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)

Avatar

Kyle Smith

02/28/17 05:06pm

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. 

Undisclosed #1

02/28/17 08:28pm

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.

Undisclosed Integrator #2

02/28/17 10:32pm

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

Undisclosed Manufacturer #3

03/01/17 03:42am

[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.

 

Avatar

Brian Rhodes

IPVMU Certified | In reply to Undisclosed Manufacturer #3 | 03/01/17 06:21pm

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:

Avatar

Michael Gonzalez

Integrated Security Technologies, Inc. | In reply to Undisclosed Manufacturer #3 | 03/02/17 10:49pm

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.

Undisclosed Manufacturer #3

In reply to Michael Gonzalez | 03/03/17 01:01am

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?

Avatar

Michael Gonzalez

Integrated Security Technologies, Inc. | In reply to Undisclosed Manufacturer #3 | 03/03/17 01:56am

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.

 

 

Undisclosed Manufacturer #3

03/03/17 03:10am

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.

Login to read this IPVM report.
Why do I need to log in?
IPVM conducts unique testing and research funded by member's payments enabling us to offer the most independent, accurate and in-depth information.

Related Reports

Bezos-Funded Deep Sentinel Tested on Mar 28, 2019
Backed by Jeff Bezos, the Silicon Valley startup, Deep Sentinel, has declared: No One Does Home Security Like We Do Our Surveillance Team has...
Bosch AI Camera Trainer Released And Tested on Apr 09, 2019
Bosch is releasing a highly unusual new AI feature - 'Camera Trainer'. Now, coming as a standard feature in Bosch IVA/EVA analytics, one can train...
Camera Disruptor Wyze Enters Sensor / Security Market on Mar 28, 2019
Wyze, the company that has disrupted consumer IP cameras, combining American marketing and Chinese manufacturer, has just announced its expansion...
Axis Live Privacy Shield Analytics Tested on Jun 25, 2019
Privacy is becoming a bigger factor in video surveillance, driven both by increased public awareness and by GDPR. Now, Axis has released Live...
Calipsa - UK AI Startup Profile on Jul 10, 2019
Analytic startups are a major industry trend. One UK company, Calipsa is aiming to use AI to filter out false positive alarms for live video...
ZeroEyes Gun Detection Startup on Jul 16, 2019
A gun detection video analytics startup, ZeroEyes, is being led by a group of 6 former Navy SEALs, aiming to "save lives" by using AI to assist...
Lasers Impact on Surveillance Cameras Tested on Sep 25, 2019
Hong Kong protests have brought global attention to video surveillance and the ongoing attempts of protesters to disable or undermine those cameras...
Camect "Worlds Smartest Camera Hub" Tested on Oct 18, 2019
Camect is a Silicon Valley startup that claims the "Smartest AI Object Detection On The Market", detecting not only people and vehicles, but...
Hidden Camera Detectors Tested on Nov 18, 2019
Hidden cameras are a growing problem as cameras become smaller, cheaper and easier to access. However, some companies claim to be able to detect...
Halo Smart Vape Detector Tested on Jan 16, 2020
The Halo Smart Sensor claims to detect vaping, including popular brand Juul and even THC vapes. But how well does it work in real world...

Most Recent Industry Reports

Hazardous & Explosion Proof Access Control Tutorial on Feb 27, 2020
Controlling access to hazardous environments requires equipment meeting specific ratings that certify they will not start fires or will not...
Motorola / Avigilon Drops ISC West on Feb 26, 2020
Motorola Solutions has pulled out of ISC West 2020 effective immediately, because of coronavirus concerns, IPVM has learned. This is done amidst...
Cancel or Not? Industry Split Over ISC West on Feb 26, 2020
The industry is split, polarized, over whether ISC West 2020 should run or be canceled. New IPVM survey results of 400+ respondents show heated...
Coronavirus Hits Sony, Bosch Says Switch on Feb 26, 2020
Sony's fall in video surveillance has been severe over the past decade. Now, they may be done. In this note, we examine Bosch's new...
Video Surveillance Cameras 101 on Feb 25, 2020
Cameras come in many shapes, sizes and specifications. This 101 examines the basics of cameras and features used in 2020. In this report, we...
Favorite Video Analytic Manufacturers 2020 on Feb 25, 2020
Video analytics is now as hot as ever, driven by the excitement of advancing deep learning offers. But what are actually integrator's...
Latest London Police Facial Recognition Suffers Serious Issues on Feb 24, 2020
On February 20, IPVM visited another live face rec deployment by London police, but this time the system was thwarted by technical problems and...
Masks Cause Major Facial Recognition Problems on Feb 24, 2020
Coronavirus is spurring an increase in the use of medical masks, which new IPVM test results show cause major problems for facial recognition...
Every VMS Will Become a VSaaS on Feb 21, 2020
VMS is ending. Soon every VMS will be a VSaaS. Competitive dynamics will be redrawn. What does this mean? VMS Historically...
Video Surveillance 101 Course - Last Chance on Feb 20, 2020
This is the last chance to join IPVM's first Video Surveillance 101 course, designed to help those new to the industry to quickly understand the...

What IPVM Is

The world's leading authority on video surveillance, with 200,000+ visits monthly.

  • Articles on cameras, video analytics, VMS, and trends
  • Tests showing actual performance and problems
  • Courses in surveillance, access control, etc
  • Camera Calculator for designing systems

Dedicated To Independence

We're dedicated to staying independent and objective. We're the only industry source to refuse any and all advertisements, sponsorship, and consulting from manufacturers. Why?