Camect "Worlds Smartest Camera Hub" Tested

By Rob Kilpatrick, Published Oct 18, 2019, 09:26am EDT (Research)

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Many More Object Types Than Most Analytics

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Delivery Trucks Accurately Detected And Classified

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Person Classified As Bird (One Instance)

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Trucks Classified As Cars

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Person-Missed-Completely

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Running-Subjects-Missed

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Partially Obscured Subjects Detected

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No False Alerts On Animals

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No False Alerts On Heavy Rain

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No-Indoor-Alerts-On-Shadows

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No Direct Option For ROI

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Many ******* ******* ****

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Wyze Cameras Supported

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No Mobile App  Hub Home Screen Added As Bookmark

Events ******* ***** ** **

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Alerts Require Telegram IM Or Email

Camera "*******" ******

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Occasional Camera “Stalled” Issues

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Versions ****

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Comments (53)

Rob, good work on this!

We'd like to do more tests on startups that are coming into the video surveillance market. Camect is obviously early but they have enough together that we think it has potential to become a player in the NVR market that wants a lower cost, high-performance, non-Hikua recorder. We will see how they evolve.

If you are a startup or know a startup that has an up and coming product that you want IPVM to test, email us info@ipvm.com or john@ipvm.com, thanks.

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I can't wait to see where Camect is a year from now! Once they overcome some of the issues listed I would be very interested. Not being locked into some of the proprietary systems is well worth it.

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Hi Ross ... Which of the issues listed would be the most important to you? We're listening to our users to decide what to focus on, but we're certainly also interested in what you or anyone else reading this article would want most.

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I think the biggies are when it missed the guy standing in front of the camera for 1 minute as well as not detecting that guy running in front of the camera.

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That's fair .... We were pretty surprised by those two as well and want to fix them. We've already asked Rob for some more info about those cases. It was especially hard to believe we missed the guy at the door.

The software automatically temporarily suppresses notifications for alerts that are occurring "too frequently" to be useful to an average person, and we're wondering if this is what happened to the guy standing in front of the door. (It would depend on what was happening before this guy showed up at the door.) Suppressed alerts are still reviewable in the UI and if you then rate one such alert as important, it will learn that it's not supposed to suppress notifications, e.g. for people, and it will send them to you no matter how frequently they're occurring.

For the running guy case we've requested the video clip if they still have it. From the image in the report it might have been due to the fuzziness of the image, but this also could have been due to the frequent alert suppression if it occurred after several other tests that detected people in that room.

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Thanks for the follow-up Arup. The number one thing for me would be the native app that links directly back to the interface. That is huge for functionality and to make it seamless. Second is the region of interest. That feature is a must. Without that some of the cameras I have would be pretty useless as they only have a small area that I need to get alerts for.

Those are the major issues from my point of view. I also think the automatic discovery of cameras would be nice, but not a big deal for me. To market it to the general public though that would be an important feature.

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Hi Ross, I think we already have at least 90% of what you want. See what you think:

1. Both the email alerts and telegram alerts link back to the UI to see the actual video.

2. We have region of interest that you can draw out, although it's hidden away as we consider it an advanced feature from the perspective of the ordinary home user.

3. We have automatic camera discovery for a large variety of cameras, including specific drivers for several brands, and fallback to Onvif and autoprobing of several common RTSP urls when Onvif is not present. Note that IPVM said that RTSP urls may be required for commercial cameras. We haven't tested many expensive cameras an average end-user won't buy themselves, and this is easily remedied. (Adding those drivers is usually much easier than drivers for consumer cameras.)

4. It's true we don't have a native app, but I want to make sure you understand what a Progressive Web App is. It uses the browser to present the UI, but after installation the app is fully standalone like any other app -- i.e., it launches from an icon on your home screen, opens with a splash screen, is a standalone app distinct from your browser in the app switcher, does not share credentials with your browser, and you don't see any browser controls anywhere. (i.e. It behaves a lot like a native app, but subject to some caveats as mentioned below.)

Here are more details complete with all gory caveats:

Email alerts: You get back to the UI by clicking the animated gif... Check out some example email alerts in our alerts demo. You can try clicking the link although you won't have permisson to open the UI. In Android, the link will open the Progressive Web App. In iOS, it opens Safari.

Telegram alerts: You get back to the UI by clicking the list of detected objects, e.g. in one alert in the report above, you see "Wyze person detection cam saw a person" and clicking on "a person" will take you to the video. Telegram currently enforces that the link opens in a browser, but we're going to file a bug asking if they'll allow the PWA to be used when there is one.

Our PWA also has native text-only alerts on Android, but not on iOS as iOS does not support them for PWAs yet. We recommend telegram alerts across the board because the video clip we can send in them makes them much nicer than what the size limits on native alerts would allow for, and 90% of the time eliminates the need to go look at the video.

Region of interest: As IPVM described, the software attempts to automatically learn the region of interest based on feedback you give on the alerts (i.e. click on "thumbs down" and tell it that the alert is unwanted because of the area of the image it came from). However, we do also allow you to draw out one or more regions of interest manually if you want, and even to do somewhat complex logic using overlapping regions with and/or behavior if it comes to that. This feature is hidden away in the UI so it's understandable that IPVM didn't find it. We don't expect most users to use it, but it's mentioned in the docs.

Automatic Camera Discovery: We have several automatic discovery mechanisms. Our specific drivers include Axis, Hikvision, Dahua, Reolink, Foscam, Nest, Arlo, Wyze, Doorbird, Trivision, Ubiquiti, consumer models of Samsung, and some models of Vstarcam, Dlink, and Trendnet. We have a fallback Onvif driver that works for many brands but currently cannot find the media service on some of them. We also auto-probe cameras with open RTSP ports for several common urls, .e.g although we're never recommend them, the large number of XiongMai-based cameras out there will work.

Since our drivers only support the basic stuff (get the video stream, move the PTZ, and sometimes set/get the camera name and set wifi credentials) it's very easy to add new drivers. We haven't tried several of the commercial cameras that IPVM used (as no one in our target market has them) but it's much easier to add drivers for these cameras than for the average consumer camera. The large brands are recognizable from MAC address alone, and usually have well documented RTSP urls, so we can quickly add the right RTSP urls for any big brands.

IPVM has not shared details of the camera problems they ran into with non Hikvision/Dahua, but I'd guess that they had problems with the Onvif driver above and with cameras that don't use the list of common consumer RTSP urls we probe. It's also possible that our discovery had some problems due to the number of cameras on IPVM's network, which was much larger than you'd find in a typical home or small business.

Native app vs Progressive Web App: As I mentioned above, the PWA is actually quite a lot like a native app although you install it differently. The biggest caveat is that iOS does not support notifications for PWAs -- but Telegram produces much nicer alerts anyway.

What you see in the app looks like the mobile web UI minus all the browser chrome. That's something that many people like, because everything works the same way as it does from your desktop/laptop. We're aware of several shortcomings in our UI -- but those are our fault, not the fault of it being a PWA versus a native app.

Are there specific things you worry about the PWA experience versus a native app (other than the installation experience, and the lack of notifications on iOS)? We are really curious to see what people actually think after they try the app. If there really are issues that aren't fixable in a PWA, we'll do a native app too -- but so far we haven't really heard complaints that are limitations due to the fact that we implmented as a PWA. It is certainly true that the installation experience could be better, as having to separately install the telegram app is definitely not ideal.

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Thank you for the detailed reply Arup! I was unaware of how the PWA functioned so that absolutely clears that up. Also, thank you for the clarification on the region of interest, I would go that route.

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Interesting to see the amount of analytics running on that NUC PC. Does it require a net connection to work or is it doing it offline?

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UI1, no internet connection is required for the analytics, they are processed locally on the machine.

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Camect is using an Intel Celeron Apollo lake processor (J3455) with 4 cores/4 threads @ 1.50 Ghz. and 4GB of RAM to power their onboard analytics

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I also read that there is no GPU. It seems amazing that they can do all those real time analytics on a slow processor with no GPU.

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There is no external GPU (e.g. Nvidia), but intel processors have an integrated GPU ("intel hd graphics XXX") and we make extensive use of it. In recent intel processor generations, even the low end CPUs have a pretty good GPU, hence our ability to use the J3455, which, as you noted, is not a fast CPU.

The choice of CPU was a matter of trying to get to handling what you find in an average consumer's home at a reasonable price point. On this particular device, we recommend using no more than 24M of total camera resolution under "typical home security usage", as the processor becomes a bottleneck somewhere around that point. Our configuration allows for up to 6 4M cameras, which is already one step above the average user with 4-5 1080p cameras.

The software can run on any x86 processor with an integrated GPU. A 7th generation Core i5 processor approximately doubles the processing capability, but also costs significantly more.

On the lower other end, we can handle about 5 1080p streams on a box based on an intel Z8350. That's about $99 plus the cost of a hard drive.

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Very informative! Does your software access the integrated GPU through OpenCL?

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No. We're linux-based, and we use VAAPI for video processing, and OpenVino for the AI.

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Rob, did it pass or fail on the crawl test?

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Solid evaluations. Thanks IPVM!

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Running subjects were also completely missed, regardless of how long they remained in the camera's field of view...

Does anyone else find it ironic that, as good as this AI is, it fails on a test which would never fail on the cheapest dvr from 5 yrs ago?

CPU vs GPU

CPU: Did you see that?

GPU: See what?

CPU: Something or someone is in motion; I’m quite sure, you know there was a time before AI, when I was perfectly capable of detecting motion on my own.

GPU: Yes, the dark ages, back when shadows and fall foliage were considered the biggest threats to humanity...

CPU: Ha! You don’t know what it was, do you, Mr. AI, with all your fancy logic and neural bs?

GPU: Look, I don’t have to put up with this crap, I don’t know what I was even thinking taking this gig. Everybody said, “Go where the action is!” and “Live on the Edge!”, but I get down here and I don’t even have my own dedicated chip! I swear, the next firmware upgrade, I’m outta here, going back to the Cloud!

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If you miss the "alert for all motion" behavior, it's available if enabled via the UI. In our experience, the inevitable result of alerting on all motion is that the recipient either turns off the alerts or simply ignores them - and beyond that point it's not terribly useful that everything that moves is detected.

Nevertheless, we're also pretty surprised we missed the guy at the door. Our goal is to keep the user from having to disable alerts, and our best guess right now is that our attempt to do that might have been what caused the guy at the door not to produce a notification.

See my response above to "Undisclosed Manufacturer #3" for more detail.

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...our best guess right now is that our attempt to do that might have been what caused the guy at the door not to produce a notification.

if that’s the case then in should be in the suppressed event log, correct? Same thing if the running man alert was suppressed. though, Rob didn’t mention it. how does one see suppressed events?

If you miss the "alert for all motion" behavior, it's available if enabled via the UI.

...and beyond that point it's not terribly useful that everything that moves is detected.

perhaps, as in my simulated dialog above, in the case where the legacy motion detection is triggered, but the A.I. doesn’t “see” anything (even to suppress), it could still log the event for further review, even if not alerting in real-time.

finally, are you by any chance using anything from XNOR.ai?

if not, perhaps you could comment on what your take is on their offerings...

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Re: Suppressed alerts ...

Correct -- it is possible to determine whether not the notification was suppressed. That's what we've asked Rob about.

All motion is constantly analyzed and what was found is recorded. After that, there's a decision about whether the alert is "interesting" or not (based on feedback the user has provided) and another decision, based on frequency of occurrence, as to whether the alert should be automatically suppressed even if interesting.

When you review alerts in the UI, the defaults show you all "interesting" alerts. In the version Rob tested, we had just enabled the display of "interesting but suppressed" alerts by default as well, but there was a bug in it so I'm not sure whether or not the alert, if suppressed, would have shown up at the time Rob captured the experience.

We also have controls that allow you to see more, including "uninteresting" alerts, or even all detected motion w/o detected objects. They can also allow you to see less, by filtering the alerts by what objects were detected. The controls appear if you click the alert bell you see in the overlay.

Re: Xnor.ai

No, we are not using anything from them, and our knowledge about them is mostly limited to our experience with Wyze cam. They are impressive in the low amount of resources they require, especially given that they can do something useful on the Wyze cam hardware. On our Wyze cams, our own person detection detects people more reliably (on the same video stream), but theirs is pretty good too. We have yet to see ours miss a person that they detected, but we fairly regularly find examples we caught and they did not. I imagine they may be able to do a better job on more powerful hardware.

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...I'm not sure whether or not the alert, if suppressed, would have shown up at the time Rob captured the experience.

but, regardless it should still be on the device today, assuming Rob hasn’t defaulted it, right?

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If the footage corresponding to that time period has not already been deleted, it is possible to check via the UI to see what kind of alert there was, if any.

If the box has been running continuously since then and the footage corresponding to that time has been deleted, it will no longer be possible to check via the UI. In that case, it might still be possible to pull some metadata to see if there was indeed an alert detected -- but if we really failed, it will be much harder or impossible to tell what went wrong.

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Tested the analytics on a RTSP feed ? curious to see how it fares

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You mean you have an RTSP feed on which you'd like to test? If it's accessible over the net, yes we can hook it up for you and send you the alerts.

We also have a demo of the alerts live on google groups here ... We found two cameras that people unknown to us are streaming live on youtube, and we use them as input. You can watch the camera on youtube and see what shows up on the google group.

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Arup, sorry, left out a critical word, have you tested on a thermal RTSP stream ?

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Sorry, we have never tried a thermal stream. I don't want to hazard any guesses about whether or not our model is appropriate for a thermal stream, but if you're aware of an accessible feed anywhere, we could hook it up and find out.

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@Arup-

I work for FLIR and have multiple thermal cameras looking out across a field that could be used for testing. Send me an email at shawn.jepson@flir.com and I can get you connection details.

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Works great with my FLIR...it’s the “el cheapo” that was a Dahua OEM (was $350-$400 at ADI a few years ago)

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pass or fail on the crawl?

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Thanks for bringing that to our attention! I updated the image with the proper green check mark.

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Am I right that the "hub" is just a gateway and some storage, but that all of the analytics and UI for that comes from their cloud service?

Anybody know whose analytics their using? (homegrown, AWS, Azure, Google?)

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no, it’s all local.

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What does that mean? All the anlaytics are local on the box? Or all the analytics are locally developed, but on the cloud?

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All analytics are running locally on the box. Your video never leaves the box unless you ask for it to, e.g. when remotely viewing, or because you ask for a copy of alerts to be backed up to storage like Dropbox or Google Drive.

We developed the analytics in-house, built on top of some widely available tools (e.g. Tensorflow, SSD, MobileNet) but with a lot of optimization to make them work well for home security usage on an affordable piece of hardware.

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Thank you :)

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Can you direct connect the App to your box, or does it have to portal through your cloud?

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The app uses WebRTC to make a direct connection from your viewing device to your box. The cloud is involved in doing some pre-authentication and setting up of this connection -- but once the connection is set up, everything is going directly from your app to the box. On rare occasions, a direct connection is not possible due to the way the local network is set up. If that happens, data is sent through a relay. All data transmission (direct or not) is encrypted in transit and the relay, if any, has no access to the decryption key.

If you are on the same network as the device (or use a VPN) you can also connect directly to the web UI on the IP address of the device and sign in with a local account. When you do this, features that require a cloud identity (e.g. sharing to Dropbox or Google Drive) are not available.

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I notice that the detection tests, eg crawl, were done under normal white light lighting conditions. How well does the analytics perform when the cameras are in IR mode?

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We (i.e. Camect) have not conducted formal IR-only testing. We would not expect the results to be significantly worse in IR-only conditions as long as the camera maintains at least 5 fps and the images are clear, i.e. black and white vs color should not cause a big difference, but low-quality video coming from the camera could definitely degrade detection.

Anecdotally, detection of people and vehicles has been reliable in actual residential use in situations where the person is adequately lit by the IR. In normal usage, vehicles are usually detectable from headlights although the type of vehicle could be wrong if headlights are all you can really make out. We have not tested vehicles driving without headlights at night. We also have plenty of examples of nocturnal animals being detected (including one example clip visible on our home page) but it's harder to know whether any are being missed.

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Very informative report. I was intrigued enough by this to purchase the Camect + lifetime subscription. I would love to beta test if you are looking for more people to join your program.

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This seems like a great product! Glad you did a review.

What is interesting to me is that it works with Wyze/Arlo/Nest "cloud" cameras. AFAIK, these cameras do not expose an RTSP stream that you can pull video from. It's a neat trick that Camect can intercept their cloud communications. I also wonder when these 800lb gorillas will be sending their armies of lawyers with "you can't do that" notices. Probably once they start losing their cloud subscription money.

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With Wyze, the video comes directly from the camera, but for Nest and Arlo, there is no option other than to get it from the cloud, i.e. the video is going to the cloud and back.

Nest and Arlo support is a way for Nest and Arlo users to try our device without having to get new cameras -- but if they're happy with the feature set and user experience, we recommend that they eventually switch to IP cameras to eliminate the dependency on the cloud, knowing that our device will give them the same experience and feature set on their new cameras.

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Hi Arup, we have been testing 2 similar systems in our home market (not US) since about Feb 2019. Both rely on cloud analytics and this has been challenging so we fully agree with your approach of processing at the edge. Both also interface via Telegram. We typically install 2MP IR cameras back-to-back along a boundary fence to form a perimeter. Our goal is to achieve a very high degree of human movement detection of anyone breaching the perimeter. The cameras are installed at about 3m height and at 35m intervals. We find that at max distance on a dark night, detection accuracy on both systems is very inconsistent. Our goal is to try find the sweet spot of cost vs accuracy. We would be glad to provide you with access to our cameras to see how Camect performs relative to our existing test systems.

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By "IR cameras" do you mean regular IP cameras with IR leds, or do you mean thermal cameras? We haven't done anything with thermal cameras so it's very possible our model will not work. In any case, send me a note (arup@camect.com) ... We can hook up a camera or two and see whether our product can do something useful for you.

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Is the onboard storage drive replaceable/upgradeable? I noticed on the Camect website FAQ, they said you can use an external drive or NAS for extra storage, but was just curious about the onboard storage.

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Yes, you can replace or upgrade it easily. (There's a little access panel on the bottom of the device. Removing two screws exposes the drive and allows you to disconnect and remove it.) After you replace it you'll have to format the new drive from the UI.

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So the OS/UI or what ever is independent of the onboard storage drive? That's nifty.

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Yes. The device has a small internal SSD that holds the OS.

The disk compartment is also completely detachable (by moving two sliding clips) from the rest of the unit so that in the event of a failure a privacy-conscious customer can hold onto their drive compartment and send the rest back to us.

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Arup for v2 can I please request a field upgradable hard drive? A 10tb unit is about 300. Having a sled where a user can upgrade would very much future proof this appliance.

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If it helps at all for the current iteration, you can add up to to USB 3.0 external hard drives to it. (It also supports writing to a NAS, although that probably doesn't help.)

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Was thinking about splurging on one today, looks like Corona Virus has caused some delays

Has anyone received one yet? Any more feedback or experience with these?

Camect Updates

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(In case none of our users are subscribers to this thread ... )

We have a few hundred active users now, and you can read some of our favorite unsolicited comments here, each with a link to the original public discussion from which it came.

If you have specific things you'd like to know about, I'm happy to answer, or you could ask in our user forum, referenced from the above page, and also linked off camect.com.

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