Key ********
*** ******* ****** **** the ****** *** ******* decent ******** ** ************ VMD *** *** ****** that ***********, ********* **** 2 **** ******:
- *** ****** *** ****** restrictive / *********** ************ 'recommendations', **** ******* ** - **° ********.
- **** **** *** ******** recommendation, ***** **** ***** false ********* (*.*., ****** being *********** **** ** people **** *******).
- *******, *** ********* *** restrictive ******** **************, *** false ********* **** **** more ***********.
**** *****, ******** ** conventional ***, ******* ***** alerts **** *****.
Solid ***** ***** **********
** *** *******, *****.***'* Video ****** ********* (***** Analytics) *** ********* ********* in ******** ****** ***** alerts ****** ** ******* foliage, ****** ******, *****, insects, *******, *** ****** which ********** ********* ************** ********* ** *** testing.
********** *** *********** *** customers, ***** *** ***** Analytics ****** **** *** down ** *** **** 'false *****' ******. *******, it *** ******* *** reliable ****** ** ********* all ******.
Classification ******
*** ******* ******** *********** is *** ******** ***-***-****, even **** ******* *** installed ********* ** *************. Some *******/****** **** ***** to ** **** ****** inaccurate **** ******. *** example, *** ****** ******** often ******** *** ******* 'people' ** *** **** scene ** ********:
** ******* ** ***** events, ** ****** **** present, ******* *** *****. The ******** ** ** LP-Natural **** *** *****, in *********** **** * moving *******, ***** ******** in *** ****** ********* the *** ***** ******** as * '******':
** ***** *****, *** system ****** ****** *** animals ********, ** ** this *****:
****** *** ********** ** the *** **** * person ******* ** ** classification ****.
Small ****** *********
*** **** ***** ******** the '******' ************** ** working. *** ****** *** not **** ** ****** and ****** ****** ******** accurately (** **** *********, dogs *** *******), *** the ****** *** *** classify *** ******** ** 'animal' ********* ** *** way ** ******* ****** and ********.
*** **** ***** ** an ******* ** ********, but *** **********, ****** movement:
********** *********** ***** ****** may ***** ********* ********, especially ** ***** *** rules ** ****** *** general ****** ****** **** a **** *****-***** ***********, but ******* ******* ****** to ***** ** ******* or **** **** *** be ********* ** **** that **** ****** *****.
** ***** *****, *** zone ****** ********* *** have ** ** *** as **** ** **** 'fast' ***** ***** ** 0.5 ******* ** **** an ***** ** ****** small ** ****-****** *******, but ***** ******** *** also ************* ******** ******** alarms ** *** **** time.
Steep ******** *********
****** **** *** ******** analytic ****** ** ******, Alarm.com *** *********** *********** requirements ** **-**° ********, mounted ** ***** * feet **** *** ** coverage ****** **' ** night:
*** *********** ** ***** makes ** ***** *********** in *** ** *** be ***** *** *** far ** *** *****, even ******** ***** ** consumer *********.
Nonconformance ********* ******
******* *** ****** ** be *** ** **** shallower *********, ******** **-**° for ****** *** ** users ** ********** *** familiar **** ***'* **************.
*******, ** **** *****, we *********** ***** ******** errors ** * ******. For *******, ** **** case * ******* *** not ********** ** ** approached *** ******, *** was ********** ******** ***** the **** ** ** was *******:
**** **** ***** ******* was ******* ** ** activity ***** ** *** system, *** ********* *** clip ***** ** *********** movement ** *** ****** at ***:
***** ******** ******** ****** did *** ******* **** adjusted ** *** ******** specification *********** ** ***, but ***** ******** ***** are *** ***** ** highlighted ** ********* ********* during *****.
Rain/Snow ********* ******
** **** *** *** tested **** *** **** to *** **** ****** that ******. ** ****** to *** **** ** the **** ****** *** will **** ** ****** in *** ******.
******: **** ***********
***** * ~* **** period ** ****** **** in ******* *** *****, our **** *** *** record *** ***** ******** or ******** ****** ** classification.
Detection *********
*** ******* ************ ******** objects ********** ** *** levels ***** **** ********* in *** ***** *****. For *******, *** ***** disclaims ****** ********* ****** 25' ** *** *** 15' ** *****, *** the ****** ********* ****** at **** ** ***** ranges.
*** ***** ***** ***** ~50' ************** ** * vehicle ** ******* *****:
Good *** **********
******* ****** ******* ** VMD **** ***'* ********* overcomes ** ****** ********** due ** ****** *******, leaves, *** *******. *** ADC ****** *** *** trigger ********** ** **** nuisance ************* ** *** point ****** *** ****.
**** ** ** ******* clip ******* ****** ******** that ***** ******* *** but *** *** ***** Analytics *****:
Motion/Analytic *************
** ******, *** ** offering *** ********* *****, a ***- ** ************* 'tripwire' ** * '****** zone' **** ******* **** objects ***** ****-******* *****:
** ******** ** *** rules, ***** *** ********* assign *** **** ******* must ** ** ********* of *** **** ****** an ***** ** ****, or **** ** ***** arm/disarm ****** ** **** of *** ********** ********. The ******** **** ****** assigning ** ***** ** objects ***** ** *** direction ** *** *****.
*** '****** ****', *** detection **** ***** ** flexible *** *********** ****** scenes ******* *********** ********* areas:
Camera *********
*****.*** ****** ~* ***** camera ******, *** **** 2 ** **** *** supported ** ***** ** analytics, *** ****** ***** w/IR (***-******) ********* ******** (***-*****). ** ****** *** (Vivotek ***'*) ******* ****, shown ** *** *****.
Camera/Service *******
*** *** ******* ******* a ******* ************ ** order ** ******* ********/***** alerts ***/** **** ***** video. ****** ******* ** ~$1 **** *** ***** added ** *** ~$*/*** four ******* '***' ***** plan ** ******** *** AI *********. *** ********* package **** **** ******** clips, ******** *** ***** to *,*** *** * cameras ** **** *,***. Camera ****** *** ~$*** for ***-*****.
Versus ******/****
****'* ********* **** **** accurate **** *****.*** *** does *** ********* **** installation ************. ***** ****** detection ********* ** *** require * ************ ** receive ******. *******, ***** video ******** ** *********** without ***** ***** ************, ******* **** $*/***** per ****** (* ****) through $**/***** *** ** days. *** **** ******* IQ ** ***************** **** **** *** $349.
Versus ****
*******'* ****** ********* *** more ***** ****** *** require **** ****** ******** distances/higher *** **** ***. Arlo ****** ********* ********* require * ************ ****** *****, ******** ** $*.** per ******, ********* * days *******, *** ** to $**.** *** ** days *******. **** ******* and **** ******* ***** at $*** *** *** original**** ****** $*** *** ******** **** *
Versus ******/****
** *******, ***'* ********* are ****** ********** **** Amazon/Ring, *** ******* ***** quality *** **** ** not **** *** ***** made ***** ** ******* WiFi.
****'* "******** ****** *********" motion ********* **** *** require * ************ *** motion ******, ******** * subscription ** ****** ** view ******** ***** ******** at $* *** *****.**** ********* ********** *** $*** *** can ** ********* **** the **** *******.
Comments (13)
John Honovich
Brian, good report!
Vendors need to be more cautious and conservative about using "AI" in marketing, as mediocre performance like this is going to disappoint and undermine the confidence in "AI" generally.
On the one hand, since machine learning is generally considered part of AI and surely Alarm.com is using some form of machine learning, they could technically make the case that it is "AI".
The problem is that most people expect "AI" to be, well, intelligent or at least as intelligent as a 5-year-old. For $1 a month, this is not a bad offering but it's not good enough to be trusted for high accuracy or to be marketed as "AI".
Create New Topic
Brian Rhodes
One interesting aspect of the 'AI' implementation is that 'learning' is fairly coarse and only happens without user refinement.
Right now, AI video learning happens as all video is ingested into ADC's cloud via an opt-in sharing feature:
Alarm.com mentioned to us in a call they plan to add a self-reporting feature allowing users to flag incorrectly classified objects.
The platform does not currently have this or any method to manually 'teach' or 'learn' the system based on user feedback.
Create New Topic
Michael Gonzalez
11/30/18 06:49pm
Excellent report Brian! Thanks for doing this, it saved me a massive amount of time.
Create New Topic
Scott Sheldrake
Thanks for the detailed report. Please update when you have gone through a good rain. That's going to be the real test.
Do you have a rough idea of the number of clips you get in a typical day? How well does the ridiculous 1000 clip/month recommendation from ADC hold up? 1000 clips /mo= 33 clips per day or 1.3 clips per hour. Seems unlikely you would be able to have less than 1000 clips per month.
Create New Topic
Undisclosed #2
highest-performing AI to date: The Answer
Create New Topic
Brian Rhodes
UPDATE: RAIN PERFORMANCE (added above to report)
After a ~3 hour period of steady rain in evening and night, our test did not record any false positive or observed errors in classification.
Create New Topic
Scott Sheldrake
This about summarizes ADC video :
Create New Topic