QTSI Seismic Acoustic Perimeter Detection Profile

By: Brian Rhodes, Published on Feb 28, 2017

Detection of objects across hundreds of acres through obstacles?

Perimeter security startup Quantum Technology Sciences (QTSI) claims their system is so sensitive it can detect 'a foot step two football fields away'.

QTSI's Vector system is fundamentally different than perimeter detection methods like radar, fiber-on-fence, and thermal cameras. Instead, the system uses seismic-acoustic sensors to detect people, vehicles, drones, and aircraft through obstructions like trees or hills, often impenetrable by other detection methods.

In this note, we look at Vector's components, management team, range claims, soil impact and pricing comparing it to other long range detection systems.

********* ** ******* ****** hundreds ** ***** ******* *********?

********* ******** ************** ********** ******** (****) ****** ***** ****** ** so ********* ** *** detect '* **** **** *** football ****** ****'.

****'* ****** ****** ** ************* different **** ********* ********* methods **** *****, *****-**-*****, and ******* *******. *******, the ****** **** *******-******** sensors ** ****** ******, vehicles, ******, *** ******** ******* obstructions **** ***** ** hills, ***** ************ ** other ********* *******.

** **** ****, ** look ** ******'* **********, management ****, ***** ******, soil ****** *** ******* comparing ** ** ***** **** range ********* *******.

[***************]

Key ******

******* ****** *** *******-******** based ****** ******** *** software *** ****** *** classify ******** ***** ** threats ** ***** *********. The ******* ***:

  • ****-*****/********: **** *** ** detected ** ** *** meters (~*** ****) ***** larger ******** *** ** detected ** ** **** meters (~*,*** ****).
  • *******: ******* *** ****** shovel ******* ** **** up ** ** ****** (~150 ****).
  • ********: *********** *** ** detected ** ** *** meters (~*** ****).
  • ***********: ********* ** **** can ** ****** ** to *** ****** (~*** feet).
  • ********: *** ******** ****** elements *** ****** *****-******** up ** *** ****** (~1,500 ****).

*** ****** *** ********** by *******'* ****** ******* that ****** ******* ************ by ******-****** ********** ** by ******** ********* ********. The ***** ***** ******* example ********** ** ****** that **** *** ** further ************* **** ******* noise ** ****'* ********:

********

******* ******** ************ ** ***** ********, ********** ** ***********, by ***** *** **** sensors *** *********** *************** based ** *** **** are ********** **** *** system's ********** *** ***** software.

*** **** ********* ** a ******/***** ** ****** seismic-acoustic ******* ********* ** a ********** ****. ***** quantity *** ****** ** ***** sensors ****** ** *** area ***** *******, *** is ********* ********* ** a "****-***** *******" ** 1-8 *******, **** ******* being *********** ********* ** several ********.

  • **-*** [**** ** ****** available]: ***** **** * single ********* ******.
  • **-***: ***** **** ** to * ******* *******
  • **-*** **** ***** [**** no ****** *********]: **** version ******** ********* ** QM ***** *** ******* them **** ********* *** subsequently **** ******** **** ganged-unit ********* *** ********* finding.

*********** ** ***** ************ or ***** ******** ******* is ******** *** ***, but ** *** *** shelf ************ *** *******.

Demo *****

*******'* ******* ********** **** analyzes ******* *** ******** data **** ******** ******* to ******** ****** ******** and *********, ***** ** then ********* ** * graphical **** *********, ***** in *** ***** *****. The ***** *** ** audio:

*** ***** ***** ****'* non-Line ** ***** ********* performance, ***** **** ***** is * ***** ************** over ********* ************ **** thermal *******, ***** ** fence, or ***** ****.

Non ****-**-***** ********* ******

****** ***** **** **** detection *******, ****'* ****** claims detecting ******* ** *** other **** ** * hill ** ** **** cover, ****** *** ******/******* is **** ** ** seen ** *******. **** additionally ****** ** *** be ******** ** ******* weather ********** **** ** fog ** **** ***** makes ********* ********* **** other ************.

******* ***** ****** ***** on *** *******. *** maximum ********* ****** **** a ****** ****** *** 50 * *** *******, 125 * *** ***********, 300 * *** ********* vehicles, *** *** * for ********. *******, *** QA ******** **** ***** to ******** ***** ********* ranges. ** ****** ******* are ******** ** * small ***** *************, ***** the ** ****** *** deployed ** * ****** perimeter ***********.

Soil ******* **** ********* *** *******

**** **** *** ****** sensor ********* ***** ** how **** ** ******** signal ******. ** *******, the ****** **** ** at ************ ********** **** come **** *** *****, the ******/******* *** ********* zones. ********** ***** ** clay **** **** **** a ******* ***** **** loose, ***, *** ***** soil.  ************, **** ********** soil ********* ***** ********, saying '**** **** **** ******* into ********, *** ****** soil ** *** ***** medium *** ******** **** the *****.'

****** ******* ** ********* on background *******, ****** ************** type (******, ****, ***.), and *** *********** ******* of *** ****. ** general, ******* ******** ** 30 ****** (~*** ****) for *** ** ******, but *** **-*** *** spaced ******* ***** ****** a ** ***** ******** circle.

***** ************* *** ********* follows * **** ****** and * ********** ** requirements *** **** **********, with ******* ***** ***** recommendations ** ****** ************ and *************.

Price ********

** *******, **** ****** solutions ******* *** ** the **** *** ** most ********* ********* *******. However, ***** *** *********** and ************ ***** *** more, *** ********* *** maintenance ***** *** **** lower *** ** *** system's ****** *** ***-******* hardware.

** ******* ********* ********* project ******** * ********* (~0.65 *****) ** ****** using ** ****** ********* has ** $**,*** ****.  Quantum ******* ****** ********* distance ** * *******'* perimeter ** **** ** pricing. *** ******* ******** onsite ******, ****** ****, hardware, ********, *** * year ** ** ****** support ********. ************ (*.*., digging ****** ****** *** cable ****) ** *** included ** *** ***** or ********* ** ****, but ******* ********* ******* or ******* ************* *****.

** ********,*********'* ********** ***** *** * 750 ****** (*,*** * 2,500 ****) *** **** coverage ** ~*** ***** for ** **** ** $30,000.

***** *** ***** ********** and ********* ********** ** a ****, *** ***** number *** ************* ** radars ****** *******-******** ****** units ** *** * clear **********. ********* **** generally ** **** ********* than * **** ******** on * '*** ********* foot' *****, ******* ***** conditions, ****-**-***** ******, *** the ******* ********* ***** may ********** ***** ****'* ****** and ****** ** ***** costs.

Management ****

[**** ** ****** *********]

**** *** ** *********** management *** *********** ****, led ** **** ****** [link ** ****** *********], who *** * *** in ********** *** ********** and *** **** **** QTSI *** ****** ** years. ***** *** ******* is *** ** *** security ************** *****, **** have **** ********** ** the ********** ********** ****** it.

[**** ** ****** *********]

** *** ******** ****, QTSI ***** **** ******* [link ** ****** *********], who ********** *** ** Milestone, ** *** ****'* channels. ******* ** ******* for ******** ********** ******* partners ** **** ***** sales. **** ********** **** first ******* ** ******* the ******** ******** *******. 

Competitive **********

******'* **** ****** ********** is ******-***** *****, ***** used *** **** **** detection ** **** *****. Visible ********* *******, **** as ******* ******* ** video ********* *** ********* not * ****** ************* at ***** ****** *** to *** ***** ******** in ********** ************** *** cameras ** ***** **** **** areas.

******** ** ***** ********* systems (*** ********* ** ***** ********), ******'* *** ********* is ***-**** ** ***** detection. ***** ******-***** ***** is ****** ** ****** ******* objects **** ** *****, walls, ** *** *****, Vector ****** ** *** be ******** ** ****. 

*** ******** ***** ** radar ****** ******, ********* on *** ****** ****, but easily ******* ** ****** equal ** ** ******* than ****** ** ****** clutter *** ************ *** not ** *****.

*** ******* ************ *** QTSI ******: ***** *** cabling **** ** ******, ********** installation ***** ******** ** radar, ***** ** ********* centrally **** *******.

************

******* ** *** **** and ********** ** * Vector ************, ** ****** it **** *** **** use *** **** ***** facilities, **** ** ******** or ******** **************, **** as ****** ***********, *********, nuclear *****, ***. ***** facilities *** **** ***** located ** ***** ***** Vector's ***-**** ** ***** detection ***** ** * key ********* **** ***** means ** *********.

**** **, **** **** scenario, * ***** ******** but *** **** ***** be ** *********** ************** for ******-*** *********** *** security *********.

Comments (9)

I have spoken at length with this company at the last two ASIS shows. The technology and team are quite impressive and I look forward to an opportunity to deploy this technology. The use cases beyond perimeter detection are fascinating. Monitoring generators and equipment for mechanical anomalies before they manifest into greater problems as one example. They also have an interesting example of how they can monitor the electrical loads moving through transmission lines. 

An example perimeter detection project covering 1 kilometer (~0.65 miles) of fences using QM Series detectors has an $85,000 MSRP.

I know a real terrific guy that might be interested in 3100 km of 'top-shelf' perimeter protection for a bigly barrier.

With a 20 billion total budget, 250 million for acoustics is would be trump change.

Is it me but on the video the detection stops when the person moves from the shrubbery to the white building?  

[Mod Note: Poster is a competitor to QTSI]

Those detection estimates are imaginary at best. May in a very quiet environment with no one miles from the system, I was hoping you will actually test the system to show that it does not come even close to the claims.

Anyone that dealt with Seismic detection in military knows that beyond 50ft it starts to get almost impossible to detect footsteps, the seismic vibration does not travel that far in the ground and also no the acoustic signature. I’m not even getting into the subject of different ground types, rain, snow on the ground, ground movement, heat and cold, sand vs rocky.

I highly doubt that in a tactical walk those sensors will detect anything in 100ft let along 400ft without high level of false alarms. On top of that the foot print of 2+ people and animal are the same so this can't be placed in an area with wild life.

The reason this company has been in the market for 4+ years and haven't grown and still using an old video to prove the capabilities is that they didn't realize that over selling, over promising and BSing doesn't work on the long term.

 

We asked QTSI for response on the criticism in this post.  It is pasted below:

The sensor type QTSI uses differs from other seismic sensors.  QTSI claims theirs is higher performing, and the detection ranges are not overstated:

"QTSI's sensor is solid state (no moving parts) and is omni directional.  By combining the high quality signal data with our proprietary algorithms, we have achieved the distances we shared with you. Keep in mind, the [detection] distances are ones we are comfortable calling our maximums. There are environments where we have lesser detection ranges, which you mentioned in the article."

They included an example of the older 'geophone' style sensor versus their newer sensor design:

QTSI also furnished this demo clip of a 'tactical walk' where detection signatures are registered ~100m away from the sensor:

I tested this system at one of my company's facilities last year. The facility is located at the end of a dead end street, and is surrounded on two sides by housing, one side by a mountain, and the other is the main road. We were able to consistently detect footsteps around the facility with about 50-75 meters of buffer zone detection before the targets were picked up by our FLIR cameras along our perimeter. Further detection was unnecessary in this use case, but I did not see anything that would have led me to believe 125 meters wouldn't have been possible for pedestrian detection.

Vehicle detection was consistent with their claims, but I did not test the gunfire detection capabilities during that round. This may not be a cookie cutter solution for me, as our facilities are spread out all over the place with various terrain and soil types, and various levels of normal pedestrian and vehicle traffic, but I know I can use it in a large number of them. This technology looks like it will save me a significant amount of money over the long term, especially in terms of total cost of ownership over the life cycle of the product. The sensor's predicted lifespan is impressive as well according to their study of fail rates. The gunfire detection function will allow for the combination of two of our security layers, which will eliminate quite a few security devices and ultimately save me even more money on each project.

I completely agree with this article's comments when comparing it against products like SpotterRF, which I also tested at the same facility. There are quite a few factors which would call for additional radar units to cover dead spaces, which are mitigated when using buried sensors like these. The facilities I'm upgrading also have RFI issues, so that's another factor that led me down the buried sensor path. This is an excellent solution when used in conjunction with other layers of security.

Hi Michael,

Interesting answer but i would like to hear few other details if you don't mind.

Since detection is not telling the whole story other information is important too like:
What was the false alarm rate was or nuisance rate? How did you avoid having false alarms from animals? How did the system detect or operate in harsh weather like heavy rain or snow?
How far those facilities were from human activity, i just can't wrap my head that it can operate in those distances other than a sunny day in the middle of no where.

How many units did you use? the problem with single sensor is that there's no directional detection, did you have problem of detection in the protected side?

Hi, sorry, I didn't catch your name, other than the note that you're one of their competitors. That being said, I'll answer the best I can, but I don't want to be drawn into a debate about it since that is something that is more appropriately done between your two organizations. I can only speak from my personal experience, but given the tone of your previous comment I thought it would be best to preface my response to maintain a level of professionalism that I can be comfortable with.

As I mentioned in my comment, this system is best used in conjunction with other layers of security, notably, integrated PTZ cameras that will cue and slew to active threats. Like most systems, it is unlikely you'll be able to completely eliminate false alarms without also potentially masking legitimate alarms. It's a fine line, and it takes patience and fine tuning. In my particular use case, I am willing to tolerate a certain number of false alarms per day in order to ensure I don't miss legitimate threats. Preventing our operators from becoming complacent and desensitized to alerts is something we handle through training and analysis of alarm and response data. That becomes particularly difficult once systems grow. My system uses quite a few layers of security around our assets, with built in redundancies, so rules have been created to further reduce false alarms by masking them unless a redundant system also detects the same threat/a threat in the same area. That kind of thing is cost prohibitive to most small system owners, but is crucial when dealing with thousands of sensors.

Regarding your question on harsh weather, we did experience heavy rain during our testing period and I did not see a significant impact on the system's detection abilities. As far as snow is concerned, that isn't something that happens where I live, so I have no idea how the sensors would perform, you'd have to ask them.

The test system we used utilized four sensors (possibly six, I can't remember) spaced about 25-30 meters apart. As I mentioned in my comment, the facility was surrounded on two sides by residential areas, with a mountain on one side, and a main street on the other. The facility was on the end of a dead end street, so vehicle traffic was not heavy but was present during most times of the day. The area is also frequented by wild boars, but I don't recall seeing any during the test period. We were able to get highly accurate directional data for pedestrians during all of our functional tests. Vehicle detection was also accurate, but given they can only travel in two directions in this case, I can't speak for how it would perform in any other situation. For our needs, it did exactly what we needed it to do. It told us when a vehicle pulled up near our gate, and told us when pedestrians exited and approached the facility. All of this was verified in real time by our PTZ, FLIR, and fixed cameras.

I agree with you that a single sensor has limitations, and I wouldn't recommend using a single sensor if you're looking for a high degree of accuracy. What I like about this system is that it is modular, and can be tailored to each facility's specific needs. I also think the type of customers who would use this kind of system/can afford it, understand most of the concepts that we've been discussing and design their systems to avoid being led astray by erroneous data coming in from remote sites.

 

 

Just to clarify the Mod note, although in the same industry I’m not a competitor and never competed against them not in technology, not in price and not in target market... all the questions that I asked were based on my knowledge and experience of existing technologies and capabilities.

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