Frigate – object detection and notifications

Intro

My notes on setting up Frigate NVR for a home CCTV setup.

The main focus of this post is on object detection (utilising a Google Coral TPU) and configuring notifications to Amazon Fire TVs (and other devices) via intregration with HomeAssistant.

There’s a lot to cover and no point in reproducing the existing documentation, you can find full details & info on setting up the main components here:

ZoneMinder
Frigate
HomeAssistant

Background

I used Zoneminder for many years to capture and display my home CCTV cameras. There are several posts – going back to around 2016 – on this site under the ZoneMinder category here

This worked really well for me all that time, but I was never able to setup Object Detection in a way I liked – it can be done, in a number of different ways, but everything I tried out was either very resource intensive, required linking to Cloud services like TensorFlow for processing, or was just too flaky and unreliable, none of which suited my needs. Integration and notification options were also possible, but not straightforward.

So, I eventually took the plunge and switched to Frigate along with HomeAssistant. There was a lot to learn and figure out, so I’m posting some general info here in case it helps other people – or myself in future when I wonder why/how I did things this way….

Hardware

I have 4 CCTV cameras, these are generic and cheap 1080p Network IP cameras, connected via Ethernet. I don’t permit them any direct access to the Internet for notifications, updates, event analysis or anything.

I ran ZoneMinder (the server software that manages and presents the feeds from the cameras) on various hardware over the years, but for the Frigate and HomeAssistant setup I have gone for an energy-efficient and quiet little “server” – an HP ProDesk 600 G1 Mini – it’s very very basic and very low powered… and cost £40 on eBay:

I have added a Google Coral Edge TPU to that via USB so I can offload the detection/inference work and spare the little CPU’s energy for other tasks:

Objectives

My key goals here were to:

  1. Setup and trial Frigate – to see if it could fit my requirements and replace ZoneMinder
  2. Add Object Detection – without having to throw a lot of hardware at it or use Cloud Services like TensorFlow
  3. Integrate with HomeAssistant – I’d been wanting to try this for a while, to integrate my HomeKit devices with other things like Sonos, Amazon Fire TVs, etc

Setup and trial Frigate: setting up Frigate was easy, I went for Ubuntu on my host and installed Docker on that then configured Frigate and MQTT containers to communicate. These are both simply declared in the Frigate config like this:

mqtt:
  host: 192.168.0.27
detectors:
  coral:
    type: edgetpu
    device: usb

Add Object Detection: with Frigate, this can be done by a Google Coral Edge TPU (above) – more info here: https://coral.ai/products/accelerator/ and details on my config below. I first trialled this using the host CPU and it ‘worked’ but was very CPU intensive: adding the dedicated TPU makes a massive difference and inference speeds are usually around 10ms for analysis of 4 HD feeds. This means the host CPU is free to focus on other things (which is just as well given the size of the thing).

    objects:
      track:
        - person
        - dog
        - car
        - bird
        - cat

https://docs.frigate.video/configuration/objects

Integrate with HomeAssistant : Added the HomeAssistant Docker instance to my host, then ran and configured MQTT container for Frigate then configured Frigate + HomeAssistant to work together. This was done by first installing HACS in HA, then using the Frigate Integration as explained here:
https://docs.frigate.video/integrations/home-assistant/

Setup Notifications

Phone notifications – I have previosuly had (and posted about my) issues with CGNAT and expected I would need to set up and ngrok tunnel and certs and jump through all sorts of hoops to get HA working remotely.

HA offers a very simple Cloud Integration via https://www.nabucasa.com/

I trialled this and was so impressed I have already signed up for a year – it’s well worth it for me and makes things much simpler. Phone notifications can be setup under HomeAssistant > Settings > Automations and Scenes > Frigate Notifications – after installing the Frigate Notifications Bueprint via HACS.


Amazon FireTV notifications – I have just setup the sending of notifications to the screen of my Amazon Fire TV, this was done by first installing this app on the device:
https://www.amazon.com/Christian-Fees-Notifications-for-Fire/dp/B00OESCXEK
Then installing
https://www.home-assistant.io/integrations/nfandroidtv/
on HA and configuring Notifications as described there. I now get a pop-up window on my projector screen whenever there’s someone at my front gate.

This is a quick pic of my projector screen with an Amazon Fire TV 4k displaying a pop-up notification in the bottom-right corner:

This means I now don’t need to leave a monitor on showing my CCTV feeds any more, as I am notified either via my mobile or on screen. And my notifications are only set up for specific object types – people & cars, and not for birds or sheep!

Minor Apple Watch update – these notifications are also picked up on Apple Watch, if it’s set to display your phone notifications. So I can also get a short video clip of the key frames on mine.


My Frigate Config – here’s an example from the main “driveway” camera feed, this is the one I want to be montoring & ntoified about most. It’s using RTSP to connect, record and detect the listed object types that I am interested in:

  driveway:
    birdseye:
      order: 1  
    enabled: True
    ffmpeg:
      inputs:
        - path: rtsp://THEUSER:THEPASSWORD@192.168.0.123:554/1
          roles:
            - detect
            - rtmp
        - path: rtsp://THEUSER:THEPASSWORD@192.168.0.123:554/1
          roles:
            - record        
    detect:
      width: 1280
      height: 720
      fps: 5
      stationary:
        interval: 0
        threshold: 50  
    objects:
      track:
        - person
        - dog
        - car
        - bird
        - cat

The full 24/7 recordings are all kept (one file/hour) for a few days then deleted and can be seen via HA under
Media > Frigate > Recordings > {camera name} > {date} > {hour}

Docker container start scripts

A note of the scripts I use to start the various docker containers.

This would be much better managed under Docker Compose or something, there are plenty of examples of that online, but I’d like to look at setting all of this up on Kubernetes so leaving this as rough as it is for now.

I am also running Grafana and NodeExporter at the moment to keep an eye on the stats, although things would probably look less worrying if I wasn’t adding to the load just to monitor them:

<help!>

I’ll need to do something about that system load; it’s tempting to just get a second HP host & Coral TPU and put some of the load and half of the cameras on that – will see… a k8s cluster of them would be neat.

# Start Frigate container
docker run -d \
--name frigate \
--restart=unless-stopped \
--mount type=tmpfs,target=/tmp/cache,tmpfs-size=1000000000 \
--device /dev/bus/usb:/dev/bus/usb \
--device /dev/dri/renderD128 \
--shm-size=80m \
-v /root/frigate//storage:/media/frigate \
-v /root/frigate/config.yml:/config/config.yml \
-v /etc/localtime:/etc/localtime:ro \
-e FRIGATE_RTSP_PASSWORD='password' \
-p 5000:5000 \
-p 8554:8554 \
-p 8555:8555/tcp \
-p 8555:8555/udp \
ghcr.io/blakeblackshear/frigate:stable

# Start homeassistant container
docker run -d \
--name homeassistant \
--privileged \
--restart=unless-stopped \
-e TZ=Europe/Belfast \
-v /root/ha_files:/config \
--network=host \
ghcr.io/home-assistant/home-assistant:stable

# Start MQTT container
docker run -itd \
--name=mqtt \
--restart=unless-stopped \
--network=host \
-v /storage/mosquitto/config:/mosquitto/config \
-v /storage/mosquitto/data:/mosquitto/data \
-v /storage/mosquitto/log:/mosquitto/log \
eclipse-mosquitto

# Start NodeExporter container
docker run -d \
--name node_exporter \
--privileged \
--restart=unless-stopped \
-e TZ=Europe/Belfast \
-p 9100:9100 \
prom/node-exporter

# Start Grafana container
docker run -d \
--name grafana \
--privileged \
--restart=unless-stopped \
-e TZ=Europe/Belfast \
-p 3000:3000 \
grafana/grafana

Hey Siri, manage my server…

Intro

I use Siri and Apple Homekit to automate some basic things – switching lights and heaters on/off, etc – and was wondering if there was some way I could use Siri to run tasks on my computers and servers at home.

Some googling showed me this was possible and also reasonably easy to set up – these are my notes on the process and some examples of what I’ve done with it so far.

Setup on iPhone

There’s a free Apple “Shortcuts” app for iPhones:

https://apps.apple.com/us/app/shortcuts/id915249334

which can perform a wide range of tasks, including – as of reasonably recently – the abiltiy to run scripts over SSH.

Open the Shortcuts App, click + and then Add action. These pics show the process from that point on:

Click on Add Action….

From here you fill out the details – the IP address of the remote computer, the user and password, and the path to the script you want to run.

Requirements

You need to have SSH setup and a working script you can run over SSH first.

On Ubuntu that means installing and configuring SSH as described here:

https://linuxize.com/post/how-to-enable-ssh-on-ubuntu-20-04/

On MacOS you need to enable Remote Login under Sharing here:

You also need a script that is executable as the user you are connecting with.

Obviously, be aware of the security risk of enabling tasks to be run remotely, etc.

Examples

Here are some I made earlier.

This one connects to my old Mac Pro (it runs Ubuntu) and runs a ‘shutdown’ script.

My /home/don/shutdown script simply contains “sudo init 0” and the ‘don‘ user is enabled for passwordless sudo.

and this one connects to the same host and powers on the attached monitor, that runs Firefox showing my CCTV/Zoneminder conosole:

The “/home/don/screenon” script contains this:

xset -display :0.0 dpms force on

and there’s a ‘screenoff’ that switches the display off when I don’t want it too.

For my iMac runnning MacOS I’ve added a shutdown script – useful when I don’t want to go and power it off manually.

I’ve ended up with a selection of shortcuts to power things on & off, and can now say “Hey Siri, CCTV on please“, or “Hey Siri, shutdown iMac please“, and Siri makes it so….

This setup enables me to run pretty much anything on a Linux or Mac host simply by asking Siri – it could trigger deployment pipelines, perform updates, start/stop/restart services…. anything you can put in a shell script.

If you have any interesting ideas or suggestions please let me know below.

Tunneling out of Carrier Grade Nat (CGNAT) with SSH and AWS

Update: there’s a new & improved solution here too.
Intro

After switching to a 4G broadband provider, who shall (pretty much) remain nameless, I discovered they were using Carrier-Grade  NAT (aka CGNAT) on me.

There are more details on that here and here but in short, the ISP is ‘saving’ IPv4 addresses by sharing them out amongst several users and NAT’ing their connections – in much the same way as you do at home, when you port forward multiple devices using one external IP address: my home network is just one ‘device’ in a pool of their users, who are all sharing the same external IP address.

The impact of this for me is that I can no longer NAT my internal network services, as I have been given a shared pubic-facing IPv4 address. This approach may be practical for a bunch of mobile phone users wanting to check Twitter and Facebook, but it sucks big time for gamers or anyone else wanting to connect things from their home network to the internet. So, rather than having “Everything Everywhere” through my very expensive new 4G connection – with 12 months contract – it turns out I get “not much to anywhere“.

The Aim

Point being; I would like to be able to check my internal servers and websites when I’m away – especially my ZoneMinder CCTV setup – but my home broadband no longer has its own internet address. So an alternative solution had to be found…

The “TL; DR” summary

I basically use 2 servers, the one at home (unhelpfully now stuck behind my ISPs CGNAT) and one in the Amazon Cloud (my public facing AWS web server with DNS), and create a reverse SSH Tunnel between them. Plus a couple of essential tweaks you wont find out about if you don’t read any further 🙂

The Steps
Step 1 – create the reverse SSH tunnel:

This is initiated on the internal/home server, and connects outwards to the AWS host on the internet, like so.

ssh -N -R 8888:localhost:80 -i /home/don/DonKey.pem awsuser@ec2-xx-xx-xx-xx.compute-x.amazonaws.com

Here is an explanation of each part of this command:

-N (from the SSH man page) “Do not execute a remote command.  This is useful for just forwarding ports.”

-R (from the SSH man page)  “Specifies that connections to the given TCP port or Unix socket  on the remote (server) host are to be forwarded to the given host and port, or Unix socket, on the local side.”

8888:localhost:80 – means, create the reverse tunnel from localhost port 80 (my ZoneMinder web app) to port 8888 on the destination host. This doesn’t look right to me, but it’s what’s needed for a reverse tunnel

the -i and everything after it is just me connecting to my AWS host as my user with an identity file. YMMV, whatever you nornally do should be fine.

When you run this command you should not see any issues or warnings. You need to leave it running using whatever method you like – personally I like screen for this kind of thing, and will also be setting up Jenkins jobs later (below).

Step 2 – check on the AWS host

With that SSH command still running on your local server you should now be able to connect to the web app from your remote AWS Web Server, by reading from port 8888 with curl or wget.

This is a worthwhile check to perform at this point, before moving on to the next 2 steps – for example:

don@MyAWSHost:~$ wget -q -O- localhost:8888/zm | grep -i ZoneMinder
      <h1>ZoneMinder Login</h1>
don@MyAWSHost:~$

This shows that port 8888 on my AWS server is currently connected to the ZoneMinder application that’s running on port 80 of my home web server. A good sign.

Step 3 – configure AWS Security & Ports

Progress is being made, but in order to be able to hit that port with a browser and have things work as I’d like, I still need to configure AWS to allow incomming connections to the newly chosen port 8888.

This is done through the Amazon EC2 Management Console using the left hand menu item “Network & Security” then “Security Groups”:

awsmenuThis should load your current Security Groups, which you can click on to Edit. You may have a few to check.

Now select Add and configure a new Inbound rule something like so:

awsinboundruleIt’s the “Custom TCP Rule” second from the bottom, with port 8888 and “Anywhere” and “0.0.0.0/0” as the source in my picture. Don’t go for the HTTP option – unless you’re sure that’s what you want 🙂

Step 4 – configure SSH on AWS host

At this point I thought I was done… but it didn’t work and I couldn’t immediately see why, as the wget check was all good.

Some head scratching and checking of firewalls later, I realised it was most likely to be permissions on the port I was tunneling – it’s not very likely to be exposed and world readable by default, is it? Doh.

After a quick google I found a site that explained the changes I needed to make to my sshd_config file, so:

vim /etc/ssh/sshd_config

and add a new line that says:

GatewayPorts yes

to that file, checking that there’s no existing reference to GatewayPorts – edit this file carefully and at your own risk.

As I understand it – which may best be described as ‘loosely’ – the reason this worked when I tested with wget earlier is because I was connecting to the loopback interface; this change to sshd binds the port to all interfaces. See the detailed answer on this post for further detail, including ways to limit this to specific users.

Once that’s done, restart sshd with

service ssh restart

and you should now be able to connect by pointing a web browser at port 8888 (or whatever you set) of your AWS web server and see your app responding from the other end:

zmlogin
Step 5 – automate it with Jenkins

The final step for me is to wrap this (the ssh tunnel creation part) up in a Jenkins job running on my home server.

This is useful for a number of reasons, such as avoiding and resetting defunct/stale connections and enabling scheduling – i.e. I can have the port forwarded when I want it, and have it shutdown during the hours I don’t.

CCTV with Tenvis cameras and ZoneMinder

This post details the processes I went through to create my own DIY home CCTV system.

Topics covered include:
1. Hardware – some cheap but impressive Tenvis TH692 720p IP cameras, and some Power over Ethernet (PoE) injectors and extractors to go with them
2. Camera setup – how to set them up, connect to them, and a quick summary of basic functions
3. Clients – info on a few different ways to attach to and use the cameras – VLC, Kodi/XBMC, RTSP and the built-in app and web interfaces
4. Jenkins – using Jenkins jobs to capture and record from Tenvis cameras
5. ZoneMinder – installation, OVA and manual install, settings used
6. Summary, links and general info

1. Hardware
On recommendation from a friend, the cameras I went for are these:
Tenvis TH692’s
“720P HD Outdoor Network Wireless CCTV IP Camera with 15M Night Vision”

these cameras are currently available on Amazon for only £27 each!

The cameras can happily run over WiFi but as they will still need a power connection, I have opted to run them over Ethernet and to send the power over the CAT6 cable too – this way there’s still only 1 cable required, and I get a faster network connection too.

To do this I have used these:
AKORD® POE Passive Power Over Ethernet Adapter Injector Extractor Kit

These clever little beasties work with the power adapter that comes with the Tenvis TH692’s, and come complete with both a PoE Injector and Extractor, for only £3.99 – another mega-bargain! I haven’t tested them for outdoor use in bad weather yet, but suspect they may require some protection from the elements, which is fair enough.

2. Camera Setup
Connecting the cameras to your home network and getting them up and running is pretty easy. You need to connect them wired initially and use DHCP to assign an address. With that done, you can then use the supplied software to find, connect to and configure the cameras. After that’s complete, you can connect them to your WiFi, change the name/label for the camera, set up users and passwords, set up Email and FTP alerts and settings and so on.

3. Clients
I found the supplied software sufficient for the initial setup, and the phone app (search for “NEW Tenvis” in the App store) works very well, allowing you to monitor your camera(s) from anywhere in the world assuming you’ve got an internet connection at both ends. Here’s a picture from my iPhone:

iphone_tenvis

 

The web interface relies on browser plugins and didn’t work on my Mac under Chrome, Firefox or Safari – it wanted an out dated QuickTime plugin which I couldn’t get working, though I confess I didn’t try too hard. It worked ok on my Windows VM, but I don’t want to use that interface or that OS. Luckily there are plenty of alternative options though, as these cameras use RTSP…

The Real Time Streaming Protocol (RTSP) is a network control protocol designed for use in entertainment and communications systems to control streaming media servers. The protocol is used for establishing and controlling media sessions between end points.

[ Source: Real Time Streaming Protocol – Wikipedia, the free encyclopedia ]

This opens up several options for connecting to the cameras, and means that you don’t need to rely on the supplied software and interfaces. For me, this is what makes these cameras so good.

Here are the solutions I use, though there are many more available…

VLCVideoLAN – as you’ll probably know, this great free and open source cross-platform multimedia player plays pretty much anything, and on pretty much every platform.  Not surprisingly, I found I could point this player at the cameras RTSP feed, enabling me to view the video content from all devices that VLC runs on.

I use this approach on my Mac laptop mostly, and it’s as easy as creating a small config file for each camera feed then clicking on it to open the live feed. The files can be saved with “.m3u” extensions, as long as you’ve set that file type to be handled by VLC.

For example, here are the contents of the “cctv_driveway.m3u” file I currently have on my OSX Desktop, and that I click to connect to that feed:

#EXTM3U
#EXTINF:0, Driveway CCTV
rtsp://USERNAME:YOURPASSWORD@192.168.0.151:554/1

that’s it – just 3 lines.

Line 1, “#EXTM3U” is the file header which must be the first line of the file – like a Bash “shebang”.

Line 2, “#EXTINF:0, Driveway CCTV” contains the track information (just a zero here) and the title of the feed. This is displayed as “Driveway CCTV” in the VLC Window title, which is a handy feature.

Line 3, ” rtsp://USERNAME:YOURPASSWORD@192.168.0.151:554/1″ is simply the RTSP URL for the camera feed you want to stream from.

The RTSP URL contains the protocol (rtsp://), then user and password details, then the address of the camera (192.168.0.151 in this case), which is followed by the port the feed is served on: 554. This port can be seen in the camera config during the initial setup, but if you are unsure you can run a simple nmap scan against your camera like this:

nmap

Here we can see port 80 and 8080 are open for the web interfaces (viewing and configuration respectively), and 554 which is the standard RTSP port.

This useful web page can also generate the correct RTSP URL for many popular cameras:
Tenvis IP camera URL

The final part of the URL is the endpoint to connect to on the remote camera/host – you can see in the config above that I am connecting to “/1” at the very end of the third line in my M3U file; this is the location for the full 720 HD feed for these particualr cameras. There are also lower resolution feeds available which can also be useful to know about, especially when monitoring multiple cameras or connecting remotely (e.g. with lower bandwidth).

For these Tenvis cameras, changing to the “/12” endpoint will fetch the lower quality feed, and there are other options inbetween that you can use to suit your requirements. These end points can also be modified further through the Tenvis settings app (which is running on port 8080).

Kodi (formerly XBMC) – from a quick google it looks like there are several ways in which Kodi can be set up to consume and view RTSP feeds. The simple option I’ve gone for is, again, to create a tiny config file containing the settings for each camera, and to place these files on my NAS storage. This means that watching a camera live on my TV is as simple as selecting the corresponding file in Kodi, and it will launch the stream just like you had clicked on a movie.

The files I use have the “.strm” extension and simply contain the full URL for the RTSP stream:

rtsp://user:password@192.168.0.156:554/1

Using this simple approach, I can click on files like “cctv_driveway.strm” in Kodi to launch the various streams. Because I only ever use this on my TV or Projector, I go for the full 720 HD feed in these files via the “/1” end points.

4. Jenkins

Disclaimer: I have a tendency to use Jenkins to automate everything. 
Sometimes this extends to things that don't really need it, just to see if/how it can be done. 
This section and idea is driven from that personal tendency/obsession.
The ZoneMinder solution (described below) is by far the more sensible option for most cases :-)

After setting up some cameras and connecting to them, I then wanted to record and archive the footage. The provided software enables you to set up FTP archiving and email alerts, but I wanted to do something more flexible, that would allow me to easily change & tune the retention, housekeeping and archiving. The approach I used is slightly unusual, but it’s very simple, effective and flexible, allowing me to easily tweak things to suit my requirements.

To use Jenkins for recording and managing my CCTV Camera feeds, I went through the following high-level steps:

1. Create a new ‘Freestyle’ Jenkins job, set to run on my Ubuntu host

2. Add an ‘Execute shell’ step. To this I added the following shell commands:

export MY_DATE=`date +"%Y%m%d%H%M%S"`
rm -f *.ts
/usr/bin/vlc -vvv rtsp://USER:PASSWORD@192.168.0.151:554/12 --sout=file/ts:/home/don/cctv/recording-${MY_DATE}.ts -I dummy --stop-time=1800 vlc://quit
mv /home/don/cctv/recording-${MY_DATE}.ts .

This is cleaning up any previous/old files then capturing 30 minutes of output from the camera via VLC, writing the data stream to a file. After 30 minites VLC quits, and I move the newly captured file to the current working directory with a timestamp in the filename.

3. Archive files
After the shell command above is complete, I have configured the Jenkins job to archive the captured file along with this job run. This makes it nice and easy to browse through previous (date & timestamped) jobs and simply click to view the corresponding video capture from that time.

4. Create a Jenkins job loop
At the end of every 30 minute run, I set the “Build other projects” option for this build to trigger another run of this same job, creating an infinite loop of 30 minute runs. There’s a tiny pause between the job ending and the next build starting, but it’s only a second or two at most, which I can live with.

Once I was happy that the data was being captured and archived ok, I was then able to configure and tune the retention through Jenkins – there are loads of Jenkins built-in options that enable you to do things like ‘keep the last x builds’, or ‘keep builds for n days’, or whatever you would like. You can also mark certain builds as ‘keep forever’ if you wanted to preserve anything interesting.

This process works well for me, and the CPU and memory usage created from having 3 of these jobs running constantly is, to my surprise, next to nothing; thanks to the impressive efficiency of VLC.

The disk usage is the main issue here; with this approach I’m constantly recording, and you can fill up a LOT of disk by writing several HD video streams to disk! One plan I was considering is to reencode video footage at a lesser bitrate (to reduce the file size) as they get older (using another Jenkins job), but I think that may be over-kill: for me, 2 weeks retention with the ability to archive/keep anything I want to quite easily is more than enough really.

5. ZoneMinder
Nearly every search I did when looking for software to manage my new CCTV cameras led me to the same place – https://zoneminder.com/

Like VLC, Kodi and Jenkins, ZoneMinder is a fantastic bit of software; it’s free, there’s loads of documentation, and it’s extremely configurable. For managing CCTV video recordings I’ve not yet seen anything that compares to it, even if you are willing to spend serious money.

Initially I tried installing everything in a ready-made VM Template – an OVA file – I think it was this one:
http://blog.waldrondigital.com/2012/09/23/zoneminder-virtual-machine-appliance-for-vmware-esxi-workstation-fusion/

This is a great solution and can be a real timesaver to get you up and running, especially if you don’t have a VM with Ubuntu and a LAMP stack to hand. It took something like 2 minutes to deploy this to my ESX server, and it was working a few minutes after that. The software was out of date with the VM I downloaded and deployed, but there are clear and easy instructions on that page explaining how to update to the latest versions.

I decided I didn’t want the overhead of running another VM just for this one function, and as I already have a few running I looked in to installing ZoneMinder from scratch on an existing Ubuntu VM, which is actually pretty easy as detailed here:

http://zoneminder.readthedocs.io/en/stable/installationguide/ubuntu.html

This went quite smoothly, I had to do a couple of MySQL tweaks but it took about 20 minutes from start to finish, and I ended up with ZoneMinder running on an existing Ubuntu host which will mean less update and maintenance grief for me (as oppposed to running a separate and dedicated VM just for ZoneMinder).

It took a little experimenting to get the Tenvis TH692 cameras working in ZoneMinder, but nothing complex – here’s what I used for the “General” settings with the Tenvis TH692 cameras:

ZoneMinderGeneral

and here are the “Source” settings for the RTSP Stream, using the same basic details we’ve used to set up VLC, Kodi etc previously:

ZoneMinderSource

Once that’s done, you can tweak the settings to your liking. You can have ZoneMinder record events as they happen and archive them, and/or use it to act as a nicer web interface to your cameras. You get the option to cycle through your different cameras automatically, or you can watch several feeds on one page – the options and possibilities are great.

One of the main points of using ZoneMinder for me is that it serves the camera feeds to the browser without the need for plugins like QuickTime, and it works well on all operating systems I’ve tried – and all devices.

Note that it’s advisable to set up a ZoneMinder Filter to archive your old footage – preferably before your disks get full!

This link explains how to do this in a variety of ways:

http://zoneminder.readthedocs.io/en/latest/faq.html

After some inital experimenting I have gone for both a “Purge after x days” filter and a “Purge when disk over 50% full” – both types of Filter are detailed in that FAQ.

Summary

I can now connect to all of my cameras from all of my devices – my Nexus tablet, mobile phone, Mac and Linux computers, television, projector – quickly and easily, and from anywhere. I can also monitor, record, replay and generate alerts whenever they are required, and tune each camera to suit my needs. I think these cameras are a total bargain, the HD picture quality is excellent, and the night time IR is good too. If you are happy to set up your own connectivity and monitoring solutions like ZoneMinder (or Jenkins) you can quite easily create a sophisicated system for very little cost, and it’s good fun too!

 

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