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Are you suggesting not using cloud for privacy concerns? Based on the feedback from people's comments here, I realize we should do more to alleviate the privacy
by mrafiee 7y ago
Are you suggesting not using cloud for privacy concerns? Based on the feedback from people's comments here, I realize we should do more to alleviate the privacy concerns. Curious on to know your thoughts about the following aspect: As I mentioned, we only store short video clips corresponding to events that the user created (we already discard the other motion clips that are deemed as irrelevant by our models.) We also allow users to delete the the alerts they have received and when they delete each alert, we permanently delete the corresponding video clips from our dbs... would that alleviate your privacy concerns?
We actually built our first prototype using RPi, we tried 3-4 different RPi cams, the image quality of all of them was very poor. Also the final cost would much higher than the cameras we are using right now...
Supporting IFTTT is in our near term road map.
Appreciate the suggestions!
- SirYandi 7y agoIt was my understanding that GP's main concern was the service shutting down should his internet fail, and not one of privacy.
- mrafiee 7y agoI see. That is actually a great point and we have heard that concern from others as well. The cameras we are offering now come with local storage. We have been thinking of adding some capabilities when camera is offline but since we do the inference on the cloud, the smart alert and video indexing features (our main value props) would not work offline.
- pletsch 7y agoNot OP, but if you want privacy conscious users to use your business, they will want to be able to host it themselves.
- mrafiee 7y agoYa I see your point. We have tried to take the privacy seriously from the beginning (and now realize we need to do more) but as far as not using the cloud at all, that would be a significant limitation on the type of inference that can be done locally and I think the benefits may outweigh the associated risks for many users/use cases...
- bradknowles 7y agoI have a number of cloud enabled cameras now, but I’m also building my own system to keep everything local-only. If you want to sell me an ML-based system, you’re welcome to train the models in the cloud, but they have to run on local-only assets. And you have to give me complete control over downloading new models periodically to a machine of my choice, and the updating my local devices.
- mrafiee 7y agoThanks for the feedback. What are you using the cameras for?
- mc32 7y agoThere will be many kinds of customers, but among them those who value privacy and those who want convenience. One of them will drive the bulk of sales, the other maybe not. On the other hand, if this is a value prop that excites people you’ll surely have the incumbents consider the economic threat and may add that feature as needed.
- mrafiee 7y agoYa I think finding the right balance between privacy related risks and cost/convenience/features is a an important aspect of this space.
- king_magic 7y agoEven storing short video clips in the cloud is not good enough.
- king_magic 7y agoEven storing short video clips in the cloud is simply not good enough.
- mrafiee 7y agoHow about giving the users full control over them and let them delete them individually and also all of the past alerts at once after they view them?
- mattlondon 7y agoIt was more that if my internet connection goes down, are the cameras useless? What if the internet/AWS is just "slow" one day - will the notifications be delayed significantly making any "reactive" integrations pointless/ludicrously delayed? If things can run locally (doing inference for multiple cameras via a single "box" you plug in to your WiFi router etc) then you can be super-fast with IFTTT integrations. My main line if thought was that I built basically your product for spotting when a cat climbed into my plant pots using ML and a RPi3 - the idea was that when it saw the cat, it would squirt a water pistol at it to scare it away - inference on the RPi 3 was too slow (if I was doing this now I'd use a coral accelerator maybe) and by the time it realised a cat had got into the plant pots, the cat had already taken a shit and left. I worry that your product might suffer from similar end to end latency. Niche use-case? Perhaps. I have Amazon Blink cameras here and the IFTTT integration is delayed by about 30 seconds so by the time you get a notification there is someone at your door it is to late to do anything as they will.have already left/kicked the door in by then etc. Doing all this locally would be super fast My main concern was not really about privacy - you'll need to cover GRPR if someone from the EU happens to walk into frame of one of your customers' cameras one day in the future anyway (Good luck)
- mrafiee 7y agoLove that use case :) re your point about latency, that is one of the main reasons we are doing all the inference on the cloud. Almost all deep learning models (at least CV models) need GPU to run with low latency. That's true that if you have set up an automated response from another device, it may still work if the internet is down but for alerting the user, you would still need internet connection even with a central hub...