INSTRUMENTING BOMB DISPOSAL SUITS WITH WIRELESS

ENSOR NETWORKS

John Kemp, Elena I. Gaura and James Brusey

Cogent Computing Applied Research Centre, Coventry University, Priory St, Coventry, CV1 5FB, U.K.

Keywords:

Body sensor networks, ﬁrst responders, actuation.

Abstract:

Bomb disposal suits contain a large amount of padding and armour to protect the wearer’s vital organs in the

case of explosion. The combination of the heavy (roughly 40kg) suit, physical exertion, and the environment

in which these suits are worn can cause the wearer’s temperature to rise to uncomfortable and potentially

dangerous levels during missions. This paper reports on the development of a wearable wireless sensing

system suitable for deployment in such manned bomb disposal missions. In its ﬁnal form, the system will

be capable of making in-network autonomous decisions related to the actuation of cooling within the suit, in

order to increase the comfort of the wearer. In addition, it will allow an external observer to remotely monitor

the health and comfort of the operative. Laboratory experiments with the instrumented suit show how skin

temperature varies differently for different skin sites, motivating the need for multiple, distributed sensing.

The need for timely application of in-suit cooling is also shown, as well as the importance of monitoring the

overall health of the wearer of the suit.

1 INTRODUCTION

The monitoring of hazardous environments, along

with the people working within them, is an area which

lends itself to the use of wireless and body sensor

networks (WSNs and BSNs). The ﬁeld is rich with

potential WSN applications in detecting hazards, pro-

viding feedback to remote observers and other critical

tasks that can increase the safety and beneﬁt the over-

all working conditions of people operating in these

environments. This paper reports the work towards

the development of a wireless body sensor network

for the protective suits worn in bomb disposal mis-

sions.

A typical bomb disposal mission will initially in-

volve investigating the site using a remote controlled

robot, and if possible, disarming the bomb remotely.

Sometimes, however, it is necessary for a human

bomb disposal expert to disarm the device. For this,

the expert will put on a protective suit and helmet (as

shown in ﬁgure 1), pick up a tool box of equipment,

and walk the 100 or so metres to the site. To reach the

bomb’s location, it may be necessary to climb stairs,

crawl through passageways, or even lie down.

The environment where the suit is used, such as

the hot climate of the Middle East, plays an impor-

Figure 1: Explosive Ordinance Disposal (EOD)Suit.

ant role in the design of the protective suit. One of

the UK manufacturers of such suits has identiﬁed the

problem of the suit wearer becoming uncomfortably

hot and, in the worst case, suffering heat exhaustion.

They have attempted to address this by installing an

in-suit cooling system based on a dry-ice pack and a

fan that cycles air through the pack and blows cooled

air onto the wearer’s back and into the helmet. The

cooling system has a variable control thus both allow-

ing the airﬂow to be adjusted for comfort and also

allowing the life of the batteries that power the fan

to be extended, as they would only provide sufﬁcient

power for part of the mission otherwise. The problem

with this cooling approach, though, is that the bomb

disposal expert has other critical concerns during the

mission and either does not bother to put the fan on or

tends to set it to maximum airﬂow from the beginning

Kemp J., I. Gaura E. and Brusey J. (2008).

INSTRUMENTING BOMB DISPOSAL SUITS WITH WIRELESS SENSOR NETWORKS.

In Proceedings of the Fifth International Conference on Informatics in Control, Automation and Robotics - SPSMC, pages 23-31

DOI: 10.5220/0001486400230031

 SciTePress

of the mission.

To address the above problems, this work pro-

poses embedding into the suit a body sensor network

that aims to:

• sense the temperature of the skin of various parts

of the body, in order to assess overall comfort, and

• adjust the cooling dynamically to both remove the

need for human intervention, and also to prolong

battery life.

The prolonging of battery life is intended to provide

cooling over the whole mission duration (compared

to the partial coverage provided currently) rather than

increasing the mission duration itself.

A secondary goal of this work is to help the

manufacturer better understand how the suit material

and design choices are affecting the wearer’s thermal

comfort during use. Finally, the prototype presented

here has been designed such as to allow easy integra-

tion of additional sensors, such as accelerometers to

monitor posture, heart rate monitors, and CO

sens-

ing within the helmet.

The paper is organised as follows: Section 2 ex-

amines related work, focusing in particular on body

sensor networks and research relating to instrument-

ing ﬁrst responders (such as police, ﬁre services etc).

Section 3 describes the system design and architec-

ture developed for the prototype system produced to

date. Section 4 contains an evaluation of the proto-

type. Finally the paper concludes with some obser-

vations based on the work so far and outlines future

work.

2 RELATED WORK

The work reported in this paper is most closely

aligned with respect to the instrumentation design and

implementation with the ﬁeld of Body Sensor Net-

works. This is a sub-area of Wireless Sensor Net-

works that makes use of a combination of wireless

and miniaturised sensor technologies to monitor the

human body. The scope of present BSN approaches

is patient care. Such systems are either designed to fo-

cus on capturing the evolution of a particular physio-

logical parameter and ensuring that alarms are gener-

ated when parameters stray outside a safe range (Keoh

et al., 2007), or aimed to provide general monitoring

solutions for patient status within a hospital or similar

environment (Shnayder et al., 2005). In comparison,

the work presented here is concerned with increased

safety and comfort of human subjects in constrained

environments through integrating sensing, actuation,

and autonomous decision making. In this context,

wireless sensor technology is used as an enabler for

the necessary detailed measurement of physiological

parameters. 5A This work shares some of the design

space of BSN in terms of the type of physiological

parameters sensed and the wearability requirements

of the implemented system. On the other hand, given

that the application is within the safety critical do-

main, the work here also shares some common char-

acteristics with the area of instrumenting and monitor-

ing ﬁrst responders. In this section, samples of BSN

platforms are reviewed together with commercial in-

stances of ﬁrst responder monitoring and prior, moti-

vating, physiological ﬁndings about the EOD suit.

2.1 Body Sensor Networks—Platforms

BSN based systems are often more constrained than

ordinary embedded systems. These constraints are

mainly in terms of power, size and weight. Power

is restricted because mains AC power is not avail-

able. Furthermore, size and weight restrictions limit

the battery supplies that can be used. Size and weight

must be limited because large and heavy devices

would be cumbersome, uncomfortable, and in appli-

cations such as the one described here, an unnecessary

distraction.

In response to the above, some of the BSN sys-

tems designed and implemented by research groups

integrate within the nodes an appropriate central pro-

cessing unit, memory and radio transceiver as a single

custom chip. An example here is the MITes platform

(for monitoring movement of human subjects) devel-

oped by (Tapia et al., 2004), which is based around the

Nordic VLSI Semiconductors nRF24E1 chip. This

chip integrates a radio transceiver and an Intel 8051

based processor core that runs at 16MHz and pro-

vides a nine channel 12-bit ADC and various other in-

terfaces, such as SPI (serial peripheral interface) and

GPIO (general purpose I/O). This approach is efﬁ-

cient in terms of size and weight due to the integra-

tion of several functions into one chip, but has limited

generality as it can not be easily adapted for new ap-

plications.

Another, more popular design option is to use off-

the-shelf components. There is a trade off made be-

tween processing and storage capabilities and the size

and power consumption of the devices. This means

that the devices selected would likely be considered

severely under-powered in other systems (often in-

cluding 16- or even 8-bit processors) and have small

amounts of memory (in the order of tens or hundreds

of kilobytes). For instance, the Texas Instruments

MSP430F149 micro-controller has been used for sev-

eral systems including those developed by (Lo and

ICINCO 2008 - International Conference on Informatics in Control, Automation and Robotics

Yang, 2005) and (Jovanov et al., 2001). This is a 16-

bit processor running at 8MHz incorporating 60KB

of ﬂash memory and 2KB of RAM and provides in-

terfacing opportunities via 48 GPIO lines and a 12-bit

ADC. The system developed by Lo and Yang used

ECG sensors, accelerometers, and a temperature sen-

sor to monitor patient health. The system developed

by Jovanov et al., was used for monitoring the elderly

and those undergoing physiotherapy.

Other systems expand upon commercial devices

such as the Mica2 and MicaZ motes developed at the

University of California, Berkeley, or Intel’s Imote

platform. This approach often has a disadvantage in

that the basic platform is generic, and may not di-

rectly provide the facilities required for the speciﬁc

BSN project. Such commercial platforms are also

often larger and heavier than custom developed plat-

forms as they are required to be general purpose in

order to achieve any commercial success. The MicaZ

mote uses the Atmega128L, an 8-bit processor run-

ning at 8MHz and featuring 128KB of ﬂash memory

to which an additional 512KB is added externally on

the mote itself. A 10-bit ADC, UART and I2C bus are

also available. (Gao et al., 2005) developed a system

based around the this mote, adding various sensors

and supporting devices to allow patient tagging and

monitoring in an emergency response environment.

(Walker et al., 2006) present a blood pressure mon-

itoring system based on the MicaZ platform. In that

work, a commercial blood pressure monitoring device

is connected to the MicaZ via a serial interface.

2.2 Instrumenting First Responders

The best ﬁt example of a commercial product de-

signed for the purpose of monitoring personnel carry-

ing out missions in dangerous environments is the Vi-

voResponder by (Vivometrics, 2007). VivoResponder

is based upon an earlier product called the LifeShirt

and is aimed at personnel engaged in ﬁreﬁghting

and hazardous materials training or emergency re-

sponse, industrial clean-ups using protective gear, and

biohazard-related occupational work. The VivoRe-

sponder is supplied in three parts: a lightweight, ma-

chine washable chest strap with embedded sensors; a

data receiver; and, VivoCommand software for moni-

toring and data analysis. The sensors embedded in the

chest strap monitor the subject’s breathing rate, heart

rate, activity level, posture, and single point skin tem-

perature.

Monitoring of the subject’s breathing is performed

using a method called inductive plethysmography,

where breathing patterns are monitored by passing a

low voltage electrical current through a series of con-

tact points around the subject’s ribcage and abdomen.

Monitoring of the subject’s heart rate is performed via

an ECG.

The VivoCommand software, provided with the

device, displays the gathered data from the chest strap

in real-time on a remote PC. The parameters are up-

dated every second along with 30-second average

trends. The parameters are displayed with colour cod-

ing intended to allow quick assessment of the status of

up to 25 monitored personnel simultaneously. Base-

line readings can be set individually per monitored

person.

The work developed here differs in intent: the aim

here is to provide a detailed thermal assessment based

on sensors integrated into the protective suit and de-

liver remotely abstracted comfort information.

2.3 Other Work on EOD Suits

Working from a physiological perspective, (Thake

and Price, 2007) have investigated the thermal strain

of a subject when wearing EOD suits in hot envi-

ronments. The work looks at quantifying the level

of strain by assessing how hot and tired the suit

wearer feels whilst wearing various combinations of

suit components. An “activity” regime was developed

for the assessment based on the types of activities that

a bomb disposal technician would undergo during a

mission and included walking on a treadmill, unload-

ing and loading weights from a rucksack, crawling

and searching activity, arm cranking and cognitive

tests. Aspects of hand-eye coordination and psycho-

logical performance were also assessed. The inves-

tigations have demonstrated a large increase in phys-

iological strain when wearing the EOD suit, though

beneﬁts have been shown when the ambient air is

cooled for the suit ventilation purpose and lighter-

weight trousers are worn.

It is indeed these types of studies, together with

the user requests, that prompted the development

of the detailed physiological monitoring system pre-

sented in this paper. The activity regimes described

by Thake and Price were used in the experiments pre-

sented in this paper to allow validation of ﬁndings.

3 SYSTEM DESIGN AND

ARCHITECTURE

The main part of the prototype system is designed

following a sense-model-decide-act architecture as

shown in ﬁgure 2. The environment within the suit

is sensed in terms of temperature; sensed data is in-

tegrated into a model representing the thermal state

INSTRUMENTING BOMB DISPOSAL SUITS WITH WIRELESS SENSOR NETWORKS

environment

sense

model

decide

act

transmit

visualise

mission plan

changes

Figure 2: Conceptual design of prototype system.

of the wearer; a decision is made about how to ad-

just the cooling system based on the thermal state; ﬁ-

nally, the determined action is transmitted to the fan

speed controller. In addition to this basic architec-

ture, the system also transmits inferred state values

for the purpose of remote, on-line, visualisation of

the thermal state of the wearer. From this visualisa-

tion, the operator can assess how different parts of

the mission, or different actions being taken by the

suit wearer are affecting their thermal state and hence

assess the wearer’s ﬁtness for the mission. (It is ex-

pected that such information, collected during ﬁeld

trials and real missions, might lead to changes to fu-

ture mission planning or to changes in the design of

the suit.) In summary, the prototype system can be

seen as being composed of two control loops: one

giving rapid feedback to autonomously adjust cool-

ing; the other, longer term one, providing support for

an iterative design process in terms of both the mis-

sion use and construction of the suit.

The prototype design consists of a number of

hardware components, including a remote monitor-

ing station, two processing nodes, one actuation node,

12 temperature sensors, and the cooling system. The

connection between these components is shown in

ﬁgure 3. The processing nodes, actuation nodes, and

remote monitoring point form a wireless network.

Each processing node is wired to several sensor pack-

ages via an I2C bus. Although it would be possible

to integrate all sensor packages used in this proto-

type into a single processing / actuation node, using

separate processing nodes allows the helmet, jacket,

and trousers to be kept separate with no wires run-

ning between them. This is essential for ensuring that

the product remains easy to use and transparent to the

wearer.

The system componentsand their functionality are

described in the remainder of this section.

System

Cooling

Remote Monitoring Point

Subject with Sensors

Processing Node

Actuation Node

Processing Node

Figure 3: Prototype system hardware components and sen-

sor positioning (A – neck, B – chest, C – bicep, D – ab-

domen, E – thigh, F – calf).

Figure 4: Sensor package, which is based on an ADT75A

chip.

3.1 Sensor Packages and Sensor

Positioning

The prototype system discussed here uses twelve sen-

sor packages based on Analog Devices ADT75A tem-

perature sensor ICs (shown in ﬁgure 4). This device

has the advantage that it contains the sensor, ADC,

and bus interface in a single package. Temperature

values are transmitted as 12 bits, which causes round-

ing to within 1/8°C. The sensor packages are con-

nected to only two nodes in the current version: one

actuation node and one processing node.

The sensor packages were positioned around var-

ious parts of the body roughly following the standard

positioning used for skin sensors as used by (Thake

and Price, 2007), which is a subset of the locations

discussed by (Shanks, 1975). These were: lateral

calf muscle, front of thigh (or quadruceps), abdomen,

chest, biceps, and neck, as indicated in ﬁgure 3. Given

that temperatures are known to be symmetrical be-

tween left and right sides in healthy people (Silber-

stein et al., 1975), sensors have been placed on a sin-

gle side. Two sensor packages were used per skin site.

ICINCO 2008 - International Conference on Informatics in Control, Automation and Robotics

This arrangement enables individual data validation.

3.2 Processing and Actuation Nodes

3.2.1 Construction

There are a variety of available embedded platforms

for sensing and control applications. The hardware

choice decisions for the prototype system here were

based on the available platforms’ processing power,

external interfaces, ease of software development,and

size.

Gumstix Connex 400xm-bt boards were selected

as the main processing platform. Although not as

popular as Mica2 motes, they are becoming more

prevalent (see (Keoh et al., 2007) for an example).

These devices offer more processing power and mem-

ory (in terms of both RAM and ﬂash) than many sim-

ilarly sized platforms. The Connex includes an Intel

XScale PXA255 400MHz processor, 16MB of ﬂash

memory, 64MB of RAM, a Bluetooth controller and

antenna, and 60-pin and 92-pin connectors for expan-

sion boards. There are no on-board sensors provided.

The sensor packages connect to the Connex board via

an expansion board, designed in-house.

The prototype system exploits the following ca-

pabilities offered by the Gumstix Connex device:

Bluetooth communications to transmit data between

nodes; I2C bus interface for the attachment of sen-

sor packages; real-time data modelling and decision-

making; and, a small form factor, which enables con-

venient mounting on or around a subject’s body.

3.2.2 Functionality

In the current revision of the prototype, the actua-

tion and processing nodes only transmit data back to

the remote monitoring station, upon ﬁltering outlying

values. The longer term view is for the processing

and actuation nodes to perform in-network modelling

of the suit wearer’s comfort through collaborative be-

haviour. Comfort modellingwould ﬁrstly involve pro-

duction of a thermal sensation model within the net-

work. This will be followed by integration of sup-

plementary physiological and contextual sensing per-

formed by expanded sensor packages. Work to date in

thermal sensation modelling and its integration within

the processing and actuation nodes is reported in a

separate paper. The actuation node will eventually be

used to perform decision making on the basis of the

wearer’s comfort and act by controlling the fan speed.

Figure 5: A snapshot of the remote monitoring component.

3.3 Remote Monitoring

The remote monitoring component of this system al-

lows an external observer to monitor both the instru-

mentation system (to ensure that trustworthy informa-

tion is being recorded) and the bomb disposal techni-

cian during a mission (which is the main function of

the instrumentation). The remote monitoring compo-

nent displays the health and comfort information and

provides alerts to the remote observer if physiologi-

cal parameters fall outside safe ranges or the wearer

is shown to be signiﬁcantly uncomfortable. A snap-

shot of the remote monitoring component is shown in

ﬁgure 5. Currently the remote monitor displays skin

site temperature data and a rotating, suggestive, 3-D

interpolated model of skin temperatures. Cool to hot

zones are displayed dynamically through a range of

colours, from blue to red.

4 PROTOTYPE EVALUATION

4.1 Experimental Setup

The prototype instrumentation system was evaluated

through laboratory experiments that attempt to repro-

duce typical bomb disposal mission situations by hav-

ing the subject undertake a series of activities and

tasks, as discussed in section 2.3. The experiments

begin with sensors being attached to the subject, fol-

lowed by suiting-up. The upper body sensors are in-

tegrated into the clothing and thus easier to attach,

whilst lower body sensors are attached with PVC

tape. The subject wore the outer shell of the bomb dis-

posal suit including the jacket and trouser segments in

addition to armour plating and the helmet.

INSTRUMENTING BOMB DISPOSAL SUITS WITH WIRELESS SENSOR NETWORKS

Figure 6: First activity: walking at 4km/h.

Figure 7: Second activity: kneeling while removing weights

from a sack. The wired-in data logger can be seen taped

onto the subject’s lower back.

The subject then undertakes an activity regime

composed of: (1) walking (3 minutes) (see ﬁgure 6);

(2) kneeling while putting weights into and out of a

rucksack (2 minutes) (see ﬁgure 7); (3) crawling (2

minutes); (4) arm exercise (4 minutes); (5) sitting (3

minutes); (6) standing (1 minute). Temperature data

is collected both via the prototype wireless system

and via a wired-in data logger. Data was gathered dur-

ing two consecutive runs, both consisting of the same

routine and taking place in a 5m x 6m draft free room,

with an ambient temperature of 21°C.

4.2 Evaluation Results

The prototypewas evaluated according to a number of

criteria that follow directly from user requirements.

The criteria were: ease of use, data yield, accuracy,

robustness, communication range, and information

gain.

Ease of Use. Instrumentation systems, particu-

larly those used for bomb disposal missions, are ex-

pected to have stringent ease of use requirements as

they should be transparent to the user and should not

interfere with the mission. Ease of use was assessed

here subjectively by comparing the ease of applica-

tion of the sensor packages with sensor mountings for

a wired data logger.

As mentioned previously some of the sensor pack-

ages have been integrated into clothing, whilst some

(neck, thigh, and calf) have been taped to the skin.

It is expected that clothing integrated sensors will be

less accurate than ones taped to the skin because con-

tact with the skin surface will change when the sub-

ject is moving. While avoiding the problem of incon-

sistent contact, taping on sensors, on the other hand,

means that they are less convenient to apply and re-

move. In comparison to using a standard wired data

logger, the wireless system mounting takes consider-

ably less time and has been found to be more comfort-

able by experimental subjects. Further revisions of

the prototype will have all sensor packages mounted

on individual elasticated straps, ensuring both ﬁrm

contact and comfort.

Data Yield is a measure of the proportion of data

captured. Wireless sensing systems are inherently

prone to low yields due to both transmission errors

and sensor faults. For the system here, during experi-

mentation, no packets were lost in transmission, how-

ever 5% of the sensor samples were found to be out

of range (95% yield). Most of the out of range val-

ues were from particular sensor packages (3.3% from

the worst two), with several sensor packages having

no out of range values at all. It is likely that the er-

roneous values were introduced by I2C bus transmis-

sion errors. In comparison, there were no errors ap-

parent in the wired data logger values apart from the

chest sensor, which produced incorrect values 61% of

the time (39% yield for this sensor, 88% over all data

logger sensors).

Accuracy is a measure of how closely the sensor

data obtained corresponds to the underlying physical

phenomena being sensed. As the data logger results

in ﬁgure 9 show, calibration is needed. Discretisation

due to the 12 bit resolution causes some information

loss that is offset by sampling frequently. The sys-

tem is currently being calibrated against a newer data

logger instrument.

Robustness is particularly important for this sys-

tem as the intended usage scenario involves it func-

tioning in an environment where it may be subjected

to large mechanical shocks and radio frequency in-

terference (RFI). The activity regime here reproduces

shocks roughly equivalent to normal application us-

age and the prototype functioned correctly throughout

all trials. As yet, no RFI testing has been carried out.

Communication Range is a measure of how far

the subject can roam from the monitoring station

ICINCO 2008 - International Conference on Informatics in Control, Automation and Robotics

without losing communications. In line-of-sight tests,

a range of 50 metres was achieved,whilst non-line-of-

sight range (through several walls) was about 10 me-

tres. Bluetooth communication will be replaced by

ZigBee in the next revision of the prototype.

Information Gain is a measure of the beneﬁt

of the system in terms of providing more (or bet-

ter) information about the subject. The prototype

has demonstrated two advantages. First, by being

untethered, it allows data gathering to occur in the

ﬁeld. Second, it provides a means for real-time re-

mote monitoring and actuation as opposed to ofﬂine

data acquisition, which is the only role fulﬁlled by the

wired data logger.

4.3 Data Analysis

A summary of temperature data obtained from all sen-

sors for a sample run is given in the series of graphs

in ﬁgure 9. Data was recorded during the experimen-

tation using both the prototype system and a wired-in

data logger. These graphs show that the two systems

agree in terms of the changes in temperature. It is

important to note that the shapes of the graphs, not

the exact temperatures measured, are compared here

as the sensors on the prototype system had not yet

been fully calibrated. The graphs show sensed tem-

peratures over a period of time starting from the third

activity (crawling) through to the ﬁfth activity (sit-

ting) followed by a repeat from the ﬁrst (walking on a

treadmill) through to the last again (see section 4.1).

In the graphs, the start and end times for each activity

are indicated by a vertical bar and the activity num-

ber (starting with 3) is given in between each set of

bars. Note that there were some rest periods between

activities, which are left unmarked.

The aim of the experimentation carried out was

two-fold. First, the system under development was

compared, in terms of the criteria discussed previ-

ously, with a commercially available, wired-in data

logger. Second, the data obtained from the two sys-

tems was compared to check for consistency. The po-

sitioning of the sensors, with several locations having

more than one sensor, also meant that the data from

the system could be compared internally.

While detailed interpretation of the physiological

meaning of the data obtained is beyond the scope of

this paper, the data gathered is meaningful in the con-

text of the developed application as follows: 1) Large

variations in the skin temperature on some of the sites

monitored (maximum three degrees C over 30 min-

utes) indicate the need for both monitoring and ac-

curate cooling actuation; 2) There are uncorrelated

skin temperature variations over the sites monitored

Figure 8: Enhanced sensor package, which is comprised

of a PIC processor, 3-DOF accelerometer, I2C buffer, and

temperature sensor.

stressing the need for distributed and detailed mea-

surement (as opposed to single point measurement

performed by most developed BSN systems); 3) From

the graphs, the relationship between activity and skin

temperature at different sites is not an obvious one.

(An example here is the sudden dip in temperature

which occurs for all chest sensors during crawling

(activity 3). Crawling is strenuous with the suit on,

so this result is surprising.) This indicates the need

for added sensing such as humidity and posture infor-

mation in order to predict the physiological effects of

wearing the suit during such exercise regimes. The

next prototype, currently under production contains

such enhanced sensor packages.

5 CONCLUSIONS AND FUTURE

WORK

WSN technology is clearly an enabler for detailed

measurement in domains such as the one discussed

in this paper, domains which are currently not sufﬁ-

ciently understood and lack the necessary instrumen-

tation to further scientiﬁc investigation.

Experimental results obtained with a detailed,

WSN-based temperature monitoring instrument

showed that 1) under a set of activities typical to

a bomb disposal mission, skin temperatures for

different parts of the body (arms, thigh, chest, and so

forth) vary differently thus there is value in sampling

at many points; 2) skin temperatures exhibit large

variations leading potentially to heat exhaustion

hence the need for health monitoring of subjects; 3)

autonomous feedback control of the in-suit cooling

system, based on a detailed map of how temperature

is changing over time, is enabled by the prototype

developed so far but more work is needed to deter-

mine how best to respond to changes in temperature

to ensure that the wearer is kept comfortable.

In the next revision of the prototype, it is planned

INSTRUMENTING BOMB DISPOSAL SUITS WITH WIRELESS SENSOR NETWORKS

0 5 10 15 20 25 30 35

Temperature (degrees Celsius)

Time (minutes)

3 4 5 1 2 3 4 5

Right Arm

Left Arm

Logger

0 5 10 15 20 25 30 35

Temperature (degrees Celsius)

Time (minutes)

3 4 5 1 2 3 4 53 4 5 1 2 3 4 5

Right Neck

Left Neck

(a) (b)

0 5 10 15 20 25 30 35

Temperature (degrees Celsius)

Time (minutes)

3 4 5 1 2 3 4 53 4 5 1 2 3 4 53 4 5 1 2 3 4 53 4 5 1 2 3 4 5

Right Abdomen

Left Abdomen

0 5 10 15 20 25 30 35

Temperature (degrees Celsius)

Time (minutes)

3 4 5 1 2 3 4 53 4 5 1 2 3 4 53 4 5 1 2 3 4 5

Right Chest

Left Chest

Logger

0 5 10 15 20 25 30 35

Temperature (degrees Celsius)

Time (minutes)

3 4 5 1 2 3 4 53 4 5 1 2 3 4 53 4 5 1 2 3 4 53 4 5 1 2 3 4 53 4 5 1 2 3 4 5

Right Thigh (1)

Right Thigh (2)

Logger

0 5 10 15 20 25 30 35

Temperature (degrees Celsius)

Time (minutes)

3 4 5 1 2 3 4 53 4 5 1 2 3 4 53 4 5 1 2 3 4 53 4 5 1 2 3 4 53 4 5 1 2 3 4 53 4 5 1 2 3 4 5

Right Calf (1)

Right Calf (2)

Logger

(e) (f)

Figure 9: Skin temperature over time for (a) arm, (b) neck, (c) abdomen, (d) chest, (e) thigh, and (f) calf sites. The two

leg sensors (thigh and calf positions) were placed on the right leg only. For several skin sites, temperature values were also

obtained using a wired-in data logger (denoted “Logger”). The vertical lines in each graph show the start and end of activities.

Each activity is represented by a number.

to integrate temperature sensors into a multi-modal

sensor board designed in-house, as shown in ﬁg-

ure 8. Each board has a temperature sensor and an ac-

celerometer, along with a PIC micro-controller. The

two sensors allow the combined monitoring of tem-

perature and acceleration data at any point on a sub-

ject’s body. The acceleration data will be used for

posture identiﬁcation in further work, which will al-

low enhanced, activity based remote visualisation of

the subject and lead to improved estimates about how

the thermal state and thus comfort of the subject is

changing. This will hence improve the timeliness and

appropriateness of autonomous cooling decisions.

ACKNOWLEDGEMENTS

The authors wish to thank Doug Thake and his stu-

dents for the use of and assistance with the Coventry

University Health and Life Sciences laboratory and

equipment. The authors also wish to thank Bob New-

man for his contribution to hardware development in

the early stages of this project.

ICINCO 2008 - International Conference on Informatics in Control, Automation and Robotics

REFERENCES

Gao, T., Greenspan, D., Welsh, M., Juang, R. R., and Alm,

A. (2005). Vital signs monitoring and patient track-

ing over a wireless network. In 27th Annual Interna-

tional Conference of the IEEE EMBS, pages 102–105,

Shanghai.

Jovanov, E., Raskovic, D., Price, J., Chapman, J., Moore,

A., and Krishnamurthy, A. (2001). Patient monitor-

ing using personal area networks of wireless intelli-

gent sensors. Biomedical Sciences Instrumentation,

37:373–378.

Keoh, S. L., Dulay, N., Lupu, E., Twidle, K., Schaeffer-

Filho, A. E., Sloman, M., Heeps, S., Strowes, S., and

Sventek, J. (2007). Self managed cell: A middle-

ware for managing body sensor networks. In Pro-

ceedings of the 4th International Conference on Mo-

bile and Ubiquitous Systems: Computing, Networking

and Services (Mobiquitous), Philadelphia, USA.

Lo, B. and Yang, G.-Z. (2005). Architecture for body sen-

sor networks. In Perspective in Pervasive Computing,

pages 23–28.

Shanks, C. A. (1975). Mean skin temperature during anaes-

thesia: An assessment of formulae in the supine surgi-

cal patient. British Journal of Anaesthesia, 47(8):871–

876.

Shnayder, V., rong Chen, B., Lorincz, K., Fulford-Jones,

T. R. F., and Welsh, M. (2005). Sensor networks for

medical care. Technical report, Division of Engineer-

ing and Applied Sciences, Harvard University.

Silberstein, E., Bahra, G., and Kattan, J. (1975). Thermo-

graphically measured normal skin temperature asym-

metry in the human male. Cancer, 36(4):1506–1510.

Tapia, E. M., Marmasse, N., Intille, S. S., and Larson, K.

(2004). Mites: Wireless portable sensors for study-

ing behavior. In Proceedings of Extended Abstracts

UbiComp 2004: Ubiquitous Computing.

Thake, C. D. and Price, M. J. (2007). Reducing uncom-

pensable heat stress an a bomb disposal (EOD) suit:

a laboratory based assessment. In Proceedings of the

12th International Conference on Environmental Er-

gonomics (ICEE 2007), Piran, Slovenia. ISBN 978-

961-90545-1-2.

Vivometrics (2007). Vivometrics: Better results

through non-invasive monitoring. Website.

http://www.vivometrics.com; (Online; accessed

16/11/2007).

Walker, W., Polk, T., Hande, A., and Bhatia, D. (2006). Re-

mote blood pressure monitoring using a wireless sen-

sor network. In 6th Annual IEEE Emerging Informa-

tion Technology Conference, Dallas, Texas.

INSTRUMENTING BOMB DISPOSAL SUITS WITH WIRELESS SENSOR NETWORKS