Synch

SynchSynch

Data 1

Data 1

Data 2

Tslot

Tslot

Tslot

Tslot


Data 2

Tslot


Xor(Data 1 Data 2)

Tslot

Tslot

Tslot


Tslot

Data 2

Data 1

Synch

Synch Synch

Synch




0

05

1

15

2

25

3

06

Goo

dput

(pkt

s)






+48









1

1

3

5

6

RSSI

RSSI RSSI RSSI RSSI

RSSIRSSI RSSI

RSSI

RSSI

RSSI

RSSI

RSSI RSSI RSSIRSSI

RSSI

(1 2) (1 3)(1 2) (1 3)

A1

2 (2 1)

A2

3 (3 1) (3 4) (3 5) (3 6)

(3 1) (3 4) (3 5) (3 6)

A4

4 (4 3)RSSI

6 (6 3)

(6 3)

RSSI5 (5 3)

(5 3)

A3SN

A6

A5A

n

[D(1 3) RSSI(1 3)]

Distance

X2 Y2

X1 Y1

X3 Y3

X5 Y5

X6 Y6

X6Y6

X5 Y5

X4Y4

X3 Y3

X1 Y1




Sequencenumber


header


MHR MAC payload MFR

Node unique address

Position RSSIs














163

5

1

545m492m

204m

144m

038m

054m

148m

136m249m

1998400

161

162

3

9

2

7

165

164

166

8

13

5998400

3998400

9998400

7998400

2998400

13998400

8998400

6

6998400





























Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of




1

1

3

5

6

RSSI

RSSI RSSI RSSI RSSI

RSSIRSSI RSSI

RSSI

RSSI

RSSI

RSSI

RSSI RSSI RSSIRSSI

RSSI

(1 2) (1 3)(1 2) (1 3)

A1

2 (2 1)

A2

3 (3 1) (3 4) (3 5) (3 6)

(3 1) (3 4) (3 5) (3 6)

A4

4 (4 3)RSSI

6 (6 3)

(6 3)

RSSI5 (5 3)

(5 3)

A3SN

A6

A5A

n

[D(1 3) RSSI(1 3)]

Distance

X2 Y2

X1 Y1

X3 Y3

X5 Y5

X6 Y6

X6Y6

X5 Y5

X4Y4

X3 Y3

X1 Y1




Sequencenumber


header


MHR MAC payload MFR

Node unique address

Position RSSIs














163

5

1

545m492m

204m

144m

038m

054m

148m

136m249m

1998400

161

162

3

9

2

7

165

164

166

8

13

5998400

3998400

9998400

7998400

2998400

13998400

8998400

6

6998400





























Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of




Sequencenumber


header


MHR MAC payload MFR

Node unique address

Position RSSIs














163

5

1

545m492m

204m

144m

038m

054m

148m

136m249m

1998400

161

162

3

9

2

7

165

164

166

8

13

5998400

3998400

9998400

7998400

2998400

13998400

8998400

6

6998400





























Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of



163

5

1

545m492m

204m

144m

038m

054m

148m

136m249m

1998400

161

162

3

9

2

7

165

164

166

8

13

5998400

3998400

9998400

7998400

2998400

13998400

8998400

6

6998400





























Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of























Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of












Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of



Internet

Ad hoc

Wirelesssensor

network

Remotestation Local

station


tier



GPRS3G WiFi



Smart shirt 1

Smart shirt 2

Smart shirt 3


WSN802154(non-IP)

Locationsubsystem

Gateway

IPnetwork

Managementsubsystem

Managementserver

GUIs

WTB

BP

DP




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of




7 Conclusions





Acknowledgments


References





























































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of








































VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of







VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of



VLSI Design



RotatingMachinery





Shock and Vibration



Advances in







Journal of





SensorsJournal of








Journal of










Volume 2014

RoboticsJournal of


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