motion sensor 2 way audio alarm function and multiple
play

MOTION SENSOR, 2 WAY AUDIO, ALARM FUNCTION AND MULTIPLE USER AND - PowerPoint PPT Presentation

Jan 02, 2024 •236 likes •342 views

PANORAMIC 360 DEGREE MINI WIFI CAMERA WITH NIGHT VISION, MOTION SENSOR, 2 WAY AUDIO, ALARM FUNCTION AND MULTIPLE USER AND EQUIPMENT INTEGRATION. Panoramic Mini WiFi Camera and Security System Night vision capabilities add an additional layer

  1. PANORAMIC 360 DEGREE MINI WIFI CAMERA WITH NIGHT VISION, MOTION SENSOR, 2 WAY AUDIO, ALARM FUNCTION AND MULTIPLE USER AND EQUIPMENT INTEGRATION.

  2. Panoramic Mini WiFi Camera and Security System

  5. Night vision capabilities add an additional layer of security.

  6. IP Camera has motion detection. It will notify you if it senses any motion and record a 10 second clip of the event. You can also arm it from your phone via free app to sound an alarm from its built in speaker.

  7. Excellent app with 2 way voice. You can listen or have a conversation. Record video or take images and save on your phone. Split screen allows you to monitor several areas at the same time. Great Packaging

  8. Shared Access Up to 5 users can access cameras. One app for multiple integrated units. Additional cameras, Doorbell or outdoor cameras.

  9. Ideal for Home surveillance Home security Checking in on loved ones Monitoring pets Ideal for retail security and safety.

Download Presentation
Download Policy: The content available on the website is offered to you 'AS IS' for your personal information and use only. It cannot be commercialized, licensed, or distributed on other websites without prior consent from the author. To download a presentation, simply click this link. If you encounter any difficulties during the download process, it's possible that the publisher has removed the file from their server.

Recommend

Likelihood Functions The likelihood function answers the question: What does the sensor tell about

Likelihood Functions The likelihood function answers the question: What does the sensor tell about

Likelihood Functions The likelihood function answers the question: What does the sensor tell about the state x of the object? (input: sensor data, sensor model) ideal conditions, one object: P D = 1 , F = 0 p ( z k | x k ) = N ( z k ; Hx k

520 views • 37 slides
Wireless Ad Hoc & Sensor Networks Wireless Ad Hoc & Sensor Networks Multiple Access

Wireless Ad Hoc & Sensor Networks Wireless Ad Hoc & Sensor Networks Multiple Access

Outline Wireless Ad Hoc & Sensor Networks Wireless Ad Hoc & Sensor Networks Multiple Access Technique Medium Access Control Application Designing Issues of MAC protocols Classification of MAC protocols Classification of

306 views • 14 slides
Crop Supply Logistics This Spring Scott Irwin Jeff Bunting Audio Poor Audio Normal function

Crop Supply Logistics This Spring Scott Irwin Jeff Bunting Audio Poor Audio Normal function

LIVE | Coronavirus and Ag Crop Supply Logistics This Spring Scott Irwin Jeff Bunting Audio Poor Audio Normal function of your internet connection Solution: Call in by following instructions in email No Audio on computer Ensure

567 views • 30 slides
Coordination Algorithms Outline for Motion-Enabled Sensor Networks CDC Workshop

Coordination Algorithms Outline for Motion-Enabled Sensor Networks CDC Workshop

Coordination Algorithms Outline for Motion-Enabled Sensor Networks CDC Workshop Point-Stabilization, Trajectory-Tracking, Path-Following, and (i) state of the art Formation Control of Autonomous Vehicles (ii) research directions San Diego,

170 views • 5 slides
Multiple Sensor Target Tracking: Basic Idea Iterative updating of conditional probability

Multiple Sensor Target Tracking: Basic Idea Iterative updating of conditional probability

Multiple Sensor Target Tracking: Basic Idea Iterative updating of conditional probability densities! kinematic target state x k at time t k , accumulated sensor data Z k a priori knowledge: target dynamics models, sensor model dynamics model p ( x

541 views • 25 slides
Multiple Sensor Target Tracking: Basic Idea Iterative updating of conditional probability

Multiple Sensor Target Tracking: Basic Idea Iterative updating of conditional probability

Multiple Sensor Target Tracking: Basic Idea Iterative updating of conditional probability densities! kinematic target state x k at time t k , accumulated sensor data Z k a priori knowledge: target dynamics models, sensor model dynamics model p ( x

652 views • 34 slides
Likelihood Functions The likelihood function answers the question: What does the sensor tell about

Likelihood Functions The likelihood function answers the question: What does the sensor tell about

ambiguous sensor data ( P D < 1 , F > 0 ) k } n k n k + 1 possible interpretations of the sensor data Z k = { z j j =1 ! E 0 : the object was not detected; n k false data in the Field of View ( FoV ) E j , j = 1 , . . . , n k :

866 views • 68 slides
Integrated Motion Sensor Detection Technology When is sens TECH required ? sens TECH ensures that

Integrated Motion Sensor Detection Technology When is sens TECH required ? sens TECH ensures that

Integrated Motion Sensor Detection Technology When is sens TECH required ? sens TECH ensures that light is produced only when actually needed. INTEGRATED MICROWAVE SENSOR Direct line of sight not required Can detect through materials

457 views • 9 slides
The webinar will start at 12:00 PM EDT Topics to be covered Problems with clinical trials

The webinar will start at 12:00 PM EDT Topics to be covered Problems with clinical trials

The webinar will start at 12:00 PM EDT Topics to be covered Problems with clinical trials Deep Brain Stimulation (DBS) as a tool to simulate disease progression Motion sensor sensitivity to DBS Motion sensor test-retest reliability

212 views • 20 slides
Astrometric Stability and Precision of Fine Guidance Sensor #3: The Parallax and Proper Motion of

Astrometric Stability and Precision of Fine Guidance Sensor #3: The Parallax and Proper Motion of

Astrometric Stability and Precision of Fine Guidance Sensor #3: The Parallax and Proper Motion of Proxima Centauri G. F. Benedict 1 , B. McArthur 1 , E. Nelan 1 , D. Story 1 , A. L. Whipple 1 , W. H. Jefferys 2 Q. Wang 2 , P. J. Shelus 1 , P. D.

350 views • 5 slides
Multiple Zeta Values and Multiple Ap ery-Like Sums P. Akhilesh Institute of Mathematical

Multiple Zeta Values and Multiple Ap ery-Like Sums P. Akhilesh Institute of Mathematical

Multiple Zeta Values and Multiple Ap ery-Like Sums P. Akhilesh Institute of Mathematical Sciences (IMSc), Chennai Multiple zeta values Riemann zeta function The Riemann zeta function ( s ), is a function of a complex variable s that

755 views • 59 slides
Real-time Motion Planning of Multiple Formations in Virtual Environments: Flexible Virtual

Real-time Motion Planning of Multiple Formations in Virtual Environments: Flexible Virtual

Real-time Motion Planning of Multiple Formations in Virtual Environments: Flexible Virtual Structures and Continuum Model Yi Li & Kamal Gupta Robotic Algorithms & Motion Planning (RAMP) Lab School of Engineering Science Simon Fraser

696 views • 42 slides
WebEx Functionality Use audio on computer if available Mute phones or audio to reduce

WebEx Functionality Use audio on computer if available Mute phones or audio to reduce

WebEx Functionality Use audio on computer if available Mute phones or audio to reduce background noise Turn off video function to save bandwidth/ prevent lagging between presentation and audio Using the chat feature: Open chat

568 views • 52 slides
Motion Interpolation & Sensor Fusion Final presentation Lennart Bastian Antoine Keller Sofia

Motion Interpolation & Sensor Fusion Final presentation Lennart Bastian Antoine Keller Sofia

Introduction Background Interpolation and Approximation Interpolation and Approximation Optimization Sensor Fusion Motion Interpolation & Sensor Fusion Final presentation Lennart Bastian Antoine Keller Sofia Morales Santiago TUM

821 views • 44 slides
Multiple-output Gaussian processes Mauricio A. Alvarez Department of Computer Science, The

Multiple-output Gaussian processes Mauricio A. Alvarez Department of Computer Science, The

Multiple-output Gaussian processes Mauricio A. Alvarez Department of Computer Science, The University of Sheffield. 1 / 76 Sensor Network South Coast of England Sensor location 2 / 76 Sensor Network South Coast of England Sensor

1.97k views • 192 slides
Visual Motion Motion illusions Uses for motion cues Optic flow Motion blindness

Visual Motion Motion illusions Uses for motion cues Optic flow Motion blindness

Motion without movement illusion Visual Motion Motion illusions Uses for motion cues Optic flow Motion blindness Space-time receptive fields and the aperture problem and its solution Motion and cortical areas MT, MST

791 views • 10 slides
The BLP classroom Guy Claxton RESILIENCE emotional strength Inquisitive : has a

The BLP classroom Guy Claxton RESILIENCE emotional strength Inquisitive : has a

The BLP classroom Guy Claxton RESILIENCE emotional strength Inquisitive : has a questioning and positive attitude to learning Persistent : stays determined, positive and patient in the face of difficulty or mistakes Adventurous :

298 views • 26 slides
INTEGRATED PROCESS FOR DOCUMENT QUALITY ASSURANCE 16 th LCI Congress | San Francisco, CA |

INTEGRATED PROCESS FOR DOCUMENT QUALITY ASSURANCE 16 th LCI Congress | San Francisco, CA |

LEAN CONSTRUCTION INSTITUTE INTEGRATED PROCESS FOR DOCUMENT QUALITY ASSURANCE 16 th LCI Congress | San Francisco, CA | October 7-10, 2014 YOUR PRESENTER DENIS J STROUP, AIA SENIOR ASSOCIATE 16 th LCI Congress | San Francisco, CA | October

940 views • 80 slides
THE LATEST AND GREATEST WITH IPADS IN MUSIC EDUCATION MMEA Mid-Winter Conference February 12,

THE LATEST AND GREATEST WITH IPADS IN MUSIC EDUCATION MMEA Mid-Winter Conference February 12,

THE LATEST AND GREATEST WITH IPADS IN MUSIC EDUCATION MMEA Mid-Winter Conference February 12, 2016 Christopher J. Russell, Ph.D. Need or want a handout? Visit techinmusiced.com and download the PDF! THE LATEST AND GREATEST WITH IPADS IN

389 views • 22 slides
Conical Spiral Antennas for EoR applications A. Jiwani, S. K. Padhi, M. W. Waterson, Peter J.

Conical Spiral Antennas for EoR applications A. Jiwani, S. K. Padhi, M. W. Waterson, Peter J.

Conical Spiral Antennas for EoR applications A. Jiwani, S. K. Padhi, M. W. Waterson, Peter J. Hall, A. Sutinjo and J. G. bij de Vaate* ICRAR/Curtin University, Australia * ASTRON, The Netherlands EoR Global Signal workshop, November 19-21,

502 views • 17 slides
Induction bending provides a cost effective and more sustainable alternative to traditional pipe

Induction bending provides a cost effective and more sustainable alternative to traditional pipe

Induction bending provides a cost effective and more sustainable alternative to traditional pipe spool fabrication. NIRAS handles bending of pipes in the outer diameter range: to 20 Laboratory: Microstructural analysis Hardness

417 views • 26 slides
PRODUCT NUMBER: RT01 REAL TENDER Product Number: RT01 FASTER Crank handle for faster

PRODUCT NUMBER: RT01 REAL TENDER Product Number: RT01 FASTER Crank handle for faster

PRODUCT NUMBER: RT01 REAL TENDER Product Number: RT01 FASTER Crank handle for faster re-spooling. SAFER No more lifting Heavy wire spools. SMARTER Rolls over rough terrain on the jobsite. REAL TENDER Product Number: RT01 Product

319 views • 6 slides
Capabilities Overview Location: Date: June 20, 2017 CADS Representatives : David Stutes

Capabilities Overview Location: Date: June 20, 2017 CADS Representatives : David Stutes

Capabilities Overview Location: Date: June 20, 2017 CADS Representatives : David Stutes PRESIDENT Bobby Stollsteimer Sr PM/PCM Lonnie Gatte Sr PM Sam McNabb Sr PM (REFERED BY JIM LINSKEY) Overview Local

272 views • 11 slides
GER-LINE GERMANY Featuring th the fin finest monofilament, Founded in in 2008,

GER-LINE GERMANY Featuring th the fin finest monofilament, Founded in in 2008,

GER-LINE GERMANY Featuring th the fin finest monofilament, Founded in in 2008, fluorocarbon, GER-LINE is is pro roviding braided fishing lines worlds best range of A passion fo for qualit lity fis fishing lin lines

619 views • 29 slides

More recommend