Indoor & Outdoor Location of
Firefighters & Safety Personnel
An Integrated Approach
Final Report Submitted to
Maryland Fire and Rescue Institute
Submitted by
Dr. Neil Goldsman
(301)405-3648
neil@eng.umd.edu
Dr. Gilmer Blankenship
(240)790-0620
gilmer@technosci.com
April 14, 2006
I
Contents
Section I.
Abstract .............................................................................................................................1
Section II.
Final Report ......................................................................................................................2
a.
Introduction........................................................................................................................2
b.
Indoor / Outdoor Tracking Performance Trials................................................................4
c.
Detailed Technical Description and Approach ................................................................6
c.1.
Integrated Positioning ..................................................................................................6
c.2.
Elements of the Existing Sentinel System ..................................................................8
c.3.
3D Graphical User Interface ......................................................................................11
d.
Miniaturization of Prototype ............................................................................................14
d.1.
INU Improvements .....................................................................................................17
e.
Node Controller ...............................................................................................................20
f.
Future Work ..............................................................................................................................21
Figures
Figure 1. Fire Sentinel Beacon has 2 pieces, the INU is worn on the firefighters belt. The
INU is connected to the radio via blue tooth. The radio can be connected in any
convenient location so as not to interfere with movement or other gear. ..............................2
Figure 2 (Left) Trajectory produced by the Sentinel INU of a user walking on the third floor
of the AV Williams Bldg. (Right) The actual path the user walked inside the building.
The journey lasted about 5 minutes.........................................................................................4
Figure 3 Shows a path traversed outdoors, around a relatively large building by a user of
the prototype Sentinel Beacon. The path is 2/5 of a mile. No GPS is used. .........................6
Figure 4 Inertial Navigation Unit ......................................................................................................9
Figure 5 Transceiver module and RSSI display.............................................................................9
Figure 6 Motherboard of prototype sensor interface. ...................................................................10
Figure 7 GPS System designed by TRX ......................................................................................10
Figure 13. System Block Diagram ...............................................................................................11
Figure 8 A part of the path shown previously: (Left) Path plotted (in real-time) on a floor
plan using prototype map-matching Virtual Reality software. (Right) 3 dimensional
VR view of the unit moving on the floor plan. ........................................................................13
Figure 9 Building internal structure constructed by JAVA3D map-building software for the
path shown earlier using data provided by the INU. .............................................................14
Figure 10. First Generation INU Block Diagram..........................................................................17
Figure 11. Second Generation INU Block Diagram ....................................................................17
Figure 12. Second Generation INU Boards a) INU main board is worn vertically with back
against firefighter’s belt. b) INU secondary board inserts into the main board at silk
screened rectangle and allows for tracking of firefighters in non-vertical orientations
such as crawling. ....................................................................................................................19
Figure 14 Liteye HUD mounted on a helmet. The viewer is “transparent” enabling the user
to see objects ahead...............................................................................................................24
FINAL REPORT
Section I.
Abstract
In work funded by the Department of Homeland Security (DHS), the Maryland Industrial
Partnerships Program (MIPS) and the Maryland Fire and Rescue Institute (MFRI), an
innovative technology prototype for tracking individuals moving inside buildings and
structures (and outside as well) has been developed. Specifically, the Sentinel System is
designed to locate and track firefighters and other first responders indoors and outdoors using
inertial and other measurements, including GPS signals, if available. The system includes a
Sentinel Beacon and a “Command Station” (a ruggedized PC) that receives the data
transmitted from the beacons and processes it to produce location and track information for
the incident commander. The Sentinel Beacon system is designed to work as a “mesh
network” so that a beacon that is out of range of the command station can have its data relayed
by other beacons.
We have been able to leverage the ongoing work for DHS and MIPS to allow us to
accomplish the results presented here. The funding from the University of Maryland Fire and
Rescue Institute has been used to support the miniaturization of the prototype hardware.
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Section II.
Final Report
Our previous work established a strong foundation for
the project by developing and implementing a prototype
integrated positioning technology for indoor and
outdoor tracking. The development of the prototype
system has been supported by the US Department of
Homeland
Security
(DHS)/Technology
Support
Working Group (TSWG) and the Maryland Industrial
Partnerships Program (MIPS). We have been able to
leverage the ongoing work for DHS and MIPS to allow
us to accomplish the results presented here.
The
funding from the University of Maryland Fire and
Figure 1. The second generation Fire Sentinel
Beacon has 2 pieces, the INU is worn on the
firefighters belt. The INU is connected to the
radio via blue tooth. The radio can be connected
in any convenient location so as not to interfere
with movement or other gear.
Rescue Institute (MFRI) has been used to support the
miniaturization of the prototype hardware.
a.
Introduction
The ability to accurately track first responders at
incident sites both inside and outside structures is a top priority for safety and command and
control. Our Sentinel System is designed to enable the Incident Commander to locate and
track responders inside a building, or in the vicinity of an incident. The Sentinel System
consists of the following elements:

A compact, body worn unit (a Personal Locator Beacon – PLB) that computes
the responder’s location in absolute coordinates and communicates it locally to
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the Incident Commander. The capability to relay data from out of range nodes
is also provided by PLB units;

A Base Station that enables the Incident Commander to see the locations of all
the responders in the squads (at the scene, both inside and outside), together
with other information such as responder health, equipment condition,
environmental data, building plan, assets, etc.; and

A Communications Network that links all responders and the Commander(s).
The initial product will compute location and measure basic health status of the responder
(body temperature, pulse rate, net movement, impact alarm, etc.) and transmit location, health
status, and alarms to the base station. It will transmit an alarm when the responder’s status
leaves a nominal range, or when the responder activates the alarm manually.
The base station will show the Incident Commander where the responders are as mapped on a
3-D “floor plan” displayed using a graphical user interface. The personnel locations and
tracks will be shown on a building plan or, if a building plan is not available, a map of the
building will be developed implicitly from the historical path data.
An important feature of our system is that, all of the mobile units form a mesh network so if a
responder goes out of range of the base station transceiver, as long another mobile unit is in
range of the responder and base station, the information can be forwarded to the base station,
effectively extending the range using multiple hops to get out of the building. Finally, the
environmental data collected by the sensors in the unit can be used to create a “map” of the
environmental conditions inside the structure. No other system has this collection of broad and
rich capabilities.
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With our system, if a responder goes down
the Commander will know where they are and how they got there.
While the responders will go after a comrade with that knowledge, it may still difficult to find
their way to the downed comrade if, for example, the room is filled with smoke, so our mobile
units will have LED indicators to indicate direction and distance to a downed responder.
Future designs will include a heads up display to aid in locating responders. The display will
include a map of the individual’s path through the structure and other mission specific critical
data.
b.
Indoor / Outdoor Tracking Performance Trials
In the figures that follow we summarize evaluations of the performance of the current Sentinel
System in tracking individuals inside and outside a building. The tests were conducted at the
AV Williams Building1 at the University of Maryland in College Park in February 2006. This
is a four story building with a complex internal structure. It houses the Electrical Engineering
Figure 2 (Left) Trajectory produced by the Sentinel INU of a user walking on the third floor of the AV Williams Bldg.
(Right) The actual path the user walked inside the building. The journey lasted about 5 minutes.
1
http://www.umd.edu/CampusMaps/bld_detail.cfm?bld_code=AVW. See also http://www.ee.umd.edu/Map/Avw/ for floor
plans.
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and Computer Science Departments, and contains a large amount of electrical equipment – a
potential source of interference with the Sentinel System.
The first trial (Figure 2) shows the track of an individual walking in the hallways of the third
floor of the building. The track was taken in a continuous experiment that lasted about 5
minutes. Note the straight lines of the path corresponding to the long corridors in the building,
and the sharp 90o changes in the track as the individual turns each corner. Note also the
accuracy of the unit as the individual moves back along the same corridors. Since the return
paths overlap the outward bound paths, we conclude that the location error is less than the
width of the corridor (6 feet). As the data trajectory indicates, the INU sends more data when it
perceives a turn in the path.
A video demonstrating the indoor tracking capabilities of the Sentinel System is
available for review – specifically a recording of the experiment shown in Figure 2.
This video can be viewed by downloading a Windows Media file from the TRX
Systems website:
http://www.trxsystems.com/downloads
Login as “MFRI” with password “trackme”. Download the file named “TRX
Tracking Demo” to your computer and view it using the Windows Media Player.2
The trial displayed in Figure 3 is a path of about 2/5 mile traversed outside the building. The
individual stayed as close to the walls of the building as possible during the journey (to
provide a reference for accuracy). The trajectory is overlaid on a satellite image of the building
from the Google Earth web site. Although the experiment was outside, we did not use GPS
A DVD with a larger format vers2 ion of the video is available.
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data – only the Sentinel INU. If typical GPS accuracy is 2-10 meters, then the location results
from the Sentinel unit are better than GPS.
Figure 3 Shows a path traversed outdoors, around a relatively large building
by a user of the prototype Sentinel Beacon. The path is 2/5 of a mile. No GPS is used.
c.
Detailed Technical Description and Approach
We call our approach Integrated Positioning.
Integrated positioning combines several
technologies to obtain accurate position estimates. The integration of the different
technologies is seamless to the user and provides more robust, accurate position estimates than
a single technique used alone. The final Personal Locator Beacon (PLB) unit worn by a first
responder will contain all of the integrated positioning subsystems and will be approximately
the size of a cell phone. The information obtained by the mobile PLB, is then transmitted to
the base station. In addition to communicating with the base station, the mobile PLB also
supports communication of positioning and condition data to other responders at the incident.
c.1.
Integrated Positioning
The positioning technologies used in Integrated Positioning are summarized below:
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
Inertial Navigation Unit (INU): Contains a MEMS-accelerometer, MEMS-compass
and MEMS-gyroscope to track an individual’s motion. We have already developed a
first generation of the hardware, most of the signal processing software, and a
functioning prototype. The accelerometers are also used to determine if a responder is
not moving or undergoes a rapid acceleration, e.g., falls through a floor or gets
knocked over.
The Sentinel INU is targeted toward monitoring the position of personnel and is
capable of accurate locations over a longer period of time compared to conventional
INU’s. The data processing methods are targeted specifically toward recognizing
distinctive characteristics in human gait and to take advantage the gait properties and
their relation to movement. By monitoring and analyzing specific characteristics, the
INU’s processor uses specific filtering techniques to compare the recorded motions
with a library of predefined gait motions.

Global Positioning (GPS): A small unit based on the latest GPS receiver chips that
can track at very low signal to noise ratios (SNR). We have designed the hardware and
software that enables the realization of this chip in a GPS receiver. A prototype of this
subsystem about the size of a postage stamp has already been developed and
integrated into the Sentinel Beacon.

Received Signal Strength Indication (RSSI): Each base station and PLB will have
the capability to measure the signal strength of received radio signals. The weaker the
signal, the further the responder is from the signal source. This method is also used to
determine distance between responders in the network. RSSI becomes very accurate
when the transmit/receive pair are in close proximity to each other, for example, in a
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room or large open area. RSSI can be used as a backup to locate downed responders
in a situation where vision is impaired such as in a smoke filled room. A prototype for
hardware and software has been developed.

Mesh Network: The mobile nodes in our sentinel system form a mesh network. By
forming a mesh network data is allowed to be routed (“hopped”) though other nodes if
the nodes cannot form a direct link with the base station. The ability to hop extends
the range of the system. Each member of the team is thus networked to each other,
and each node in the network can know the location and other pertinent data of the
other nodes. A working system has been tested in prototype form.

Active Radar: This location method uses extremely accurate GHz clocks and
electromagnetic ultra-wide-band pulses for positioning. This method is very similar to
police and aircraft radar. However, it uses ultra-wide band technology and transceiver
pairs as opposed to the passive reflection of radio waves employed by existing
systems. Theory, algorithms, and proof of concept hardware have been developed.
c.2.
Elements of the Existing Sentinel System
The positioning technology uses multiple sensors, subsystems, and algorithms to determine
the location of the tracked personnel. The data from each subsystem is fused onboard the
Sentinel Beacon and in the Sentinel Command Station. Using data fusion and complex
algorithms, the integrated positioning software is able to locate personnel both indoors and out
with excellent accuracy. The subsystems are integrated into a small motherboard that
coordinates their operation.
The subsystems used in the integrated positioning system are summarized below:
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Inertial Navigation Unit (INU): The INU
subsystem contains a MEMS accelerometer,
compass and gyroscope. The information from these
micro-sensors is combined using novel signal
processing
algorithms,
programmed
into
Figure 4 Inertial Navigation Unit
microprocessors, to track the path taken by an individual on foot. We use this technique inside
buildings and structures where GPS is not effective.
Received Signal Strength Indication (RSSI): This subsystem uses the radio signal strength
of the beacon transceiver to measure the distance from an individual to the Command Station.
This method is useful for homing in on an individual during a search and rescue operation.
Figure 5 shows a prototype of the transceiver equipped with RSSI capabilities and the basestation interface with the RSSI data. The circle indicates the distance of an individual from the
Base Unit.
Figure 5 Transceiver module and RSSI display
Motherboard: In Figure 6 we show the motherboard for the current Sentinel Beacon. This
unit is currently being miniaturized under funding from DHS. The motherboard was designed
to operate with a wide assortment of plug-and-play sensors. (TRX Systems developed the
interface hardware and software that allowed these sensors to be plug-and-play.) This is
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reflected by the eight rows of connector pins, where various sensors plug into the
motherboard, depending on the application desired by the user.
Figure 6 Motherboard of prototype sensor interface.
We will continue to provide an option for adding a
plug-and-play modular sensors, as desired by the
user. The PIC motherboard microprocessor will be
programmed to interpret the data obtained from these
plug and play sensors, and incorporate the
information into the node report that will be sent to
Figure 7 GPS System designed by TRX
the Base Station.
Global Positioning (GPS) Unit: This is a subunit that employs the latest single chip GPS
receivers, which is shown in Figure 7. The GPS unit can usually provide tracking information
outdoors. GPS is not effective for indoor tracking.
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c.3.
3D Graphical User Interface
The Sentinel Base Station is a
Panasonic Toughbook, a ruggedized
laptop that runs standard Windows
operating systems. The user interface
can plot the trajectory of the personnel
and archive the data. Future plans
Figure 8. System Block Diagram
include enhancement the base station
with algorithms which help to eliminate errors, and provide even more accurate values for the
trajectories. If building floor plans or structure (tunnel) maps are available, the trajectories will
be plotted on them for ease of observation and for corrections based on the structure.
The laptop can be connected to a Wide Area Network (WAN) modem for distribution of data
to other surveillance locations. The Toughbook has an 80-pin reinforced port-replicator port
which allows it to be connected to a preinstalled set of peripherals, such as a wireless modem.
The Base Station Transceiver will be developed by TRX Systems. It will be a transceiver for
receiving and interpreting information from the Sentinel PLBs and interfacing with the
Command Station. It will receive the node reports transmitted by the PLBs, and have a
microprocessor to control communications. The Base Station Transceiver is smaller than the
size of a small cell phone.
The interface concept design is shown in Figure 9 in prototype form. The base station user
interface will run on a ruggedized laptop. The interface will be capable of displaying current
and past location and sensor information for all mobile units on a building floor plan – if
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available. It will have 3D and 2D viewing options with natural transitions among views, for
example, click on a floor in the 3D move to change to 2D view.
A whole building wire-frame view of the building structure will be developed with the
position of each responder indicated. The building will include a scale showing grid spaces of
approximately 10 feet in every direction. Positions will be shown for all responders, if an
alarm is detected the subject’s marker will be changed to red and enlarged or blink. Detailed
information on sensor data, etc. can be seen by clicking on an individual marker. Historical
path data can be shown if desired, for a selected individual, group, or for all mobile nodes.
The user interface will allow the incident commander to group individuals into teams (by task,
by engine,…) that can be represented by different color or shape markers for ease of tracking.
We are experimenting with various 3D software packages for display of the data. A key is to
provide a system of maximum effectiveness to field commanders – the GUI cannot be overly
complex. It must make the information, especially alarms, very easy to understand in an
operational setting. We will work with MFRI and DHS to achieve an effective design.
The Base Station software is critical for displaying the positions of responders for decisive
analysis and action. To enhance the accuracy of indoor tracking, and to aid visualization, we
shall develop algorithms and software to project the path of the first responder on pre-existing
maps3 or to create maps created based on the subject’s trajectory.
The key features of this task are: Map Matching; Map Building; and Outdoor Terrain
Mapping.
3
The command station will have the ability to import maps and building floor plans as available at the incident.
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Figure 9 A part of the path shown previously:
(Left) Path plotted (in real-time) on a floor plan using prototype map-matching Virtual Reality software.
(Right) 3 dimensional VR view of the unit moving on the floor plan.
As shown in the prototype design in Figure 9, the software will plot the current location and
maintain a database of previous positions to produce a “trail” of the path taken by the first
responder, if desired. The historical data will also be used to provide an incident playback
feature.
The program shown in Figure 9 was designed using the Virtual Reality Toolbox4 in
MATLAB R14, which uses the Virtual Reality Modeling Language (VRML) for scene
modeling and display. This display will be available on the Base Station, enabling command
personnel to monitor locations within a building. This will be of significant importance when
hazardous situations occur. Information from sensors will also be displayed by the same
software, using appropriate formats – e.g., for temperature (by color), sounds (by type, noise,
voice), radiation or biohazards (by color), etc.
Map building: The second mapping algorithm takes precedence in the absence of floor plans.
While first responder positions are collected and plotted, a 3-dimensional floor plan is
automatically generated with a lifelike look and feel – as shown in Figure 10. This figure is a
4
We are using MATLAB to develop the software design and key functions. The commercial version of the software will be
compiled code that does not depend on MATLAB.
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reconstruction (in real-time) of the path in Figure 2 using JAVA3D objects to build walls and
corridors.
Figure 10 Building internal structure constructed by JAVA3D map-building software
for the path shown earlier using data provided by the INU.
This capability is important in constructing hypothetical models of the interior of a structure.
As individuals make their way through a building, the software attempts to identify key
features such as stairwells, elevators, and hallways, and generates walls, floors and other
features, to define the structure of the building to aid the incident commander viewing the
progress.
d.
Miniaturization of Prototype
Under the funding from MFRI, we have worked on developing second generation hardware
for the Firefighter Sentinel system. The final design boards have been sent out and we will
have prototypes for testing by mid-late April.
The motivations for development of a generation two system are:
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
miniaturization

improved heat dissipation

addition of sensors

improved compass

replacing INU to data radio wiring with Bluetooth

replacing analog sensors with digital counterparts

connector upgrades
As shown in Figure 1, the Fire Sentinel Beacon in its new design has 2 pieces, the INU is
worn on the firefighters belt. The INU is now connected to the data radio via Bluetooth, while
the generation 1 required a wired connection. With the addition of the Bluetooth wireless
connection, the radio can be connected in any convenient location so as not to interfere with
movement or other gear.
The improved INU, which we plan to test at MFRI in May or June, has several new motion
detecting microelectronic sensors. These sensors are made possible with the advent of MEMS
sensors that have only become available in the last several months. The new INU includes a
MEMS three-axis accelerometer, two MEMS gyroscopes, and a 3-axis magnetic field sensor.
The data from the accelerometer will be used to identify individual steps taken by the subject,
or other distinctive features of the motion. The gyroscope provides the rate of angular change
of the user’s direction. This information will be used to help calculate the direction of the
user’s line of progress. Data from the magnetic field sensors (compass) will also be used to
calculate the direction of the subject’s trajectory.
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These sensors are controlled by a dsPIC signal processing micro-controller chip. The data
obtained from the sensors, will be combined with unique algorithms to ascertain the precise
trajectory of a subject in motion. Currently, the algorithm is optimized for walking or stair
climbing in buildings, and largely relies on the gyroscope to track variations in direction. With
the new hardware, the algorithm can be enhanced to more reliably determine whether the
subject is crawling, running, etc.
The role of the magnetic sensor data will be increased to provide another source of directional
data in addition to that obtained from the gyroscope. Errors in compass readings resulting
from nearby ferrous objects will be corrected by comparing the total local magnetic field
magnitude to that of the earth to recognize corrupted compass data. The algorithm will be
coded using assembly language into the dsPIC. This microprocessor, which is optimized for
signal processing, will implement the algorithm, and output XYZ coordinates of the subject.
Error correction algorithms will be developed to accommodate for sensor readings which are
momentarily corrupted.
The dsPIC will calculate the coordinates of the user, and send them via blue tooth to the
motherboard microprocessor. This information will then be incorporated into the node report
that the motherboard assembles, and output to the transceiver. The transceiver will then
transmit the node report, which includes the coordinates of the subject to other team members.
In summary, the modifications we are making to the system are:

INU:
We are miniaturizing the INU and adding several new sensors so that
movements such as crawling can be tracked. We are adding a Bluetooth module for
communications between the INU and data radio.
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
Data Radio: we are combining the motherboard, GPS unit, and data radio onto one
board and adding a Bluetooth module for communications between this unit and the
INU.
d.1.
INU Improvements
Figure 11 and Figure 12 show block diagrams for the first and second generation INU,
respectively. Key improvements are the addition of z component to the magnetic field
magnitude and the second gyroscope. These are critical components for tracking firefighters
when they are crawling, or any other non-vertical mode of locomotion. The first generation
INU has limited capability to track a user when they are not vertical. For this reason
generation two has includes a vertically mounted MEMS gyroscope sensor and vertical axis
magnetic field sensor. These additional sensors are necessary for determining the direction the
user is crawling. The vertical axis magnetic field sensor will also assist in compensating for
compass bearing errors.
Figure 11. First Generation INU Block Diagram
Figure 12. Second Generation INU Block Diagram
Analog sensors used for the INU have all been replaced with their digital counterparts. The
new digital sensors operate using SPI (serial peripheral interface) which allows them to all
connect to the microcontroller via a common three wire bus. This allows PCB trace routing
space to be saved. In addition the digital sensors do not require buffers between their output
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signals and the microcontroller. By eliminating these buffers, a large amount of additional
board space is saved.
The first generation INU is connected to the node controller via a 8-wire interface and was
considered to be a standard plug and play sensor. For generation two, the wired interface was
replaced with a Bluetooth wireless connection that is dedicated to communications between
INU and node controller. This benefits the user as it is less awkward, the risk of snagging
wires is eliminated, and time is saved because there is no additional connection for the user to
make while putting on the unit.
For the second generation INU all component sizes were reduced. The package type for all
resistors and capacitors was changed from 1206 (0.12” x 0.06”) to 0402 (0.04” x 0.02”). The
accelerometer was changed from a 15.4mm x 7.5mm leaded SOIC package to a 7mm x 7mm
leadless QFN package. The microcontroller was changed from a leaded 12mm x 12mm
TQFP package to and 8mm x 8mm leadless QFN package. The gyro was changed from a
26.5mm x 11.3mm evaluation module to a leadless 8.2mm x 8.2mm LGA. The programming
and power connectors were also replaced with smaller counterparts. Total PCB dimensions
were reduced dramatically. The critical dimension that defines how far the unit protrudes
from the body was reduced from 64mm to 14.3mm.

Old INU dimensions 13mm x 81mm x 64mm

New INU dimensions 37.6mm x 45mm x 14.3mm
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Figure 13. Second Generation INU Boards a) INU main board is worn vertically with back against firefighter’s belt. b) INU secondary
board inserts into the main board at silk screened rectangle and allows for tracking of firefighters in non-vertical orientations such as
crawling.
Libraries have been created for new parts with manufacturing ease and heat management in
mind. This involved defining solder masks openings and optimized solder paste stencil
patterns for each component.
In addition, thermal vias were placed beneath the
microcontroller. These vias connect the exposed paddle of the QFN package to the ground
plane and a copper area beneath the IC to dissipate heat.
Assembly instruction packages have been created for the INU which include formatted
component centroid data file, silk screen and copper gerber files, solder paste gerbers,
formatted bill of materials, and special instructions. This information is used by the board
assembler to place the parts.
PCB design was panelized and a border was added to meet requirements for automatic
component placement machines. Score lines were drawn and cut so that assembled arrays of
PCBs can be easily snapped apart. Each board array contains 9 PCB’s. This not only eases
component placement but reduces the cost for each PCB.
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Mounting holes were placed on the PCB to allow for easy and secure installation in a plastic
enclosure. Prototype enclosure will be made from flame retardant ABS plastic with flame
rating UL94-0. Outer dimensions of enclosure will be about 2.5” x 2” x 0.8.
e.
Node Controller
The first generation node controller played the role of reading data from external sensors
(INU, GPS, etc.), formatting data packets for transmission to the base station and sending the
packets to the data radio for transmission. The data radio and GPS were separate modules that
communicated with the node controller via a 8-wire interface. This modular approach was
taken in the beginning stages of the project so that different devices could be evaluated on the
same system. We were able to determine from testing data radios and GPS which were most
reliable.
Generation two combines the selected data radio and GPS module with the node controller on
the same PCB. The new node controller will still have plug and play ports but the connectors
to these ports have been improved to provide extra reliability. The second generation node
controller has additional features including 4Mbit onboard memory for data logging, onboard
temperature sensor, onboard audible tone
generator for alerts, low battery detection
with LED indicators, USB interface, alert
button to signal base station for help, and
dedicated GPS controller.
The microcontroller for generation two has
also been upgraded to a signal processing
microcontroller. This will allow for more
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Figure 14. Second Generation Node Controller
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efficient computations within the device.
As mentioned above, the first generation node controller was connected to the INU via a 8wire interface, where the INU was considered to be a standard plug and play sensor. For
generation two, the wired interface between the two devices has been replaced with a
Bluetooth wireless connection that is dedicated to communications between the node
controller and INU.
The new node controller will operate on four AA alkaline (or any chemistry over 1.3V/cell)
batteries which will fit conveniently into PCB mounted plastic holders. All electronics on the
node controller PCB except for data radio will operate at 3.3V. The data radio will operate at
5V. Additional mounting holes on the PCB will allow for easy integration into an electronics
enclosure.
f.
Future Work
Further development and testing of the Sentinel System is necessary in order to transition this
technology into a product that is available for firefighters across the country. TRx Systems,
Inc. and partner company Techno-Sciences, Inc., along with MFRI, have applied for further
government funding from a variety of sources in order to continue this development.
Elements of the future work are outlined below.
Signal Processing
Remaining key technical challenges are self initialization, (auto) calibration, and diagnostics.
In addition, algorithms that automatically recognize and adapt to varying motion types and
users must be developed.
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Specifically, we shall develop “multi-mode” tracking algorithms that can “recognize” the
nature of the movement (walking, running, crawling, etc.) and select the appropriate signal
processing algorithm to compute location data for the context.
Mesh Networking
The mobile nodes in our sentinel system form a mesh network. By forming a mesh network
data is allowed to be routed (“hopped”) though other nodes if the nodes cannot form a direct
link with the base station. The ability to hop extends the range of the system. Our current
system supports a single hop operation, which means if the data cannot get back to the base
station directly; it can be routed through one other node to get there. We are in the process of
upgrading the networking software to allow multiple hops, thus further extending the range of
the network. In our testing so far in up to 4 story buildings, a single hop has been sufficient to
obtain full coverage.
The mesh network also allows data to be communicated directly between mobile nodes on the
network, so that a node can know where all the other nodes in the network are. Currently the
nodes do not store information from other nodes. The redesigned mother board has onboard
memory that will enable local storage of information on everyone in the network, so for
example, each node will store the last position of all other active nodes.
Sensor Information
The conditions a firefighter endures in a fire fight require extreme physical fitness. But in the
adrenalin rush of the fire, even a firefighter in peak condition can push his body too far.
Stress, heat, high body temperature and dehydration are all factors that can conspire to cause
critical injury. In fact, heart attack remains the leading cause of death among firefighters (44
percent of firefighter in-the-line-of-duty deaths are attributed to heart attack). A system that
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FINAL REPORT
monitors and transmits a firefighter’s biometric data such as temperature, heart rate and blood
pressure, could detect a firefighter in distress and provide necessary and timely information for
their extraction.
Our motherboard microprocessor has the capability to receive data sent from blue tooth
devices. We will demonstrate the capability to communicate with off the shelf heart rate
monitors that send blue tooth signals.
The firefighters gear has become so good that they are not always able to feel the external
temperature to know when they are in danger of overheating. Our INU hardware contains a
temperature sensor and in addition we will add a sensor into the firefighter’s jacket. Using
data from these sensors and an algorithm developed and tested by MFRI in conjunction with
the University of Maryland Fire Protection Engineering Department, we will give the
firefighters (and incident commander) a time remaining warning when the firefighter enters a
high heat environment. The algorithm computes exposure levels and estimates tolerable heat
levels based on a model of the insulating properties of the coat. As the temperature decreases,
for example, from controlling the fire, the time remaining will increase.
Information to Firefighter
Our current system collects information (position, sensor data, …) from the firefighters and
transmits it to the base station for display. We have not yet developed a system that allows the
firefighter to get information from the command station, for example, for alerts to evacuate, or
for egress direction, or for directions on most quickly get to a downed comrade. We will
develop and test a varying systems for getting this information to the firefighter. The systems
we intend to test range from simple systems including LEDS in the SCBA mask to indicate
warning or direction, to preprogrammed text messaging and/or audio messaging (similar to the
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FINAL REPORT
Magellan system in cars) to a blue tooth ear piece, to a fully functional HUD that would
eventually be built into the mask. (See Figure 15 for a commercially available system, that is
expensive www.liteye.com.) Even a simple communications system will allow the incident
commander to get important information quickly to the person or group that needs it.
Figure 15 Liteye HUD mounted on a helmet. The viewer is “transparent” enabling the user to see objects ahead.
Getting user feedback on these communications systems is critical. We have seen devices
with nice displays that we have been told will not be able to be seen in a smoke filled room, or
with audio that we are told could not possibly be understood in the noise of a ranging fire.
Testing our systems with MFRI and local fire departments will be a valuable step in coming
up a workable design.
We expect that this system will be an add-on module to our main tracking device
Testing
Further testing and customer feedback are crucial. To accomplish this we will continue to
work with the Maryland Fire and Rescue Institute (MFRI). With the help of MFRI our
technology will be tested successively more difficult operational scenarios. First the system
will go through trials in the burn building and smoke maze with fire fighter trainees in full
turnout gear. Once these tests are completed successfully and feedback is aggregated and
addressed, MFRI will arrange for local fire departments to beta test the system and provide
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FINAL REPORT
feedback. In parallel, we will test the system in buildings that are complex from the point of
view of transmission of radio signals. Test results and user feedback from will be a major
driver for rapid improvement of system. Testing the system in a variety of different scenarios
will help to assess and eliminate failure modes. Feedback from users will be rapidly turned
around to improve system usability by the customers.
Certification
We have begun to look into certification testing. At this point there are no NFPA standards
for location and tracking technology but our plan is to take what we can from the NFPA 1982
Standard on Personal Alert Safety Systems. We have spoken with Steve Sanders at The
Safety Equipment Institute (SEI) who has made us aware of a developing electronics standard
NFPA 1800 that may also have relevant tests but that will probably not be complete for
another couple of years. In the meantime, we will follow the development to assure we are
prepared for any new testing. SEI is a local company that provides third-party certification
programs to test and certify a broad range of safety equipment products.
The Safety
Equipment Institute headquartered in McLean, Virgina. SEI's certification programs are
accredited by the American National Standards Institute (ANSI) in accordance with the
standard, ISO Guide 65, General Requirements for Bodies Operating Product Certification
Systems. We will have the system certified for Intrinsic Safety (UL 913). We plan to sub this
testing to Intertec Testing Services in Courtland NY. This is also one of the labs used by SEI
in NFPA 1982 certification testing.
We plan to initiate certification design reviews before
about 6 months into this effort to ensure that there are no clear issues with our electronics and
enclosures that need to be addressed before testing can begin.
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FINAL REPORT
Manufacturing
We have identified and met with a subcontractor that we will be using for enclosure design
and manufacture, EG&G in Ijamsville, MD. They have engineering as well as full CNC and
conventional machine shop facilities to support our effort. In addition, they have experience
with developing for and going through certification testing. We have identified companies to
make and assemble the circuit boards. Advanced Circuits (www.4pcb.com ), who we have
worked
with
in
the
past,
will
make
the
boards
and
Screaming
Circuits
(www.screamingcircuits.com) will assemble them. Both companies will do small runs and
are also capable of running productions quantities. We plan to do final assembly and system
testing in house for quality control purposes.
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