MONITORING LIFT-SERVED BACKCOUNTRY ACCESS GATES IN REAL TIME:SKINTRACK’S FIRST SEASON AT SKI LOVELAND, COLORADO

Marc J. Rubin and Tracy CampDept. of Electrical Engineering and Computer Science, Colorado School of Mines, Golden, CO, USA

ABSTRACT: In this article, we present details from the inaugural deployment of a wireless sensorsystem called SkinTrack. SkinTrack is a wireless embedded system designed to automatically countthe number of people and transmitting avalanche transceivers passing through a lift-served backcoun-try access gate at Ski Loveland, Colorado. Designed and implemented using existing off-the-shelfproducts, SkinTrack counted nearly 900 total backcountry users during the 2011-2012 ski season. Ofall the backcountry users tracked, less than 40% had transmitting avalanche transceivers, a crucialpiece of safety equipment for traversing dangerous and unpatrolled avalanche terrain. Fortunately,beacon usage went up to over 60% on days forecasted as High avalanche danger. In addition topresenting results obtained from SkinTrack, we summarize the shortcomings of this prototype systemand describe our plans to improve SkinTrack (version 2.0) for the 2012-2013 ski season and beyond.Most notably, SkinTrack 2.0 will be more fault-tolerant and include sensors to track the directionality ofbackcountry users.

1. INTRODUCTION

Many ski resorts have backcountry gates thatoffer patrons quick and easy access to danger-ous and uncontrolled avalanche terrain (e.g., Fig-ure 1). Beyond resort boundaries, ski patrollersare not responsible for maintaining snowpackstability or for rescuing injured patrons. Whenbackcountry users pass through access gates,they assume all liability for their own safety andwell being. Though many ski resorts offer lift-served backcountry access, the gate usage hadnot been tracked in any way. Ski resorts haveno idea how many people use such gates, norwhether or not they carry the proper safety equip-ment (i.e., avalanche transceiver, shovel, probe).With funds from an American Avalanche Associ-ation Graduate Student Research Grant, we havedesigned and implemented SkinTrack: a wire-less embedded system capable of monitoring lift-served backcountry access gates.

SkinTrack is designed to count the numberof people passing through backcountry accessgates with and without transmitting avalanchetransceivers (Figure 2). Such backcountry us-age information could be valuable in many ways.First, in the event of a backcountry avalanche,local search and rescue teams would have nearreal-time data (i.e., number of people, number ofbeacons, last known time and location) that couldaid recovery efforts. Second, avalanche forecast-ing and research institutions could analyze usagestatistics to gain an understanding of the back-country population. Lastly, ski resorts could use

∗Corresponding author address: Marc J. Rubin, Dept.of Electrical Engineering and Computer Science, ColoradoSchool of Mines, Golden, CO, USA 80401; tel: (713) 628 -5822; email: mrubin@mines.edu

Figure 1: Many ski resorts (e.g., Loveland) havebackcountry access gates that are not monitoredin any way.

the information to inform risk management deci-sions (e.g., should we close the gate during thepeak tourist season?).

This article is structured as follows. First,we summarize the overall design of SkinTrack.Second, we present details of our prototype sys-tem that was installed at Ski Loveland, Colorado.Third, we discuss results from our initial test de-ployment. Lastly, we state our conclusions andprovide a brief outline of our future plans for Skin-Track 2.0.

2. DESIGN

SkinTrack is designed to collect backcountryaccess gate usage information using a wirelessmote, two sensors, and a base station computer(Figure 3). A wireless mote is a small, low-

Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska

487

Figure 2: SkinTrack is an embedded wireless sys-tem designed to track backcountry usage (Origi-nal image from O’Bannon and Clelland (2007)).

wireless mote

infrared beam sensor

beacon checker

Figure 3: The basic design of SkinTrack’s gateincludes a wireless mote and two sensors.

power, inexpensive, embedded computing devicethat can collect and transmit sensor data. The twosensors used by SkinTrack are a passive infrared(PIR) beam sensor and an avalanche transceiveror beacon checker.

SkinTrack works as follows. The wireless motecontinuously polls the infrared beam sensor andavalanche transceiver checker. When the in-frared beam is broken by a person going throughthe gate, the wireless mote uses the beaconchecker to determine the presence or absenceof a transmitting avalanche transceiver (Figure 4).The wireless mote then transmits this informationwirelessly to a base station computer, where thedata is processed further to provide near real-timeupdates.

3. IMPLEMENTATION

We successfully implemented a prototype ofSkinTrack using many commercially available

Figure 4: When a person breaks the infraredbeam the mote determines whether a beacon ex-ists and transmits the information wirelessly.

products. SkinTrack was installed at Ski Love-land, Colorado on the Forest Service Access gatenear the top of Lift One (Figure 5). The datacollected from SkinTrack was posted to our webserver in near real time: http://toilers.mines.edu/SkinTrack/display_data.php. The follow-ing is a brief description of the components weused to build SkinTrack.

Wireless Mote: The wireless mote is an Ar-duino Fio with an XBee XSC Pro 900 MHz ra-dio module (Figure 6a). An Arduino (2011) basedsystem was selected because Arduino motes areinexpensive, open-source, easy to use, and havea large support community. In addition, theXBee radio modules created by Digi International(2008) are designed as “plug and play” compo-nents, making it very easy to upgrade to a higherpower radio based on the needed transmissionrange (e.g., 100m to 10km line of sight). The wire-less mote is housed in a waterproof aluminum en-closure and the XBee radio uses a 12 dbi direc-tional Yagi antenna.

Infrared Beam Sensor: The infrared beamsensor is a SECO-LARM (2011) curtain sensorbuilt specifically for outdoor security applications(Figure 6b). This brand of infrared sensor was se-lected for two main reasons. First, the sensor isdesigned for outdoor use, with a water-tight con-struction and large operating temperature range(-49°F to 131°F). Second, to prevent false pos-itives, the sensor uses a modulated dual beamapproach, which only triggers an alarm when bothinfrared beams are broken.

Avalanche Transceiver Checker: To sensethe presence or absence of an avalanchetransceiver, we used a Beacon Checker (Figure6c) made by Backcountry Access (2010). Whenturned on, the Beacon Checker listens for a trans-mitting (457 kHz) avalanche transceiver withinproximity and indicates the presence or absence

Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska

488

Figure 5: SkinTrack was installed on the back-country access gate near Lift One at Ski Love-land, Colorado.

(a) (b)

(c)

Figure 6: We used many commercially availableproducts to build SkinTrack. (a) The wireless moteis an Arduino Fio with XBee Pro XSC 900 Mhzradio module. (b) The infrared beam sensor is aSECO-LARM passive infrared curtain sensor. (c)The avalanche transceiver checker is a BeaconChecker made by Backcountry Access.

of a beacon through visual and digital outputs.The Beacon Checker is highly adjustable, withknobs and switches to adjust the receiver range,light emitting diode (LED) brightness, power savemodes, and digital output. In addition, we in-stalled an “Are You Beeping” sign above the Bea-con Checker, which reminds backcountry travel-ers to wear and use an avalanche transceiver.

Electrical Power: Depending on the selectedbrightness of the Beacon Checker’s LEDs, Skin-

Track consumes up to three Watts of power, whichis less than an average lightbulb. SkinTrack ispowered by a 12 Volt, 35 Amp-Hour lead-acidbattery charged by a 30 Watt solar panel. Thebattery was housed in a sealed plastic container,placed on the ground, and became buried by sea-sonal snow. We chose to use a relatively largebattery and solar panel to guard against the harshwinter environment found at Ski Loveland. Inother words, the battery should last through multi-day storms and extremely cold temperatures, andthen recharge quickly when sunshine returns.

Base Station: SkinTrack’s base station con-sists of an XBee radio module and 12 dbi Yagi an-tenna connected via a USB cable to a Dell com-puter running Ubuntu Linux. The computer wasinstalled at the top of Ski Loveland’s Lift One,which has grid power and network connectivity(Ethernet). When the base station receives thewirelessly transmitted data, a daemon processstores and transfers the information to a serverlocated at the Colorado School of Mines (CSM).The server at CSM then processes the data bystoring it in a MySQL database and displaying thedata to a webpage (http://toilers.mines.edu/SkinTrack/display_data.php). After installingSkinTrack at Ski Loveland, initial tests revealedthat the data is displayed on the webpage withinseconds of walking through the gate.

4. RESULTS

SkinTrack successfully collected data fromOctober 2011 until the end of January 2012, andthen again during April 2012. Unfortunately, welost data between February-March 2012 becauseof inconsistent power and connectivity at the basestation. More specifically, we failed to implementfault-tolerance into our prototype system. Sincewe assumed constant grid power at the base sta-tion, we did not include a backup battery to keepthe base station and Ethernet port online. Thus,when Lift One lost power, the computer and Eth-ernet port would shut off, requiring a human (e.g.,lift technician) to manually restart the computerand reset the router. In Section 6, we discuss ourplans to implement fault-tolerance in SkinTrack2.0..

In this section we present results from thedata collected during our test deployment. First,we summarize the total number of backcoun-try travelers both with and without avalanchetransceivers. Second, we track backcountry us-age throughout the data collection period (i.e.,from October 2011 until February 2012, and April2012). Third, we investigate the usage results in

Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska

489

terms of each day’s avalanche forecast. Lastly,we analyze the data in terms of new snowfall asreported by Ski Loveland.

4.1. Overall Statistics

Every time a person crossed through thebackcountry gate, SkinTrack recorded the time,date, and whether or not the person was wear-ing a transmitting avalanche transceiver. Table1 summarizes the backcountry usage statisticsfor the 2011-2012 ski season. Of the 868 peo-ple that passed through the backcountry accessgate, only 327 (37.7%) were wearing transmit-ting avalanche transceivers. This number maysurprise avalanche professionals and avid back-country users; an avalanche transceiver, shovel,and probe are crucial pieces of safety equipmentthat are supposed to be carried by all backcoun-try travelers. Based on our results, less than 40%of backcountry users carried the proper safetyequipment.

Description N %With Avalanche Transceiver 327 37.7Without Avalanche Transceiver 541 62.3

Table 1: The total and percentage of backcoun-try users who passed through the SkinTrack gateboth with and without avalanche transceivers.

We now consider gate usage over the courseof the ski season. Figure 7 shows the backcoun-try access gate usage during the 2011-2012 skiseason. There are several days (e.g., Decem-ber 6th, 2011) where many people (e.g., 49 witha transceiver and 18 without a transceiver, for atotal of 67) passed through the gate. As previ-ously mentioned, SkinTrack lost power at the endof January, and was restarted at the beginning ofApril.

4.2. Gate Usage Given Forecast

We further processed SkinTrack’s data by an-alyzing gate usage in terms of the daily avalancheforecast. Throughout the snow season, the Col-orado Avalanche Information Center (CAIC) postsregional avalanche forecasts each morning wellbefore the ski lifts open (e.g., 5:30 am). Eachforecast rates the daily avalanche danger on aninternationally recognized scale from one to fiveor Low to Extreme, respectively.

The blue line in Figure 8 plots the dailyavalanche forecasts throughout the entire 2011-2012 avalanche season. In the figure, a forecast

Nov ’11 Dec ’11 Jan ’12 Feb ’12 Mar ’12 Apr ’120

10

20

30

40

50

60

Date

Co

un

t

Gate Usage per Day

No Transceiver

Transceiver

Figure 7: Backcountry access gate usagethroughout the ski season for backcountry userswith and without avalanche transceivers.

of “N/A” or “Not Available” indicates that the CAICdid not post an avalanche forecast for that day.This usually occurs at the beginning and end ofthe avalanche season (i.e., October, April).

Nov ’11 Dec ’11 Jan ’12 Feb ’12 Mar ’12 Apr ’12

N/A

Low

Moderate

Considerable

High

Extreme

Date

Daily Avalanche Forecast

Forecast

Figure 8: The daily avalanche forecasts for the2011-2012 season.

According to the avalanche forecasts plottedin Figure 8, there was a steady period of instability(i.e., Considerable or High ratings) from the end ofJanuary through the beginning of March. Unfor-tunately SkinTrack was not online for the monthsof February and March. Thus, in the rest of thispaper, we only analyze the avalanche forecastswhen SkinTrack was online. Figure 9 shows thetotal number of avalanche forecasts while Skin-Track was online. More specifically, most dayswere rated Moderate, while three days were ratedHigh. Since zero days were forecasted as Ex-treme, this rating is not included in our analysis.

We now analyze backcountry access gate

Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska

490

Low Moderate Considerable High0

5

10

15

20

25

30

35

40

45

50Number of Forecasts Given SkinTrack Online

Nu

mb

er

of

Fo

reca

sts

(N

)

Avalanche Forecast

Figure 9: The total number of forecasted dayswhile SkinTrack was online during the 2011-2012avalanche season.

usage based on the daily avalanche forecast.More specifically, we evaluate the total and aver-age number of backcountry users given the dailyavalanche forecast (Figures 10 and 11, respec-tively). Given that the majority of daily avalancheforecasts were “Moderate,” the results in Figure10 are not surprising.

More interesting results are found in the av-erage number of backcountry users given dailyforecast (Figure 11). Based on the data wecollected, an average of 15 backcountry userspassed through the access gate on days fore-casted as High on the avalanche danger scale.This number is almost five more average back-country users per day than during Moderate orConsiderable forecasts and ten more than duringLow forecasts. Thus, even when the avalanchedanger was rated as High and travel in avalancheterrain was not recommended, backcountry usersstill ventured into dangerous unpatrolled back-country terrain.

Next, we analyze transceiver usage basedon avalanche forecast. More specifically, foreach forecasted danger rating, we calculatedthe percentage of all backcountry users wear-ing transmitting avalanche transceivers (Figure12). The results indicate that when the avalanchedanger was High, 61.4% of backcountry userswore avalanche transceivers; however, only22.8% of backcountry users donned transmittingavalanche transceivers during periods of Con-siderable avalanche danger. As a comparison,35.4% and 24.2% of backcountry users woreavalanche transceivers during Moderate and Lowdanger forecasts, respectively. Though avalanchetransceiver usage was highest during periods of

Low Moderate Considerable High0

50

100

150

200

250

300

350

400

450

500Total Backcountry Users per Forecast

Ba

ckco

un

try U

se

rs (

N)

Avalanche Forecast

Figure 10: The total number of backcountry ac-cess gate usage given the daily avalanche fore-cast.

Low Moderate Considerable High0

5

10

15

20

25

30Average Number of Backcountry Users per Forecast

Ave

rag

e N

um

be

r o

f B

ackco

un

try U

se

rs

Avalanche Forecast

Figure 11: The average number of backcountryaccess gate usage given the daily forecast. Theerror bars plot the standard deviation.

High danger, these low numbers are probably dis-concerting for avalanche professionals.

4.3. Gate Usage Given New Snowfall

Lastly, we analyze gate and transceiver usagebased on the amount of new snowfall reportedeach morning on Ski Loveland’s website. In par-ticular, we divided the days with new snowfall intofour categories: trace to three, three to six, sixto nine, and nine or more inches. Of the daysSkinTrack was online, the 2011-2012 ski seasonwas mediocre; that is, there was only a handful ofpowder days with six or more inches of new snowrecorded (Figure 13).

When the amount of new snow was betweensix to nine inches (i.e., good powder days), the av-erage number of backcountry access gate usersjumped from around seven to nearly 20 people

Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska

491

Low Moderate Considerable High0

0.1

0.2

0.3

0.4

0.5

0.6

0.7Percentage of Users with Transceivers per Forecast

Pe

rce

nt

with

Tra

nsce

ive

rs (

%)

Avalanche Forecast

Figure 12: The percentage of backcountryusers with avalanche transceivers given the dailyavalanche forecast.

>0−3 3−6 6−9 9+0

5

10

15

20

25

30

35

40Number of Days with New Snowfall

Nu

mb

er

of

Da

ys (

N)

New Snowfall (in)

Figure 13: The number of days with a givenamount of snowfall while SkinTrack was onlineduring the (dry) 2011-2012 ski season.

per day (Figure 14). We found it interesting thatthere was no reported gate usage on the threepowder days with nine or more inches of snow;is nine or more inches of snow considered ‘toomuch’ by backcountry travelers?

Next, we analyze transceiver usage based onthe amount of new snowfall. Our results showthat beacon usage was lowest (17%) on dayswith six to nine inches of new snowfall, and high-est (49%) with three to six inches (Figure 15).This drop in transceiver usage is again quite dis-concerting, given that forecasts are consistentlymore dangerous with higher snowfall rates (Fig-ure 16). These results help confirm the notion thatthe excitement of fresh powder may impede deci-sion making. In other words, more people wentthrough the access gate on days with six to nineinches of fresh snow, yet far fewer had transmit-

>0−3 3−6 6−9 9+0

5

10

15

20

25

30

35

40

45

50Average Number of Backcountry Users per New Snowfall

Ave

rag

e N

um

be

r o

f B

ackco

un

try U

se

rs

New Snowfall (in)

Figure 14: The average number of backcountryusers given the amount of new snowfall reportedthat morning by Ski Loveland.

ting avalanche transceivers.

>0−3 3−6 6−90

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1Percentage of Users with Transceivers per New Snowfall

Pe

rce

nt

with

Tra

nsce

ive

rs (

%)

New Snowfall (in)

Figure 15: The percentage of backcountry userswith transmitting avalanche transceivers givennew snowfall reported.

5. CONCLUSIONS

In this article we share results from Skin-Track’s first season at Ski Loveland, Colorado.SkinTrack was installed in September of 2011and successfully collected data from October2011 through January 2012, and during April2012. The results from the collected data showthat less than 40% of the nearly 900 backcoun-try users were wearing a transmitting avalanchetransceiver.

Furthermore, our results show that the aver-age number of backcountry users and percent-age with transmitting avalanche transceivers washighest on days with High forecasted avalanchedanger. These findings seem to imply that back-

Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska

492

>0−3 3−6 6−90

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

New Snowfall (in)

Fore

cast R

ate

(%

)

Rate of Forecasts given New Snowfall

Low

Moderate

Considerable

High

Figure 16: The percentage of avalanche forecastsgiven the new snowfall. For example, 10% of thepowder days with 3-6 inches of new snowfall wereforecasted as Low avalanche danger.

country users did, in fact, modify their behavior(i.e., donned avalanche beacons) based on theHigh avalanche forecast. On the other hand, pow-der days with six to nine inches of fresh snow hadthe highest rate of backcountry users yet the low-est percentage of avalanche transceiver usage.These results provide quantitative evidence thatthe lure of new powder snow may impede deci-sion making.

Although the results we obtained from Skin-Track provide interesting backcountry usagestatistics, the two months of missing data leavesmuch room for improvement. In particular, weneed to design and implement a more robust andfault-tolerant system to collect data for the 2012-2013 season and beyond. Fortunately, our teamhas recently received a grant from the MazamasMountaineering Club to design, implement, anddeploy the next version of SkinTrack.

6. FUTURE WORK: SkinTrack 2.0

Due to our experiences in deploying SkinTrackduring the 2011-2012 ski season, we plan to de-sign SkinTrack 2.0 as a fault tolerant communi-cation system that does not rely on a local basestation. We expect SkinTrack 2.0 to be a cloud-based sensor system that will use a cell phonemodem for communication. Without a local basestation, we will have one less element that couldfail. Additionally, SkinTrack 2.0 will have backupstorage on the device itself. Thus, even if the cellphone network goes down (unlikely), we will notlose data.

SkinTrack 1.0 does not take directionality intoconsideration. Since SkinTrack 1.0 has only one

PIR sensor, it can only count whether a personhas passed through the gate, and not which di-rection the person was traveling. Thus, a personwho leaves the ski resort (through the gate) andreturns to the ski resort (through the same gate,perhaps moments later) would be counted as twodifferent people leaving the ski area. SkinTrack2.0 will solve this issue by using two PIR beamsensors. The order that the beams are brokenwill inform the direction of travel.

We plan to install SkinTrack 2.0 at Ski Love-land this October and collect data for the 2012-2013 season. Please visit http://toilers.

mines.edu/SkinTrack/ for updates and nearreal-time data.

7. REFERENCES

Arduino, 2011: Homepage. http://arduino.cc/en/. Retrieved 05-10-2012.

Backcountry Access, 2010: BeaconChecker. http://www.backcountryaccess.

com/education-research/

resorces-for-av-pros/

beaconcheckergreen/. Retrieved 05-10-2012.

Digi International, 2008: Product Datasheet:XBee Multipoint RF Modules. Tech. rep., DigiInternational.

O’Bannon, A. and M. Clelland, 2007: Allen andMike’s Really Cool Backcountry Ski Book: Trav-eling and Camping Skills for a Winter Environ-ment. Globe Pequot, Guilford, CT.

SECO-LARM, 2011: ENFORCER: Curtain Sen-sors for Indoor/Outdoor Access Control. Tech.rep., SECO-LARM USA Inc.

Proceedings, 2012 International Snow Science Workshop, Anchorage, Alaska

493